STUDIES ON BIOLOGY, ECOLOGY AND MANAGEMENT OF Asphodelus tenuifolius Cav. IN CHICKPEA

BY

MUHAMMAD ISHFAQ KHAN

A dissertation submitted to NWFP Agricultural University Peshawar in partial fulfillment of the requirements for the Degree of

DOCTOR OF PHILOSOPHY IN AGRICULTURE

(WEED SCIENCE)

DEPARTMENT OF WEED SCIENCE FACULTY OF CROP PROTECTION SCIENCES

NWFP AGRICULTURAL UNIVERSITY PESHAWAR-PAKISTAN

FEBRUARY, 2009

STUDIES ON BIOLOGY, ECOLOGY AND MANAGEMENT OF Asphodelus tenuifolius CAV. IN CHICKPEA

A dissertation submitted to NWFP Agricultural University Peshawar in partial

fulfillment of the requirements for the Degree of

DOCTOR OF PHILOSOPHY IN AGRICULTURE (WEED SCIENCE)

BY

MUHAMMAD ISHFAQ KHAN

Approved by: __________________________ Chairman Supervisory Committee Prof. Dr. Gul Hassan __________________________ Member Prof. Dr. Khan Bahadar Marwat ___________________________ Member Prof. Dr. Khalid Nawab Agri. Ext. Edu. & Communication ____________________________ Chairman/Convener Board of Studies Prof. Dr. Khan Bahadar Marwat ____________________________ Dean Faculty of Crop Protection Sciences Prof. Dr. Muhammad Naeem _____________________________ Director Advanced Studies and Research Prof. Dr. Muhammad Jamal Khan

DEPARTMENT OF WEED SCIENCE

FACULTY OF CROP PROTECTION SCIENCES NWFP AGRICULTURAL UNIVERSITY, PESHAWAR (PAKISTAN)

FEBRUARY, 2009

Dedication

I dedicate these humble efforts to my late father

Muhammad Ishfaq Khan

CONTENTS

CHAPTER No. TITLE PAGE# i ii

ACKNOWLEDGEMENTS----------------------------------------------------------► ABSTRACT----------------------------------------------------------------------------► LIST OF FIGURES-------------------------------------------------------------------► iv 1. Impact, review and objectives of the studies------------------------------------------- ----► 1

2. Review of literature------------------------------------------------------------------------------► 6

3. Studies on Temperature Regimes and Dormancy Breaking Chemicals Influencing Seed Germination of Chickpea and A. tenuifolius (Cav.)---------------------------------►

Abstract-----------------------------------------------------------------------------------► 3.1. Introduction------------------------------------------------------------------------------► 3.2. Materials and Methods-----------------------------------------------------------------► 3.3. Results------------------------------------------------------------------------------------► 3.4. Discussion--------------------------------------------------------------------------------►

21

21 23 25 28 33

4. Effect of Different Herbicides and their Doses at Various Growth Stages of A. tenuifolius Grown in Pots.---------------------------------------------------------------------- ►

Abstract-----------------------------------------------------------------------------------► 4.1. Introduction------------------------------------------------------------------------------► 4.2. Materials and Methods-----------------------------------------------------------------► 4.3. Results------------------------------------------------------------------------------------► 4.4. Discussion--------------------------------------------------------------------------------►

35 35 37 40 42 48

5. Tolerance of Chickpea Cultivars to Major Chickpea Herbicides----------------------► Abstract-----------------------------------------------------------------------------------►

5.1. Introduction------------------------------------------------------------------------------► 5.2. Materials and Methods-----------------------------------------------------------------► 5.3. Results------------------------------------------------------------------------------------► 5.4. Discussion--------------------------------------------------------------------------------►

50 50 51 54 55 62

6. Effect of Pre and Post Emergence Herbicides on A. in Chickpea Under Field Conditions------------------------------------------------------------------------------------------►

Abstract-----------------------------------------------------------------------------------► 6.1. Introduction------------------------------------------------------------------------------► 6.2. Materials and Methods------------------------------------------------------------------► 6.3. Results------------------------------------------------------------------------------------► 6.4. Discussion--------------------------------------------------------------------------------►

63 63 64 67 69 81

7. Effect of Some Herbicides and Their Doses at Different Growth Stages A. tenuifolius Under Field Condition.------------------------------------------------------------►

Abstract-----------------------------------------------------------------------------------► 6.1. Introduction------------------------------------------------------------------------------► 6.2. Materials and Methods-----------------------------------------------------------------► 6.3. Results------------------------------------------------------------------------------------► 6.4. Discussion--------------------------------------------------------------------------------►

83 83 84 86 87

102 8. SUMMARY, CONCLUSIONS AND RECOMMENDATIONS------------------------► 103 LITERATURE CITED--------------------------------------------------------------► APPENDICES -----------------------------------------------------------►

107 122

i

ACKNOWLEDGEMENTS

All praises are for Almighty Allah, Who bestowed me with potential to contribute a drop of material

to the existing ocean of knowledge. All the praises be for the holy prophet Hazrat Muhammad

(S.A.W) who is forever a module of guidance and knowledge for humanity as a whole.

I would like to express my deepest sense of gratitude and profound respect to my advisor, Prof.

Dr. Gul Hassan, Department of Weed Science, NWFP Agricultural University Peshawar for his

enthusiastic guidance, valuable and constructive criticism, encouragement and sincere help in the

completion of this manuscript. Countless thanks are extended to the honorable Prof. Dr.

Khan Bahadar Marwat Chairman Department of Weed Science, NWFP Agricultural University

Peshawar for his overall cooperation and technical advice.

I want to extend my cordial gratitude to Prof. Dr. Khalid Nawab, chairman department of Extension,

Education and Communication, NWFP Agricultural University Peshawar for evaluating my PhD

dissertation as a technical member.

Thanks are also extended to the external experts, Jhon Cardina of Ohio State University USA and

Prof. Dr. Steve W. Adkin, University of Queens Land Australia for evaluation my disseratation and

valuable comments.

I must not forget all other teachers of the Weed Science Department, NWFP Agricultural University

Peshawar, Dr. Ijaz Ahmad Khan and Dr. Muhammad Azim Khan for their sincere help and

cooperation during my studies.

I express my profound feeling of admiration and gratitude to Dr. Imtiaz Khan, Dr. Muhammad Idrees,

Major Jehangir Khan, Zahid Hanif, Lt Hanif, Muhammad Afzal, Muhammad Akbar, Rehmatullah

and Munir Khan who always encouraged me in accomplishing my research work.

Last but not the least, I pay my cordial thanks to my respectable parents, brothers (Haji

Nazeef Khan, Rizwan Khan), cousins (Haji Nawab Khan, Mashal Khan, Muhammad Shoaib

Khan, Hayat Khan and Khanzada ) my nephews (Abdurazaq, Masood Khan and Abdul

Samad Khan) and loving sisters who prayed for my success and bright future and provided

me financial as well as moral support throughout my educational carrier. Muhammad Ishfaq Khan

ii

STUDIES ON BIOLOGY, ECOLOGY AND MANAGEMENT OF Asphodelus tenuifolius Cav. IN CHICKPEA

Muhammad Ishfaq Khan and Gul Hassan

Department of Weed Science, Faculty of Crop Protection Sciences NWFP Agricultural University Peshawar-Pakistan

ABSTRACT

A series of experiments were conducted for the management of Asphodelus tenuifolius in

chickpea. A. tenuifolius is a noxious weed in sandy areas of Pakistan. Average losses

due to this weed in chickpea range from 38 to 42%. Thus, in order to harvest potential

chickpea yield, the judicious management of this weed is essential. In the first

experiment, seeds of four biotypes of A. tenufolius were collected from Bannu, Karak,

Bhakkar and Mianwali districts of Pakistan for a series of laboratory experiments at the

Department of Weed Science, NWFP Agricultural University Peshawar-Pakistan. Seeds

were treated with four chemicals viz.gibberellic acid (GA3), potassium nitrate (KNO3),

thiourea (THU) and sodium azide (SA) at different rates and incubated at three

temperatures (10, 20 or 30oC). The Bannu and Mianwali biotypes were most germinable

at 20oC, while germination of the Bhakkar biotype was slightly higher at 10oC as

compared to other biotypes. In another experiment, four chickpea cultivars, along with A.

tenuifolius seeds, were tested under the same protocols. All chickpea cultivars showed

100% germination at all concentrations except 3.07 mM while A. tenuifolius produced

very little or no germination at all concentrations except 0 and 0.76 mM. The second

experiment was also undertaken in pots to investigate the effect of different herbicides

and doses on A. tenuifolius at different growth stages. Four biotypes (Bannu, Karak,

Bhakkar and Mianwali) of A. tenuifolius were subjected to two herbicides, viz.

isoproturon and fenoxaprop-p-ethyl, each at four doses including an untreated check. The

main effects of growth stages, biotypes and herbicide doses significantly affected the

fresh and dry weight of A. teuifolius. Two leaf stage was more susceptible to herbicides at

all doses as compared to other growth stages. Another pot experiment was undertaken for

testing the tolerance of chickpea cultivars to preemergence pendimethalin 330E and post

emergence fenoxaprop-p-ethyl 75 EW, each with four doses. The varieties tested for

iii

tolerance were KC-98, Sheenghar, Lawaghir, KK-1, KK-2, SL-01-13, SL-02-13, SL-02-

20, SL-02-22, SL-02-29, SL-03-29 and SL-04-29. The 1X dose produced intermediate

fresh and dry biomass. Untreated check and ½x dose produced maximum biomass while

either of the herbicides at 1.5X dose produced very low dry weight. All the tested

cultivars were tolerant to both the herbicides at ½x and 1X doses. Two experiments were

conducted in chickpea during 2005-06 and 2006-07 on farmer’s field at district Lakki

Marwat, North West Frontier Province, Pakistan. Five herbicides pendimethalin (pre-

emergence), s-metolachlor (pre-emergence), fenoxaprop-p-ethyl (post-emergence),

MCPA (post-emergence), and isoproturon (post-emergence) with four different doses (0,

½x, 1X and 1.5X) were studied in the trials. All herbicides except MCPA and isoproturon

showed no phytotoxic effects on chickpea crop. MCPA proved detrimental to both crop

and weed growth. While isoproturon was weaker on A. tenuifolius as well as had lesser

phytoxicity on crop. Best seed yield (1164 kg ha-1) was recorded in pre-emergence

herbicide pendimethalin at 1.5X dose as compared to post emergence herbicide

isoproturon (981.6 kg ha-1). Another field experiment was conducted on herbicides and

growth stages of A. tenuifolius. Two herbicides isoproturon and fenoxaprop-p-ethyl with

four rates (0, ½x, 1X and 1.5X) and two growth stages (2 leaf and 4 leaf) were

undertaken in the studies. Fenoxaprop-p-ethyl produced better results at the 1X rate by

producing 1114 kg ha-1 seed yield in 2005-06 and 1098 in 2006-07 as compared to

untreated check (988.6, 979.6 kg ha-1) in 2005-06 and 2006-07, respectively. Two leaf

stage of wild onion was more susceptible to fenoxaprop-p-ethyl as compared to 4 leaf

stage. Our findings proved that pre emergence herbicides like pendimethalin and s-

metolachlor at 1.5X dose are the best choice for reducing wild onion infestation in

chickpea under field conditions.

iv

LIST OF FIGURES

S. No. Titles Page

Fig-3.3.1. Comparison of seed germination of A. tenuifolius biotypes. 28 Fig-3.3.2. Comparison of seed germination of biotypes with temperature regimes. 29 Fig-3.3.3. Germination of Bannu biotype as affected by chemical and concentrations. 29 Fig-3.3.4. Regression of concentrations of different chemicals with Bhakkar biotype 30 Fig-3.3.5. Germination of Karak biotype as affected by chemical and concentrations. 31 Fig-3.3.6. Germination of Mianwali biotype as affected by chemical and concentrations. 31 Fig-3.3.7. Germination of chickpea cultivars treated with sodium azide at different concentrations. 32 Fig-3.3.8. A. tenuifolius biotypes seed germination as affected by sodium azide concentrations. 32 Fig-4.3.1.1. Fresh biomass of different biotypes of A.tenuifolius as affected by the interaction of different

herbicides and biotypes. 43

Fig-4.3.1.2. Fresh biomass of different biotypes of A.tenuifolius as affected by the interaction of herbicides Doses and growth stages.

44

Fig-4.3.1. 3. Dry biomass of different biotypes of A.tenuifolius as affected by the interaction of different herbicides and their doses.

44

Fig-4.3.1. 4 Dry biomass of different biotypes of A.tenuifolius as affected by the interaction of different herbicides, biotypes and growth stages.

44

Fig-4.3.2.1. Fresh biomass of biotypes of A.tenuifolius as affected by the interaction of herbicides and biotypes.

46

Fig-4.3.2.2. Fresh biomass of biotypes of A.tenuifolius as affected by growth stages. 46 Fig-4.3.2.3. Dry biomass of different biotypes of A.tenuifolius as affected by the interaction of herbicides

doses and growth stages. 47

Fig-4.3.2.4. Dry biomass of different biotypes of A.tenuifolius as affected by the Interaction of different herbicides, biotypes and growth stages.

47

Fig-5.3.1a. Fresh biomass as affected by chickpea cultivars and herbicides. 57 Fig-5.3.1b Fresh biomass of chickpea as affected by herbicides and doses. 57 Fig-5.3.2a. Dry biomass as affected by chickpea cultivars and herbicides. 57 Fig-5.3.2b. Dry biomass of chickpea as affected by herbicides and doses. 58 Fig-5.3.2c Dry biomass of chickpea cultivars as affected by cultivar x herbicides x doses. 61 Fig-6.3.1.1. Fresh biomass of A..tenuifolius as affected by herbicides and herbicides doses. 69 Fig-6.3.1.2. Dry biomass of A.tenuifolius as affected by herbicides and herbicides doses. 70 Fig-6.3.1.3. No. of branches plant-1 of chickpea as affected by herbicides and herbicides doses. 71 Fig-6.3.1.4. No. of pods plant-1 of chickpea as affected by herbicides and herbicides doses. 72 Fig-6.3.1.5. No. of seed pod-1 of chickpea as affected by herbicides and herbicides doses. 72 Fig-6.3.1.6. 100 seed weight of chickpea as affected by herbicides and herbicides doses. 73 Fig-6.3.1.7. Seed yield kg ha-1 of chickpea as affected by herbicides and herbicides doses. 74 Fig-6.3.2.1. Fresh biomass of A. tenuifolius as affected by herbicides and herbicides doses. 75 Fig-6.3.2.2. Dry weed biomass of A.tenuifolius as affected by herbicides and herbicides doses. 76 Fig-6.3.2.3. No. of branches plant-1 of chickpea as affected by herbicides and herbicides doses. 77 Fig-6.3.2.4. No. of pods plant-1 of chickpea as affected by herbicides and herbicides doses. 78 Fig-6.3.2.5. No. of seeds pod-1 of chickpea as affected by herbicides and herbicides doses. 78 Fig-6.3.2.6. 100 seed weight of chickpea as affected by herbicides and herbicides doses. 79 Fig-6.3.2.7. Seed yield kg ha-1 of chickpea as affected by herbicides and herbicides doses. 80 Fig-7.3.1.1a Fresh biomass of A. tenuifolius as affected by the interaction of herbicides x growth stages. 87 Fig-7.3.1.1b. Fresh biomass of A. tenuifolius as affected by the interaction of herbicides doses x growth

stages. 91

Fig-7.3.1.1c. Fresh biomass of A. tenuifolius as affected by the interaction of herbicides x doses. 88

v

S. No. Titles Page Fig-7.3.1.2a. Dry biomass of A. tenuifolius as affected by the interaction of herbicides x growth stages. 89 Fig-7.3.1.2b Dry biomass of A. tenuifolius as affected by the interaction of herbicides x doses. 90 Fig- 7.3.1.3. No. of branches plant-1 of chickpea as affected by the interaction of herbicides and herbicides

doses. 90

Fig-7.3.1.4. No. of pods plant-1 as of chickpea as affected by the interaction of herbicides x doses x growth stages.

91

Fig-7.3.1.5. No. of seed pod-1 of chickpea as affected by the interaction of herbicides x doses. 92 Fig-7.3.1.6. 100 seed weight of chickpea as affected by the interaction of herbicides x herbicides doses. 92 Fig-7.3.1.7. Seed yield (kg ha-1) of chickpea as affected by the interaction of herbicides x doses 93 Fig-7.3.2.1a. Fresh biomass of A. tenuifolius as affected by the interaction of herbicides x dose. 94 Fig-7.3.2.1b. Fresh biomass of A. tenuifolius as affected by the interaction of herbicides x growth stages. 95 Fig-7.3.2.1c Fresh biomass of A. tenuifolius as affected by the interaction of herbicides doses x growth

stages. 95

Fig-7.3.2.2a Dry biomass of A. tenuifolius as affected by the interaction of herbicides x growth stages. 96 Fig-7.3.2.2b Dry biomass of A. tenuifolius as affected by the interaction of growth stages and herbicides

doses. 97

Fig-7.3.2.3. No. of branches plant-1 of chickpea as affected by the interaction of herbicides and herbicides doses.

97

Fig-7.3.2.4. No. of pods plant-1 as of chickpea as affected by the interaction of herbicides x doses x growth stages.

98

Fig-7.3.2.5a. No. of seed pod-1 as of chickpea as affected by the interaction of herbicides x doses x growth stages.

99

Fig-7.3.2.5b No. of seed pod-1 of chickpea as affected by the interaction of herbicides x growth stages 99 Fig-7.3.2.6. 100 seed weight of chickpea as affected by the interaction of herbicides x doses. 100 Fig-7.3.2.7a. Seed yield (kg ha-1) of chickpea as affected by the interaction of herbicides x doses. 101 Fig-7.3.2.8b. Seed yield (kg ha-1) of chickpea as affected by the interaction of herbicides x growth stages. 101

1

CHAPTER-1.

IMPACT, REVIEW AND OBJECTIVES OF THE STUDIES

Chickpea (Cicer arietinum L.) belongs to family Fabacceae and sub family

Faboideae. The common names of chickpea world wide are, Bengal gram (Indian),

Chickpea (English), Chana (Urdu) in Pakistan, Garbanzo (Latin America), Hommes,

Hamaz (Arab world), Nohud, Lablabi (Turkey) and Shimbra (Ethiopia). It is a rich source

of unsaturated fatty acids (US Department of Agriculture 2007; Willium and Singh,

1986), resistant and starch (Willium Singh, 1986; Nestal et al., 2004; Guillon and Champ,

2002), dietary fiber (US Department of Agriculture, 2007), vitamins (Australian Grains

Research Development Corporation 2002), minerals (Petterson et al., 1997) and

phytoestrogens (Sharma, 1981; Siddique and Siddiqi, 1976). In Pakistan and India

chickpea is consumed locally, and about 56% of the crop is retained by growers (Duke,

1981). In Pakistan chickpea is planted in September and harvested in late April or early

May. Seeding rates vary from 25-40 kg ha-1 to 80-120 kg ha-1 depending on the area and

seed type (Smithson et al., 1985). Two types of chickpea are recognized, desi (colored,

small seeded, angular and fibrous) and kabuli (beige, large seeded, rams-head shaped

with lower fiber content) types (Malhotra et al., 1987).

The Chickpea yields in Pakistan are lower than the maximum potential yield

(1500-1800 kg ha-1) of the cultivars. One of the main reasons for this yield loss is weed

competition in addition to other production constraints. In Pakistan chickpea is

traditionally grown on residual soil moisture, hence, weed infestation poses major

problem due to competition for moisture. Common weed species of chickpea include

Asphodelus tenuifolius Cav., Chenopodium album L., Carthamus oxyacantha Beib.,

Cyperus rotundus L., Fumaria indica (Hausskn.) Pugsley, Polygonum aviculare L.,

Lathyrus aphaca L., Vicia sativa L., Cynodon dactylon L. and Cirsium arvense (L.) Scop.

(Mullen et al., 2000; Saxena and Yadav, 1976).

2

Among the abiotic factors, drought is an important factor in chickpea growing regions

because the crop is grown on residual moisture and eventually exposed to terminal

drought (Johansen et al., 1994). In West Asia and North African countries, low

temperature causing freezing injury or death or delayed onset of podding reduces yield

tremendously (Singh, 1987). Heat and salinity problems are relatively important

following drought and cold stresses (Singh et al., 1994). Chickpea yields usually

averaged from 400-600 kg ha-1, but can surpass 2000 kg ha-1, and in the experiments

yield have been attained to as high as 5200 kg ha-1. Yields from irrigated crops are

20-28% higher than yields from rainfed crops.

In Pakistan, during 2006-07, chickpea was grown on an area of 1052.3 thousand

ha with a production of 837.8 thousand tons with an average yield of 796 kg ha-1. During

the same year, the area, production and yield kg ha-1in NWFP was 49.0 thousand ha, 21.0

thousand tons and 429, respectively. Punjab with an area of 910.7 thousand ha and

production of 728.3 thousand tons and yield at 800 kg ha-1 is the leader in chickpea

production in Pakistan (MINFAL, 2007).

Traditionally weeds are being controlled through hand weeding or by various

cultural practices. However, with the scarcity of manual labour and intensive crop

production, introduction of chemical weed control has been used to replace the

conventional control measures. Chemical weed control certainly has its merits.over the

existing methods of weed control. Still it is not as common as it could be practiced on

commercial scale. Potential yield losses in chickpea due to weeds range between 22-

100% (Saxena and Yadav, 1976). Whereas Singh (1998) and Sakhalin et al. (1999)

pointed out that weeds reduced productivity in chickpea by 36.8% and 41-44%,

respectively.

Post emergence application of predate herbicide gave 97.5% weed control in

chickpea (Skrobakova, 1999). Bhalla et al., (1998) reported that herbicide treatment gave

50-64% weed control with increase in yield. Weed growth was significantly reduced by

3

the use of herbicides and resulted in increased yield of 50% against the control (Stork,

1998)

Wild onion (A. tenuifolius Cav.) is a notorious weed of sandy soils of Indo-Pak

sub-continent (Mishra et al., 2006). It belongs to the Ashodelaceae sub family of the

Liliaceae and is a serious weed of 15 crops in 17 countries (Holm et al., 1997). It is

annual in habit. It has been observed as a serious weed of chickpea (Cicer arietinum L.),

wheat (Triticum aestivum L.), mustard (Brassica juncea L. Czern. et Coss.), lentil (Lens

culinaris Medic.), and linseed (Linum usitatissimum L.) (Gupta et al., 1977; Poonia et al.,

2001; Tiwari et al., 2001). The same weed was found most dangerous to the chickpea

growers in the sandy districts of North West Frontier Province (NWFP) viz. Karak, Lakki

Marwat and parts of Dera Ismail Khan Pakistan. In the Punjab Pakistan, it is the worst

competitor with rabi crops in Mianwali, Bhakkar, Jhang and Layyah and causes huge

losses to the chickpea crop in the sandy zone of Pakistan (Hassan, et al., 2004; Sultan and

Nasir, 2003).

Farmers must continuously deal with weed infestations in crops and their

importance is reflected in the amount of manual labor, tillage, and herbicides used to

control them (Eue, 1986). The advent of herbicides has been hailed as one of the most

important advances in agriculture (Pike,1991). Herbicides now comprise 20–30% of

input costs in North American Cropping Systems (Derksen et al., 2002). Despite

widespread farmer adoption of herbicides, there is ever-increasing interest in reducing

herbicide doses and overall herbicide use.

A. tenuifolius is not relished by cattle, hence it cannot be fed to them by the family

labour, so manual weeding is very uncommon because farmers are very poor and they

cannot afford the cost of labour. In some infested fields, the damage is about 100% and

farmers leave their fields unharvested. One wild onion plant produces thousands of seeds

which grow next year at the suitable time and the damage is continued to the crop

throughout the growing season.

4

Based on the literature reviewed above, I conclude that A. tenuifolius is an

important weed that is not presently controlled effectively in chickpea. If we could reduce

the damage that A. tenuifolius causes in this crop, chickpea production could be more

productive and the economic return from this crop would increase for farmers. Therefore,

I conducted studies to better understand the biology of A. tenuifolius, and do identify

appropriate chemical control methods. What follows is a description of these studies,

their results, and a summary of the conclusions and recommendations for farmers.

Keeping in view the importance of wild onion in chickpea crop, a project was

undertaken at the Department of Weed Science NWFP Agricultural University Peshawar

envisaging the following work.

5

Experiment 1: Studies on Temperature Regimes and Dormancy Breaking

Chemicals Influencing Seed Germination of Chickpea and

A. tenuifolius (Cav.)

Experiment 2: Effect of Different Herbicides and their Doses at Various Growth

Stages of A. tenuifolirius Grown in Pots.

Experiment 3: Tolerance of Chickpea Cultivars to Major Chickpea Herbicides

Experiment 4: Effect of Pre and Post Emergence Herbicides on A. tenuifolius in

Chickpea under Field Condition.

Experiment 5: Effect of Some Herbicides and their Doses at different Growth

Stages of A. tenuifolius Under Field Conditions.

Overall objectives of the studies:

1. To acquire knowledge of the biology of A. tenuifolius.

2. To formulate different control measures for A. tenuifolius in chickpea.

3. To quantify the tolerance of chickpea germplasm to herbicides.

4. To work on reduced herbicides doses for sustainable weed management.

5. To test the dormancy behaviour of biotypes of A. tenuifolius with various dormancy breaking chemicals.

6

CHAPTER-2

REVIEW OF LITERATURE

2.1 BIOLOGY

Ruiz et al. (1990) analyzed 6 populations of A. tenuifolius and 12 populations of

A. fistulosus and confirmed that they are separate species. Floral structures (length of

tepals, stamens, anthers and style) and pollen size were clearly different. A. tenuifolius

possessed 2n = 28 chromosomes, while A. fistulosus had 2n = 28 and 2n = 56.

Electrophoretic analysis of esterases, alcohol dehydrogenases and glutamate oxaloacetate

transaminase [aspartate aminotransferase] revealed that A. tenuifolius was genetically less

variable than A. fistulosus. Gene duplication phenomena existed at the 2n = 28 level of

both species.

Gandar and Rasmussen (1991) reported that the pattern of growth (velocity field)

in the intercalary growth zones of monocotyledon leaves can be determined from patterns

of cell number density (number per unit length of cell file) and leaf elongation rates using

theory based on a cell number conservation equation. The case where elongation rate is

non-steady while the pattern of cell number density is steady was discussed and a method

for extending calculations into the meristem using observations of numbers of mitotic

cells was outlined. Application of these methods is illustrated using data for epidermal

cells in the first leaf of A. tenuifolius. During early leaf development, leaf elongation rate

increased exponentially but cell number density and mitotic number density were steady.

Cells 0.1 mm from the base of the leaf when leaves were 3.2 mm long took 8.3 d to move

through the growth zone. In leaves that were 4 d older, similar cells took 5.1 d to traverse

the growth zone. Increases in the rates of leaf elongation and of cell movement appeared

to be associated mainly with increases in total rates of cell production in the epidermal

meristem.

Obese (1993) examined the fruiting patterns of the rhizomatous perennial A. albus

studied in five populations during 1989 and in one population over 3 years. Fruit/flower

(Fr/Fl) ratio and seed/ovule (S/O) ratio varied markedly between populations. Although

7

there were differences between years within the population studied over 3 years, these

variations, although statistically significant, were less important than those between

populations. Neither flowering phenology nor plant size influenced Fr/Fl or S/O ratios.

