vegetable cultivation in mizoram: status, issues and sustainable approaches · 2013-08-02 · june...

June 2013 Volume 26 Issue 1

Indian Journal of Hill Farming

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Vegetable Cultivation in Mizoram: Status, Issues and

Sustainable Approaches

B. K. SINGH1 *, Y. RAMAKRISHNA2 , V. K. VERMA3, S. B. SINGH1

ABSTRACT

The terrains of Lushai hills (Mizoram) are endowed with rich genetic bio-diversity of various vegetables(Sechium edule, Cucurbita moschata, Benincasa hispida, Cucumis sativus, Momordica spp.,Trichosanthes spp., Phaseolus vulgaris, Vigna unguiculata, Dolichus purpureous, Vigna umbellata,Parkia roxburghii, Psophocarpous tetragonolobus, Brassica juncea var. rugosa, Brassica oleracea

var. alboglabra, Cyphomandra betacea, Zingiber officinale, Curcuma spp., Colocasia spp., Solanum

melongena, Solanum gilo, Solanum macrocarpon, Capsicum annum, Capsicum frutescens andCapsicum chinense) which could be used to improve yield potential, quality and tolerance to stresses.Moreover, the use of hybrids/ high yielding varieties, access to knowledge and technologies, interactivedemonstrations, better input delivery systems, good communication, and proper utilization of availableresources would be very useful in enhancing the vegetables’ productivity, and ensuring the food andnutritional security to the tribal community.

Keywords: Vegetable, Spices, Genetic diversity, Mizoram

1 IIVR, Shahanshahpur-221305, Varanasi, Uttar Pradesh;2 ICAR-RC-NEH Region, Mizoram Centre, Kolasib, Mizoram3 ICAR-RC-NEH Region, Umroi Road, Barapani-7793103, Meghalaya* Corresponding author’s E-mail: [email protected]

INTRODUCTION

Vegetable crops are edible herbaceous, viny,shrubby or tree in growth habitats, but usuallysucculent plant, eaten with staples as main courseor as supplementary food either in cooked, semi-cooked or raw form. Vegetables improve nutrition(being good source of vitamins, minerals,antioxidants, nutraceuticals, carbohydrate, proteinand fiber), possess some medicinal values, generateemployment, increase income, provide businessopportunities and have export potential; and finally“prosperity for the poor and health for all” byproviding food, nutrition and income security.

Mizoram, comprising of nine districts, is 23rd

state of India located at 21º58´ to 23º35´ N latitudeand 92º15´ to 93º29´ E longitude and surroundedby Tripura, Assam and Manipur in north frontierregions; Bangladesh in west; and Myanmar in eastand south. The undulated topography of Mizoram,named as Lushai hills during British period, hasvaried altitudes ranging from 21 to 2157 m abovethe mean sea level with an annual rainfall of 2000-3200 mm. In summer (Monsoon), mean monthly

temperature ranges from 14.6ºC to 29.6ºC, whileduring winter minimum temperature falls up to11.8ºC. Soils, in general, are sandy loam to loamand loam-clay to clay, rich in humus, acidic (4.5-6.5 pH), and medium in phosphorus and potashcontent. The total geographical area of Mizoram isabout 21087 km2, of which net sown area constitutesonly 4.4 %. The ever increasing population pressurehas brought down the jhum cycle and low soilfertility due to degradation of soil and naturalresources, heavy rainfall and poor nutrientrecycling. The terrain of Lushai hills ischaracterized by inaccessibility, marginality,fragility, ethnicity, rich bio-diversity and low cropproductivity in general. The agricultural land inMizoram is comprised of slopy upland (jhum/shifting cultivation) and low land of valley (settledagriculture). Moreover, jhum cultivation isconsidered as major source of rural economy and apart of cultural requirement. In general, the uplandand low lands are under traditional system ofcultivation without any improved inputtechnologies. Mizoram is producing 206314 t ofvegetables including tuber crops and spices from

Indian Journal of Hill Farming 26(1):1-7 Available online at www.kiran.nic.in



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12195 ha area with a productivity of 16.9 t/ ha. In aunique system ‘The Shop without a Keeper’(Nghahloh Dawr in Mizo), one of the raresttraditional barter systems, is still in practice eventoday. In this system one can shop by himself at aguard less roadside store and then drop the moneyinto a box and walk away. One can buy some freshvegetables, fruits or eggs at various places‘Nghahloh Dawr’ along the route between Selingto Keifang villages in Mizoram.

PRESENT STATUS

Vegetable cultivation in Mizoram

The vegetable crops with their Mizo name (inparentheses) which are being grown and consumedto a considerable extent are cabbage (Zikhlum),chow-chow (Iskut), chilli (Hmarcha), ginger(Sawhthieng), turmeric (Aieng), French bean(Bean), Chinese/ vegetable mustard (Antam),Chinese kale (Fren antam), potato (Alu), cowpea(Behlawi), Indian bean (Bepui), brinjal(Bawkbawn), African egg plant (Satinrem),Solanum gilo (Samtawk and samtawkte), tomato(Tomoto), tree tomato (Thing or Shillong tomoto),tree bean (Zawngtha), Allium fistulosum

(Mizopurun), okra (Bawrhsaiabe), Burmesecoriander (Pardi), pumpkin (Mai), kakrol(Maitamtok), snake gourd (Berul), wax gourd(Maipawl), cucumber (Fanghma), ridge gourd(Awmpawng), bitter gourd (Changkha), bottlegourd (Umei), muskmelon (Hmazil), water melon(Dawnfawh), carrot, radish (Buluih), tapioca(Pangbal), colocasia (Bal), cauliflower (Parbawr),knol-khol (Bulbawk), garden pea (Motor chana),sweet potato (Kawl bahra), yam (Bahra), pigeonpea (Behliang), rice bean (Bete), soybean (Bekang),water mimosa (Dum zawngtah), subabul (Japanzawngtah), Indian fern (Chakawk), various bamboospecies (rawte, rawthing, talan, vairua, phar,phulrua, rawlak, rawnal, rawmi, rawpui, tursing,mautak, chal, saiman, rawngal, rawthla, lik andankua), etc. Apart from human food, these vegetablecrops have the potential for processing industry forvalue addition, and also by-products provide feedto pig, poultry, cattle and fish. The diverse agroclimatic conditions (humid temperate sub-alpinezone, humid sub-tropical hill zone and humid mild-tropical zone), varied soil type, and abundance ofrainfall offer immense scope for cultivation andconservation of different types of vegetable crops.

In Mizoram, the commercial cultivations ofvegetable crops are practiced only in few pocketssuch as Sihphir, Seling and Sateek in Aizawldistrict; Buhchangphai and Saihapui in Kolasibdistrict; Dintharveng and Kyonzar in Khazawldistrict; Hnalan and Ramthalang in Champhaidistrict; and peri-town area of Lunglei, Lawngtlaiand Saiha districts. The area, production andproductivity of leading vegetables including tubercrops and spices being grown in Mizoram are givenin Table 1.

Table 1: Status of vegetable area, production and

productivity in Mizoram (2007-08)

Vegetable crops Area Production Productivity(ha) (t) (t/ ha)

Chow-chow 714 26418 37.0Cabbage 200 5000 25.0Tomato 17 298 17.5Brinjal 80 100351 16.9Pea 139 462 3.3French bean 167 470 2.8Radish 37 181 4.9Carrot 45 950 21.1Cauliflower 30 438 14.6Knol-khol 52 698 13.4Chinese cabbage 167 803 4.8Broccoli 36 385 10.7Cucumber 91 802 8.8Okra 92 540 5.9Cowpea 107 718 6.7Pumpkin 103 1533 14.9Bitter gourd 76 996 13.1Snake gourd 64 1149 18.0Bottle gourd 26 531 20.4Ash gourd 90 2408 26.8Water melon 91 1799 19.8Musk melon 29 450 15.5Rice bean 15 100 6.7Samtawk 58 273 4.7Potato 1688 15960 9.5Other tubers 119 890 7.5Turmeric 4175 8350 20.0Ginger 3587 57011 15.9Bird eye chilli 100 200 2.0Total 12195 206314 16.9

Anonymous (2008)

Bio-diversity of vegetable crops in Mizoram

The terrain of Lushai hills is well known for itsrich genetic resources and variability for varioustypes of cucurbitaceous vegetables such as chow-chow (Sechium edule), pumpkin (Cucurbita

moschata), wax gourd (Benincasa hispida),



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cucumber (Cucumis sativus), sweet gourd or kheksaor kakrol (Momordica cochichinensis), kartoli orspine gourd (M. dioca) and snake gourd(Trichosanthes cucumerina and T. anguina). Theregion also abounds with leguminous vegetableslike French bean (Phaseolus vulgaris), cowpea(Vigna unguiculata cv.gr. sesquipedalis and V.

unguiculata cv. gr. unguiculata), Indian bean(Dolichus purpureous), rice bean (Vigna

umbellata), tree bean (Parkia roxburghii) andwinged bean (Psophocarpous tetragonolobus).Tree bean is one of the most useful multipurposetree species found in Mizoram. Morphologicalvariants of Chinese/ vegetable mustard (Brassica

juncea var. rugosa) and Chinese kale (Brassica

oleracea var. alboglabra), and tree tomato(Cyphomandra betacea) are also available on tribalcommunity’s domain. Tree tomato is a perennialshrub producing egg shaped, reddish-yellow colourand smooth skinned fruits of 30-50 g weight.Among the root/ rhizomatous vegetables, sufficientdiversity is available in ginger (Zingiber officinale),turmeric and related species (Curcuma longa, C.

amada, C. spp.), colocasia (Colocasia spp.), tapioca(Manihot esculenta), etc. Rich bio-diversity is alsoavailable for Abelmoschus species. A local cultivarof Abelmoschus esculentus having 7-9 stigmasinstead of 6-7 in general are also in cultivationamong rural populations. Among the solanaceousvegetables, the genetic variants of brinjal (Solanum

melongena) are widely distributed all around ofLushai hills. In addition to cultivated brinjal, twovariants of S. gilo having green, purple andcreamish-white colour fruits at physiologicalmaturity which turns red on ripening (Samtawk)and small green fruited (samtawkte) are found inabundance. The young leaves of African egg plant(Solanum macrocarpon) are usually cooked andused in curry, boil, meat and soup, and could beused as a genetic resource for improving agronomictraits of brinjal. Besides Solanum species, chilligroups offer a greater extent of heritable geneticvariability among common chilli (Capsicum

annum), bird eye chilli (C. frutescens), world’shottest chilli, i.e. King chilli (Capsicum chinense),dulle chilli and many more (Asati and Yadav 2004,Singh et al. 2010b, Singh et al. 2011d, Singh et al.2013, Yadav et al. 2005 and Yadav et al. 2009).

Constraints of vegetable cultivation

Although the area is blessed with dense forestand shrubs, rich bio-diversity and good weather

conditions; yet productivity of various vegetablesare too low due to following reasons as follows:● Jhum cultivation is still the preferred cultivation

practice.● Poor water-harvesting structures and almost no

irrigation facilities.● Mono-cropping.● Lack of awareness for productive and efficient

inputs.● Cultivation devoid of good agricultural practices

(GAP).● Minimum use of biological, physical and

chemical inputs.● Inadequate input delivery systems.● Poor basic communication infrastructures like

roads, transport, market, etc.● Inadequate post harvest management and

processing technologies.● High incidence of pest and diseases especially

during summer-rainy season, i.e. with onset ofrain to its recession (April to October).

● Unawareness of off-season and high-techproduction technologies.

● Inexperienced human resources and poorresearch infrastructures.

FUTURE STRATEGIES

Over the years, the tribal farming communitieshave been using many indigenous technologies tofulfill their vegetable requirements by utilizing theavailable resources from jhum lands. They weredepending entirely on locally available inputresources and knowledge base for maintaining theproductivity. But due to time factor, changingclimate and system responsiveness to varyingrequirements of ever increasing population; thereare needs to intervene the jhum practices andtraditional cultivation to increase the landproductivity and fertility sustainably, and also tomeet the self-reliance in vegetable demand (Singhet al. 2010a, Singh et al. 2010c, Singh et al. 2011a,Singh et al. 2011b, Singh et al. 2011c, Singh et al.2011e and Singh et al. 2012). Therefore, strategiesformulated for meeting the demand and need ofvegetable production, the planners should addresstwo major issues: firstly, a sustainable vegetableproduction plan and secondly, livelihoodenhancement opportunities. Hence, the segmentswhich require immediate steps are as mentionedhereafter point by point:



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Introduction of high yielding varieties and

hybrids

One of the most important and basicrequirements for higher productivity is adoption ofhigh yielding varieties/ hybrids and accessibilityof quality seeds to the farmers. ICAR ResearchComplex, Kolasib, and KVKs are main agencies

in the state for varietal trial. The few varieties whichperformed better at ICAR Research Complex,Kolasib, Mizoram are as follows (Table 2):

Plant population and crop geometry

It is very important to maintain the proper plantpopulation and crop geometry to harness thecomplete synergy of sun-light, nutrition and water

Table 2: High yielding varieties and hybrids of various vegetable crops

Vegetables Varieties/ cultivars Hybrids

Cabbage Pusa Ageti, Golden Acre, Pride of India and Pusa KGMR-1, Blue Diamond, Harnil, Bahar, Pragati,Mukta Green Express, Green Challenger, Kaveri, Quisto,

Fieldman, Green Ball and RyozekiKnol-khol Early Vienna, White Vienna and Late Vienna INDAM Early ViennaCauliflower Pusa Subhra, Pusa Snowball K-1, Pusa Himjyoti Pusa Synthetic, Pusa Hybrid-2, Deepa, Asmita,

and Meghalaya Local Suhashini, Mahima and HimaniBroccoli Pusa Broccoli KTS-1 Pushpa, Aishwarya, Fiesta and Harumi-188Brinjal Pusa Purple Long, Pusa Purple Cluster, KT-4, Pusa Hybrid-5, Pusa Hybrid-6, and NDBH-1

Pant Samrat, Pant Rituraj, Pusa Bhairav, ArkaKushumakar, Arka Sheel, Arka Shirish, PusaKranti, Megha Brinjal-1, Megha Brinjal-2 andMegha Brinjal-3

Chilli Pusa Jwala, K-2, Pusa Sadabahar, Arka Lohit, Agni, CH-1, BSS-782, Mahima and TejashwiniKing chilli, Mizo chilli (Bird eye chilli), Dullechilli and Pant C-1

Tomato Pusa Ruby, Pusa Gaurav, Pusa Rohini, Sioux, Avinash-2, Pusa Divya, Rocky, INDAM-100,Arka Abha, Arka Saurabh, Arka Alok, Sel-1, INDAM-1116, Pusa Hybrid-2, Vaishali, Rupali,Sel-2, Sel-3, Pusa 120 and Punjab Chhuhara Mahavir, BSS-3000, TO-017, Arvind, TO-1458,

NP-169 and RitaFrench bean Arka Komal, Kentucky Wonder, Canadian -

Wonder, Sel-60 (Nagaland), Sel-43 (Silchar),Sel-35 (Meghalaya), Sel-37 (Meghalaya),Sel-19 (Manipur), Sel-33 (Arunachal Pradesh) and Mizoram locals such as MZFB-27, MZFB-30, MZFB-40, MZFB-48, MZFB-44, MZFB-32,MZFB-38, MZFB-29, MZFB-51 and MZFB-47

Cowpea Yard Long Bean, Pusa Komal, Mizoram locals -such as MZCP-9, MZCP-10 and MZCP-11

Indian bean Pusa Early Prolific and LocalGarden pea Arkel, Bonneville, Arka Ajit, Lincoln, PM-2 -

and VL-3Carrot Pusa Yamadagni, Nantes, Pusa Kesar, Pusa Hybrid-1

Meghali and Meghalaya LocalCapsicum California Wonder and Pusa Deepti Swarna, KT-1, Bharat, Mahabharat and

INDAM-7207Okra Parbhani Kranti, Arka Anamika, Arka Abhay, Varsha Uphar, NS-801, NS-818, NS-810, Okra-151,

Pusa A-4, Pusa Makhmali, Punjab Padmini NOL-303, NOL-101, OH-597 and Greenand VRO-6 Challenger

Cucumber Poinsett, Japanese Long Green and Mizoram Local Pusa SanyogRadish Japanese White, Pusa Himani and Meghalaya Local -Ginger Nadia, Thingaria, Thinglaidum, Thingpui, Basar -

Local and Meghalaya LocalTurmeric RCT-1 (Megha Turmeric-1), Lakadong, IISR Allepy -

Supreme, IISR Pratibha, IISR Kedaram, Roma,Rasmi, Suranjana and Duggirala

Mizoram Local: These are the local land races collected from Mizo farmers and evaluated at ICAR Kolasib, Mizoram.



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for maximizing the yield per unit area per unit timeas well as to minimize the plant-weed competition.The time of sowing/ planting/ transplanting, seedrate and spacing of various vegetables are as follows(Table 3):

Integrated water management

Mizoram is blessed with good rainfall to the tuneof 200-320 cm annually which is mainly distributedfrom April to October and there is a lot of waterscarcity being faced by whole of the state fromNovember to March, peak period of winter seasonvegetable cultivation. Following the mentionedpractices would help in reducing the water scarcityefficiently and also will enhance the water useefficiency and vegetable productivity.● Water-harvesting and construction of Jal-Kund

(Water storing structure).● Mulching with locally available grasses, crop

residues, forest shrubs, etc during dry period.● Drip irrigation

Integrated nutrient management (INM)

A live healthy soil with proper cropping patterns,crop residue management (Vermicomposting, greenmanuring, etc.), application of organic manures andbio-fertilizers, effective crop rotation, and judicioususe of chemical fertilizers can sustain optimumproductivity over the years. INM includes acomprehensive management approach and additionof plant nutrients through all sources to improvesoil health and ecosystem of the region, and therebyproductivity and quality of produce. To promotethe INM and organic farming in Mizoram, the ICARResearch Complex, Kolasib supplied more than6000 kg of vermiculture to the State Govt., Growers’Association and farmers of Mizoram during 2008-2010.

Integrated pest management (IPM)

It is the integration of all the practices to managethe diseases and pests effectively without any lossto crop production, soil, environment and

Table 3: Time of sowing/ planting/ transplanting, seed rate and spacing of vegetables

Vegetables Time of sowing/ Seed rate Spacing (cm)planting/ transplanting (per ha)

Row to row Plant to plant

Cabbage November 400-500 g 40-50 40-50Knol-khol November 0.8-1.0 kg 40-45 40-45Cauliflower November 400-500 g 40-50 40-50Broccoli November 400-500 g 40-45 40-45Brinjal April-May 350-500 g 50-60 50-60

SeptemberChilli April-May 1-1.5 kg 50-60 40-50Tomato November 300-400 g (V) 50-60 40-50

125-175 g (H)Chinese kale and October-November 1.5-2.0 kg 40-45 25-30vegetable mustardFrench bean April-May & October (Pole type) 25-30 kg 100-125 80-100

November (Bush type) 80-90 kg 45-60 10-15Cowpea April-May (Pole type) 15-20 kg 100-125 80-100

November (Bush type) 40-50 kg 45-60 10-15Indian bean April-May 8-10 kg 200-250 125-150Garden pea October-November 80-100 kg 30-45 8-10Carrot November 5.0-6.0 kg 25-30 8-10Capsicum November 500-600 g (V)300-400 g (H) 50-60 40-50Okra April 8-.0-10.0 kg 50-60 45-50Cucumber April-May 2.0-2.5 kg 200-250 60-75Bitter gourd April-May 6.0-7.0 kg 150-200 60-75Radish November 7.0-8.0 kg 25-30 8-10Ginger April 1500-1800 kg 25-30 20-25Turmeric April 2000-2500 kg 35-45 25-30

V: variety H: hybrid



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ecosystems. IPM does not require any additionalbudget; however it is economical and ecologicallyviable. Planning in advance for cropping pattern,selection of crops, selection of cultivars and timeof sowing/ planting/ transplanting is of utmostimportance.● Emphasis should be given on use of resistant/

tolerant varieties suited to local situation.● Avoid mono-cropping and monoculture

practices.● Use of trap crops fits well in IPM.● Use of physical traps and repellants, pheromone

traps and poison baits would be very imperative.● Encourage predators, parasitoids, etc. for

effective suppression of pests/ diseases.● Emphasis should be given on use of bio-

pesticides and botanical pesticides.● Chemical pesticides, fungicides and weedicides

should be used judiciously and need based only.

Hi-tech horticulture

High-tech horticulture is the modern technologywhich is less dependent on environment, capitalintensive and has the capacity to improve theproductivity and quality of horticultural crops.Adoption of this technology is necessary to ensurethe food and nutritional security of ever increasingpopulation and shrinking of land and waterresources day by day, and to cope up with erraticand extreme type of weather events in impendingclimate change scenario. This includes micro-propagation, micro-irrigation, fertigation, protectedcultivation (greenhouse/ poly-house, plasticmulching, low tunnel, etc.), mechanization,nutrition modeling, and use of remote sensing.A Bangalore-based firm ‘Zopar Export Ltd’ withthe support of Mizoram Government startedproduction and export of flowers such as rose,anthurium, chrysanthemum, gerbera, lilium,limonium, orchid, etc., and strawberry from 2006.The firm has its own large production center atVaipuanpho, Aizawl. Zopar is providingtechnological know-how in big-way to the statefloriculture department’s own flower farm atChampai as well as the progressive farmers ofAizawl and Champhai districts, and also marketingtheir produce to the National and Internationalmarkets. More than 1,000 families are engaged incultivation of the flowers in Mizoram, out of which275 were Hi-tech producers. Entrepreneurshipdevelopment through cultivation of flowers has not

only brought about a change in the Horticulturescenarios of Mizoram, but also uplifted the livingcondition of the growers to a great extent. It is asuccessful model of Public-Private-Partnership(PPP) in which the roles of Mizoram Government,Zopar and growers are significantly synergestic andeffective. The success story may also be replicatein vegetable crops (High-value and Low-volume).

On-farm trials (OFTs)/ front-line

demonstrations (FLDs)

Poor communication and inadequate inputdelivery systems made it difficult to access therecent technologies and know-how. Therefore, thereis need to conduct demonstrations/ OFTs/ FLDs asmuch as possible at farmers’ field in the identifiedcrops to convince the farmers about the efficacyand importance of various inputs in enhancing theproductivity. Apart from this, field demonstrations,farmers’ day, farmers’ fair, yield competition, awardand recognition, and media coverage will be veryuseful in making it interactive. The ICAR ResearchComplex, Kolasib has successfully demonstrated/tested the various technologies at own Farm andfarmers’ field having significant impact onenhancing the productivity of vegetables such asadoption of Megha Turmeric-1 of turmeric (15-30%); Avinash-2 and Arvind of tomato (20-35 %);KGMR-1, Blue Diamond and Ryozeki of cabbage(15-35 %); Nantes and Pusa Kesar of carrot (10-22%); Harumi and Aishwaraya of broccoli (17-32 %);MZFB-27, MZFB-30 and MZFB-44 of French bean(20-30 %); MZCP-10 and MZCP-9 of cowpea (13-30 %); MZNC-1 of King chilli (30-62 %); Nadiaand Thingpui of ginger (15-20 %); Arka Anamikaand VRO-6 of okra (20-45 %); BSS-32 andTejasiwini of chilli (15-22 %); MZAE-1 of Africaneggplant (15-25 %); Local-4 of chow-chow (20-25%); leaf pruning of old vineyard in chow-chow (10-12 %), Naga chilli production under 50 % shade-net house (400-800 %); INM in tomato, cabbage,carrot, broccoli, French bean and chow-chow (15-20 %), application of borax in cauliflower andbroccoli (15-28 %); and mulching in cauliflower,tomato, cabbage and broccoli (10-25 %).

Post-harvest management and processing

The state is lacking in trained personnel withsound knowledge of post-harvest management andprocessing of produces. There is also need toestablish few units of post-harvest handling,



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packaging, storage, processing industries, etc.especially for chow-chow, chilli, ginger andturmeric for value addition as well as to reduce thebulk transport.

Search of market for organic foods

Mizoram is one of the least users of inorganicfertilizers (80.9 kg NPK/ ha/ annum) and chemicalpesticides, and the produce is almost organic innature. Searching the markets for chow-chow, chilli,ginger, turmeric, etc. especially in Metro cities, anddeveloped and economically sound countries wouldhelp in getting assured markets and good priceswhich will eventually help in strengthening thefarming communities.

Collection, characterization, conservation and

utilization of germplasm

The Lushai hill is blessed with rich bio-diversityof many vegetables. In the era of Plant Variety andFarmers’ Right Act; collection, characterization andconservation of available gene pools would provideroyalty to farming community for commercialutilization of their specific genetic resources. Theutilization of available genetic resources will alsoassure the high productivity and well adaptabilityof developed varieties/ hybrids.

ACKNOWLEDGEMENTS

We would like to express our thanks to theDirector, ICAR-RC-NEH Region, Umiam,Meghalaya for his moral and financial support.

REFERENCES

Anonymous (2008). Statistical Abstract (2007-08), Departmentof Horticulture, Govt. of Mizoram, Aizawl, Mizoram

Asati BS, Yadav DS (2004). Diversity of horticultural crops innorth eastern region. ENVIS Bulletin on HimalayanEcology 12 (1): 1-11

Singh BK, Pathak KA, Boopathi T, Deka BC (2010a).

