scholarly journals Unravelling the variability and causes of smallholder maize yield gaps in Ethiopia

Food Security ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 83-103 ◽  
Author(s):  
Banchayehu Tessema Assefa ◽  
Jordan Chamberlin ◽  
Pytrik Reidsma ◽  
João Vasco Silva ◽  
Martin K. van Ittersum
Keyword(s):  
Stochastic Frontier Analysis ◽  
National Level ◽  
Total Yield ◽  
Maize Yield ◽  
Sub Saharan Africa ◽  
Yield Gap ◽  
Potential Yield ◽  
Frontier Analysis ◽  
Yield Gaps ◽  
Maize Yields

AbstractEthiopia has achieved the second highest maize yield in sub-Saharan Africa. Yet, farmers’ maize yields are still much lower than on-farm and on-station trial yields, and only ca. 20% of the estimated water-limited potential yield. This article provides a comprehensive national level analysis of the drivers of maize yields in Ethiopia, by decomposing yield gaps into efficiency, resource and technology components, and accounting for a broad set of detailed input and crop management choices. Stochastic frontier analysis was combined with concepts of production ecology to estimate and explain technically efficient yields, the efficiency yield gap and the resource yield gap. The technology yield gap was estimated based on water-limited potential yields from the Global Yield Gap Atlas. The relative magnitudes of the efficiency, resource and technology yield gaps differed across farming systems; they ranged from 15% (1.6 t/ha) to 21% (1.9 t/ha), 12% (1.3 t/ha) to 25% (2.3 t/ha) and 54% (4.8 t/ha) to 73% (7.8 t/ha), respectively. Factors that reduce the efficiency yield gap include: income from non-farm sources, value of productive assets, education and plot distance from home. The resource yield gap can be explained by sub-optimal input use, from a yield perspective. The technology yield gap comprised the largest share of the total yield gap, partly due to limited use of fertilizer and improved seeds. We conclude that targeted but integrated policy design and implementation is required to narrow the overall maize yield gap and improve food security.

scholarly journals Wheat yield gaps across smallholder farming systems in Ethiopia

2021 ◽  
Vol 41 (1) ◽  
Author(s):  
João Vasco Silva ◽  
Pytrik Reidsma ◽  
Frédéric Baudron ◽  
Moti Jaleta ◽  
Kindie Tesfaye ◽  
...  
Keyword(s):  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Wheat Yield ◽  
Farming Systems ◽  
Smallholder Farming ◽  
Yield Gap ◽  
Frontier Analysis ◽  
Ecological Zones ◽  
Relative Contribution ◽  
Yield Gaps

AbstractWheat yields in Ethiopia need to increase considerably to reduce import dependency and keep up with the expected increase in population and dietary changes. Despite the yield progress observed in recent years, wheat yield gaps remain large. Here, we decompose wheat yield gaps in Ethiopia into efficiency, resource, and technology yield gaps and relate those yield gaps to broader farm(ing) systems aspects. To do so, stochastic frontier analysis was applied to a nationally representative panel dataset covering the Meher seasons of 2009 and 2013 and crop modelling was used to simulate the water-limited yield (Yw) in the same years. Farming systems analysis was conducted to describe crop area shares and the availability of land, labour, and capital in contrasting administrative zones. Wheat yield in farmers’ fields averaged 1.9 t ha− 1 corresponding to ca. 20% of Yw. Most of the yield gap was attributed to the technology yield gap (> 50% of Yw) but narrowing efficiency (ca. 10% of Yw) and resource yield gaps (ca. 15% of Yw) with current technologies can nearly double actual yields and contribute to achieve wheat self-sufficiency in Ethiopia. There were small differences in the relative contribution of the intermediate yield gaps to the overall yield gap across agro-ecological zones, administrative zones, and farming systems. At farm level, oxen ownership was positively associated with the wheat cultivated area in zones with relatively large cultivated areas per household (West Arsi and North Showa) while no relationship was found between oxen ownership and the amount of inputs used per hectare of wheat in the zones studied. This is the first thorough yield gap decomposition for wheat in Ethiopia and our results suggest government policies aiming to increase wheat production should prioritise accessibility and affordability of inputs and dissemination of technologies that allow for precise use of these inputs.