Field experiments tested whether fruit and seed set were pollen- or resource-limited.

Hand-pollination had no effect on Fr/Fl or S/O ratios, but the reduction of resources by

defoliation at the time of flowering decreased both relative components of fecundity.

Manipulation of resources by hand-thinning flowers and tiny fruits had no demonstrable

effect on these ratios, although brood size of individual fruits was significantly affected.

It may be concluded that fruit maturation is resource-limited rather than pollen-limited.

Most of the fruits aborted early in the fruiting season, and fruits with higher numbers of

developing seeds had a lower probability of abortion than fruits with fewer seeds.

Diaz (1996a) reported that in A. aestivus the large number of showy flowers

opened per inflorescence, high nectar and pollen production, and absence of automatic

self-pollination indicate that cross-fertilization is favoured. Large Hymenoptera are the

main pollinators. Hand self-pollinations result in some degree of fruit-set, but cross-

pollinations also yield low fruit- and seed-set. The perennial habit and polyploid status

are in agreement with the breeding system of this species, with sexual reproduction being

rather inefficient and vegetative propagation being very effective.

Diaz (1996b) reported the pollen morphology of the 16 recognized species of the

genus Asphodelus (Asphodelaceae) investigated by light and scanning electron

microscopy. Four pollen types can be distinguished on the basis of variation in size of the

polar, equatorial, longitudinal and transverse axes, as well as in exine structure and

sculpturing, which correlate with the subdivision of the genus into sections. Correlations

between pollen size and some biological characters were made. Phylogenetic

implications were suggested, and trends of pollen evolution in the genus were indicated.

8

Sahai and Bhan (1991a) reported that A. tenuifolius seeds germinated between 10

and 35°C in laboratory experiments, showed maximum germination at 15° (50.7%) and

most rapid germination at 20°. Seeds stored in the laboratory or soil for up to 6 months

showed dormancy for 4 months and seed germination after 5 months. The influence of

sowing depth was investigated by sowing seeds at 1 cm intervals up to 7-cm depth. Max.

Seedling emergence (19.7%) occurred when seeds were sown at 3 cm, closely followed

by 2 cm (18.1%). Sowing seeds at 2-cm depth resulted in the greatest number of leaves,

inflorescences and capsules, and the greatest capsule weight and seed yield plant-1.

Sahai and Bhan (1991b) reported the effect of environmental conditions on the

growth and reproduction of A. tenuifolius investigated in screen-house trials. Max.

Seedling emergence and greater number of leaves, DW of capsules and seed yields/plant

were recorded with the earliest sowing (31 Oct.). These characters decreased as the

sowing date was progressively delayed until 30 Nov.

Patterson (1996) evaluated the environmental factors that affect the growth and

development of onion weed (A. fistulosus) in order to predict its potential range and

impact. In controlled-environment experiments, onion weed achieved 60-100% of its

maximum vegetative growth at temperatures ranging from 18/11 to 30/23°C day/night.

The greatest biomass was produced at day temperatures of 18 or 24°C and night

temperatures of 11 or 17°C. Leaf production and reproductive development were greatest

at 18/11°C. Plants eventually flowered at 18/17, 24/17 and 24/11°C, but not in any

regime with a 30°C day or a 23°C night. Flowering occurred earlier in 16-h photoperiods

than in 8-h photoperiods. Climatic analyses revealed no USA analogues of the principal

Australian onion weed sites. Based on its environmental responses and its pattern of

distribution as a weed in Australia, onion weed is likely to remain confined to the

southwestern USA.

Yirdaw and Leinonen (2002) showed the germination response of Cordia

africana, Juniperus procera, Acacia abyssinica, and Faidherbia albida seeds to

continuous exposure of various red to far-red ratios (R/FR) and constant-temperatures of

9

15, 20, 25 and 3000 C. Germination of C. africana seeds was strongly inhibited at low

R/FR and it appears that this species has evolved a light quality sensing mechanism that

prevents seed germination beneath leaf canopies. The germination probability of C.

africana increased as temperature increased from 15 to 300 C. R/FR, temperature, and

their interaction significantly affected germination of J. procera. Seeds of this species

displayed a complex dormancy mechanism and germinated only in a narrow range of

temperatures and R/FR. The effect of R/FR on germination of J. procera was most

pronounced and the highest germination probability was recorded at 20 degree C. The

germination probability of F. albida seeds increased with rising temperature (from 15 to

30 degree C), but there was no significant effect of light. At high temperatures, mean

germination time in this species decreased with increasing R/FR, but increased with

rising R/FR at low temperatures. Neither R/FR, temperature, nor their interaction had a

significant effect on the germination of A. abyssinica seeds.

Mitsunori and Tomokazu (2002) reported that abscisic acid (ABA) is a plant

hormone that plays important roles during many phases of the plant life cycle, including

seed development and dormancy, and in plant responses to various environmental

stresses. Because many of these physiological processes are correlated with endogenous

ABA levels, the regulation of ABA biosynthesis is a key element facilitating the

elucidation of these physiological characteristics. Recent studies on the identification of

genes encoding enzymes involved in ABA biosynthesis have revealed details of the main

ABA biosynthetic pathway. At the same time, the presence of gene families and their

respective organ-specific expression are indicative of the complex mechanisms governing

the regulation of ABA biosynthesis in response to plant organ and/or environmental

conditions. There have been recent advances in the study of ABA biosynthesis and new

insights into the regulation of ABA biosynthesis in relation to physiological phenomena.

Hoth et al. (2002) stated that the phytohormone abscisic acid (ABA) plays

important regulatory roles in many plant developmental processes including seed

dormancy, germination, growth, and stomatal movements. These physiological responses

to ABA are in large part brought about by changes in gene expression. To study genome-

10

wide ABA-responsive gene expression they applied massively parallel signature

sequencing (MPSS) to samples from Arabidopsis thaliana wild type (WT). They

identified 1354 genes that are either up- or down regulated following ABA treatment of

WT seedlings. Among these ABA-responsive genes, many encode signal transduction

components. In addition, they identified novel ABA-responsive gene families including

those encoding ribosomal proteins and proteins involved in regulated proteolysis. In the

ABA-insensitive mutant abi1-1), ABA regulation of about 84.5% and 6.9% of the

identified genes was impaired or strongly diminished, respectively; however, 8.6% of the

genes remained appropriately regulated. Compared to other methods of gene expression

analysis, the high sensitivity and specificity of MPSS allowed them to identify a large

number of ABA-responsive genes in Arabidopsis thaliana.

Baskin et al. (2002) undertook studies on seeds of the summer annual mudflat

species Ammannia coccinea and Rotala ramosior to determine the (1) effects of flooding

during late autumn to late spring on dormancy break and (2) optimum temperature for

dormancy break. At maturity in autumn, about 65-100% of the seeds of these species

were dormant. Seeds of both species buried under flooded and under non flooded

conditions in a non heated greenhouse germinated to 70-98% at 30(day)/15(night) degree

C and at 35/20 degree C the following June or July; seeds required light for germination.

As dormancy break occurred, seeds of R. ramosior showed a decrease in the minimum

temperature for germination, but those of A. coccinea did not. In another experiment,

seeds buried under non flooded conditions in the non heated greenhouse were flooded

and all flooded seeds and non flooded controls were exhumed and tested. With few

exceptions, seeds of both species flooded for short or long periods germinated to

significantly higher percentages over a range of temperatures when exhumed in July than

did seeds that had not been flooded. In a third experiment, seeds of both species were

incubated on moist sand in darkness at 5, 15 /6, 20/10, and 30/15o C for 0, 3, 6, 9, and 12

wk and then tested in light at 15/6, 20/10, 25/15, 30/15, and 35/20o C. The optimal

temperature regime for dormancy break in seeds of R. ramosior and A. coccinea was

20/10 and 30/15o C, respectively. In the nonheated greenhouse, some dormancy break

11

began in buried seeds of both species during late autumn and winter, and it continued as

temperatures increased in spring and/or early summer. The ability of seeds of both

species to come out of dormancy during flooding at field temperatures from late autumn

to early summer means that seeds are non dormant when mudflats become dewatered in

summer.

Barrera and Nobel (2003) reported that responses of seed germination to

temperature, water potential, time after harvest, and light in Stenocereus queretaroensis,

a columnar cactus native to west central Mexico. Germination was optimal between 20o

C and 30o C, and the germination percentage decreased as the water potential was

lowered from 0.00 to 1.0 MPa. Maximum germination of 85% occurred for seeds that

were 11-28 months old. Germination required light but became light saturated at a

photosynthetic photon flux over 10 days of only 0.15 mu mol m-2 equivalent to a fluence

of 67 mmol m-2. Germination was apparently phytochrome mediated, as evidenced by its

relative spectral sensitivity (greatest at 660 nm). The environmental requirements for

breaking seed dormancy for S. queretaroensis are finely tuned to those typical of the

rainy season in its native habitat.

Wang et al. (2006) conducted a study to determine the effect of high temperature

stress during the reproductive development on pod fertility, seed set, and seed yield of

Chickpea (Cicer arietinum L.). ‘Myles’ desi and ‘Xena’ kabuli chickpea were grown in a

controlled environment under 20-16 0C day/night air temperatures (controlled). High

(35-160C) and moderate (28-16 0C) temperature stresses were imposed for 10d during

early flowering and pod development. Compared to the control, the early flower high

temperature stress decreased pod production by 34 % for Myles and 22 % for Xena,

where as high temperature stress during pod development decrease seeds per plant by 33

% for Myles and 39 % for Xena. Consequently the high temperature stress during pod

development decrease seed yield by 59 % for Myles and 53 % for Xena. Yield reduction

was greater due to the stress during pod development compared to the stress during early

12

flowering. The Myles desi producing 40 seeds plant-1 and Xena kabuli produced 15 seeds

plant-1, where as the Myles has smaller individual seed size than the Xena. Consequently,

the Myles desi produced 26 % greater seed yield than the Xena kabuli under the same

condition. Minimizing the exposure of Chickpea to high temperature stress during pot

development will increase pod fertility, seed set, and seed yield of the crop.

Khan et al. (2006) conducted laboratory studies on wild onion (A. tenuifolius) to

investigate the dormancy breaking by using GA3, KNO3, Thiourea and Sodium Azide at 0

to 800 ppm exposed to 10, 20 and 30oC temperature regimes. The data revealed

temperatures, biotypes, chemicals, concentrations and their interactions significantly

affected germination except the interactions temperature x biotypes x concentration and

biotypes x chemical x concentrations. The highest germination was recorded at 20oC

(47.41%), while 1.09% germination was recorded at 30oC. Mianwali biotypes germinated

the most (40.83%) as compared to 24.38 and 22.88% germination in Karak and Bhakkar

biotypes. Miawali when exposed to 20oC had the highest germination (69.13%). Among

the chemicals the highest germination was recorded in KNO3 and thiourea. Mianwali

biotype when exposed to KNO3 or GA3 or thiourea out performed all other biotype x

chemical interactions. The temperature effect over-rides the chemicals or biotype effects.

13

2.3 HERBICIDES

Iqbal et al. (1991) conducted a field trial evaluated the effect of pre-emergence

application of pendimethalin, dimethyl tetrachloroterephthalate, trifluralin and

methabenzthiazuron on Cicer arietinum and weeds. None of the herbicides adversely

affected the nodulation of C. arietinum. Pendimethalin, trifluralin and

methabenzthiazuron applied at rates of 1.32 liter, 0.64 liter and 1.4 kg air ha-1,

respectively, were suitable for C. arietinum on sandy loam soil. However,

methabenzthiazuron gave a higher yield.

Poonia and Gupta (1993) studied the application of phosphate (0 or 40 kg ha-1),

the application of simazine (at 0.25-0.5 kg ha-1) and fluchloralin (at 0.5-0.75 kg), and

hand weeding twice for weed control in chickpeas. The dominant weeds were

Chenopodium album, C. murale and A. tenuifolius. All weed control treatments decreased

weed dry weight from untreated control values of 1066 kg ha-1 to 2556 kg ha-1. All

treatments, except simazine at 0.5 kg, increased grain yields from 648 kg ha-1 to 845 kg

ha-1. Fluchloralin at 0.75 kg resulted in the greatest net returns (Rs.2828 kg ha-1).

Plew et al. (1994) reported results of 7 pre-emergence and 10 post-emergence

herbicide treatments and 3 untreated controls: unweeded, hand weeded, and hoed in

chickpea. The most effective level of weed control and the greatest dry matter production

of chickpeas was obtained from a pre-emergence treatment with cyanazine at 1.0 kg a.i

ha-1, terbuthylazine at 1.0 kg a.i ha-1, a combination of cyanazine at 1.0 kg a.i ha-1+

metribuzin at 0.25 kg a.i ha-1, and hand weeding. Chickpeas were seriously damaged by

the post-emergence application of cyanazine, bentazone and their combination.

De et al. (1995) conducted field trials at Sriniketan in 1989-91 to assess the

efficacy of weed control in sandy loam of 1.0 kg ha-1 fluchloralin, 0.5 kg alachlor and 1.0

kg pendimethalin, all ± hand weeding 25 days after planting (DAP), and hand weeding 25

± 45 DAP in summer black gram (Vigna mungo) with 0.5-1.0 kg pendimethalin, 1.0-0.5

kg alachlor and 0.5 kg fluchloralin, all ± hand weeding 21 DAP at the lower rate, and

hand weeding 21 ± 42 DAP in winter chickpeas. Results indicated that all treatments

14

were effective against grassy weeds, and herbicide + hand weeding (integrated)

treatments gave greatest reductions in weed populations and biomass at 30 DAPS in both

crops.

Yasin et al. (1995) reported that pre-em. pronamide, post-em. Sethoxydim and

post-em. fluazifop-butyl, all applied at 0.5 kg a.i ha-1), efficiently controlled grass weeds

and improved yields in chickpea and Lentil. Inclusion of pre-emergence terbutryn at 3.0

kg a.i ha-1) in a herbicide combination with any of the above-mentioned graminicides in

chickpea resulted in as effective weed-control and yield as obtained from hand-weeding

twice. None of the herbicide treatments resulted in yields higher than the weed-free

check. Herbicide efficiency in controlling weeds depended on the weed species present.

Sesharee et al. (1996) claimed that the best weed control and highest seed yield

(883 kg ha-1) of C. arietinum was given by pre-sowing application of 1 kg fluchloralin ha-

1 and hand weeding 30 days after sowing. When herbicides alone were applied,

fluchloralin was more effective than pre-emergence alachlor or isoproturon. Hand

weeding twice at 15 and 30 days after sowing gave good weed control and the second

highest seed yield of 828 kg. Dominant weed species were Cynodon dactylon L. and

Cyperus rotundus L.

Singh and Sahu (1996) assessed the efficacy of hand weeding 30 and or 45 or 60 days

after planting (DAP), pre-emergence, pendimethalin at 0.75-1.5 kg ha-1 or oxyfluorfen at

0.08-0.15 kg, or pre-plant incorporated fluchloralin at 1.0 kg, all ± hand weeding 45 DAP

at the lower doses, for control of a weed flora dominated by C.rotundus, M. indica, A.

arvensis and C. album in chickpeas. Results indicated that best yields of 2257 and 2222

kg ha-1 respectively, were obtained by hand weeding 60 or 30 + 60 DAP. Among

herbicide treatments, best yields of 1944 kg were obtained with pendimethalin + hand

weeding. It is concluded that hand weeding once 60 DAP was sufficient to control weeds

in this system.

Tesar and Smolikova (1996) conducted greenhouse and field trials at to assess 10 pre-

preemergence soil-applied herbicides for controlling of dicotyledonous weeds and

15

Echinochloa crus-galli, and for crop phytotoxicity in kabuli and desi chickpeas. Results

indicated that for kabuli chickpeas, the most effective herbicide was 1.32 kg ha-1

pendimethalin, while 0.875 + 0.375 kg terbutryn + terbuthylazine was the most effective

treatment in desi chickpeas but it did not give good control of E. crus-galli. Kabuli

chickpeas were found to be the more herbicide-tolerant, but 0.35 kg metribuzin was

found to be phytotoxic to both chickpea types.

Balyan and Malik (1996) investigated the efficacy of pre-plant incorporated

trifluralin at 1.0 -1.5 kg-1 pre-emergence pendimethalin at 10-1.5 kg ha-1, pre-em.

metribuzin at 0.22-066 kg ha-1 with all at the lowest doses + hand weeding), metribuzin at

0.22 kg ha-1 + isoproturon at 0.25 -0.5 kg ha-1, and hand weeding twice, for control of a

weed flora dominated by Chenopodium album, Fumaria parviflora and Lathyrus aphaca

in C. arietinum. Results indicated that all herbicide treatments reduced weed populations,

although they differed in their ability to control the dominant weeds. Best control was

achieved with trifluralin and pendimethalin, and weed biomass was reduced more in

treatments incorporating hand weeding. All treatments gave higher yields than the

unweeded control. Best grain yields of 956-1220 kg ha-1 were achieved with a weed- free

control, the hand weeded treatment and trifluralin or pendimethalin in combination with

hand weeding.

Bhalla et al. ( 1998) reported pre-emergence applications of alachlor ( 1.5 kg ha-1),

isoproturon (1.0 kg ha-1), oxyfluron (0.23 kg ha-1), metolachlor ( 1.5 and 2.0 kg ha-1),

linuron (0.625 and 0.750 kg ha-1), metribuzin (0.35 kg ha-1), pendimethalin (0.35 kg ha-1)

and pre-planting application of fluchloralin (0.0 kg ha-1), they were compared with hand

weeding once and an unweeded control in a chickpea. Linuron at 0.75 kg ha-1 and

isoproturon reduced the population of broadleaf weeds, which included Medicago

hispida, Cichorium intybus (chicory) and Trifolium fragiferum. Weed control efficiency

was the greatest under hand weeding (85%), followed by isoproturon (64%) and linuron

at 0.75 kg ha-1 (50%). Cichorium intybus, Medicago hispida, Phalaris minor and

Cynodon dactylon were poorly controlled by alachlor, pendimethalin, metribuzin,

16

oxyfluoralin, fluchloralin and metolachlor. All herbicide treatments gave significantly

higher seed yields than the unweeded control (246 kg ha-1) while the highest seed yield

was recorded from the hand weeding treatment (2090 kg ha-1), followed by linuron at

0.75 kg ha-1 (1995 kg ha-1),isoproturon (1481 kg ha-1) and linuron at o.625 kg ha-1 (1455).

Stork (1998) stated that both atrazine formulations (conventional and release

formulation) gave complete weed kill in chickpea crop dominated by Lolium rigidum,

Hordeum leporinum, Avena fatua, Polygonum aviculare and Sisymbrium orientale. Crop

safety ratings of chickpeas sown at application were higher for the controlled release than

the conventional formulation 10 weeks after sowing, and harvest yields were 50% higher.

Singh (1998) studied the impact of different herbicides on weed suppression and

yield in chickpea + mustard intercropping (4:1) at Bichpur. Cyperus rotundus,

Chenopodium album, Anagallis arvensis and Convolvulus arvensis were the dominating

weed species. Weeds reduced productivity by up to 36.8 %. Both pre-plant soil

incorporation of fluchloralin and pre-em. Application of pendimethalin, each at 1.5 kg ha-

1, resulted into lowest density and biomass of weeds. There was no significant variation

between these two treatments, but they were significantly superior over the control. The

same was true with respect to yield attributes. Chickpea equivalent yield was maximum

(1945 kg ha-1) with fluchloralin at 1.5 kg ha-1(58% higher yield than the control).

Sukhadia et al. (1999) conducted research on vertisol soils in chickpea, showed

that the maximum grain and fodder yield (1432 and 1660 kg ha-1, respectively) and

highest net return ( Rs.15450 ha-1) were obtained followed one hand weeding +

intercropping 30-35 days after sowing. Using herbicides with hand weeding and

intercropping gave and effective level of control of all weeds.

Thakar et al. (2000) conducted field trials at the PAU Regional Research Station,

Bathinda during 1990-91 to 1992-93 showed that weeds caused a reduction of 54 to 56 %

in yield of pigeon pea cv. GL-769 when they were allowed to grow undisturbed till

harvest. Application of linuron at 0.94 kg ha-1 gave the lowest weed population and dry

weight, the highest weed control efficiency (92.3 %), and the highest pigeon pea seed

17

yield of 1.59 t ha-1 compared with 0.69 t ha-1 in untreated controls. Application of

pendimethalin at 0.75 kg ha-1, linuron at 0.75 kg ha-1 and isoproturon 0.95 kg ha-1 was

also as effective as hand weeding in controlling weeds and increasing the yield, while

fluchloralin and 0.75 kg isoproturon were ineffective.

Ishwar et al. (2000) identified suitable herbicides for the management of A.

tenuifolius in Indian mustard. Treatments included a weeding 30 days after sowing

(DAS), fluchloralin at 1.00 litre ha-1 (pre-plant incorporation), pendimethalin at 1.00 kg

ha-1 (pre-emergence, PE), oxyfluorfen at 150 ml ha-1) (PE); oxyfluorfen at 250 ml ha-1

(PE), oxadiazon at 500 ml ha-1 (PE), and isoproturon at 750 g ha-1) (30 DAS). Indian

mustard was sown in first fortnight of October and A. tenuifolius and total weed counts

were recorded 60 DAS. The hoeing treatment gave the highest mean seed yield (1769 kg

ha-1), closely followed by the oxadiazon treatment (1742 kg ha-1) and then pendimethalin

(1692 kg ha-1). A. tenuifolius counts in the hoeing and oxadiazon treatments were 3.3 and

3.4 plants m-2, respectively, compared with the control (9.5 plants m-2). Oxyfluorfen (250

ml ha-1) resulted in the lowest A. tenuifolius count (2.7 plants m-2), but only increased the

seed yield by 10% (to 1430 kg ha-1), compared with the weedy control. Isoproturon was

least effective for both A. tenuifolius and total weed control, giving counts of 6.3 and 12.6

plants m-2, respectively. The highest net return (IRs.28390 ha-1) and benefit cost ratio

(4.36:1) were recorded with the oxadiazon treatment.

Malik et al. (2003) evaluated different herbicides alone or integrated with hand

weeding against weeds in chickpea. Integration of one hand weeding (30 DAS), with

follow up application of thiazopyr at 120g ha-1 reduced the density and dry weight of

weeds significantly attaining weed control efficiency of 94%.

Aamil et al. (2004) reported the effects of isoproturon, fluchloralin and 2, 4-D (0,

1000, 5000 and 10 000 µg ml-1) respectively on chickpea rhizobia, chickpea-Rhizobium

symbiosis, and yields, N content and photosynthetic pigments of chickpea (cv. BG-256)

were studied. Higher concentrations of these herbicides inhibited the growth of the root

nodule bacterium (Mesorhizobium ciceri) in vitro. The herbicides applied at 2-fold the

18

recommended rates (TF) adversely affected the health, photosynthetic pigments, and N

content of chickpea. The normal and TF rates of the herbicides except fluchloralin TF

increased the seed yield of chickpea. Nodulation and leghaemoglobin content were also

negatively affected by the herbicides at TF rates. Populations of specific and inoculated

chickpea rhizobia within single nodule of each treated plant were also adversely affected

by herbicide application, and showed variation in rhizobial populations within each

nodule as determined through replica immunoblot assay.

Marwat et al. (2004) tested the effect of 7 herbicides for weed control in chickpea.

The herbicides included; s-metolachlor at 1.44, metribuzin at 0.35 and pendimethalin at

0.99 kg a.i ha-1 as pre-emergence. The post emergence herbicides were isoproturon at

0.85, clodinafop at 0.03, and fenoxaprop-P-ethyl at 0.75 and pendimethalin at 0.99 kg a.i

ha-1. The data were recorded on weed density m-2, number of branches plant-1, number of

pods plant-1, number of grains plant-1, 1000-grains weight (g) and grain yield (kg ha-1).

For controlling weeds, hand weeding proved to be the best, giving only 9.17 weeds m-2 as

compared to 33.67 weeds m-2 in weedy check plots. Similarly, maximum grain yield

(1147.8 kg ha-1) was recorded in hand weeding plots. In herbicidal treatments,

pendimethalin as pre-emergence produced highest yield (1060.3 kg ha-1) as compared to

weedy check plots (338 kg ha-1).

Khan et al. (2004) carried out an experiment under greenhouse conditions in order

to evaluate the effects of applications of Bentozone, Isoproturon, Fluchloralin and 2, 4-D

on plant vitality and seed production in chickpea, inoculated with Mesorhizobium ciceri.

It was observed that ten times the recommended rates of all herbicides adversely affected

the plant vigour and seed production. Fluchloralin and 2,4-D gave the highest adverse

effects on seed production.

Hassan et al. (2006) applied s-metolachlor at 5.31 kg a.i ha-1, isoproturon (pre) at

4.5 kg a.i ha-1, isoproturon (post) at 4.5 kg a.i ha-1, pendimethalin (pre) at 3.7 kg a.i ha-1,

pendimethalin (post) at 3.7 kg a.i ha-1, metribuzin (pre) at 2.45 kg a.i ha-1, metribuzin

(post) at 2.45 kg a.i ha-1, fenoxaprop-p-ethyl at 1.87 kg a.i ha-1, clodinafop-propargyl at

19

0.16 kg a.i ha-1 for weed control in chickpea. For controlling weeds, fenoxaprop-p-ethyl

proved to be the best, giving only 20.70 weeds m-2 as compared to 31.23 weeds m-2 in

weedy check plots. Similarly, maximum grains yield (1.077 kg ha-1), 100 grains weight

(58.33 g) were recorded in fenoxaprop-p-ethyl plots followed by clodinafop-propargyl

produced highest yield (0.8767 kg ha-1). The herbicides were equally effective against all

grassy and broadleaf weeds in chickpea except A. tenuifolius, which is a threat to legume

and cereal crops in southern districts of North West Frontier Province Pakistan.

Hassan and Khan (2007) investigated the control of the noxious weed A.

tenuifolius in Cicer arietinum L. through application of post emergent herbicides. The

herbicides included were metribuzin at 2.45 kg a.i ha-1, isoproturon 4.5 kg a.i ha-1,

clodinafop-propargyl at 0.16 kg a.i ha-1, and fenoxaprop-p-ethyl at 1.87 kg a.i ha-1. All

the herbicides failed to give an adequate control of A. tenuifolius. For controlling weeds,

hand weeding proved to be the best, giving only 3.733 weeds m-2 as compared to other

herbicidal treated plots. The grain yield although non-significant statistically among the

different treatments was the maximum in clodinafop-propargyl treated plots. It was close

to hand weeding (2470 kg ha-1) and isoprotuon (2392.5 kg ha-1).

Datta et al. (2008) investigated the effect of soil pH on chickpea (Cicer arietinum)

tolerance to isoxaflutole applied pre-emergence at 300 g a.i. ha−1. For this study, the

variables examined were two desi chickpea genotypes (97039-1275 as a tolerant line and

91025-3021 as a sensitive line) and four pH levels (5.1, 6.9, 8.1, and 8.9). The results

demonstrated differential tolerances among chickpea genotypes to isoxaflutole at

different rates and soil pH levels. Isoxaflutole applied pre-emergence resulted in

increased phytotoxicity with increases in soil pH and herbicide rate. Even the most

tolerant chickpea genotype was damaged when exposed to higher pH and herbicide rates,

as indicated by increased leaf chlorosis and significant reductions in plant height, and

shoot and root dry weight. The effects were more severe with the sensitive genotype. The

susceptibility of chickpea to this herbicide depends on genotype and soil pH which

should be taken into account in breeding new lines, and in the agronomy of chickpea

production.

