Mwalwanda AB, Ajayi OC, Akinnifesi FK, Beedy T, Sileshi G, G. Chiundu 2011 Impact of Fertilizer Trees on Maize Production and Food Security in Six Districts of Malawi, World Agroforestry Centre, Lilongwe, Malawi

JULY 2011

Table of Contents

EXECUTIVE SUMMARY43PREFACE54ACRONYMS AND ABREVIATIONS USED64Definition of terms75INTRODUCTION86JUSTIFICATION FOR THE STUDY97Research Gap98OBJECTIVE98METHODOLOGY108Study sites and sampling108Data collection1110Questionnaire survey1110Statistical Design and data analysis1211RESULTS AND DISCUSSION1311Description of respondents1312Maize grain yield comparison between fertilizer tree users and non users1312Effect of plot management on maize grain yield1312Frequency of plot management types1312Maize grain yield (kgha-1) correlations1514Fertilizer Application rate (kgha-1)1514Fertilizer trees management types and maize grain yield1615Area specific comparison of Maize grain kg ha-1after selected fertilizer trees1817Maize grain yield and Gliricidia1817Maize grain yield and Tephrosia1817Maize grain yield and Sesbania sesban1817Maize grain yield and Faidherbia albida1817Maize grain yield and Pigeon peas1917Plot sizes versus plot management1917Maize seed rate (kg ha-1) versus plot management type2018Maize grain yield (kg ha-1) and location2018Maize grain yield (kgha-1) disaggregated by gender of farmer and location2119Maize grain yield (kg ha-1) disaggregated by gender of household head2319Plot sizes disaggregated by type of plot management, location and gender of household head2320Plot size and gender2320Land ownership and gender2320Respondents’ perception on impact of fertilizer trees on maize yield2421Respondents’ (fertilizer tree users) use of bumper maize yield2421Effect of previous crop on maize grain yield (kg/ha)2521CONCLUSION2622ACKNOWLEDGEMENT2623REFERENCES2723APPENDIX2824Appendix 1 Questionnaire for the study2824Appendix 2 Respondents of the survey3329

List of figures

Figure 1 Map of Malawi showing pilot districts for AFSP109

Figure 2 Possible interactions of factors determining maize yield for the study1211

Figure 3 Frequencies of plot management types1413

Figure 4 Mean mineral fertilizer application (kgha-1) for conventional versus tree legume intercropping1514

Figure 5 Frequency of most dominant fertilizer tree management types among the fertilizer tree users1615

Figure 6 Fertilizer trees intercropped with Maize under different management types versus plot sizes1716

Figure 7 Maize grain yield (kg/ha) versus common fertilizer tree management types1716

Figure 8 Comparison of maize grain yield (kg/ha) across locations for different fertilizer trees1817

Figure 9 Average land sizes (hectares) among respondents for different plot types1918

Figure 10 Maize seed rate used (kgha-1) versus plot management type2018

Figure 13 Maize grain yield (kg/ha) in study districts as affected by type of plots2119

Figure 13 Mean plot sizes (hectares) as related to gender of farmer, type of plot management and location2320

Figure 14 Frequencies for land ownership based on household head gender as related to location and type of plot management2421

Figure 15 Fertilizer tree users' prioritization of bumper maize yield2521

Figure 16 Estimates of grain yield (kg/ha) as influenced by previous crop2522

EXECUTIVE SUMMARY

World Agroforestry Centre in Malawi with its partners implemented a four year (2007-2010) pilot project in Agroforestry with financial support from Irish Aid. The project known as Agroforestry Food Security Programme (AFSP) was being piloted in 11 districts spread within 8 Agricultural Development Divisions (ADDs). The overall programme purpose is to combine sound science, effective partnership and responsive scaling up approaches with informed policies that will help to increase food security and income, and improve livelihood opportunities for rural communities in Malawi, through accelerated adoption of fertilizer trees and fruit tree portfolios.

The programme has been focussing on four Agroforestry options; fertilizer trees, fruit trees, fodder trees and fuel wood trees.

To determine the impact of fertilizer trees on maize production and food security among its users, a study was conceived to assess comparative performance of maize (focussing on grain yield) under different species of fertilizer trees and different areas. The study also compared two broad maize production systems; conventional (use of mineral fertilizer and or unfertilized maize) with intercropping maize with fertilizer trees.

This report is a synthesis of a survey results that involved randomly selected smallholder farmers from six districts in Malawi who have either been using fertilizer trees or not as intercrops with maize to boost soil fertility. The objective of the survey was to compare maize grain yields between users and non users of the fertilizer trees and also to compare the maize grain yield from maize intercropped with different types of fertilizer trees.

This study was conducted during the 2009/10 growing season and involved 240 randomly selected farmers from 6 of the 11 districts in Malawi.

The survey results showed that use of fertilizer trees enhanced maize grain yields over those who did not use fertilizer trees. Maize grain yields from plots intercropped with fertilizer trees were over two times more than sole cropped maize without any fertilizer. Overall, fertilizer tree users obtained 1.4 times more maize grain than non users. More grain yield translates into more food security (longer periods of household food availability) among the participating farmers as maize is a staple food crop for most Malawian households.

The study also showed that users of fertilizer trees preferred pigeon pea ( Cajanus cajan) to other types of fertilizer tree species; Tephrosia (Tephrosia candida), Gliricidia (Gliricidia sepium), Sesbania (Sesbania sesban) and Faidherbia (Faidherbia albida)respectively among the dominant fertilizer trees species as intercrops with maize. However, Gliricidia sepium influenced highest maize grain yields followed by Tephrosia and Pigeon Peas.

PREFACE

Through the Agroforestry Food Security Project and other similar projects implemented in earlier years in Malawi, different fertilizer tree germplasm have been provided to smallholder farmers as to popularize best bet fertilizer trees for intercropping with maize. Fertilizer trees have proven to be beneficial in improving maize productivity for resource constrained smallholder farmers. However, availability of quality germplasm has been one of the challenges in their use by smallholder farmers.

World Agroforestry Centre with its partners has been championing promotion of fertilizer trees among smallholder farmers. As such, it has been providing quality germplasm of different species suitable for different agro-ecologies. This was deliberate as farmers have different preferences to a range of fertilizer tree species and also the performance of the trees varies in different agro ecologies vary. The most dominant fertilizer trees that were provided for maize intercropping to boost soil fertility were; Gliricidia sepium, Tephrosia candida, Sesbania sesban, Cajanus cajan, and Faidherbia albida.

The study on impact of fertilizer trees on maize production and food security provided an opportunity to get first hand testimonies from smallholder farmers on their experiences with maize production particularly use of fertilizer trees.

The study provided information on farmers’ perceptions, practices, in maize production and in soil fertility management. This report dwells more on comparisons between users of fertilizer trees and non users with respect to maize production. It provides key information on maize grain yield across the study locations differentiated by various attributes.