scholarly journals Identifying maize yield and precipitation gaps in Uganda

2021 ◽  
Vol 3 (5) ◽  
Author(s):  
Terence Epule Epule ◽  
Driss Dhiba ◽  
Daniel Etongo ◽  
Changhui Peng ◽  
Laurent Lepage
Keyword(s):  
Cropping Systems ◽  
Growing Season ◽  
Maize Yield ◽  
Sub Saharan Africa ◽  
World Bank Group ◽  
Precipitation Data ◽  
Yield Data ◽  
Yield Gaps ◽  
Maize Yields ◽  
Growing Season Precipitation

AbstractIn sub-Saharan Africa (SSA), precipitation is an important driver of agricultural production. In Uganda, maize production is essentially rain-fed. However, due to changes in climate, projected maize yield targets have not often been met as actual observed maize yields are often below simulated/projected yields. This outcome has often been attributed to parallel gaps in precipitation. This study aims at identifying maize yield and precipitation gaps in Uganda for the period 1998–2017. Time series historical actual observed maize yield data (hg/ha/year) for the period 1998–2017 were collected from FAOSTAT. Actual observed maize growing season precipitation data were also collected from the climate portal of World Bank Group for the period 1998–2017. The simulated or projected maize yield data and the simulated or projected growing season precipitation data were simulated using a simple linear regression approach. The actual maize yield and actual growing season precipitation data were now compared with the simulated maize yield data and simulated growing season precipitation to establish the yield gaps. The results show that three key periods of maize yield gaps were observed (period one: 1998, period two: 2004–2007 and period three: 2015–2017) with parallel precipitation gaps. However, in the entire series (1998–2017), the years 2008–2009 had no yield gaps yet, precipitation gaps were observed. This implies that precipitation is not the only driver of maize yields in Uganda. In fact, this is supported by a low correlation between precipitation gaps and maize yield gaps of about 6.3%. For a better understanding of cropping systems in SSA, other potential drivers of maize yield gaps in Uganda such as soils, farm inputs, crop pests and diseases, high yielding varieties, literacy, and poverty levels should be considered.

scholarly journals Rice Yield Gaps in Smallholder Systems of the Kilombero Floodplain in Tanzania

Agronomy ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 1135
Author(s):  
Julius Kwesiga ◽  
Kristina Grotelüschen ◽  
Kalimuthu Senthilkumar ◽  
Daniel Neuhoff ◽  
Thomas F. Döring ◽  
...  
Keyword(s):  
Field Experiments ◽  
Farmyard Manure ◽  
Total Yield ◽  
Crop Management ◽  
Nutrient Deficiencies ◽  
Green Manures ◽  
Yield Gap ◽  
Potential Yield ◽  
Mineral N ◽  
Yield Gaps

To meet the growing rice demand in Africa, gaps between actual and attainable yields have to be reduced. In Tanzania, this particularly concerns smallholder rain-fed production systems in the floodplains. After quantifying the existing yield gaps, key contributing factors need to be analyzed to improve site-specific management. Field experiments were conducted for three years and in three pedo-hydrological environments (fringe, middle, and center positions) of the Kilombero floodplain to evaluate: (1) The grain yield under farmers’ management (actual yield), (2) yield with the best-recommended management (attainable yield), and (3) the non-limited yield simulated by the APSIM model (potential yield). In the field, we additionally assessed incremental effects of (1) field bunding and soil levelling, (2 and 3) additionally applying of 60 kg N ha−1, as urea or as farmyard manure (FYM), and (4 and 5) incorporating in-situ-grown leguminous green manures. Attainable yields were determined with mineral N application at 120 kg ha−1, additional PK fertilizer and supplemental irrigation. On average across years and positions, the potential, the attainable, and farmers’ actual yields were 11.5, 8.5, and 2.8 t ha−1 indicating a high total yield gap. About 16–38%, 11–20%, and 28–42% of this gap could be attributed to non-controllable yield-reducing (i.e., pest and diseases), yield-limiting (i.e., water and nutrient deficiencies), and yield-defining factors (i.e., poor soil and crop management), respectively. Results indicate a closure of the exploitable yield gap (differences between attainable and farmers’ actual yields) by up to 6.5 t ha−1 (nearly 60% of the potential yield). This exploitable yield gap was larger in 2016 than in 2017. Also, the gap was larger in the water-limited fringe and middle than in the frequently submerged center positions. Simple field bunds combined with land levelling could close 15–35% of the exploitable yield gap, depending on field positions and year. FYM or green manures were less effective than mineral N; however, in 2017 and in the wetter middle and center positions, they reduced the yield gap by >50%. We conclude that yield gaps in rainfed rice in Kilombero floodplain are large, but that a site- and system-specific adaptation of crop management can close much of the exploitable yield gap and increase grain yields by 0.7–4.8 t ha−1. Similar benefits may be obtained in other hydrologically variable floodplain environments of the region and beyond.

