scholarly journals Linking field survey with crop modeling to forecast maize yield in smallholder farmers’ fields in Tanzania

Food Security ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 537-548 ◽  
Author(s):  
Lin Liu ◽  
Bruno Basso
Keyword(s):  
Field Survey ◽  
Smallholder Farmers ◽  
Maize Yield ◽  
Crop Modeling

scholarly journals Sensitivity of Maize Yield in Smallholder Systems to Climate Scenarios in Semi-Arid Regions of West Africa: Accounting for Variability in Farm Management Practices

Agronomy ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 639 ◽  
Author(s):  
Bright Freduah ◽  
Dilys MacCarthy ◽  
Myriam Adam ◽  
Mouhamed Ly ◽  
Alex Ruane ◽  
...  
Keyword(s):  
Climate Change ◽  
Arid Regions ◽  
Climate Models ◽  
Smallholder Farmers ◽  
Maize Yield ◽  
Climate Scenarios ◽  
Relative Standard ◽  
The Impact ◽  
Semi Arid ◽  
Smallholder Systems

Climate change is estimated to exacerbate existing challenges faced by smallholder farmers in Sub-Sahara Africa. However, limited studies quantify the extent of variation in climate change impact under these systems at the local scale. The Decision Support System for Agro-technological Transfer (DSSAT) was used to quantify variation in climate change impacts on maize yield under current agricultural practices in semi-arid regions of Senegal (Nioro du Rip) and Ghana (Navrongo and Tamale). Multi-benchmark climate models (Mid-Century, 2040–2069 for two Representative Concentration Pathways, RCP4.5 and RCP8.5), and multiple soil and management information from agronomic surveys were used as input for DSSAT. The average impact of climate scenarios on grain yield among farms ranged between −9% and −39% across sites. Substantial variation in climate response exists across farms in the same farming zone with relative standard deviations from 8% to 117% at Nioro du Rip, 13% to 64% in Navrongo and 9% to 37% in Tamale across climate models. Variations in fertilizer application, planting dates and soil types explained the variation in the impact among farms. This study provides insight into the complexities of the impact of climate scenarios on maize yield and the need for better representation of heterogeneous farming systems for optimized outcomes in adaptation and resilience planning in smallholder systems.

Are conservation agriculture (CA) systems productive and profitable options for smallholder farmers in different agro-ecoregions of Zimbabwe?

2016 ◽  
Vol 32 (1) ◽  
pp. 87-103 ◽  
Author(s):  
W. Mupangwa ◽  
M. Mutenje ◽  
C. Thierfelder ◽  
I. Nyagumbo
Keyword(s):  
Smallholder Farmers ◽  
Cropping Systems ◽  
Conservation Agriculture ◽  
Maize Yield ◽  
Crop Productivity ◽  
Conventional Tillage ◽  
Direct Seeding ◽  
Maize Production ◽  
Production Risk ◽  
Conventional Practice

AbstractContinuous conventional tillage coupled with unsystematic cereal/legume rotations has promoted low crop productivity on smallholder farms. A multi-locational study was established in three agro-ecoregions (AEs) of Zimbabwe. The aim of the study was to determine the effect of four tillage systems (conventional plowing, planting basins, rip-line and animal traction direct seeding systems) on maize (Zea mays L.), cowpea [Vigna unguiculata (L.) Walp] and soybean [Glycine max (L.) Merrill] yields, and evaluate the economic performance of the conservation agriculture (CA) systems relative to conventional plowing. Each farmer was a replicate of the trial over the three cropping seasons. In the high (750–1000 mm per annum) and low (450–650 mm) rainfall AEs, conventional practice and CA systems gave similar maize grain yield. Under medium rainfall conditions (500–800 mm) planting basins, rip-line and direct seeding systems gave 547, 548 and 1690 kg ha−1 more maize yield than the conventional practice. In the high and low rainfall AEs, conventional practice and planting basins had the lowest maize production risk. Cowpea yield was 35 and 45% higher in the rip-line and direct seeding than conventional practice. Soybean yield was higher in rip-line (36%) and direct seeding (51%) systems than conventional practice. Direct seeding system gave the highest net benefits in all AEs. A combination of long-term biophysical and socio-economic assessments of the different cropping systems tested in our study is critical in order to fully understand their performance under different AEs of Zimbabwe.

scholarly journals Effect of the Push-Pull Cropping System on Maize Yield, Stem Borer Infestation and Farmers’ Perception