Professor Festus Akinnifesi

Regional Coordinator

Southern Africa, World Agroforestry Centre

ACRONYMS AND ABREVIATIONS USED

AFSP Agroforestry Food Security Programme

BNFBiological Nitrogen Fixation

CEC Cation Exchange Capacity

CISANET Civil Society Agriculture Network

DAES Department of Agricultural Extension Services

DAHLP Department of Animal Health and Livestock Development

EPA Extension Planning Area

GPS Geographical Positioning System

LRCD Land Resources Conservation Centre

MK Malawi kwacha

MoAFS Ministry of Agriculture and Food Security

MT Metric Tonne

NACAL The National Census of Agriculture and Livestock

NSO National Statistics Office

RDP Rural Development Project

WAC World Agroforestry Centre

Definition of terms

Estimated maize grain yield

Maize grain yield harvested based on farmers’ estimation

Estimated mineral fertilizer applied

Fertilizer quantities applied estimated by farmers

Fertilizer tree users

Farmers currently using fertilizer trees in their farms to improve soil fertility for at least one year

Non users

Farmers who have never used and/or are not presently using fertilizer trees in their maize farms

INTRODUCTION

Maize (Zea mays) is the staple food crop in much of Malawi, and the cropping system is dominated by this crop. Maize accounts for 60% or more of cropped area in Malawi (Kumwenda et al. 1996). Food security in resource-poor households is critically linked to the productivity and sustainability of maize-based cropping system.

Table 1 Relative importance of staple food in diet of Malawi (2003)

Commodity

Per capita consumption (kg/person/year)

Daily Caloric intake (kcal/person/day)

Share of caloric intake (%)

Maize

133

1154

54

Cassava

89

161

7

Potato*

88

163

8

Others

647

31

Total

 

2125

100

*FAO data combine Potato and Sweet Potato

Source: FAO, 2009a

One of the identified challenges in maize production in the small holder sector is low soil fertility (Swift et al. 2007). Increasing human population has led to continuous cropping on same pieces of land often in maize monoculture without allowing regeneration of soil fertility through traditional systems such as natural bush fallows. High costs of mineral fertilizers preclude resource poor smallholder farmers from using them to replenish soil fertility.

The availability of maize is so crucial that Malawi government subsidizes mineral fertilizers for small holder farming families targeting food crop production. However, the financial sustainability of the Fertilizer Input Subsidy Program is questioned due to its high cost to the national budget.

However, fertilizer use alone is inadequate to alleviate the physical and biological degradation of soil. Besides, fertilizer response is very low on already degraded soils (Sileshi et al., 2009). Even if fertilizer is readily available, if the land is not managed properly (through addition of organic inputs and conservation practices) fertilizers will not be used by the crop efficiently as much of it will be lost though leaching and soil erosion. Hence, more sustainable soil fertility management practices such as fertilizer tree systems that recapitalize soil organic matter, which plays a vital role in the maintenance of healthy soil biological, physical and chemical properties.

In the last 20 years the World Agroforestry Centre (ICRAF) has been promoting Agroforestry as a sustainable farming practice for resource poor farmers in Malawi. Studies on effect of leguminous trees and herbaceous legumes on maize yields have shown positive increase over unfertilized maize and natural fallows (Sileshi et al. 2008). On station experiments on effect of leguminous trees intercropped with maize have similarly shown significant increase in maize productivity (Akinnifesi et al. 2007).

World Agroforestry Centre with government partners such as Department of Agriculture Extension Services (DAES), Land Resources Conservation Department (LRCD), Department of Animal Health and Livestock Production (DAHLP, has been implementing an Agroforestry project funded and supported by Irish Aid through the Irish Embassy between 2007 and 2011. The project, Agroforestry Food Security Programme (AFSP) is implemented in eleven districts spread through eight agro ecological zones in Malawi. The project’s goal is to improve food security, incomes and livelihood opportunities for rural communities in Malawi. The project, among other interventions focuses on the fertilizer tree system as one best bet farming practices suitable for resource constrained farming families to ameliorate degraded soils.

JUSTIFICATION FOR THE STUDY

Research Gap

There is no doubt about high variability of maize productivity among small holder farmers owing to different levels of field management as well as variability due to different geophysical characteristics. To compare and quantify maize yield under smallholder farming situation in Malawi who have used leguminous fertilizer trees in their maize based farming systems with those that are not using fertilizer trees (hereafter called non-users) under different social economic as well as agro ecological zones can provide further evidence[footnoteRef:1] on whether or not leguminous fertilizer trees have had a positive effect on maize yield. Use of fertilizer trees in maize based farming systems under smallholder farming is low as the intervention is relatively strange to most small holder farmers in much of Malawi and inherent constraints exist associated with the cropping system under smallholder farming conditions. Among other constraints to use of fertilizer trees, smallholder farmers lack permanent land tenure rights, incidences of bush fires and browsing of trees by livestock (Ajayi and Kwesiga, 2003) after harvest of main crops such as maize. Assessment of impact of fertilizer trees on maize production and food security would generate additional information to enhance Agroforestry scaling up strategies/opportunities among smallholder farmers. [1: Particularly under small holder agriculture sector]

The study was conceptualized to provide an opportunity of identifying and quantifying some of the multiple factors that impinge on maize productivity under Agroforestry.

This being the final year of implementation of AFSP, tracking project impact on increasing food security with respect to set impact indicators will guide decisions on evaluation. Apart from a possible evaluation study to be commissioned from which comprehensive information on impact of AFSP will be collected, estimated maize yield data will provide some indirect information on early project impact on food security.

We proposed to quantify the average grain yield of maize from farmers’ fields both using fertilizer tree systems and non-users. The rationale was to compare maize grain yield across the districts participating in AFSP and quantify if there is a significant improvement in maize yield attributable to fertilizer tree system. Our hypothesis is that farms using fertilizer trees will have higher maize grain yield than those who are not using.

OBJECTIVE

The main objective of conducting this study was to assess the impact of fertilizer trees on maize yield and household food security.

The study was conceptualized to provide specific information on:

· The proportion of maize yield difference attributed to different fertilizer trees

· Profiling of households using fertilizer trees and those not using

METHODOLOGY

Study sites and sampling

The study was conducted in six districts as shown in figure 1 and Appendix 2. The six districts were selected from eleven districts which are participating[footnoteRef:2] in Agroforestry Food Security Programme (AFSP). The 2009/10 growing season in Malawi was affected by widespread erratic rainfall pattern characterized by dry spells. The dry spells also caused delays in out planting of nursery based fertilizer trees such as Gliricidia sepium and Sesbania sesban. These districts were judiciously selected because there were comparatively more Agroforestry adopters who embraced fertilizer trees for periods of more than three [2: Out of the 11 districts]

Figure 1 Map of Malawi showing pilot districts for AFSP

growing seasons and because of observed relative success of fertilizer trees growth and development despite dry spells and erratic rainfall regime experienced during the 2009/10 growing season.

AFSP was also being implemented in either one or two EPAs per district in the 11 districts across the country. Twenty farmers’ fields using and ten non-user farmers’ fields were randomly[footnoteRef:3] selected per EPA. Pair-wise comparison was done for user household so that on each farm yield was compared for maize with and without fertilizer trees. The total number of respondents was 240 (Table 2 and 3). [3: Using random numbers, lists of 100 farmers for both fertilizer tree users and non users from each EPA were used to select the first 20 users and 10 non users farmers per EPA to be used as sample size ]

The study was designed to sample equal numbers of male and female farmers for participating and non- participating households but this was not possible due to insufficiency of respondents from data sources.