scholarly journals Economics of Milk Production and Yield Differentials among the Marginal Women Farmers of Jharkhand State in India

2019 ◽  
pp. 1-11
Author(s):  
Aniketa Horo ◽  
B. S. Chandel
Keyword(s):  
Milk Production ◽  
Milk Yield ◽  
Total Yield ◽  
Fixed Cost ◽  
Yield Gap ◽  
Potential Yield ◽  
Average Productivity ◽  
Net Returns ◽  
Yield Gaps ◽  
Crossbred Cow

Aim: To determine the economics of milk production and yield gaps of crossbred cow, buffalo and indigenous cow in Jharkhand State of India. Study Design: The study was designed to cater the scope of production economics in reality by suggesting ways to bridge the yield gaps. Place and Duration of Study: The present study was conducted using 130 beneficiary farmers in Hazaribagh and Khunti districts of Jharkhand during the 2016-17 agricultural year. Methodology: As per the technique of the yield gap analysis, developed by Gomez (1977), the total yield gap is the sum of Yield Gap I (YG I) and Yield Gap II (YG II). The various cost components were identified under fixed cost and variable cost. Gross returns and net returns were then calculated accordingly. Results: The sampled households were post-stratified into two groups: Group 1 abbreviated as G1, having less than or equal to 2 lactating animals and Group 2 as G2, having more than two lactating animals. The proportion of G1 and G2 households were about 79 and 21 per cent, respectively. The results of data analysis reflected that milk yield gap between potential yield and actual yield (YG II) was higher than yield gap between experimental yield and potential yield (YG I) for both household groups across all the type of dairy animals. The YG II in crossbred cow was more than two times higher on G1 farm as compared to G2 farm while it was more than five times higher in local cow. The average productivity of crossbred (9.23 litres/ day) was much higher than the average productivity of buffalo (6.09 litres) and local cow (4.98 litres/day). Conclusion: Overall value of total yield gap (TYG) entails that if all the constraints regarding the milk production were tackled then the milk yield of the two districts could be increased by about 43 per cent. Buffalo was providing higher net returns per day per animal (Rs. 7.39) in comparison to crossbred (Rs. 5.19). Net returns both for per day and per litre were negative in case of local cow. The study reveals that the marginal farmers can become economically stable by incorporating dairying (crossbred and buffalo) as a component in their farming system.

scholarly journals Closing maize yield gaps in sub-Saharan Africa will boost soil N2O emissions

2020 ◽  
Vol 47 ◽  
pp. 95-105 ◽  
Author(s):  
Sonja Leitner ◽  
David E Pelster ◽  
Christian Werner ◽  
Lutz Merbold ◽  
Elizabeth M Baggs ◽  
...  
Keyword(s):  
Maize Yield ◽  
Sub Saharan Africa ◽  
N2o Emissions ◽  
Yield Gaps ◽  
Sub Saharan

scholarly journals Diagnosing the Climatic and Agronomic Dimensions of Rain-Fed Oat Yield Gaps and Their Restrictions in North and Northeast China