Vermicompost and NPK fertilizer effects on morpho-physiological traits of plants, yield and quality of tomatofruits (Solanum lycopersicum L.). Vegetable CropsResearch Bulletin 73: 77-86

Singh BK, Pathak KA, Boopathi T, Ramakrishna Y, Kumar S(2011a). Cabbage: package of practices for cultivationin Mizoram. ICAR-RC-NEH Region, Mizoram Centre,Kolasib, Mizoram. Extension folder

Singh BK, Pathak KA, Boopathi T, Ramakrishna Y, Kumar S,Chaudhury P (2011b). Package of practices for tomatocultivation in Mizoram. ICAR-RC-NEH Region,Mizoram Centre, Kolasib, Mizoram. Extension folder

Singh BK, Pathak KA, Boopathi T, Ramakrishna Y, Kumar S,Verma AK (2011c). Broccoli: package of practices forcultivation in Mizoram. ICAR-RC-NEH Region,Mizoram Centre, Kolasib, Mizoram. Extension folder

Singh BK, Pathak KA, Ngachan SV (2012). Chow-chow[Sechium edule (Jacq) Swartz]: An underutilizedvegetable of Mizoram with immense domestic andcommercial market potential. Indian Horticulture 57 (5):3-5

Singh BK, Pathak KA, Ramakrishna Y (2013). UnderutilizedVegetable Crops and Spices of Mizoram: NeedsExploration and Utilization. In: (Prakash N, Roy SS,Sharma PK, Ngachan SV (eds) Developing the Potentialof Underutilized Horticultural Crops of Hill Regions,Today & Tomorrow’s Printers and Publishers, New Delhi,pp 217-232.\

Singh BK, Pathak KA, Ramakrishna Y, Verma VK, Deka BC(2010b). Solanum macrocarpon: Leafy vegetable ofMizoram. ICAR News: A Science and TechnologyNewsletter 16 (3): 5

Singh BK, Pathak KA, Ramakrishna Y, Verma VK, Deka BC(2011d). Purple-podded French bean with highantioxidant content. ICAR News: A Science andTechnology Newsletter 17 (3): 9

Singh BK, Pathak KA, Sarma KA, Thapa M (2010c). Effectof transplanting dates on plant growth, yield and qualitytraits of cabbage (Brassica oleracea var. capitata L.)cultivars. Indian Journal of Hill Farming 23(2):1-5

Singh BK, Pathak KA, Verma AK, Verma VK, Deka BC(2011e). Effects of vermicompost, fertilizer and mulchon plant growth, nodulation and pod yield of French bean(Phaseolus vulgaris L.). Vegetable Crops ResearchBulletin 74: 153-165

Yadav RK, Deka BC, Sanwal SK (2009). Genetic resources ofvegetable crops of north eastern Himalayan region.ENVIS Bulletin on Himalayan Ecology 17: 8-18

Yadav RK, Yadav DS, Sarma P (2005). Diversity ofcucurbitaceous crops in north eastern region. ENVISBulletin on Himalayan Ecology 13 (2): 9-15



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Characteristics of Weed Biomass-derived Biochar and Their

Effect on Properties of Beehive Briquettes

S. MANDAL*, R. K. SINGH, A. KUMAR, B. C. VERMA,S. V. NGACHAN

ABSTRACT

Charcoal is a carbonaceous solid with a fixed carbon content of 70% or more. Among its diversifiedutilization techniques, biochar and briquette production have been identified as most environmentfriendly. It can be derived from any ligno-cellulosic biomass by pyrolysis or retorting in presence oflittle or no oxygen. As wastes of wood and agricultural industries have many uses, sources of charcoalor biochar production have been limited to other biomass. In North-East India, weed biomass can beapotential source of biochar with a productivity of 20 t ha–1 annually. Experiments were conducted toassess the yield and quality of biochar from two weed biomass:Lantana camera, Chromolaenaodorata

and compared with biocharderived from pine wood. Further, propertiesof beehive briquette producedfrom these biocharswere evaluated. Charring was carried out in a portable metallic kiln to keep theprocess simple, quick and low cost. Biochar production efficiency of Lantana and Chromolaenawas27.72 and 18.34%, respectively whereas that of pine wood was 34.28%. Carbon content of Lantana

(65.99%) and Chromolaena(61.22%) biochar was lesser than the pine wood biochar (75.82%). Thecalorific value of beehive briquettes ranged between 18.1 and 19.4 MJ kg–1. The average burning timevaried from 133 to 143 minutes with a peak temperature range of 437°C to 572°C. It was found thatthough the quality of biochar produced from Lantana and Chromolaena was inferior compared topine wood, they can be effectively used as potential source of biochar and may be used in makingbeehive briquette to fulfil the energy need of rural household.

Keywords: Biochar, Beehive briquette, Weed biomass, Charring

ICAR Research Complex for NEH Region, Umiam, Meghalya 793 103, India

INTRODUCTION

In the context of changing climatic scenario,attention has to be given to the potential for storingthe significant amounts of carbon (C) in soil, forestsand other ecosystems which certainly might be anefficient alternative means of offsetting the effectof emissions of green house gases (GHGs) andcarbon dioxide (CO

2) in the atmosphere (Lehmann

2007). In this context, biochar, a pyrolysis productof plant biomass containing more than 70% carbonoffers a significant, multidimensional opportunityto transform large scale agricultural waste from afinancial and environmental liability to valuableassets. Biochar, fine grained charcoal added to soils,has been promoted with claims it can sequestercarbon in soils for “hundreds to thousands of years”,improve soil fertility and hence increase crop yields

and also provide renewable energy from pyrolysisproduction. Interestingly biochar incorporation insoil would yield more stable soil carbon thanburning or direct land application of biomass(Baldock and Smernik 2002).

In biochar, approximately 50% of the C inbiomass is left as stable residue and another 50%is released immediately, while non-burnt biomassdecomposes slowly over time and leaves only 10-20% C in agricultural soil after 5-10 years(Lehmann et al. 2006). It is believed that biocharcan store carbon in soil for hundreds to thousandsof years and reduce the level of green house gaseslike CO

2 and methane significantly in the

atmosphere thus offsetting the effect of climatechange (Lal 2009). Biomass conversion to biocharand biofuel by pyrolysis technology has attracted anumber of research activities and it has been

* Corresponding author’s E-mail: [email protected]




9

considered as a viable technology to mitigate theenergy demand, green house gas emission and soilcarbon sequestration (Steiner 2008).

Biochar could be used as an energy carrier tomeet the energy demand of rural people. In manydeveloping countries, the charcoal produced fromwoody biomass is directly used in industry. On theother hand the biochar produced from fibrous orlight density biomass need to be strengthened byadding binder in a briquetting machine.Charcoalbriquettes can be used as fuel in rural houses forcooking, laundering and in boilers in teashops andbigger sized stoves in small hotels(Sugumaran andSeshadri 2010).Cooking tests conducted using anon-pressurized cooker (Sarai cooker, ARTI) showsthat 200-250g of briquettes is enough to cook foodin about 45-60 minutes with stable heat for 2 hours.Low density charcoal briquettes like beehivebriquettes, produced from charcoal and mud, canbe burnt smokeless for 3 hours (Mandal et al. 2012)

Biochar has been produced from different cropresidues and their effects on soil properties and cropproductivity have been studied by earlierresearchers (Major et al. 2010; Yao et al. 2011; Penget al. 2011) but little information is available forconversion of weed biomass to biochar. In NE India,weed biomass productivity of 20 t ha–1 has beenobserved. Hence, in this study an attempt has beenmade to find out properties of biochar fromcommon weed biomass such as Lantana camera

and Chromolaena odorata and characteristics ofbeehive briquettes made from this biochar. Theseweeds are abundant and naturally grown andsurvive in widely ranged climatic conditions andelevations. Their stems are non-thorny and becomesup to 15 cm thick as they grow older. Among manyuses of these weeds, fuel wood supplement is themajor one (Sankaran 2012; Francis 2000).

MATERIALS AND METHODS

Making of biochar

Three biomass namely, Lantana camera,Chromolaenaodorata and pine wood were collectedfrom nearby forest area of the ICAR ResearchComplex for NEH Region, Umiam and shreddedto pieces of less than 15 cm. Shredded pieces weresun–dried for two months before charring.Charringof all the biomass was carried out in a charring drumsimilar to one described by Nienhuys(2003).

The drum was placed on three bricks and theconical grate with chimney attachment placedinside. An entire load of chopped biomass wasstacked next to the drum.The drum was filledaround the funnel base with a loose layer of easilyburnable material and ignited. After the first portionof biomass material started to burn, another layerof biomass material was added, covering theburning layer.The chimney extension was thenplaced on top of the inner chimney.More biomasswas placed onto the fire, avoiding that the fireextinguishes. The white smoke escaped throughthe chimney.The entire drum was gradually filledwith the biomass, leaving sufficient space for smoketo escape. When the smoke started turning fromwhite (containing water) to light grey and blue, theadditional chimney pipe was removed and the lidwas placed on the drum. The gutter was filled withwater.The fire slowly extinguished inside the drumand the biomass was charred in about two hours.The drum was cooled down for few hours beforetaking out the biochar.

Making of briquettes

Beehive briquettes were made using finelypowdered biochar sieved through 5 mm sieve andmud as binder. In addition to binding, mud alsoacted as a burning controller. It reduces the rate ofburning. After mixing charcoal and mudin 2:1 ratiov/v, 250 ml of water was added to make the pastesoft enough to hold the structure. A mould withoverall dimension of 400 × 100mm was used tomake the briquettes. The mould consisted of threeparts: a) cylinder, b) base plate fitted with 21 rodsand c) cover plate. Cylinder’s diameter was 145mmand height 85mm. Base plate had total 21 rods of12mm diameter and 95 mm height welded on it.Cover plate had same number of holes havingdiameter little higher than that of rods so that itcould move through the rods on base plate. Afterputting cover plate and cylinder on base plate, thebiochar and mud dough was put into the cylinderand the whole unit was beaten on ground to increasecompaction of the material. Then the cylinder andcover plate were pulled out of the base plate alongwith the newly formed briquette. It was placedupside down on ground and the cover plate waspressed to release the briquette. Thus, the dimensionof each briquette was 145mm in diameter and85mm in height which perfectly fits in a briquettestove. Raw briquettes were allowed to dry in open



10

air as well as in sunlight for two weeks (Mandal etal. 2012).

Proximate analysis

Proximate analysis of biochar and briquettes wascarried out following the process described byMcLaughlin (2010) for characterization of biochar.Approximately 15g of sample was kept at the tempof the 150°C for 48 hours to determine the moisturecontent. For determination of volatile matter content10g of sample was kept in covered crucible andput inside a Muffle Furnace at the temperature of400°C for 30 minutes. To determine the ash content,the sample was put inside a Muffle Furnace at atemp of 550°C of 30 minutes. Residual carboncontent was calculated by subtracting the amountof moisture, ash and volatile matter from the totalweight. Calorific value was determined using abomb calorimeter operating under standardconditions. About 1g sample was used for eachexperiment and was replicated three times (ASTMD-4809).

Combustion test

A test platform was fabricated using mild steelflats and wire mesh to carry out the combustiontest. A single briquette was placed on the centre ofthe steel wire mesh. The platform with briquettewas placed on an electronic digital balance withleast count of 0.1g to record the weight loss in everytwo minute interval over the burning period. Eachbriquette was ignited by placing it over an electricheater for 5 min and allowed to burn until thetemperature becomes less than 100°C. Smoke ofburning was extracted using the extraction hoodmethod (Ballard and Jawurek 1999). Temperaturewas recorded in every two minutes by a digitaltemperature indicator connected with a K–typethermocouple placed 50 mm above the base of thefire. Height of a cooking pan over an oven does notexceed this height. The temperature indicator hadan accuracy of 1°C.

RESULTS AND DISCUSSION

Biochar production efficiency

Biochar conversion efficiency of the portablekiln for three biomassesis presented in Table 1.Charring efficiency ranged between 18.34 and34.28%. The highest charring efficiency was

observed for pine wood which was due to the lowermoisture content. In a conventional kiln, themoisture content of the feed strongly affects thereaction time and charcoal yield. More feed mustbe burnt to dry the remainder (prior tocarbonization) when the feed is very wet. Moisturecontents of 15–20% are satisfactory for most woodkilns, which often require drying of the wood feedfor 6–18 months (Antal and Gronli 2003). Thelower biochar yield was observed in case ofChromolaena which might be due to the higherinitial moisture content and leafy nature of biomasswhich burnt immediately.

Characteristics of biochar

Properties of the biochar derived from threebiomasses are depicted through Fig. 1. Biochar fromall three biomasses had almost equal moisturecontent. Volatile matter was the highest inChromolaena biochar (30.49 %) and the lowest inpine wood biochar (14.98 %). Ash was the highestin Lantanabiochar (12.41 %) and the lowest inChromolaenabiochar (8.29 %). Carbon content ofpine wood biochar (75.82 %) was the highestfollowed by Lantana (65.99 %) and Chromolaena

Table 1: Biochar conversion efficiency of

different biomass

Biomass Biomass Char Charringmoisture moisture efficiency content content (%)(wb, %) (wb, %)

Lantana camera 21.36 5.44 27.72

Chromolaena odorata 21.73 5.22 18.34

Pine wood 20.60 6.59 34.28

Fig. 1: Properties of biocharmade from three

biomasses



11

biochar (61.22 %). Both the weed biomass hadhigher carbon content than the biochars derivedfrom digested and undigested sugar beettrailingsbut lesser than wood biochar (Major et al. 2010;Yao et al. 2011).

Characteristics of briquettes

Average temperature profiles of briquettes madefrom three types of biochar are shown in Fig. 2.Good combustion temperatures in the degassingphase and slow rate of temperature decline in thecarbonization phaseof burningis ideal forcookingand heating purposes (Smit and Meincken 2012).Beehive briquette of Lantana biochar showedcomparable temperature with pine wood biocharbriquette in degassing phase. The highesttemperature attained by Lantana and Chromolaena

biochar briquette was recorded as 553°C and 437°Cwhich was lesser than pine wood biochar briquetteby 19 and 135 °C, respectively.

Duration of burning of Lantana biocharbriquette was 133 min, which was 10 min lesserthan the pine wood biochar briquette and 4 minlesser than Chromolaena biochar briquette. It showsthat all briquettes burn for almost 2.5 hours whichis sufficient time for cooking three items ineveryday meal. Calorific value of briquette madefrom Lantana and Chromolaenabiocharwas 18.6and 18.1 MJ kg -1 which was lesser than that ofpine wood biochar briquette by 0.8 and 1.3 MJ kg-1, respectively.

CONCLUSIONS

Biochar produced from two weed biomasses:Lantana camera and Chromolaena odorata in aportable metallic kiln had similar characteristicswith biocharproduced from pine wood. Theconversion efficiency of biomass of Lantana andChromolaena into biochar was 27.72 and 18.34%,respectively whereas that of pine wood was 34.28%.Carbon content in biochar obtained from Lantana

(65.99%) and Chromolaena (61.22%) was lesserthan the pine wood biochar (75.82%). The beehivebriquettes made from these three biochars recordedaverage burning time from 133 to 143 minutes witha peak temperature range of 437°C to 572°C. Thehighest burning time and temperature was recordedin case of pine wood biochar briquettes. Thecalorific value of beehive briquettes made fromLantana and Chromolaena biochar was comparablewith pine wood biochar briquettes.

REFERENCES

Lehmann J(2007). Bio-energy in the black. Front EcolEnviron5(7): 381–387

Baldock W J, Smernik R J(2002). Chemical composition andbioavailability of thermally altered Pinusresinosa (redpine). Org Geochem3(9): 1093-1109

Lehmann J, Gaunt J, Rondon M (2006). Bio-char sequestrationin terrestrial ecosystems – a review. Mitigation AdapStrategies Global Change 11: 403-427

Lal R (2009). Challenges and opportunities in soil organicmatter research. Eur J Soil Sci 60: 158–169

Steiner C (2008). Biocharcarbon sequestration. Athens. http://www.biochar.org/joomla/ images/stories/Steiner %20Chapter % 2017 % 202009.pdf. Accessed 30 Jan 2012

Dennis (2010). ArtiSarai Cooker, http://arti-africa.org/2010/07/arti-sarai-cooker/. Accessed 13 Jan 2013

Sugumaran P, Seshadri S (2010). Biomass charcoal biquetting,Shri AMM MurugappaChettiar Research Centre,Taramani Chennai, India, pp. 1–22. http://www.amm-mcrc.org/publications/Biomass Charcoal Briquetting_English.pdf. Accessed 13 Jan 2013

Mandal S, Kumar A, Singh RK, Ngachan SV (2012).Evaluation of composition, burn rate and economyBeehive Charcoal Briquettes.Int J AgricEng 5(2): 158-162

Sankaran K(2012). V. Lantana Camera, Kerala Forest ResearchInstitute, Peechi, Kerala, India. www.fao.org/.../13375-06ba52ce294a4e15f8264c42027052db0.pdf. Accessed22 Jan 2013

Francis JK (2012).Forestry Research, U.S. Department ofAgriculture, Forest Service, International Institute ofTropical Forestry, JardínBotánico Sur, 1201 CalleCeiba,San Juan PR

Fig. 2: Temperature profile of briquettes made

from three biochars



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Nienhuys IS (2003). The beehive charcoal briquette stove inthe Khumbu Region, Nepal. http://www.repp.org,Accessed 12 June 2011

McLaughlin H (2010). Characterizing biochars prior toaddition to soils–Version I. http://cees.colorado.edu/biochar_characterization.html,Accessed 10 May 2011

ASTM D-4809. Standard Test Method for heat of combustionof liquid hydrocarbons fuel by bomb calorimeter,American Society for Testing and Materials, WashingtonDC, USA

Yao Y, Gao B, Inyang M, Zimmerman AR, Cao X,Pullammanappallil P, Yang L (2011). Biochar derivedfrom anaerobically digested sugar beet tailings:Characterization and phosphate removal potential.BioresTech 102: 6273-6278

Major J, Rondon M, Molina D, Riha SJ, Lehmann J (2010).Maize yield and nutrition during 4 years after biochar

application to a Colombian savannaoxisol. Plant Soil333:117-128

Peng X,Ye LL, Wang CH, Zhou H, Sun B (2011). Temperatureand duration-dependent rice straw-derived biochar:Characteristics and its effects on soil properties of anUltisol in southern China. Soil Tillage Res 112:159-166

Ballard-TremeerG, Jawurek HH(1999). The hood method ofmeasuring emissions of rural cooking devices.BiomassBioenerg16:341-345.

Antal J, Gronli(2003). The art and science and technology ofcharcoal production, Hawai Natural Energy Institute,Hawai, AmericanChemSoc, p:1619-1640

Smit HC, Meincken M(2012). Time/temperature combustionprofiles of various wood-based biofuels. BiomassBioenerg 39: 317-323



13

Incidence of Putative Virulence Factors and Antimicrobial

Resistance in Aeromonas caviae Isolated from Livestock

in Northeast India

K.L PRASHANT¹, S. GHATAK²*, A. KUMAR¹, K.N. BHILEGAONKAR¹, S. DANDAPAT¹,A. SEN², I. SHAKUNTALA², K. PURO², S. DAS², R. PEGU², A. KARAM²,A. AHUJA², U. BHATTACHARJEE², L. MINAKSHI SINGHA², T. K. DEY²,

A. CHAKRABORTY², A. DUTTA².

ABSTRACT

Processing of 172 rectal swab samples comprising swabs from cattle (n = 26), pigs (n = 127) and dogs(n = 19) for isolation of Aeromonas spp. revealed incidence of 0%, 10.5% and 3.9%, respectively.Overall incidence was 4.06%. Identification of isolates through automated ID/AST system (Phoenix100) revealed all isolates belonging to A. caviae. Determination of virulence potential by haemolysinassay and lecithinase production indicated that all canine isolates were haemolytic and 50% of themproduced lecithinase, while porcine isolates were neither haemolytic nor lecithinase producing.Detection of three virulence genes (AHCYTOEN, cytotonic enterotoxin, and aerolysin) throughpolymerase chain reaction revealed all isolates of canine origin and 80% isolates of porcine originharboured the AHCYTOEN gene, 50% of the canine isolates and 40% of swine isolates possessedcytotonic enterotoxin gene, 50% of the canine isolates and 20% of the porcine isolates 40% carriedthe aerolysin gene. Determination of antimicrobial resistance among the isolates indicated widespreadresistance against a number of antimicrobials including penicillin, ampicillin, cephalexin, cefazolin,cefoxitin and nalidixic acid. Multiple antibiotic resistance was also common. Results of the presentstudy highlighted the incidence of virulent, drug resistant A. caviae isolates in canines and pigs fromnortheast India with possible risk of human infection or contamination of food and water from thesesources.

Keywords: Aeromonas, Virulence, Incidence, Drug resistance, PCR, Canine, Porcine.

1. IVRI, Izatnagar, India.2. ICAR RC for NEH Region, Umiam, Meghalaya, India* Corresponding author’s E-mail: [email protected]

INTRODUCTION

Aeromonas species are gram-negative,cocccobacillary, non-spore forming, motile,facultatively anaerobic organisms that are alsocatalase and oxidase positive (Abott et al. 2003).Though these organismd are widely distributed innature, they are also known to cause a number ofinfections in humans and animals (Janda and Abott2010; Evangelista-Barreto et al. 2010).

As with other bacterial pathogens, the ailmentscaused by aeromonads are linked to a number ofvirulence properties including aerolysin, hemolysin,enterotoxins, cytotoxins, adhesins, extracellularlipase, etc. (Cahill 1990; Janda et al. 2002).

Though many previous researchers documentedincidence and virulence properties of Aeromonas

spp. in humans (Janda and Abott 2010; Evangelista-Barreto et al. 2010; Messi et al. 2003) and too someextent from animals (Gray 1984; Gray and Stickler1989; Figura and Marri 1985), there is paucity ofsimilar literature corresponding to animalsespecially from India.

In recent years development of resistant ormultidrug resistant pathogens has become a majorproblem in India and many countries (WHO 2013).Bacterial pathogens, that are capable of infectingboth humans and animals are considered majoroffender for the origin of antibiotic resistance inthe environment (Allen et al. 2010). Since




14

Aeromonas spp. has been implicated in human andanimal diseases, and many members of theorganisms are inherently resistant to beta-lactamantibiotics, they may play important role inemergence of antimicrobial resistance. In India,antimicrobial resistance of Aeromonas spp. havebeen studied by previously (Thayumanavan et al.2003) though these studies involved food isolatesand reported qualitative data only.

Considering the gaps in the scientific data onvirulence potential and drug resistance profiles ofaeromonads from animal sources, present study wasundertaken to assess the incidence, virulenceproperties and antimicrobial resistance patterns ofAeromonas spp. isolated from domestic animalsfrom north-eastern part of India.


Sampling

A total of 172 rectal swab samples werecollected aseptically from various regions ofMeghalaya and Assam over a period of October toFebruary months (29/10/12 to 3/2/13). Samplescomprised of faecal swab from cattle (n = 26), pigs(n = 127), dogs (n = 19). Of the 26 total animalsampled 20 (76.92%) cattle were healthy and 6(23.07) % out of which were diarrhoeic; of the 127isolates from rectal swab of pigs 13(10.23%) werehealthy and 114(89.76%) were diarrhoeic. For dogs,the diarrhoeic cases comprised 18(94.73%) while1(5.26%) were healthy canine subjects. Sampleswere shipped to laboratory immediately aftercollection under refrigeration temperature and wereprocessed immediately. In no case processing ofsamples were delayed more than 24 h and till thenthey were stored in the laboratory at 2-8º C.

Isolation and identification of Aeromonas species

Collected samples were processed for isolationof Aeromonas spp employing Alkaline PeptoneWater, pH 8.6 (APW, HiMedia, India) AmpicillinDextrin Agar (ADA) containing ampicillin @ 10mg / ml as described previously (Ghatak et al.2009). Briefly, the samples were enriched for 16 –18 h at 37 ºC followed by selective plating on ADA.Plates were incubated at 37ºC for 18 - 24 h. Smoothhoney drop yellow colonies that were negative foroxidase reaction along with gram negative short

coccobacillary morphology were presumptivelyidentified as Aeromonas spp. Suspected isolateswere saved on fresh nutrient agar (Hi-media, India)slants and were further processed for confirmationand speciation. Confirmation and speciation ofpresumptive isolates were undertaken by acombination of conventional (Carnahan et al. 1991)and automated identification systems (Phoenix TM

100, Becton Dickinson, Singapore).

Haemolysin production

Aeromonas isolates were examined for theirability to produce haemolysin on 5% Sheep BloodAgar as described previously (Gerhardt et al. 1981;Ghatak, 2005) with suitable modifications. Tenmicrolitres of overnight grown broth cultures ofAeromonas isolates with OD A

600 between 0.5 –

0.6 were spotted aseptically onto blood agar platescontaining 5% defibrinated sheep blood. Plateswere incubated for 24 – 48 h at 37 ºC. Productionof haemolysin by an isolate was indicated byappearance of clear or opalescent zone around thecolony.

Production of lecithinase

Lipase production by the isolates was estimatedon Egg Yolk Agar containing 5% sterile egg yolkemulsion as described previously (Anguita et al.1993). In short the method involved spotting of 10µl of broth cultures of isolates (OD A

600 0.5 – 0.6)

onto 5% egg yolk agar followed by incubation at37ºC for 24 – 48 h. Expression of lecithinase wasobserved as a zone of opalescence around thespotting site at the end of incubation period.

Detection virulence genes by polymerase chain

reaction (PCR)

Aeromonas isolates were characterized for threevirulence genes namely, AHCYTOEN (amultivirulence gene that included mice lethality,haemolysin production, enterotoxigenicity andcytotoxicity), cytotonic enterotoxin, and aerolysin(Kingombe et al. 1999; Nam et al. 2007; Granumet al. 1998) (Table 1).

PCR for AHCYTOEN gene

Templates for PCR was prepared by boiling ofovernight grown broth cultures of isolates for 15minutes followed by snap chilling on crushed icefor 20 minutes. The lysate was centrifuged briefly



15

at 10000 g for 4 minutes and the supernatant wasused as template for subsequent PCR reaction. Foreach PCR run templates were prepared afresh.