Data collection

Questionnaire survey

Data was collected using a structured questionnaire (Appendix 1.) from both participating farmers, hereinafter referred to as users and non-participating farmers hereinafter referred to as non-users. These farmers were randomly selected[footnoteRef:4] from lists of 100 farmers participating and 100 non participating farmers from each EPA. There was further screening and replacement of respondents’ in the study areas where respondent was deemed unsuitable for the study. Major criteria for replaced respondents: [4: Use of random numbers]

· Unavailability of respondent during time of questionnaire administration

· Respondents applied other organic manures to their maize crop apart from fertilizer trees

· Respondent could not recall estimated quantities of inputs and maize outputs from his/her field

All respondents’ maize fields’ areas were measured using Geographical Positioning System (GPS) device by perimeter survey. The areas were used to calculate estimated maize grain yield (kg ha-1), estimated maize seeding rate per hectare and estimated mineral fertilizer applied (kgha-1).

The questionnaire comprised the following sets of questions (see Appendix 1 for a complete copy):

· Basic household information

· Household income sources

· Household composition

· Household prioritization of yield and income from Agroforestry plots

· Description and history of each specific farmer’s plot

· Soil type (as described by farmers themselves) and fertilizer use

· Maize inputs used and outputs obtained from the farmers’ plots

Maize grain yield harvest was estimated by the farmer including maize that was harvested green or otherwise before the final harvest.

Secondary data on maize yield crop estimates and total monthly rainfall was collected from study areas for two seasons; 2008/9 and 2009/10 seasons.

The study was conceptualized to show interactions as shown in figure 2 below:

(Maize YieldFertilizer Tree userNon userSocio-economic factorsLocation (Agro ecology)Species of fertilizer tree)multiple interactions to be studied

Figure 2 Possible interactions of factors determining maize yield for the study

It is expected that among fertilizer tree users, there is diverse knowledge and practices in utilization of fertilizer trees that in turn may have different effects on maize production. We also expect that different agro zones would influence differently growth and development of both the fertilizer trees and maize crop. Existing socio-economic conditions among both users and non users would also contribute to differences in abilities and potentials in management of the maize crop and leading to variations in maize yield, which would affect the socio-economic conditions of the farmers in succeeding years..

Statistical Design and data analysis

The study adopted an unbalanced randomized complete block design after noting the difficulty of getting optimal or planned sample sizes for all study sites in the final data set.

Data collected was analyzed using SAS (Littel, R.C. et al. 2006) for general descriptive statistics and Analysis of Variance for means of maize yields.

The information from analysis only gives indication of likely impact of the fertilizer trees on maize yield because of limitations of the field sampling technique[footnoteRef:5] deployed as well as the limited years the project has been on the ground. [5: Particularly on quantities of input and outputs were estimated by respondents]

RESULTS AND DISCUSSION

Description of respondents

The study involved 240 respondents from 9 extension planning areas[footnoteRef:6] from six districts of which 52.9% (127) were females while 47.1% (113) were males. Of the respondents, a total of 161 (67.1%) were fertilizer tree users or participating farmers and 79 (32.9%) were non fertilizer tree users. A majority of households representing 81.7% (196) were male-headed while 18.3% (44) were female-headed. The households’ size had a mode of 6 and mean of 5.91. The level of education among the interviewees was generally primary school level (67.9%). Most of the sampled households (87.9%) received trainings related to Agroforestry and farming practices and only 12.1% did not receive such training. A majority of respondents (79.6%) have non-farm income as in contrast with (20.4%) households who did not have any non-farm income. [6: In Thyolo, two EPAs (Thyolo Central and Matapwata) were combined as each could not provide adequate number of required respondents]

Maize grain yield comparison between fertilizer tree users and non users

The results showed very significant differences (p<0.0001) in maize grain yield between fertilizer tree users and non users. Overall the mean maize grain yield from fertilizer tree users was 2481 kg ha-1 while from non users was 1723 kg ha-1. Fertilizer tree users therefore had 1.4 times more maize grain translating into more months of food availability (food security) at the household.

Effect of plot management on maize grain yield

The study further subdivided the two groups of farmers interviewed (fertilizer tree users and non users) into four general cultural practices[footnoteRef:7] for maize production, these: maize without fertilizer application[footnoteRef:8], maize with fertilizer application, maize intercropped with fertilizer trees and maize with combined use of mineral fertilizers and fertilizer trees as intercrops. This study compared means of total maize yield[footnoteRef:9] per hectare for mean maize grain yield across all observations. These means were very highly significant (p<0.0001) across all observations attributed to type of cultural practices for maize production. [7: Common maize production systems among the respondents] [8: Or negligible amount applied (≤5kgha-1)] [9: The respondents’ estimated sum of all maize harvested including green maize]

There were also very significant differences among means of total maize grain yield for each of the general cultural practices (Table 2).

Frequency of plot management types

The commonest maize plot management type among respondents was conventional type of maize production (46%), where farmers rely on mineral fertilizers, followed by combined use of mineral fertilizers and fertilizer trees (30%), intercropping maize with fertilizer trees (16%) and the least common maize plot management type was unfertilized maize (8%). The relatively higher percentage of farmers opting for conventional maize growing over intercropping with leguminous fertilizer trees underlines the importance farmers attach to mineral fertilizers and that despite the cost, they find mineral fertilizer to be more convenient. This study has shown that there are relatively fewer farmers practicing Agroforestry in form of intercropping maize with fertilizer trees. Despite evidence showing that Agroforestry is a sustainable farming system, many farmers still practice conventional farming. Similar observations were made by Snapp et al (1998) who noted challenges farmers face with Agroforestry as including; high establishment costs, resource competition and delayed benefits (Snapp et al. 1998).

Figure 3 Frequencies of plot management types

Table 2 Comparison of means of total maize yield at harvest (kg ha-1)

Plot Management

Frequency

Mean

Standard Error

Maize without fertilizer

36

1322

220.33

Maize with fertilizer

213

1736

118.95

Maize with fertilizer trees

72

3053

359.8

Maize with fertilizer trees + fertilizer

135

3071

264.31

The yield difference between maize with fertilizer trees and Maize with both fertilizer trees and mineral fertilizer was negligible indicating fertilizer trees had stronger influence over mineral fertilizers in contributing to maize yield. Maize grain yield from plots with fertilizer trees had 1.8 times more yield than maize from plots that only received mineral fertilizer. Under ideal[footnoteRef:10] or full mineral fertilizer application this may not be the case as maize grain yield after full fertilizer application gives more maize grain yield than where only coppicing fertilizer trees are used as noted in a study of comparative literature indicating evidence of impact of green fertilizers on maize production by Sileshi et al. (2009). In their study, the yield difference between unfertilized maize and maize with full fertilizer application was higher than yield difference between maize with coppicing fertilizer trees and maize that was unfertilized. However, under resource-poor smallholder farming scenario, variability of field management and in particular general sub optimal rates of fertilizer application may give comparatively lower response to mineral fertilizer application. Under such conditions, soil fertility improvement through fertilizer trees is likely to provide a higher net increase in nutrients additions from mineralization of high quality biomass, nutrient recycling from lower soil depths that maize roots may otherwise not access as well as biological nitrogen fixation (BNF) that translates into higher maize productivity. Apart from BNF, fertilizer trees also improve soil organic matter that in turn improves moisture and nutrient holding capacity of soils. In our study, mean maize yield from unfertilized maize was half that from maize intercropped with fertilizer trees. This is consistent with results from a study by Sileshi et al. (1999) where maize yields were higher with intercropping with coppicing green manure legume crops than from unfertilized maize. [10: Under small holder conditions mineral fertilizer applications is generally sub-optimal (Waddington, S.R. and Heisey, P.W. 1997)]

The results showed high variability (standard errors) of mean maize grain yield for maize intercropped with fertilizer trees. This could be because there was wide variability of management of the trees, variability in growth and development of the trees in different districts that in turn had different impacts on maize growth and development. As with conventional maize production, mineral fertilizers application to maize intercropped with fertilizer trees showed reduced yield variability.