2019 ◽  
Vol 11 (7) ◽  
pp. 2104 ◽  
Author(s):  
Chong Wang ◽  
Jiangang Liu ◽  
Shuo Li ◽  
Ting Zhang ◽  
Xiaoyu Shi ◽  
...  
Keyword(s):  
Northeast China ◽  
Crop Production ◽  
Crop Yields ◽  
Climatic Conditions ◽  
Planting Density ◽  
Limiting Factors ◽  
High Yield ◽  
Yield Gap ◽  
Potential Yield ◽  
Yield Gaps

Confronted with the great challenges of globally growing populations and food shortages, society must achieve future food security by increasing grain output and narrowing the gap between potential yields and farmers’ actual yields. This study attempts to diagnose the climatic and agronomic dimensions of oat yield gaps and further to explore their restrictions. A conceptual framework was put forward to analyze the different dimensions of yield gaps and their limiting factors. We quantified the potential yield (Yp), attainable yield (Yt), experimental yield (Ye), and farmers’ actual yield (Ya) of oat, and evaluated three levels of yield gaps in a rain-fed cropping system in North and Northeast China (NC and NEC, respectively). The results showed that there were great differences in the spatial distributions of the four kinds of yields and three yield gaps. The average yield gap between Yt and Ye (YG-II) was greater than the yield gap between Yp and Yt (YG-I). The yield gap between Ye and Ya (YG-III) was the largest among the three yield gaps at most sites, which indicated that farmers have great potential to increase their crop yields. Due to non-controllable climatic conditions (e.g., light and temperature) for obtaining Yp, reducing YG-I is extremely difficult. Although YG-II could be narrowed through enriching soil nutrients, it is not easy to improve soil quality in the short term. In contrast, narrowing YG-III is the most feasible for farmers by means of introducing high-yield crop varieties and optimizing agronomic managements (e.g., properly adjusting sowing dates and planting density). This study figured out various dimensions of yield gaps and investigated their limiting factors, which should be helpful to increase farmers’ yields and regional crop production, as long as these restrictions are well addressed.

Relative Sowing Time and Density of Component Crops in a Maize/Cowpea Intercrop System

1987 ◽  
Vol 23 (1) ◽  
pp. 41-52 ◽  
Author(s):  
Francis Ofori ◽  
W. R. Stern
Keyword(s):  
Seed Protein ◽  
Total Yield ◽  
Maize Yield ◽  
Protein Yield ◽  
Sowing Time ◽  
Maize Yields ◽  
Total Seed

SUMMARYThe effect of variations in the relative sowing time and density of component crops in a maize/cowpea intercrop were examined in two experiments. In the first experiment, maize and cowpea were sown together, and either 10 or 21 days before or after each other. Maize yield was reduced when sown at the same time or after cowpea; intercrop cowpea yields were less than sole cowpea yields at all sowings. In the second experiment, maize densities of 35, 50 and 70 × 103plants ha−1were combined with cowpea densities of 70, 100 and 140 × 103plants ha−1. Increasing the density of either crop in the mixture resulted in increases in total yield. Maize reduced cowpea yields more than the effect of cowpea on maize yields. In terms of LER and total seed protein yield, there was no advantage of either staggered sowings over simultaneous sowing or of the various intercrop density combinations, except between the lowest and the highest densities of either maize or cowpea. The LERs appeared to follow the trends in cowpea yields and total seed protein yields the trends in maize yields.

scholarly journals Technical efficiency and yield gap of smallholder wheat producers in Ethiopia: A Stochastic Frontier Analysis

2018 ◽  
Vol 13 (28) ◽  
pp. 1407-1418 ◽  
Author(s):  
Mamo Tadele ◽  
Getahun Wudineh ◽  
Chebil Ali ◽  
Tesfaye Agajie ◽  
Debele Tolessa ◽  
...  
Keyword(s):  
Technical Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Yield Gap ◽  
Frontier Analysis