20

Scott and Christy ( 2008) concluded that sugar beet varieties vary in their response

to herbicides. s-Metolachlor and dimethenamid-P were recently registered for use in

sugar beet. Field trials were conducted to evaluate the response of 12 sugar beet varieties

to s-metolachlor and dimethenamid-P applied Pre and Post to two-leaf and four-leaf stage

sugar beet. s-Metolachlor and dimethenamid-P reduced sugar beet density when rainfall

occurred within 7 days of the Pre applications. Dimethenamid-P Pre caused the most

injury across all varieties followed by s-metolachlor Pre. Applying dimethenamid-P Post

to two-leaf sugar beet injured plants more than s-metolachlor applied Post to two- and

four-leaf stage sugar beet. The least amount of sugar beet injury from dimethenamid-P

was from Post applications at the four-leaf stage. Sugar beet varietals differences were

most pronounced from Pre applications of both herbicides and from the Post two-leaf

application of dimethenamid-P. Of the 12 sugar beet varieties evaluated, Hellish 2771RZ

and Beta 5833R were the most tolerant, whereas Hilleshog 7172RZ was typically the

most sensitive variety to these herbicides.

21

CHAPTER-3.

Studies on Temperature Regimes and Dormancy Breaking Chemicals Influencing

Seed Germination of Chickpea and Asphodelus. tenuifolius (Cav.)

Muhammad Ishfaq Khan and Gul Hassan Department of Weed Science, Faculty of Crop Protection Sciences

NWFP Agricultural University Peshawar-Pakistan

ABSTRACT

Wild onion (Asphodelus. tenuifolius Cav.) is a major weed of chickpea in the sandy tract

of Pakistan and its biology and physiology are little understood. Seeds of four biotypes

were collected from Bannu, Karak, Bhakkar and Mianwali districts of Pakistan for a

series of laboratory experiments. Seeds were treated with a range of concentrations of

gibberellic acid, potassium nitrate, thiourea or sodium azide and incubated at three

temperatures 10, 20 or 30oC. The experiment was repeated once. Biotypes differed in

dormancy status. Seeds of Mianwali biotype had the highest germination (74.5%) at

20oC, while the lower germination was recorded for both Bhakkar (44.8%) and Karak

(44.6%) biotypes at 10 and 20oC. The optimum germinating temperature was 20°C for all

four biotypes. Very little germination occurred at 30oC. The Bannu and Mianwali

biotypes were most germinable at 20oC, while germination of the Bhakkar biotype was

slightly higher at 10oC as compared to other biotypes. The differences in germination

may have occurred due to the geographical differences where the biotypes evolved.

Potassium nitrate, gibberlic acid and thiourea enhanced germination while sodium azide

completely inhibited seed germination. None of the chemicals was able to induce

germination at 30oC. The tolerance of five chickpea cultivars to Sodium azide was further

probed in the second experiment. Seeds of A.tenuifolius and five chickpea cultivars were

treated with sodium azide at 0, 0.76,1.53,2.30 and 3.07 mM for comparison. All chickpea

cultivars showed 100% germination at all concentrations except 3.07 mM where the two

cultivars KK-1 and KC-98 had 95% germination. The differences however were

statistically non significant from the remaining three cultivars, while A.tenuifolius

produced very little or no germination at all concentrations except 0 and 0.76 mM. Thus

22

to minimize the competition of wild onion in chickpea, sodium azide application could be

selectively applied to inhibit germination of wild onion without affecting chickpea

germination. Further studies are suggested to further probe the differential tolerance of

germplasm to sodium azide before recommending the intervention for practical adoption.

Key words: Biotypes, Chemicals, Concentrations, Temperature, Wild onion.

23

3.1 INTRODUCTION

Wild onion (A. tenuifolius Cav.), a member of family Asphodelaceae is a monocot

plant and a serious weed of 15 crops in 17 countries (Holm et al. 1997). It is a notorious

weed of sandy soils of Indo-Pak sub-continent (Mishra et al., 2006) and is annual in

habit. It has been observed as a serious weed of wheat (Triticum aestivum L.), mustard

(Brassica juncea L.), chickpea (Cicer arietinum L.), lentil (Lens culinaris Medic.), and

linseed (Linum usitatissimum L.) [Gupta et al., 1977; Poonia et al., 2001; Tiwari et al.,

2001]. A. tenuifolius was found most dangerous to the chickpea growers in sandy districts

of Northwest Frontier Province (NWFP), Pakistan viz. Karak, Lakki Marwat and parts of

Dera Ismail Khan (Hassan et al., 2004). In Punjab Province of Pakistan, it is the worst

competitor with winter crops in the sandy soils of Mianwali, Bhakkar, Jhang and Layyah

and sometimes causes 100% damage to chickpea in the sandy zone of Pakistan (Hassan et

al., 2004; Sultan and Nasir, 2003).

There are several features, which have rendered this weed species successful but the most

important one is the seed dormancy, which enables the seeds to persist in the soil and

survive under unfavourable conditions (Karssen, 1982; Harper, 1977; Holt, 1987).

Dormancy and its losses are associated with a number of biotic and abiotic factors

(Taylorson, 1970; Taylorson, 1980/81). Benvenuti and Macchia (1995) showed that high

CO2 and low O2 (hypoxia) induced dormancy in different weed species while Taylorson

(1980/81) reported otherwise. Several studies have exhibited that the buried seeds of

annual weeds undergo dormancy-non-dormancy cycles and even light does not stimulate

germination (Taylorson, 1970).

Chickpea (Cicer arietinum L.) is the principal pulse and provides a major source

of protein in the diet of the predominantly vegetarian population in Indo-Pak. It is

traditionally cultivated in arid (sandy areas) of NWFP but recently its production has

declined as chickpea has been replaced by wheat due to rapid expansion of irrigated areas

24

Farm surveys conducted during 2003 ranked A. tenuifolius as the top most weed of

chickpea in Lakki Marwat and Karak, Pakistan (Hassan and Khan, 2005). While

reporting the yield reduction due to A. tenuifolius Tiwari et al. (2001) observed 80% in

chickpea and Yaduraju et al. (2000) reported a 56% yield reduction in mustard when

wild onion was allowed to compete for full season. They also concluded that the initial

60 days period appeared to be critical for its competition in rain-fed chickpea. Apart

from competition this weed has the allelopathic potential to suppress the germination

and growth of wheat, mustard, chickpea, and lentil (Mishra et al., 2002).

Sahi and Bhan (1991b) reported that A. tenuifolius seeds can germinate in a range of

temperatures from 10 to 35oC, with an optimum at 15oC. A. tenuifolius is a greater

problem in chickpea as compared to wheat in the sandy districts of Pakistan. It is

speculated that due to thermo-sensitive nature of the weed, it is more abundant in

chickpea because the planting time of chickpea is during late September when the

temperatures are higher enough for germination of wild onion while wheat planting is

done in late October, the lower ambient temperatures at that time are conducive to the

germination of A. tenuifolius which is uprooted during land preparation at the planting

time. In order to understand the effect of temperature and germination promoters, seeds

of A. tenuifolius and chickpea were exposed to various temperatures and germination

promoters to investigate the most favourable temperature and effective chemical at

different concentrations. Investigating the germination requirement of temperature and

chemicals will enable us to formulate a package for its control. Keeping in view the

importance of the above studies, experiments were undertaken with the following

objectives:

1. To get insight into dormancy occurrence in different biotypes of A. tenuifolius.

2. To figure out the behavior of dormancy related to different dormancy breaking

chemicals, their concentrations and temperature regimes.

3. To investigate the dormancy pattern of A. tenuifolius under the interaction of

chemicals with their concentrations and temperatures.

4. To pinpoint the most tolerant cultivar to sodium azide at different concentrations.

25

3.2 MATERIALS AND METHODS

Experiment No. 1

3.2.1 Seed Collection

A. tenuifolius seeds were collected during chickpea harvesting in June 2005 in two

provinces (NWFP and Punjab) Pakistan. The locations selected from each provinces were

Bannu (32o N and 70o E), Karak (33o N and 71o E)] from NWFP and Bhakkar (31o N and

71o E) and Mianwali (32o N and 71o E) from Punjab. A. tenuifolious is a serious problem

in these districts of the two provinces. The average annual rainfall in these regions is 250-

300 mm. The seeds were cleaned and stored in paper bags at ambient temperature in the

laboratory.

3.2.2 Chemicals Treatments and Temperature Regimes

An experiment was conducted with the main plot being temperature regimes of 10oC,

20oC and 30oC. Subplots of Petri dishes containing twenty seeds on tissue paper in (CR)

design with factorial arrangement with four biotypes and four chemicals (gibberellic acid

(GA3), potassium nitrate (KNO3), thiourea (THU) and sodium azide (SA).Gibberellic

acid was applied at the rate of (0.57, 1.15, 1.73 and 2.30 mM), potassium nitrate (1.97,

3.95, 5.93 and 7.91 mM), sodium azid (3.07, 6.15, 9.22 and 12.30 mM) and thiourea

(2.62, 5.25, 7.88 and 10.50 mM). Individual Petri dishes were treated with 5 ml of

solution on days 0, 3, 9 and then kept moist with distilled water through out the

experiment. Each treatment was replicated twice. Germination assays were performed

over four weeks in a growth incubator (Model No.2020-2E, Shelab Manufacturing Inc.,

300 N, and 26th Cornelius, OR 97113) with a 12 hr daily photoperiod.

Experiment No. 2

Certified seed of five chickpea cultivars; Sheenghar, Lawaghir, KK-1, KK-2 and KC-98

were collected from the Gram Research Station, Ahmad Wala, Karak Pakistan. These

seeds were tested in comparison with the seed of A. tenuifolius biotypes Karak and

Bannu. The seed germination of both species was assayed by the procedure as outlined in

the first experiment. Five seeds of each chickpea cultivar and A. tenuifolus biotypes were

put for germination in Petri dishes. In comparison of seed germination of chickpea

26

cultivars with A. tenuifolius the same protocol as highlighted in experiment 1 was

followed except that only SA was applied at five concentration i.e. 0, 0.76, 1.53, 2.30 and

3.07 mM). In the previous experiments SA, was safe for chickpea and deleterious to A.

tenuifolious, therefore this chemical was tested against chickpea. Both experiments were

conducted under laboratory conditions at the Department of Weed Science, North West

Frontier Province Agricultural University, Peshawar, Pakistan from July-October 2005

and were repeated under the same laboratory conditions during July-October 2006. Petri

dishes were monitored twice a week for germinated seeds, which were then removed.

Seeds were deemed to have germinated when two mm of radicle was emerged.

3.2.3 Preparation of Chemicals

Solutions were prepared by the following procedure.

Instruments:

• Electronic balance (Metter AE-200)

• Lab Line Multimagnestir and Shaker No-1262-1

• Conical flask

• Beaker

• Stirring Magnet

Reagents

• Sodium azide (SA) NaNo3

• Gibberlic acid (GA3) C19H22O6

• Thiourea (TH) CSN2H4

• Potassium nitrate (KNO3)

• Distilled water

In the first experiment 0.8 g of each chemical were taken carefully through small tea

spoon and weighed through electronic balance (Metter AE-200) and added to make it

1000 ml. the remaing concentrations were than made from stock solution. Then the

solutions was transferred to Lab Line Multimagnestir and Shaker No-1262-1 for mixing

up the reagents well with distilled water for almost 6 minutes with the help of stirring

27

magnets inside the flask. After the preparation of all concentrations, flasks were covered

with hard polythene bags and were stored in a refrigerator.

Both the experiments were repeated under similar laboratory conditions during July-

October- 2005 and 2006.

Statistical Model and Data Analyses

GENSTAT software was used for analysis of variance and the model used for analysis

was completely randomized (CR) design with factorial arrangements and means were

separated through Fisher’s protected LSD test by using MSTATC. The mean data were

then transferred to MS Excel for graphical presentations.

28

0

5

10

15

20

25

30

35

40

45

50

Bannu Bhakkar Karak MianwaliBiotypes

Ger

min

atio

n %

July-October 2005

July-October 2006

32.31b 25.06c 24.25c 40.96a

3.3 RESULTS

Studies on Temperature Regimes and Dormancy Breaking Chemicals Influencing Seed Germination of Chickpea and A. tenuifolius (Cav.)

Experiment No.1

Germination of four biotypes of A.tenuifolius showed non significant differences during

the course of experiment in both the runs i.e. July-October 2005 and July-October 2006

(Fig-3.3.1). The data depicted that Mianwali biotype produced maximum (41.67 and

40.25%) germination in the either Run followed by Bannu biotypes and the remaining

two biotypes produced minimum germination.

Fig-3.3.1. Comparison of seed germination of A. tenuifolius biotypes.

The germination of A.tenuifolius biotypes (Bannu, Karak, Bhakkar and Mianwali)

averaged across runs, chemicals and concentrations were differentially affected

(Fig-3.3. 2) by temperature (P<0.001). Fig-3.3.2 indicates the nature of this interaction

with significantly higher germination observed at 20oC than at 10oC for Mianwali and

Bannu (88.4 and 66.0%), respectively. Mianwali biotype produced maximum

germination among all the biotypes at all temperatures (51%). Minimum average

germination was recorded for Karak (26%) while Bannu and Karak biotypes produced

29

0

10

20

30

40

50

60

70

80

90

100

10 20 30Temperature (Celsius)

Ger

min

atio

n %

Bannu

Bhakar

Karak

Mianwali

40.86b 49.42a 1.63c

Means

32.31b

25.05c

24.25c

40.96a

Gibberellic acid

010

2030

4050

6070

Bannu Bhakkar Karak Mianwali

Biotypes

Ger

min

atio

n %

0mM

0.57mM

1.15mM

0.1.73mM

2.30mM

Concentrations Means

38.74b 27.77c 25.25cd 52.0a

35.20b

40.52a

35.31b

34.47bc

34.16bc

same germination. Higher temperature (30oC) produced minimum or almost no

germination for all biotypes.

Fig-3.3.2. Comparison of seed germination of biotypes at different temperature regimes.

Analysis of variance of the data revealed that gibberellic acid and its concentrations

concentration significantly affected the germination of the different biotypes P<0.001

(Fig-3.3.3). The main effects of biotypes showed that maximum (52.0%) germination

was recorded in Mianwali biotype followed by Bannu biotype. While minimum (25.25%)

germination was produced by Karak biotype. However, it was statistically at par with

Bhakkar biotype. Among the gibberellic acid concentration maximum (40.52%)

germination was recorded at 0.57 mM. while minimum (34.16%) germination was

recorded at 2.30 mM. However, it was statistically at par with 1.73 mM. In the interaction

of biotypes and concentrations maximum (55.42%) germination was observed 0.57 mM

in Mianwali biotype. However, it was statistically at par with same biotype at 1.73 mM

and 0 mM.

Fig.3.3.3. Germination of biotypes as affected by gibberellic acid and its concentrations.

30

Potassium Nitrate

01020304050607080

Bannu Bhakkar Karak Mianwali

Biotypes

Ger

min

atio

n %

0mM

1.97mM

3.95mM

5.93mM

7.91mM

Concentrations Means

44.08b 35.33c 35.41c 55.49

48.64a

42.08b

42.39b

41.04bc

38.75d

Statistical analysis of the data revealed that potassium nitrate and its concentrations

concentration significantly affected the germination of the different biotypes P<0.001

(Fig-3.3.4). The main effects of biotypes showed that maximum (55.49%) germination

was recorded in Mianwali biotype followed by Bannu biotype. While minimum (35.41%)

germination was produced by Karak biotype. However, it was statistically at par with

Bhakkar biotype. Among the potassium nitrate concentration maximum (48.64%)

germination was recorded at 5.93 mM. While minimum (38.75%) germination was

recorded at 0 mM. The remaining concentrations produced moderate germination. In the

interaction of biotypes and concentrations maximum (62.08%) germination was observed

1.97 mM in Mianwali biotype. Followed by the same biotype at 3.95 mM, 7.91 mM and

0 mM.

Fig.3.3.4. Germination of biotypes as affected by potassium nitrate acid and its concentrations.

Biotypes germination was also significantly affected by sodium azid and its concentration

P<0.001 (Fig-3.3.5). The main effects of biotypes showed that maximum (11.75%)

germination was recorded in Mianwali biotype followed by Bhakkar biotype. While

minimum (5.58%) germination was produced by Karak biotype. Among the sodium azide

concentrations maximum (2.29%) germination was recorded at 3.07 mM. While the rest

of the concentration produced very less germination. In the interaction of biotypes and

concentrations maximum (47.92%) germination was observed in Mianwali at 0 mM. All

other biotypes produced significantly better germination at 0 mM, while very less or no

germination at all concentrations of sodium azide.

31

Sodium Azide

0

10

20

30

40

50

60

Bannu Bhakkar Karak Mianwali

Biotypes

Ger

min

atio

n %

0mM

3.07mM

6.15mM

9.22mM

12.30mM

Concentrations Means

6.92c 8.50b 5.58cd 11.75a

37.29a2.29b

0.62c0.31cd0.41cd

Fig. 3.3.5. Germination of biotypes as affected by sodium azide acid and its concentrations.

Thiourea and its concentrations also significantly affected the germination of different

biotypes P<0.001 (Fig-3.3.6). The main effects of biotypes showed that maximum

(44.58%) germination was recorded in Mianwali biotype followed by Bannu biotype.

While minimum (28.51%) germination was produced by Bhakkar biotype. However, it

was statistically at par with Karak biotype. Among the thiourea concentration maximum

(41.45%) germination was recorded at 10.50 mM. While minimum (26.56%) germination

was recorded at 2.62 mM. The remaining concentrations produced moderate germination.

In the interaction of biotypes and concentrations maximum (49.58%) germination was

observed at 10.50 mM in Mianwali biotype. Followed by the same biotype at all

concentration except 2.62 mM.

Thiourea

010

20304050

6070

Bannu Bhakkar Karak Mianwali

Biotypes

Ger

min

atio

n %

0mM

2.62mM

5.25mM

7.88mM

10.50mM

Concentrations Means

39.5b 28.5cd 30.75c 44.58a

41.45a37.60b37.50b

26.56d

36.04bc

Fig. 3.3.6. Germination of biotypes as affected by thiourea acid and its concentrations..

32

Experiment No.2

Chickpea cultivars showed non significant differences to sodium azide concentrations.

The data (Fig-3.3.7.) indicated that 100% germination was recorded at all concentration

except 3.07 mM when applied to Lawaghir and KK-1 (99% germination each) however

these were statistically similar to other concentrations.

90

92

94

96

98

100

102

S he enghar Lawa ghir KC-98 KK-1 KK-2

Chic kpea cult iva rs

0mM

0.76mM

1.53mM

2.30mM

3.07mM

Mea 100a 100a 99a 99a 100a

100a100a

100a

100a

98a

Means

Fig-3.3.7. Germination of chickpea cultivars treated with sodium azide at different concentrations.

Sodium azide concentration affected the germination A.tenuifolius significantly

(P<0.001) as shown in Fig-3.3.8. The data indicated 3.07 mM of sodium azide inhibit

germination of both the biotypes tested by 100% followed by 150 1.53 mM at which

Karak and Bannu biotypes germinated to the extent of 17.50 and 15 % respectively.

Control (0 mM) produced 100% germination followed by 65% in 50 mM and 60 in 0.76

mM in both the biotypes.

0

20

40

60

80

100

120

140

0mM 0.76mM 1.53mM 2.30mM 3.07mM

Sodium Azide Concentrations

Ger

min

atio

n %

KARAK

BANNU

100aMeans 65b 60b 16.25c 0d

Fig-3.3.8. A. tenuifolius biotypes seed germination as affected by sodium azide concentrations

33

3.4 DISCUSSION

The study demonstrated that germination of A. tenuifolius biotypes was significantly

affected by the temperature and dormancy breaking chemicals. Temperature being the

most important factor in seed germination played a vital role in breaking seed dormancy.

Intermediate temperature (20oC) was the optimum temperature for seed germination of

two biotypes i.e. Mianwali and Karak; the same biotypes also produced comparatively

higher germination at 10oC tested in this experiment. Little or no germination was

recorded at 30oC, suggesting that the thermal optimum for A. tenuifolius had been

exceeded at this temperature. Gorai et al. (2006) reported that exceeding the thermal

optimum can either inhibit germination or may cause irreversible seed damage. These

results provide the evidence for farmers to grow chickpea crop when the temperature falls

below 20oC to minimize the competition of A. tenuifolius. However, it is cautioned that

availability of moisture and lower chickpea yield due to delayed planting may be kept

into focus. On the other hand the growth regulators are also very important for breaking

dormancy and we found that KNO3 significantly promoted germination. Ecological

difference among biotypes was also found. Mianwali and Karak biotypes produced

higher while Bhakkar and Bannu biotypes produced lesser germination which is the

additional management strategy for A. tenuifolius due to ecological differences in the

germinability of the biotypes. Wild onion achieved 60 to 100% of its maximum

vegetative growth at temperatures ranging from 18/11 to 30/23°C day/night (Patterson,

1996). The greatest biomass was produced at day temperatures of 18 or 24°C and night

temperatures of 11 or 17°C.

Sahi and Bhan (1991a) reported that temperatures ranging from 10-35oC favour

germination of A. tenuifolius with maximum germination at 15oC. Hassan et al. (2004).

Hassan and Khan (2005) investigated that GA3 and KNO3 break dormancy in many weed

species. Mishra et al. (2002), Poonia et al. (2001), Yadev and Poonia (2005) and

Yaduraju et al. (2000) also concluded that temperature is the most important parameter

affecting germination. Bennvenuti and Macchia (1995), Karssen (1982) and Harper

(1977) and Holt (1987) claimed that temperature and growth regulators are important

factors in seed germination besides ecological differences among biotypes is also very

34

important for the management of wild onion (A. tenuifolius). The instant results show that

early sowing of chickpea or late sowing of wheat in rainfed areas in conjunction with

other weed control methods could suppress this weed. In addition to these competitive

cultivars, higher seed rates and rotation are also very important for the management of A.

tenuifolius (Mishra et al. 2002).

In experiment 2, all the chickpea cultivars germinated at all concentrations except 3.07

mM while, no germination was observed in A. tenuifolius biotypes at 3.07 mM of sodium

azide. The tested cultivars were found tolerant to all the concentrations of sodium azide

except its maximum dose (3.07 mM), so these cultivars are recommended for the use of

sodium azide to inhibit the germination of wild onion. These studies provide the evidence

that if sodium azide applied to the field during seed bed preparation will inhibit the

germination of A. tenuifolius seeds. Further studies are suggested to investigate the

feasibility of sodium azide as a germination inhibitor of A. tenuifolius under the field

conditions. Differential herbicides tolerance has been attributed to a differential uptake

in wheat (DeFelipe et al., 1988), barely (Snipes et al., 1987) and other grasses (Derr,

et al., 1985). But such a tolerance even in other barely and wheat cultivars was assigned

to rapid metabolism in tolerant cultivars (Fedtke and Schmidt, 1988; Gawaronski et al.,

1987). Moreover, along with rapid metabolism, differential uptake and translocation was

presented as the cause of tolerance in soybean (Connely et al., 1986). In many cases

tolerance has been attributed to a varying target site (Stoltenberg et al., 1989).

35

CHAPTER-4.

Effect of Different Herbicide and their Doses at Various Growth Stages of Asphodelu tenuifolius Grown in Pots

Muhammad Ishfaq Khan and Gul Hassan Department of Weed Science, Faculty of Crop Protection Sciences

NWFP Agricultural University Peshawar-Pakistan

ABSTRACT

A pot experiment was conducted at the Department of Weed Science, NWFP

Agricultural University Peshawar, Pakistan during 2005-06 and 2006-07 in Completely

Randomized design with factorial arrangement. The experiment was undertaken to

investigate the effect of different herbicides and their doses on A.tenuifolius at different

growth stages. Four biotypes (Bannu, Karak, Bhakkar and Mianwali) of A. tenuifolius

were subjected to two herbicides viz. isoproturon and fenoxaprop-p-ethyl each having

four doses including an untreated check. The doses of fenoxaprop-p-ethyl were 0, 0.47

(½x), 0.94 (1X) and 1.30 (1.5X) kg a.i ha-1, while the doses of isoproturon were 0, 2.0

(½x), 4.0 (1X) and 6.0 (1.5X) kg a.i ha-1. Each biotype was subjected to 4 doses of each

herbicide at 2 and 4 leaf and flowering stages. Each treatment was replicated twice. The

data were recorded on fresh and dry weight of A. tenuifolius. The main effects of growth

stages, biotypes and herbicides doses and the interaction of herbicides x doses and

biotypes x growth stages significantly affected the fresh and dry weight. The remaining 2

and 3-way interactions, were non significant statistically. Among the growth stages, the

highest value was observed for flowering stage (9.19 g), while lowest (0.95 g) fresh weed

biomass was recorded at 2 leaf stage of A. tenuifolius. For dry weed biomass, maximum

(3.53 g) value was again recorded for flowering stage while 0.40 value was observed at 2

leaf growth stage. Among the herbicides doses the highest (4.83 g) fresh weight was

recorded in untreated check while the lowest (3.66 g) fresh weight was observed at higher

doses. Highest (4.76 g) fresh weight was observed for Mianwali biotype and the

remaining biotypes showed similar response statistically. For dry weight, highest (1.97 g)

value was recorded in untreated check, while the lowest (1.40 g) value was recorded in

36

the higher doses. Among the biotypes, highest (2.16 g) dry weight was recorded for

Mianwali biotype while the lowest (1.37 g) dry weight was recorded for Bannu biotype.

Flowering stage produced highest (3.51 g) dry weight while the lowest (0.40 g) dry

weight was recorded at 2 leaf stage indicating the 2 leaf stage as the most susceptible

stage to the herbicide tested. In the three way interaction of biotypes x herbicides x

growth stages, the highest (4.36 g) dry weight was observed under Mianwali in both

herbicides at flowering stage while, the lowest (0.31 g) dry weight was recorded at 2 leaf

stage in fenoxaprop-p-ethyl, however it was statistically at par with the value recorded in

isoproturon at 2 leaf stage. It is thus recommended that wild onion may be treated at its 2

leaf stage with either fenoxaprop-p-ethyl or isoproturon for economy and environmental

safety.

Key words: A. tenuifolius, biotypes, doses, herbicides, growth stages, wild onion

37

4.1 INTRODUCTION

Wild onion (A.tenuifolius Cav.) is the most aggressive weed of chickpea in the sandy

zone of Pakistan. Herbicides comprise 20-30% of input costs in North American

cropping systems (Derksen et al. 2002). Despite widespread farmer adoption of

herbicides, there is ever-increasing interest in reducing herbicide doses and overall

herbicide use. Growers cite low commodity prices, crop injury, and herbicide carryover

concerns, the escalating problem of herbicide resistant weeds, and rising unease with the

environmental and human health effects of pesticides as issues forcing them to reconsider

how should they manage weeds. Without herbicides, successful long-term weed

management will require a shift away from simply controlling problem weeds to systems

that restrict weed reproduction, reduce weed emergence, and minimize weed competition

with crops. Research has shown that competitive crop production practices can contribute

to the development of more sustainable weed management systems (Mohler, 2002).