PCR assay for detection of AHCYTOEN genewas standardized as described previously byKingombe et al (1999) with necessarymodifications. The reaction mixture (20 µl) wasoptimized with 10µl of 2 X PCR master mix(Fermentas MBI), 10 pmol each of forward andreverse primers, 6µl of nuclease free water and 2µlof DNA template.

Thermocycling conditions for AHCYTOENgene comprised of following: an initial hold of 4minutes at 94°C, denaturation at 94°C for 45 s,annealing at 60°C for 30 s, extension at 72°C for30 s for a total of 35 cycles and a final extension of72°C for 3 minutes. The polymerase chain reactionswere carried out using a DNA thermal cycler withheated lid (iCycler, Bio-Rad, Germany). All PCRruns included appropriate negative control withDNA blank and were repeated at least thrice toensure reproducibility of the assay.

Following electrophoresis products wereelectrophoresed through 1.5% agarose gel with 1XTris-Acetate EDTA (TAE) buffer under electricalfield strength of 6V/cm (Sambrook et al. 2001).Each run was accompanied with molecular weightmarker of suitable range. Upon completion of therun, amplicons were visualized under UVillumination in a gel documentation system (DNRMiniLumi, Israel).

PCR for cytotonic enterotoxin gene

PCR for cytotonic enterotoxin gene wasoptimized as reported by Granum et al. (1998) withnecessary adaptations. In short, the reaction mix

was optimized with 10 pmol each of forward andreverse primers and 1 µl of template DNA preparedby boiling and snap chilling as described inpreceding section. Thermocycing conditionsinvolved denaturation at 94ºC for 45 s, annealingat 61ºC for 30 s, primer extension a 72ºC for 45 sfor 30 cycles and a final extension step at 72ºC for3 minutes. Appropriate PCR controls were includedin each run. Finally products were electrophoresedin 1.5% agarose gel and visualized under UVillumination.

PCR for aerolysin gene

Similar to AHCYTOEN and cytotonicenterotoxin gene, PCR methodology described byNam et al (2007) was adapted suitably for aerolysingene. Reaction mix contained 10 pmol each offorward and reverse primers and 1.5µl of templateDNA. PCR run conditions were optimized withdenaturation at 94ºC for 1 minute, annealing at 62ºCfor 40 s, primer extension a 72ºC for 1 minute for30 cycles and a final extension step at 72ºC for 3minutes. On completion of run, products wereelectrophoresed, visualized under UV andphotographed.

Antimicrobial susceptibility testing and

determination of Minimum Inhibitory

Concentration (MIC)

Antimicrobial susceptibility tests along withdetermination of MIC of the isolates wereperformed using Phoenix TM 100 automated ID/ASTsystem employing NMIC/ID 55 panel. The panelcontained following antimicrobials- amikacin,amoxicillin/clavulanate, ampicillin, aztreonam,cefazolin, cefepime, cefoperazone/sulbactam,

Table1: PCR primers for detection of virulence genes of Aeromonas isolates

Target gene Primer sequence Product Annealing Referencesize (bp) temperature

AHCYTOEN Forward: 5’- 232 60°C Kingombe et al.GAGAAGGTGACCACCAAGAACA- 3’ (1999)Reverse: 5’-AACTGACATCGGCCTTGAACTC-3’

Cytotonic Forward: 5’- 482 64°C Granum et al.enterotoxin GCAAGTGTTCTAGTCTTTCCG-3’ (1998)

Reverse: 5’-ACCTGCCAAAGTTTGCTGTGA-3’

Aerolysin Forward: 5’- 417 60°C Nam et al.GAGCGAGAAGGTGACCACCAAGAAC-3’ (2007)Reverse: 5’-TTCCAGTCCCACCACTTCACTTCAC-3’



16

cefotaxime, cefoxitin, ceftazidime,chloramphenicol, ciprofloxacin, colistin,gentamicin, imipenem, levofloxacin, meropenem,piperacillin, piperacillin/tazobactam, tetracycline,and trimethoprim/sulfamethoxazole. The results ofMIC were interpreted as per CLSI and EUCASTguidelines along with BD XpertTM rules of theEpicentreTM software.


Incidence of aeromonads

Out of 172 rectal swab samples collected fromcanines, swine and bovines, 7 samples yieldedAeromonas spp. indicating overall incidence of4.06%. All isolates were identified as A. caviae withno other species detected in the course of the presentstudy. Incidences among canine and porcinesamples were 10.5% and 3.9%, respectively. NoAeromonas could be isolated from cattle samples.

Of these seven isolates, two (28.6 %) originatedfrom canines and rest five (71.4 %) were of swineorigin (Table 2). Two of the canine subjects fromwhich isolation of Aeromonas was possible hadhistories of elevated body temperature, anorexia,vomition and dysentery. On the other hand all swinesubjects wherefrom aeromonads could be isolated,were normal healthy animals with no signs ofillnesses.

Virulence factors

Of the seven isolates of A. caviae, two (28.6%)isolates caused haemolysis of SRBC on 5% sheep

blood agar. While both these isolates originatedfrom canines, none of the isolates from pigs werehaemolytic of 5% sheep blood agar (Table 2).

Production of lecithinase was assessed on eggyolk agar, which indicated that only one isolate(14.3%) of canine origin produced lecithinaseobserved as zone of lecithin precipitation aroundthe colonies of the isolate (Table 2).

Detection of virulence genes

The PCR assays optimized for detection of threevirulence genes (AHCYTOEN, cytotonicenterotoxin, and aerolysin) proved to be efficacious,as all three assays yielded PCR amplicons ofexpected molecular weight (Fig. 1, 2 & 3).

Majority (85.7%) of the A. caviae isolatespossessed AHCYTOEN gene. All isolates of canineorigin and 80% isolates of porcine origin harbouredthe AHCYTOEN gene. On the other hand, cytotonicenterotoxin gene was present in 42.9% of isolates

Table 2: Sources and virulence properties of A. caviae isolates

Isolate code Source Virulence factors Virulence genes

Haemolysis of Lecithinase AHCYTOEN Cytotonic Aerolysinsheep RBC production enterotoxin

ARSDG6GH Canine +ve -ve +ve +ve +veARSDG10GH Canine +ve +ve +ve -ve -veARSPG4a Swine -ve -ve -ve -ve -veARSPG5a Swine -ve -ve +ve +ve -veARSPG38a Swine -ve -ve +ve +ve -veARSPG39a Swine -ve -ve +ve -ve +veARSPG50a Swine -ve -ve +ve -ve -ve

Canine: 28.6% Haemolytic: Lecithinase AHCYTOEN Cytotonic AerolysinSwine: 71.4% 28.6% +ve: 14.3% +ve: 85.7% enterotoxin +ve: 28.6%

+ve: 42.9%

+ve = presence, -ve = absence

Fig. 1: PCR amplification of Aerolysin gene (417)

from Aeromonas caviae isolates, Lane 1: Molecular

weight marker (100 bp); Lanes 4, 6, 8: A. caviae

isolates with positive amplifications (417 bp); Lane

8: Positive control (A. hydrophila ATCC 35654);

Lane 9: Negative control



17

with 50% of canine isolates 40% of the swineisolates harbouring the gene. PCR for aerolysingene indicated that 28.6% of the isolates yieldedpositive amplification. Aerolysin gene was detectedin 50% of the canine isolates and 20% of the porcineisolates (Table 2).

Antimicrobial resistance

The strains of A. caviae isolated from bothcanine and porcine were examined for theirresitance pattern against 23 antimicrobialsincluding determination of MIC values employingBD PhoenixTM 100 automated ID/AST system.

Results revealed that all isolates were resistantto 6 antimicrobials (penicillin, ampicillin,cephalexin, cefazolin, cefoxitin and nalidixic acid).High degree of resistance (71.5%) was also notedagainst tetracycline with most observed MIC being>8 µg / ml.

Most effective antimicrobials as revealed in thestudy were amikacin, imipenem, meropenem,levofloxacin and ciprofloxacin with 100%sensitivity for all isolates. Among penicillin grouppiperacillin-tazobactam (most prevalent MIC - <=4/4 µg/ml) and amoxicillin-clavalunate (mostprevalent MIC - 8/4 µg/ml) combinations were mosteffective, with 14.3% isolates being resistant tothese antimicrobials. Similar sensitivities were alsoobserved for aztreonam (monobactam), thirdgeneration cephalosporins (cefotaxime,ceftazidime) and gentamicin (aminoglycoside).

Compared to isolates of porcine origin, isolatesof canine origin were clearly more resistant with41-67% antimicrobials rendered ineffective.Isolates of porcine origin, on the other hand,revealed uniform sensitivities to a number ofantimicrobials including amoxicillin-clavulanate,piperacillin-tazobactam, azetreonam, cefotaxime,ceftazidime, amikacin, imipenem, meropenem,levofloxacin, ciprofloxacin and gentamicin withMIC values of 8/4 µg /ml, <=4/4 µg /ml, <=2 µg /ml, <=4 µg /ml, <=0.5 – 2 µg /ml, <=8 µg /ml, <=1µg /ml, <=1 µg /ml, <=1 µg /ml, <=0.5 µg /ml and<=2 µg /ml, respectively (Table 3).

All isolates were multidrug resistant withresistance recorded for >= 3 antimicrobials. Overallresistance rate varied from 27 – 67%.

The present study reports incidence, virulenceproperties and antimicrobial resistance patterns ofa collection of Aeromonas (A. caviae) isolates thatwere obtained from canines and porcines ofnortheast India (Assam and Meghalaya).

The Aeromonas species isolated from rectalswabs were identified at phenotypic level byintegrating an automated system BD PhoenixTM 100(Singapore). This approach proved to be useful interms of rapidity and convenience with an averageidentification / confirmation time of 12 h.

Overall incidence of Aeromonas species was4.06%, which is slightly in variation with theprevious report by Ghatak et al. (2009) whoreported an incidence of 4.35% in canine species.This minor difference may be attributed todifference in geographical location and differencein host species studied. All isolates obtained fromcanines and pigs were identified as A. caviae. Thiswas rather unusual because previous worksdocumented variety of species of aeromonads fromanimal sources (Gray and Stickler 1989; Ghatak etal. 2009; Ghengesh et al. 1999). According to

Fig. 2: PCR amplification of AHCYTOEN gene

(232) in Aeromonas caviae isolates, Lane M:

Molecular weight marker (100 bp); Lanes 1, 2, 3, 4,

5, 6, 7: A. caviae isolates with positive

amplifications (232 bp); Lane 8: Positive control

(A. hydrophila ATCC 35654); Lane 9: Negative

control

Fig. 3: PCR amplification of Cytotonic Enterotoxin

gene (482bp) in Aeromonas caviae isolates, Lane M:

Molecular weight marker (100 bp); Lanes: 2, 3, 4,

6: A. caviae isolates with positive amplifications

(482 bp); Lane 8: Positive control (A. hydrophila

ATCC 35654); Lane 9: Negative control.



18

researchers, A. hydrophila and A. caviae were mostprevalent in clinical samples (Figueras 2005; Jandaand Abbott 1998, 2010). Similar observations werealso revealed in the present study with all isolatesfrom canine clinical cases were of A. caviae.Incidence of aeromonads in porcine samples (rectalswabs) were considerably lower (3.93%) than 9.6%(11 of 115) as reported previously (Gray 1984).However, in contrast to the report of Gray andStickler (1989), no aeromonads could be isolatedfrom bovine samples.

It has been reported that Aeromonas specieswhich were isolated from the species of dog andcat (Boynukara et al. 2002; Ceylan et al. 2003;Ghenghesh et al. 1999) may cause fatal septicaemia

in dogs and puppies (Andre fontaine et al. 1995;Zdovc et al. 2004). In the present study the caninesubjects from which A. caviae were isolated,suffered with clinical symptoms of anorexia,vomition, gastroenteritis. Moreover, for these casesno conclusive diagnosis could be established.Therefore, though it could not be ascertained thatwhether the symptoms were due to A. caviae

infection or not, present findings indicate possiblerole of aeromonads in gastrointestinal illnesses ofcanines under study.

All isolates of canine origin were haemolyticwhile 20% of porcine isolates were so. This findingis in line with previous report by Ghengesh et al(1999).

Table 3: MIC values and drug resistance patterns of A. caviae isolates of canine and porcine origin

Antimicrobials MIC values for A. caviae isolates Resistance(%)

Canine isolates Swine isolates

ARSDG6GH ARSDG10GH ARSPG4a ARSPG5a ARSPG38a ARSPG39a ARSPG50a

PenicillinsAmpicillin >16 R >16 R >16 R >16R >16 R >16 R >16 R 100%Amoxicillin- >16/8 R <=4/2 S 8/4 S 8/4 S 8/4 S 8/4 S 8/4 S 14.28%ClavulanatePiperacillin- >64/2 R <=4/4 S <=4/4 S <=4/4 S <=4/4 S <=4/4 S <=4/4 S 14.28%TazobactamTicarcillin- >8 R <=8/2 S 16/2 R <=8/2 S 16/2 R <=8/2 S <=8/2 S 42.85%ClavulanateMonobactamsAzetreonam (ATM)>16 R <=2 S <=2 S <=2 S <=2 S <=2 S <=2 S 14.28%CephahalosporinsCephalexin >16 R >16 R <=4 R 8 R >16 R >16 R >16 R 100%Cefazolin >16 R >16 R <=4 R 8 R >16 R >16 R >16 R 100%Cefotaxime >32 R <=4 S <=4 S <=4 S <=4 S <=4 S <=4 S 14.28%Cefoxitin >16 R <=4 R <=4 R <=4 R <=4 R <=4 R <=4 R 100%Ceftazidime >16 R <=0.5 S <=0.5 S 1 S 2 S 2 S 1 S 14.28%CarbapenemsImipenem <=1 S <=1 S <=1 S <=1S <=1 S <=1 S <=1 S -Meropenems <=1S <=1 S <=1 S <=1 S <=1 S <=1 S <=1 S -AminoglycosidesAmikacin <=8 S <=8 S <=8 S <=8 S <=8 S <=8 S <=8 S -Tobramycin >8 R >8 R 8 R <=2 S <=2 S <=2 S <=2 S 42.85%Gentamicin <=2 S >8 R <=2 S <=2 S <=2 S <=2 S <=2 S 14.28%Tetracyclines >8 R >8 R <=2 S >8 R >8 R >8 R <=2 S 71.48%FluoroquinolonesNalidixic acid >16 R >16 R >16 R >16 R >16 R >16 R >16 R 100%Levofloxacin <=1 S <=1 S <=1 S <=1 S <=1 S <=1 S <=1 S -Ciprofloxacin <=0.5S 1 S <=0.5 S 1S 2 I 2 I <=0.5 S -Trimethoprim- >2/38 R >2/38 R >2/38 R <0.5/9.5S 1/19 S 1/19 S <0.5/9.5S 42.85%SulphamethoxazoleMiscellaneousColistin <=1S <=1S <=1S <=1S <=1S <=1S <=1SNitrofurantoin 32S <=16S <=16S <=16S <=16S <=16 S <=16S -Ineffective 67% 41% 37% 27.27% 32% 27.27% 23%antimicrobials

(%)

Highest MIC breakpoints- mentioned resistance in bold.



19

Lipase play important role in bacterial virulencesince insertion mutants for the lipase gene plc

reduces the lethal dose (LD50

) in mice and fish(Anguita et al. 1993; Merino et al. 1999). In thepresent study, 50% of canine isolates and none ofporcine isolated exhibited lipase activity indicatingvirulent nature of the canine isolates. However, theoverall lipase activity was lower than previousreport by Merino et al (1999).

Molecular characterization of isolates forvirulence genes indicated that most (85.7%) of theisolates harboured AHCYTOEN gene. This issomewhat in excess of the previous report byKingombe et al. (1999) who documented 58%incidence of the same gene. The higher incidencein the present study might be due to the clinicalnature of the isolates while Kingombe et al. (1999)reported the same for environmental isolates.

Incidence of aerolysin gene on the other hand,was somewhat lower (28.6% overall). Previousworkers recorded incidence of this gene in the rangebetween 20 – 84% (Ghatak 2005; Gonzalez-Rodriguez et al. 2002; Ottaviani et al. 2011).Therefore, results of the present study rest wellwithin reported range.

Possession of cytotonic enterotoxin gene byaeromonads is indicative of enterotoxigenicpotential (Janda and Abott 1998). In the presentstudy 42.9% of isolates harboured cytotonicenterotoxin gene which was contributed by 50%of canine isolates and 40% of swine isolates.However, the incidence of cytotonic enterotoxingene recorded in the present study was lower thanprevious reports with incidence range of 65 – 75%.(Granum et al. 1998; Abdullah et al. 2003; Ottavianiet al. 2011). This apparent anomaly may beattributable to the difference in the set isolatesstudied by various authors.

Emergence of drug resistant microbe is a globalconcern. Wide spread use of antibiotics for treatingbacterial diseases sub-therapeutic use of antibioticsin animal husbandry and aquaculture are heldresponsible for emergence of antibiotic resistance(WHO 2013). In developing countries includingIndia, the situation is more precarious due to lessstringent regulatory control of antibiotics withextensive use of antibiotics in animal husbandryand aquaculture (Vivekanandhan et al. 2002; WHO2000). In the present study, therefore, attempts weremade to document antibiotic susceptibility/resistance pattern of Aeromonas isolates that were

obtained from animal sources. All isolates weretested against a panel of 22 antimicrobial agents.

In a previous study (Overman and Janda 1999),reported antimicrobial resistance in clinical isolateswith resistance to ampicillin (94.9%), cephalexin(76.3%), Trimethoprim (37.3%), tetracycline(11.9%). However, the results of the present studyrevealed higher resistance to these antimicrobialswhich may be due to difference in previousexposure to these antimicrobials. Similarly,nalidixic acid resistance was higher in the presentstudy (100%) than that reported by Sinha et al.(2004) who recorded nalidixic acid resistance in54 – 62% isolates. Similar variation in incidenceof antimicrobial resistance among Aeromonas

isolates have been reported by previous researchersalso (Diker et al. 1984; Megraud 1986; Das andParanjape 1990; Jindal et al. 1993; Kienzle et al.2000).

A number of researchers have previouslyreported the MIC values for aeromonads (Ko et al.1998; Kim et al. 2011; Bakken et al. 1988).However, there have been no studies reporting thesame from animal isolates. Therefore the MIC dataof the present study could not be compared withprevious reports.

Though gastrointestinal infection of Aeromonas

is a self-limiting disease and antimicrobials areindicated for only severe and unresponsive casesof Aeromonas gastroenteritis (Phavichitr and Catto-Smith 2003), resistant strains of aeromonads asidentified in the present study do pose a clinicalchallenge.

Multiple antibiotic resistance furthercomplicates the situation. Previous researchers alsodocumented, multiple resistance in aeromonads(Vivekanandhan et al. 2002). In the present study,all isolates were multi-resistant with canine isolatesharbouring more resistance than swine isolates.This perhaps indicated greater antimicrobial usagein canine clinical cases compared to porcine cases.

CONCLUSIONS

The results of the present study reportedincidence of virulent, drug resistant A. caviae

isolates in canines and pigs from northeast Indiahighlighting possible risk of human infection orcontamination of food and water from thesesources.



20

ACKNOWLEDGEMENTS

First author is thankful to ICAR for financialassistance in the form ICAR JRF and to Director,ICAR RC for NEHR, Umiam for extendingsubsidized lodging during the study. All authors arethankful to Director, ICAR RC for NEHR andDirector, IVRI for providing necessary laboratoryfacilities.

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Microbial Biomass Nitrogen as an Index of N Availability in Acidic

Soils of North East India

L. J. BORDOLOI2*, A. K. SINGH1, MANOJ-KUMAR2, PATIRAM2, S. HAZARIKA2

ABSTRACT

A reliable estimate of soil’s nitrogen (N) supplying capacity is essentialto improve N fertilizer efficiencyand crop productivity.In the study reported here, we evaluated the utility of soil microbial biomass N(SMB-N) vis-à-visalkaline KMnO

4 extractable-Nas an index of N availability in acidic soils of northeast

India. These indices were evaluated based on their correlation with available N obtained through twostandard incubation methods viz., aerobic incubation (AI-N) and anaerobic incubation (ANI-N), andalso with dry matter yield, N concentration and N uptake (PNU) in maize (Zea mays L.). SMB-Ncorrelated significantly better with AI-N and ANI-N (r = 0.836** and 0.811** respectively) comparedto alkaline KMnO

4-N(r =0.394** and 0.548** respectively). Correlations of plant parameters were also

stronger with SMB-N (r=0.707** for PNU) than with alkaline KMnO4-N (r= 0.625**).Based on the

significantly stronger relationship of SMB-N with the standard biological indices and the plantresponses, we envisage SMB-N as a reliable index of N availability in acidic soils of northeast India.

Keywords: Biological incubation, Chemical extraction, Maize, N supplying capacity

1Nagaland University, Medziphema-797 106, Nagaland, India2ICAR Research Complex for NEH Region, Umiam-793 103, Meghalaya, India

INTRODUCTION

Nitrogen (N) is often the most limiting nutrientfor crop production in majority of the world soils,including those in India. To bridge the gap betweenplant N demand and available N in soil, supply ofthe nutrient from external sources is imperative.An accurate estimate of potentially available N insoil is therefore essential to ensure optimum cropyield and quality and also to minimize nutrient lossto environment that may result from overuse offertilizers. Among the numerous methods proposedfor assaying the N-supplying capacity of soils,biological methods (aerobic and anaerobicincubation)are considered to be most reliable. Theprecision of biological methods gets reflected mostoften in higher correlations of N availabilityestimates obtained through them with yield and Nuptake by plants. However, owing to tedious andtime consuming nature of these biological methods,they are not considered suitable for routineestimation of plant available N in soil. In pursuit ofdeveloping a rapid, yet reliable, index of soil Navailability, many chemical indices have been

proposed over time, but no single method hasperformed consistently enough to receive broadacceptance across a wide range of soils. In India,alkaline permanganate extraction procedure, asproposed by Subbiah and Asija (1956) and modifiedby Stanford (1978), has been the most preferredmethod of estimating available N in soils, includingthe acidic soils of northeast India. However,effectiveness of this method as a reliable predictorof N availability in the soils of this region has notbeen tested adequately. Furthermore,there arereports that indicate the poor relationship betweensoil N availability obtained through this method andplant responses. This necessitates the evaluation ofalkaline KMnO

4 extractable-N as a predictor of N

availability in acidic soils of northeast India.Soil microbial biomass nitrogen (SMBN) has

been successfully used by many researchers as areliable predictor of N availability (Hu and Cao2007; Sharifi et al. 2007). Carter and Macleod(1987) found SMBN to be closely related topotentially mineralizable N in soil (R2 = 0.94). Jinet al. (2007) also reported a good correlation ofSMBN (r = 0.665) with N mineralization potential





23

of soil and hence suggested its use as a biologicalindex of soil N availability. The relative ease ofdetermining SMBN in comparison to theincubation-based biological methods also makes ita better proposition for assessing soil N availability.However, there is serious dearth of informationregarding relationship between SMBN and otherestablished biological indices viz., aerobicincubation (AI) and anaerobic incubation (ANI).The existing knowledge on correlation of SMBNwith plant parameters (viz., dry matter yield, plantN content and N uptake (PNU) is also inadequate.In this context, the present study was undertakento evaluate the performance of soil microbialbiomass N (SMB-N) vis-à-vis alkaline KMnO

4

extractable-N as an index of N availability in acidicsoils of northeast India. The evaluation was madebased on their strength of correlation with theavailable N obtained through two standardincubation methods viz., aerobic incubation (AI-N) and anaerobic incubation (ANI-N), and also withdry matter yield, N concentration and N uptake(PNU) in maize (Zea mays L.).


Experimental soils

The soils used in the study were collected from20 representative sites in the state of Meghalaya,northeast India. Using the previously availableinformation, these sampling sites were selected toaccommodate a wide variation in soil properties,including total N, available N and organic C. Thebulk soils collected from 0-20 cm depth wereshipped to laboratory, air-dried and passed through2-mm sieve (0.5 mm for organic C) for furtheranalysis. Samples were analysed for initial physico-chemical properties as follows: soil pH wasmeasured with a glass electrode in a 1:2.5 (w/v)soil/water suspension; organic C by Walkey-Blackmethod (1934); total N by kjeldahl method(Bremner 1996); available N by alkaline KMnO

4

distillation method (Subbiah and Asija 1956);available P by Bray-II method (Bray and Kurtz1945). Exchangeable K and Na was determinedusing ammonium acetate extraction followed byemission spectrometry (Jackson 1973).Exchangeable Ca and Mg were determined byversene titration (Baruah and Barthakur 1999);

exchangeable-Al and acidity by neutral KClextraction method (Page et al. 1982) and cationexchange capacity (CEC) by sodium saturationmethod (Jackson 1973). Percent base saturation(PBS) was estimated as the proportion (%) of CECcontributed by exchangeable bases (Na, K, Ca, andMg). Percent sand, silt and clay were determinedby international pipette method (Piper1966). Somepertinent physico-chemical properties of theexperimental soils are shown in table 1.

Pot experiment

To work out the correlation between Navailability indices and the plant responses (drymatter yield, N concentration, and N uptake), a potexperiment was conducted with maize (Zea mays

L.) as a test crop. Maize seeds (Cv. RCM 1-1) weresown in plastic pots containing 7.5 kg ofexperimental soils with four replications. The plantwas harvested at the initiation of tasseling stage,and the dry matter weights were recorded after ovendrying at 70ºC for 48 hours. N concentration inmaize tops was estimated using micro kjeldahlprocedure (Jackson 1973) and the N uptake wassubsequently worked out.

Methods of assessing potentially available soil-

N (N availability indices)

The performance of SMBN as a predictor ofpotentially available soil N was assessed againsttwo biological incubation methods (as reference)and one of the most commonly used chemicalmethods as briefed below. Soil microbial biomassN (SMBN) was extracted using 0.5M K

2SO

4

following chloroform fumigation extractionprocedures (Anderson and Ingram 1993).

