Smallholder Maize Research Articles

In-season plot area loss and implications for yield estimation in smallholder rainfed farming systems at the village level in Sub-Saharan Africa

The shortfalls in the quality, quantity, and reliability of agriculture performance data are neither new nor confined to Sub-Saharan Africa (SSA). It is, however, a more dire challenge given the overwhelming importance of agriculture in the economies of most countries in the region in terms of food security and poverty reduction. While farmers’ self-reported (SR) data on crop outputs and farm sizes remain popular variables for computing plot productivity and yields, especially in SSA, other methods such GPS measurement and remote sensing measurement of crop area, crop cuts (CC) as well as whole plot harvests have been touted as the gold standard methods for yield measurement. All these approaches to yield estimation are insufficient in capturing real agriculture productivity in rainfed farming systems due to the significant area loss that characterizes these farming systems in the course of each cropping season. This paper compares yield data of smallholder maize plots from two farming communities in the Eastern Region of Ghana based on farmer self-reported outputs and crop cuts, as well as GPS and aerial imagery measurement of plot area. The study finds a high level of agreement between GPS-measured plot area and that measured using remote sensing methods (R2 = 0.80) with the minor deviations between the two measures attributable to changes in farmers’ plans in the course of the season with regards to their cultivation extent. More interestingly, the study finds a substantial disparity between measured CC yields and SR yields; 2174 kg/ha for CC yields compared to 651 kg/ha for SR yields. The significant disparity between the two measures of yield is partly attributable to the significant intra-plot variability in crop performance leading to plot area loss in the course of the season. This area loss (ranging from 15 to 30% of the planted area) is usually not taken into account in current yield measurement approaches. Delineating the productive and planted-but-unproductive sections of plots has important implications not only for yield estimation methodologies but also for shedding more light on the factors underlying current poor yields and pathways to improving productivity on smallholder rainfed maize farms.

Exploring the profitability of improved storage technologies and their potential impacts on food security and income of smallholder farm households in Tanzania

This study assesses the profitability of selected improved grain storage technologies and the potential impact of their adoption on food security and income of smallholder maize producers in Tanzania. We used on-farm experiment data, time series maize price data, and household survey data to address the objectives. For the improved technologies, we considered Purdue Improved Crop Storage (PICS) bags, metallic silos of different sizes, and polypropylene (PP) bags treated with Actellic Super®. We compared them with PP bags without insecticide treatment as the control. Results show that PICS bags and PP bags plus Actellic Super are profitable in all locations and not significantly different. While the feasible period varies by location, profit is most likely negative if farmers sell their maize in the first two months after harvest and in the last two months before the next harvest. There are mixed results with regards to the profitability of metallic silos; bigger silos are profitable for farmers who have economies of scale to use them while smaller ones are profitable only within the context of higher grain price and bigger seasonal price gap. The results also show that PICS bags (or PP bags plus Actellic Super) are useful to address food security and income objectives among poor rural households whereas metallic silos with bigger storage capacity can increase the income of those farmers who have bigger surplus grain to sale.

Understanding The Purpose and Potential Popularity of Mobile Phone Use in Zambia’s Maize Production

There is a growing use of mobile phones in rural areas on account of its relative inexpensiveness and lack of requirement for an urban environment. As a platform for accessing information through text messages and voice calls, farmers are able to collect agricultural information which may lead to higher productivity due to technology spillover. If the use of mobile phones contributes to the improvement of farmers’ productivity, their agricultural output level should increase. In this study, we investigate the adoption of mobile phones to obtain agricultural information and its effect on smallholder maize farmers’ production using cross-sectional data from Zambia. Understanding such causal effects is indispensable especially against the background of vision 2030. The propensity score matching (PSM) method was adopted to estimate the average treatment effect of treated of mobile phone adoption in agriculture. We found that the use of mobile phones significantly increases farmers’ productivity, by about 30%. If farmers start to adopt mobile phones to collect agricultural information, the total maize output would also increase by 30.36%, which would culminate in feeding two more people per household daily for the whole year. Therefore, we cautiously conclude that mobile phone use in agriculture serves the purpose of contributing to the fight against hunger via enhancing maize production and this is driving its popularity among smallholder farmers in rural Zambia.