Aamil et al., (2004) reported the effects of isoproturon, fluchloralin and 2,4-D (0, 1000,

5000 and 10 000 µg ml-1) on chickpea rhizobia, chickpea-Rhizobium symbiosis, yields, N

content and photosynthetic pigments. Higher concentrations of these herbicides inhibited

the growth of the root nodule bacterium (Mesorhizobium ciceri) in vitro. The herbicides

applied at 2-fold the recommended doses (TF) adversely affected the health,

photosynthetic pigments, and N content of chickpea. The normal and TF doses of the

herbicides except fluchloralin TF increased the seed yield of chickpea.

The study of the response of the crop at various growth stages is also important because

fenoxaprop, like other graminicide, is only effective in post emergence application to

weeds and effectively control some weeds even in advanced stages of growth (Beringer

et al., 1982). Therefore, the knowledge of a crop at its developmental stages is utmost

importance. Many other workers have reported the enhanced tolerance with advanced

stage (Kells et al., 1984 and 1986 and Derr et al., 1985). On the other hand, some

findings show susceptibility at certain later stages of growth particularly in cereal (Olson

et al., 1951).

38

Timing of chemical weed control has an important impact on the efficacy of herbicides.

For good economic returns, herbicides need to be applied at the most tolerant stage of the

crop coupled with the most vulnerable stage of weeds. An increased tolerance to

herbicides due to age has been reported in several weeds and crop species (Street and

Richard, 1983; Kells et al., 1984). Increased tolerance to fenoxasprop in rice with more

advanced growth stage has been reported by (Snipes and Street, 1987).

The efficiency of herbicides on weeds is influenced by dose. Generally, high herbicide

doses are recommended but these doses may be an overestimation of the amount required

to obtain adequate control. Promising ways to minimize herbicide consumption include

the use of low doses (Zoschke, 1994). However, as the surviving weeds will be able to set

seed and, when incorporated to the seed bank, weed populations may increase in the

following years, the effective herbicide dose must be precisely known. Weed species vary

in their susceptibility to herbicides and there is growing concern due to the increase of

species difficult to control with herbicides. Furthermore, as weeds increase in size, they

become less susceptible to herbicides (Devlin et al., 1991; Klingaman et al., 1991;

Blackshaw & Harker, 1997). Wille et al. (1998) concluded that herbicides were more

efficacious at low wild oat densities than at high wild oat densities. Dieleman et al.

(1999) also reported that herbicide efficacy on velvetleaf and common sunflower

(Helianthus annuus L.) was greater at low than at high weed densities. Thus, any crop

production practice that reduces weed populations over time is important to the

successful use of reduced herbicide doses.

Some crops are likely to be more amenable than others to the use of reduced herbicide

doses. Kirkland et al. (2000) reported that good crop yields and the highest net returns

could be attained with a 50% herbicide dose in barley but that a 100% herbicide dose was

required to attain the highest yields and net returns in lentil (Lens culinaris L.).

39

The present studies are an attempt to investigate efficacy of ½x, 1X and 1.5X doses of

herbicides against A. tenuifolius with the following objectives.

1. To identify the most susceptible growth stage of A. tenuifolius to herbicides. 2. To figure out the more economical herbicide for the control of A. tenuifolius. 3. To quantify herbicides doses for the better management of A. tenuifolius.

40

4.2 MATERIALS AND METHODS

4.2.1 Location of Experiment

The experiment designed to evaluate the effect of different herbicide doses at various

growth stages of A. tenuifolius grown in pots was conducted at the Department of Weed

Science, NWFP Agricultural University Peshawar, Pakistan.

4.2.2 Seed Collection and Herbicides Application

Four biotypes of A. tenuifolius were collected from districts Bannu, Karak (North West

Frontier Province- Pakistan) and Bhakkar and Mianwali (Punjab- Pakistan) were seeded

in pots of 10 cm filled with a sandy loam soil, during mid-October, 2005-06 and 2006-07

in three phases. Ten seeds per pot were seeded. The seeds of wild onion were planted in

three phases at one month interval to obtain the plant simultaneously at all growth stages

(2 leaf, 4 leaf and flowering). Two herbicides (isoproturon and fenoxaprop-p-ethyl) were

tried each having four doses including an untreated check. The doses of fenoxaprop-p-

ethyl were 0, 0.47 (½x), 0.94 (1X) and 1.30 (1.5X) kg a.i ha-1. Whereas the doses used for

isoproturon were 0, 2.0 (½x), 4.0 (1X) and 6.0 (1.5X) kg a.i. ha-1.

4.2.3 Procedure for Herbicides Applications

Each biotype was subjected to 4 doses of each herbicide at 2 leaf, 4 leaf and flowering

stage of A. tenuifolius. All the three stages of plants were sprayed at the same time when

the last phase reached two leaf, second was with four leaf and the last phase at flowering

stage at the time of herbicides application. For herbicides spray, knapsack sprayer was

used fitted with T-jet nozzle. Each treatment was replicated twice. Pots were watered

weekly.

4.2.4 Data recording

The data were recorded on fresh and dry weight of A. tenuifolius one month after

application at each growth stage. The plants were harvested manually with the help of a

scissor at the time when the plants were free of dew. After harvesting, plants were put in

paper bags. The Paper bags were labeled with a permanent marker. Fresh weight was

41

recorded right after harvesting the sample. While dry weight was recorded after drying

the plants at 65oC in oven for 48 hours when the plants were completely dried and free of

moisture. Both fresh and dry weight was taken on an electronic balance (Veg tag

International) in grams (g).

Statistical Analysis

The data recorded on each trait were individually subjected to ANOVA using MSTATC

computer software and the means were separated by using Fisher’s protected LSD test

(Steel and Torrie, 1980).

42

4.3 RESULTS

Effect of Different Herbicides and their Doses at Various Growth Stages of

A. tenuifolius Grown in Pots during 2005-06.

Analysis of variance of the data showed that herbicides, biotypes, and their interactions

differentially affected the fresh biomass of A. tenuifolius (Fig-4.3.1.1). The main effects

of biotypes showed that the lowest (4.16 g) fresh biomass was observed for Bannu

biotype and highest (4.70 g) weight was recorded in Mianwali biotype while the

remaining biotypes produced almost the same fresh weight. In the interaction of

herbicides and biotypes, fenoxaprop-p-ethyl produced the highest (4.90 kg ha-1) fresh

weight in Mianwali biotype while lowest (3.97 g) fresh weight was recorded for Karak

biotype for the same herbicide. Almost similar responses have been recorded for

isoproturon in all the tested biotypes.

Growth stages, herbicides doses and their interactions differentially affected the fresh

biomass of A. tenuifolius (Fig-4.3.1.2). The data indicated that the main effect of growth

stages produced the lowest (0.95 g) biomass at two leaf stage while highest (9.19 g) fresh

weight was recorded at flowering stage. Among the herbicide doses minimum (3.66 g)

fresh weight was recorded at the highest herbicide (1.5X) dose while maximum (4.83 g

and 4.73 g) fresh weight was observed in untreated and low (½x) doses, respectively. In

the interaction of growth stages and herbicides doses the minimum (0.95 g) fresh weed

biomass was recorded at 2 leaf stage for all the tested herbicides doses while maximum

(9.44 g) fresh weight was recorded at flowering stage for all the doses.

Analysis of variance of the data showed that growth stages, herbicide doses and their

interaction had significantly affected the dry weight of A. tenuifolius (Fig-4.3.1.3). The

data in Fig-4.3.1.3 showed that the main effects of doses produced minimum (1.40 g) dry

biomass at 1.5X dose while maximum (1.98 and 1.91 g) at untreated and ½x dose,

respectively. Among growth stages the maximum (3.53 g) dry biomass was observed at

flowering stage while minimum (0.40 g) dry biomass was recorded at 2 leaf stage. Four

43

leaf stage produced 1.29 g dry biomass. In the interaction of growth stages and herbicide

doses, maximum (3.5 g) dry biomass was observed at flowering stage at all the herbicide

doses except 1.5X dose. While minimum (0.2 g) dry biomass was recorded at 2 leaf stage

at 1.5X dose of the herbicide.

Herbicides, growth stages, and dose three way interactions differentially affected the dry

biomass of A. tenuifolius (Fig-4.3.1.4). In the three way interaction, the highest (4.36 g)

dry weight was recorded in Mianwali biotype treated with fenoxaprop-p-ethyl at

flowering stage followed by the same biotype at same growth stage treated with

isoproturon (4.07 g). All the biotypes at two leaf stage showed statistically similar

response to both herbicides. At four leaf stage, Mianwali biotype produced statistically

similar dry weed biomass (1.816 and 1.693 g) in fenoxaprop-p-ethyl and isoproturon,

respectively. Mianwali biotype was the most tolerant to the herbicides in biomass

production. Whereas two leaf stage was the most susceptible growth stage of the A

.tenuifolius to both the herbicides tested.

0

1

2

3

4

5

6

Bannu Karak Bahkkar Minawali

Biotypes

Fres

h bi

omas

s (g)

fenoxaprop-p-ethyl

isoproturon

c bc cab c bc

aab

Means 4.164b 4.320b 4.200b 4.760a

Fig-4.3.1.1. Fresh biomass of different biotypes of A.tenuifolius as affected by the interaction of different herbicides and biotypes.

44

0

2

4

6

8

10

12

0 ½x 1X 1.5X

Herbicide doses

Fres

h bi

omas

s (g)

2 leaf

4 leaf

Floweringf

d

a

f

e

c

f

e

ab

f

e

bc

Means

Means

4.83a 4.73a 4.20a 3.66c

0.95c

2.94b

4.83a

Fig-4.3.1.2. Fresh biomass of different biotypes of A.tenuifolius as affected by the interaction of herbicides Doses and growth stages.

00.5

11.5

22.5

33.5

44.5

0 ½x 1X 1.5X

Herbicide doses

Dry

bio

mas

s (g) 2 leaf

4 leaf

Floweringf

c

a

fg

c

a

gh

d

a

h

e

b

Means

Means

1.98a 1.91a 1.67b 1.40c

0.54c

1.71b

4.70a

Fig-4.3.1.3. Dry biomass of different biotypes of A.tenuifolius as affected by the interaction of different herbicides and their doses.

00.5

11.5

22.5

33.5

44.5

5

Bannu Karak Bhakkar Mianwali Bannu Karak Bhakkar Mianwali

fenoxaprop-p-ethyl isoproturon

Herbicides and biotypes

Fres

h bi

omas

s (g)

2 leaf

4 leaf

Floweringk kkkkkkkj

f

hi

de

ij

d

g

a

ij

e

ij

c

h

bc

g

bMeans

0.405c

1.29b

3.53a

Fig-4.3.1. 4 Dry biomass of different biotypes of A.tenuifolius as affected by the interaction of different herbicides, biotypes and growth stages.

45

Effect of Different Herbicides and their Doses at Various Growth Stages of A.tenuifolius Grown in Pots during 2006-07.

Fresh weed biomass of A. tenuifolius was differentially affected by herbicides, biotypes,

and their interactions (Fig-4.3.2.1). The main effects of biotypes showed that maximum

(4.74 g) fresh weight was recorded in Mianwali biotype while rest of the biotypes showed

statistically similar response. In the interaction of herbicides and biotypes minimum

(4.01, 4.73 g) fresh weight was recorded in Bannu and Karak biotype respectively treated

with fenoxaprop-p-ethyl while maximum (4.86 g) fresh weight was observed in Mianwli

biotype treated with fenoxaprop-p-ethyl. However, it was statistically at par with Karak

biotype (4.73 g) treated with isoproturon. Mianwali biotype showed maximum tolerance

to both herbicides while Karak biotype also showed a good tolerance against isoproturon.

Analysis of variance of the data revealed that the main effects of growth stages

significantly affected fresh biomass of A. tenuifolius (Fig-4.3.2.2). The data indicated that

minimum (1.0 g) fresh biomass was observed at two leaf stage while maximum (9.30 g)

fresh weight was recorded at flowering stage. Four leaf was intermediate stage producing

2.91 g fresh biomass.

Growth stages and herbicides doses differentially affected dry biomass of A. tenuifolius

(Fig-4.3.2.3). The main effects of herbicide doses showed that minimum (1.43 g) dry

weight was observed at 1.5X dose of herbicides, while maximum (2.0 and 1.96 g) dry

weight was recorded in untreated check and ½x dose of herbicides, respectively. Among

the growth stages, minimum (0.41 g) dry weight was recorded at two leaf stage of wild

onion and maximum (3.59 g) dry weight was recorded at flowering stage followed by

four leaf stage (1.32 g). In the interaction of herbicides doses and growth stages,

minimum (0.23 and 0.34 g) dry biomass was observed at two leaf stage at 1X and 1.5X

doses of herbicides while maximum (3.75, 3.61 and 3.76 g) dry biomass was observed at

flowering stages at ½x and 1X doses of herbicides and in the untreated check,

respectively.

46

Herbicides, biotypes, growth stages and their interactions differentially affected the dry

weed biomass of A. tenuifolius (Fig-4.3.2.4). In the interaction of biotypes and herbicides

minimum (0.321 g) dry biomass was recorded in Bannu biotype treated with fenoxaprop-

p-ethyl at two leaf growth stage however, it was statistically similar with rest of the

biotypes treated with both the herbicides at the same growth stage while, highest (4.43 g)

dry biomass was observed in Mianwali biotype treated with fenoxaprop-p-ethyl.

However, it was statistically at par with the same biotype treated with isoproturon at

flowering stage of wild onion. At the four leaf growth stage maximum (1.84 g) dry

biomass was observed in Mianwali biotype treated with either of the herbicides while

minimum (0.92 g) dry biomass was recorded in Bannu biotype which was statistically at

par with same biotype treated with isoproturon and also with Karak biotype treated with

isoproturon and Bhakkar biotype treated with fenoxaprop-p-ethyl (Fig-4.3.2.4).

0

1

2

3

4

5

6

Bannu Karak Bahkkar Minawali

Biotypes

Fres

h bi

omas

s (g)

fenoxaprop-p-ethyl

isoproturon

d d cda

b-d ab b-d a-c

Means 4.17b 4.34b 4.25b 4.74a

Fig-4.3.2.1. Fresh biomass of biotypes of A.tenuifolius as affected by the interaction of herbicides and biotypes

02468

101214

2 leaf 4 leaf Flowering

Growth stages

Fres

h bi

omas

s (g)

cb

a

1.0 2.91 9.3

Fig-4.3.2.2. Fresh biomass of biotypes of A.tenuifolius as affected by growth stages.

47

00.5

11.5

22.5

33.5

44.5

0 ½x 1X 1.5X

Herbicide doses

Dry

bio

mas

s (g)

2 leaf

4 leaf

Floweringf

c

a

fg

c

a

gh

e

b

h

e

b

Means

Means

1.96a 1.70b 1.43c2.0a

0.55c

1.76b

4.78a

Fig-4.3.2.3. Dry biomass of different biotypes of A.tenuifolius as affected by the interaction of herbicides doses and growth stages.

00.5

11.5

22.5

33.5

44.5

5

Bannu Karak Bhakkar Mianwali Bannu Karak Bhakkar Mianwali

fenoxaprop-p-ethyl isoproturon

Herbicides and biotypes

Fres

h bi

omas

s (g)

2 leaf

4 leaf

Floweringk kkkkkkkj

f

hi

de

ij

d

g

a

ij

e

ij

c

h

bc

g

bMeans

0.42c

1.32b

3.59a

Fig-4.3.2.4. Dry biomass of different biotypes of A.tenuifolius as affected by the Interaction of different herbicides, biotypes and growth stages.

48

4.4 DISCUSSION

The variability in fresh and dry weight of biotypes showed that agro-ecological factors

play an important role in the tolerance of wild onion to herbicides. All the herbicide doses

responded to the growth stages of wild onion. Lower (½x) and recommended (1X) doses

provided satisfactory results at two and four leaf stages, which mean that reducing the

herbicides doses will work adequately and reduce the environmental risk. All the four

biotypes, produced very low dry biomass at two leaf stage. The variability among the

growth stages and biotypes showed that two leaf stage was more susceptible stage to

herbicides as compared to four leaf and flowering stages. As the test species increased in

size, it becomes less susceptible to herbicides depicting that tolerance in wild onion is

directly proportional to the growth stage (Devlin et al., 1991; Klingaman et al., 1991;

Blackshaw & Harker, 1997). In another study Puricelli et al. (2004) proved that with ½x

the herbicides were also able to control many weed species.

Herbicides doses being the most important factor in the experiment, made it clear that

highest dose of herbicides reduced the weed biomass better as compared to the rest of the

doses at all the growth stages. But for the environment safety or if there is a narrow

margin in tolerance between the crop and weeds, reduced dose are preferred (Defelice et

al. 1989).

Reduced dose technology is an approach to lower costs that can provide effective control

of susceptible species and decrease weed seedling vigour of less susceptible species to

give the crop competitive growth advantage (Vangessel & Westra, 1997). However, in

our study 1⁄2X gave an adequate control of wild onion at 2 leaf stage. Defelice et al.

(1989) were also of the view that ½x reduced the fresh and dry biomass of the weed

species.

The herbicide fenoxaprop-p-ethyl decreased the weed biomass more as compared to

isoproturon. While in biotypes, Mianwali biotype produced maximum biomass as

compared to the rest of the biotypes while Bannu biotype produced the least biomass and

49

was more susceptible to fenoxaprop-p-ethyl. Thus, for controlling wild onion, the

prevalent biotype will need to give a due consideration in adjusting the dose of herbicide.

The instant findings are supported by Zoschke, (1994), Zhang et al. (2000), Spandl et al.

(1997), Stougaard et al. (1997), Brain et al. (1999), Bostrom and Fogelfors (2002),

O’ Donovan et al. (2003), Walker et al. (2002), Gressel (1995) and Beckie and Kirkland

(2003). These workers concluded that the risk associated with reduced herbicide doses

increased in the absence of other weed management practices such as higher crop seed

rate or competitive cultivars.

50

CHAPTER-5.

Tolerance of Chickpea Cultivars to Major Chickpea Herbicides

Muhammad Ishfaq Khan and Gul Hassan Department of Weed Science, Faculty of Crop Protection Sciences

NWFP Agricultural University Peshawar

ABSTRACT

Growing chickpea in sustainable systems requires the use and development of more

adaptable genotypes which can adjust to the package of technology in vogue. Legumes

are poor competitors with weeds. Hence repeated experiments were undertaken for

quantifying the tolerance of chickpea cultivars with pre emergence herbicide

pendimethalin 330E and post emergence herbicide fenoxaprop-p-ethyl 75 EW each at

four doses. The chickpea varieties tested for tolerance were KC-98, Sheenghar,

Lawaghir, KK-1, KK-2, SL-01-13, SL-02-13, SL-02-20, SL-02-22, SL-02-29, SL-03-29

and SL-04-29. Data were recorded on fresh and dry biomass of the germplasm.

GENSTAT computer software was used for data analysis and separation of means. Non

significant differences were found in both of the experiments for fresh and dry biomass of

cultivars (11.45 and 11.31) and (2.932, 2.938), respectively. Sheenghar variety produced

the best fresh weight (13.7 g) fol1owed by KC-98, Lawaghir and KK-1 (13.1, 12.24 and

13.0 g), respectively. Average effects of both the herbicides i.e. fenoxaprop-p-ethyl and

pendimethalin were same on fresh biomass (11.37 and 11.39 kg ha-1), respectively.

Untreated and ½x dose produced statistically similar results for fresh biomass (12.53 and

12.8 kg ha-1) respectively. While minimum fresh biomass was recorded at 1.5X dose

(8.8). 1X dose produced intermediate fresh weight (11.3). For dry biomass untreated

check produced maximum (3.45 g) fol1owed by ½x dose (3.40 g) while, 1.5X dose

produced very low dry biomass (1.84 g) at either of the herbicides. It is thus, concluded

from the data that all the tested cultivars have a reasonable tolerance to the two herbicides

and these herbicides could be used in any of the tested cultivars at the 1/2 and 1X doses

without any adverse effect on the tested cultivars.

Key words: Chickpea, cultivar, herbicides, doses.

51

5.1 INTRODUCTION

Chickpea (C. arietinum L.) belongs to family Fabacceae; sub family Faboideae having

diploid chromosome number 16. The name chickpea is derived from the Latin name

Cicer (Muehlbauer, 1996). Chickpea is an annual grain legume or "pulse" crop that

originated in the Fertile Crescent of the Near East. Chickpea was one of the first legumes

cultivated by humans, dating back to 7000-6000 BC. The term "pulse" originates from

the Latin word puls, meaning "thick soup." Pulse crops like chickpeas, dry beans, dry

peas, faba beans, lentils and lupine work with rhizobia bacteria to convert nitrogen from

the atmosphere into nitrogen nodules on the plant roots (Soltani et al., 2000). Most

chickpea growing areas have cool and cold semiarid climates with terminal drought stress

that occurs between flowering and the beginning of grain filling (Soltani et al., 2001).

Chickpeas are classified as "desi" or "kabuli" types based in part on seed size, color and

the thickness and shape of the seed coat. Desi types produce smaller seeds, generally 100

or more seeds per ounce. The seeds have a thick, irregular-shaped seed coat which can

range in color from light tan to black. Kabuli types, also called "garbanzo beans,"

produce larger seeds that have a paper thin seed coat and are graded into 58 or fewer

seeds per ounce. The kabuli types produce seeds with colors that range from white to a

pale cream colored. (ICARDA Annual Report, 1983). It is a member of the West Asian

Neolithic crop assemblage, having been domesticated some 10,000 years ago alongside

other pulses such as pea and lentil, as well as cereals such as barley etc (Abbo et al.

2003). The chickpea has been disseminated widely, and now ranks second among the

world’s food legumes in terms of area, being grown over 9.9 million ha on all continents

except Antarctica (FAO 2004). Chickpea cultivars were studied with various

environmental concern (Singh et al., 1987; Jain and Pandya 1988; Rao and Suryawanshi

1988; Ashraf et al., 2001; Zubair & Ghafoor, 2001). The stability parameters have also

been studied in grain legumes for measuring phenotypic stability (Khan et al., 1987;

Khan et al., 1988; Bakhsh et al., 1995; Sharif et al., 1998; Qureshi, 2001), but still it is

very important information that should be available for the forthcoming chickpea

varieties.

52

Hassan and Mueller-Warrant (1992) evaluated the tolerance among rice and ryegrass

cultivars to fenoxaprop. Differential tolerance among the cultivars was reported in the

both species.

Chickpea germplasm is maintained at two International centers (ICRISAT in India and

ICARDA in Syria) and at National centers including the Vavilov institute in Russia, the

USDA-ARS Regional Plant Introduction Station at Pullman in the U.S. and other gene

banks. Tremendous variation for economically important traits has been documented and

improved cultivars have been developed and released (Ashraf et al., 2001).Variation for

Flower and seed color and size, growth duration, yield, and biomass, disease resistance,

quality traits (cooking time, amino acid content, flatulence and digestibility) are recorded.

'Kabuli' type chickpeas (Mediterranean and Middle Eastern origin) generally have the

largest seeds, and grow well under irrigation. Desi chickpeas (Indian distribution) have

smaller seeds, and yield better in Indian subcontinent, Ethiopia and often elsewhere.

Hybrids between Kabuli and Desi have produced strains with medium-size seeds and fair

yields. The bulk of chickpeas grown in developing countries are from unselected land

races. Germplasm with resistance to major diseases has been identified and genes for

important diseases have been named (ICARDA Annual Report, 1983).

Acceptable control of weeds can often be obtained by applying herbicides at lower doses

than those normally recommended (Fogelfors, 1990; Salonen, 1992; Lundkvist, 1997).

This makes it possible to lower production costs and reduce possible negative effects of

pesticides on the environment.

At present, the aim of weed management is to keep the weed community at an acceptable

level rather than to keep the crop totally free of weeds. Several studies have shown that

weeds may often be satisfactorily controlled when herbicides are used at lower doses than

those normally recommended (Fernandez-Quintanilla et al. 1998; Navarrete et al. 2000;

Zhang et al. 2000; Boström and Fogelfors, 2002) while maintaining satisfactory crop

yield (Steckel et al. 1990; Fernandez-Quintanilla et al. 1998; Navarrete et al. 2000).

53

Herbicides at reduced doses are often sufficient to control weed density at or below the

threshold levels, and below-labelled herbicide doses in combination with some

mechanical weed control have proven to be an effective way of reducing herbicide input

in agricultural systems (Hamill and Zhang, 1995).

A.tenuifolius is very aggressive weed species prevailing in the study area and competes

with chickpea crop for the whole season. This weed species produced 45% average yield

losses annually in sandy zone of Pakistan. To overcome problem, we investigated

herbicides with recommended (1X), lower (½x) and higher (1.5X) doses on chickpea

genotypes for their tolerance with the following objectives:

1. To investigate the most tolerant cultivar (s) of chickpea to herbicides.

2. To minimize injury of chickpea crop to herbicides.

3. To find out the most suitable herbicides dose applied in chickpea.

.

54

5.2 MATERIALS AND METHODS

5.2.1 Collection of seeds

Chickpea varieties were collected from Ahmad wala Research Station Karak (North West

Frontier Province) Pakistan during August 2005. The seeds were cleaned and sun dried to

minimize the risk of contamination. The varieties tested for tolerance were KC-98,

Sheenghar, Lawaghir, KK-1, KK-2, SL-01-13, SL-02-13, SL-02-20, SL-02-22, SL-02-

29, SL-03-29 and SL-04-29. All the varieties were tested with pre and post emergence

herbicide (pendimethalin and fenoxaprop-p-ethyl).

5.2.2 Seed germination

The experiment was undertaken in pots having 10 cm size, filled with sandy loam soil at

the department of weed science, NWFP, Agricultural University Peshawar Pakistan

during October 2005-06 and 2006-07. Initially, ten seeds were planted in each pot and

after germination, the plants were thinned to 5 plants per pot.

5.2.3 Herbicides application

The herbicides pendimethalin 330E (pre emergence) and fenoxaprop-p-ethyl 75 EW

(post emergence) were tested for tolerance of the above stated cultivars. The doses were

0, 0.41 (½x), 0.82 (1X) and 1.20 (1.5X) and 0, 0.28, 0.56 and 0.90 kg a.i ha-1 respectively

and were sprayed to each pot individually except the untreated check through knapsack

sprayer having jet nozzle when the plants reached 10 cm in height. Two run of the

experiment were undertaken in both the years in the same environmental conditions.

Statistical Model and Data Analysis

The experiment was laid out in completely randomized (CR) design with factorial

arrangements. Experiment was comprised of two replicates. Cultivars assigned to main

plots, herbicides to sub plots and herbicides doses to sub- sub plots. Data were recorded

on fresh and dry biomass of the chickpea cultivars after 4 weeks of herbicides

application. GENSTAT computer software was used for data analysis and mean

separation. The graphical presentation of data was made through MS Excel computer

software.