Aerobic incubation

The method involves estimation of the(exchangeable ammonium + nitrate + nitrite)-Nproduced when 10 g of soil mixed with 30 g ofquartz sand are treated with 6 ml of water andincubated at 30ºC for 14 days under conditionswhich ensure adequate aeration without loss ofwater (Keeney and Bremner 1966). Briefly, amixture of 10 g soil with 30 g quartz sand wasdistributed evenly over the bottom of a 250-mlbottle containing 6 ml of distilled water to bringthe moisture content to field capacity. The necksof the bottles were fitted with rubber stoppershaving a central hole, sealed tightly with an aeration



24

device, and incubated at 30 ±1ºC for 14 days.Thereafter, 100 ml of 2M KCl was added to eachbottle. The bottles were then fitted with solid rubberstoppers and shaken for one hour in a mechanicalshaker. Thereafter, bottles were allowed to standuntil the mixture settled and the supernatant liquidwas clear. Twenty ml aliquot of the supernatant wasadded to a 100-ml distillation flask. The amount of(NH

4+NO

3+NO

2)-N produced from the soil-sand

mixture during the incubation period wasdetermined from the NH

4-N liberated by the steam

distillation of this aliquot with 0.2g MgO and 0.2gDevarda alloy for 3.3 minutes. The mineralizable-N was calculated as the difference between amountof NH

4-N liberated after and before incubation.

Anaerobic incubation

The method involves incubation of a soil sampleunder waterlogged conditions in an enclosed testtube with minimum possible head space (Keeney1982; modified from Waring and Bremner 1964).Briefly, 12.5 ml of distilled water was placed in atest tube (16X150-mm) followed by addition of 5goven dry equivalent of soil. The test tubes werestoppered and incubated at 40±10C for 7 days.Thereafter, tubes were removed from the incubator,shaken briefly to mix the content, and the mixturewas quantitatively transferred to a 150-ml

distillation flask by washing with 15 ml of 4 MKCl solution. About 0.2 g of MgO was added tothe mixture and steam distilled for 4 minutes toestimate the amount of NH

4-N liberated. The initial

amounts of NH4-N present in soil were determined

by steam distillation of another sub-sample beforeincubation. The mineralizable N was calculatedfrom the difference between the results of these twoanalyses.

Alkaline permanganate extraction

The method described by Stanford (1978) wasfollowed for the extraction. Briefly, 1.0 g of air-dried soil was placed in a 100-ml distillation flask.Ten ml of 0.25 M NaOH containing 0.1g of KMnO

4

was added to the flask and the contents steamdistilled for 4 minutes. The liberated NH

4-N was

collected in a 50-ml Erlenmeyer flask containing 5ml of boric acid-indicator solution. The amount ofNH

4-N was determined by titration with standard

0.005 N H2SO

4. Another 1.0 g of soil sample was

treated with 10 ml of 0.25 M NaOH only, steamdistilled for 4 minutes and the liberated NH

4-N

trapped and estimated as mentioned above. TheNH

4-N produced by alkaline KMnO

4 oxidation was

calculated as the difference between results of thetwo analyses.

Table 1: Physico-chemical properties of the soils used in the study

Sample Sampling pH Sand Clay CEC Base SOC Total N Avail. N Avail. Avail.ID site (1:2.5) (%) (%) [Cmol Saturation (g kg-1) (mg kg-1) (mg kg-1) P

2O

5 K

2O

(P+) kg-1] (%) (mg kg-1) (mg kg-1)

S1

Nongpoh 4.90 65.44 25.61 12.50 21.28 7.1 1296.1 132.2 14.5 108.9S

2Sokhwai 4.50 60.96 29.71 14.80 23.91 17.1 1516.5 249.8 11.3 145.8

S3

Jirang 4.54 62.77 31.89 14.62 27.91 17.2 1876.8 208.1 8.6 113.6S

4Aphrewmer 4.96 68.53 21.46 11.00 23.50 10.2 1488.2 138.8 9.5 121.2

S5

Nongkrah 4.64 56.11 34.56 14.50 18.97 8.3 1425.2 166.5 10.3 124.8S

6Mawphru 4.89 66.34 28.09 13.50 19.70 11.7 1606.1 222.0 13.6 134.3

S7

Umsning 4.31 51.53 39.04 15.90 18.30 16.5 1421.1 235.2 6.6 151.6S

8Mawksiew 5.32 62.29 31.04 14.40 69.22 13.5 1219.2 214.5 10.0 136.4

S9

Killing 4.60 66.29 28.37 10.63 38.10 15.9 1704.5 203.7 15.3 137.9S

10Raitong) 4.39 49.01 37.65 19.20 13.02 18.2 1281.5 112.0 7.3 100.3

S11

Umiam 4.27 56.96 31.04 14.50 22.89 17.6 1538.2 102.3 6.0 102.8S

12Nongpoh 4.69 62.77 25.71 18.30 22.13 23.2 1705.3 251.8 17.0 152.2

S13

Umden 4.99 55.63 32.37 14.20 32.61 19.3 2014.0 223.4 14.9 158.5S

14Umrit 4.79 58.35 32.37 14.90 13.36 16.4 1333.2 184.6 14.9 138.1

S15

Mawhati 4.64 52.96 35.04 10.80 19.54 9.4 1188.5 95.8 8.8 84.3S

16Klew 4.69 74.08 21.92 9.90 56.56 13.2 1615.6 172.0 5.9 96.7

S17

Myrdon 4.70 63.68 28.37 10.10 19.91 12.5 1316.8 138.0 6.8 118.6S

18Umsning 5.05 51.63 34.04 10.60 43.39 12.2 1456.9 176.4 14.4 130.0

S19

Mawpun 4.56 50.29 33.71 13.10 45.27 8.6 1296.1 138.9 14.1 118.4S

20Mynsain 4.79 58.29 31.04 11.10 26.31 7.6 1108.8 120.3 12.8 94.1



25

Statistical analysis

Data were statistically analyzed using the SPSS16.0 statistical package (SPSS Inc., Chicago, IL,USA). Pearson’s correlation coefficient was usedto compare the correlation between chemical andbiological indices and the plant parameters;significance of these tests was considered at 0.05and 0.01 probability levels.


Characteristics of the soils and N-availability

indices

In this study, SMBN as an index of soil Navailability was evaluated against the biologicalincubation (aerobic and anaerobic) methods, whichare often used as the reference methods forpredicting N-supplying capacity of soils, and alsoagainst one of the most commonly used chemicalindex of soil N availability (alkaline KMnO

4-N).

The indices were further correlated with plantresponses (dry matter yield, percent N and plant N

uptake) which provide a more realistic assessmentof soil’s capacity to supply N to growing crops(Dalal and Mayer 1990). In general, the soils usedin the study showed large variability in N-supplyingcapacity as indicated by the differential responseof growth and N uptake by plants grown thereon(Table 2). Since dry matter yield of plant isinfluenced by too many factors other than availableN, plant N uptake (PNU) is taken as a more realisticindicator of N availability in soils (Sahrawat 1983;Hussain et al. 1984; Li et al. 2011). Thus, a largevariability in PNU ranging from 598 mg pot-1 (S

10)

to 1026 mg pot-1 (S12

) is indicative of the varyingN-supplying capacities of soils under study. OrganicC content of soils ranged between 7.1 to 23.2 g kg-

1, total N between 1109 to 2014 mg kg-1, clay contentbetween 21.92 to 39.04 %, CEC between 9.9 to19.2 Cmol (P+) kg-1, base saturation between 13 to57 %, and so varied the other soil properties aswell (Table 1).

Of the two biological methods of determiningsoil N-availability, anaerobic incubation (ANI), onaverage, yielded more value than the aerobicincubation (AI) (20.72 and 49.94 mg N kg-1 soil,

Table 2: Dry matter yield and N uptake by plant, and various indices of N availability in soil as

estimated by biological incubations and chemical extraction methods

Plant response Indices of available N in soil (mg kg-1)

Sample Dry matter N content N uptake AI-N ANI-N SMB-N Alk.ID yield (g pot-1) (%) (mg pot-1) KMnO

4-N

S1

72.5 0.87 631 9.74 34.56 11.18 107.4S

280.6 0.97 782 15.51 52.65 9.95 185.4

S3

75.6 0.91 688 12.98 35.11 15.77 226.0S

473.3 0.88 645 10.68 38.80 13.97 121.1

S5

72.0 0.86 619 10.29 35.18 11.66 144.6S

676.8 0.92 707 13.77 41.23 14.78 212.6

S7

83.3 1.00 833 36.95 79.68 23.17 182.1S

881.1 0.98 795 24.42 61.18 19.76 192.2

S9

82.6 0.99 818 24.83 65.54 12.22 200.3S

1070.4 0.85 598 9.23 26.18 9.31 89.4

S11

71.2 0.86 612 9.42 33.49 13.35 77.8S

1292.4 1.11 1026 78.30 107.66 32.92 149.3

S13

88.2 1.06 935 48.71 87.18 26.12 229.8S

1480.7 0.97 783 31.73 74.21 22.63 201.0

S15

70.1 0.84 589 9.39 28.59 12.38 72.4S

1678.9 0.95 750 14.66 39.44 13.29 154.6

S17

75.5 0.91 687 13.37 38.12 15.61 115.4S

1880.4 0.97 780 15.23 48.75 15.58 161.4

S19

74.7 0.90 672 12.69 36.18 12.79 97.7S

2074.6 0.90 671 12.50 35.07 12.91 116.9

Mean 77.7 0.93 723 20.72 49.94 151.9

Each datum is the average of four replications; AI-N – available-N through aerobic incubation; ANI-N – available-N throughanaerobic incubation; SMB-N: soil microbial biomass N



26

respectively). This is in conformity with the resultsobtained by Elkarim and Usta (2001). Greateramounts of mineralized N obtained under ANIcould be attributed to the fact that the losses ofammonia which may occur under AI were avoidedin the enclosed system of ANI. Also, highertemperature used in ANI (40ºC) than in AI (30ºC)might have resulted in higher values of mineralisedN (Bremner 1965; Keeney 1982). Out of all theindices under study, alkaline KMnO

4, on average,

extracted the highest amount of N (151.9 mg kg-1).Similar extracting ability of N by alkaline KMnO

4

was also reported by Nayyar et al. (2006) and Li etal. (2011). Soil microbial biomass nitrogen (SMBN)yielded the lowest values (15.97 mg N kg-1 soil).

Relationships between soil N-availability indices

and plant response

Correlations between all the pairs of soil Navailability indices were found significant (Table3). The highest coefficient of correlation (r =0.946**, p<0.01) was obtained between AI-N andANI-N the two standard indices of soil N-availability. The next stronger correlation observedwas that of SMBN with AI and ANI (r = 0.836**

and 0.811**, respectively). Interestingly, alkalineKMnO

4-N showed least correlations with AI-N and

ANI-N (r = 0.394** and 0.548**, respectively).

Table 3: Correlation coefficients (r) between

indices of soil N availability

AI-N ANI-N SMB-N Alk.KMnO

4-N

AI-N 1ANI-N .946** 1SMB-N .836** .811** 1Alk. KMnO

4-N .394** .548** .390** 1

*P < 0.05; **P < 0.01. AI-N: available-N through aerobicincubation;ANI-N:available-N through anaerobic incubation; SMB-N: soilmicrobial biomass N

Correlations of the N-availability indices withplant parameters are shown in table 4. Highestcorrelations with plant N uptake (PNU) were shownby the biological indices, of which, ANI-N showedstronger correlations (r = 0.920**) than the AI-N (r= 0.876**). This was followed by SMBN, whichrecorded a correlation coefficient of 0.707** withPNU. Of all the indices of N availability under

study, alkaline KMnO4-N registered the lowest

correlation (r = 0.625**) with PNU. Correlations ofthe other two plant parameters (dry matter yieldand N concentration) with various N-availabilityindices showed similar trend and strength as withPNU.

Table 4: Correlation coefficients (r) between

plant parameters and the indices of soil N

availability

AI-N ANI-N SMB-N Alk.KMnO

4-N

Dry matter yield .885** .925** 0.711** .633**

N Concentration .876** .928** 0.723** .631**

N uptake .876** .920** 0.707** .625**

*P < 0.05; **P < 0.01. AI-N: available-N through aerobicincubation;ANI-N: available-N through anaerobic incubation; SMB-N:soil microbial biomass N

As anticipated, the biological incubationmethods, being the most reliable predictors of soilN availability registered the strongest correlationsamong themselves and also with plant parameters.The better reliability of these methods as comparedto the chemical indices was further confirmed bythe higher levels of their correlation with plantparameters including PNU, as frequently reportedin literature (Sahrawat 1983; Hussain et al. 1984).The strong correlation of SMBN with AI-N andANI-N and also with the plant parameters suggeststhe worth of the procedure in describing thepotential N supplying capacity of the soil. Similarfindings regarding SMBN as a predictor of soil’spotential N supplying capacity was also reportedby Carter and Macleoid (1987). The ability ofSMBN in predicting soil’s N supplying capacity inthis study perhaps implies the importance ofmicrobially transformed N as the plant available Npool. In situations like Meghalaya, where the lossof N through processes like leaching etc. is rampant,the quantity of N microbially transformed into plantavailable form at a particular point of time bearsutmost importance. This might be the reason behindsuch reliability of SMBN in predicting soil Navailability as observed in this study, although manyother workers suggested microbial activity ratherthan size of the microbial biomass as a betterindicator of soil N availability (Puri and Ashman1998).



27

Compared to SMBN, alkaline KMnO4

extraction, the most commonly used method forestimating soil N availability in India, remained apoor performer despite yielding significantcorrelations with the biological incubationprocedures and plant parameters. Most of thestudies (Subbiah and Asija 1956; Nayyar et al. 2006;Maiti and Das 2007) establishing the applicabilityof alkaline KMnO

4 extraction method for predicting

soil N-availability in India were carried out in soilswith neutral to alkaline reaction leaving a vast scopefor such studies in acidic soils of the country.Manystudies have reported that alkaline KMnO

4 method

does not provide satisfactory results (Bordoloi etal 2012). In a study by Gianello and Bremner(1986), alkaline permanganate method had thepoorest precision of the 12 chemical indices usedin assessing N availability in Brazilian soils.Further consolidating the results of the presentinvestigation, Elkarim and Usta (2001) reported thepoorest correlation of biological incubation methodswith alkaline KMnO

4-N out of six chemical indices

of N availability tested in Central Anatolian soils.

CONCLUSIONS

In comparison with alkaline KMnO4-N, soil

microbial biomass N (SMB-N) correlatedconsistently better with AI-N and ANI-N as well aswith plant responses. Thus, based on results of thepresent study, we envisage SMB-N as a reliableindex of N availability in acidic soils of northeastIndia.

REFERENCES

Anderson JM,Ingram JSI (1993). Tropical Soil Biology andFertility: A Hand book of Methods. CAB International.Wallingford, U.K.

Bordoloi LJ, Singh AK, Manoj-Kumar, Patiram, Hazarika S(2013). Evaluation of nitrogen availability indices andtheir relationship with plant response on acidic soils ofIndia. Plant Soil Environ 59(6): 235–240

Baruah TC,Barthakur HP (1999). A text book of soilanalysis.Vikas Publishing Private Limited, New Delhi

Bray RH, Kurtz LT (1945). Determination of total, organicand available forms of phosphorus in soils. Soil Sci 59:39–45

Bremner JM (1965). Nitrogen availability indexes, In Methodsof Soil Analysis, edited by C.A. Black. Part 2, pp. 1324-1345. American Society of Agronomy, Madison, USA

Bremner JM (1996). Nitrogen - Total. In, Methods of SoilAnalysis, Part 3, Chemical Methods, 3rd edn. pp. 1035-1122. SSSA Book Series 5.Soil Science Society ofAmerica and American Society of Agronomy, Madison,Wisconsin, USA

Carter MR, Macleod JA (1987). Biological properties of somePrince Edward Island soils: Relationship betweenmicrobial biomass nitrogen and mineralizable nitrogen.Can J Soil Sci 67: 333–340

Dalal RC, Mayer RJ (1990). Long term trends in fertility ofsoils under continuous cultivation and cereal croppingin southern Queensland .VIII. Available nitrogen indexesand their relationships to crop yield and N uptake.Aust JSoil Res 28: 563–575

ElkarimAKHA,Usta U (2001). Evaluation of some chemicalextraction methods used as indices of soil nitrogenavailability in Polatli state farm soils in Ankara province.Turk J Agric For 25: 337–345

Gianello C,Bremner JM (1986). Comparison of chemicalmethods of assessing potentially available organicnitrogen in soil.Commun Soil Sci Plant Anal 17: 215–236

Hu C, Cao Z (2007). Size and activity of the soil microbialbiomass and soil enzyme activity in long-term fieldexperiments. World J Agric Sci 3: 63–70

Hussain F, KauserAM, Azam F (1984). Evaluation of acidpermanganate extraction as an index of soil nitrogenavailability. Plant Soil 79: 249–254

Jackson ML (1973). Soil chemical analysis. Prentice Hall ofIndia Private limited, New Delhi

Jin FH, Li SQ, Lu HL, Li SX (2007). Relationships of microbialbiomass carbon and nitrogen with particle compositionand nitrogen mineralization potential in calcareous soil.The J App Ecol 18 (12): 2739- 46

Keeney DR (1982). Nitrogen-availability. p. 711–733. In A.L.Page et al (ed.) Methods of soil analysis. Part 2. Chemicaland microbiological properties, Agronomy Monograph9, Soil Science Society of America and American Societyof Agronomy, Madison, Wisconsin, USA

Keeney DR, Bremner JM (1966). Comparison and evaluationof laboratory methods of obtaining an index of soilnitrogen availability. Agron J 58: 498–503

Li W, Xia Y, Ti C, Yan X (2011). Evaluation of biological andchemical nitrogen indices for predicting nitrogen-supplying capacity of paddy soils in the Taihu Lakeregion, China. Biol Fertil Soils 47: 669–678

Maiti D, Das DK (2007). Evaluation of different analyticalmethods for the estimation of available N, P, K and Zn insoil. Arch Agron Soil Sci 53(1): 89–94

Nayyar A, Bijay-Singh,Yadvinder-Singh (2006). Nitrogen-supplying capacity of soils for rice and wheat and nitrogenavailability indices in soils of northwest India. CommunSoil Sci Plant Anal 37: 961–976

Page AL, Miller RH, Keeney DR (1982). Methods of SoilAnalysis (Part 2).American Society of Agronomy and SoilScience Society of America. Madison, Wisconsin, USA

Piper CS (1966). Soil and plant analysis. Hans Publisher,Bombay

Puri G, Ashman M R (1998). Relationship between soilmicrobial biomass and gross N mineralisation. SoilBiolBiochem 30: 251–256



28

Sahrawat KL (1983). Correlation between indexes of soilnitrogen availability and nitrogen percent in plant,nitrogen uptake and dry matter yield of rice grown in thegreen house. Plant Soil 74: 223–228

Sharifi M, Zebarth BJ, Burton DL, Grant CA, Cooper JM(2007). Evaluation of some indices of potentiallymineralizable nitrogen in soil. Soil Sci Soc Am J 71:1233–1239

Stanford G (1978). Evaluation of ammonium release by alkalinepermanganate extraction as an index of soil nitrogenavailability. Soil Sci 126: 244–253

Subbiah BV, Asija GL (1956). A rapid procedure for estimationof available nitrogen in soils. Curr Sci 25: 259–60

Walkley A, Black IA (1934). An examination of the Degtjareffmethod for determining soil organic matter, and aproposed modification of the chromic acid titrationmethod. Soil Sci 37: 29–38

Waring SA,Bremner JM (1964). Ammonium production in soilunder waterlogged conditions as an index of nitrogenavailability. Nature 201: 951–952



29

Multiple Use of Pond Water for Enhancing Water Productivity

and Livelihood of Small and Marginal Farmers

A. DAS*, B. U. CHOUDHURY, RAMKRUSHNA, G. I., A. K. TRIPATHI, R. K. SINGH, S. V. NGACHAN,D. P. PATEL, J. LAYEK, G. C. MUNDA

ABSTRACT

Multiple use of pond water (MUW), an integrated approach for rain water management for enhancingwater productivity was demonstrated during 2010-12 in a participatory mode in 18 farmers’ fieldcovering 15 villages across Ri-Bhoi District, Meghalaya. The programme was sponsored by the Ministryof Water Resources, Government of India under the scheme Farmers’ Participatory Action ResearchProgramme (FPARP) Phase-II. Interventions of crop-fish-pig (pig based) and crop-fish-duck basedMUW in farmers’ field resulted significant improvement in water productivity, employment generation,income and livelihood of farmers over the farmers’ practice. The pig and duck based MUW throughdiversified farming (crop, fruit, livestock and fishery) enhanced system productivity by 352 % and190 % and generated a net return of Rs. 28,250 and 20,350 from an area of 1500 m2, which were284% and 176 % higher than the farmers’ practice (without integration), respectively. The MUW forharnessing complementary interaction of crop-fish-livestock also substantially improved employmentgeneration to 67 and 52 man days annually under a pig and duck based MUW system from an area of1500 m2 compared to 24 man-days under farmers’ practice, respectively. The water productivityrecorded with these MUW systems were 0.70 kg fish/m3 (equivalent to 4.7 kg rice/m3) and 0.45 kgfish/m3 (equivalent to 3 kg rice/m3) water compared to 0.23 kg fish/m3 under farmers’ practice,respectively. Thus, the efficacy in MUW through farm diversification of small and marginal farmersin the north-eastern hilly region with colossal disparity in water balance frontage (surfeit in rainyseasons and scarce in winter) can bring a sea change (positively) in socio-economy, food and livelihoodsecurity. Hence, integrated water resource management through farm diversification offers theopportunity for efficient use of scarce water resources for better livelihood security as well as “noregrets” measures in making resilience of small hill farming to the impacts of climate change.

Keywords: Water productivity, Farm diversification, Integrated water resource management, Life-saving irrigation, Livelihood security, Multiple water use.

ICAR Research Complex for NEH Region, Umiam, Meghalaya* Corresponding author’s E-mail: [email protected]

INTRODUCTION

The farmers of the North Eastern Region (NER)of India are mostly small and marginal in landholdings and depend mainly on agriculture for theirlivelihood. The agricultural productivity in theregion is very low and the region is in severe deficitof food grains (13%), fish (48 %), meat (57 %) andeggs (80%) (Vision 2050) and the requirement aremet through supply from neighboring states, WestBengal, Andhra Pradesh, etc. The region is veryrich in water resources (42 million ha m), receiveshigh rainfall (the long-term average rainfall of theNER is about 2000 mm and Ri-Bhoi; the study site

is 2450 mm), but most of it goes waste as runoffalong the steep slopes. Further, erratic distributionof rainfall (both in spatial and temporal dimensions)often leads NER to suffer from extreme waterscarcity during pre- and post- monsoon months. Itis projected that by 2021, 15 million populationwill be added to the current 45 million in the region(Choudhury et al. 2012). Consequently, the alreadylow per-capita per year total utilizable wateravailability (1404 m3) will further reduce to < 1000m3 and the region will be pushed from already waterstressed to water scarce zone. Trend analysis of longterm rainfall data (1983-2010) for mid altitudeMeghalaya (Umiam, 25° 41´ N latitude, 91°55´E




30

longitude, 1010m msl) using non-parametric MannKendall test further revealed that contributions ofmonsoon months to total annual rainfall aredeclining marginally at the rate of 1.70 mm.Probability analysis also showed a high frequencyof anomalies (p>0.6) of either deficit or excess inoccurrence of normal monsoon rainfall (Choudhuryet al. 2012). Therefore, water harvesting and theirefficient utilization is the major approach forproviding security to the livelihood in the hills ofNER of India. The harvested water should beefficiently utilized for enhancing water productivity(Das et al. 2013). There are many existing smalland large water bodies, farm ponds and wet lands,which are mostly underutilized. The fishproductivity is very low (500 kg/ha) mainly due tonon-adoption of improved species and husbandrypractices. The water productivity in the region isvery low, mainly due to the conspicuous absenceof scientific integration among different enterprisesinvolving agriculture, livestock, horticulture andfishery (Das et al. 2012; Das et al. 2013). Farmingsystem approach for promoting a multiple use ofpond water (MUW) allows efficient use of water,recycling of farm wastes and less dependency onsupply of external inputs to a great extent. It isbelieved that rain water harvesting and its recyclingin farming system mode will improve resource useefficiency, farm productivity, net income andemployment generation round the year from bio-resource flow of one or other components andthereby, promoting food and nutritional security atthe house hold level. Keeping these in view, in thepresent paper, result demonstrations on adoptionof such multiple uses of water through farmingsystem approach at several farmers’ fields acrossRi-bhoi district, Meghalaya has been discussed atlength.


Climate of study area

The study area experiences a tropical monsoonclimate. Analysis of long-term climate data (30years) reveals that seventy percent of the totalrainfall is received during July to September, withaverage annual rainfall of 2450 mm. April is thehottest month, with average minimum andmaximum temperatures of 17.3 ºC and 29.4 ºC,respectively. The coldest month is December where

the average minimum and maximum temperaturesare 7.6 ºC and 20.4 ºC, respectively. The averagerelative humidity is highest in the month of June(89.4 %) while January records the lowest relativehumidity of 72 %. Daily pan evaporation rate variesfrom 2.04 mm day-1(during December) to 4.60 mmday-1 (during April) with a mean value of 2.89 mmday-1. Daily wind speed varies from 2.58 to 4.39km hr-1, with a mean value of 3.36 km hr-1. Averagesunshine hours are 5.42 hr day-1.