Maize grain yield (kgha-1) correlations

The following variables had positive correlations at P<0.0001 with overall maize grain yields per hectare as follows:

Table 3 Maize grain yield and correlations

Factor

Sample size

% Correlation

Rate of fertilizer application

455

23

Rate of maize seed application

456

46.6

Green maize harvested

456

36.7

Maize grain yield at harvest (discounting green maize)

456

97

There was also a negative correlation (29.7%) between maize grain yield and plot size. This could be because of low productivity in smallholder production system. As land size increases, the efficiency in use of inputs such labour and mineral fertilizers were reduced. The average land holding was 0.28 ha with the individual household’s maximum and minimum land holding sizes of 3.2 ha and 0.00089 ha respectively.

Fertilizer Application rate (kgha-1)

There were very significant (p<0.0001) differences among means of quantities of estimated mineral fertilizers applied to maize in all observations. This study showed that overall farmers made substantial savings (53.2%) on quantities of mineral fertilizers when they intercropped maize with fertilizer trees as they substantially reduced quantities of mineral fertilizer applied unlike under conventional system[footnoteRef:11]. This gives evidence that farmers are aware of the positive contribution of fertilizer trees to nutrient needs of their maize crop. [11: Monoculture maize that mainly rely on mineral fertilizers ]

Figure 4 Mean mineral fertilizer application (kgha-1) for conventional versus tree legume intercropping

Fertilizer trees management types and maize grain yield

The study revealed that three fertilizer trees species are the most predominant among the five types of fertilizer trees that were intercropped with maize across all the six study districts among sampled adopter farmers (Table 4 and figure 5). These are Pigeon peas, Tephrosia and Gliricidia. Pigeon pea was the most favoured possibly because it has multiple benefits such as food, cash crop apart from its organic fertilizers.

Table 5 Fertilizer tree management types with mean plot sizes and grain yield (kgha-1)

Fertilizer tree management

Frequency

Plot Size (ha)

Maize kg/ha

Gliricidia No fertilizer

15

0.12563

3153.82

Gliricidia + fertilizer

27

0.09467

3569.66

Tephrosia No fertilizer

21

0.14752

3170.31

Tephrosia + fertilizer

27

0.125

2887.09

Sesbania No fertilizer

5

0.12306

2163.91

Sesbania + fertilizer

4

0.10997

4784.99

Faidherbia No fertilizer

1

0.18227

548.62

Faidherbia + fertilizer

6

0.50651

1872.49

Pigeon pea No fertilizer

22

0.15275

2273.91

Pigeon pea + fertilizer

52

0.19173

2711.42

Others No fertilizer

2

0.09211

1160.13

Others + fertilizer

5

0.22482

2440.23

Gliricidia + Pigeon pea + No fertilizer

2

0.07463

11758.48

Gliricidia + Pigeon pea + fertilizer

2

0.05349

9255.34

Tephrosia + Pigeon pea + fertilizer

6

0.22547

1985.99

Gliricidia + Tephrosia + fertilizer

3

0.31895

4124.39

Tephrosia + Pigeon pea + No fertilizer

2

0.08475

6636.71

Tephrosia + Others + No fertilizer

1

0.18375

2503.43

Gliricidia + Faidherbia + fertilizer

2

0.2001

1775.32

Pigeon pea + Sesbania + No fertilizer

1

0.1349

2816.9

Tephrosia + Sesbania + fertilizer

1

0.16803

6427.61

Figure 5 Frequency of most dominant fertilizer tree management types among the fertilizer tree users

The study also noted that among the fertilizer trees, Pigeon pea intercropped with maize had larger plot sizes allocated than Tephrosia and Gliricidia intercropped with maize respectively (Figure 6). This further confirms the greater importance farmers in this study attach to Pigeon peas as a fertilizer tree.

Figure 6 Fertilizer trees intercropped with Maize under different management types versus plot sizes

It was also interesting to note from the study that despite the farmers’ preference of Pigeon pea over the other fertilizer trees, Gliricidia sepium was outstanding in influencing higher maize grain yields followed by Tephrosia and Pigeon peas (Figure 7). Application of mineral fertilizers to intercropped maize with fertilizer trees improve maize grain yields slightly particularly for farmers who used Gliricidia and Pigeon peas across the locations (figures 7-8).This may be attributed to insignificant amounts as well as highly variable amounts used of mineral fertilizers applied among the farmers who used fertilizer trees.

Figure 7 Maize grain yield (kg/ha) versus common fertilizer tree management types

Figure 8 Comparison of maize grain yield (kg/ha) across locations for different fertilizer trees

Area specific comparison of Maize grain kg ha-1after selected fertilizer trees

Maize grain yield and Gliricidia

The study revealed that maize grain yields from plots with Gliricidia sepium without mineral fertilizers were highest in Thyolo and Mulanje but where fertilizers were added, Maize grain yield was highest in Salima followed by Lilongwe (figure 8).

Maize grain yield and Tephrosia

Maize grain yields from Tephrosia plots without mineral fertilizer were variable. Salima had highest grain yields followed by Mulanje and Thyolo respectively. However, where mineral fertilizers were applied the grain yield were somewhat stable (small variation) across the study sites with Mzimba producing higher maize grain yield followed by Lilongwe and Salima (figure 8).

Maize grain yield and Sesbania sesban

Generally most farmers who intercropped their maize with Sesbania sesban applied mineral fertilizers except for two farmers in Lilongwe. Maize grain yields from plots intercropped with Sesbania were highest in Salima although it was only a single farmer followed by Lilongwe (figure 8).

Maize grain yield and Faidherbia albida

The study noted that generally maize grain yields were comparatively lower under plots with Faidherbia albida. Grain yields were highest from Salima followed by Mzimba district (figure 8).

Maize grain yield and Pigeon peas

The study found that intra district variation in maize grain yield was not very wide between non fertilized and fertilized plots intercropped with Pigeon peas. However, grain yields were markedly higher in Salima followed by Lilongwe (figure 8).