55

5.3 RESULTS

Tolerance of Chickpea Cultivars to Major Chickpea Herbicides during 2005-07

5.3.1. Fresh biomass (g)

The fresh biomass of chickpea cultivars and herbicides averaged across runs and doses

were differentially affected by herbicides (P<0.001). Fig-5.3.1a indicated that the main

effects of cultivars showed that maximum (13.32 and 13.17 g) fresh biomass was

produced by Sheenghar and KC-98 varieties respectively. While minimum (10.31 g)

fresh biomass was produced by SL-03-29 however, it was statistically at par with SL-02-

29, SL-04-29, SL-02-22, SL-02-20, SL-01-13, SL-02-13.The interaction with

significantly higher fresh weight was observed in KC-98 and Sheenghar cultivars (14.4

and 14.1) respectively. Minimum fresh biomass in interaction was recorded for SL-03-29

(9.29).

Herbicides and dose interaction averaged across years and cultivars differentially

(P<0.001) affected the fresh weight of chickpea cultivars. Figure-5.3.1b exhibited that the

main effects of doses revealed that maximum (15.4 g) fresh biomass was observed at

untreated check followed by ½x and 1X (12.8 and 11.36 g) respectively. Minimum (8.81

g) fresh biomass was recorded at 1.5X. In the interaction of herbicides and doses

fenoxaprop-p-ethyl differentially increased the fresh weight (9.0) at 1.5X as compared to

pendimethalin at the same dose (8.6). While at ½x and 1X doses both herbicides

produced statistically similar fresh biomass.

5.3.2. Dry biomass (g)

Cultivars, herbicides and their interaction had significantly affected the dry biomass of

chickpea cultivars P<0.001 (Figure-5.3.2a). The data indicated that the main effects of

cultivars showed that maximum (4.55 g) dry biomass was recorded for KC-98 variety of

chickpea followed by Sheenghar variety (3.68 g), while all other cultivars produced

moderate dry biomass. The minimum (2.26 g) dry biomass was produced by SL-02-22

however, it was statistically at par with SL-02-29, SL-04-29, SL-02-22, SL-02-20, SL-

01-13, SL-02-13. The data further indicated the nature of this interaction with

56

significantly higher dry weight observed for KC-98 (4.5 and 4.6) at both fenoxaprop-p-

ethyl and pendimethalin respectively followed by Sheenghar variety (4.11 g) at

fenoxaprop-p-ethyl . Minimum dry weight was observed for SL-02-22 (2.2). However,

it was statistically not different to SL-02-22, SL-04-29, SL02-20, SL-01-13.

Herbicides, doses, and their interactions significantly affected the dry weight of chickpea

cultivars (Figure-5.3.2b). The data indicated that the main effects of herbicides doses

showed that maximum (3.45 and 3.40 g) dry biomass was recorded for untreated and ½x

doses respectively followed by 1X dose (3.04 g). While minimum (1.8 g) dry biomass

was observed at 1.5X dose. The data further indicated that dry weight decreased at 1.5X

dose (1.8) each in both the herbicides tested. Maximum dry weight was recorded at

untreated check (3.5) in fenoxaprop-p-ethyl treatment however, it was statistically similar

to the ½x dose in the same herbicides treatment. 1X dose produced statistically similar

results in both the herbicides.

The three way interaction of cultivars x herbicides x doses significantly affected the dry

biomass of chickpea cultivars (Figure-5.3.2c). The data indicated that the main effects of

cultivars showed that maximum (5.5 g) dry biomass was recorded for KC-98 variety of

chickpea followed by Sheenghar variety (4.68 g). While minimum (2.26 g) dry biomass

was produced by SL-02-22 however, it was statistically at par with SL-02-29, SL-04-29,

SL-02-22, SL-02-20, SL-01-13 and SL-02-13. Among the herbicide doses maximum

(3.45 and 3.40 g) dry biomass was recorded for untreated and ½x doses respectively

followed by 1X dose (3.04 g). While minimum (1.8 g) dry biomass was observed at 1.5X

dose. The interaction showed that maximum dry biomass was recorded for KC-98 at ½x

dose in both the pre and post emergence herbicide (5.9 and 5.5 g) respectively. Sheenghar

cultivar produces (5.0 g) dry biomass at ½x dose in fenoxaprop-p-ethyl herbicide.

Minimum dry weight was recorded for SL-02-22 and SL-02-20 (1.2 and 1.0 g) under

fenoaprop-p-ethyl, respectively.

57

0

2

4

6

8

10

12

14

16

KC-98.

KK-1KK-2

Lawaghi r

Sheenghar

SL-01-13

SL-02-13

SL-02-20

SL-02-22

SL-02-29

SL-03-29

SL-04-29

Chickpea cultivars

Fres

h bi

omas

s (g)

fenoxaprop-p-ethyl

pendimethalin

Means 14.17a 12.96ab 11.90c 11.64cd 14.72a 9.95f 10.67e 10.44e 10.29ef 10.18e 10.26e 10.31e

0

2

4

6

8

10

12

14

16

18

0 ½x 1X 1.5X

Herbicide doses

Fres

h bi

omas

s (g)

fenoxaprop-p-ethyl

pendimethalin

Means 15.4a 12.81b 11.36bc 8.81d

Fig-5.3.1a. Fresh biomass as affected by chickpea cultivars and herbicides.

Fig-5.3.1b. Fresh biomass of chickpea as affected by herbicides and doses.

0

1

2

3

4

5

6

KC-98.

KK-1KK-2

Lawaghir

Sheengh

ar

SL-01-13

SL-02-13

SL-02-20

SL-02-22

SL-02-29

SL-03-29

SL-04-29

Chickpea cultivars

Dry

bio

mas

s (g)

fenoxaprop-p-ethyl

pendimethalin

Means 4.5a 3.2b 2.6f 2.8d 2.7de3.68b 2.64ef 2.5f 2.52f 2.543f 2.55f 2.63ef

Fig. 5.3.2a. Dry biomass as affected by chickpea cultivars and herbicides.

58

01234567

0 ½x 1X 1.5X

KC-98

Herbicide doses

Dry

bio

mas

s (g)

fenoxaprop-p-ethyl

pendimethalin

012345

0 ½x 1X 1.5X

KK-1

Herbicide doses

Dry

bio

mas

s (g)

fenoxaprop-p-ethyl

pendimethalin

00.5

11.5

22.5

33.5

0 ½x 1X 1.5X

KK-2

Herbicide doses

Dry

bio

mas

s (g)

fenoxaprop-p-ethyl

pendimethalin

0

0.51

1.5

2

2.53

3.5

4

0 ½x 1X 1.5X

Herbicide doses

Dry

bio

mas

s (g)

fenoxaprop-p-ethyl

pendimethalin

3.45aMeans 3.4a 3.04b 1.8c

Figur-5.3.2b. Dry biomass of chickpea as affected by herbicides and doses.

59

00.5

11.5

22.5

33.5

4

0 ½x 1X 1.5X

Lawaghir

Herbicide doses

Dry

bio

mas

s (g)

fenoxaprop-p-ethyl

pendimethalin

0123456

0 ½x 1X 1.5X

Sheenghar

Herbicide doses

Dry

bio

mas

s (g)

fenoxaprop-p-ethyl

pendimethalin

00.5

11.5

22.5

33.5

4

0 ½x 1X 1.5X

SL-01-13

Herbicide doses

Dry

bio

mas

s (g)

fenoxaprop-p-ethyl

pendimethalin

00.5

11.5

22.5

33.5

4

0 ½x 1X 1.5X

SL-02-13

Herbicide doses

Dry

bio

mas

s (g)

fenoxaprop-p-ethyl

pendimethalin

60

00.5

11.5

22.5

33.5

4

0 ½x 1X 1.5X

SL-04-29

Herbicide doses

Dry

bio

mas

s (g)

fenoxaprop-p-ethyl

pendimethalin

00.5

11.5

22.5

3

0 ½x 1X 1.5X

SL-02-22

Herbicide doses

Dry

bio

mas

s (g)

fenoxaprop-p-ethyl

pendimethalin

00.5

11.5

22.5

33.5

4

0 ½x 1X 1.5X

SL-02-20

Herbicide doses

Dry

bio

mas

s (g)

fenoxaprop-p-ethyl

pendimethalin

00.5

11.5

22.5

33.5

0 ½x 1X 1.5X

SL-03-29.

Herbicides doses

Dry

bio

mas

s (g

)

fenoxprop-p-ethyl

pendimethalin

61

00.5

11.5

22.5

33.5

0 ½x 1X 1.5X

SL-02-29

Herbicide doses

Dry

bio

mas

s (g)

fenoxaprop-p-ethyl

pendimethalin

Fig-5.3.2c. Dry biomass of chickpea cultivars as affected by cultivar x herbicides x doses.

62

5.4. DISCUSSION

For elucidating the tolerance of different chickpea genotypes to herbicides, the instant

studies were undertaken on twelve varieties of chickpea. Two varieties (KC-98 and

Sheenghar) showed maximum tolerance to both the herbicides while the remaining

varieties were susceptible. It was postulated that ½x dose of herbicides produced

adequate results as compared to the 1.5X or 1X dose in case of legumes. Kudsk and

Streibig (1993) recommended ½x doses for keeping good stands of plants, pollution free

environment and other human health hazards. The response of both the herbicidal

treatments to chickpea genotypes were not differential (P< 0.84) regarding fresh weight.

Several studies were conducted on reduced herbicide doses regarding chickpea crop. The

results of Seefeldt et al. (1995) and Kudsk and Mathiassen (2007) showed that herbicides

were the most effective tools for maximizing agronomic parameters in field crops by

reducing weeds infestation. These results indicated that post emergent application of

fenoxaprop-p-ethyl should be the best choice at ½x dose and 1X dose, while

recommended and 1.5X dose of pendimethaline will be effective as pre emergence.

Johnson et al. (2002) reported similar results on herbicides doses and growth relationship

of the crops. Our findings are also in a great conformity with those reported by Bagossi

et al. (2000), Covarelli and Pannacci (2000) and Green and Streibig (1993) who reported

that herbicides with ½x dose are the best tools for weed control depending on species and

situations.

63

CHAPTER-6

Effect of Pre and Post Emergence Herbicides on Asphodelus tenuifolius in Chickpea under Field Conditions

Muhammad Ishfaq Khan and Gul Hassan Department of Weed Science, Faculty of Crop Protection Sciences

NWFP Agricultural University -Peshawar

ABSTRACT

The study aims to determine the effect of pre and post emergence herbicides on A.

tenuifolius and to establish minimum dose of herbicides required for controlling A.

tenuifolius under field conditions. Two experiments were conducted in chickpea during

2005-06 and 2006-07 on farmer’s field in district Lakki Marwat. Five herbicides

pendimethalin (pre-emergence) s-metolachlor (pre-emergence), fenoxaprop-p-ethyl

(post-emergence), MCPA (post-emergence) and isoproturon (post-emergence) with four

different doses (0. , ½x, 1X and 1.5X) were studied in the trials. The experiment was

arranged in a Randomized Complete Block (RCB) design with three replications. All

herbicides except MCPA and isoproturon gave adequate control. MCPA produced

phytotoxic effect on both weed and crop and completely inhibited both crop and weed

growth. Isoproturon was less effective on A. tenuifolius with comparatively less

phytoxicity on crop. Best seed yield was recorded in pre-emergence herbicides (1164 and

1150 kg ha-1) at high dose as compared to fenoxaprop-p-ethyl and isoproturon (1088 and

981.6 kg ha-1) respectively. Next year (2006-2007) again the same herbicides were tested

while MCPA due to its phytotoxicity on crop was replaced by clodinafop propargyl

(post-emergence). Almost similar results were recorded with the only difference of

herbicides clodinafop propargyl. The best seed yield of 1109 kg ha-1 was recorded each

for pendimethalin and s-metolachlor which was however, statistically similar with

fenoxaprop-p-ethyl (1107 kg ha-1). The rest of the herbicides produced comparatively

lower seed yield. Lower (½x) and 1X doses of post emergence herbicides produced good

results as compared to higher (1.5X) dose. Pre emergence herbicides at high (1.5X) dose

are encourage to apply to good economic return.

Key words: chickpea, A.tenuifolius, pre and post emergence herbicides, doses.

64

6.1 INTRODUCTION

Chickpea (C. arietinum L.) is a major food legume and an important source of protein in

many countries in Asia and Africa. This species is the second most consumed and the

third most cultivated grain legume (Dodak et al. 1993). It is cultivated on large scale in

the world; nevertheless, many biotic and abiotic stresses limit the productivity of this

legume viz. leaf diseases, salinity, drought, cold, and micronutrients deficiencies

(Upadhyaya et al. 2001). Several studies are involved in the exploration of stress-resistant

chickpea varieties (ICARDA, 2004). It is an ancient crop and is grown in tropical,

subtropical and temperate regions. Major producers of chickpea include India, Pakistan

and Mexico (Badshah et al. 2003). In India and Pakistan, chickpeas are consumed

locally, and about 56% of the crop is retained by growers. Turkey, Mexico, Iran,

Australia and Canada are the main exporters. Chickpea is valued for its nutritive seeds

with high-protein content, (17–22% and 25.3–28.9%), before and after dehulling,

respectively (Hulse, 1991; Badshah et al. 2003). Chickpea (Cicer arietinum L.), an

annual herbage plant, is the third most important grain legume in the world on the basis

of total grain production (FAO, 1994). In 1980s, hundreds of chickpea varieties were

imported from the International Center for Agricultural Research in the Dry Areas

(ICARDA) and the International Crops Research Institute for the Semi-arid Tropics

(ICRISAT) and have been planted in Gansu, Qinghai and Xinjiang of China (Zhang et

al., 2007).

Weeds are a serious constraint to increased production and easy harvesting in chickpea.

Chickpea, however, is a poor competitor to weeds because of slow growth rate and

limited leaf area development at early stages of crop growth and establishment. Yield

losses due to weed competition vary considerably depending on the level of weed

infestation and weed species prevailing. Nevertheless, almost all values reflect the

seriousness of the weed problem. Yield losses were observed to vary between 40 to 94%

in the Indian subcontinent (ICARDA, 1985; Bhan and Kukula, 1987), between 40 to 75%

in West Asia (ICARDA, 1982a, 1986), 13 to 98% in North Africa (El-Brahli, 1988; Knott

65

and Halila, 1988; ICARDA, 1982, 1986), and 35% in Italy (Calcagno et al. 1987).

Effective weed control may increase yield in chickpea by 17-105% (ICARDA-FSP,

1986).

There are more than 75 weed species that were reported to infest chickpea fields in the

Mediterranean region (Calcagno et al. 1987; El-Brahli, 1988). These species are mostly

dicotyledonous and belong to 26 different families.

Post emergence application of herbicides can be, indeed, substantially reduced if the

“minimum dose requirement for a satisfactory efficacy” (MDRE) is known with respect

to the most common “herbicide-weed species” combinations (Davies et al., 1993, Kudsk,

1989, Onofri et al., 1997; Pannacci and Covarelli, 2003).

Effective pre-planting and soil incorporated (PPI) herbicides include fluchloralin,

oxyfluorfen, trifluralin and triallate. Those effective as pre-emergent herbicides are

alachlor, chlorobromuron, cyanazine, dinoseb amine, methabenzthiazuron, metribuzin,

pronamide, prometryne and terbutryne. Post-emergent herbicides include dinosebacetate,

fluazifop-butyl and fenoxprop-ethyl. Post emergent applications need great care with

respect to stage of growth and air temperature to avoid phytotoxicity (Bhan and Kukula,

1987).

In a series of on-farm trials in northern Syria during 1985/86 chemical weed control (pre-

emergence terbutryne at 2.0 kg a.i. ha-1 and pronamide at 0.5 kg a.i. ha-1) increased yield

by 26% and 6% in winter and spring sowing, respectively, compared to control. Cuscuta

campestris was selectively controlled by pre emergence application of pronamide with

chlorthal dimethyl (Graf et al. 1982).

Some crops are likely to be more amenable than others to the use of reduced herbicide

doses. Kirkland et al. (2000) reported that good crop yields and the highest net returns

could be attained with a 50% herbicide dose in barley but that a 100% herbicide dose was

required to attain the highest yields and net returns in lentil (Lens culinaris L.).

66

Keeping in mind the economic importance of wild onion infestation in chickpea crop the

present studies were conducted with the following objectives:

1. To figure out the most economical herbicide for the control of A. tenuifolius.

2. To test the efficacy of herbicides at varying doses and its effects on crop.

3. To identify the minimum dose requirement of each herbicide studied.

67

6.2 MATERIALS AND METHODS

Experiments were conducted in chickpea on farmer’s field at district Lakki Marwat,

North West Frontier Province, Pakistan during rabi season 2005-06 and 2006-07. The

experiments were laid out in Randomized Complete Block (RCB) design with split plot

arrangements with three replications. The herbicides were assigned to main plots, while

herbicides doses were kept in the sub plots. KC-98 chickpea variety was seeded during

the second week of October, in each year of study. Each sub plot measured 5 x 2 m2. Two

pre-emergence and three post-emergence herbicides each with four doses were included

in the studies. The herbicidal treatments were the pre emergence application of

pendimethalin and s-metolchlor at 0, 0.41 (½x), 0.82 (1X) and 1.20 (1.5X). While the

post emergence herbicides were isoproturon at 0, 2.0 (½x), 4.0 (1X) and 6.0 (1.5X),

fenoxaprop-p-ethyl at 0, 0.47 (½x), 0.94 (1X) and 1.30 (1.5X) and MCPA at 0, 0.28 (½x),

0.56 (1X) and 0.90 (1.5X) and clodinafop propargyl 0, 0.48 (½x), 0.98 (1X) and 1.50

(1.5X) and kg a.i. ha-1. MCPA was replaced by clodinafop propargyl due to its

phytotoxic effects on the crop. Herbicides were sprayed with knapsack sprayer. All the

weeds in the field were uprooted manually except A. tenuifolius.

Data were recorded on the following parameters in either of the field experiments.

6.2.1. Fresh Weed Biomass (kg ha-1)

For fresh weed biomass the plants of A.tenuifolius were collected with the help of

quadrate of 25 x 25 cm2 from each treatment and weighed in kg. three random quadrates

were used in each treatment. The data was subsequently converted to kg ha-1 with the

following formula.

Fresh weight (kg ha-1) = weight in g x 10000 1000 x 0.25 x 0.25

6.2.2. Dry Weed Biomass (kg ha-1)

The wild onion plants in the above quadrats were kept in oven at 65oC for 48 hours and

dry biomass then weighed and subsequently the data were converted to kg ha-1

highlighted as above.

68

6.2.3 Number of chickpea branches plant-1

Ten chickpea plants were randomly selected from each sub plot in the each experiment

and the numbers of branches in each plant were counted and the average numbers of

branches plant-1 were calculated and recorded.

6.2.4. Number of pods plant-1

The seeds were counted in the pods from the above randomly selected 10 plants and

mean grain pod-1 were computed and recorded.

6.2.5. Number of seeds pod-1

Ten plants were randomly selected from each treatment and their grains were counted

and their average was calculated for number of grains pod-1.

6.2.6. 100 seed weight (g)

A random sun dried and clean seeds sample of 100 grains from each treatment was taken

and weight was recorded in gram (g) with the help of electronic balance.

6.2.7. Seed yield (kg ha-1)

For grain yield central two rows were harvested in each plot and the grain yield kg ha-1

was obtained by the following formula:

Grain yield (kg ha-1) = Grain yield (kg) x 10000 Area harvested (m2)

Statistical analysis

The data recorded for each trait was individually subjected to the ANOVA technique by

using MSTATC computer software and the means were separated by using Fisher’s

protected LSD test (Steel and Torrie, 1980).

69

6.3 RESULTS

Effect of Pre and Post Emergence Herbicides on A. tenuifolius in Chickpea under Field Conditions during 2005-06

6.3.1.1. Fresh biomass (kg ha-1)

Analysis of variance of the data showed that herbicides, herbicides doses and their

interaction had significant effect on the fresh weight of A. tenuifolius (Fig-6.3.1.1). The

data exhibited that minimum 4.98 kg ha-1 fresh weight was recorded for MCPA followed

by pendimethalin, s-metolachlor and fenoxaprop-p-ethyl 8.27, 8.42 and 8.57 kg ha-1

respectively. While maximum 11.0 kg ha-1 fresh weight was recorded in untreated check.

Among the doses of herbicides, the lowest 6.41 kg ha-1, fresh biomass was observed for

1.5X dose of herbicides, while maximum 11.61 kg ha-1 fresh weight was recorded in

untreated check. In the interaction of herbicides and doses maximum 11.61 kg ha-1 fresh

weight was observed in untreated check, followed by isoproturon at all the herbicidal

doses while minimum (2.5 kg ha-1) fresh weight in the interaction was observed in MCPA

at high dose which was statistically at par with rest of the doses of the same herbicide.

Pendimethalin, s-metolachlor and fenoxaprop-p-ethyl produced statistically similar

response at 1.5X dose 6.63, 5.91 and 6.23 kg ha-1, respectively.

0

2

4

6

8

10

12

14

pendimethalin s-metolachlor fenoxaprop-p-ethyl MCPA isoproturon

Herbicides and doses

Fres

h bi

omas

s (kg

ha-1

) 0

½x

1X

1.5X

a a a a

bcb b

f

aa

7.70b

b-db b

f

a

c-e e e

f

a

8.28b 8.42b 8.57b 4.98c 11.0a

11.61a

7.28

6.41

Fig-6.3.1.1. Fresh biomass of A.tenuifolius as affected by different herbicides and their doses.

6.3.1.2. Dry biomass (kg ha-1)

Statistical analysis of the data showed that herbicides, doses and their interaction had

significant effect on the dry biomass of A. tenuifolius (Fig-6.3.1.2). The data indicated

70

that lowest (1.82 kg ha-1) dry weight was recorded in MCPA followed by s-metolachlor

2.86 while maximum 4.16 kg ha-1 dry biomass was recorded in untreated check. Among

the herbicides doses minimum (2.20 kg ha-1) dry biomass was recorded at 1.5X dose of

herbicides while maximum (4.16 kg ha-1) dry biomass was recorded in untreated check.

In the interaction of herbicides and doses, maximum (4.16 kg ha-1) dry weight was

observed in untreated check in all the herbicides followed by isoproturon (3.88 kg ha-1) at

1X dose however it was statically at par with rest of the doses of the same herbicide.

While the minimum (1.07 kg ha-1) dry biomass in the interaction was observed in MCPA

which was statistically at par with rest of the doses of the same herbicide. s-metolachlor

declined the dry weight up to 1.69 kg ha-1 followed by the same herbicide at ½x dose

2.65 kg ha-1 however it was statistically at par with pendimethalin and fenoxaprop-p-

ethyl (2.25 and 2.41 kg ha-1) respectively at 1.5X dose.

0

1

2

3

4

5

pendimethalin s-metolachlor fenoxaprop-p-ethyl MCPA isoproturon

Herbicides and doses

Dry

bio

mas

s (k

g ha

-1) 0

½x

1X

1.5X

ff f f f

de efde

h

ab

de decd

h

a-c

fg

ef

h

b-c

3.03bc 2.86c 3.20bMeans

1.82d 3.84a

4.16a

2.64b

2.80b

2.20c

Mea

Fig-6.3.1.2. Dry biomass of A.tenuifolius as affected by different herbicides and their doses. 6.3.1.3. Number of branches plant-1 Analysis of variance of the data showed herbicides, doses and their interaction had

significant effect on branches plant-1 (Fig.6.3.1.3.). The data in figure exhibited that

maximum (8.55 and 8.48 branches plant-1) were observed in the pre emergence

herbicides pendimethalin and s-metolachlor respectively. While minimum (1.76 branches

plant-1) were observed for MCPA followed by isoproturon (7.20 branches plant-1).

Among the herbicides doses maximum (7.32 branches plant-1) were observed at 1X dose

followed by untreated check (7.03). In the interaction of herbicides and doses maximum

(10.17 branches plant-1) were observed in pendimethalin at 1X dose however, it was

statistically at par with the s-metolachlor (9.97 kg ha-1) at the same dose. The minimum

71

0.0 branches plant-1 were observed in MCPA treated plot due to the phytotoxic effects of

the herbicide on the crop.

0

2

4

6

8

10

12

14

pendimethalin s-metolachlor fenoxaprop-p-ethyl MCPA isoproturon

Herbicides and doses

No.

of b

ranc

hes p

lant

-1 0

½x

1X

1.5X

g g gg g

bc bcde

h h h

g

a a b

fgcd de ef fg

Means 8.55a 8.48a 7.96b 1.76d 7.20c

7.03b

6.53c

7.32a

6.28d

Means

Fig-6.3.1.3. No. of branches plant-1 of chickpea as affected by different herbicides and their doses.

6.3.1.4. Number of Pods plant-1

Statistical analysis of the data revealed that herbicides, doses and their interaction had

significant affects on pod plant-1 (Fig.6.3.1.4.). The data showed that the main effects of

herbicides produced highest (37.79 and 37.95 pods plant-1) in pendimethalin and s-

metolachlor respectively while minimum (33.04 pods plant-1) were observed in

isoproturon treated plots. Among doses, maximum (32.73 and 32.35 pods plant-1) were

recorded in untreated and at 1X dose, respectively. While the minimum (28.93 pods

plant-1) were recorded at high dose. In the interaction of herbicides and doses highest

44.30 pods plant-1 were recorded in s-metolachlor at 1X dose however it was statistically

similar with pendimethalin (43.77 pods plant-1) at the same dose. While minimum (7.03

branches plant-1) were recorded in isoproturon at untreated check, however it was

statistically at par with the rest of the doses of the same herbicide. MCPA produced zero

pods due to phytotoxic effects on the crop.

72

0

10

20

30

40

50

60

pendimethalin s-metolachlor fenoxaprop-p-ethyl MCPA isoproturon

Herbicides and doses

No.

of s

eed

pod-

1 0

½x

1X

1.5X

fffff

ggg

c-e c-e e fff

a ab

cdc

de

Means

Means

37.79a 37.95a 36.13b 8.18d 33.04c

32.73a

28.46b

32.35a

28.93b

Fig-6.3.1.4. No. of pods plant-1 of chickpea as affected by different herbicides and their doses.

6.3.1.5. Number of seeds pod-1

Number of seeds pod-1 was also significantly affected by herbicides, doses and their

interaction (Fig-6.3.1.5). The data exhibited that the main affects of herbicides produced

highest (1.50, 1.51 and 1.48 seeds pod-1) by pendimethalin, s-metolachlor and

fenoxaprop-p-ethyl treated plots, respectively. While minimum (1.37 seeds pod-1) was

recorded in isoproturon. Among the doses maximum (1.37 seeds pod-1) was observed in

untreated check followed by 1X dose (1.25). In the interaction of herbicides and doses

maximum (1.70 seeds pod-1) was recoded in s-metolachlor at 1X dose however it was

statistically at par with pendimethalin and fenoxaprop-p-ethyl (1.63 and 1.60) at 1X

doses respectively.

0

0.5

1

1.5

2

2.5

pendimethalin s-metolachlor fenoxaprop-p-ethyl MCPA isoproturon

Herbicides and doses

No.

of s

eed

pod-

1

0

½x

1X

1.5X

efefefefef

ggg

de b-d cdf f d-f

ab a a-cb-d d-f de

Means

Means

1.50a 1.51a 1.48a 0.34c 1.37b

1.37a

1.17c

1.25b

1.17c

Fig-6.3.1.5. No. of seeds pod-1 of chickpea as affected by different herbicides and their doses.