The average amount of annual rainfall receivedduring 2010-12 was 2351 mm, about 79 % of whichwas received during May to September. Decemberto March was the extreme dry period during whichcrop suffers from water scarcity. The averagemaximum and minimum temperature were 25.33ºCand 13.68 ºC, respectively. The average monthlyweather parameters of 2010-12 are presented in Fig1.

Field survey and farmers’ selection

Field surveys were conducted to selectbeneficiaries among the farmers from differentvillages of Ri-Bhoi district, Meghalaya forimplementing the demonstration units. Beneficiaryfarmers having existing ponds were givenpreference in selection while special care was takenin covering more villages representing small andmarginal farmers. Two MUW models demonstratedwere crop-fish-pig (pig based) and crop-fish-duckbased integrated farming systems. Meetings wereconducted with farmers along with village leaderssuch as headman, secretaries as well as membersof youth clubs, NGOs, etc. The objectives, goal andimportance of MUW were highlighted during themeetings. The name of farmers, villages andgeographical locations of the demonstration siteshave been provided in Table 1.

Fig 1: Average monthly weather parameter of

Umiam during 2010-12



31

The performance of crops, fish and livestockunder demonstration were compared with thefarmers’ practice (no integration) in term ofproductivity, income and employment.

Soil and plant sample analysis

Composite soil samples were collected at 0-20cm depth from all the demonstration sites todetermine soil chemical properties. The soil pH wasdetermined in a 1:2.5 soil:water suspension(Jackson 1973), soil organic carbon (SOC) byWalkley and Black method (1934), available N byalkaline potassium permanganate method (Subbiahand Asija 1956), available P

2O

5 by Bray’s method

(Bray and Kurtz 1945) and available K2O by

Ammonium Acetate Extraction method (Jackson1973).The soils were mostly high in organic carbon(SOC), available N, K

2O and low to medium in

P2O

5 status. The soils were acidic in reaction (pH:

5-6) but the water collected from ponds were neutralin reaction (pH:7) mainly due to periodical limingand was found favourable for fish culture. Importantsoil chemical and fertility status of thedemonstration sites are given in Table 2.

Farm layout/design and implementation

To promote MUW, integrated crop-fish-livestock systems were demonstrated in farmers’field. Field crops, fruits and vegetables were grown

in association with the livestock such as pigs, ducks,etc. This system involves recycling of wastes orby-products of one farming component as an inputto another component, with a view to optimize theproduction while maximizing the marginal returnper unit input use from a unit area, with dueenvironmental considerations. Early bearing fruitssuch as banana, lemon, guava, papaya andvegetables like carrot, tomato, and cabbage werecultivated close to the pond/livestock shed togenerate additional income and to minimize theoperational expenses on feed, fertilizers andmaintained a balanced ecosystem with no waste inthe system. Wherever possible high-value crops likebroccoli, capsicum, etc. were cultivated for higherincome and water productivity.

Training cum awareness programme

Training, practical demonstrations andawareness programmes were conducted in theInstitute as well in farmers’ field on various aspectsof water harvesting, multiple use of water throughfarming system and improved crop and livestockhusbandry practices. First sensitization-cum-training program on “Rain water management” wasorganized on 25th October, 2011. Another training-cum-demonstration programme on “Enhancing soiland water productivity” was held on the 22nd March,2012 at ICAR Research Complex for NEH Region,

Table 1: List of beneficiary and their geographical location of the demonstration site

Name of beneficiary Village name Area of Latitude Longitude Elevation abovepond (m2) (N) (E) mean sea level (m)

Ms. Aitihunsuting Ladsyat 180 25.738500 91.885933 765Ms. S. Sohshang Mawbri 350 25.736017 92.054800 889Mr. K. Lyngdoh MawleinMawkhan 770 25.705267 91.895833 940Mr. N. Kharpan Umtrew 450 25.722567 91.890583 805Ms. JrisLyngdoh Road iew 1150 25.719233 91.984533 900Mr. Shining Rynghang Mawbri 360 25.724350 92.040183 903Mr. P. Nongrum Byrwa 870 25.692633 91.890467 872Ms. SyndamonKhyriem Nongpyrdet 1560 25.676733 92.064400 888Ms. IohkyntiKharumnuid Umtung 1110 25.688683 92.027600 883Ms. RibhaShylla Sawnumber 210 25.693100 91.890750 863Mr. R. R. Makdoh Mawtnum 560 25.870033 91.888000 584Ms. PhidalisMakdoh Iewmawlong 880 25.893250 91.886367 550Ms. PhotinaNongrum Umeit 490 25.706833 91.952917 900Ms. MilianMarsharing Kyrdem 170 25.692817 92.074750 881Ms. Philinda Sumer Liarkhla 520 25.745550 92.075283 898Mr. PhringstarUmdor Larsyat 450 25.738533 91.886100 775Ms. SyrpailinRymbai Kdonghulu 1060 25.741400 92.067283 883Mr. R. Mukhim Nongpyrdet 530 25.676517 92.065833 876



32

Umiam, Meghalaya. In both the programmes,beneficiaries and village Panchayat

“DorbarShnong” members attended in a largenumber with active participation of womanmembers. During the awareness-cum-trainingprogramme, the objectives and activities to beundertaken in the selected farmers’ field werehighlighted. Scientists-farmers-stakeholdersinteraction on importance of water harvesting andconservation, efficient recycling through MUW forhigher water productivity was also organized.

Developing farm ponds

The pond size ranged from 170 m2 to as large as1000 m2 with average size of about 500 m2 and depthof 1.25-1.5 m. The existing underutilized anddefunct ponds of the farmers were renovated duringthe dry season (December to March) by removingthe silts, repairing the dykes and spill ways. Theunwanted weeds, bushes, weed fish, etc. wereremoved from the pond before stocking the fish. Atotal of 18 beneficiaries was selected covering 16villages in Ri-Bhoi District of Meghalaya.Participatory approach was adopted for renovationof ponds, repairing dykes, cleaning, etc. The fullcost of external materials and inputs such as GIsheet, fingerlings, lime, fertilizer, etc. were provided

from the project. Whereas, for digging, repairing,making livestock sheds, etc. only 50 to 60 % costswere provided from the project and the rest werethe contributions of the beneficiary farmers. Theaverage pond sizes of the selected farmers wereabout 500 m2. Wherever, the pond size was lessthan average size (500 m2), additional digging wasundertaken to enlarge the pond for water harvestingto promote MUW.

Liming and manuring of pond

Liming was done to raise the pH of water toabout 6.5 to 7.0 for better fish growth. About 60-70 kg lime was required for a pond area of 500 m2

in one year. About 50 % of lime was applied duringthe dry season (after renovation, silt removal, etc.)and rests of the limewas applied in 3-4 splits at the30-day intervals after stocking the fingerlings.Manuring is very important for better growth ofplankton (phytoplankton and zooplankton) andpromoting natural food organisms for fish. Hence,500 kg cow dung (1 kg/m2) was applied in 4 to 5splits. The first split application was done alongwith first dose of lime in dry season. The pig shedwashing was effectively diverted to pond topromote growth of plankton as fish feed in pig basedMUW. The droppings of ducks served as fish feed

Table 2: Soil fertility status of the demonstration sites

Name of farmers Village name Available nutrients (kg/ha) SOC (%) Soil pH Water pH

N P2O

5K

2O

Ms. Aitihunsuting Ladsyat 188.2 34.4 239.8 2.64 5.13 7.98Ms. S. Sohshang Mawbri 213.2 31.6 196.2 2.51 5.81 7.88Mr. K. Lyngdoh MawleinMawkhan 225.8 35.1 336.1 2.15 5.65 7.6Mr. N. Kharpan Umtrew 250.9 18.4 167.3 2.65 5.66 6.41Ms. JrisLyngdoh Road Iew 150.5 26.7 110.4 2.12 5.09 8.2Mr. Shining Rynghang Mawtneng 213.2 28.1 240.8 2.53 5.82 7.88Mr. P. Nongrum Byrwa 200.7 30.9 172.4 1.69 5.00 7.9Ms. SyndamonKhyriem Nongpyrdet 225.8 34.4 289.6 2.3 5.19 6.88Ms. Iohkyntikharumnuid Umtung 188.2 31.6 209.6 2.09 5.66 7.6Ms. RibhaShylla Sawnumber 225.8 18.4 46.4 1.69 5.31 7.04Mr. R. R. Makdoh Mawtnum 150.5 28.1 342.4 1.92 5.9 7.48Ms. PhidalisMakdoh Iewmawlong 138.0 40.9 649.1 2.07 5.91 7.58Ms. PhotinaNongrum Umeit 225.8 30.2 214.8 2.12 5.91 7.44Ms. MilianMarsharing Kyrdem 163.1 27.4 181.7 2.05 5.12 7.40Ms. Philinda Sumer Liarkhla 188.2 29.5 198.3 2.1 5.15 7.75Mr. PhringstarUmdor Larsyat 200.7 38.8 110.4 2.6 5.13 7.47Ms. SyrpailinRymbai Kdonghulu 225.8 36.5 277.8 2.1 5.1 7.84Mr. R. Mukhim Nongpyrdet 213.3 37.4 240.8 2.09 5.2 7.5



33

and encouraged plankton growth in fish basedMUW. The manurial value of pig dung and duckdroppings were analyzed and presented in Table 3.Manuring and diverting livestock washing to pondwas stopped whenever excess algal gloom (greencolour) observed in the pond. The piglets and duckswere fed with available on-farm materials like ricebran, broken maize, sweet potato, colocasia, kitchenwaste, etc. Mineral mixture and common salts wereadded to the feed for better health of animals.

Table 3: Manurial value of pig dung and duck

droppings

Type of Manure Moisture (%) N (%) P (%)

Pig dung 70 1.6 0.35Duck dropping 80 1.0 0.40

Pig and duck components

Low cost pig (2 x 2 m2 size) and duck shed (2 x1 m2 size) were made on the pond embankmentsutilizing locally available materials like bamboo,wooden logs, thatch grass, Tina, etc. for providingshelter to pigs and ducks. The duck shed wasconstructed over the water body so that thedroppings directly fall into the pond. Improved pigbreeds (75 % Hampshire x 25 % Khasi local) andducks (Khaki Campbell, Sonali) were reared forbetter productivity and income. Compositepisciculture was integrated with duckery (10 nos.)or pigs (2 females + 1 male) for enhancingproductivity and income. The stocking was donein June/July with the onset of monsoon. A stockingdensity of 10,000 fingerlings/ha (1 fingerlings/m2

pond surface area) was followed for integratedfarming system (IFS). The surface, column andbottom feeders were simultaneously cultured foreffective utilization of water resources. Catla, rohu,mrigal and common carpwere stocked in the ratioof 2:2:1:1. For a pond with surface area of 500 m2,the numbers required were 166 catla, 166 rohu, 84mrigal and 83 common carp.

Integration with fruits and vegetable

Fruits like banana, citrus, guava, papaya andvegetables like carrot, tomato, broccoli, etc. werecultivated in the pond dykes/banks, vicinity of theanimal shed to generate additional income. Theplant nutrition of crops was mostly met from thelivestock excreta based organic manures. Somefarmers used minimal amount of fertilizers (<20

kg/ha) such as di-ammonium phosphate for nutrientsupply to crops. Life-saving irrigation was providedto crops manually or using 1HP Tulu pumpwhenever needed. Climbing vegetables like chow-chow, bottle gourd, pumpkin, etc. were trained overthe water bodies using bamboo made structure forefficient utilization of space to promote verticalintensification. Furrow liming @ 500 kg/ha wasadvocated for higher productivity of crops andvegetables.

Pest and disease management

Adequate prophylactic measures were followedfor various livestock components in farmingsystem. The diseased animals were separated fortreatment; netting was done to enhance fish healthat regular intervals. For protecting crops from pestand diseases, mostly indigenous means such asapplication of wood ash from kitchen, neem oil (3%), hand weeding, stripping diseased leaves, etc.were followed. All the produce of farm wasconverted to Fish Equivalent Yield (FEY)considering the local market price for comparison.B: C ratio was computed by dividing the grossreturn with cost of production.

Technical support

Farmers were provided with improved seeds/breeds of crops, fruits, vegetables, fingerlings andlivestock for higher productivity and income.Improved cross bred piglets (25 % Meghalaya localand 75 % Hampshire) of 2 females and 1 male wasprovided to each beneficiary farmer. Starter feedwas also given to farmers for better growth of thepiglets. Ten adult ducks (Sonali breed/Khakicampbell) were integrated with the system.Fingerlings were distributed to each farmerdepending on the area of the pond (1 m2 = 1fingerling) during the month June-July. For small-scale mechanization, tools and implements such asan electric pump along with pipe, sprayer, cono-weeder, furrow opener, rose can, etc. were beingdistributed to the farmers. For technologydemonstration and dissemination, leaflets in locallanguage were prepared and distributed to thefarmers. Need based technical backstopping fornutrition, and healthcare was provided to thefarmers. For nutrition of crops and vegetables,effective recycling of on-farm biomass throughcomposting, mulching, residue management, etc.was encouraged.



34


A total of 18 farm ponds were renovated throughexcavation, dyke repairing, cleaning, etc. and madefunctional under the project. The pond size rangedfrom 400 m2 to as large as 1000 m2 with averagesize of about 500 m2and depth of 1.25-1.5 m, whichcould harvest 625 m3 to 750 m3 of water whencompletely filled during the rainy season. Anelectric tulu pump (1 HP) was given to each farmerfor irrigating their crops and cleaning the animalsheds, etc. Necessary training for integrated farmingsystem to promote MUW was provided by theICAR Research Complex for NEH Region, Umiam.After two years, the farmers could harvest about150 kg fish from their respective ponds with anaverage productivity of 2800 kg/ha (Table 4). Theimproved ducks on an average were laying 100eggs/annum. Improved pigs in farmers’ field could givetwo farrowing in a single year with 7-11 piglets/farrowing as compared to 5-7 from local breeds.However, the average number of piglets per unitwas 15/year. The income from vegetables (Tomato,French bean, broccoli, laipatta, etc.) and fruits(Guava, Assam lemon, papaya, etc.) grown on ponddykes were also encouraging. For effectiveutilization of space, vegetables like mustard(laipatta), chilies, etc. were intercropped in betweenfruit plants.

The average pig dung production was 6 kg/day(2 kg/pig/day) and considering 10% washings; atleast 600 g pig manure was diverted to pond everyday. Similarly, average duck dropping per day was1.5 kg (150 g/day) which was directly falling onthe water body and served as fish feed. On anaverage, farmer earned a net income of Rs. 28,250annually from crop-fish-pig integrated farmingsystem unit of 1500 m2area, i.e. Rs. 1,88,333/hacompared to the net income of only Rs. 7,360 fromfarmers’ practice (Rs. 49,060/ha). The net returnobtained from crop-fish-duck integration was Rs.20,350 from1500 m2area, i.e. Rs. 1,35,666/ha. Dueto the adoption of diversified farming activities, thefarmer’s employment enhanced by about 179 % and117% under pig and duck integrated MUW systemcompared to farmers’ practice. Similarly, the netreturns enhanced by 284% and 176% over farmers’practice with pig and duck integrated MUW system,respectively. Enhancement in cropping intensity,employment generation and farm income owing torain water harvesting and its efficient recycling in

farm ponds (Das et al. 2013) and micro rain waterharvesting structure (Ghosh et al. 2009) has beenreported by other researchers.

The fish equivalent yield from the pig and duckintegrated MUW was 352 % and 190% higher thanthe farmers’ practice (No integration), respectively.The water productivity under these MUW systemswas also enhanced by about 2.04 and 0.98 timesover farmers’ practice, respectively (Table 5). Thebenefit: cost ratio under farmers’ practice wasmarginally higher compared to MUW, mainlybecause of low investment and sustenanceproduction system.

The interaction with the farmers and fieldobservations revealed that the operational expensesin feed, fertilizer was minimized to a great extent(by about 50 %) due to integration of variouscomponents and effective recycling of on-farmresources such as biomass, farmyard manure, farmlitters, etc. The farmers could harvest one or othercomponents throughout the year and thus, improvednutritional security. Due to MUW in a farmingsystem mode, the farmers’ risks reduced and in theevents of failure or poor performance of oneenterprise, farmer got assured income from othercomponents. Therefore, fish based integratedfarming system has an immense potential to prosperin hilly states of Meghalaya, mostly due to the foodhabit, small land holdings, low investmentrequirement and high profitability.

Feedback and impact

The ponds before FPARP-II interventions weremostly defunct, underutilized, filled with garbage,infested with aquatic weeds and were mostly underunproductive domestic uses. Only local weed fishspecies were grown under natural condition withoutfollowing any management practices. Under thepresentprogramme, the renovation works wereundertaken to make the ponds functional and depthwas maintained at about 1.25-1.5 m through earthworks. About 750 m3 of rain water could beharvested in each pond. Thus, in 18 ponds, about13.5 million litre rain water was harvested. In someareas, farmers filled the pond with spring water,other sources during dry season and used formultiple agricultural activities. Considering theavailability of about 50 % water for life-savingirrigation, it would be possible to irrigate about 8hectare areas under multiple crops (2 cm/irrigation)with 3 to 4 irrigations in each crop. Rest of the water



35

could be used for multiple activities such ascomposite fish culture, livestock, domestic purpose,etc.

Mr. Phringstar Umdor, from Ladsyat village Ri-Bhoi District, Meghalaya narrated that “Beforeadopting this improved method of farming system,I used to practice only fish culture. This is the firsttime that I am practicing fish-livestock cumvegetable cultivation. By following the suggestiongiven by the experts and field staffs from ICAR, Icould easily manage this system. We wereoverwhelmed to see that the sow provided by theICAR has delivered eleven (11) piglets in onefarrowing. My family members are very happy, andI hope that the other sow would also deliver the

same number of piglets. We have learned tocultivate bottle gourd over water bodies (pond) thus,enhancing income by vertical intensification. Myfamily income is really boosted due to adoption ofthe multiple water use model demonstrated underFPARP.”

CONCLUSIONS

Multiple use of pond water (MUW) throughintegrated farming system approach enhancedproduction, yield,and employment and reduceddependence on external resources. The pond waterwas efficiently utilised for fish culture in addition

Table 4: Production, employment and income from various components of IFS

Particulars Area Production Employment Cost Gross Netallotted (kg) (Man- days) involvement return return(m2) (Rs.) (Rs.) (Rs.)

Multiple use of water (Integration of components)

Composite fish culture 500 150 10 5000 15000 10000Tomato 250 500 15 2000 5000 3000French bean 250 250 10 1750 5000 3250Mixed vegetables: Chow-chow, All sides of Pond dykemustard (laipatta), chilli, cucumber, 500 200 10 2500 4000 1500broccoli from pond dyke /adjacentareas.Banana, Assam lemon, papaya, 3 sides of pond dykeGuava (20 plant) - 50 2 500 1000 500Duckkery (Eggs) 9 F + 900 nos. 5 1500 3600 2100

1 MPiggery (Piglets) 2 sow + 15 piglet 20 12500 22500 10000

1 boar /annumTotalCrop-fish-pig 1500 67 24250 52500 28250Crop-fish-duck 1500 52 13250 33600 20350Farmers’ practice (Without integration)

Fish Culture 500 50 5 1000 5000 4000Pond dyke 500 - - - - -Maize 200 64 5 600 960 360Frenchbean 100 80 4 700 1600 900Others (Chilli, turmeric, mustard 200 200 10 2000 4000 2000(laipatta), etc.)Total 1500 - 24 4300 11560 7360

Table 5: Equivalent fish production, water productivity and benefit: cost ratio

Farming practice Fish equivalent Water productivity Water productivity B:C ratio(kg) (kg fish/m3 water) (Rs./m3 water)

Crop-fish-pig 525 0.70 70 2.16Crop-fish-duck 336 0.45 45 2.53Farmers’ practice (no integration) 116 0.23 23 2.69



36

to meet the water requirement of various diversifiedfarming activities. It was possible to get year-roundemployment and income due to diversification. Thelivelihood of farmers improved substantially dueto higher income, better food and nutrition. Inaddition, t water productivity enhanced by aboutone to two times due to MUW compared to farmers’practice. The technical skills and level of exposureof farmers, to manage multiple agriculturalproduction systems and resource recycling,enhanced substantially. In the event of failure ofone component, farmers can compensate the lossthrough another component and hence, enhancesthe farmers risk bearing ability and providesresilience against risks associated with climatechange. Depending upon farmers’ choice, resourceavailability and demand in the local market, thecomponents of farming system models for MUWhas to be chosen for higher productivity, incomeand livelihood security.

ACKNOWLEDGEMENTS

The authors would like to place on sincerethanks to Central Water Commission, Ministry ofWater Resources, Govt. of India for providingfinancial support to carry out the present work underFarmers Participatory Action Research Programme(FPARP-II).

REFERENCES

Choudhury BU, Das A, Ngachan SV, Bordoloi LJ, ChowdhuryP (2012). Trend Analysis of Long Term Weather Variablesin Mid Altitude Meghalaya, North-East India. Journal ofAgricultural Physics 12(1):12-22

Das A, Munda GC, Azad Thakur NS, Lal B, Ghosh PK,Ngachan SV, Bujarbaruah KM, Yadav RK, MahapatraBK, Das SK, Dutta KK (2013). Integrated agriculturaldevelopment in high altitude tribal areas- a participatorywatershed programme in the East Indian Himalaya.Outlook on Agriculture 42 (2) doi:10.5367/0a.2013.0129

Das A, Ngachan SV, Ramkrushna GI, Choudhury BU, SinghRK, Tripathi AK, Patel DP,Munda GC (2012).Participatory rain water management for enhancing waterproductivity and livelihood in hill ecosystem- actionprogramme for research applications. ICAR ResearchComplex for NEH Region, Umiam, Meghalaya, p115

Ghosh PK, Saha R, Das Anup, Tripathi AK, Samuel MP, LamaTD, Mandal S, Ngachan SV(2009). Participatory Rainwater Management in Hill Ecosystem – a success story.Technical Bulletin No. 67.FPARP- Phase I. ICARResearch Complex for NEH Region, Umiam-793 103,Meghalaya, p 37

Jackson, ML(1973). Soil chemical analysis. Prentice Hall ofIndia, New Delhi

Subbiah BV, AsijaGL (1956). A rapid procedure for thedetermination of available nitrogen in soils.CurrSci25:259-260

Vision 2050.ICAR Research Complex for NEH Region,Umiam, Meghalaya.

Walkley A, Black JA(1934). Estimation of soil organic carbonby chromic acid titration method.Soil Sci17: 29-38



37

Input use Pattern in Rainfed ‘Kandi’ Area of Jammu Region in

Jammu and Kashmir

P. KUMAR*, S. K. KHER, P. S. SLATHIA, G. KUMARI

ABSTRACT

The present study conducted in the subtropical rain fed ‘Kandi’ belt of Jammu region aimed to findout the input use pattern and the adoption gap in seed and fertilizers. The results revealed that morethan eighty percent of the respondents used urea in maize and wheat crops respectively. Only 14.1percent of the respondents used Urea in Bajra. The extent of fertilizer use for different crops alsoreveals that there was no use of MOP in case of marginal farmers. In case of small farmers, MOP wasused by only 15.5 percent of the respondents in maize crop only, whereas in case of semi mediumfarmers MOP was used by 50 percent of respondents in maize and 46.1 percent of respondents inWheat. An adoption gap existed in seed rate as well as fertilizer dose. The average adoption gap incase of maize crop was 8.5 kg/ha which was less than the recommendation. Similarly the seed rate incase of til, moong and lentil was less than the recommended. The crops where the seed rate (kg/ha)was more than the recommended were wheat (+3.1), bajra (+2.7), mustard (+0.71), mash (+ 1.7) andcowpea (+2.6).The fertilizer application (kg/ha) was also far less than the recommendations. It was47.8 for DAP followed by Urea (20.4) and MOP (9.3). The adoption gap for Wheat was 16.7 kg /hafor urea and 22.3 kg/ha for DAP.

Keywords: Seed, Fertilizers, Adoption gap-recommended

Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu, Main Campus, Chatha-180009.

INTRODUCTION

Growth in production per unit of area is centralto development of agriculture. Fertilizer and seedconstitute two vital inputs in the agriculturalproduction process. The green revolution of thesixties which transformed India from a ‘beggingbowl’ to ‘bread basket’ was due to the use of highyielding varieties of seeds and adequate fertilizers.Studies have shown that around 50 to 60 percent ofthe enhanced food grains production during 1960-77 could be attributed to fertilizers (PlanningCommission 2007)

In Jammu and Kashmir, 58.03 percent of thearea is rain fed (Anonymous 2008), which is locallycalled ‘Kandi’ belt. The sub mountain tract of theouter Himalayas in Jammu division of Jammu andKashmir that arises gradually from Punjab plainswith a gentle slope of 30 comprising mostly ofShivalik system of rocks is locally known as Kandi

(Kumar 2004). It is characterized by water scarcityand undulating topography. Economically, thefarmers of this area are poor with small holdings.

Moreover the adoption of scientific technologiesin the crop production is low because of lowliteracy, lack of awareness regarding the mode ofadoption of modern technologies resulting in lowand unstable income since agriculture is mostly inrain fed conditions, the use of inputs is very crucialfor making the farming economically viable in theseareas. The focus of agriculture research has to befield oriented so as to ensure efficient use ofresources along with introduction of new varietiesof seeds and modern technology (Mukherjee 2012).The present study was thus conducted with theobjective to find out the input use pattern amongthe farmers of Kandi region and to find out theadoption gap in inputs i.e. seed and fertilizers.


The present investigation was carried insubtropical Kandi belt of Jammu region comprisingfour districts of Jammu, Kathua, Udhampur andRajouri. From each district two blocks were





38

selected and from each block two Panchayats wereselected. From each Panchayat two villages wereselected. Fifteen respondents were selected fromeach Panchayat. Thus from each block thirtyrespondents were selected and from each districtsixty respondents were selected, taking the finalsample size to 240.