Smallholder maize area and yield mapping at national scales with Google Earth Engine

Accurate measurements of maize yields at field or subfield scales are useful for guiding agronomic practices and investments and policies for improving food security. Data on smallholder maize systems are currently sparse, but satellite remote sensing offers promise for accelerating learning about these systems. Here we document the use of Google Earth Engine (GEE) to build “wall-to-wall” 10 m resolution maps of (i) cropland presence, (ii) maize presence, and (iii) maize yields for the main 2017 maize season in Kenya and Tanzania. Mapping these outcomes at this scale is extremely challenging because of very heterogeneous landscapes, lack of cloud-free satellite imagery, and the low quantity of quality ground-based data in these regions.First, we computed seasonal median composites of Sentinel-1 radar backscatter and Sentinel-2 optical reflectance measures for each pixel in the region, and used them to build both crop/non-crop and maize/non-maize Random Forest (RF) classifiers. Several thousand crop/non-crop labels were collected through an in-house GEE labeler, and thousands of crop type labels from the 2015–2017 growing seasons were obtained from various sources. Results show that the crop/non-crop classifier successfully identified cropland with over 85% out-of-sample accuracy in both countries, with Sentinel-1 being particularly useful for prediction. Among the cropped pixels, the maize/non-maize classier had an accuracy of 79% in Tanzania and 63% in Kenya.To map maize yields, we build on past work using a scalable crop yield mapper (SCYM) that utilizes simulations from a crop model to train a regression that predicts yields from observations. Here we advance past approaches by (i) grouping simulations by Global Agro-Environmental Stratification (GAES) zones across the two countries, in order to account for landscape heterogeneity, (ii) utilizing gridded datasets on soil and sowing and harvest dates to setup model simulations in a scalable way; and (iii) utilizing all available satellite observations during the growing season in a parsimonious way by using harmonic regression fits implemented in GEE. SCYM estimates were able to capture about 50% of the variation in the yields at the district level in Western Kenya as measured by objective ground-based crop cuts.Finally, we illustrated the utility of our yield maps with two case studies. First, we document the magnitude and interannual variability of spatial heterogeneity of yields in each district, and how it varies for different parts of the region. Second, we combine our estimates with recently released soil databases in the region to investigate the most important soil constraints in the region. Soil factors explain a high fraction (72%) of variation in predicted yields, with the predominant factor being soil nitrogen levels. Overall, this study illustrates the power of combining Sentinel-1 and Sentinel-2 imagery, the GEE platform, and advanced classification and yield mapping algorithms to advance understanding of smallholder agricultural systems.

The Influence of an Agricultural Subsidy Extension Program on Smallholder Maize Farmers in Tanzania

Smallholder farming in Tanzania is a household activity implemented at the subsistence level. The government of Tanzania launched the subsidy program to promote food secure households and shift subsistence farming to business farming. Food insecurity was associated by low rates of fertilizer application and poor seed quality among smallholder farmers due to fertilizer and seed costs which led to an increase in food prices. This study aimed at assessing the impact of the agricultural subsidy program for smallholder maize farmers. Four research objectives focused on agricultural productivity, food security, usage of improved inputs, and farmers’ perceptions of how the program functioned. An ex post facto research design was used with a sample of 120 smallholder farmers. The investigation involved 60 farmers who received subsidies and 60 who did not. The study used an interviewer administered questionnaire. Farmers who received subsidies significantly increased maize production. Comparison of average output before and after subsides shows an increase in number of bags (100 kg) per acre from an average of 5.35 bags to 10.10 bags. Farmers who did not receive subsides produced about the same amount of maize at time one and time two. There was general satisfaction with the functioning of the program, however certain areas need to be improved including that program objectives are followed, ensuring farmers can manage market price of inputs, and enhancing extension services for farmers to produce more surplus

The Influence of an Agricultural Subsidy Extension Program on Smallholder Maize Farmers in Tanzania