Agronomy ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 452
Author(s):  
Teshome Kumela ◽  
Esayas Mendesil ◽  
Bayu Enchalew ◽  
Menale Kassie ◽  
Tadele Tefera
Keyword(s):  
Soil Fertility ◽  
Smallholder Farmers ◽  
Abiotic Factors ◽  
Sustainable Use ◽  
Cropping System ◽  
Maize Yield ◽  
Stem Borer ◽  
Maize Production ◽  
Maize Productivity ◽  
Livestock Feed

The productivity of maize in Ethiopia has remained lower than the world average because of several biotic and abiotic factors. Stemborers and poor soil fertility are among the main factors that contribute to this poor maize productivity. A novel cropping strategy, such as the use of push-pull technology, is one of the methods known to solve both challenges at once. A push-pull technology targeting the management of maize stemborers was implemented in the Hawassa district of Ethiopia with the ultimate goal of increased food security among smallholder farmers. This study evaluated farmers’ perception of push-pull technology based on their experiences and observations of the demonstration plots that were established on-farm in Dore Bafano, Jara Gelelcha and Lebu Koremo village of the Hawasa district in 2016 and 2017. This study examined farmers’ perception of the importance of push-pull technology in controlling stemborers and improving soil fertility and access to livestock feed. In both cropping seasons, except for Jara Gelelcha, the maize grain yields were significantly higher in the climate-adapted push-pull plots compared to the maize monocrop plots. The majority (89%) of push-pull technology-practising farmers rated the technology better than their maize production methods on attributes such as access to new livestock feed and the control of stemborer damage. As a result, approximately 96% of the interviewed farmers were interested in adopting the technology starting in the upcoming crop season. Awareness through training and effective dissemination strategies should be strengthened among stakeholders and policymakers for the sustainable use and scaling-up of push-pull technology.

scholarly journals 11-Year Rainfall and Maize Yield Variation (2003-2013) in Four Northern Districts of Malawi

2016 ◽  
Vol 8 (5) ◽  
pp. 95
Author(s):  
Naohiro Matsui
Keyword(s):  
Sweet Potato ◽  
Crop Yields ◽  
Smallholder Farmers ◽  
Seasonal Fluctuation ◽  
Critical Factor ◽  
Maize Yield ◽  
Total Rainfall ◽  
Yield Variation ◽  
Cropping Season ◽  
Maize Yields

<p>Rainfall in the maize cropping season (Oct-Apr) in the four northern districts of Malawi was examined in terms of seasonal fluctuation and spatial distribution, and data spanning 11 years were analyzed. Rainfall fluctuations in the 11-year period differed considerably among the four districts and the Extension Planning Areas (EPAs) showed high coefficients of variance (CVs) (16.9-93.7). The equation with the three-month rainfall (October, February, and April), i.e., Maize yield (kg/ha) in SH = 2.29 + 0.0042 × Oct rainfall – 0.0009 × Feb rainfall + 0.00045 × Apr rainfall (r<sup>2</sup> = 0.41), better explained maize yield in the 2013/14 season than the equation with total rainfall in the cropping season. Rainfall accounted for more than 41% of the total variation in maize yields of smallholder farmers (SHs). Rainfall in April was the most critical factor influencing maize and other crop yields. After the Farm Input Subsidy Programme (FISP) was implemented in 2005/06, maize yield became more dependent on rainfall. CV was higher in maize than in groundnut and sweet potato, indicating that maize is susceptible to rainfall fluctuations, and groundnut and sweet potato should be incorporated in farming as a countermeasure against unpredictable rainfall.</p>

Improving crop modeling to better simulate maize yield variability under different irrigation managements

2022 ◽  
Vol 262 ◽  
pp. 107429
Author(s):  
Olufemi P. Abimbola ◽  
Trenton E. Franz ◽  
Daran Rudnick ◽  
Derek Heeren ◽  
Haishun Yang ◽  
...  
Keyword(s):  
Maize Yield ◽  
Yield Variability ◽  
Crop Modeling

scholarly journals Current Status of Pearl Millet Downy Mildew Prevalence across Agroecological Zones of Senegal

2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Yedomon Ange Bovys Zoclanclounon ◽  
Ghislain Kanfany ◽  
Aboubacry Kane ◽  
Daniel Fonceka ◽  
Georgina Lala Ehemba ◽  
...  
Keyword(s):  
Downy Mildew ◽  
Pearl Millet ◽  
Field Survey ◽  
Smallholder Farmers ◽  
Disease Incidence ◽  
Climatic Conditions ◽  
Current Status ◽  
Biotic Stresses ◽  
Agroecological Zones ◽  
Infected Area

