Targeting sorghum improvement in drought-prone environments: Approaches and progress

Grain sorghum is grown in environments of highly variable water supply, both within and between seasons. This variability, coupled with associated genotype-by-environment (GxE) interactions, results in unclear definition of both target environment(s) and traits that may be used as selection criteria, causing slow progress in breeding for drought resistance. This paper reviews new approaches to characterize environments in terms of the incidence of water deficits and to assess the value of traits for improvement of drought resistance. Sorghum simulation models are powerful tools to characterize types of environmental challenges and their frequency of occurrence at different locations. Models also are being used to assess hypotheses about trait action and their value, and to develop optimal combinations of traits for different environmental challenges. Further research involving physiologists, agronomists, and plant breeders using integrated systems analysis will realize the potential of these approaches and improve the efficiency of selection in drought-prone environments

Soil organic carbon dynamics and crop yield for different crop rotations in a degraded ferruginous tropical soil in a semi-arid region: a simulation approach

In recent years, simulation models have been used as a complementary tool for research and for quantifying soil carbon sequestration under widely varying conditions. This has improved the understanding and prediction of soil organic carbon (SOC) dynamics and crop yield responses to soil and climate conditions and crop management scenarios. The goal of the present study was to estimate the changes in SOC for different cropping systems in West Africa using a simulation model. A crop rotation experiment conducted in Farakô-Ba, Burkina Faso was used to evaluate the performance of the cropping system model (CSM) of the Decision Support System for Agrotechnology Transfer (DSSAT) for simulating yield of different crops. Eight crop rotations that included cotton, sorghum, peanut, maize and fallow, and three different management scenarios, one without N (control), one with chemical fertilizer (N) and one with manure applications, were studied. The CSM was able to simulate the yield trends of various crops, with inconsistencies for a few years. The simulated SOC increased slightly across the years for the sorghum–fallow rotation with manure application. However, SOC decreased for all other rotations except for the continuous fallow (native grassland), in which the SOC remained stable. The model simulated SOC for the continuous fallow system with a high degree of accuracy normalized root mean square error (RMSE)=0·001, while for the other crop rotations the simulated SOC values were generally within the standard deviation (s.d.) range of the observed data. The crop rotations that included a supplemental N-fertilizer or manure application showed an increase in the average simulated aboveground biomass for all crops. The incorporation of this biomass into the soil after harvest reduced the loss of SOC. In the present study, the observed SOC data were used for characterization of production systems with different SOC dynamics. Following careful evaluation of the CSM with observed soil organic matter (SOM) data similar to the study presented here, there are many opportunities for the application of the CSM for carbon sequestration and resource management in Sub-Saharan Africa

Leaf photosynthesis and respiration of three bioenergy crops in relation to temperature and leaf nitrogen: how conserved are biochemical model parameters among crop species?

Given the need for parallel increases in food and energy production from crops in the context of global change, crop simulation models and data sets to feed these models with photosynthesis and respiration parameters are increasingly important. This study provides information on photosynthesis and respiration for three energy crops (sunflower, kenaf, and cynara), reviews relevant information for five other crops (wheat, barley, cotton, tobacco, and grape), and assesses how conserved photosynthesis parameters are among crops. Using large data sets and optimization techniques, the C3 leaf photosynthesis model of Farquhar, von Caemmerer, and Berry (FvCB) and an empirical night respiration model for tested energy crops accounting for effects of temperature and leaf nitrogen were parameterized. Instead of the common approach of using information on net photosynthesis response to CO2 at the stomatal cavity (An–Ci), the model was parameterized by analysing the photosynthesis response to incident light intensity (An–Iinc). Convincing evidence is provided that the maximum Rubisco carboxylation rate or the maximum electron transport rate was very similar whether derived from An–Ci or from An–Iinc data sets. Parameters characterizing Rubisco limitation, electron transport limitation, the degree to which light inhibits leaf respiration, night respiration, and the minimum leaf nitrogen required for photosynthesis were then determined. Model predictions were validated against independent sets. Only a few FvCB parameters were conserved among crop species, thus species-specific FvCB model parameters are needed for crop modelling. Therefore, information from readily available but underexplored An–Iinc data should be re-analysed, thereby expanding the potential of combining classical photosynthetic data and the biochemical model

Lablab purpureus—A Crop Lost for Africa?

In recent years, so-called ‘lost crops’ have been appraised in a number of reviews, among them Lablab purpureus in the context of African vegetable species. This crop cannot truly be considered ‘lost’ because worldwide more than 150 common names are applied to it. Based on a comprehensive literature review, this paper aims to put forward four theses, (i) Lablab is one of the most diverse domesticated legume species and has multiple uses. Although its largest agro-morphological diversity occurs in South Asia, its origin appears to be Africa. (ii) Crop improvement in South Asia is based on limited genetic diversity. (iii) The restricted research and development performed in Africa focuses either on improving forage or soil properties mostly through one popular cultivar, Rongai, while the available diversity of lablab in Africa might be under threat of genetic erosion. (iv) Lablab is better adapted to drought than common beans (Phaseolus vulgaris) or cowpea (Vigna unguiculata), both of which have been preferred to lablab in African agricultural production systems. Lablab might offer comparable opportunities for African agriculture in the view of global change. Its wide potential for adaptation throughout eastern and southern Africa is shown with a GIS (geographic information systems) approach