Smallholder farming in Tanzania is a household activity implemented at the subsistence level. The government of Tanzania launched the subsidy program to promote food secure households and shift subsistence farming to business farming. Food insecurity was associated by low rates of fertilizer application and poor seed quality among smallholder farmers due to fertilizer and seed costs which led to an increase in food prices. This study aimed at assessing the impact of the agricultural subsidy program for smallholder maize farmers. Four research objectives focused on agricultural productivity, food security, usage of improved inputs, and farmers’ perceptions of how the program functioned. An ex post facto research design was used with a sample of 120 smallholder farmers. The investigation involved 60 farmers who received subsidies and 60 who did not. The study used an interviewer administered questionnaire. Farmers who received subsidies significantly increased maize production. Comparison of average output before and after subsides shows an increase in number of bags (100 kg) per acre from an average of 5.35 bags to 10.10 bags. Farmers who did not receive subsides produced about the same amount of maize at time one and time two. There was general satisfaction with the functioning of the program, however certain areas need to be improved including that program objectives are followed, ensuring farmers can manage market price of inputs, and enhancing extension services for farmers to produce more surplus

The effects of 2015 El Nino on smallholder maize production in the transitional ecological zone of Ghana

PurposeThis paper aims to provide empirical evidence on the El Nino and its effects on maize production in three municipalities: Ejura, Techiman and Wenchi in the transitional zone of Ghana. Using a mixed approach, the study details the effects of the El Nino on rainy season characteristics, particularly, rainfall amounts and distribution, onset and cessation of rains, duration of the rainy season and total seasonal rainfall and how it impacted smallholder maize production.Design/methodology/approachThe study used a mixed method approach in collecting and analyzing data. For stronger evidence building, (Creswell, 2013) the authors combined interviews and focus group discussions (FGD) to collect the qualitative data. Semi-structured questionnaires were administered to extension officers, management information system officers and other relevant personnel of the Ministry of Agriculture in the three municipalities. Six FGD’s were held for maize farmers in six communities in all three municipalities.FindingsThe study shows that the 2015 El Nino had dire consequences on farm yields, subsequently affecting farmer’s incomes and livelihoods. The study further finds that complex socio-cultural factors, some unrelated to the El Nino, aggravated the effects on maize farmers. These include the lack of adequate climatic information, predominance of rain-fed farming, a lack of capacity to adapt and existing levels of poverty.Originality/valueThe study recommends inter alia, appropriate use of seasonal rainfall forecasting to enhance better farming decision-making and the development of elaborate climate variability interventions by national and local agencies.

Factors Influencing the Extent of Push-Pull Technology Expansion Among Smallholder Maize Farmers in Homa Bay, Kenya

The research is financed by African Economic Research Consortium (AERC)and Egerton University Abstract Dissemination, continued uptake and expansion of the area covered by push-pull technology (PPT), remain critical requirements in addressing the major constraints facing maize production such as infestation by striga weed and stem borers, and declining soil fertility for improved livelihoods. Despite increasing investment and literature on PPT in Homa Bay County, there are still smallholder farmers who for unknown reasons have chosen only to expand a smaller portion of their potential land for PPT or those who have chosen to reduce the area covered by PPT since adoption. This study econometrically addresses this information gap by looking at the rate and factors influencing extent of PPT expansion. A multi-stage sampling procedure was applied to select a sample of 240 smallholder farmers in Homa Bay County. Data were obtained through a face-to-face interviews using a pretested semi-structured questionnaire, and analyzed using censored tobit model. The results revealed relatively low PPT expansion rate of about 48.59%. Tobit results revealed that gender, marital status, access to extension services, dissemination pathways, perception on the stem borer severity, napier seed availability, longevity of PPT use, total size of cultivable land, and distance to the nearest market significantly influenced the extent of PPT expansion. Interestingly, farmer-to-farmer, field days and farmer teachers were found to be the most important and effective dissemination pathways enhancing the extent of PPT expansion. Therefore, the paper recommends policies that seek to ensure equitable access to output and input markets, efficient and effective extension system, as well as those that ensure strengthening of social institutions for extensive use of PPT. Again, such policies should ensure establishment of an integrated input development system which involves all stakeholders in the development and dissemination of PPT inputs such as desmodium seeds. Keywords: Dissemination, Continued Adoption, Extent of PPT Expansion, Censored Tobit Model DOI : 10.7176/JESD/10-7-08 Publication date : April 30 th 2019