Pearl millet is a dominant staple cereal crop for smallholder farmers in Senegal. However, the crop is constrained by various nonbiotic and biotic stresses such as downy mildew disease. To assess the prevalence of this disease in Senegal, a field survey was conducted during the rainy season of 2017 across eight main pearl millet production regions following latitudinal gradient with different climatic conditions. Results showed that downy mildew prevalence was higher in Kaolack (incidence = 68.19%), Kaffrine (incidence = 77.19%), Tambacounda (incidence = 97.03%), Sedhiou (incidence = 82.78%), and Kolda (incidence = 98.01%) than Thies (incidence = 28.21%), Diourbel (incidence = 24.46%), and Fatick (incidence = 37.75%) regions. The field survey revealed an incidence as high as 98% and 28% of infected area in surveyed fields. Significant correlations between geographic coordinates, disease incidence, and infected areas were also observed. This study provided information that could help to understand the prevalence of downy mildew in pearl millet in Senegal.

scholarly journals Soil Nutrients and Maize Yields Responses to Agroforestry Tree Post-fallows Management in Tanzania

2021 ◽  
Author(s):  
Vincent G. Vyamana ◽  
Shabani A.O. Chamshama ◽  
Samora Macrice Andrew
Keyword(s):  
Soil Fertility ◽  
Smallholder Farmers ◽  
Maize Yield ◽  
Sub Saharan Africa ◽  
Degraded Land ◽  
Agricultural Technologies ◽  
Short Rotation ◽  
Continuous Maize ◽  
Development Goals ◽  
Sub Saharan

Abstract Agriculture forms a backbone of many countries in sub-Saharan Africa (SSA) thus has the potential to contribute to achieving Sustainable Development Goals (SDGs). However, agriculture in the SSA is characterized by low production due to soil fertility depletion. Use of appropriate low input agricultural technologies may increase production and benefit smallholder farmers through increased productivity in already degraded land. A field experiment was established to assess tree coppice intercropping of Albizia harveyi and Albizia versicolor for soil fertility and maize yield improvements in Morogoro, Tanzania. Tree fallows of A. versicolor aged three years increased significantly soil organic Carbon, Calcium, Magnesium and Potassium. Yields of maize grain, cobs and stover in maize fields intercropped with A. versicolor were significantly higher than those with A. harveyi. Fields with continuous maize cropping had the least yields of grain, cobs and stover. The studied agroforestry tree species are recommended for rotational woodlots and short rotation coppice systems to enhance agricultural productivity for achieving SDGs.

scholarly journals Divergent responses of maize yield to precipitation in the United States

2021 ◽  
Author(s):  
Ru Xu ◽  
Yan Li ◽  
Kaiyu Guan ◽  
Lei Zhao ◽  
Bin Peng ◽  
...  
Keyword(s):  
United States ◽  
Spatial Heterogeneity ◽  
Temperature Response ◽  
Maize Yield ◽  
The United States ◽  
Security Assessment ◽  
Crop Modeling ◽  
Crop Models ◽  
Precipitation Response ◽  
Precipitation Threshold

Abstract How maize yield responds to precipitation variability in space and time over broader scales is largely unknown compared with the well-understood temperature response, even though precipitation change is more erratic with greater spatial heterogeneity. Here, we develop a method to quantify the spatially explicit precipitation response of maize yield using statistical data and crop models in the contiguous United States. We find the precipitation responses are highly heterogeneous with inverted-U (40.3%) being the leading response type, followed by unresponsive (30.39 %), and linear increase (28.6%). The optimal precipitation threshold derived from inverted-U response exhibits considerable spatial variations, which is higher under wetter, hotter, and well-drainage conditions but lower under drier and poor-drainage conditions. Irrigation alters precipitation response by making yield either unresponsive to precipitation or having lower optimal thresholds than rainfed conditions. We further find that the observed precipitation responses of maize yield are misrepresented in crop models, with a too high percentage of increase type (59.0% versus 29.6%) and an overestimation in optimal precipitation threshold by ~90 mm. These two factors explain about 30% and 85% of the inter-model yield overestimation biases under extreme rainfall conditions. Our study highlights the large spatial heterogeneity and the key role of human management in the precipitation responses of maize yield, which need to be better characterized in crop modeling and food security assessment under climate change.

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