The cropping pattern of the study area wasstudied under three seasons. The crops grown inkharif season were maize both as pure as well asmixed crop with cowpea. The other crops grown inkharif season were bajra, mash, til and moongwhereas in rabi season the crops grown were wheatboth as a pure as well as a mixed crop with mustard.The other crops grown in rabi season were toriaand lentil. Mash was also grown as a zaid seasoncrop.

Input use pattern

In the present study an attempt was made tostudy the input use pattern of seed and fertilizersof the respondents and the results are presented asfollows

Type of seed used by farmers

It is evident from table1 that farmers mostly uselocal varieties of seeds. In maize, 72.08 percent andin wheat, 67.5 percent of the respondents used seedsof local varieties. This trend continued in case ofpulses and oilseed crops also. In case of mustard47.83 percent of the respondents used high yielding

varieties followed by cowpea (39.13%), til(35.30%), mash and lentil (33.33% each), moong(31.25%) and toria (23.31%).

Extent of adoption of seed

The data in the table2 reveals that the adoptionof seed rate in case of maize was 25.8, 29.4 and31.6 kg/ha for marginal, small and semi mediumcategories of farmers, respectively. For wheat theseed rate was 105.60, 117.80 and 123.60 kg/ha formarginal, small and semi-medium category,respectively. Similarly in case of bajra the seed ratewas 14.2, 11.04 and 12.85 for marginal, small andsemi-medium category, for mustard it was 6.34,6.45, and 7.34, for mash it was 17.42, 19.60 and20.80, for til the seed rate was 6.14, 6.21 and 6.87,for cowpea as a mix crop with maize the seed ratewas 12.42, 11.80 and 13.60 for marginal, small andsemi-medium farmers respectively.

Table 2: Average seed rate used by different

categories of farmers (n=240)

Name of Number Average Seed rate used(kg/ha)Crop

Marginal Small Semimedium

Maize 240 25.80 29.40 31.60

Wheat 240 105.60 117.8 123.60

Bajra 240 14.20 11.04 12.85

Mustard 23 6.34 6.45 7.34

Toria 19 6.37 6.48 7.23

Mash 21 17.42 19.60 20.80

Til 17 6.14 6.21 6.87

Cowpea 23 12.42 11.80 13.60(Mix cropwith Maize)

Moong 32 17.35 18.32 23.45

Lentil 15 34.75 35.75 37.85

Adoption gap

The adoption gap in seed rate depicted in table3 divulges that the average adoption gap in case ofmaize crop was (8.57 kg/ha) which was less thanthe recommended. Similarly the seed rate in caseof til, moong and lentil was less than therecommended. The crops where the seed rate (kg/ha) was more than the recommended were wheat(+3.17), bajra (+2.70), mustard (+0.71), mash(+1.77) and cowpea (+2.60).

Table 1: Type of seed used by the farmers

Crop Number Local Hybridof farmers seeds (%) seeds (%)

Maize 240 72.08 27.92

Wheat 240 67.50 32.50

Bajra 240 59.58 40.42

Mustard 23 52.17 47.83

Toria 19 73.69 23.31

Mash 21 66.67 33.33

Til 17 64.70 35.30

Cowpea 23 60.87 39.13

Moong 32 68.75 31.25

Lentil 15 66.67 33.33



39

Extent of fertilizer use

The data in the table 4 shows that 86.20 and59.77 percent of the respondents from the marginalcategory used urea and DAP in maize, respectively.For wheat crop, urea and DAP fertilizers were usedby 83.90 percent and 59.77 percent of therespondents, whereas in case of bajra only urea wasused by 6.50 percent of the respondents. It is hereinteresting to note that none from the marginalcategory farmers used MOP.

Table 4: Extent of fertilizer use by different

categories of farmers for different crops (n=240)

Category of farmer Percentage of farmers using

Urea DAP MOP

Marginal (n=174)Maize 86.20 59.77 00.00Wheat 83.90 59.77 00.00Bajra 6.50 00.00 00.00

Small (n=45)Maize 84.44 77.78 15.55Wheat 82.22 88.10 15.55Bajra 13.33 00.00 00.00

Semi Medium(n=21)Maize 100 100.00 52.38Wheat 100 100.00 47.61

Bajra 65.38 00.00 00.00

In case of small farmers 84.44 percent used Ureaand 77.78 percent used DAP in maize, In wheat82.22 percent used Urea and 88.10 percent usedDAP, only 13.33 percent of the respondents usedUrea in case of bajra. MOP was used by 15.55percent of the respondents each in case of maizeand wheat respectively. Further it was also observed

that from the semi-medium category all therespondents used Urea and DAP in maize and wheatcrop and 65.38 percent used Urea in bajra. MOPwas used by 52.38 percent in maize crop and 47.61percent in wheat (47.61%).

Overall distribution of respondents according to

fertilizer use

Table 5 reveals that a very high percentage ofrespondents used Urea in maize and wheat and avery low percentage used urea in bajra.. Similarlyuse of DAP was quiet high by the respondents inmaize and in wheat. DAP was not used byrespondents in bajra. MOP was used by very lessrespondents both in case of maize as well as wheat.

Table5: Overall distribution of respondents

according to fertilizer use

Crop %age %age %age

Maize(n=240) 87.08 66.67 7.50

Wheat(n=240) 85.41 67.50 7.08

Bajra(n=240) 14.17 00.00 00.00

Category wise use of average fertilizer dose

The data in the table 6 shows the averagefertilizer dose (kg/ha) used by different categoriesof farmers. In case of marginal category the averagefertilizer dose in Kg/ha used in maize was Urea(77.60) and DAP (42.60). In case of wheat it wasUrea (82.40), DAP (43.40) and for bajra only ureawas used at the rate of 42.40 kg/ha.

Table 3: Average adoption gap in seed rate for all categories of farmers

Name of Crop Number of farmers Average seed rate Average recommended Adoption Gapused (kg/ha) seed rate (kg/ha) (kg/ha)

Maize 240 28.93 37.50 -8.57Wheat 240 115.67 112.50 +3.17Bajra 240 12.70 10.00 +2.70Mustard 23 6.71 6.00 +0.71Toria 19 6.69 6.00 +0.69Mash 21 19.27 17.50 +1.77Til 17 6.40 7.00 -0.60Cowpea (as Mixed crop ) 23 12.60 10.00 +2.60Moong 32 19.70 20.00 -0.30Lentil 15 36.11 40.00 -3.89



40

As is evident from the table the average fertilizerdose (kg/ha) of Urea used by small farmers followedby DAP and least by MOP. In case of wheat it washighest for Urea, followed by DAP and MOP. Incase of bajra only urea was used at a rate of 41.20kg/ha. Similarly for semi medium farmers theaverage fertilizer dose (kg/ha) for maize was urea(84.20), DAP (43.80) and MOP (23.20). For wheatthe corresponding rates were 84.20, 43.80 and 25.40kg/ha for urea, DAP and MOP respectively. In bajraonly urea was applied at a rate of 42 kg/ha.

Adoption gap in fertilizer dose

The adoption gap was calculated on the basisof package of practice recommended by Sher-e-Kashmir University of Agricultural Sciences andTechnology of Jammu. The data in the table 7reveals that for almost all the fertilizers there existedan adoption gap. In case of Maize the adoption gapwas highest. The fertilizer application (kg/ha) wasfar less than the recommendations. It was highestfor DAP followed by Urea and least for MOP.Similarly, the adoption gap for Wheat was highestin case of DAP followed by Urea and than by DAP.In case of Bajra where only Urea was used, thedose was more than the recommended.

Table 7: Average adoption gap in fertilizer dose

for all categories of farmers

Fertilizer dose kg/ha Maize Wheat Bajra

UreaUsed 79.53 83.27 41.87Recommended 100 100 35Gap -20.47 -16.73 +6.87

DAPUsed 42.20 43.67 0.0Recommended 90 66 33Gap -47.80 -22.33 -33

MOPUsed 23.70 24.10 0.0Recommended 33 35 25

Gap -9.30 -10.90 -25

The extent of fertilizer use in the study area ishigh in case of maize and wheat. More than 80percent of the respondents used urea and more than60 percent of the respondents used DAP in maizeand wheat crops, respectively. In bajra the use offertilizers was quiet low. Only 14.17 percent of therespondents used urea in bajra. Similarly the useof MOP was dismal. One of the reasons for its lowuse is the non availability of MOP in the market atthe time of sowing as reported by 92.50 percent ofrespondents in the study area

The extent of fertilizer use for different cropsalso reveals that there was no use of MOP in caseof marginal farmers. In case of small farmers, MOPwas used by only 15.55 percent of the respondentsin maize crop only whereas in case of semi-mediumfarmers MOP was used by 50 percent ofrespondents in case of maize and 46.15 percent ofrespondents in case of wheat. The negligible useof MOP might be due to unawareness and nonavailability of the fertilizer at the time of sowingof crops.

The seed rate used by the respondents in thestudy area is not as per the recommended packageof practices developed by SKUAST-J for Kandi

area. In case of maize and wheat the seed rate usedis less than the recommended where as in case ofbajra, pulse crops and oilseed crops it is more thanthe recommended rate.

An adoption gap existed in seed rate as well asfertilizer dose. The average adoption gap in caseof maize crop was (8.57 kg/ha) which was less thanthe recommendation. Similarly the seed rate in caseof til, moong and lentil was less than therecommended. The crops where the seed rate (kg/ha) was more than the recommended were wheat(+3.17), bajra (+2.70), mustard (+0.71), mash (+1.77) and cowpea (+2.60).

The fertilizer application (kg/ha) was also farless than the recommendations. It was 47.80 forDAP followed by urea (20.47) and MOP (9.30).Similarly the adoption gap for wheat was16.73 kg/

Table 6: Average fertilizer dose used by different categories of farmers for different crops

Crop Marginal (n= 174) (kg/ha) Small (n=45) (kg/ha) Semi medium (n=21) (kg/ha)

Urea DAP MOP Urea DAP MOP Urea DAP MOP

Maize 77.60 42.60 00.00 78.40 41.60 24.20 82.60 42.40 23.20Wheat 82.40 43.40 00.00 83.20 43.80 22.80 84.20 43.80 25.40Bajra 42.40 00.00 00.00 41.20 00.00 00.00 42.00 00.00 00.00



41

ha and 22.33 kg/ha for urea and DAP respectively.In case of bajra where only urea was used, the doseexceeded the recommendations by 6.87 kg/ha.

CONCLUSIONS

As rain fed belt is vital for achieving foodsecurity both at the state as well as the nationallevel, strenuous efforts are needed to boost theagriculture production in this region. With theefforts of state agricultural department, the seedreplacement rate has gone up over the last four yearsfrom 10 % to 24.78 % in Paddy and from 10.79%to 29.77% in wheat (Mir 2013). Similar strategyneeds to be planned for increasing the seedreplacement rate in case of maize also to achievethe national level benchmark of 33 percent. Farmersshould be educated about the optimum dose of seedas well as fertilizer application. Also, thrust shouldbe given to introduction of latest technology and

farm mechanization to reduce the production coststo make the sector more profitable.

REFERENCES

Anonymous (2008). Digest of Statistics 2007-08. Directorateof Economics and Statistics, Government of Jammu andKashmir

Kumar V (2004). Land use mapping of Kandi belt of Jammuregion. Cited at link.springer.com/content/pdf/10.1007/

BF03030857.pdf

Mir GH (2013). Multipronged strategy to promote agricultureand allied sectors. Daily Excelsior, March 16

Mukherjee D (2012). Second green revolution: Eastern statesto lead the way. Kurukshetra 60(6): 23-28

Report of working group on Fertilizers in the context of theEleventh Five Year Plan (2007-2012), Cited at http:planningcommission.nic.in/aboutus/committee/.../

wg11_fertliser.doc



42

A Report on Gastrointestinal Parasitic Infections in Yaks

A. GOSWAMI1, R. LAHA1, D. SARMA1, L. R. CHATLOD2

ABSTRACT

A study was conducted to know the prevalence of gastrointestinal parasitism in yaks in some pocketsof Arunachal Pradesh and Sikkim by examination of faecal samples. For this, 152 and 80 numbers offaecal samples were collected randomly from Arunachal Pradesh and Sikkim, respectively. Out ofthese, 40 (26.31%) yaks were found positive in Arunachal Pradesh and 16 (20.00%) yaks were foundpositive in Sikkim for gastrointestinal parasitic infection with overall 24.13% infections. The percentageof infection of Strongyle sp. and Eimeria sp. were 95.00% and 10.00% in Arunachal Pradesh and75.00% and 25.00% in Sikkim, respectively. Mean faecal egg count of infected yaks in ArunachalPradesh and Sikkim were 185.00 and 168.75, respectively. It can be concluded from this study that amoderate percentage of yaks were suffering from gastrointestinal parasitic infections with less faecalegg count which is significant to contaminate the pasture and aid in spread of infections to healthyyaks as well as to contribute to increase faecal egg count in repeated infections.

Keywords: Arunachal Pradesh, Gastrointestinal parasite, Sikkim, Yak

1ICAR Research Complex for NEH Region, Umroi Road, Umiam, Meghalaya -793 1032ICAR Research Complex for NEH Region, Sikkim Centre, Gangtok, Sikkim -737 102

INTRODUCTION

Yak (Poephagus gruenniens L.) is amultipurpose animal which provides meat, milk,hair, wool, and hide. As per livestock census (2007),the total population of yaks in India is 83,169 whichare distributed in Arunachal Pradesh (14,251),Himachal Pradesh (1,705), Jammu and Kashmir(61,910), Sikkim (5,225), Uttarakhand (50), WestBengal (26) and Nagaland (2). Yaks play a vitalrole in agricultural and rural economies of thepeople. They are considered to be an excellent packanimal for transportation of goods in difficult terrain(Lensch 1996). They are also considered to be oneof the hardiest animals and an efficient converterof forest biomass into valued beef (Rahman et al.2007). They are reared under free-range system inthe high hills and migratory system of grazing is inpractice. They becomes susceptible to manydiseases affecting cattle due to the reason that inwinter, yaks are taken to a lower altitude grazingland (<3000 msl) which is shared by otherdomesticated animals. Therefore, many of theinfectious diseases of cattle are also reported in yaks(Geilhausen 2000).

Gastrointestinal (GI) parasitic infections inanimals cause degradation of health as a resultproduction of quality milk, meat and hair productsdecrease (Waller 2002). This GI parasitic infectionis one of the most common health problems in thehilly regions of India. Prevalence of gastrointestinalparasites is considerably influenced bygeographical location and climatic conditions.There are reports of nematodes, cestodes andtrematodes infection in yaks from India (Katiyar etal. 1981; Ansari et al. 1989; Ansari and Rai 1991;RangaRao et al. 1994; Yadav et al. 2007). GIparasitic infections in animals may vary from timeto time within a state even within an area dependingupon the climatic conditions of the area, availabilityof infective stages of the parasites in the pastureand management practices. The information relatedto yak health is very scarce due to the remoteness,inaccessibility and the migratory system of yakhusbandry (Rahman et al. 2010). Keeping in viewof these, the present study was undertaken in somepockets of Arunachal Pradesh and Sikkim, to addmore information regarding GI parasitic infectionsin yaks.





43


During the year 2011-12, a total of 232 numbersof faecal samples of yaks were collected fromMandala, Dirang, West Kameng district, ArunachalPradesh (n=152) and East Sikkim, Gnathang andKupup area (n=80). All the samples were collectedrandomly directly from rectum in sterile plasticcontainer and brought to the laboratory maintainingrefrigerated condition. Faecal samples obtainedwere examined by direct smear, sedimentation andflotation methods as per standard techniques(MAFF 1986). Quantitative examination of thesefaecal samples was done to know the eggs per gramof faeces (EPG) by Modified MacMaster Technique(MAFF 1986). The eggs of the helminthes wereidentified using low and high power microscopeaccording to the size of eggs and morphologicalcharacteristics (Soulsby 1986).


The prevalence of GI parasitic infection in yakduring the study period has been presented in table1. It could be observed from the table that, out of232 numbers of faecal samples of yak, 56 (24.13%)were found positive for gastrointestinal parasiticinfection. The percentage of infection recorded inMandala (Arunachal Pradesh) was 26.31% and inSikkim was 20.00%. Only Strongyle sp. andEimeria sp. were found in faecal samples of yakscollected from these two areas. The percentage ofinfection of Strongyle sp. and Eimeria sp. were95.00% and 10.00% in Arunachal Pradesh and75.00% and 25.00% in Sikkim, respectively. Meanfaecal egg count (FEC) of infected yaks inArunachal Pradesh and Sikkim were 185.00 (ranges50-750) and 168.75 (ranges 50-250), respectively.

No cestode and trematode infections could berecorded from the samples collected from both theplaces in the study.

The present findings of percentage of infectionsin yaks of Sikkim is in agreement with those ofRahman et al. (2010) who reported 20.68%gastrointestinal parasitic infection in yaks of Sikkimduring 2001 to 2008. Although they have reportedhigher FEC ranges from 100 to 2900, but in thepresent study lower EPG ranges (50-250) with meanEPG 168.75 have been observed, might be due topersonal variation. On the contrary, Bandyopadhyayet al. (2010) observed lower prevalence of GIparasitic infection in yaks of Sikkim (10.05%) incomparison to the present study but they recordedFEC ranges from 100 to 200 which is almost similarto the present study. In a recent study at ArunachalPradesh (West Kameng and Tawang), Bam et al.(2012) reported 5.47% helminth and protozoaninfections in yaks after examination of faecalsamples. A high percentage (81.82%) of GI parasiticinfections in yaks of Nepal have been recorded byByanju et al.(2011), who also observed highprevalence of Strongyle infection (47.23%) in yaks.The highest infection rate of nematoda andcoccidian (average 56.7%) in yaks has beenreported from China (Yunfei et al. 2004). Strongylesp. (42%) was recorded as most prevalent speciesfollowed by Eimeria sp. (32%) in yaks of China(Hogg 2004), supported the findings of the presentstudy. Although most of the earlier workersrecorded some other GI parasitic infections in yaksin addition to Strongyle sp. and Eimeria sp. mightbe due to nonavailability of infective stages of suchinfections in our study area.

CONCLUSIONS

It can be concluded from this study that amoderate percentage of yaks were suffering fromGI parasitic infections with less FEC which issignificant to contaminate the pasture and spreadinfections to healthy yaks as well as to increaseEPG on repeated infections.

ACKNOWLEDGEMENTS

We are thankful to Indian Council ofAgricultural Research, New Delhi to carry out this

Table 1: Prevalence of GI parasitic infection in

yaks with EPG

Location Nos. of faecal Nos. Meansamples Positive EPGexamined (%)

Arunachal Pradesh 152 40 (26.31) 185.00Sikkim 80 16 (20.00) 168.75Total 232 56 (24.13) 181.50



44

research work under All India Network Programmeon Gastrointestinal Parasitism. The facilitiesprovided by Director, ICAR Research Complex forNEH Region, Umiam, Meghalaya are thankfullyacknowledged.

REFERENCES

Ansari MZ, Rai MK, Chauhan HVS (1989). Pathology of liver,lung and caecum of yak (Bos poephagus) infected withDicrocoelium, Fasciola, Echinococcus and Trichuris. TheIndian J Anim Sci 59: 552-554

Ansari MZ, Rai MK (1991). Studies on occurrence andincidence of hydatid disease in yak in Sikkim. IndianVet J 68: 112-114

Bam J, Deori S, Paul V, Bhattacharya D, Bera AK, Bora L,Baruah KK (2012).Seasonal prevalence of Yaks inArunachal Pradesh, India. Asian Pac J Trop Dis 2: 264-267

Bandyopadhyay S, Pal P, Bhattacharya D, Bera AK, Pan D,Rahman H (2010). A report on the prevalence ofgastrointestinal parasites in yaks (Bos poephagus) in thecold desert area of North Sikkim, India. Trop Anim HealthProd 42:119-121

Byanju R, Shrestha SP, Khanal DR (2011). Prevalence ofgastrointestinal parasites in yaks of Lehe VDC, ManasluConservation Area. Nepal J Sci Tech 12: 366-369

Gielhausen HE (2000). Serological survey on infectiousdiseases of a white yak herd in the Gansu Province.Proceedings of the 3rd. International congress on yaksheld in Lhasa (September 4-9 2000) Nairobi, Kenya

Hogg K (2004). Internal parasites of yak (Poephagus

grunniens) of the Gannan, Gansu Province, P.R. China

Proceedings of the International Congress on Yak,Chengdu, Sichuan, P.R. China

Katiyar RD, Srivastava VK, Khera RC, Sinha SB (1991).Incidence of Helminths in domesticated yak (Bos

poephagus) in Sikkim. Livestock Res 1:115-118Lensch, J (1996). Yaks, Asian mountain cattle-in science and

in practice, International Yak Newsletter, 2: 1-11MAFF (1986). Manual of Veterinary Parasitological

Laboratory Technoques, HMSO, London.Rahman H, Bhattacharya M, Rajkhowa J, Soud N, Nandankar

U, Mukherjee S (2010). Seroprevalence of brucellosisin yaks (Poephagus grunniens). Indian J Anim Sci 77:4-7

Rahman H, Pal P, Bandyopadhyay S (2010). Occurrence ofgastrointestinal parasites in domestic yaks in Sikkim.Indian J Anim Sci 80: 195-198

RangaRao GSC, Sharma RL, Hemaprasanth (1994). Parasiticinfections of Indian yak Bos (Poephagus) grunniens -An overview. Vet Parasitol 53: 75-82

Soulsby EJL (1986). Helminths, Arthropods and Protozoa ofDomesticated Animals. 7th Edn. The English LanguageBook Society and Bailliere Tindal, London.

Waller PJ (2002). Reindeer (Rangifer tarandus) and yak (Bos

(Poephagus) grunniens) : Disparate animal species –similar environment, management and parasite problems?In: Proceedings of the 3rd. International congress on yaksheld in Lhasa (September 4-9 2000) Nairobi, Kenya, pp429-438

Yadav SC, Saravanan BC, Borkataki S, Barua K (2007). Arecord of Parafilaria bovicola from yak (Poephagus

grunniens L. ) in India. J Vet Parasitol 21: 37-38Yunfei Y, Hongning W, Guangyou Y, Guangrong L, Bing T

(2004). Epidemiological survey and control method ofenterozoic diseases of yak and Tibetan sheep in theSichuan west-north grasslands. Proceedings of theInternational Congress on Yak, Chengdu, Sichuan, P.R.China



45

Gastrointestinal Parasitic Infections in Mithun in Organised Farm

R. LAHA1*, C. RAJKHOWA2, J.K.CHAMUAH2, A. GOSWAMI1

ABSTRACT

A total of 62 numbers of faecal samples of mithuns were collected from National Research Centreon Mithun, Jharnapani, Medziphema, and Nagaland during the year 2011-12, for detection ofgastrointestinal (GI) parasitic infections, using standard techniques. Out of 62 faecal samples examined,18 (29.03%) faecal samples were found positive for GI parasitic infections. The eggs of Strongylespp. and oocysts of Eimeria spp. were recorded in 24.19% and 8.06% mithuns, respectively. Meanfaecal egg count (FEC) of infected mithuns was 103.55. No cestodes and trematodes eggs were recordedin this study. It can be concluded from this study that a lower percentage of mithuns maintained in thisfarm suffers from GI parasitic infections, but lower faecal egg counts have been observed in infectedanimals as a result of regular deworming. So, mithun rearers should practice regular deworming tocontrol GI parasitic infections.

Keywords: Gastrointestinal, Parasite, Mithun

INTRODUCTION

Mithun (Bos frontalis) is considered as ‘Cattleof Hilly Region’ (Shisode et al. 2009). Mithun playsan important role in hill agriculture by providingmeat, milk and hide. They can also be used forploughing purpose (http://www.worldvet.org/node/5122). Unlike other animals, mithun is uniquespecies of the north east in the sense that they areceremonial animals and associated withsocioeconomic status of the tribal people of north-east India. As per livestock census (2007), totalpopulation of mithun in India is 2,64,279 whichare distributed in Arunachal Pradesh (82.84%),Nagaland (12.63%), Manipur (3.79%) andMizoram (0.73%). Like other animals, mithuns alsosuffers from bacterial, viral and parasitic diseases(Rajkhowa et al. 2003, 2004a, 2004b, 2005;Chamuah et al. 2009a, 2009b). Gastrointestinal (GI)parasitic infections in mithuns have been reportedto cause mortality and morbidity (Chamuah et al.2013). GI parasitic infections in animals may varyfrom time to time depending upon the climaticconditions of the area, availability of infectivestages of the parasites in the pasture andmanagemental practices. Keeping in view of theabove, present study was undertaken to know the

GI parasitic infections in mithuns in an organisedfarm.


In the present study 62 faecal samples of mithunswere collected from National Research Centre onMithun, Jharnapani, Medziphema, Nagaland duringthe year 2011-12, to know the prevalence ofgastrointestinal parasitic infections. Faecal sampleswere collected randomly and parasitologicalexaminations of these faecal samples were doneby direct smear, sedimentation, and flotationmethods as per standard techniques (MAFF 1986).To know the eggs per gram of faeces (EPG),Modified MacMaster Technique (MAFF 1986) wasfollowed. The eggs of the helminthes wereidentified after observing the size andmorphological characteristics of eggs (Soulsby1986) using low and high power microscope.