Plot sizes versus plot management

There were very significant differences (p<0.0001) across all respondents in average plot sizes for different maize plot management types. Conventional system of maize production were allocated more land (≥0.35 hectares) compared to either intercropped system with fertilizer trees or a system of combining both fertilizer trees and mineral fertilizers (≥0.15 hectares). Since respondents were smallholder farmers, more land allocation to maize is a rational choice to maximize their maize food output. The dominance of the conventional production of maize may also be a reflection of previous overemphasis by agricultural extension agents on use of mineral fertilizers and hybrid seed for maize production (Mtawali, 1993)

Figure 9 Average land sizes (hectares) among respondents for different plot types

Maize seed rate (kg ha-1) versus plot management type

There were very significant differences (p<0.0001) across all respondents in means of maize seed rate (kg/ha) and seed rate very significantly influenced maize grain yield (kgha-1). Except for maize plots that received mineral fertilizers, the other plot management types had relatively very high estimated seed rate applications possibly due to resupplying of seed due to failure to germinate or establish under zero fertilizer level or where there was intercropping with fertilizer trees. Farmers probably had preferential treatment on their plots with fertilized maize over other plot management types. Better crop management may also have entailed better optimization and selection of seed input type. It should also be noted that the seed rates were based respondents estimations as such there was possibility of either over estimation or otherwise.

Figure 10 Maize seed rate used (kgha-1) versus plot management type

Maize grain yield (kg ha-1) and location

Maize grain yield (kg ha-1) variations were less with mineral fertilizer applications across the six locations but variation was marked where maize was sole cropped without fertilizer, intercropped with fertilizer trees or combination with mineral fertilizers. This may be partly due to a) diversity of agronomic practices such planting patterns, times, maize seed selection, etc and b) variations in fertilizer tree performance across the locations due to genotypic variations in adaptability to geophysical conditions. In this study there were no farmers who practiced maize monoculture without fertilizer in Thyolo perhaps underlying the severe land pressure by humans due to high population density that makes intercropping as the best choice in maximizing productivity of land. Figure 11 shows the general picture of maize grain yield in the study districts as affected by type of plot management.

Figure 11 Maize grain yield (kg/ha) in study districts as affected by type of plots

Maize grain yield (kgha-1) disaggregated by gender of farmer and location

In general, maize grain yield was higher for male farmers than female farmers for all the four types of plot management (figure 13). This may be because of resource entitlement disparities between male and female farmers where generally male farmers dominate in controlling financial resources as well as land which directly influence production abilities.

Figure 12 Mean grain yield (kg/ha) as influenced by type of plot management, gender of farmer and location

Maize grain yield (kg ha-1) disaggregated by gender of household head

There were no consistent patterns in maize grain yield attributed to gender of household head for three plot management types except where mineral fertilizers only was applied. In plots where mineral fertilizers only were applied, maize grain yield was generally higher for male headed households than female headed households. This may be because such male headed households tend to have at their disposal more resources for production such as labour and opportunities for non farm income that enhances efficiency of maize or crop production.

Plot sizes disaggregated by type of plot management, location and gender of household head

Plot size and gender

The survey results show that male headed households generally have larger pieces of land than female headed households for all plot management types across all the sites although the distinction in plot sizes based on gender was not very clear for maize plots with both fertilizer trees and mineral fertilizers (figure 14).

Land ownership and gender

The study also observed male domination in land ownership across all the study areas and for all for all plot management types (figure 15). Male dominion was very apparent in Mzimba and Lilongwe districts. In the former, the status perhaps reflects patriarchal culture prevalent in the area. However disparity in land ownership between male and female headed households is minimal for Mulanje and Thyolo districts perhaps underlying a matriarchal society predominant in the two districts. Our findings are also consistent with NSO (2007) that reported dominion of males over females in both land sizes owned and number of plots owned under smallholder sector being operated by male operators as household heads.

Figure 13 Mean plot sizes (hectares) as related to gender of farmer, type of plot management and location

Figure 14 Frequencies for land ownership for household head gender as related to location and type of plot management

Respondents’ perception on impact of fertilizer trees on maize yield

It was interesting to note that a majority of fertilizer tree users (97%) gave a positive perception of impact of the fertilizer trees on maize yield. This was based on pair-wise comparisons[footnoteRef:12] over the period of adoption of the fertilizer trees. [12: Each fertilizer tree user compared maize yield between sole cropped and intercropped maize with fertilizer trees]

Respondents’ (fertilizer tree users) use of bumper maize yield

Respondents’ major use of bumper harvest from maize intercropped with fertilizer trees was to ensure household had adequate food reserves. This is based on summation of two related categories of responses. These; 22% of respondents retained the bumper harvest for later consumption and 30% of respondents consumed more maize. Household food security is the overriding rationale for keeping surplus maize grain yield. Extra maize yield also act as cash income source (25% of respondents) and therefore augmented household income.

Figure 15 Fertilizer tree users' prioritization of bumper maize yield

Effect of previous crop on maize grain yield (kg/ha)

The results show that maize after Tobacco gave highest grain yield. Most farmers apply mineral fertilizers to Tobacco hence there is residual effect of the mineral fertilizers on maize.

Figure 16 Estimates of grain yield (kg/ha) as influenced by previous crop

CONCLUSION

Under smallholder farming system, fertilizer trees have been perceived in this study to substantially enhance maize yield and therefore positively improve household food security among farmers who intercrop their maize crop with them. Under smallholder farming situation where access of mineral fertilizers is a challenge because of cost, use of fertilizer trees offers alternative soil improving organic fertilizer and sustainable production system.

Fertilizer tree use is still very limited among smallholder farmers in Malawi despite the obvious benefits in yield improvement. Even among those few farmers who have embraced the fertilizer trees in their maize based farms, the proportion of maize crop intercropped with the fertilizer trees is negligible.

It is recommended that further studies on farm use of fertilizer trees among smallholder farmers be done focusing on underlying challenges associated with utilization of the fertilizer trees and also to have more empirical studies on effects on soils as well as maize performance.

ACKNOWLEDGEMENT

We sincerely thank the Irish Aid for the financial support in implementing the Agroforestry Food Security Programme. We would like to thank all our partners for the good collaboration during implementation of the project.

We thank the farmers who allowed our team of enumerators to interview them to share their experiences of on-farm maize production with or without fertilizer trees and other related information. I am also grateful to the enumerators, data entry clerks, government field extension workers who supported the survey in many ways. I am very indebted to the team of ICRAF Malawi scientists who provided their invaluable input in analyzing the data collected and subsequently in the write up of the research report.

REFERENCES

Ajayi, O.C. and Kwesiga, F., 2003. Implications of local policies and institutions on the adoption of improved fallows in eastern Zambia. In: Agroforestry Systems, 59: pp 327-336.

Akinnifesi, F., W. Makumba, G. Sileshi, O. Ajayi, and D. Mweta. 2007. Synergistic effect of inorganic N and P fertilizers and organic inputs from Gliricidia sepium on productivity of intercropped maize in Southern Malawi. Plant and Soil 294:203-217.

FAO (Food and Agriculture Organization). 2009a. FAO Food balance sheet. http://faostat.fao.org/site/368/default.aspx#ancor.