73

6.3.1.6. 100 seed weight (g)

The mean value of 100 seed weight was significantly affected by the herbicides, doses

and their interaction (Fig-6.3.1.6). Among the herbicides maximum 26.96 and 26.82 (g)

seed weight was recorded in the pre-emergence treatment of pendimethalin and s-

metolachlor respectively while, the minimum (23.76 and 24.88 g) 100 seed weight was

observed in isoproturon and fenoxaprop-p-ethyl, respectively. Untreated check produced

highest 24.10 g seed weight while 1.5X dose produced lowest 19.88 (g) seed weight. In

the interaction of herbicides and doses highest 31.90 and 31.43 (g) 100 seed weight was

observed in pendimethalin and s-metolachlor at 1X dose while the minimum 23.33 (g)

seed weight was observed in isoproturon treated plots however, it was statistically at par

with the rest of the doses of the same herbicides. MCPA produce zero seed rate due to

phytotoxic effects on the crop.

0

5

10

15

20

25

30

35

40

pendimethalin s-metolachlor fenoxaprop-p-ethyl MCPA isoproturon

Herbicides and doses

100

grai

n w

eigh

t (g) 0X

½x

1X

1.5X

efefefefef

ggg

bc b-dc-f f

a a

bef

b-f b-ec-f d-f

Means

Means

26.96a 26.87a 24.88b 6.04c 23.76b

24.10a

20.04c

22.79b

19.88c

Fig-6.3.1.6. 100 seed weight (g) of chickpea as affected by different herbicides and their doses. 6.3.1.7. Seed yield (kg ha-1) Seed yield was significantly affected by herbicides, doses and their interaction

(Fig-6.3.1.7.). The data indicated that the main effects of herbicides produced (1164 kg

ha-1) seed yield in pendimethalin treated plots however it was statistically at par with s-

metolachlor (1150.0 kg ha-1) followed by fenoxaprop-p-ethyl (1088.0 kg ha-1) while

minimum (991.6 kg ha-1) yield was recorded in isoproturon and MCPA treated plots.

Among the doses maximum (984.0 kg ha-1) seed yield was recorded in untreated plots

followed by the 1X dose (93.0 kg ha-1) while minimum (910.0 kg ha-1) seed yield was

observed at high dose. In the interaction of herbicides and doses highest (1270.0 and

74

1233.0 kg ha-1) yield was observed in pendimethalin at higher and 1X doses respectively.

While the pre emergence herbicide s-metolachlor paid almost similar response at all the

doses.

0

200

400

600

800

1000

1200

1400

1600

pendimethalin s-metolachlor fenoxaprop-p-ethyl MCPA isoproturon

Herbicides and doses

Seed

yie

ld (k

g ha-1

) 0

½x

1X

1.5X

fffff

ggg

d cd efff

ab bc bca bce

Means

Means

1164.0a 1150a 1088.0a 246.0d 991.6c

984a

886d

930.5b

910.3c

Fig-6.3.1.7. Seed yield kg ha-1 of chickpea as affected by different herbicides and their doses.

75

Effect of Pre and Post Emergence Herbicides on Asphodelus tenuifolius in Chickpea Under Field Conditions during 2006-07

6.3.2.1. Fresh Biomass (kg ha-1)

Herbicides, herbicide doses and their interactions had differentially affected the fresh

biomass of A. tenuifolius (Fig-6.3.2.1). The main effects of herbicides showed that lowest

(9.47 kg ha-1) fresh weight was recorded for pendimethalin however, it was followed by

the s-metolachlor, fenoxaprop-p-ethyl and clodinafop propargyl(9.47, 9.69 and 10.02 kg

ha-1) respectively. While highest (11.80 kg ha-1) fresh weight was recorded in

isoproturon. Among the herbicides doses minimum (8.40 kg ha-1) fresh weight was

recorded at high dose. While maximum (12.50 kg ha-1) fresh weight was recorded in

untreated check. In the interaction of herbicides and doses minimum (7.05 kg ha-1) fresh

weight was observed in s-metolachlor at 1.5X dose however it was statistically at par

with pendimethalin, fenoxaprop-p-ethyl and clodinafop propargyl at 1.5X dose and

pendimethalin at 1X dose as well. While maximum (12.63 kg ha-1) fresh weight was

observed in untreated check in all the herbicides followed by isoproturon at all the

herbicidal doses.

0

2

4

6

8

10

12

14

pendimethalin s-matolachlor fenoxaprop-p-ethyl clodinafop propargyl isoproturon

Herbicides and doses

Fres

h bi

omas

s (kg

ha-

1)

0

½x

1X

1.5X

a a a a a

c-ed-f d-f

cd c-e

f

cd cd

f

cdbcef

aab

a

Means

Means 9.47b 9.47b 9.69b 10.02b 11.80a

12.50a

10.0b

9.50b

8.40c

Fig-6.3.2.1. Fresh biomass of A. tenuifolius as affected by different herbicides and their doses.

6.3.2.2. Dry Biomass (kg ha-1)

Dry weed biomass of A. tenuifolius was also differentially affected by herbicides,

herbicides doses and their interaction (Fig-6.3.2.2). The data exhibited that among the

herbicides, the lowest (3.43 kg ha-1) dry weight was recorded in s-metolachlor followed

76

by pendimethalin (3.49 kg ha-1) however, it was statistically at par with s-metolachlor

(3.43) and fenoxprop-p-ethyl (3.70) which in turn was statistically comparable with

clodinafop propargyl(4.18), while maximum (4.44 kg ha-1) dry weight was recorded in

isoproturon treated plots. The main effects of herbicides showed that the minimum (3.09

kg ha-1) dry weight was recorded at high dose. ½x and 1X doses showed similar response

statistically for dry weight of A. tenuifolius. While highest dry weight was recorded in

untreated check. In the interaction of herbicides and doses minimum (2.50 kg ha-1) dry

weight was observed in s-metolachlor followed by pendimethalin (2.66) and fenoxaprop-

p-ethyl (2.97) at 1.5X doses. The herbicides s-metolachlor, pendimethalin and

fenoxaprop-p-ethyl were non significant among themselves, best results at 1.5X dose was

achieved in case of dry weight of A. tenuifolius. The maximum (4.89 kg ha-1) dry weight

was observed in untreated check in all the herbicides followed by isoproturon (4.50 kg

ha-1) at ½x dose however it was statically at par with rest of the doses of the same

herbicide (Fig 5.3.2.2).

0

1

2

3

4

5

6

pendimethalin s-matolachlor fenoxaprop-p-ethyl clodinafop propargyl isoproturon

Herbicides and doses

Dry

bio

mas

s (kg

ha-1

)

0

½x

1X

1.5X

Means

Meansaaaaa

de d-ffg

e-g de

g

de cde-g

b b

d-f

abb bc

3.49c 3.43c 3.70bc 4.18ab 4.44a

4.88a

3.66b

3.80b

3.09c

Fig-6.3.2.2. Dry biomass of A.tenuifolius as affected by different herbicides and their doses. 6.3.2.3. Number of Branches plant-1

Analysis of variance of the data showed that herbicide, herbicides doses and their

interaction had the significant effect on No. of branches plant-1 (Fig-6.3.2.3). The data

exhibited that among the herbicides the highest (7.97 and 7.38) branches plant-1 were

observed in the pre emergence herbicides s-metolachlor and pendimethalin respectively.

77

While minimum 6.87 and 7.23 branches plant was observed in post emergence herbicides

viz. isoproturon and topic. The main affects of herbicides showed that maximum (8.06)

branches plant-1 was observed at 1X dose followed by ½x and 1.5X doses (7.47 and 7.23)

respectively. While minimum (6.97) branches plant-1 were observed in untreated check.

In the interaction of herbicides and doses maximum (9.20) branches plant-1 was observed

in s-metolachlor at 1X dose followed by fenoxaprop-p-ethyl at 1X dose (8.53). The

minimum (6.53) branches plant-1 was observed in isoproturon at ½x dose however it was

statistically at par with all the untreated checks.

0

2

4

6

8

10

12

pendimethalin s-matolachlor fenoxaprop-p-ethyl clodinafop propargyl isoproturon

Herbicides and doses

No.

of b

ranc

hes p

lant

-1

0

½x

1X

1.5X

e-ge-ge-ge-ge-gb-f

b-e bcg g

c-g

aab

b-dd-gc-f b-f

c-g fg fg

Means

Means

7.38a-c 7.97a 7.73ab 7.23bc 6.84c

6.97c

4.47b

8.06a

7.23bc

Fig-6.3.2.3. No. of branches plant-1 of chickpea as affected by different herbicides and their doses.

6.3.2.4. Number of Pods Plant-1

No. of pods plant-1 were also differentially affected by herbicides, doses and their

interaction (Fig-6.3.2.4). The data Fig showed that among the herbicides, highest (37.48

and 37.34) pods plant-1 were recorded in pendimethalin and s-metolachlor respectively

while minimum (32.38) pods plant-1 were observed in isoproturon treated plots. The main

effects of herbicides showed that maximum (39.85) pods plant-1 were recorded at 1X

dose which were statistically similar with the ½x and 1.5X doses while the minimum

(31.83) pods plant-1 were observed in untreated check. In the interaction of herbicides and

doses the highest (43.90) pods plant-1 were recorded in pendimethalin at 1X dose

however it was statistically similar with s-metolachlor (42.87) pods plant-1 at the same

dose.

78

05

101520253035404550

pendimethalin s-matolachlor fenoxaprop-p-ethyl clodinafop propargyl isoproturon

Herbicides and doses

No.

of p

ods p

lant

-1

0X

½x

1X

1.5X

hhhhhd d-f e-f

gh h

aab bc

ghde cd

fg gh gh

Means

Means

37.48a 37.34a 35.62a 34.31c 32.38d

31.83c

34.95b

39.85a

35,08b

Fig-6.3.2.4. No. of Pods plant-1 of chickpea as affected by different herbicides and their doses.

6.3.2.5. Number of Seeds Pod-1

Number of seeds pod-1 was significantly affected by different herbicidal treatment and

doses (Fig-6.3.2.5). The data exhibited that the main effects of herbicides showed that

highest (1.38, 1.38, 1.38 and 1.33) pods were observed in pendimethalin, s-metolachlor,

fenoxaprop-p-ethyl and clodinafop propargyl as compared to the minimum (1.27) seeds

pod-1 in isoproturon. Among the herbicides rates maximum (1.43) seeds pod-1) was

observed at 1X dose followed by 1.5X dose (1.35). While the lowest seeds pod-1 were

observed in untreated check. In the interaction of herbicides and doses highest pod

formation were observed at 1X dose of pendimethalin and s-metolachlor followed by

fenoxaprop-p-ethyl while the minimum pods were recorded in isoproturon both at ½x and

1X doses.

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

pendimethalin s-matolachlor fenoxaprop-p-ethyl clodinafop propargyl isoproturon

Herbicides and doses

No.

of s

eeds

pod

-1

0

½x

1X

1.5X

dedededede c-e c-e bc b-de

aa ab bc

ebc b-d bc

de c-eMeans

Means 1.38a 1.38a1.38a 1.33b 1.27b

1.27c

1.33b

1.43a

1.35b

z

Fig-6.3.2.5. No. of seed pod-1 of chickpea as affected different herbicides and their doses.

79

6.3.2.6. 100 Seed weight (g)

The 100 seed weight was significantly affected by the herbicides, herbicide doses and

their interaction (Fig-6.3.2.6). Among the herbicides, maximum (26.96 and 26.31 g) seed

weight was recorded in the pre-emergence treatment of s-metolachlor and pendimethalin

respectively while, the minimum (22.18 and 23.14 g) 100 seed weight was observed in

clodinafop propargyl and isoproturon respectively. Among the herbicides doses

maximum (26.41 g) weight was recorded at 1X dose while rest of the herbicide doses

produced statistically similar results. In the interaction of herbicides and doses the highest

(31.18 g) 100 seed weight was observed in pendimethalin at 1X dose while the minimum

(21.55, 21.70 and 21.85 g) seed weight was observed in clodinafop propargyl at all

herbicidal doses treated plots however, it was statistically at par with the all herbicides

doses of isoproturon and all doses of fenoxaprop-p-ethyl except the 1X dose

0

5

10

15

20

25

30

35

pendimethalin s-matolachlor fenoxaprop-p-ethyl clodinafop propargyl isoproturon

Herbicides and doses

100

seed

wei

ght (

g)

0

½x

1X

1.5X

c-ec-ec-ec-ec-ec

b

c-e e de

aab

c

edecd cd c-e

e deMeans

Means 26.31a 26.96a 24.14b 22.18c 23.14bc

23.61b

24.51b

26.41a

23.61b

Fig-6.3.2.6. 100 seed weight (g) of chickpea as affected by different herbicides and their doses.

6.3.2.7. Seed yield (kg ha-1)

Seed yield was also differentially affected by herbicides, herbicide doses and their

interaction (Fig-6.3.2.7). The data indicated that among the herbicides, highest (1109 kg

ha-1) seed yield was recorded in pendimethalin and s-metolachlor treated plots, followed

by fenoxaprop-p-ethyl (104.52 kg ha-1) while the minimum (943.4 kg ha-1) yield was

recorded in isoproturon and clodinafop propargyl(955.3). The main effects of herbicides

doses indicated that maximum (1111 kg ha-1) seed yield was recorded at 1X dose

however it was statistically at par with ½x doses of the herbicides (1043) while minimum

(931.3 kg ha-1) seed yield was observed in untreated check. In the interaction of

80

herbicides and doses, highest (1175 kg ha-1) yield was observed in s-metolachlor however

it was statistically at par with pendimethalin at 1.5X dose.

0

200

400

600

800

1000

1200

1400

pendimethalin s-matolachlor fenoxaprop-p-ethyl clodinafop propargyl isoproturon

Herbicides and doses

Seed

yie

ld (k

g ha-1

)

0

½x

1X

1.5X

eeeee

b-e a-ec-e c-e

e

ab a-ca-e

b-ede

a-e a-d

e ee

1109a 1109a 943.4c

931.3c

1043b

1111a

Means

Means

1008bc

1004.5b 982bc

Fig-6.3.2.7. Seed yield kg ha-1 of chickpea as affected by different herbicides and their doses.

81

6.4 DISCUSSION

Herbicides, doses, and their interaction affected almost all the parameters during either

year of the studies. During the first year, MCPA reduced the fresh and dry biomass more

than did other herbicides in the studies. This herbicide, however, also showed phytotoxic

effect on the crop. So MCPA was substituted with clodinafop propargyl for the year

2006-07. Pre-emergence herbicides pendimethalin and s-metolachlor and the post

emergence herbicide fenoxaprop-p-ethyl reduce the fresh weed biomass significantly of

the target weed without any injury to the crop. In case of fresh weed biomass

pendimethalin, s-metolachlor and fenoxaprop-p-ethyl were the best without injury to the

crop. Pendimethalin, s-metolachlor and fenoxaprop-p-ethyl significantly declined the dry

weed biomass at lower dose which has an implication for the farmers that to use lower

than label dose will be of immense help in minimizing the environmental pollution as

well as having economic benefit. Malik et al. (2003) also reported that herbicides

decreased the dry weight significantly. These results are also in a great analogy with the

work of Iqbal et al. (1991) and Poonia et al. (1993) who were also of the view that

herbicides decreased the weed dry weight significantly. No. of branches plant-1 were also

significantly affected by pendimethalin s-metolachlor and fenoxprop-p-ethyl. Similarly

No. of pods plant-1 were also significantly increased by herbicides at recommended doses

and higher doses as compared to the untreated check. Pendimethalin, s-metolachlor and

fenoxprop-p-ethyl were the best treatments for increasing the pods plant-1. The probable

reason for the best performance of these herbicides is their efficacious control of A.

tenuifolius, while the possible reason for minimum pods plant-1 in weedy check plots

might be due to higher competition with wild onion. Quite analogous results were

reported by Althahi (1994) who stated that weeds reduce pods plant-1 in chickpea. 100

grain weight (g) and grain yield (kg ha-1) were also increased by the pre-emergence

herbicides and the post emergence fenoxaprop-p-ethyl. The 100 seed weight and seed

yield in these treatment were probably due to maximum inhibition of wild onion

consequently the crop was flourished and efficiently utilized all the available resources.

82

In both the experiments during the two years studies pre emergence herbicides 1X and

1.5X dose produced best results as compared to the lower dose while in post emergence

herbicides ½x and 1X dose produced best results as compared to 1.5X dose. 1.5X dose of

herbicides showed phytotoxic effects on crops and reduced the yield in both the

experiments.

83

CHAPTER-7

Effect of Some Herbicides and Their Doses at Different Growth Stages of Asphodelus tenuifolius under Field Conditions.

Muhammad Ishfaq Khan and Gul Hassan

Department of Weed Science, Faculty of Crop Protection Sciences NWFP Agricultural University Peshawar-Pakistan

ABSTRACT

Herbicides are an integral part of farmer’s cultural practices world-wide. To maximize

yield and yield components of chickpea, herbicides and herbicide doses were tested

against A. tenuifolius growth stages in chickpea for two growing seasons during 2005-06

and 2006-07 at district Lakki Marwat, North West Frontier Province Pakistan. Two

herbicides (isoproturon and fenoxaprop-p-ethyl) with four doses (0, ½x, 1X, and 1.5X)

and two growth stages (2 leaf and 4 leaf) were evaluated in the studies. The experiment

was arranged in a Randomized Complete Block Design with split plot arrangement

having three replications. Growth stages were assigned to main plots, herbicides to sub

plots and herbicides rates to sub-sub plots. Growth stages and herbicides differentially

affected the seed yield (kg ha-1) of chickpea during 2006-07. The interaction of herbicides

and growth stages showed that maximum (1124) grain yield was achieved from

fenoxprop-p-ethyl at 2 leaf stage. While minimum (943.4) seed yield was observed in

isoproturon at the same growth stage of wild onion. Statistically similar results were

recorded for 4 leaf stage to either of the herbicide. Fenoxaprop-p-ethyl produced better

results at the 1X rate by providing (1114 kg ha-1) seed yield in 2005-06 and 1098 in 2006-

07 as compared to untreated check (988.6, 979.6 kg ha-1) in 2005-06 and 2006-07

respectively. 2 leaf stages was more susceptible to fenoxaprop-p-ethyl by providing good

yield as compared to 4 leaf stage of wild onion.

Key words: Herbicides, doses, growth stages, A. tenuifolius, Chickpea.

84

7.1 INTRODUCTION

Weeds are a serious constraint to increased production and easy harvesting in chickpea.

Chickpea, however, is a poor competitor to weeds because of slow growth rate and

limited leaf area development at early stages of crop growth and establishment. Yield

losses due to weed competition vary considerably depending on the level of weed

infestation and weed species prevailing. Nevertheless, almost all values reflect the

seriousness of the weed problem. Yield losses were observed to vary between 40 to 94%

in the Indian subcontinent (ICARDA, 1985).

Among weeds, wild onion (A. tenuifolius.) is a notorious weed of sandy soils of Indo-Pak

sub-continent (Mishra et al., 2006). The same weed was found most dangerous to the

chickpea growers in the sandy Districts of North West Frontier Province (NWFP) viz.

Karak, Lakki Marwat and parts of Dera Ismail Khan Pakistan. In the Punjab-Pakistan, it

is the worst competitor with rabi crops in Mianwali, Bhakkar, Jhang and Layyah and

caused huge losses to the chickpea crop in the sandy zone of Pakistan (Sultan and Nasir

2003).

Due to lack of knowledge of non chemical weed management our farmers only rely on

chemical weed control. Research has shown that competitive crop production practices

can contribute to the development of more sustainable weed management systems

(Mohler 2002). Aamil et al. 2004 reported the effects of isoproturon, fluchloralin and 2,

4-D (0, 1000, 5000 and 10, 000 µg ml-1) on chickpea rhizobia, chickpea-Rhizobium

symbiosis, and yields, N content and photosynthetic pigments of chickpea (cv. BG-256)

were studied. Higher concentrations of these herbicides inhibited the growth of the root

nodule bacterium (Mesorhizobium ciceri) in vitro. The herbicides applied at 2-fold the

recommended rates (TF) adversely affected the health, photosynthetic pigments, and N

content of chickpea. The normal and TF rates of the herbicides except fluchloralin TF

increased the seed yield of chickpea. Indeed, reduced doses of tralkoxydim

(Bells et al., 2000) or imazamethabenz (Wille et al., 1998) were more efficacious at low

wild oat densities than at high wild oat densities. Dieleman et al., 1999 also reported that

herbicide efficacy on velvetleaf and common sunflower (Helianthus annuus L.) was

85

greater at low than at high weed densities. Thus, any crop production practice that

reduces weed populations over time is important to the successful use of reduced

herbicide doses. Some crops are likely to be more amenable than others to the use of

reduced herbicide doses. Kirkland et al. (2000) reported that good crop yields and the

highest net returns could be attained with a 50% herbicide dose in barley but that a 100%

herbicide dose was required to attain the highest yields and net returns in lentil (Lens

culinaris L.).

Promising ways to minimize herbicide consumption include the use of low doses

(Zoschke, 1994). However, as the surviving weeds will be able to set seed and, when

incorporated to the seed bank, weed populations may increase in the following years, the

effective herbicide dose must be precisely known. Weed species vary in their

susceptibility to herbicides and there is growing concern due to the increase of species

difficult to control with herbicides. Perennial weeds are difficult to control because there

are few selective herbicides and the non-selective ones require high doses or multiple

applications and usually require a combination of herbicides and cultural practices.

Furthermore, as weeds increase in size, they become less susceptible to herbicides

(Devlin et al., 1991, Klingaman et al., 1991, Blackshaw and Harker, 1997). Weed size

may influence the performance of reduced glyphosate rates (Vanlieshout and Loux,

2000). Although the effect of weed species type and plant growth stage on herbicide

efficacy is widely known, the minimum reduced dose that controls weeds effectively has

seldom been determined (Puricelli and Tuesca, 2006).

Keeping in view the importance of A. tenuifolius the present studies were conducted with

the following objectives:

1. To know about the most susceptible growth stages under field conditions

2. To investigate the most suitable and economical herbicides dose for

A. tenuifolius.

3. To minimize the injury of chickpea to herbicides by applying reduced doses.

86

7.2 MATERIALS AND METHODS

Efficacy of different herbicides doses at various growth stages of A. tenuifolius was

investigated under field conditions 2005-06 and 2006-07 on farmer’s field in district

Lakki Marwat. Field trials were comprised of two post emergence herbicides each with

four doses viz. isoproturon at 0, 2.0 (½x), 4.0 (1X) and 6.0 (1.5X) and fenoxaprop-p-ethyl

at 0, 0.47 (½x), 0.94 (1X) and 1.30 (1.5X) kg a.i ha-1 were included in the trials. Growth

stages were assigned to main-plots, herbicides to the sub plots and herbicides doses to the

sub sub plots. Herbicides were sprayed with knapsack spryaer.KC-98 chickpea variety

was seeded during the second week of October, in each year of study. Each sub-sub plot

measured 5 x 2 m2. Row-row distance was kept at 40 cm uniformly with five rows in each

treatment. Herbicides were applied at two growth stages of wild onion viz. 2 leaf and 4

leaf stages.

Data were recorded on the following parameters (Detail of the treatments already

mentioned in the Materials and Methods in section 5.2)

7.2.1. Fresh Biomass (kg ha-1)

7.2.2. Dry Biomass (kg ha-1)

7.2.3 Number of chickpea branches plant-1

7.2.4. Number of pods plant-1

7.2.5. Number of seeds pod-1

7.2.6. 100 seed weight (g)

7.2.7. Seed yield (kg ha-1)

Statistical analysis

The data recorded for each trait was individually subjected to the ANOVA technique by

using MSTATC computer software and the means were separated by using Fisher’s

protected LSD test (Steel and Torrie, 1980).

87

0

5

10

15

20

25

2 leaf 4 leaf

Growth stage

Fres

h bi

omas

s (kg

ha-1

)

fenoxaprop-p-ethyl

isoproturond

cb

a

7.3 RESULTS

Effect of Some Herbicides and Their Doses at Different Growth Stages of A. tenuifolius Under Field Conditions 2005-06.

7.3.1.1. Fresh (kg ha-1)

Analysis of variance of the data showed that growth stages, herbicides and their

interaction differentially affected fresh biomass of A. tenuifolius (Fig-7.3.1.1a). The data

indicated that the minimum (8.56) fresh biomass was observed in fenoxaprop-p-ethyl at

two leaf stage followed by the same herbicide at 4 leaf growth stage of wild onion. While

maximum (17.78) fresh weed biomass was recorded in isoproturon treated plots at four

leaf stage.

Fig-7.3.1.1a. Fresh biomass of A. tenuifolius as affected by the interaction of herbicides x growth stages.

Herbicides doses and growth stages differentially affected the fresh biomass of A.

tenuifolius (Fig-7.3.1.1b). The data indicated that minimum (8.51) fresh weight was

recorded at 1.5X dose at two leaf stage, which however was statistically at par with all

other doses except the untreated check at same growth stage. While maximum (19.10)

fresh weight was observed in untreated plot at four leaf stage. The interaction of growth

stages with herbicides indicated that minimum (10.50) fresh weight was recorded at 1.5X

dose of herbicide. While 4 leaf stage produced maximum (15.5) fresh weight in untreated

check.

88

0

5

10

15

20

25

0 ½x 1X 1.5X

Herbicides doses

Fres

h bi

omas

s (k

g ha

-1)

2 leaf

4 leaf

cd

a

de

b

de

ab

ce

Fig-7.3.1.1b Fresh biomass of A. tenuifolius as affected by the interaction of herbicides doses x growth stages.

Fresh biomass of A. tenuifolius was differentially affected by herbicides, herbicides doses

and their interaction (Fig-7.3.1.1c). The data exhibited that the main effects of herbicides

doses showed that minimum (10.50 kg ha-1) fresh weed biomass was achieved from the

1.5X dose of the herbicides. While maximum (15.35 kg ha-1) fresh weed biomass was

obtained from the untreated check however it was statistically at par with the 1X dose of

the herbicides. While, in the interaction of herbicides and doses highest (16.60) fresh

weight was observed in isoproturon at 1X dose which was statistically similar with the

same herbicide at ½x dose and the untreated check. The minimum (7.75 kg ha-1) fresh

weight was observed in fenoxaprop-p-ethyl at 1.5X dose.

0

5

10

15

20

0 ½x 1X 1.5X

Herbicides doses

Fres

h bi

omas

s (kg

ha-1

)

fenoxaprop-p-ethyl

isoproturon

abab

c abc

a

d

bc

15.35a 13.03b 13.72ab 10.50cMeans

Fig-7.3.1.1c. Fresh biomass of A. tenuifolius as affected by the interaction of herbicides x doses.

89

7.3.1.2. Dry biomass (kg ha-1)

Statistical analysis of the data showed that the interaction of herbicides and growth stages

differentially affected the dry weed biomass of A. tenuifolius (Fig-7.3.1.2a). The data

indicated that lowest (3.20 kg ha-1) dry weight was observed in fenoxaprop-p-ethyl at two

leaf stage. While highest (6.92 kg ha-1) dry weigh was recorded in isoproturon treated

plots at four leaf stage. It was however, at with the isoproturon at the same growth stage.