Review on Economic Efficiency of Maize Production in Ethiopia

Despite the fact that, agriculture remains to be the most significant sector of the Ethiopian economy, its performance has been disappointing and food production has been lagging behind population growth. Although increasing population pressure and low levels of agricultural productivity have aggravated the food insecurity situation by widening the gap between the demand for and supply of food in the country. This gap can be decreased by improving productivity either through the introduction of modern technologies or improving the efficiency of crop production. However, as the possibility to enhance production by bringing more resources into use became more and more limited, the efficiency with which the farmers use available resources has received the greatest attention. Since maize is a significant contributor to the Ethiopian economy, escalating productivity and efficiency of maize production could be taken as an important step in achieving food security. This review was aimed at assessing the levels of technical, allocative and economic efficiencies of smallholder maize producers; and to identify factors affecting the efficiency of smallholder farmers in maize production in Ethiopia. In these review factors like education, land fragmentation, livestock ownership, a frequency of extension contact, soil fertility, off/non-farm activities, sex, land owned, credit utilization and perception on agricultural policy are identified as the key determinants of the economic efficiency of maize production in Ethiopia. The frequency distribution of technical, allocative and economic efficiency levels was not fairly distributed. The maize farms were being operated in a different level of efficiency. This implies that a large number of maize farmers in Ethiopia faced inefficiency problems. Keywords: Maize, Economic efficiency, Determinants, Ethiopia DOI : 10.7176/FSQM/84-04

Understanding the factors influencing fall armyworm (Spodoptera frugiperda J.E. Smith) damage in African smallholder maize fields and quantifying its impact on yield. A case study in Eastern Zimbabwe

Fall armyworm (FAW, Spodoptera frugiperda J.E. Smith) is an invasive lepidopteran pest established in most of sub-Saharan Africa since 2016. Although the immediate reaction of governments has been to invest in chemical pesticides, control methods based on agronomic management would be more affordable to resource-constrained smallholders and minimize risks for health and the environment. However, little is known about the most effective agronomic practices that could control FAW under typical African smallholder conditions. In addition, the impact of FAW damage on yield in Africa has been reported as very large, but these estimates are mainly based on farmers' perceptions, and not on rigorous field scouting methods. Thus, the objectives of this study were to understand the factors influencing FAW damage in African smallholder maize fields and quantify its impact on yield, using two districts of Eastern Zimbabwe as cases. A total of 791 smallholder maize plots were scouted for FAW damage and the head of the corresponding farming household interviewed. Grain yield was later determined in about 20% of these fields. FAW damage was found to be significantly reduced by frequent weeding operations and by minimum- and zero-tillage. Conversely, pumpkin intercropping was found to significantly increase FAW damage. FAW damage was also found to be higher for some maize varieties, although these varieties may not be the lowest yielding. If the incidence of plants with FAW damage symptoms recorded in this research (32–48%, depending on the estimate used) is commensurate with what other studies conducted on the continent found, our best estimate of the impact of FAW damage on yield (11.57%) is much lower than what these studies reported. Although our study presents limitations, losses due to FAW damage in Africa could have been over-estimated. The threat that FAW represents for African smallholders, although very real, should not divert attention away from other pressing challenges they face.