Littel, R.C., G.A. Milliken, W.W. Stroup, R.D. Wolfinger, and O. Schabenberger. 2006. SAS for Mixed Models, Second Edition SAS Institute Inc., Cary, NC, USA.

Kumwenda, JD.T., S.R. Waddington, S.S. Snapp, R.B. Jones, and M.J. Blackie. 1996. Soil Fertility Management Research for the Maize Cropping Systems of Smallholders in Southern Africa: A Review. NRG Paper 96-02. Mexico, D.F.: CIMMYT

Mtawali, K.M. 1993. Current status of and reform proposals for agriculture: Malawi. In: Agricultural reforms and regional market integration in Malawi, Zambia and Zimbabwe, ed. A. Valdes and K. Muir-Leresche. Washington, D.C. International Food Policy Research Institute.

National Statistics Office, 2007. The National Census of Agriculture and Livestock.

School of oriental and African Studies (SOAS), Wadonda Consult, Oversees Development Institute and Michigan State University. 2008. Evaluation of the 2006/7 Agricultural Input Supply Programme, Malawi: Final Report. London School of Oriental and African Studies; March 2008.

Sileshi G., Akinnifesi F.K., Ajayi O.C., Place F. (2008) Meta-analysis of maize yield response to planted fallow and green manure legumes in sub-Saharan Africa. Plant and Soil 307:1-19.

Sileshi G, Akinnifesi FK, Ajayi OC, Place F. 2009. Evidence for impact of green fertilizers on maize production in sub-saharan Africa: a meta-analysis. ICRAF Occasional Paper.

Snapp, S.S. , Mafongoya, P.L. , and Waddington , S. 1998. Organic Matter Technologies for Integrated nutrient Management in smallholder cropping systems of southern Africa. In: Agriculture, Ecosystems and Environment. pp185-200.

Swift M.J., Shepherd K.D. (Eds) 2007. Saving Africs's Soils: Science and Technology for Improved Soil

Management in Africa. Nairobi: World Agroforestry Centre.

Waddington, S.R., Heisey, P.W., 1997. Meeting the nitrogen requirements of maize grown by

resource-poor farmers in southern Africa by integrating varieties, fertilizer use, crop

Management and policies. In: Edmeades, G.O., BaÈnziger, M.,Mickelson, H.R., PenÄa-

Valdivia, C.B. (Eds.), Developing Drought and Low N-Tolerant Maize. Proc. Symp.,

CIMMYT, El BataÂn, Texcoco, Mexico D.F Mexico, 25±29 March 1996.

APPENDIXAppendix 1 Questionnaire for the study

Name of farmer: ___________Identification number: ________________

Village: ___________________Section:____________________________

EPA: _________________________District: ____________________________

Date of interview: Day ____Month_____ Name of enumerator________________

Section A: (complete this section once for each household)

A1.Basic household information

Information required

Response

Code

a. Type of farmer

1=Agroforestry farmer

2=Non agroforestry farmer 

b. Total number of years of experience with fertilizer trees

AFSP:________

CIDA:________

TARGET :____

Other:________

Write the number of years for each project

c. Have you had any training on agroforestry or other related agricultural practices in the last 3-4 years?

1=No 2=Yes

d. Please name them (rank with the most important first)

1st: __________

1=Agroforestry

2=Conservation agriculture

3=Compost making

4=Manure farming

5=Soil & water conservation

2nd : ________

3rd: __________

4th: __________

e. Gender of interviewee

1=Female

2=Male

f. What is the gender of the head of your household

1=Female

2=Male

g. Age of farmer (actual years)

h. Level of formal education of farmer

1=None at all

2=Primary school

3=Secondary school

4=Post secondary

5=Others (specify)

A2.Household income sources

a. Do you have any type of non-farm income?

1=No 2=Yes

b. Tell me these sources or off-farm income

Type of off-farm income

Average income from this source per month (MK)

· Ganyu

· Small-scale business/trading

· Artisans- bicycle & radio repairs, brick making, mat etc

· Seasonal contract

· Remittance from outside

A3.Household Demography

What is the total number of persons in your household? ___________________________

How many of these are male and female? Male: _______Female: _____

Please tell me the composition of these individuals based on the following table

Category

Number in each category

Fully engaged in farm work

Schooling fulltime

Too young/ too old to participate in farm work or school

a. Male

b. Female

A4.Use of extra maize yield or income from AF plots

Type of information

Response

Code

a. Please compare the maize yield from your AF and non- plots?

1=Yield from AF plot is higher

2= Yield from AF plot is lower

3=Same / No difference

b. In your opinion, what do you think is responsible for this?

1=Soil fertility is better in AF plot

2=Soil moisture is better in AF plot

3=Weeds are less in AF plots

4=Due to the type of seeds planted

5=..

6=…

c. Who makes the decision on how to use the extra maize yield or income obtained from AF plots?

1=Myself

2=My husband

3=My wife

4=The Chief

5=…

d. What do you do with the extra maize yield and/or cash obtained in AF plots?

1=Sold to obtain cash

2=Eat more often than before

3=Gave out to friends and relations

4=Food lasts longer

5=Exchanged for household items (clothes, bowls, etc)

6=Exchanged for farm inputs (slashers, hoes, fertilizer, etc)

7=Pay medical bills

8=Pay children school fees /uniforms

9=Buy or develop plot of land

10-Renovate existing family house

11=Marry new spouse

12=Buy transport (bicycles, bike, etc)

13=Buy new clothes for self or family

Section B: (complete this section for EACH PLOT cultivated by the household)

B1.Description and history of each specific plot

Name of farmer: ____________________Identification number: ________________

Plot code: _________________________

Type of information

Response

Code

a. Description of plot

Plot 1

Plot 2

Plot 3

Plot 4

Maize with….

1=Fertilizer tree only

2=Fertilizer tree + mineral fertilizer

3=Mineral fertilizer only

4=No fertilization at all

b. What is the size of this plot?

Measure field with GPS and give answer in square meters

c. Type of fertilizer trees planted in the plot

10=Gliricidia, NO fertilizer

11=Gliricidia + fertilizer

20=Tephrosia, NO fert

21=Tephrosia + fert

30=Sesbania, NO fert

31=Sesbania + fertilizer

40=Faidherbia, NO fert

41=Faidherbia + fert

50=Pigeon pea, NO fert

51=Pigeon pea + fert

60=Others, NO fert

61=Others +fert

d. Did you apply mineral fertilizer in this fertilizer tree plot?

1=No 2=Yes

e. Which year did you establish the fertilizer tree plot?

Put the year directly, 2001/02, 2008/09, etc

f. Which year did you incorporate biomass into the plot?

Put the year directly, 2001, 2008, etc

g. How many times did you incorporate biomass in this plot during the season?

h. When did you make the biomass incorporations in this plot?

1st biomass: _____

1=January

2=Feb

3=March

4=April

5=May

6=June

7=July

8=August

9=Sept

10=Oct

11=Nov

12=Dec

2nd biomass: _____

i. How old were the trees before incorporating them in this plot?

Plot 1

Plot 2

Plot 2

Plot 4

Indicate the number of years between establishment and incorporation of biomass

j. What is the situation of the growth (quantity & quality of biomass) when you were incorporating them?

