Related Experiment Video
Updated: Feb 3, 2026

Measuring Crop Motility and Food Passaging in Drosophila
Published on: May 9, 2020
Modelling predicts that soybean is poised to dominate crop production across Africa
Christine H Foyer1,2, Kadambot H M Siddique3, Amos P K Tai4,5
1Centre for Plant Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, UK.
Abstract:
The superior agronomic and human nutritional properties of grain legumes (pulses) make them an ideal foundation for future sustainable agriculture. Legume-based farming is particularly important in Africa, where small-scale agricultural systems dominate the food production landscape. Legumes provide an inexpensive source of protein and nutrients to African households as well as natural fertilization for the soil. Although the consumption of traditionally grown legumes has started to decline, the production of soybeans (Glycine max Merr.) is spreading fast, especially across southern Africa. Predictions of future land-use allocation and production show that the soybean is poised to dominate future production across Africa. Land use models project an expansion of harvest area, whereas crop models project possible yield increases. Moreover, a seed change in farming strategy is underway. This is being driven largely by the combined cash crop value of products such as oils and the high nutritional benefits of soybean as an animal feed. Intensification of soybean production has the potential to reduce the dependence of Africa on soybean imports. However, a successful "soybean bonanza" across Africa necessitates an intensive research, development, extension, and policy agenda to ensure that soybean genetic improvements and production technology meet future demands for sustainable production.
Related Concept Videos
Predicting Products: Substitution vs. Elimination
The following factors can influence the mechanisms competing against each other:
Predicting Products: SN1 vs. SN2
With increased substitution on the alkyl halide,...
Incomplete Dominance
Predicting Molecular Geometry
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
End Point Prediction: Gran Plot
For potentiometric titration, the Gran plot is created by plotting...