Post-harvest Loss and Adoption of Improved Post-harvest Storage Technologies by Smallholder Maize Farmers in Tanzania

The study examines factors that influence the adoption of improved post-harvest storage technologies (IPHSTs) by smallholder maize farmers in Tanzania. The study employed a sample of 1620 observations from the National Panel Survey (NPS). Descriptive statistics indicated that 9 percent of the farmers experienced PHL and an average of 115 kilograms of maize per household is lost in various stages of post-harvest chain. Only 19 percent of farmers adopted IPHSTs. Logit regression results indicated that gender, age, harvest working days, use of hired labour and use of storage protectorant (pesticides and insecticides) had positive and significant influence on PHL. Further, quantity of maize harvested and age of households’ heads had positive and significant influence on adoption of IPHSTs. Therefore, the Government and development agencies should emphasize and promote the adoption of IPHSTs by smallholder farmers in order to mitigate PHL. Provision and support of extension education to farmers through trainings and seminars and extension visits on proper crop post-harvest management, storage technologies and skills is pertinent. Keywords: post-harvest loss, adoption, improved post-harvest storage technologies, panel data, smallholder farmers JEL Classification: Q12, Q13, Q17, Q18, C23

Profitability of Improved Seed Adoption on Small Holders Maize Farmers in Abuja Nigeria

The study analysed the profitability of improved seed adoption on the profitability and technical efficiency of smallholder maize farmers in Abuja, Nigeria. Descriptive statistics were used to describe the socioeconomic characteristics, gross margin analysis was used to determine the costs and returns of maize production. The t-test was used to compare the yield of improved maize seed adopters and non-adopters. The logit regression was used to analyse the determinants of adoption. The stochastic production frontier model was used to determine the technical efficiency of IMV. The results revealed that the average age of respondents (adopters and non-adopters) was 48 years and 39 years, respectively. Furthermore, 56% and 66% were male, 75% and 93% were married with average household size of 6 and 7 persons, respectively, and majority had formal education. Adopters had a mean farm size of 1.95 ha, while non-adopters had a mean farm size of 1.76 ha. The gross margin analysis result showed the profitability index for IMV and local seed were 0.66 and 0.41, respectively. The t-test result showed that IMV had higher yield per hectare (2,713.66kg/ha) compared to local maize variety (1,281.33kg/ha). The result of maximum likelihood estimate showed that the mean technical efficiency was 0.56 and 0.49 for adopters and non-adopters, respectively. The study revealed that adopters of improved maize seed varieties earned higher profits and were more technically efficient than non-adopters. It recommended the strengthening of extension services to enhance adoption through awareness by government. Farmers should form cooperatives to enable resourceful negotiation for inputs. Also, an improvement in the research and development of high quality improved maize varieties should be encouraged.

An Analysis of the Characteristics of Maize Storage Types Used by Smallholder Producers in Developing Countries: A Case of Uganda

Smallholder maize farmers are often faced with storage challenges. In Uganda, smallholder farmers are the major producers of maize. After production, the majority sell most of the maize then later buy for consumption at higher prices. This puzzle of producing, selling and later buying for consumption is attributed to inadequate and inefficient storage and is the premise of this investigation. The knowledge of the impact of household storage and farmers’ perception in Uganda is limited. The study sought to assess whether the storage types used are associated with the smallholder farmers’ characteristics. A multi-stage random sampling procedure was used to collect cross-sectional data from 270 farmers. The region of Eastern Uganda was selected because it is the highest maize producing. Three districts were selected on the basis of being the highest, medium and lowest maize producers, respectively. The chi-square tests were used to check for the relationships between the variables measured at 95% confidence level (p

Determinants of Access to Agricultural Credit among Small holder Maize Farmers: The Case of Hababo Guduru District, Horro Guduru Wollega Zone, Ethiopia

Access to agricultural credit remains a major challenge for smallholder farmers in Ethiopia. One of the reasons for very low agricultural productivity in developing countries and particularly in Ethiopia is that lack of access to agricultural credit. Hence, we intend to identify determinants of access to agricultural credit among smallholder maize farmers in Hababo Guduru District, Horro Guduru Wollega Zone, Ethiopia. The data were obtained from a total of 260 sample households, 120 who have access to credit and 140 who do not have access to credit via two stage random sampling technique. Descriptive statistics and probit model were used to analyze the data.The results of the probit model show that age, sex, education, number of livestock owned, year of membership for the credit institution, frequency of extension contact and distance from credit source were significant factors affecting farmers’ accessibility to agricultural credit in the study area. Therefore, government policy that intends to improve the smallholder farmer’s access to agricultural credit facilities should formulate well-functioning system of providing credit.