0

2

4

6

8

10

2 leaf 4 leaf

Growth stages

Dry

bio

mas

s (kg

ha-1

)

fenoxaprop-p-ethyl

Isoproturonc

cb

a

Fig-7.3.1.2a. Dry biomass of A. tenuifolius as affected by the interaction of herbicides x growth stages.

Dry biomass was also significantly affected by herbicides and herbicides doses

(Fig-7.3.1.2b). The herbicides doses showed that minimum (3.89) dry weed biomass was

achieved at 1.5X dose of the herbicide. While maximum (5.73) dry biomass was obtained

from the untreated check. In the interaction of herbicides and doses minimum (2.82) dry

weed biomass was observed in fenoxaprop-p-ethyl treated plots at 1.5X dose. While,

highest (5.57, 5.34 and 5.33) dry biomass was recorded in isoproturon treated plots at

untreated, and ½x dose respectively.

90

0

1

2

3

4

5

6

7

0 ½x 1X 1.5X

Herbicides doses

Dry

bio

mas

s (kg

ha-1

)

fenoxaprop-p-ethyl

isoproturon

a

ab

cdab

e

bcd

bc

5.73aMeans 4.46b 4.57b 3.89c

Fig-7.3.1.2b Dry biomass of A. tenuifolius as affected by the interaction of herbicides x doses.

7.3.1.3. No. of branches plant-1

Analysis of variance of the data reveals that herbicides and herbicides doses had

significantly affected the No. of branches plant-1 (Fig-7.3.1.3). The maximum (8.30)

branches plant-1 were obtained at 1.5X dose of the herbicide followed by ½x dose (7.70).

In the interactions of herbicides and doses, the highest (9.0) branches plant-1 were

recorded in fenoxaprop-p-ethyl treated plots at 1X dose followed by the same herbicide at

½x dose (8.25). Minimum (7.03) branches plant-1 were observed in untreated plots in

both the herbicides under studies. However, it was statistically at par with isoproturon at

½x and 1.5X doses.

0

2

4

6

8

10

0 ½x 1X 1.5X

Herbicide doses

No.

of b

ranc

hes p

lant

-1

fenoxaprop-p-ethyl

isoproturon

ddb

d

a

cc

d

7.03cMeans 7.70b 8.30a 7.46bc

Fig- 7.3.1.3. No. of branches plant-1 of chickpea as affected by the interaction of herbicides and herbicide doses.

91

7.3.1.4. No. of pods plant-1

Statistical analysis of the data revealed that herbicides, growth stages, herbicides doses

and their interactions differentially affected No. of pods plant-1 (Fig-7.3.1.4). The

maximum (36.67) pods plant-1 was obtained at 1X dose of the herbicide fenoxaprop-p-

ethyl while minimum (30.43) pods plant-1 were recorded in untreated check. In the

interaction of herbicides, herbicide doses and growth stages highest (45.23) pods plant-1

were observed at four leaf stage in the fenoxaprop-p-ethyl herbicide at 1X dose while

lowest (27.73) pods plant-1 were observed at four leaf stage in the isoproturon treated

plots at 1X dose however, it was statistically at par with the rest of the doses of the same

herbicides.

0

10

20

30

40

50

0 ½x X 1.5X 0 1/2X X 1.5X

fenoxaprop-p-ethyl isoproturon

Herbicides and doses

No.

of p

ods p

lant

-1

2 Leaf

4 Leaf

e fd

c ba

d cde f e f e

f e f

Means

Fig-7.3.1.4. No. of pods plant-1 of chickpea as affected by the interaction of herbicides x doses x growth stages.

7.3.1.5. No. of seeds pod-1

No. of seeds pod-1 were also differentially affected by the herbicides and herbicide doses

(Fig-7.3.1.5.). The main effects of herbicides doses indicated that maximum (1.54) seeds

pod-1 were obtained at 1X while minimum (1.38) seed pod-1 were observed in untreated

check. In the interaction of herbicides and doses, the highest (1.667) seeds pod-1 were

recorded in fenoxaprop-p-ethyl at 1X dose followed by the ½x dose of the same herbicide

(1.517). The lowest (1.38) value in the interaction was observed in untreated check in

both the herbicides.

92

0

0.5

1

1.5

2

0 ½x 1X 1.5X

Herbicides doses

No.

of s

eed

pod-1

fenoxaprop-p-ethyl

isoproturon

eeb

c-ea

debc b-d

Means 1.47b1.38c 1.54a 1.48b

Fig-7.3.1.5. No. of seed pod-1 of chickpea as affected by the interaction of herbicides x doses.

7.3.1.6. 100 seed weight (g)

Analysis of variance of the data revealed that herbicides and herbicide doses

differentially affected 100 seed weight (Fig-7.3.1.6). The main effects of herbicides doses

showed that maximum (26.40) 100 seed weight was recorded at 1X dose followed by rest

of the doses which gave statistically similar results. In the interaction of herbicides and

doses, highest (29.02) 100 seed weight was observed at 1X dose in fenoxaprop-p-ethyl

treated plots while the lowest (23.36) 100 seed weight was recorded in isoproturon at

1.5X dose however, it was statistically at par with rest of the doses of isoproturon as well

as with the untreated check.

0

5

10

15

20

25

30

35

0 ½x 1X 1.5X

Herbicide doses

100

seed

wei

ght (

g)

fenoxaprop-p-ethyl

isoproturon

bb bba

b bb

Means 24.72b 24.0b 26.40a 24.6b

Fig-7.3.1.6. 100 seed weight of chickpea as affected by the interaction of herbicides x herbicide doses.

93

7.3.1.7. Seed yield (kg ha-1)

Analysis of variance of he data revealed that herbicides and herbicides doses

differentially affected the seed yield of chickpea (Fig-7.3.1.7). The main effects of

herbicides doses exhibited that maximum (1114 kg ha-1) seed yield was observed at 1X

dose followed by ½x and 1.5X doses of herbicides while minimum (988.6 kg ha-1) seed

yield was recorded in untreated check. In the interaction of herbicides and doses

maximum (1213 kg ha-1) seed yield was observed at 1X dose of fenoxaprop-p-ethyl

followed by ½x and 1.5X dose of the same herbicide while minimum (1004 kg ha-1) yield

of chickpea was observed at ½x dose of isoproturon however it was statistically at par

with untreated check of fenoxaprop-p-ethyl and the rest of the doses of the same

herbicide.

0200

400600

8001000

12001400

0 ½x 1X 1.5X

Herbicide doses

Seed

yie

ld (k

g ha-1

)

fenoxaprop-p-ethyl

isoproturon

ccb

ca

cb

c

Means 988.6c 1055.0b 1114.0a 1042.0b

Fig-7.3.1.7. Seed yield (kg ha-1) of chickpea as affected by the interaction of herbicide x doses.

94

Effect of Some Herbicides and Their Doses at Different Growth Stages of A. tenuifolius Under Field Conditions 2006-07.

7.3.2.1. Fresh biomass (kg ha-1)

Analysis of variance of the data showed that the fresh biomass of A. tenuifolius was

significantly affected by the herbicides, doses and their interaction (Fig-7.3.2.1a). The

data showed that among the herbicides doses, minimum fresh biomass was recorded at

1.5X dose of herbicides while maximum (14.90) fresh biomass was observed in untreated

treatment. Both ½x and 1X doses produced the same fresh biomass. The interaction

showed that minimum (7.85) fresh weight was observed at 1.5X dose of fenoxaprop-p-

ethyl followed by the same herbicide at 1X dose (10.48). While maximum (14.90 g) fresh

biomass was recorded at untreated check.

02468

1012141618

0 ½x 1X 1.5X

Herbicides doses

Fres

h bi

omas

s (kg

ha-1

)

fenoxaprop-p-ethyl

isoproturon

aacd

ab

da

e

bc

Means 12.91b14.90a 12.64b 10.30c

Fig-7.3.2.1a. Fresh biomass of A. tenuifolius as affected by the interaction of herbicides x dose

Growth stages, herbicides and their interaction differentially affected fresh weed biomass

of A. tenuifolius (Fig-7.3.2.1b). The figure quantifies the nature of this interaction that

minimum (9.67) fresh weigh was recorded in fenoxaprop-p-ethyl at 2 leaf stage. While

maximum (16.39) fresh biomass was observed in isoproturon treatment at 4 leaf stage.

95

0

5

10

15

20

2 leaf 4 leaf

Growth stages

Fres

h bi

omas

s (kg

ha

-1) fenoxaprop-p-ethyl

isoproturon

cb

b

a

Fig-7.3.2.1b. Fresh biomass of A. tenuifolius as affected by the interaction of herbicides x growth stages

Statistical analysis of the data further revealed that growth stages and herbicide doses had

significantly affected the fresh biomass of A. tenuifolius (Fig-7.3.2.1c). The data showed

that minimum (9.38) fresh weight was observed at 1.5X dose of herbicides at 2 leaf stage,

however, it was statistically at par with ½x and 1X dose at the same growth stage.

Maximum (17.38) fresh weight was recorded in untreated check at 4 leaf stage.

0

2

4

6

8

10

12

14

16

18

20

0 ½x 1X 1.5X

Herbicides doses

Fres

h bi

omas

s (kg

ha-

1)

2 leaf

4 leaf

c

a

de

b

d

b

e

cd

Means 12.91b14.90a 12.64b 10.30c

Fig-7.3.2.1c. Fresh biomass of A. tenuifolius as affected by the interaction of herbicides doses x growth stages.

96

7.3.2.2. Dry biomass (kg ha-1)

Growth stages and herbicides differentially affect the dry weight of A. tenuifolius

(Fig-7.3.2.2a). The data showed that minimum (3.91) dry biomass was observed at 2 leaf

stage in fenoxaprop-p-ethyl treatment, however it was statistically at par with isoproturon

treatment at 4 leaf stage. Maximum (6.52) dry biomass was recorded at 4 leaf stage in

isoproturon.

012345678

2 leaf 4 leaf

Growth stages

Dry

bio

mas

(kg

ha-1)

fenoxaprop-p-ethyl

isoproturon

cbc b

a

Fig-7.3.2.2a Dry biomass of A. tenuifolius as affected by the interaction of herbicides x growth stages.

Dry biomass was also differentially affected by herbicides doses and growth stages and

their interaction (Fig-7.3.2.2b). The main effects of herbicides exhibited that minimum

(3.97) dry weight was observed at 1.5X dose of herbicides. ½x and 1X dose produced

statistically similar results. Maximum (6.18) dry biomass was recorded in untreated

check. In the interaction of herbicides and growth stages, minimum (3.56 and 3.98) dry

weight was observed 1.5X and ½x dose at 2 leaf stage respectively. However, it was

statistically at par with 1X dose at same growth stage. While maximum (7.47) dry

biomass was recorded in untreated check at 4 leaf stage.

97

0

2

4

6

8

10

0 ½x 1X 1.5X

Herbicide doses

Dry

bio

mas

s (kg

ha-1

)2 Leaf

4 Leaf

cd

a

e

b

debc

ede

Means 4.93b6.18a 4.83b 3.97c

Fig-7.3.2.2b Dry biomass of A. tenuifolius as affected by the interaction of growth stages and herbicide doses.

7.3.2.3. Number of branches plant-1

No. of branches plant-1 of chickpea were differentially affected by herbicides, herbicide

doses and their interaction (Fig-7.3.2.3). The main effects of herbicide doses showed that

maximum (8.24 branches plant-1) were recorded at 1X dose followed by ½x and 1.5X

dose and the minimum (7.05 branches plant-1) were observed in untreated check. In the

interaction, highest (9.0) value was observed at 1X dose in fenoxaprop-p-ethyl herbicide

followed by same herbicide at ½x dose while minimum (6.85 branches plant-1) were

recorded at ½x dose of isoproturon treated plots however it was statistically at par with

1.5X dose of the same herbicide and untreated check of both the herbicides.

0

2

4

6

8

10

0 ½x 1X 1.5X

Herbicides doses

No.

of b

ranc

hes p

lant

-1

fenoxaprop-p-ethyl

isoproturon

ddb

d

a

c cd

Means 7.05c 7.45b 8.24a 7.33b

Fig-7.3.2.3. No. of branches plant-1 of chickpea as affected by the interaction of herbicides and herbicide doses.

98

7.3.2.4. Number of pods plant-1

No. of pods plant-1 of chickpea were significantly affected by herbicides, herbicide doses,

growth stages and their interactions (Fig-7.3.2.4). The main effects of herbicide doses

showed that maximum (36.59) pods plant-1 were recorded at 1X dose followed by ½x

dose and 1.5X dose while the minimum (30.32) pods plant-1 were observed for untreated

check. In the interaction of herbicides x doses x growth stages maximum (45.20) pods

were observed at 1X dose in fenoxaprop-p-ethyl treatment at 4 leaf stage followed by

(40.13) pods plant-1 in the same herbicide at 2 leaf growth stage while the minimum

(28.43) pods plant-1 was recorded at 1X dose in isoproturon treated plots at 4 leaf stage

however, it was statistically at par with rest of the doses at same herbicide at the same

growth stage.

0

10

20

30

40

50

60

2 Leaf 4 Leaf 2 Leaf 4 Leaf

fenoxaprop-p-ethyl isoproturon

Herbicides and growth stages

No.

of p

ods p

lant

-1

0

½x

1X

1.5X

e f e fd c

ef

ee f f

bd

a

cd

Means

30.43c

33.64b

36.67a

33.49b

Fig-7.3.2.4. No. of pods plant-1 as of chickpea as affected by the interaction of herbicides x doses x growth stages.

7.3.2.5. Number of seeds pod-1

Analysis of variance of the data showed that herbicides, doses and interaction had

significantly affected that seeds pod-1 of chickpea (Fig-7.3.2.5a). The data showed that

among the herbicides doses highest (1.53) seed weight was recorded at 1Xdose however

it was statistically at par with ½x and 1.5X dose of herbicides while minimum (1.42)

seeds pod-1 were observed in untreated check. In the interaction of herbicides and doses

maximum (1.62) seeds were observed at 1X dose, however these were statistically at par

with ½x and 1.5X dose of fenoxaprop-p-ethyl while the minimum (1.40) seeds pod-1 were

99

recorded at untreated check of fenoxaprop-p-ethyl which is statistically similar to the all

doses of isoproturon.

1.251.3

1.351.4

1.451.5

1.551.6

1.651.7

0 ½x 1X 1.5X

Herbicides doses

No.

of s

eed

pod-1

fenoxaprop-p-ethyl

isoproturonbb

ab

b

a

b

ab

b

Means 1.46ab 1.53a 1.49ab1.42b

Fig-7.3.2.5a. No. of seeds pod-1 as of chickpea as affected by the interaction of herbicides x doses x growth stages.

Statistical analysis of the data revealed that herbicides, growth stages and their interaction

differentially affected seeds pod-1 of chickpea (Fig-7.3.2.5b). The interaction of both the

factors showed that maximum (1.65 and 1.58) seed pod-1 were observed at 4 leaf stage in

both the herbicides while minimum (1.28) seed pod-1 were recorded at 2 leaf stage of

isoproturon. These results indicated that variation of efficacy between the growth stages

of A. tenuifolius is a good intervention for the management of the aforesaid weed and

harvesting yield of the chickpea crop.

0

0.5

1

1.5

2

2 leaf 4 leaf

Grow th stages

No.

of s

eeds

pod

-1

fenoxaprop-p-ethyl

isoproturon

bc

a a

.Fig-7.3.2.5b No. of seeds pod-1 of chickpea as affected by the interaction of herbicides x growth stages.

100

7.3.2.6. 100 seed weight (g)

Herbicides, doses and their interaction differentially affected 100 seed weight of chickpea

(Fig-7.3.2.6). The main effects of herbicide doses exhibited that maximum (24.99) 100

seed weight was recorded at 1X dose followed by ½x and 1.5X dose while minimum

(19.83) weight was observed in untreated check. In the interaction of herbicides and

doses, maximum (28.23) weight was found at 1X dose of fenoxaprop-p-ethyl followed

by the same herbicide at ½x dose (24.63), while minimum value (19.28) was recorded in

untreated check of isoproturon however it was statistically at par with untreated check of

fenoxaprop-p-ethyl and ½x and 1X doses of the same herbicide.

0

5

10

15

20

25

30

35

0 ½x 1X 1.5X

Herbicides doses

100

seed

wei

ght (

g)

fenoxaprop-p-ethyl

isoproturon

de e

b

de

a

c-ebc

b-d

Means 22.61b 24.99a 22.82b19.83c

Fig-7.3.2.6. 100 seeds weight (g) of chickpea as affected by the interaction of herbicides x doses.

7.3.2.7. Seed yield (kg ha-1)

Herbicides, doses and their interaction differentially affected the seed yield of chickpea

(Fig-7.3.2.7). The main effects of herbicides doses depicted that maximum (1098 kg

ha-1) seed yield was observed at 1X dose followed by ½x and 1.5X doses of herbicides

while minimum (976.4 kg ha-1) seed yield was recorded in untreated check. In the

interaction of herbicides and doses, maximum (1194 kg ha-1) seed yield was observed at

1X dose of fenoxaprop-p-ethyl followed by ½x and 1.5X dose of the same herbicide

while minimum (970.6 kg ha-1) seed yield of chickpea was observed at ½x dose of

isoproturon however, it was statistically at par with untreated check of fenoxaprop-p-

ethyl and 1.5X and untreated check of the same herbicide.

101

0200400600800

100012001400

0 ½x 1X 1.5X

Herbicides doses

Seed

yie

ld (k

g ha-1

)fenoxaprop-p-ethyl

isoproturon

cdcdb

da

cb

cd

Means 976.4c 1027b 1098a 1024b

Fig-7.3.2.7a. Seed yield (kg ha-1) of chickpea as affected by the interaction of herbicides x doses.

Growth stages and herbicides differentially affected the seed yield of chickpea during

2006-07 (Fig-7.3.2.8.). The interaction of herbicides and growth stages showed that

maximum (1141 kg ha-1) seed yield was achieved from fenoxprop-p-ethyl at 2 leaf stage.

While minimum (943.4 kg ha-1) seed yield was observed in isoproturon at the same

growth stage of wild onion. Statistically similar results were recorded for 4 leaf stage at

either of the herbicides.

0200400600800

100012001400

2 leaf 4 leaf

Growth stages

Seed

yie

ld k

g (h

a-1)

fenoxaprop-p-ethyl

isoproturon

ac b b

Fig-7.3.2.8b. Seed yield (kg ha-1) of chickpea as affected by the interaction of herbicides x growth stages.

102

7.4. DISCUSSION

A. tenuifolius; a weed of sandy zone in Pakistan heavily infests chickpea crop. Herbicides

were tested against this weed at 2 leaf and 4 leaf growth stages with ½x, 1X and 1.5X

doses. Post emergence herbicide, fenoxaprop-p-ethyl produced very good results at 1X

under field conditions. Significantly higher seed yield were recorded at 2 leaf stages as

compare to 4 leaf. As weeds increase in size, they may become less susceptible to

herbicides (Devlin et al., 1991; Klingaman et al., 1991; Blackshaw and Harker, 1997).

Weed control was also influenced by weed sensitivity to phenoxy carboxylic acid

herbicides in another study (Salonen, 1992). Annual broadleaved weeds should be

controlled when weeds are small and actively growing with 2, 4-D and metsulfuron-

methyl according to another study (Butler and Interrante, 2003). The low control of

perennial species was observed in other studies (Bradley et al., 2004; Whaley and

Vangessel, 2002). Among the herbicide doses 1.5X dose produced low yield as compare

the rest of the doses due to its phytotoxicity on the crop. These results are also inline

with those reported by Brain et al. (1999). Reduced-dose technology is an approach to

lower costs that can provide effective control of susceptible species and decrease weed

seedling vigour of less susceptible species to give the crop a competitive growth

advantage (Vangessel and Westra, 1997). In another study herbicides with ½x, a high

number of species showed a control lower than 83%. Furthermore, weed plants that

escape control often produce abundant seeds (Defelice et al., 1989). Results from our

experiment demonstrate that for most weed species in the community of the studied

region, weed development stage affected the efficacy of all the herbicides studied and

that increasing herbicide doses is often necessary to control weeds at the reproductive

stage.

103

CHAPTER-8.

SUMMARY, CONCLUSIONS AND RECOMMENDATIONS

8.1 SUMMARY

Asphodelus tenuifolius CAV (wild onion) is one of the troublesome weed of various

crops specifically chickpea in the sandy zone throughout Pakistan. The current studies

revealed the infestation of wild onion in North West Frontier Province (NWFP) and

Punjab. Both field and laboratory studies were undertaken to overcome the problem. Two

different types of experiments were conducted in field for the two growing seasons of

chickpea during 2005-06 and 2006-07 while three different types of experiment were

formulated under controlled environment. The first experiment under controlled

environment included dormancy breaking by using GA3, KNO3, Thiourea, and Sodium

Azide at 0 to 800 mM exposed to 10, 20, and 30oC temperature regimes. The experiment

was conducted using a completely randomized design with a factorial arrangement. The

second experiment in pots was also conducted in a Completely Randomized Design with

a factorial plot arrangements, to investigate the effect of different herbicides doses on

wild onion growth stages in its four biotypes. Two herbicides, isoproturon and

fenoxaprop-p-ethyl, were evaluated, each having four doses including an untreated check.

Each biotype was subjected to 4 doses of each herbicide at 2 leaf, 4 leaf and flowering

stages. The data were recorded on fresh and dry weight of wild onion. The interaction of

herbicides x doses and biotypes x growth stages significantly affected the fresh weight.

While the interactions of herbicides doses x growth stages, biotypes x growth stages,

herbicides x doses, herbicides x growth stages and the three way interaction of biotypes x

herbicides x growth stages significantly affected the dry weed biomass. The third

experiment under controlled environment included chickpea germplasm was again laid

out in Completely Randomized Design with factorial arrangement having two

replications. During the course of experiment, trials were made among 12 chickpea

germplasm with two herbicides pendimethalin (pre-emergence) and fenoxaprop-p-ethyl

(post-emergence). The varieties tested for tolerance were KC-98, Sheenghar, Lawaghir,

KK-1, KK-2, SL-01-13, SL-02-13, SL-02-20, SL-02-22, SL-02-29, SL-03-29 and SL-04-

104

29. Data were recorded on Fresh and dry weight of the germplasm. Among the

germplasm Sheenghar was produced highest (15.8 g) fresh weight while the lowest (7.1,

5.9, 6.4, and 5.7 g) fresh weight was recorded in SL-01-13, SL-02-13, SL-02-20, SL-03-

29 and SL-04-29, respectively. Similar trend was also observed while recording the dry

weight of the germplasm. Under field conditions, herbicides and herbicides doses

alongwith growth stages of wild onion were tested in two different experiments for two

years. In the first field experiment herbicides and herbicides doses were compared for

agronomic parameters of chickpea. Herbicides were assigned to main plots while

herbicides doses were assigned to sub plots. The experiment was laid out in Randomized

Complete Block design with three replications. There were 5 herbicides alongwith four

different doses including an untreated check. Two pre-emergence and three post

emergence herbicides were studied. Pre emergence herbicides showed maximum results

at 1.5X dose with a seed yield (1164) kg ha-1 as compared to post emergence herbicide

isoproturon (981.6) at either of the dose. In the second experiment two post emergence

herbicides were investigated which included fenoxaprop-p-ethyl and isoproturon on two

different growth stages (2 leaf and 4 leaf) of wild onion. Experiment was laid out in

Randomized Complete Block Design with three replications. Growth stages were

assigned to main plots, herbicides to sub plot and herbicides doses to sub sub plots. Wild

onion was more susceptible to fenoaprop-p-ethyl as compared to isoproturon at all the

doses at 2 leaf stage as compared to 4 leaf stage. Recommended (1X) dose of herbicides

was more effective as compared to the rest of the doses for increasing yield and yield

components of chickpea.

105

8.2 CONCULSIONS

The response of seed germination of A. tenuifolius biotypes to various temperatures and

growth regulators were differential. Mianwali biotype produced the best germination with

Potassium Nitrate at 20oC as compared to the rest of the biotypes. Overall 5.93 mM rate

of potassium nitrate was the most germinable concentration. Temperature (15-20oC) is

the most favourable for the germination of A. tenuifolius. Among the chemicals, KNO3

was the most effective in inducing germination while sodium azide emerged as inhibitory

to A. tenuifolius germination.

Under field conditions pre emergence herbicides like pendimethalin and s-metolachlor at

1.5X dose showed best results as compared to ½x and 1X doses. Among post emergence

herbicides fenoxaporp-p-ethyl was the more suitable herbicide at 1X dose under field

conditions while at ½x dose it was even effective in pot experiments as compared to the

rest of the herbicide.

Two leaf growth stage of A. tenuifolius both in pot as well under field conditions was the

most susceptible growth stage as compared to 4 leaf and flowering staged of wild onion.

Tolerance of few chickpea varieties like KC-98, KK-1 and Sheenghar was more

satisfactory to both the pre and post emergence herbicides at 1X and ½x dose, while all

remaining varieties were susceptible to both the herbicides at 1.5X dose of herbicides.

The research findings will increase farmers’ awareness regarding chickpea tolerance to

the above herbicides and provide guidelines for adjustment of rates for minimizing crop

injury.

106

8.3 RECOMMENDATIONS

It is recommended that chickpea crop may be delayed planted or rotated with wheat to

mitigate the competition of wild onion with chickpea. In addition to this sodium azide

being the most important inhibitory compound of the seed of A. tenuifolius is the new

discovery and additional management strategy for A. tenuifolius. In our results we found

it the very useful for the first time to suppress seed germination of A. tenuifolius by 100%

at very low concentration of 100 mM.

Pre emergence herbicides like pendimethalin at 1.5X dose is strongly recommended for

chickpea growers for the suppression of A. tenuifolius. While fenoxaprop-p-ethyl is

recommended at ½ x and 1X dose under field conditions.

Sheenghar, KK-1 and KC-98 varieties are recommended due its tolerance against both

pre and post emergence herbicides.

107

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APPENDICES

Experiment No. 1. Studies on Temperature Regimes and Dormancy Breaking Chemicals influencing Seed Germination of Chickpea and A. tenuifolius (Cav.)