1=Very good/Good

2=Fair / Average

3=Poor/bad

k. What crop(s) did you plant in the plot in the previous year before you embarked upon establishing fertilizer trees in the plot?

Crop1

Plot 1

Plot 2

Plot 3

Plot 4

1=Maize

2=Groundnut

3=Rice

4=Cassava

5=Tobacco

6=Sunflower

7=Cotton

8=Pigeon pea

9=Banana

10=vegetables

11=sweet potato

12=Beans

13=Sorghum

14=Millet

15=Irish potato

16=Pumpkin

17=beans

18=other crops

Crop 2

Crop 3

Crop4

B2.Soil type and use of fertilizer

Type of information

Response

Code

a. What is the dominant soil type in your plot?

Plot 1

Plot 2

Plot 3

Plot 4

1=Sandy soil (Mchenga) 2= Red soil (Katondo)

3= Dark clayey soil (Makande) 4= Others

b. What is the fertility status of the soils in your plot?

1= Poor

2= Average

3= Good

c. Did you apply mineral fertilizer in this plot during the season?

1=No 2=Yes

d. How many times did you apply the mineral fertilizer in the plot?

1=All applied at once

2=Split and applied on two different times (Basal and top dressing)

e. What is the type of fertilizer used?

1=Compound NPK

2=Urea

3=CAN

4=Others (specify) ____________________

f. What is the quantity of fertilizer applied?

Convert all quantity given in local units to Kg equivalents

B3.Maize inputs used and output obtained from the plot

Type of information

Response

Code

a. What is the estimated size of your plot?

Plot 1

Plot 2

Plot 3

Plot 4

Note the area/size given by farmers and convert to hectare

b. What type of maize seeds did you plant?

1=Local

2=Improved/hybrid

3=Composite

c. What is the source of maize seed that you planted?

1=Recycled

2=Purchase

3=Subsidy

4=Gift

d. Was the seed mentioned in (b) planted in the entire plot or part of the plot only?

1=Entire plot

2=A section of the plot only

e. What is the quantity of maize seeds planted in the plot?

Convert response to Kg

f. When did you plant the maize seeds?

1=Late November

2=Early December

3=Late December

4=Early January

5=Late January

6=Early February

g. Did it become necessary to replant your plot with maize e.g., due to mid-season drought?

1=No 2=Yes

h. How many times did you weed the plot during the season?

Indicate the number of times

i. What is the total quantity of maize that farmers estimated that s/he obtained from this plot?

Get the quantity from farmers and convert to Kg

j. What is the quantity of maize that you harvested green (i.e. before the maize is dried)

Get the quantity from farmers and convert to Kg

k. What is the total amount of maize grain harvested from this plot this year?

Important: Get the weight in local units (bags, ox carts, etc) and later convert to KG

l. Based on your estimation, how many months will this amount of maize be able to feed all the members of your household?

Obtain the estimate from the farmer

m. List ALL the other types of non-maize grain products that you got from this plot

Plot 1

Plot 2

Plot 3

Plot 4

Give the estimated value of this in MK or provide the quantity and convert to MK value

Wood

Mushroom

Seeds

Appendix 2 Respondents of the survey

Table 1 Number of respondents of the survey disaggregated by location and gender of household head

District

EPA

Gender of Household head

Type of farmer

Grand Total

Adopter

Non-adopter

Lilongwe

Chigonthi

Female

1

3

4

Male

19

7

26

 

Mpingu

Female

3

1

4

Male

18

8

26

Mzimba

Emsizini

Female

3

1

4

Male

17

9

26

 

Zombwe

Female

4

2

6

Male

16

8

24

Machinga

Nanyumbu

Female

0

1

1

Male

20

9

29

Thyolo

Matapwata

Female

5

1

6

Male

9

7

16

 

Thyolo centre

Female

2

0

2

Male

4

2

6

Mulanje

Thuchira

Female

5

5

10

Male

15

5

20

Salima

Tembwe

Female

6

1

7

Male

14

9

23

Grand totals

161

79

240

Table 2 Number of respondents of the survey disaggregated by location and gender of

Interviewee

District

EPA

Gender of Household head

Type of farmer

Grand Total

Adopter

Non-adopter

Lilongwe

Chigonthi

Female

7

6

13

Male

10

4

14

 

Mpingu

Female

13

4

17

Male

11

5

16

Mzimba

Emsizini

Female

6

5

11

Male

13

4

17

 

Zombwe

Female

14

5

19

Male

7

6

13

Machinga

Nanyumbu

Female

9

6

15

Male

11

4

15

Thyolo

Matapwata

Female

6

6

12

Male

4

0

4

 

Thyolo centre

Female

8

2

10

Male

2

2

4

Mulanje

Thuchira

Female

11

6

17

Male

9

4

13

Salima

Tembwe

Female

17

7

24

Male

3

3

6

Grand totals

161

79

240

Frequency

Maize aloneMaize + FertilizerMaize + fertilizer treesMaize + Fertilizer + Fert. trees3621272135fertilizer applied (kgha-1)Maize + FertilizerMaize + Fertilizer + Fert. trees75.79000000000000635.47

Comparison of conventional and intercropping system in fertilizer use

Mineral fertilizer application kg/ha

FreqGliricidia No fertilizerGliricidia + fertilizerTephrosia No fertilizerTephrosia + fertilizerPigeon pea No fertilizerPigeon pea + fertilizer152721272252Plot Size (ha)Gliricidia No fertilizerGliricidia + fertilizerTephrosia No fertilizerTephrosia + fertilizerPigeon pea No fertilizerPigeon pea + fertilizer0.125629999999999949.4670000000000032E-20.147520000000000010.1250.152750000000000050.19173000000000001

Dominant maize + fertilizer tree intercropping systems

Frequency

Plot Size (ha)Gliricidia No fertilizerGliricidia + fertilizerTephrosia No fertilizerTephrosia + fertilizerPigeon pea No fertilizerPigeon pea + fertilizer0.125629999999999889.4670000000000046E-20.147520000000000010.1250.152750000000000410.19173000000000001

Dominant maize + fertilizer tree intercropping systems

Mean plot sizes (hectare)

Maize kg/haGliricidia No fertilizerGliricidia + fertilizerTephrosia No fertilizerTephrosia + fertilizerPigeon pea No fertilizerPigeon pea + fertilizer3153.823569.663170.31000000000092887.092273.91000000000082711.42Plot Size (ha)Gliricidia No fertilizerGliricidia + fertilizerTephrosia No fertilizerTephrosia + fertilizerPigeon pea No fertilizerPigeon pea + fertilizer0.125629999999999949.4670000000000032E-20.147520000000000010.1250.152750000000000050.19173000000000001