How efficient is maize production among smallholder farmers in Zimbabwe? A comparison of semiparametric and parametric frontier efficiency analyses

ABSTRACTThe controversial Fast Track Land Reform Programme in Zimbabwe that redistributes commercially-owned farmland to smallholder households has caused concerns about the efficiency of agricultural production in the country. In this paper, we estimate the efficiency of resource use among smallholder farmers in Zimbabwe when producing maize, the staple crop in the country. Using both a semiparametric model and a fully parametric stochastic frontier model, we find significant production shortfalls for smallholder maize production. While labor, capital, and land all significantly affect the total output, the estimated mean efficiency score for farms with less than 10 hectares of land (A1) appears to be under 0.75, and for the entire sample (A1 and A2) it ranges between 0.595 and 0.772. There clearly exists a great potential for maize farmers to improve the technical efficiency and increase the total output. Gender and age of the household head, access to extension services, and activities of other crops significantly affect the technical efficiency of smallholder maize production in Zimbabwe. We also find that all farms operate under increasing returns to scale and that the technical efficiency score tends to increase with the level of output.

Determinants and Change in Total Factor Productivity of Smallholder Maize Production in Southern Zambia

Smallholder maize production in Zambia has been characterised by low productivity despite concerted efforts at improving the situation as is evident in budgetary allocations to programmes such as the Farmer Input Support Programme (FISP). The study assessed if there was a change in total factor productivity (TFP) in smallholder maize production in Southern Province of Zambia between the 2010/11 and 2013/14 agricultural seasons. Using a balanced panel of 778 smallholder farmers, a Stochastic Frontier Analysis was used to estimate the Malmquist Productivity Index (MPI) in measuring the productivity change in maize production. The change in TFP was further decomposed into its components, efficiency change (EC) and technical change (TC) so as to understand more on the change in productivity. It was found that over the period of study, the mean EC was 0.8734, implying that technical efficiency (TE) had declined by 12.7 % with the mean TFP of 0.9401, indicating that over the study period TFP had fallen by 5.99 %. The results further showed that the age of the farmer, education of the farmer, household size, membership to a farmer organization, ownership of cattle, access to credit, and drought stress were significant (ρ<0.05) factors in explaining TFP. In light of the findings, some recommendations were made for policy including the need to facilitate farmers’ access to credit, sensitize farmers on the benefits of belonging to farmer organizations, on ownership of livestock such as cattle and for massive investment in irrigation infrastructure.

Fertilizer response and nitrogen use efficiency in African smallholder maize farms

Improving fertilizer recommendations for farmers is essential to increase food security in smallholder landscapes. Currently, blanket recommendations are provided across agro-ecological zones, although fertilizer response and nutrient use efficiency by maize crop are spatially variable. We aimed to identify factors that could help to refine fertilizer recommendation by analyzing the variability in fertilizer response (FR) and the agronomic nitrogen use efficiency (N-AE). A literature search for on-farm studies across Kenya and Sub-Sahara Africa (SSA), excluding Kenya, yielded 71 publications. The variability in FR was studied using a meta-analysis whereas key factors that influence FR and N-AE were studied with linear regression models. On average, the FR was 2, but it varied considerably from 1 to 28.5 (excluding outliers). In SSA, 18% of the plots were non-responsive plots with an FR < 1. The main factors affecting N-AE for Kenya were P-Olsen, silt content, soil pH, clay and rainfall, whereas only soil pH, exchangeable K and texture were important for SSA. However, our study indicates that available data on soil, climate and management factors could explain only a small part (< 33%) of the variation in FR and N-AE. Soil pH, P-Olsen, silt content, and rainfall had significant but low levels of power in explaining variation in FR and N-AE. Our findings indicate that strategies to refine fertilizer recommendation should include information on soil types and soil properties.