Out of 62 faecal samples examined, 18 (29.03%)faecal samples were found positive for GI parasitic

1ICAR Research Complex for NEH Region, Umroi Road, Umiam, Meghalaya -793 1032National Research Centre on Mithun, Jharnapani, Medziphema, Nagaland-797 106* Corresponding author’s E-mail: [email protected]




46

infections. The eggs of Strongyle spp. and oocystsof Eimeria spp. were recorded in 24.19% and 8.06%mithuns, respectively. Mean faecal egg count (FEC)of infected mithuns was 103.55. A higherprevalence (70.27%) of intestinal parasiticinfections in mithuns of Arunachal Pradesh,Nagaland, Manipur and Mizoram has been reported(Rajkhowa et al. 2005). However, in the presentstudy a lower percentage of animals were found tobe infected with GI parasites with low EPG countsdue to better managements. Use of anthelminticsin this organised mithun farm might be responsiblefor such low grade of infections. Rajkhowa et al.(2005) reported the presence of cestode andtrematode infections in mithuns of ArunachalPradesh, Nagaland, Manipur and Mizoram.Besides, Chamuah et al. (2009a) reported thepresence of cestode and trematode infections inmithuns maintained in this farm. However, in thepresent study, no cestode and trematode infectionswere recorded. This might be due to the use ofanthelmintics in this organised farm and absenceof intermediate hosts like snails in the area. In thepresent study, only the eggs of Strongyle spp. andoocysts of Eimeria spp. were recorded in this farm.Earlier studies reported presence of othernematodes in addition to Strongyle spp. and Eimeria

spp. from mithun maintained in this farm as wellas Arunachal Pradesh and Bhutan (Chamuah et al.2009a; Rajkhowa et al. 2005; Tandon et al. 2005).It can be concluded from this study that a moderatepercentage of mithuns maintained in this farmsuffers from GI parasitic infections, but lower faecal

egg counts have been observed in infected animalsas a result of regular deworming. So, mithun rearersshould practice regular deworming to control GIparasitic infections.

ACKNOWLEDGEMENTS

We are thankful to the Indian Council ofAgricultural Research, New Delhi for supportingthis research work under the All India NetworkProgramme on Gastrointestinal Parasitism. Thefacilities provided by Director, ICAR ResearchComplex for NEH Region, Umiam, Meghalaya isthankfully acknowledged.

REFERENCES

Chamuah JK, Das M, Islam S, Rajkhowa C,Chakraborty A (2009a). Studies on naturally acquiredgastrointestinal helminth of mithun (Bos frontalis). J VetParasitol 23: 37-40

Chamuah JK, Das M, Rajkhowa S, Islam S, Rajkhowa C(2009b). Coccidiosis in mithun (Bos frontalis). IndianVet J 86: 419-420

Chamuah JK, Perumal P, Singh V, Mech A, Borkotoky D(2013). Helminth parasites of mithun (Bos frontalis) -An overview. Indian J Anim Sci 83: 235-237

MAFF (1986). Manual of Veterinary Parasitological LaboratoryTechnoques, HMSO, London

Rajkhowa S, Rajkhowa C, Bujarbaruah KM (2003). Diseasesof mithun (Bos frontalis) - A review. Vet Bull 73: 1R-6R

Rajkhowa S, Bujarbaruah KM, Rajkhowa C, Kapenlo T(2004a). Incidence of intestinal parasitism in mithun (Bos

frontalis). J Vet Parasitol 19: 39-41Rajkhowa S, Rajkhowa C, Rahman H, Bujarbaruah KM

(2004b). Seroprevalence of infectious bovinerhinotracheitis in mithun (Bos frontalis) in India. RevSci Tech 23: 821-829

Rajkhowa S, Bujarbaruah KM, Rajkhowa C, Kapenlo T (2005).Incidence of intestinal parasitism in mithun (Bos

frontalis). J Vet Parasitol 19: 39-41Shisode MG, Khanvilkar AV, Kulkarni MD, Samant SR, Yadav

GB, Bawaskar MS (2009). Mithun: The pride animal ofNorth-Eastern hilly region of India. Vet World 2: 480-481

Soulsby EJL (1986). Helminths, Arthropods and Protozoa ofDomesticated Animals. 7th Edn. The English LanguageBook Society and Bailliere Tindal, London

Tandon V, Kar PK, Das B, Sharma B, Dorjee J (2005).Preliminary survey of gastro-intestinal helminth infectionin herbivorous livestock of mountainous regions ofBhutan and Arunachal Pradesh. Zoos’ Print J 20: 1867-1868

Fig. 1: Mithuns maintained at National Research

Centre on Mithun, Jharnapani, Medziphema,

Nagaland



47

Estimation of Annual Maximum Rainfall for Central Meghalaya

LALA I. P. RAY*, P. K. BORA, V. RAM, A. K. SINGH, N. J. SINGH, R. SINGH, S. M. FEROZE

ABSTRACT

Daily rainfall data for 28 years (1983-2010) of Central Meghalaya, Nongstoin station has been collectedand frequency analysis for maximum daily rainfall has been attempted. The annual maximum dailyrainfall data has been fitted to five different probability distribution functions i.e. Normal, Log-normal,Pearson Type-III, Log Pearson Type-III and Gumbel Type-I extreme. The probable rainfall value fordifferent return periods has been estimated. These estimated values have been compared with thevalues obtained by Weibull‘s Method. The analysis indicates that, the Gumbel distribution gives thecloset fit to the observed data. Hence, Gumbel distribution may be used to predict maximum rainfall,which will be a great importance for economic planning and design of small and medium hydraulicstructures.

Keywords: Rainfall analysis, Maximum daily rainfall, Rainfall and probability distribution

College of Post-Graduate Studies, Central Agricultural University, Umiam- 793103, Meghalaya

INTRODUCTION

The study place, Nongstoin station is located at25° 10´ to 25° 51´ North Latitude and 90° 44´ to91° 49´ East Longitude at an altitude of 1,200 mabove mean sea level. The behavioral pattern ofrainfall with reference to the amount of rainfall andnumber of rainy days in a week at Nongstoin,Meghalaya from historic daily rainfall records(1983-2010) were calculated using probabilisticapproach. For Nongstoin, the normal annual rainfallranges from 180 - 600 cm, which is highly erraticand occurrence of high intensity rainfall issomewhat common. Under such circumstances,probable maximum rainfall value is of greatimportance while designing hydraulic structures.Generally, areas with low rainfall are having highrainfall variability, the North East Hilly (NEH)region, by virtue of receipt of heavy rainfall thevalue ranges from 8-15%.

Hydraulic and design engineers requiremaximum daily rainfall of different return periodsfor safe planning and design of small and mediumhydraulic structures such as small dams, bridges,culverts drainage works, etc. This would also beuseful for forecasting the floods to downstreamtowns and villages. Prediction of maximum dailyrainfall for higher return periods is usually done

by a probability distribution function which fit theobserved rainfall data better. Probability analysisof one day rainfall has been attempted for differentplaces (Sharda and Bhusan 1985; Prakash and Rao1986; Aggarwal et al. 1988; Bhatt et al. 1996Mohanty et al. 1999; Kumar 1999 and 2000; Georgeand Kolappadan 2002; Suresh 2003; Dingre andAtre 2005; Pandey and Bisht 2006; Ray et al. 2012a;Ray et al. 2012b). An attempt has been made inthis present study to estimate the probablemaximum daily for different return periods forNongstoin, Meghalaya by five different probabilitydistribution functions and to select the best one.


Annual maximum daily rainfall data ofNongstoin, for 28 years (1983-2010) were fitted tofive probability distribution functions i.e. Normal,Log normal, Pearson type-III, Log Pearson type-IIIand Gumbel type-I extreme distribution to predictone day maximum rainfall. The five differentprobability distributions (Chow et al. 1988) forfitting hydrologic data are given as follows:

Normal Distribution

The probability density function of thisdistribution is given by:





48

(1)

Where µ and σ are mean and standard deviationof variate ‘x’ respectively (Singh 1994)

Log Normal Distribution

The probability density function of thisdistribution is given by:

… (2)

where y = log x, µy and ó

y are mean and standard

deviation of variate ‘x’ respectively (Singh 1994)

Pearson type-III Distribution

… (3)

where λ = scale parameter; η is the shapeparameter; Γ is gamma function and A = locationparameter.

Log Pearson type-III Distribution

… (4)

where λ = scale parameter; η is the shapeparameter; Γ is gamma function and A = locationparameter.

Gumbel type-I extreme Distribution

… (5)

where α = scale parameter and β = locationparameter (Singh 1994)

All the five different probability distributionfunctions were compared by chi-square (χ2) test ofgoodness of fit by the following equation

… (6)


Central Meghalayan district i.e. West KhasiHills district is the largest district in the state with

a geographical area of 5,247 km2 with districtheadquarters located at Nongstoin. It has apopulation of 3,85,601 with a population densityof 73 (Census 2011). Agriculture is the primeoccupation of the district which is mostly rainfed.The monthly normal and extreme rainfall (numberof rainy days) along with SD, CV and percentagecontribution at Nongstoin station is presented inTable 1. More than 60% of the rainfall is contributedbetween June to September. The annual averagerainfall of Nongstoin is calculated to be 3,529.4mm with 118 numbers of rainy days. The maximumand minimum rainfall of central Meghalaya is6,189.2 and 1,825.0 during 1988 and 1998,respectively. A decreasing rainfall is found for theNongstoin station. From Table 1 it may be notedthat the standard deviation (SD) is more than 100mm for the month of April to October. The highestSD was found for the month of July i.e., 509.02;and it was the lowest for the month of Decemberi.e., 21.94. Contrarily, the coefficient of variation(CV) is the highest for the non-rainy season. Thehighest CV was recorded for the month ofDecember i.e. 128.55%. Percentage contributionof rainfall during the peak period (June toSeptember) amounting to around 73.79%. For therest eight months of the calendar year the quantumof rainfall is distributed very unevenly.

Analysis of rainfall data for the station was donefor evaluating the start and end of rainy season usingforward and backward accumulation of standardmeteorological week (SMW) rainfall. It may berecorded that the monsoon almost starts at 21st

SMW and ends at the end of 28th SMW. Similarlyduring monsoon the percentage of occurrence ofdrought is around 7% for the week 23rd, 26th, 34th

and 37th week.The probable rainfall values for different

probability distribution functions and theircomparison with the observed value have beenpresented in Table 2. The estimation of maximumannual rainfall for a region is of great importanceso as to install and establish soil conservation ordrainage structure in that place (Chow et al. 1988).Since these structures need to overcome the extremeweather events, their hydraulic design has to bemade carefully considering maximum value of therainfall with its recurring interval. The probabilitiesof occurrence of the extreme events have been doneby Weibull method (Table 2). The return period ofthe extreme event is the reciprocal of the probability



49

Table 1: Monthly Normal and Extreme Rainfall (Number of Rainy Days) along with SD, CV and

Percentage contribution at Nongstoin

Month Normal Extreme Value Standard Coefficient Percentage(mm) Deviation of Variation contribution

Minimum Maximum (mm) (%) (%)(mm) (mm)

January 16.43 0 152.7 29.92 182.09 0.47(1.18) (0) (5) (1.19) (100.80) (1.00)

February 25.50 0 104.7 24.50 96.08 0.72(2.25) (0) (8) (1.88) (83.48) (1.91)

March 76.12 11.5 257.2 65.63 86.23 2.16(4.75) (1) (12) (3.36) (70.79) (4.04)

April 196.09 17.3 467 104.37 53.22 5.56(10.36) (2) (18) (4.10) (39.61) (8.81)

May 350.44 135.4 990.1 195.26 55.72 9.93(15.32) (8) (25) (3.70) (24.16) (13.03)

June 641.40 159.9 1051.2 249.02 38.82 18.17(18.89) (12) (25) (3.79) (20.08) (16.07)

July 983.41 367.5 2655.5 509.02 51.76 27.86(20.93) (13) (26) (2.79) (13.32) (17.80)

August 570.73 240.4 2021 364.51 63.87 16.17(18.43) (11) (28) (3.47) (18.82 (15.67)

September 409.15 0 931.2 237.31 58.00 11.59(15.25) (0) (22) (4.26) (27.91) (12.97)

October 212.01 24.4 619.2 167.23 78.88 6.01(7.32) (2) (14) (3.30) (45.08) (6.23)

November 31.03 0 204 47.97 154.59 0.88(1.68) (0) (4) (1.47) (87.40) (1.43)

December 17.07 0 65.6 21.94 128.55 0.48(1.29) (0) (5) (1.49) (115.67) (1.09)

(Murthy 2002). The best probability distributionfunction was determined by comparing the Chi-square (÷2) value (Bhatt et al. 1996; Chow et al.1988). The chi-square values calculated for Normal,Log normal, Pearson type-III, Log Pearson type-IIIand Gumbel extreme distribution are 77.98, 51.87,74.85, 55.14 and 45.35, respectively. This suggeststhat Gumbel distribution gives a better fit to theobserved data (Table 2). Similar trend ofdistribution for maximum annual rainfall wasreported by Ray et al. (2012a) for Barapani station,Ri-Bhoi district of Meghalaaya. Gumbel extremedistribution generally fits well for extreme rainfallevents of hilly areas like Srinagar (Dingre and Atre2005), Ooty (Jeevarathnam and Jaykumar 1979),Pantnagar (Kumar 1999), Ranichauri (Kumar2000), Almora (Pandey and Bisht, 2006), etc.

However, the distribution patterns are different forvalley, river basin and plain regions (George andKolappadan 2002).

CONCLUSIONS

Gumbel probability distribution has been foundapproropriate on the basis of the Chi-square (÷2)goodness of fit test for describing the data set understudy and is the most suitable for predictingmaximum daily rainfall in Nongstoin, Meghalayacondition. Thus Gumbel distribution can safely beused for the design of small and medium hydraulicstructures in mid altitude regions of CentralMeghalaya.



50

ACKNOWLEDGEMENTS

The financial assistance received from CentralAgricultural University (CAU, Imphal) vide CodeNo. PG.IRP-VI/2010-11; dated, 30th November2010; for conducting the experiment is dulyacknowledged

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Bhatt VK, Tiwari AK, Sharma AK (1996). Probability modelsfor prediction of annual maximum daily rainfall of data.Indian J Soil Cons 24(1): 25-27

Chow VT, Maidment DR, Mays LW (1988). AppliedHydrology. McGraw Hill Book Company. 11, 12: 371-415

Dingre S, Atre AA (2005). Probability analysis for predictionof annual maximum daily rainfall of Srinagar region(Kashmir valley). Indian J of Soil Cons 33(3): 262-263

George C, Kolappadan C (2002). Probability analysis forprediction of annual maximum daily rainfall of Periyarbasin in Kerala. Indian J of Soil Cons 30(3): 273-276

Jeevarathnam K, Jaykumar K (1979). Probability analysis ofannual maximum daily rainfall for Ootacamund. IndianJ Soil Cons 7(1): 10-16

Kumar A (1999). Probability analysis for prediction of annualmaximum daily rainfall for Pantnagar. Indian J of SoilCons 27(2): 171-173

Kumar A (2000). Probability of annual maximum daily rainfallof Ranichuari (Tehri Garhwal) based on probabilityanalysis. Indian J of Soil Cons 28(2): 178-180

Murthy VVN (2002). Land and Water ManagementEngineering (3rd Edition). Kalyani publishers, p 31

Table 2: Annual maximum daily rainfall of Nongstoin for five different probability distribution

functions

Sl. Probability Return Observed Estimated value (E)No. (%) period value (O)

Normal Log Normal Pear -III Log Pearson-III Gumbel

1. 0.01 100.0 - 500.67 578.56 613.79 579.47 599.722. 0.02 50.0 - 473.8 525.62 549.22 524.37 543.323. 0.03 29.0 600 450.62 483.86 498.68 481.43 498.734. 0.07 14.5 450.2 417.58 429.99 434.44 426.73 441.295. 0.10 9.7 360.5 395.75 397.73 396.76 394.34 407.046. 0.14 7.3 344.4 378.73 374.28 369.89 370.97 382.257. 0.17 5.8 340.3 364.43 355.64 348.93 352.5 362.638. 0.21 4.8 340.2 351.86 340.02 331.69 337.09 346.259. 0.24 4.1 315 340.48 326.48 317 323.79 332.0810. 0.28 3.6 303 329.95 314.43 304.18 312 319.5111. 0.31 3.2 300 320.06 303.51 292.77 301.34 308.1412. 0.34 2.9 297 310.64 293.47 282.47 291.57 297.6913. 0.38 2.6 282 301.57 284.11 273.06 282.48 287.9714. 0.41 2.4 280.4 292.75 275.31 264.38 273.96 278.8315. 0.45 2.2 275 284.11 266.94 256.31 265.87 270.1516. 0.48 2.1 275 275.58 258.92 248.75 258.14 261.8317. 0.52 1.9 265 267.07 251.18 241.61 250.69 253.7918. 0.55 1.8 259.4 258.54 243.63 234.83 243.44 245.9619. 0.59 1.7 247.3 249.9 236.23 228.34 236.35 238.2820. 0.62 1.6 234 241.08 228.90 222.11 229.34 230.6821. 0.66 1.5 220.5 232.01 221.61 216.1 222.37 223.1122. 0.69 1.5 220.4 222.59 214.27 210.26 215.38 215.4923. 0.72 1.4 220.4 212.7 206.83 204.57 208.3 207.7424. 0.76 1.3 220 202.17 199.20 198.98 201.05 199.7725. 0.79 1.3 186 190.79 191.27 193.46 193.52 191.4626. 0.83 1.2 183.2 178.22 182.87 187.95 185.57 182.6127. 0.86 1.2 183.2 163.92 173.76 182.42 176.96 172.9628. 0.90 1.1 147 146.9 163.51 176.77 167.29 162.0129. 0.93 1.1 140.5 125.07 151.25 170.88 155.73 148.7330. 0.97 1.0 107.2 92.03 134.41 164.5 139.89 130.11

Chi-square (÷2) value 77.98 51.87 74.85 55.14 45.35



51

Pandey SC, Bisht KKS (2006). Probability analysis forprediction of annual maximum daily rainfall forHawalbagh (Almora). Indian J of Soil Cons 34(1): 75-76

Prakash C, Rao DH (1986). Frequency analysis of rain datafor crop planning (Kota). Indian J Soil Cons 14(2): 23-26

Ray, Lala IP, Bora PK, Ram V, Singh AK, Singh R, FerozeSM (2012a). Probable Annual Maximum Rainfall forBarapani, Meghalaya. Journal of Progressive Agriculture3 (1): 16-18

Ray, Lala IP, Bora PK, Ram V, Singh AK, Singh R, FerozeSM (2012b). Meteorological drought assessment in

Barapani. Journal of Indian Water Resources Society(IWRS) 32 (1-2): 56-61

Sharda VN, Bhusan LS (1985). Probability analysis of annualmaximum daily rainfall for Agra, Indian J Soil Cons13(1): 16-20

Singh J, Dhillon SS (1994). Physical determinants ofagriculture patterns: In Agriculture Geography (2nd

Edn.).Tata McGraw Hill Publication Co. New Delhi, pp60 -72

Suresh R (2003). Probability model for predicting annualmaximum daily rainfall for Pusa farm (Bihar). Indian Jof Soil Cons 31(1): 84-85



52

First Report on Buckwheat (Fagopyrum esculentum) from High

Altitude Temperate Zone of North Western Himalayan Region

R. A. SHAH

ABSTRACT

Buckwheat (Fagopyrum esculentum) is one of the important unattended crops cultivated in the pocketsof the high altitude temperate zones of North West Himalayan region. Due to the less economicoutput and cultivation constraints the crop is at the verge of extinction though it is of high medicinaland nutritive value. The present study is an attempt to explore the status of buckwheat in the pocketsof North West Kupwara district of Jammu & Kashmir. The study brings in the various causes of thedecrease in acreage under buckwheat and the various possible remedies to be evolved to review itsproduction for the sustenance of the farming families affiliated with it.

Keywords: Buckwheat, Himalayan region, Medicinal and nutritive value, Extinction

National Agriculture Innovation Project-3 SRLS (Kupwara) SKUAST-K -193222

INTRODUCTION

Buckwheat (Fagopyrum esculentum) belongingto the family Polygonaceae is a moistureloving,cool-climate, annual cereal crop. It is a native ofCentral Asia, cultivated in China and other Easterncountries as a bread-corn. Buckwheat is a pseudocereal. It produces edible seeds used as a cerealgrain, though the plant does not belong to the familyPoaceae (Ahmad and Raj 2012). The fruit is anachene with a single seed inside a hard outer hull,which is dark brown or black in colour. The seedcoat is green or tan, which darkens the buckwheatflour. Since buckwheat was once a staple food ofhigh altitude temperate zones of Jammu & Kashmirviz., Ladakh, Baderwah, Gurez, Keran and Machil.Now the acreage under this crop is drasticallyreduced to a few cultivation pockets and is at theverge of its extinction. Keeping in view the studywas conducted to assess the past and present statusof this valuable agricultural landrace.


Kupwara district is located between 34.17 to34.21 North Latitude and 73.10 to 73.16 EastLongitude on extreme north-west of Kashmirvalley, spread on an area of 2379 square kilometers

including 1651 sq. km. of forest area, wrapped bythe Pirpanchal and Shanbarimountain rangesaccompanied by snow clad peaks and dense verdantforests. Its northern and western borders form theline of control between India and Pakistan, and theeastern and southern borders touch Sopore,Bandipore, and Baramulla Tehsils (Fig. 1). Thereare three bad pocket areas, namely, Machil, Keranand Karnah, located near L.O.C which remains landlocked for more than six months in a year. Machiland Keranis located around the famous river Kishan

Fig. 1: Map of Kupwaradistrict

(Source:Kupwara.nic.in)




53

Ganga which separates Pakistan occupied Kashmirand Jammu & Kashmir. The survey on theidentification and utilization pattern underexploredBuckwheat was conducted in Machil and Keranvalleys of the district Kupwara. Five villages fromMachil (Machil, Pushwari, Dappal, Chontiwari,Duddi) and Keran (Kundian, Mundian, Pathro,Farkin, Bitchwal) zones of Kupwara district werepurposively selected and the investigations weremade through multiple field visits, questionnairesand interviews with elderly people regarding thepast and present status of buckwheat cultivation.


The details of the present investigation carriedout to study the status of buckwheat in high altitudezones of North Western Himalayas is presentedhereunder.

Importance of Buckwheat in the study area

Since cropping season of the studied area is ofshort duration due to early prolonged winter andearly snowfall. The crops like maize, paddy, etc,do not mature in time resulting in drastic yieldreduction. It becomes necessary for the farmingcommunity of the areas to relay on the cultivationof buckwheat, which is of short duration crop (2–3months), and fits well in the high AltitudeTemperate zone. Although it is less productive thanother grain crops, it is particularly adapted to verypoor, badly-tilled land which can produce scarcelyanything else (Fig. 2). It is one of the quickestgrowing cover crops taking only 4–5 weeks fromseeding to flowering thus suppresses weeds andprevent soil erosion due to intensive runoff. Youngleaves are eaten as vegetable and the stalks is animportant source ofcattle feed. Since it maturesquickly, itescapes early autumn frost injury. It isalso a good green manure crop and improves soil

texture, and also increase nutrient status of thesoil,particularly phosphorus and micronutrients inthe root zone, which is beneficial for the succeedingpotato crop (the only cash crop from study area) ina rotation.

Buckwheat flour is unsuitable for bread makingowing to its non-sticky character of its proteinthereby consumed in the special preparationLocally known as Seer and also used to makepancakes particularly during the winter months ,which is highly palatable. The common belief ofthese tribal communities is that Seer keeps themwarm during chilly winter months. It is also reportedthat Buckwheat is of high nutritive and medicinalvalue as the seed contains high crude proteincontent (18%), with biological values above 90%(Eggum et al. 1981), containing a highconcentration of all essential amino acids,especially lysine, threonine, tryptophan and thesulphur-containing amino acids (Bonafaccia et al.

2003). Buckwheat is very rich in trace elements(for example Zn, Cu, Mn and Se), however, it mustbe grown in unpolluted areas, to avoid accumulationof contaminating elements. Different millingfractions may contain different minerals andproteins, dark flours being generally richer than thelight ones (Ikeda and Yamashita, 1994; Kreft et al.,1996). Buckwheat is also reportedly growntraditionally in relatively warmer areas of both Lehand Kargil districts of Ladakh, where double-cropping is possible (Ahmad and Raj 2012).

Traditional cultural practices

Buckwheat is grow in a traditional way and thespecial cultural practices have been developed bythese ethnic communities as per their requirements.a. Soil: it is grown in well manured and drained

soils of the study area.b. Soil preparation: Soil is prepared by local

plough giving two to three ploughings followedby levelling.

c. Manuring: Crop is pure organic and is cultivatedon the sole application of Farm yard manure,blind application (as per availability) of whichis done during soil preparation.

d. Sowing: Sowing is done by broadcasting methodduring second fortnight of April using one five(5) quintals of seed per hectare.

e. Weed control: Due to blanket application of seedrate and high germination value of buckwheatthe soil is early covered by the crop resulting inweed growth suppression as such weed control Fig. 2: Buckwheat in Machil



54

is not required in the said crop due to naturalweed management.

f. Irrigation: The crop is grown as rainfed and isnot irrigated by any artificial means.

g. Crop protection measures: Due to its hardynature, the crop is devoid of any major insect/pest attack, accept in some negligible caseswhere it is attacked by wild animals (monkey).

h. Harvesting and threshing: The crop matures inabout three months and is harvested soon afteraround 80% of its foliage turns brownish incolour and the grain contains minimum moisturecontent which is detected by thumb method.Threshing is done manually by bullocks on athreshing floor/ beating of the stacks on thewooden log.

i. Yield:16 to 20 quintals per hectare

Constraints

Low benefit cost ratio of buckwheat

a. Since the crop is of very short duration, solelycultivated on organic manures, the properspacing between the plants is not maintained,exhausted seed is used and lack of improvedagronomic practices results in reduction in grainyield, short growing season and dwarf cropgeometry results in reduced biological yield.

b. The soil is prepared by bullocks which is costlyand increased labour charges during postharvesting management results in high cost ofcultivation.