Appendix-1. ANOVA for germination % of the four biotypes, temperature, chemical and concentrations

Source of variation D.F S.S. M.S. F.Ratio Prob. Runs 1 127.6 127.6 0.53 0.469 Temp 2 415700.7 207850.3 857.30 <.001 Biotypes 3 43601.4 14533.8 59.95 <.001 Chemicals 3 168430.1 56143.4 231.57 <.001 Conc. 4 9834.0 2458.5 10.14 <.001 Runs.Temp 2 1217.6 608.8 2.51 0.082 Runs.Biotypes 3 401.8 133.9 0.55 0.647 Temp.Biotypes 6 39091.0 6515.2 26.87 <.001 Runs.Chem. 3 663.0 221.0 0.91 0.435 Temp.Chem. 6 75992.2 12665.4 52.24 <.001 Biotypes.Chem. 9 11058.4 1228.7 5.07 <.001 Runs.Conc 4 1339.8 335.0 1.38 0.239 Temp.Conc 8 8074.6 1009.3 4.16 <.001 Biotypes.Conc 12 10046.8 837.2 3.45 <.001 Chemicals.Conc 12 50946.2 4245.5 1 7.51 <.001 Runs.Temp.Biotypes 6 1307.4 217.9 0.90 0.495 Runs.Temp.Chem. 6 1339.9 223.3 0.92 0.479 Runs.Biotypes.Chem. 9 986.8 109.6 0.45 0.906 Temp.Biotypes.Chem. 18 19421.1 1078.9 4.45 <.001 Runs.Temp.Conc 8 911.9 114.0 0.47 0.877 Runs.Biotypes.Conc 12 1333.9 111.2 0.46 0.938 Temp.Biotypes.Conc 24 8582.7 357.6 1.48 0.069 Runs.Chemicals.Conc 12 1098.7 91.6 0.38 0.971 Temp.Chemicals.Conc 24 29612.7 1233.9 5.09 <.001 Bio.Chem.Conc 36 16995.5 472.1 1.95 0.001 Runs.Temp.Bio.Chem 18 888.4 104.9 0.43 0.981 Runs.Temp.Bio.Conc 24 1591.2 66.3 0.27 1.000 Runs.Temp.Chem.Conc 24 2373.3 98.9 0.41 0.995 Runs.Bio.Chem.Conc 36 3198.4 88.8 0.37 1.000 Temp.Bio.Chem.Conc 72 22312.5 309.9 1.28 0.072 Runs.Temp.Bio.Chem.Conc 72 6157.7 85.5 0.35 1.000 Residual 480 116375.0 Total 959 1072012.4

Coefficient of variation: 50.8%

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Experiment No. 2. Effect of Different Herbicides and their Doses at Various Growth Stages of A. tenuifolius Grown in Pots during 2005-06.

Appendix-2. ANOVA for Fresh biomass of A. tenuifolius as affected by herbicides and their doses.

Appendix-3. ANOVA for dry biomass of A. tenuifolius as affected by herbicides and their doses.

Source D.f. S.S. M.S. F.value Prob Factor A 2 2365.440 182.720 1749.2458 0.0000 Factor B 3 10.853 3.618 5.3506 0.0019 AB 6 9.637 1.606 2.3755 0.0349 Factor C 1 2.039 2.039 3.0159 0.0857 AC 2 0.861 0.431 0.6369 BC 3 5.826 1.942 2.8721 0.0403 ABC 6 6.497 1.083 1.6014 0.1551 Factor D 3 41.968 13.989 20.6902 0.0000 AD 6 6.427 1.071 1.5843 0.1600 BD 9 0.657 0.073 0.1080 ABD 18 2.042 0.113 0.1678 ABD 3 0.159 0.053 0.0784 ACD 6 0.710 0.118 0.1750 BCD 9 0.820 0.091 0.1348 ABCD 18 1.410 0.078 0.1158 Error 96 64.909 0.676 Total 191 2520.255 Coefficient of Variation 18.86%

Source D.f. S.S. M.S. F.value Prob Factor A 2 332.423 166.211 1736.6977 0.0000 Factor B 3 15.520 5.173 54.0536 0.0000 AB 6 7.769 1.295 13.5296 0.0000 Factor C 1 1.446 1.446 15.1065 0.0002 AC 2 0.868 0.434 4.5370 0.0131 BC 3 1.770 0.590 6.1631 0.0007 ABC 6 1.485 0.247 2.5856 0.0229 Factor D 3 9.894 3.298 34.4606 0.0000 AD 6 1.601 0.267 2.7875 0.0153 BD 9 0.875 0.097 1.0159 0.4330 ABD 18 1.054 0.059 0.6121 ABD 3 0.110 0.037 0.3840 ACD 6 0.160 0.027 0.2786 BCD 9 0.232 0.026 0.2694 ABCD 18 0.368 0.020 0.2138 Error 96 9.188 0.096 Total 191 384.763 Coefficient of Variation 17.77%

124

Experiment No. 2. Effect of Different Herbicides and their Doses at Various Growth Stages of A. tenuifolius Grown in Pots during 2006-07.

Appendix-4. ANOVA for Fresh biomass of A. tenuifolius as affected by herbicides and their doses.

Appendix-5. ANOVA for dry biomass of A. tenuifolius as affected by herbicides and their doses.

Source D.f. S.S. M.S. F.value Prob Factor A 2 2396.969 1198.485 1520.3407 0.0000 Factor B 3 9.095 3.032 3.8457 0.0120 AB 6 8.218 1.370 1.7375 0.1205 Factor C 1 2.903 2.903 3.6824 0.0580 AC 2 0.984 0.492 0.6240 BC 3 5.643 1.881 2.3863 0.0738 ABC 6 7.296 1.216 1.5426 0.1726 Factor D 3 40.032 13.344 16.9276 0.0000 AD 6 5.093 0.849 1.0769 0.3818 BD 9 0.812 0.090 0.1145 ABD 18 2.282 0.127 0.1608 ABD 3 0.355 0.118 0.1500 ACD 6 0.611 0.102 0.1291 BCD 9 1.404 0.156 0.1978 ABCD 18 3.094 0.172 0.2180 Error 96 75.677 0.788 Total 191 2560.467 Coefficient of variation

20.25%

Source D.f. S.S. M.S. F.value Prob. Factor A 2 341.490 170.745 1675.6457 0.0000 Factor B 3 16.795 5.598 54.9396 0.0000 AB 6 8.168 1.361 13.3593 0.0000 Factor C 1 1.575 1.575 15.4573 0.0002 AC 2 0.765 0.382 3.7515 0.0270 BC 3 1.480 0.493 4.8414 0.0035 ABC 6 1.600 0.267 2.6174 0.0215 Factor D 3 10.436 3.479 34.1384 0.0000 AD 6 1.838 0.306 3.0059 0.0098 BD 9 1.000 0.111 1.0903 0.3772 ABD 18 1.126 0.063 0.6141 ABD 3 0.052 0.017 0.1715 ACD 6 0.135 0.023 0.2210 BCD 9 0.134 0.015 0.1459 ABCD 18 0.255 0.014 0.1388 Error 96 9.782 0.102 Total 191 396.630 Coefficient of Variation 17.99%

125

Experiment No. 3. Tolerance of Chickpea Cultivars to Major Chickpea Herbicides during 2005-07.

Appendix-6. ANOVA for Fresh biomass of chickpea cultivars as affected by cultivars, herbicides and their doses.

Appendix-7. ANOVA for dry biomass of chickpea cultivars as affected by cultivars, herbicides and their doses.

Source D.f. S.S. M.S. F.value Prob Runs 1 1.6420 1.6420 1.93 0.166 Cultivars 11 715.6755 65.0614 76.60 <.001 Herbicides 1 0.0339 0.0339 0.04 0.842 Doses 3 955.6786 318.5595 375.04 <.001 Runs.Cultivars 11 8.9089 0.8099 0.95 0.491 Runs.Herbicides 1 1.1430 1.1430 1.35 0.247 Cultivars.Herbicides 11 160.6209 14.6019 17.19 <.001 Runs.Doses 3 0.1079 0.0360 0.04 0.988 Cultivars.Doses 33 31.7032 0.9607 1.13 0.298 Herbicides.Doses 3 27.4499 9.1500 10.77 <.001 Runs.Culti.Herbi. 11 7.9563 0.7233 0.85 0.589 Runs.Cultivars.Doses 33 1.6996 0.0515 0.06 1.000 Runs.Herbicides.Doses 3 0.0830 0.0277 0.03 0.992 Culti.Herbi..Doses 33 17.4337 0.5283 0.62 0.947 Runs.Culti.Herbi..Doses 33 2.0847 0.0632 0.07 1.000 Residual 192 163.0831 Total 383 2095.3041 Coefficient of Variation 8.1%

Source D.f. S.S. M.S. F.value Prob. Runs 1 0.00344 0.00344 0.04 0.851 Cultivars 11 138.03010 12.54819 128.75 <.001 Herbicides 1 0.75881 0.75881 7.79 0.006 Doses 3 161.06318 53.68773 550.84 <.001 Runs.Cultivars 11 0.15270 0.01388 0.14 0.999 Runs.Herbicides 1 0.00073 0.00073 0.01 0.931 Cultivars.Herbicides 11 41.84900 3.80445 39.03 <.001 Runs.Doses 3 0.08435 0.02812 0.29 0.834 Cultivars.Doses 33 13.34808 0.40449 4.15 <.001 Herbicides.Doses 3 0.85003 0.28334 2.91 0.036 Runs.Culti.Herbi. 11 0.08272 0.00752 0.08 1.000 Runs.Cultivars.Doses 33 0.29892 0.00906 0.09 1.000 Runs.Herbicides.Doses 3 0.06781 0.02260 0.23 0.874 Culti.Herbi..Doses 33 7.11422 0.21558 2.21 <.001 Runs.Culti.Herbi..Doses 33 0.24465 0.00741 0.08 1.000 Residual 192 18.71325 Total 383 2095.3041 Coefficient of Variation 10.6%

126

Experiment No. 4. Effect of Different Herbicide Doses on A. tenuifolius CAV in Chickpea under Field Conditions during 2005-06.

Appendix-8. ANOVA for fresh biomass of A. tenuifolus as affected by herbicides and their doses.

Appendix-9. ANOVA for dry biomass of A. tenuifolius as affected by herbicides and their doses.

Appendix-10. ANOVA for No. of branches plant-1 of chickpea as affected by herbicides and their doses.

Source D.f. S.S. M.S. F.value Prob. Replication 2 15.223 7.611 9.7947 0.0071 Factor A 4 220.697 55.174 71.0002 0.0000 Error 8 6.217 0.777 Factor B 3 238.231 79.410 136.0849 0.0000 AB 12 81.407 6.784 11.6255 0.0000 Error 30 17.506 0.584 Total 59 579.280 Coefficient of Variation: 9.26%

Source D.f. S.S. M.S. F.value Prob. Replication 2 3.148 1.574 17.8633 0.0011 Factor A 4 25.879 6.470 73.4290 0.0000 Error 8 0.705 0.088 Factor B 3 32.323 10.774 103.0650 0.0000 AB 12 10.340 0.862 8.2422 0.0000 Error 30 3.136 0.105 Total 59 Coefficient of Variation: 10.95%

Source D.f. S.S. M.S. F.value Prob. Replication 2 0.229 0.114 2.8098 0.1190 Factor A 4 393.789 98.447 2415.8825 0.0000Error 8 0.326 0.041 Factor B 3 10.043 3.348 33.7970 0.0000AB 12 136.835 11.403 115.1164 0.0000Error 30 2.972 0.099 Total 59 544.194 Coefficient of Variation: 4.64%

127

Appendix-11. ANOVA for No. of pods plant-1 of chickpea as affected by herbicides and their doses.

Appendix-12. ANOVA for No. of seed pod-1 of chickpea affected by herbicides and their doses.

Appendix-13. ANOVA for 100 seed weight (g) of chickpea as affected by herbicides and their doses.

Appendix-14. ANOVA for Seed yield (kg ha-1) of chickpea as affected by herbicides and their doses.

Source D.f. S.S. M.S. F.value Prob. Replication 2 7.663 3.831 3.5278 0.0797 Factor A 4 7737.924 1934.481 1781.1534 0.0000 Error 8 8.689 1.086 Factor B 3 224.716 74.905 68.8152 0.0000 AB 12 2668.649 222.387 204.3063 0.0000 Error 30 32.655 1.089 Total 59 10680.296 Coefficient of Variation: 3.41%

Source D.f. S.S. M.S. F.value Prob. Replication 2 0.036 0.018 6.9677 0.0177 Factor A 4 12.262 3.066 1186.6769 0.0000 Error 8 0.021 0.003 Factor B 3 0.391 0.130 33.4857 0.0000 AB 12 4.218 0.351 90.3785 0.0000Error 30 0.117 0.004 Total 59 17.044 Coefficient of Variation: 5.03%

Source D.f. S.S. M.S. F.value Prob. Replication 2 10.811 5.405 3.4534 0.0829 Factor A 4 3768.563 942.141 601.9152 0.0000 Error 8 12.522 1.565 Factor B 3 195.476 65.159 37.5350 0.0000 AB 12 1327.591 110.633 63.7305 0.0000Error 30 52.078 1.736 Total 59 5367.041 Coefficient of Variation: 6.07%

Source D.f. S.S. M.S. F.value Prob. Replication 2 3785.799 1892.899 1.7639 0.2319 Factor A 4 7191111.726 1797777.932 1675.2941 0.0000 Error 8 8584.895 1073.112 Factor B 3 78342.732 26114.244 43.1507 0.0000 AB 12 2428596.395 202383.033 334.4137 0.0000Error 30 18155.627 605.188 Total 59 9728577.174 Coefficient of Variation: 2.65%

128

Experiment No. 4. Effect of Different Herbicides Doses on A. tenuifolius CAV in Chickpea under Field Conditions during 2006-07. Appendix-15. ANOVA for fresh biomass of A. tenuifolius as affected by herbicides and their doses.

Appendix-16. ANOVA for dry biomass of A.tenuifolius as affected by herbicides and their doses.

Appendix-17. ANOVA for No. of branches plant-1 of chickpea as affected by herbicides and their doses.

Source D.f. S.S. M.S. F.value Prob. Replication 2 18.052 9.026 9.1749 0.0085 Factor A 4 45.555 11.389 11.5764 0.0021 Error 8 7.870 0.984 Factor B 3 133.217 44.406 57.0545 0.0000 AB 12 23.730 1.978 2.5408 0.0190Error 30 23.349 0.778 Total 59 251.774 Coefficient of Variation: 8.75%

Source D.f. S.S. M.S. F.value Prob. Replication 2 3.975 1.987 10.2624 0.0062 Factor A 4 8.900 2.225 11.4894 0.0021 Error 8 1.549 0.194 Factor B 3 25.352 8.451 85.4079 0.0000 AB 12 4.108 0.342 3.4600 0.0028Error 30 2.968 0.099 Total 59 46.852Coefficient of Variation: 8.20%

Source D.f. S.S. M.S. F.value Prob Replication 2 1.016 0.508 1.1413 0.3664 Factor A 4 9.204 2.301 5.1679 0.0235 Error 8 3.562 0.445 Factor B 3 9.774 3.258 9.5184 0.0001 AB 12 6.865 0.572 1.6715 0.1243 Error 30 10.268 0.342 Total 59 40.690 Coefficient of Variation: 7.87%

129

Appendix-18. ANOVA for No. of pods plant-1 of chickpea as affected by herbicides and their doses.

Appendix-19. No. of seed pod-1 of chickpea as affected by herbicides and their doses.

Appendix-20. ANOVA for 100 seed weight (g) of chickpea as affected by herbicides and their doses.

Appendix-21. ANOVA for seed yield (kg ha-1) of chickpea as affected by herbicides and doses.

Source D.f. S.S. M.S. F.value Prob Replication 2 5.422 2.711 2.5941 0.1354 Factor A 4 221.349 55.337 52.9479 0.0000 Error 8 8.361 1.045 Factor B 3 491.985 163.995 131.8642 0.0000 AB 12 144.410 12.034 9.6763 0.0000 Error 30 37.310 1.244 Total 59 908.837 Coefficient of Variation: 3.15%

Source D.f. S.S. M.S. F.value Prob Replication 2 0.027 0.013 2.1039 0.1844 Factor A 4 0.118 0.029 4.5844 0.0322 Error 8 0.051 0.006 Factor B 3 0.215 0.072 15.1882 0.0000 AB 12 0.156 0.013 2.7471 0.0122 Error 30 0.142 0.005 Total 59 0.708 Coefficient of Variation: 5.11%

Source D.f. S.S. M.S. F.value Prob Replication 2 13.228 6.614 3.6974 0.0729 Factor A 4 200.504 50.126 28.0207 0.0001 Error 8 14.311 1.789 Factor B 3 77.341 25.780 13.8414 0.0000 AB 12 136.088 11.341 6.0888 0.0000 Error 30 55.876 1.863 Total 59 497.349 Coefficient of Variation: 5.56%

Source D.f. S.S. M.S. F.value Prob Replication 2 58463.535 29231.767 1.7300 0.2375 Factor A 4 294069.184 73517.296 4.3510 0.0368 Error 8 135174.143 16896.768 Factor B 3 353966.477 117988.826 6.5782 0.0015 AB 12 258930.021 21577.502 1.2030 0.3256 Error 30 538090.788 17936.360 Total 59 1638694.148 Coefficient of Variation: 12.72%

130

Experiment No. 5. Effect of Some Herbicides and Their Doses at Different Growth Stages 0f A. tenuifolius under Field Conditions 2005-06.

Appendix-22. ANOVA for fresh biomass of A. tenuifolius as affected by growth stages, herbicides and their doses.

Appendix-23. ANOVA for dry biomass of A. tenuifolius as affected by growth stages, herbicides and their doses.

Source D.f. S.S. M.S. F.value Prob Replication 2 18.418 9.209 2.6920 0.2709 Factor A 1 544.121 544.121 159.0610 0.0062 Error 2 6.842 3.421 Factor B 1 145.778 145.778 110.7015 0.0005 AB 1 13.157 13.157 9.9909 0.0342 Error 4 5.267 1.317 Factor C 3 146.586 48.862 10.9917 0.0001 AC 3 42.008 14.003 3.1500 0.0435 BC 3 66.254 22.085 4.9681 0.0080 ABC 3 23.289 7.763 1.7464 0.1843 Error 24 106.688 4.445 Total 47 1118.407 Coefficient of Variation: 16.03%

Source D.f. S.S. M.S. F.value Prob Replication 2 1.248 0.624 3.4948 0.2225

Factor A 1 80.368 80.368 450.2187 0.0022 Error 2 0.357 0.179 Factor B 1 15.312 5.312 33.0571 0.0045 AB 1 4.947 4.947 10.6810 0.0308 Error 4 1.853 0.463 Factor C 3 20.677 6.892 15.7632 0.0000 AC 3 6.887 2.296 5.2507 0.0063 BC 3 9.894 3.298 7.5429 0.0010 ABC 3 1.716 0.572 1.3084 0.2947 Error 24 10.494 0.437 Total 47 153.752 Coefficient of Variation: 13.95%

131

Appendix-24. ANOVA for No. of branches plant-1 of chickpea as affected by growth stages, herbicides and doses.

Appendix-25. ANOVA for No. of pods plant-1 of chickpea as affected by growth stages, herbicides and their doses.

Source D.f. S.S. M.S. F.value Prob Replication 2 0.108 0.054 1.1826 0.4582 Factor A 1 0.092 0.092 2.0137 0.2917 Error 2 0.091 0.046 Factor B 1 7.600 7.600 48.3192 0.0023 AB 1 0.017 0.017 0.1073 Error 4 0.629 0.157 Factor C 3 10.069 3.356 23.8436 0.0000 AC 3 0.182 0.061 0.4317 BC 3 3.311 1.104 7.8397 0.0008 ABC 3 0.967 0.322 2.2906 0.1039 Error 24 3.378 0.141 Total 47 26.445 Coefficient of Variation: 4.92%

Source D.f. S.S. M.S. F.value Prob Replication 2 5.565 2.783 2.1239 0.3201 Factor A 1 50.841 50.841 38.8036 0.0248 Error 2 2.620 1.310 Factor B 1 450.188 450.188 522.8409 0.0000 AB 1 110.413 110.413 128.2324 0.0003 Error 4 3.444 0.861 Factor C 3 233.265 77.755 102.1039 0.0000 AC 3 29.931 9.977 13.1012 0.0000 BC 3 224.684 74.895 98.3480 0.0000 ABC 3 44.568 14.856 19.5083 0.0000 Error 24 18.277 0.762 Total 47 1173.797 Coefficient of Variation: 2.60%

132

Appendix-26. ANOVA for No. of seed pod-1 of chickpea as affected by growth stages, herbicides and their doses.

Appendix-27. 100 grains weight (g) of chickpea as affected by the different herbicides their doses.

Appendix-28. ANOVA for seed yield (kg ha-1) of chickpea as affected by growth stages, herbicides and their doses.

Source D.f. S.S. M.S. F.value Prob Replication 2 0.082 0.041 1.7500 0.3636 Factor A 1 0.101 0.101 4.3214 0.1732 Error 2 0.047 0.023 Factor B 1 0.101 0.101 12.7368 0.0234 AB 1 0.008 0.008 0.9474 Error 4 0.032 0.008 Factor C 3 0.154 0.051 11.5625 0.0001 AC 3 0.024 0.008 1.8125 0.1718 BC 3 0.111 0.037 8.3125 0.0006 ABC 3 0.014 0.005 1.0625 0.3834 Error 24 0.107 0.004 Total 47 0.779 Coefficient of Variation: 4.53%

Source D.f. S.S. M.S. F.value Prob Replication 2 41.116 20.558 35.3941 0.0275 Factor A 1 14.752 14.752 25.3982 0.0372 Error 2 1.162 0.581 Factor B 1 38.039 38.039 34.8845 0.0041 AB 1 5.090 5.090 4.6675 0.0968 Error 4 4.362 1.090 Factor C 3 37.589 12.530 4.8510 0.0089 AC 3 5.921 1.974 0.7641 BC 3 50.889 16.963 6.5674 0.0021 ABC 3 9.982 3.327 1.2883 0.3011 Error 24 61.989 2.583 Total 47 270.889 Coefficient of Variation: 6.44%

Source D.f. S.S. M.S. F.value Prob Replication 2 8278.504 4139.252 3.8898 0.2045 Factor A 1 4969.472 4969.472 4.6700 0.1633 Error 2 2128.248 1064.124 Factor B 1 125250.191 125250.191 341.5271 0.0001 AB 1 453.873 453.873 1.2376 0.3283 Error 4 1466.943 366.736 Factor C 3 94957.415 31652.472 33.4905 0.0000 AC 3 606.314 202.105 0.2138 BC 3 59888.475 19962.825 21.1221 0.0000 ABC 3 4213.255 1404.418 1.4860 0.2435 Error 24 22682.823 945.118 Total 47 324895.513 Coefficient of Variation: 2.93%

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Experiment No. 5.Effect of Some Herbicides and Their Doses at Different Growth Stages 0f A. tenuifolius under Field Conditions 2006-07.

Appendix-29. ANOVA for fresh biomass of A. tenuifolius as affected by growth stages, herbicides and their doses.

Appendix-30. ANOVA for dry biomass of A. tenuifolius as affected by growth stages, herbicides and their doses.

Source D.f. S.S. M.S. F.value Prob Replication 2 12.831 6.416 44.7620 0.0219 Factor A 1 182.754 182.754 1275.1030 0.0008 Error 2 0.287 0.143 Factor B 1 94.024 94.024 85.0591 0.0008 AB 1 5.993 5.993 5.4212 0.0804 Error 4 4.422 1.105 Factor C 3 128.005 42.668 25.9469 0.0000 AC 3 17.931 5.977 3.6346 0.0271 BC 3 38.859 12.953 7.8769 0.0008 ABC 3 6.724 2.241 1.3630 0.2779 Error 24 39.467 1.644 Total 47 531.296 Coefficient of Variation: 10.11%

Source D.f. S.S. M.S. F.value Prob Replication 2 1.546 0.773 0.3017 Factor A 1 31.025 31.025 12.1054 0.0736 Error 2 5.126 2.563 Factor B 1 12.150 12.150 24.2148 0.0079 AB 1 2.760 2.760 5.5004 0.0789 Error 4 2.007 0.502 Factor C 3 29.622 9.874 17.5369 0.0000 AC 3 5.703 1.901 3.3765 0.0348 BC 3 4.773 1.591 2.8259 0.0601 ABC 3 3.490 1.163 2.0659 0.1314 Error 24 13.513 0.563 Total 47 111.716 Coefficient of Variation: 15.08%

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Appendix-31. ANOVA for No. of branches plant-1 of chickpea as affected by growth stages, herbicides and their doses.

Appendix-32. ANOVA for No. of pods plant-1 of chickpea as affected by growth stages, herbicides and their doses.

Source D.f. S.S. M.S. F.value Prob Replication 2 0.722 0.361 1.6914 0.3716 Factor A 1 3.101 3.101 14.5352 0.0624 Error 2 0.427 0.213 Factor B 1 8.841 8.841 129.3781 0.0003 AB 1 0.013 0.013 0.1951 Error 4 0.273 0.068 Factor C 3 9.302 3.101 45.7928 0.0000 AC 3 0.894 0.298 4.4021 0.0133 BC 3 4.654 1.551 22.9128 0.0000 ABC 3 0.265 0.088 1.3046 0.2959 Error 24 1.625 0.068

Total 47 30.117 Coefficient of Variation: 3.45%

Source D.f. S.S. M.S. F.value Prob Replication 2 1.912 0.956 0.6491 Factor A 1 9.188 9.188 6.2394 0.1298 Error 2 2.945 1.473 Factor B 1 456.333 456.333 746.0498 0.0000 AB 1 106.207 106.207 173.6363 0.0002 Error 4 2.447 0.612 Factor C 3 237.882 79.294 214.7108 0.0000 AC 3 21.128 7.043 19.0696 0.0000 BC 3 213.938 71.313 193.0997 0.0000 ABC 3 30.614 10.205 27.6322 0.0000 Error 24 8.863 0.369 Total 47 1091.457 Coefficient of Variation: 1.81%

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Appendix-33. ANOVA for No. of seed pod-1 of chickpea as affected by growth stages, herbicides and their doses.

Appendix-34. ANOVA for 100 seed weight (g) of chickpea as affected by growth stages, herbicides and their doses.

Source D.f. S.S. M.S. F.value Prob Replication 2 0.028 0.014 2.4815 0.2872 Factor A 1 0.992 0.992 176.3336 0.0056 Error 2 0.011 0.006 Factor B 1 0.075 0.075 12.4483 0.0243 AB 1 0.002 0.002 0.3103 Error 4 0.024 0.006 Factor C 3 0.077 0.026 2.6884 0.0690 AC 3 0.021 0.007 0.7174 BC 3 0.077 0.026 2.6884 0.0690 ABC 3 0.017 0.006 0.6014 Error 24 0.230 0.010 Total 47 1.555 Coefficient of Variation: 6.65%

Source D.f. S.S. M.S. F.value Prob Replication 2 51.620 25.810 5.6217 0.1510 Factor A 1 61.178 61.178 13.3255 0.0675 Error 2 9.182 4.591 Factor B 1 6.908 6.908 2.1658 0.2151 AB 1 0.470 0.470 0.1474 Error 4 12.759 3.190 Factor C 3 11.143 3.714 0.6423 AC 3 6.746 2.249 0.3888 BC 3 32.719 10.906 1.8860 0.1589 ABC 3 6.006 2.002 0.3462 Error 24 138.791 5.783 Total 47 337.522 Coefficient of Variation: 9.70%

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Appendix-35. ANOVA for Seed yield (kg ha-1) of chickpea as affected by growth stages, herbicides and their doses.

Source D.f. S.S. M.S. F.value Prob Replication 2 1274.918 637.459 0.3506 Factor A 1 110577.575 110577.575 60.8169 0.0160 Error 2 3636.412 1818.206 Factor B 1 122748.569 122748.569 218.9165 0.0001 AB 1 5308.596 5308.596 9.4676 0.0370 Error 4 2242.838 560.710 Factor C 3 90407.881 30135.960 47.9932 0.0000 AC 3 206.610 68.870 0.1097 BC 3 56110.013 18703.338 29.7861 0.0000 ABC 3 4385.908 1461.969 2.3283 0.0999 Error 24 15070.116 627.921 Total 47 411969.436 Coefficient of Variation: 2.43%