Dominant maize + fertilizer tree intercropping systems

Maize grain yield (kg/ha

LilongweGliricidia No fertilizerWith fertilizerTephrosiaNo fertilizerWith fertilizerPigeon peasNo fertilizerWith fertilizerSesbaniaNo fertilizerWith fertilizerFaidherbiaNo fertilizerWith fertilizer2145.154294.251829.433350.33000000000222759.922872.37000000000222875.14032.3900000000012MzimbaGliricidia No fertilizerWith fertilizerTephrosiaNo fertilizerWith fertilizerPigeon peasNo fertilizerWith fertilizerSesbaniaNo fertilizerWith fertilizerFaidherbiaNo fertilizerWith fertilizer930.91645.42510.193473.172267.94999999999982460.41000000000121689.783028.61548.621856.79MachingaGliricidia No fertilizerWith fertilizerTephrosiaNo fertilizerWith fertilizerPigeon peasNo fertilizerWith fertilizerSesbaniaNo fertilizerWith fertilizerFaidherbiaNo fertilizerWith fertilizer2782.31000000000222785.221931.872334.23221.4ThyoloGliricidia No fertilizerWith fertilizerTephrosiaNo fertilizerWith fertilizerPigeon peasNo fertilizerWith fertilizerSesbaniaNo fertilizerWith fertilizerFaidherbiaNo fertilizerWith fertilizer4083.723170.173751.093020.74MulanjeGliricidia No fertilizerWith fertilizerTephrosiaNo fertilizerWith fertilizerPigeon peasNo fertilizerWith fertilizerSesbaniaNo fertilizerWith fertilizerFaidherbiaNo fertilizerWith fertilizer3388.81000000000223560.35000000000223779.91487.11761.64891.19SalimaGliricidia No fertilizerWith fertilizerTephrosiaNo fertilizerWith fertilizerPigeon peasNo fertilizerWith fertilizerSesbaniaNo fertilizerWith fertilizerFaidherbiaNo fertilizerWith fertilizer2968.824419.047629.73321.85000000000223916.079050.35999999989873204.36

Fertilizer trees management

Maize grain yield (kg/ha)

Plot size (ha)Maize aloneMaize + FertilizerMaize + fertilizer treesMaize + Fertilizer + Fert. trees0.350000000000000310.380000000000006550.150000000000000240.17fertilizer applied (kgha-1)Maize aloneMaize + FertilizerMaize + fertilizer treesMaize + Fertilizer + Fert. trees4.9175.790000000000006035.47

Seed rate (kgha-1)Maize aloneMaize + FertilizerMaize + fertilizer treesMaize + Fertilizer + Fert. trees37.66000000000001121.1733.72000000000001348.91

Maize plot manegement type

maize seed rate (kg/ha)

Maize aloneLilongweMzimbaMachingaThyoloMulanjeSalimaMaize grain yield (kg/ha) in different districts as affected by type of plots1271.17999999999981448.011861.65999999999991171.7606.30999999999949Maize + mineral fertilizerLilongweMzimbaMachingaThyoloMulanjeSalimaMaize grain yield (kg/ha) in different districts as affected by type of plots1660.251740.221837.022031.61213.13999999999991986.37Maize + fertilizer treesLilongweMzimbaMachingaThyoloMulanjeSalimaMaize grain yield (kg/ha) in different districts as affected by type of plots3709.33000000000222063.642404.343771.194197.843700.4700000000012Maize + fertilizer trees + mineral fertilizerLilongweMzimbaMachingaThyoloMulanjeSalimaMaize grain yield (kg/ha) in different districts as affected by type of plots3185.072618.132370.53000000000023613.5327254369.9699999999993

District

Maize grain yield (kg/ha)

Maize aloneLilongwemalefemaleMzimbamalefemaleMachingamalefemaleThyolomalefemaleMulanjemalefemaleSalimamalefemale1453.54979.413144.23963.373635.4887.85748.839999999999461425.42606.30999999999949Maize +mineral fertilizerLilongwemalefemaleMzimbamalefemaleMachingamalefemaleThyolomalefemaleMulanjemalefemaleSalimamalefemale1886.18999999999981387.241774.531694.87999999999991796.221877.822304.80000000000021867.66999999999981802.6759.722217.751916.96Maize + fertilizer treesLilongwemalefemaleMzimbamalefemaleMachingamalefemaleThyolomalefemaleMulanjemalefemaleSalimamalefemale4652.16000000000442200.792052.81000000000222075.362389.39000000000122434.23999999999984250.23000000000053240.533060.925903.215163.77000000000042968.82Maize + fertilizer trees + mineral fertilizerLilongwemalefemaleMzimbamalefemaleMachingamalefemaleThyolomalefemaleMulanjemalefemaleSalimamalefemale2991.543475.37000000000222685.072554.719999999999827112030.074783.23000000000052677.83000000000222483.862869.682889.614631.21

District and gender of farmer

maize grain yield (kg/ha)

Maize aloneLilongwemalefemaleMzimbamalefemaleMachingamalefemaleThyolomalefemaleMulanjemalefemaleSalimamalefemale0.354240.274570000000000311.69344999999999990.231610000000000010.164929999999999990.177750000000000210.475570000000000380.171800000000000010.25064999999999998Maize +mineral fertilizerLilongwemalefemaleMzimbamalefemaleMachingamalefemaleThyolomalefemaleMulanjemalefemaleSalimamalefemale0.431660000000000320.402420000000000670.366510000000000670.371820000000001150.371650000000000310.433510000000000730.344860000000000670.290540000000000020.230430000000000330.387270000000000720.364750000000000020.42676000000000008Maize + fertilizer treesLilongwemalefemaleMzimbamalefemaleMachingamalefemaleThyolomalefemaleMulanjemalefemaleSalimamalefemale0.139160000000000010.160789999999999990.10439.5000000000000043E-20.250160000000000050.256270.154990000000000520.276180000000000310.109950000000000028.7940000000000018E-26.7780000000000104E-20.1104099999999998Maize + fertilizer trees + mineral fertilizerLilongwemalefemaleMzimbamalefemaleMachingamalefemaleThyolomalefemaleMulanjemalefemaleSalimamalefemale0.171630.11690.189040000000000490.136550.254249999999999980.250630000000000022.1944000000000002E-24.6760000000000024E-20.185100000000000010.137559999999999995.6639999999999996E-20.23800000000000004

District and gender of farmer

Mean plot sizes (hectare)

Maize aloneLilongwemalefemaleMzimbamalefemaleMachingamalefemaleThyolomalefemaleMulanjemalefemaleSalimamalefemale112724005320Maize +mineral fertilizerLilongwemalefemaleMzimbamalefemaleMachingamalefemaleThyolomalefemaleMulanjemalefemaleSalimamalefemale48555102111681310224Maize + fertilizer treesLilongwemalefemaleMzimbamalefemaleMachingamalefemaleThyolomalefemaleMulanjemalefemaleSalimamalefemale12121490848230Maize + fertilizer trees + mineral fertilizerLilongwemalefemaleMzimbamalefemaleMachingamalefemaleThyolomalefemaleMulanjemalefemaleSalimamalefemale3233161863115146

District and household head gender

Frequency of land ownership

Frequency

Sold to obtain cashEat more often than before Food lasts longerExchanged for farm inputs (slashers, hoes, fertilizer etc)Other uses of extra cash3946352115Estimated maize grain yield kgha-1MaizeGroundnutsCassavaTobaccoPigeon peasVegetablesBeansMilletOtherNatural fallowNot applicable30093210392643521121349338451244344133611705

Previous fallow type

Maize Yield kg/ha

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