Change of Staple food

a. Since the land holdings are minimised due topopulation growth and year by yearconstructions, the farming community uses thesmall holdings for kitchen gardening and foddermaize cultivation for their livestock which is thebackbone of their economy/ livelihood security.

b. Government keeps buffer stock of rice andwheat flour at their outlets on special subsidizedrates for these far flung areas which has almosteliminated the necessity of growing buckwheatby the farming community.

c. High sensitivity to climate, changing foodhabits, increasing demand of land for fodder andwheat, and growing competition with newercrops in the region like French beans, turnip andgreen peas as the second crop. Very lowtemperature reduces germination, favours malesterility and reduced seed set

Strategies

1 Laying of demonstration plots in the buckwheatgrowing areas is the need to set the improvedagronomic practices for the crop to increase theyield at the reduced cost of cultivation

2 The new and improved farm tools andmachinery is to be developed to reduce thedrudgery faced during Buckwheat cultivationand decreaselabour charges during postharvesting management whichotherwise resultsin high cost of cultivation.

3 New and improved varieties need to bedeveloped and tested against the prevailingclimatic conditions along with maintaining andconserving the traditional vulnerable gene pool.

4 Special schemes should be launched in suchtribal areas to attract the farming community forthe cultivation of buckwheat.

5 The nutritive value and medicinal value ofbuckwheat is to be popularised.

6 Post harvest technology of the buckwheat id tobe developed through value addition.

CONCLUSIONS

The unexplored nutritional quality andmedicinal value of buckwheat has not yet receivedthe attention as it deserves by the researchers andpolicy makers. A dire and urgent need lies inreviving its cultivation and management throughnecessary programmes and policies for enhancingits scope and thereby securing the national foodsecurity interests and the livelihood of the farmingcommunity affiliated with it.

REFERENCES

Ahmad F and Raj A (2012). Buckwheat: a legacy on the vergeof extinction in Ladakh. Cur Sci, Vol. 103, No. 1

Bonafaccia G., Marocchini M., Kreft I. (2003). Compositionand technological properties of the flour and bran fromcommon and tartary buckwheat. Food Chem. 80:9-15.

Eggum B.O., Kreft I., Javornik B. (1981).Chemicalcomposition and protein quality of buckwheat(Fagopyrum esculentum Moench). Plant Food forHuman Nutrition, 30:175-179.

Ikeda S., Yamashita Y. (1994). Buckwheat as a dietary sourceof zinc, copper and manganese.Fagopyrum 14:29-34.

Kreft I., Škrabanja V., Ikeda S., Ikeda K., Bonafaccia G. (1996).Dietary value of buckwheat. - Research Reports UL,67:73-78.



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Recent Scenario of Insect-pests of Guava in North East India and

Their Eco-friendly Management

D. M. FIRAKE*, G. T. BEHERE, N. A. DESHMUKH, P. D. FIRAKE, N. S. AZAD THAKUR

ICAR Research Complex for NEH Region, Umiam, Meghalaya-793103

INTRODUCTION

Guava is one of the most refereed and legendaryfruit because of its hardy and positive bearingnature, high vitamin C content and more incomewith minimum inputs (Singh 2010). In India, guavais cultivated on 204.8 thousand hectares of landand production is about 2462.3 million tons(Anonymous 2011). Large number of insect pestshas been reported to occur on guava at variousgrowth stages, but a few are a real menace to thecultivation of this crop. More than 80 species ofinsects and mites have been recorded on guava treesaffecting the growth and yield.

Major pest of guava in the NEH region includestrunk borer, Aristobia testudo (Coleoptra:Cerambycidae). A. testudo is the most destructivepest of Litchi in China and severe incidence of thisbeetle was first observed in Meghalaya on guavaduring 1997. Recently, the same pest was also foundon pigeon-pea at the adult stage. About three speciesof fruit fly, Bactrocera dorsalis, B. cucurbutae andB. tau (Diptera, Tephritidae) found to attack guavafruits; B. dorsalis being the dominant. Maximumactivity of fruit flies is observed during August tothe December reaching its peak during September.Two species of bark eating caterpillars, Indarbela

quadrinotata and I. tetraonis are commonly foundin the region. Sucking pests includes Mealy scale,Chloropulvinaria psidii (Hemiptera, Coccidae),Mealy bugs Ferrisia virgata, Plannococcus citri,

P. lilacinus (Hemiptera, Pseudococcidae), Teamosquito bugs, Helopeltis antonii (Hemiptera:Miridae), aphids, jassids, etc (Azad Thakur et al.2009; Kalaishekar et al. 2008; Shylesha et al. 2006).Besides, recently elephant beetles of genusXyllotrupes (Coleoptera: Scarabidae) was found tobe a new threat to the guava farming in the region.

MANAGEMENT PRACTICES

Bio-intensive pest management in guava

Bio-intensive pest management (BIPM) isessentially a component of integrated pestmanagement. The primary goal of bio-intensive pestmanagement is to provide guidelines and optionsfor the effective management of pests and beneficialorganisms in an ecological context. It will help toreduce the dependence on chemical pesticides andecological deterioration. BIPM includes bio-pesticides derived from microbes, parasitoids,predators, botanicals and all conventional non-chemical methods or use of need based and lessresidual chemicals. Indian farming, which is goingthrough a transition phase, is slowly but surelyadopting the ways and means of pest managementfor sustainable agriculture.

Following pest management practices aresuggested to reduce the guava pest problems innorth east India.

Cultural practices

1. Deep ploughing of basin avoiding root cuts,to expose soil inhabiting/resting stages ofinsects, pathogen and nematodes.

2. Select deep, well leveled and well drained soil.3. Use resistant rootstocks and select disease free

nursery plants.4. Avoid flood and channel irrigation.5. Avoid injuries to trunk and roots during farm

operations.6. Adopt proper spacing, irrigation and nutrient

management.7. Avoid application of high nitrogenous fertilizers.8. Use neem cake @ 1 ton/ ha under assured

moisture conditions in nematodes infected fieldonly.

9. For the management of mealy bugs,intermingling branches should be pruned and



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spacing trees at closed distance should beavoided so that sunlight can reach throughcanopy from all the sides.

10. Fallen fruits should be destroyed by burningthem in the ground. There should be cleancultivation of orchard to avoid furtherdevelopment of fruit flies.

11. Ant colonies in the orchard should be destroyedas they are the carrier of mealy bugs to theirfeeding sites.

Indigenous technical knowledge

Mechanical practices

1. Hand picking and removal of fallen leaves beensured

2. Light traps may be operated for themanagement of scarabid beetles.

3. Regular monitoring and killing of larva of trunkborer and bark eating caterpillar by insertingwire inside the tunnel or inserting cottonswabbed with kerosene or petrol, in the holeand sealing the hole with clay.

Biological control/botanicals/biopesticides

1. Inundative release of the predator, Chrysoperla

spp. (@ 2000/acre) and Cryptolaemus

montrouzieri (@ 2-3 adults/tree) is quitesuccessful in controlling mealy bugs

2. Neem oil (3 ml/litre) + Sweet flag 1% + releaseof Mallada boninensis @ 30 larvae/tree or onespray of imidacloprid 17.8 SL @ 0.05% +release of Mallada boninensis @ 30 larvae/tree is found very effective for controllingsucking pests .

3. Neem seed kernel extract (5 %) 5% are veryeffective in reducing sucking pest complexwithout affecting its natural enemies viz. lacewing flies etc.

4. Application of systemic biopesticide viz.Verticillium leccani culture @ 0.5 % twice atfortnightly interval during February-March,June-July and September-Oct. effectivelyreduces aphids, scales and tea mosquito bugs.

5. Application of Paecilomyces fumosoroseus

culture @ 0.5 % twice at fortnightly intervalat the time of leaf emergence reduces the mitepopulation.

6. Application of Beaveria bassiana @ 0.5 % orBacillus thuringensis @ 0.1 % thrice atfortnight interval during May- June checks the

defoliators like Spodoptera spp., leaf foldersand loopers etc.

7. Raking or ploughing the soil and applicationof Beaveria bassiana @ 5 kg/ha andMetarrhizium anisopliae @ 5 kg/ha to the soilunderneath the tree canopy reduces mealy bugsand fruit flies, respectively.

8. Application of neem + garlic spray @ 3.0 ml/l during rainy season act as a repellent fordefoliators.

Chemical control measures

1. Need based, judicious and safe application ofpesticides are the most vital, triplicate segmentof chemical control measures under the ambitof BIPM. It involves developing IPM skills toplay safe with environment but proper healthmonitoring, observing ETLs and conservingbiocontrol potential before deciding in favorof use of chemical pesticides as the last resort.

2. Pasting of trunk with Bordeaux paste (1:1:10)+ 2g/litre of Sevin, during December- Januaryfor reducing trunk borers and bark eatingcaterpillars.

3. Poison baits for fruit flies and moths : Gur +Fruit juice 20 % + Malathion 2 % @ 40 baits/ha

4. Use methyl eugenol pheromone traps at fruitdevelopment stage. Collect fallen fruits anddestroy them. Spray deltamethrin (0.0025%)+ molasses 1% for fruit flies.

5. For bark eating caterpillars, spraychloropyriphos 0.07% or carbaryl 0.1% on tree

6. For stem borer - injecting monocrotophos(0.1%) @ 5 ml/ bored hole and plugging withmud

7. Following suggestions have important bearingfor the success of control measures in thecontext of IPM strategy:● Minimize number of spray and repeated

application of same pesticides should beavoided

● Avoid using of synthetic pyrethroids whichresults in resurgence of sucking pests and useselective insecticides (e.g. Karanjin) duringearly phase of season

● Proper spray equipment should be used;Knapsack sprayer is ideal for guava gardenand use proper spray volumes for unit area.

Insect pests are one of the major constraints inguava production in the hilly tracts of NEH region



57

of the country. The NEH region is exceptionallyrich in terms of flora and fauna and the ecosystemhas been less disturbed as compared to other partsof the India. Therefore, this region has a very goodpotential for use of biological control based onnatural enemies for sustainable production ofguava.

REFERENCES

Anonymous (2011). Indian Horticulture Database 2011,Ministry of Agriculture, Govt. of India, p 296 http://nhb.gov.in/area-pro/database-2011.pdf. Accessed 28March 2013

Azad Thakur NS, Kalaishekhar A, Ngachan SV, Saikia K,Rahaman Z, Sharma S (2009). Insect pest of crops innorth east India. 360p. ICAR Research Complex for NEHregion, Umiam, Meghalaya

Kalaishekar A, Azad Thakur NS, Ramamurthy VV, SankaranM, Rahaman Z, Sharma S, Riphung S, Doley A (2008).Major insect pest of horticultural crops: A field diagnosticaid, Research Bulletin No. 69, ICAR Research Complexfor NEH Region, Umiam, Meghalaya

Shylesha AN, Azad Thakur NS, Pathak KA, Rao KR, SaikiaK, Surose S, Kodandaram N H, Kalaishekar A (2006).Integrated management of insect pest of crops in northeastern hill region. Technical Bulletin No. 19. ICAR RCfor NEH Region, Umiam, Meghalaya

Singh G (2010) Development of meadow orchard in guava forhigher production. Progress Hort 42 (2): 129-133



58

Traditional Pest Management Practices and Beliefs of Different

Ethnic Tribes of Meghalaya, North Eastern Himalaya

D. M. Firake1*, D. Lytan2, D. P .Thubru2, G.T. Behere1, P.D. Firake1, N. S. Azad Thakur1

Keywords: Traditional practices, Pest management, Meghalaya

1ICAR Research Complex for North Eastern Hill Region, Umroi road, Umiam, Meghalaya-793103, India2College of Post Graduate Studies, Central Agriculture University, Umroi road, Barapani, Meghalaya-793103, India

INTRODUCTION

Meghalaya state is a part of North EasternHimalayas and it is a land-locked territory with ageographical area of 22 429 km2, lying between25° 47' and 26° 10' N latitude, and 89° 45' and 92°47' E longitude. It is exceptionally rich inbiodiversity of insect pests and their natural enemies(Firake et al. 2012a; 2012b), the Khasi and Jaintiahill districts of the state are one of the richestbotanical habitats of Asia. The region is inhabitedby three main tribal groups, the Khasi (42%), theJaintia (12%) and the Garo (32%), which togethercomprise 86% of the state’s total population of 2.3million. Besides, frequent dynamics in food grainproduction, climate of the region is highlyconducive for the occurrence and multiplication ofseveral insect pests. These insect pests causeenormous damage to the crops resulting intoshortage of food production in the region. Storedgrain pests of worldwide importance includingrodents also cause huge losses.

The state is rich in traditional knowledge, thusdifferent tribal groups of the region preferred touse their own traditional practices based on localresources, which they inherited from theirforefathers. The traditional practices are importantelement in local life and are found to be excellentfor the management of several pests. Moreover,these practices facilitate proper utilization ofavailable bio-resources ethnologically for varioussocio-economic and developmental purposes.Though, some important traditional pestmanagement practices from different regions havebeen reported (Sinha 2010; Sinha et al. 2004); stillthere is huge scope to document common traditionalpractices of the region. Therefore, in this study we

aim to collect important pest management practicesused by farmers of the region. This comprehensiveinformation would be further useful for otherfarmers of the country and also to the researchersfor its proper scientific evaluation and validation.

About 14 villages of two districts (Ri-bhoi andEast Khasi hills) of state were visited during varioustraining/awareness programmes, demonstrationsand survey conducted either by ICAR institute orstate government (during 2010 to 2012).Additionally, three main villages of Jaintia hilldistrict were also surveyed during various croppingseasons. Information on different pest managementpractices was collected through informal discussionwith the group of 35-40 farmers (comprising bothmale and females), gathered for the programmesand adaptability of practices was also confirmed.Headmen (chief) of villages were informed priorto discussion and target was successfully achievedwith the help of local language translator. Attemptswere also made to understand the belief/logicbehind each common practice.


All the available efficient traditional pestmanagement practices commonly used by the tribalfarmers of the region are presented in Table 1.Overall study indicated that, farmers intelligentlyuse locally available natural resources for themanagement of noxious pests. Majority of practiceswere based on specific mechanisms or beliefs ofthe different tribes, which was either gained throughyears of experiences or from their precedinggenerations. Plants or products mentioned in thestudy (viz., neem, jayur, tobacco, jackfruit, bamboo,



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Table 1: Traditional pest management practices commonly used by the tribal farmers of the region

SN Traditional practices Target Belief/Remark

1 Placing tin or wooden plate containing rice Birds Birds attracts to feed on rice grains and stuck to the plategrains and latex of jackfruit (Artocarpus surfaceheterophyllus) into the paddy field

2 Use of gummy sticks in paddy field: Birds When bird rest and/ or sit on the stick for feeding the riceRolling of gummy thread (of latex) over the grains, get stuck to the gummy portion. After that, farmersbamboo sticks and fix it in the field remove the captured birds.

3 Placing bird perches in paddy and Birds Predation: while resting on the sticks bird predates onvegetable field insect pests

4 Placing cow blood inside wooden containers Birds Repellent: foul smell coming out form rotten blood repels(mostly bamboo pipe) into the paddy field the birds

5 Sprinkling of domestic ash on vegetables Defoliators Ash acts as a corrosive materials and helps in desiccationand soft or water loss from insect bodybodied insects

6 Placing green bamboo sticks into the Stem borers, Bamboo serves as a bird perchesirrigation source of paddy field leaf folder Sap of raw bamboo shoot contain insecticidal principle

and birds7 Burning of crop residue after harvesting of Hibernating Resting stages of insect pests get eradicated due to

paddy and maize stages of burninginsects,mostly stemborers

8 Placing of rotten crab/frog on sticks in Gundhi bug Faull smell attract gundhi bugs and destroy the bugs afterpaddy field collection

9 Crushing of Jaiur-blai (Zanthoxylum Parasites Smell of jayur repels the parasites like leech, nematodes,oxyphyllum Egdew) fruits on the body parts worms etc.before working in the paddy field

10 Placing of dried neem (Azadirachta indica) Rice weevil Neem leaves are both repellent and antifeedentleaves into the stored seeds and moths

11 Placing of small pine branches into the Stem borer, Pine exudates contain toxic principle that kills the insects.paddy field leaf folder Moreover, it reduces the green algae in rice field and also

and case acts as a bird perchesworm

12 Use of local (bamboo made) rat bait station Rodents Wooden bamboo bait stations/ containers protect the(Figure 1), traditional bamboo made traps poison baits from weather calamities and non target(Figure 2) and few conventional traps poisoning. It also increases the efficacy of the bait.utilizing local techniques Traditional bamboo made rat traps are highly efficient,

easily available and cheaper also, therefore these traps arealso popular in addition to some commercial traps.

13 Spraying of aqueous excreta of silkworm Leaf folder Killing action and repellents for leaf folderon paddy and vegetables and rice blast Some people believe that it also cure blast disease

disease14 Placing of citrus/orange peels into the Stem borer, Smell of orange peels repels the insects

paddy field leaf folderand skippers

15 Keeping slices of pumalo (Citrus grandis Stem borer Smell of pumalo repels the insectsOsbeck) in the paddy field and leaf

folder16 Use of iron wire for removal of grub from Red palm It kills the grubs (Mechanical control)

infested areca nut trees weevil17 Smoking below the hanging maize cobs in Rice weevil Smokes repels the stored grain pests

the kitchen18 Covering of banana bunch by polythene or Flea beetle Insects cant reach to the fruit surface

cloth bags19 Spraying of boiled tobacco (Nicotiana Lepido- It kills the pests. Moreover, tobacco contains insecticidal

tobacum) extract on vegetables pteran pests alkaloid, nicotine.



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pine and citrus etc) are commonly used for themanagement of insect pests in different parts of thecountry, showing their popularity among the people(Kalaisekar et al. 2008; Bhattacharjee and Ray2010; Das and Saikia 2010; Sharma and Borthakur2008; Sarangi et al. 2009)

Furthermore, jackfruit (Artocarpus

heterophyllus) latex is being used as a bird lime orfor attracting and trapping the birds in differentplaces (Elevitch and Manner 2006; Mortan 1987;Online sources as on 24.01.12: http://www.fruitsinfo.com/Jackfruit.php; http://www.cropsreview.com/jackfruit.html; http://creole-cuisine.com/2012/01/what-is-jackfruit-in-creole-cuisine/ and http://jackfruitlatex.blogspot.com/).Fruits and seeds of Jaiur-blai (Zanthoxylum

oxyphyllum Egdew) are employed as an aromatictonic in fever, dyspepsia, and expelling roundworms(Kalia et al. 1999), besides it exhibit goodantibacterial, antifungal, anthelmintic activities(Elevitch and Manner 2006) and insecticidalproperties (Mehta et al. 1981; Kokate et al. 2001;Udo et al. 2004; Owusu et al. 2007). Additionally,larvicidal properties of pines (Ansari et al. 2005)and bamboo (Anonymous 1948) have also beenreported.

Management of rice pests by erecting birdperches (Bhattacharjee and Ray 2010) andattracting the gundhi bugs through rotton crabs(Bhattacharjee and Ray 2010; Deka et al. 2006)have been reported from different corners of theregion. Red palm weevil is the severe pest of arecanut in the state and past report suggested itsmanagement through mechanical destruction (localword ‘Peit Ksain Kwai’) of grubs (Umdor 2004).Moreover, some cultural and mechanical practicesincluding local rodent traps observed in this study

are also being utilized in several places (Sinha 2010;Umdor 2004; Barooah and Pathak 2009).

Many traditional pest control practices fromtribal areas have been improvised and furtherutilized in the country, few of them includes popular‘Remodelled rat trap’ of Tamilnadu (Narayanasamy2006), ‘Improvised rotten crab trap’ of Meghalaya(Sinha et al. 2007; Pathak et al. 2001) and popular‘Fermented castor solution trap’ of Tamil Nadu forwhite grub control (Online source as on 30.12.11:h t t p : / / a g r i t e c h . t n a u . a c . i n / i t k /Inde_techknowledge_dist.html). Besides, severalbio-pesticide products have also been developedfrom traditional knowledge. However, it is worthto note that, all traditional practices are not eco-friendly; few practices may harm the ecosystem bydirect or indirect means viz. killing or destructionof birds, frogs as found in some practices resultingin disturbance to the ecosystem.

ACKNOWLEDGEMENTS

Authors are highly thankful to the Director,ICAR Research Complex for NEH Region, Umiam,Meghalaya for giving us the precious opportunityfor different training programmes anddemonstrations. Sincere thanks also go to theAgricultural Officers, State government ofMeghalaya, for their valuable help during the courseof study.

Fig. 1: Locally made rodent bait station/container

A

BFig. 2: Commonly used rat traps (A. Vaithang,

trap, B. Hnawhtawt trap)



61

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Ansari MA, Mittal PK, Razdan RK, Sreehari U (2005).Larvicidal and mosquito repellent activities of Pine (Pinus

longifolia, Family: Pinaceae) oil. J Vect Born Disease42: 95-99

Barooah M, Pathak A (2009). Indigenous knowledge andpractices of Thengal Kachari women in sustainablemanagement of bari system of farming. Ind J Trad Know8: 25-40

Bhattacharjee PP, Ray C (2010). Pest management beliefs andpractices of Manipuri rice farmers in Barak valley ofAssam. Ind J Trad Know 9: 673-676

Das D, Saikia P (2010). Indigenous technical knowledge formanagement of rice pests in Assam. Ann Pl Protec Sci18:123-126

Deka MK, Bhuyan M, Hazarika LK (2006). Traditional pestmanagement practices of Assam. Ind J Trad Know 5: 75-78

Elevitch CR, Manner HI (2006). Artocarpus heterophyllus

(jackfruit), ver. 1.1v, Species Profiles for Pacific IslandAgroforestry. Elevitch CR (Ed) (Permanent AgricultureResources (PAR), Hôlualoa, Hawai‘I) (http://www.traditionaltree.org)

Firake DM, Lytan D, Behere GT (2012a). Bio-diversity andSeasonal Activity of Arthropod Fauna in BrassicaceousCrop Ecosystems of Meghalaya, North East India. MolEntomol 3(4): 18-22

Firake DM, Lytan D, Behere GT, Thakur NSA (2012b). Hostplants alter the reproductive behavior of cabbage butterfly,Pieris brassicae (Lepidoptera: Pieridae) and its endo-larval parasitoid, Hyposoter ebeninus (Hymenoptera:Ichenuomonidae) in cruciferous ecosystems. FloridaEntomol 95(4): 905-913

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Kokate SD, Venkatachalam SR, Hassarajani SA (2001).Zanthoxylum armatum extract as mosquito larvicide. ProcNation Acad Sci, India Sec B- Biol Sci. Allahabad: NationAcad Sci, India, 71B: 229-232

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Narayanasamy P (2006). Traditional knowledge of tribals incrop protection Ind J Trad Know 5: 64-70

Owusu EO, Osafo WK, Nutsukpui ER (2007). Bioactivitiesof candlewood Zanthoxulum xanthoxiloides (Lam.)solvent extracts against two stored-product insect pests.African J Sci Tech 8: 17-21

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Accessed 30th March 2013



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63

Vol 26 June, 2013 No.1

Contents

Sl Title PageNo

1 Vegetable Cultivation in Mizoram: Status, Issues and Sustainable Approaches 1-7B. K. Singh, Y. Ramakrishna, V. K. Verma, S. B. Singh

2 Characteristics of Weed Biomass-derived Biochar and Their Effect on Properties 8-12of Beehive Briquettes

S. Mandal, R. K. Singh, A. Kumar, B. C. Verma, S. V. Nganchan

3 Incidence of Putative Virulence Factors and Antimicrobial Resistance in 13-21Aeromonas caviae Isolated from Livestock in Northeast India

K. L. Prashant, S. Ghatak, A. Kumar et al.

4 Microbial Biomass Nitrogen as an Index of N Availability in Acidic Soils of 22-28North East India

L. J. Bordoloi, A. K. Singh, Manoj-Kumar, Patiram, S. Hazarika

5 Multiple Use of Pond Water for Enhancing Water Productivity and Livelihood 29-36of Small and Marginal Farmers

A. Das, B. U. Choudhury, Ramkrushna, G.I., A. K. Tripathi, R. K. Singh,

S. V. Ngachan, D. P. Patel, J. Layek, G. C. Munda

6 Input Use Pattern in Rainfed ‘Kandi’ Area of Jammu Region in Jammu & Kashmir 37-41P. Kumar, S. K. Kher, P. S. Slathia, G. Kumari

7 A Report on Gastrointestinal Parasitic Infections in Yaks 42-44A. Goswami, R. Laha, D. Sarma, L. R. Chatlod

8 Gastrointestinal Parasitic Infections in Mithun in Organised Farm 45-46R. Laha, C. Rajkhowa, J. K. Chamuah, A. Goswami

9 Estimation of Annual Maximum Rainfall for Central Meghalaya 47-51Lala I. P. Ray, P. K. Bora, V. Ram, A. K. Singh, N. J. Singh, R. Singh, S. M. Feroze

10 First Report of Buckwheat (Fagopyrum esculentum) from High Altitude Temperate 52-54Zone of North Western Himalayan Region

Rayees A. Shah

Short Communication

11 Recent Scenario of Insect-pests of Guava in North East India and Their Eco-friendly 55-57Management

D. M. Firake, G. T. Behere, N. A. Deshmukh, P. D. Firake, N. S. Azad Thakur

12 Traditional Pest Management Practices and Beliefs of Different Ethnic Tribes of 58-61Meghalaya, North Eastern Himalaya

D. M. Firake, D. Lytan, D. P. Thubru, G. T. Behere, P. D. Firake, N. S. Azad Thakur

Indian Journal of Hill FarmingRegistration No. SR/IAHF 439/87 of 1987

ISSN 0970-6429

The views expressed are of the author/authors, the journal is not responsible for the technical correctness of data and does notin any way subscribe to any views or opinions expressed thereof.

vegetable cultivation in mizoram: status, issues and sustainable approaches · 2013-08-02 · june...

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