Climate Change Impacts on Sustainable Maize Production in Sub-Saharan Africa: A Review

Mulungu, Kelvin; Ng’ombe, John N.

doi:10.5772/intechopen.90033

Cited by 26 publications

(15 citation statements)

References 26 publications

(50 reference statements)

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“…Also, the use of combined climate information can improve the understanding of the relationship between crop production and the weather oscillations and improve the resilience of the global food system (food security) to unexpected climate-related shocks [16,[56][57][58].…”

Section: Discussionmentioning

confidence: 99%

Improving Soybean Production Under Light Supplementation at Field - A Case Study

Lemes

Azevedo

Domiciano

et al. 2020

Preprint

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In modern agriculture, there is a growing need for cropping efficiency e low environmental impacts. Diverse technologies are becoming available in a recent wave of modernization and integration of knowledge. The use of high-efficiency light supplementation to plant development is scarce to high-productive crops at field conditions (outdoor). The objectives of this study were to evaluate soybean plant and yield responses in an open commercial area (field scale) cultivated with artificial light supplementation. A commercial irrigated (pivot) area received an illumination system for light supplementation (LS) in the inner pivot spans. The light applied was a composition of blue, green and red bands. The outer pivot spans did not receive light supplementation (nLS). About 40 hours of LS were applied to the plants during the soybean crop cycle. Internode number, plant height, pods per plant were weekly evaluated to compose the area under the progress curve (AUPC). The grain yield was also evaluated at harvest. Analysis of variance and test of averages were used to evaluate the data. The AUPC of the internode number, plant height and pods per plant were 15.6, 23.3 and 25.3% higher than for the LS treatment. The regular soybean cycle (nLS) was about 17 weeks; however, the harvest of the LS treatment happened three weeks later. The grain productivity of the nLS was about 4,500 kg ha-1 (75 bags), and of the LS treatment was about 7,080 kg ha-1 (118 bags) - 57.3% superior. Light supplementation at field scale is a challenge; however, affordable and field resistant technologies are now accessible. The present study is the first report of light supplementation used to improve soybean crop production at field scale. The possibility of using light regulation as an additional technique for increasing yields and sustainable production are also discussed.

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Section: Discussionmentioning

confidence: 99%

Improving Soybean Production Under Light Supplementation at Field - A Case Study

Lemes

Azevedo

Domiciano

et al. 2020

Preprint

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“…Projected future changes in temperature and rainfall directly threaten the overall agricultural crop production system (Arslan, 2018;Jain, 2007) because over 90% of smallholder agriculture production in Zambia is rainfed with only about 3% of the total planted area being irrigated (Hamududu & Ngoma, 2020). For example, 70-80% of maize crop losses in sub-Saharan Africa are attributed to climate changeenhanced droughts and floods, which makes maize one of the most susceptible crops to climate change (Mulungu & Ng'ombe, 2020). Several studies have reported that maize will be among the most negatively affected crops due to anticipated future climate patterns with measurable consequences on food security (Adhikari et al, 2015;Chisanga et al, 2017;Jones & Thornton, 2003;Mulenga et al, 2015;Thornton et al, 2011;Wang et al, 2015;Wineman & Crawford, 2017;Zipper et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Climate change impacts on maize and soybean yields in Zambia

2022

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Projected changes in temperature and rainfall directly threaten the overall agricultural crop production system in Zambia where 75% of agricultural production is rainfed. This study investigates the effects of future climate on maize (Zea mays L.) and soybean [Glycine max (L.) Merr.] yields using relatively high spatial resolution downscaled climate data in Central and Eastern Zambia. The Agrometshell model was applied to simulate historical and future crop yields. To account for the effects of climate change on crop yields, global climate models (GCMs) and Representative Concentration Pathways (RCPs) were used. Most yield functions were significant with R2 values >.7 with p < .05, indicating the model's ability to capture variations in observed data. Mean maize yield change decreased across RCPs and GCMs in Central Province and the decrease amplified in several areas in the far future, suggesting worsening effects into the future. But the projected mean yield changes in Eastern Province remain mostly within the historical range of variability, suggesting that maize yield in this province is less sensitive to climate change. Projected mean soybean yield changes in Central Province consist of a combination of reductions and improvements. Soybean yields in Eastern Province were projected to increase in the near future, shifting to large increases in the far future. Drastic reductions in maize yields are likely to cause major negative effects in the agricultural system because maize is a staple crop in the country. In contrast, soybean showed less sensitivity to future climate and demonstrates the value of diversifying agricultural systems and increasing the sustainability of food production systems.

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“…Taken together, it follows that there is a growing body of research investigating the impacts of climate change adaptation strategies in Zambia and across sub-Saharan Africa (SSA). Examples of such studies include [15][16][17][18][19][20][21][22][23][24][25][26]. However, the limited capacity of smallholder farmers to adapt to climate change in Zambia [4,25] in part contributes to the low adoption rates of climate change adaptation measures [19,21].…”

Section: Introductionmentioning

confidence: 99%

“Are They Aware, and Why?” Bayesian Analysis of Predictors of Smallholder Farmers’ Awareness of Climate Change and Its Risks to Agriculture

2020

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While climate change threatens global food security, health, and nutrition outcomes, Africa is more vulnerable because its economies largely depend on rain-fed agriculture. Thus, there is need for agricultural producers in Africa to employ robust adaptive measures that withstand the risks of climate change. However, the success of adaptation measures to climate change primarily depends on the communities’ knowledge or awareness of climate change and its risks. Nonetheless, existing empirical research is still limited to illuminate farmers’ awareness of the climate change problem. This study employs a Bayesian hierarchical logistic model, estimated using Hamiltonian Monte Carlo (HMC) methods, to empirically determine drivers of smallholder farmers’ awareness of climate change and its risks to agriculture in Zambia. The results suggest that on average, 77% of farmers in Zambia are aware of climate change and its risks to agriculture. We find socio-demographics, climate change information sources, climate change adaptive factors, and climate change impact-related shocks as predictors of the expression of climate change awareness. We suggest that farmers should be given all the necessary information about climate change and its risks to agriculture. Most importantly, the drivers identified can assist policymakers to provide the effective extension and advisory services that would enhance the understanding of climate change among farmers in synergy with appropriate farm-level climate-smart agricultural practices.

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Climate Change Impacts on Sustainable Maize Production in Sub-Saharan Africa: A Review

Cited by 26 publications

References 26 publications

Improving Soybean Production Under Light Supplementation at Field - A Case Study

Improving Soybean Production Under Light Supplementation at Field - A Case Study

Climate change impacts on maize and soybean yields in Zambia

“Are They Aware, and Why?” Bayesian Analysis of Predictors of Smallholder Farmers’ Awareness of Climate Change and Its Risks to Agriculture

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