Assessing drivers of maize storage losses in south west Benin using a Fractional Response Model: Poster

An assessment of drivers of maize storage losses was undertaken in south west Benin applying the Fractional Response Model on information collected from 400 smallholder maize farmers. Overall, respondents lose on average 10.3% of their harvest during the storage period. The average marginal effect obtained from the fractional response model of storage losses revealed that storage technologies, farmers’ post-harvest attitudes, insects damage, the weather conditions and infrastructures played a significant role in the level of storage losses surveyed farmers have experienced. Farmers using bags and plastic containers have respectively reduced their storage losses by 6.7 and 7.8% compared to farmers using cribs. Considering the use of storage protectant, the results indicated that using ash, neem leaves, pepper or lemon lead to an increase of 4.1% of losses relative to storing without any protectant. Drying after harvesting decreased by 1.9% the share of the quantity stored lost during storage. The percentage of maize lost increased by 5.1% for respondents who have reported insects as predators of their stored maize. Rain at harvest time increased the percentage of losses by 2.1%. A one-degree increase in temperature increased the percentage of maize loss by 4.4% and farmers who live at less than 26.5 km to the market have reduced by 0.17% of maize losses. Effective policies for a sustainable reduction of storage losses among maize farmers in the area should consider the need to discourage the use of cribs, ash, leaves, pepper and lemon as storage technologies. Farmers should avoid harvesting during times of rain, and should properly dry their produce after harvesting. Sustainable hermetic equipment should be promoted and farmers’ access to markets facilitated.

Impact of Alternative Soil Fertility Management Options on Maize Productivity in Malawi’s Smallholder Farming System

This paper focuses on smallholder maize production in Malawi by investigating the link between productivity and soil fertility management. Many studies conducted in Malawi indicate declining levels of maize productivity thereby posing food security concerns, since maize is the staple crop for most areas of the country. This analysis focuses on the factors influencing productivity of maize among smallholder farmers, especially given the fears that unfavorable output and input market conditions throughout the 1990s may have compelled smallholder farmers into unsustainable agricultural intensification. Farm-household survey data is thus used to compare the productivity of smallholder maize production under integrated soil fertility (ISFM) and chemical-based soil fertility management. A normalized translog yield response model is estimated by imposing monotonicity and curvature correctness at the sample mean. The results indicate higher maize yield responses for integrated soil fertility management options, after controlling for the intensity of fertilizer application, labour intensity, seed rate, land husbandry practices and policy factors such as market access, extension and credit access. The estimated model is highly consistent with theoretical regularity conditions. Thus, the findings indicate that the use of ISFM increases maize productivity in comparison to the use of inorganic fertilizers. Since most farmers in the maize-based farming systems are crowded out of the agricultural input market and can hardly afford optimal quantities of inorganic fertilizer, enhancement of ISFM provides scope for enhancing maize productivity and food security especially where inorganic fertilizer is highly unaffordable and risky to use. Thus there is need for policy interventions to promote smallholder uptake of ISFM options. Finally areas of policy support in crop output and input market development, credit access and extension service provision are identified to enhance ISFM uptake in smallholder maize-based farming systems.

Labour Dynamics in Climate and Techno Reliant Small Scale Maize Production

Adoption of improved technology tends to recalibrate labour use in agricultural production. The study examined how the adoption of various maize varieties impacted labour use in smallholder production. The study utilised a structured pre-coded questionnaire-based survey of 487 smallholder maize farmers in South Africa. The purposive sample was obtained from Ingquza Hill and Port St John’s Local Municipalities in the Eastern Cape Province. A multinomial regression model and Monte Carlo Simulation were utilised to analyse the data. Statistical Package for Social Scientist (SPSS) version 23 as well as Excel were the statistical tools utilised. Through multinomial regression analysis, the study found that weeding labour was the most significantly affected by a change in maize variety. It was observed that as maize variety transcends in use from Landrace to GMO, improved OPV and conventional hybrid, ploughing and weeding hours tend to decrease. The harvesting, storage and shelling hours tend to increase. Utilising the Monte Carlo Simulation, the study also found an increased impact of maize variety utilisation on harvesting as well as on shelling and storage labour hours. The study recommends that varieties be promoted taking cognizance of the labour dynamics to tier maximize suitability and labour-based productivity, reducing tedious labour use in ploughing and weeding, whilst promoting employment in harvesting, shelling and storage.