Closing the Global Irrigation Yield Gap alongside SSPs

2020 ◽  
Author(s):  
Marina Andrijevic ◽  
Nicole van Maanen ◽  
Carl-Friedrich Schleussner ◽  
Lorenzo Rosa
Keyword(s):  
Climate Change ◽  
Economic Development ◽  
Agricultural Sector ◽  
National Level ◽  
Yield Gap ◽  
Potential Yield ◽  
Climate Change Research ◽  
Availability Constraints ◽  
Socio Economic Development ◽  
Sustainable Irrigation

<div> <div> <div> <p>The <em>global yield gap</em> is a concept to assess the difference between the actual yield and the maximum potential yield that could be achieved by applying optimal agricultural techniques such as irrigation. Climate change and socio-economic development, including population growth, call for addressing the yield gap to increase global production and to adapt to climate change as irrigation in many circumstances is a very effective adaptation measure. On the regional level, the irrigation yield gap can thus be interpreted as an indicator linked to adaptive capacity of the agricultural sector to climate change impacts. At the same time, effective deployment of irrigation is linked, among other things, to the socio-economic development including economic capabilities, but also institutional and water governance frameworks.</p> <p>Based on a detailed assessment of the irrigation yield gap, taking into account water availability constraints such as environmental flow requirements, we here establish as sustainable irrigation adaptation index for the agricultural sector. In a next step we link this sustainable irrigation index to socio-economic indicators provided by the framework of Socio- Economic Pathways (SSPs) on the national level. Doing so allows us to project the closure of the yield gap alongside the quantitative SSP narratives of socio-economic developments. We find that even under very optimistic scenarios of socio-economic development, it will take decades to close the irrigation yield gap in many developing countries, while without substantial development improvements our results suggest limited improvement in many tropical countries. Our projections present a first attempt to consistently link future irrigation expansion to socio-economic scenarios used in climate change research. We report a substantial scenario dependence of this expansion that underscores the need to incorporate socio-economic projections into projections of future agricultural impacts.</p> </div> </div> </div>

scholarly journals Narrowing the Agronomic Yield Gaps of Maize by Improved Soil, Cultivar, and Agricultural Management Practices in Different Climate Zones of Northeast China

2016 ◽  
Vol 20 (12) ◽  
pp. 1-18 ◽  
Author(s):  
Zhijuan Liu ◽  
Xiaoguang Yang ◽  
Xiaomao Lin ◽  
Kenneth G. Hubbard ◽  
Shuo Lv ◽  
...  
Keyword(s):  
Physical Properties ◽  
Agricultural Production ◽  
Northeast China ◽  
Management Practices ◽  
Growing Season ◽  
Maize Yield ◽  
Soil Physical Properties ◽  
Potential Yield ◽  
Climate Zones ◽  
Yield Gaps

Abstract Northeast China (NEC) is one of the major agricultural production areas in China, producing about 30% of China’s total maize output. In the past five decades, maize yields in NEC increased rapidly. However, farmer yields still have potential to be increased. Therefore, it is important to quantify the impacts of agronomic factors, including soil physical properties, cultivar selections, and management practices on yield gaps of maize under the changing climate in NEC in order to provide reliable recommendations to narrow down the yield gaps. In this study, the Agricultural Production Systems Simulator (APSIM)-Maize model was used to separate the contributions of soil physical properties, cultivar selections, and management practices to maize yield gaps. The results indicate that approximately 5%, 12%, and 18% of potential yield loss of maize is attributable to soil physical properties, cultivar selection, and management practices. Simulation analyses showed that potential ascensions of yield of maize by improving soil physical properties PAYs, changing to cultivar with longer maturity PAYc, and improving management practices PAYm for the entire region were 0.6, 1.5, and 2.2 ton ha−1 or 9%, 23%, and 34% increases, respectively, in NEC. In addition, PAYc and PAYm varied considerably from location to location (0.4 to 2.2 and 0.9 to 4.5 ton ha−1 respectively), which may be associated with the spatial variation of growing season temperature and precipitation among climate zones in NEC. Therefore, changing to cultivars with longer growing season requirement and improving management practices are the top strategies for improving yield of maize in NEC, especially for the north and west areas.

Sign in / Sign up

Export Citation Format

Share Document