Water use of sorghum (Sorghum bicolor L. Moench) in response to varying planting dates evaluated under rainfed conditions

It is vital to understand how rainfall onset, amount and distribution between planting dates affect sorghum yield and water use, in order to aid planting date and cultivar selection. This study investigated morphological, physiological, phenological, yield and water use characteristics of different sorghum genotypes in response to different planting dates under rainfed conditions. Four genotypes (PAN8816 [hybrid], Macia [open-pollinated variety, OPV], Ujiba and IsiZulu [both landraces]) were planted on 3 planting dates (early, optimal, and late) in a split-plot design, with planting dates as the main factor. Low soil water at the optimal planting date was associated with delayed crop establishment and low final emergence. Sorghum genotypes adapted to low and irregular rainfall at the late planting date through low leaf number, canopy cover, chlorophyll content index and stomatal conductance, and hastened phenological development. This resulted in low biomass and grain yields. Landraces exhibited grain yield stability across planting dates, whilst OPV and hybrid genotypes significantly reduced grain yield in response to low water availability when planted late. Biomass and grain yield water use efficiency (WUE) were highest at optimal planting date (30.5 and 9.2 kg∙ha-1·mm-1), relative to late (23.1 and 8.7 kg·ha-1·mm-1), and early planting dates (25.2 and 8.3 kg·ha-1·mm-1). For PAN8816 and Macia, biomass and grain WUE decreased in response to low soil water content, and irregular and disproportionate rainfall experienced during the late planting date. By contrast, biomass and grain WUE for Ujiba and IsiZulu improved with decreasing rainfall. PAN8816 is recommended when planting under low soil water availability to maximize crop stand. Cultivation of Macia is recommended under optimal conditions. Ujiba and IsiZulu landraces are recommended for low rainfall areas with highly variable rainfall. Repetition or modelling of genotype responses across environments different from Ukulinga is required for thorough water use characterisation of these genotypes.Keywords: planting dates, water use efficiency, rainfall variability, cultivar selection, landraces and improved sorghum varietie

Assessing Suitability of Sorghum to Alleviate Sub-Saharan Nutritional Deficiencies through the Nutritional Water Productivity Index in Semi-Arid Regions

Lack of cereal nutritional water productivity (NWP) information disadvantages linkages of nutrition to water–food nexus as staple food crops in Sub-Saharan Africa (SSA). This study determined the suitability of sorghum (Sorghum bicolor L. Moench) genotypes to alleviate protein, Zn and Fe deficiency under water-scarce dryland conditions through evaluation of NWP. Sorghum genotypes (Macia, Ujiba, PAN8816, IsiZulu) NWP was quantified from three planting seasons for various sorghum seed nutrients under dryland semi-arid conditions. Seasons by genotypes interaction highly and significantly affected NWPStarch, Ca, Cu, Fe, and significantly affected NWPMg, K, Na, P, Zn. Genotypic variations highly and significantly affected sorghum NWPProtein, Mn. Macia exhibited statistically superior NWPprotein (13.2–14.6 kg·m−3) and NWPZn (2.0–2.6 g·m−3) compared to other tested genotypes, while Macia NWPFe (2.6–2.7 g·m−3) was considerably inferior to that of Ujiba and IsiZulu landraces under increased water scarcity. Excellent overall NWPprotein, Fe and Zn under water scarcity make Macia a well-rounded genotype suitable to alleviating food and nutritional insecurity challenges in semi-arid SSA; however, landraces are viable alternatives with limited NWPprotein and Zn penalty under water-limited conditions. These results underline genotype selection as a vital tool in improving “nutrition per drop” in semi-arid regions

Assessing Suitability of Sorghum to Alleviate Sub-Saharan Nutritional Deficiencies through the Nutritional Water Productivity Index in Semi-Arid Regions

Lack of cereal nutritional water productivity (NWP) information disadvantages linkages of nutrition to water–food nexus as staple food crops in Sub-Saharan Africa (SSA). This study determined the suitability of sorghum (Sorghum bicolor L. Moench) genotypes to alleviate protein, Zn and Fe deficiency under water-scarce dryland conditions through evaluation of NWP. Sorghum genotypes (Macia, Ujiba, PAN8816, IsiZulu) NWP was quantified from three planting seasons for various sorghum seed nutrients under dryland semi-arid conditions. Seasons by genotypes interaction highly and significantly affected NWPStarch, Ca, Cu, Fe, and significantly affected NWPMg, K, Na, P, Zn. Genotypic variations highly and significantly affected sorghum NWPProtein, Mn. Macia exhibited statistically superior NWPprotein (13.2–14.6 kg·m−3) and NWPZn (2.0–2.6 g·m−3) compared to other tested genotypes, while Macia NWPFe (2.6–2.7 g·m−3) was considerably inferior to that of Ujiba and IsiZulu landraces under increased water scarcity. Excellent overall NWPprotein, Fe and Zn under water scarcity make Macia a well-rounded genotype suitable to alleviating food and nutritional insecurity challenges in semi-arid SSA; however, landraces are viable alternatives with limited NWPprotein and Zn penalty under water-limited conditions. These results underline genotype selection as a vital tool in improving “nutrition per drop” in semi-arid regions

Calibration and testing of AquaCrop for selected sorghum genotypes

Predicting yield response to water is important in rainfed agriculture. The objective of this study was to calibrate and test AquaCrop for simulating yield of 3 sorghum genotypes (PAN8816, a hybrid; Macia, an open-pollinated variety; and Ujiba, a landrace) grown during the 2013/14 and 2014/15 planting seasons (early, optimal and late planting dates). Variables considered during model evaluation included canopy cover (CC), biomass (B) and yield (Y). The model was able to simulate CC (R2 ≥ 0.710; root mean square error (RMSE) ≤ 22.73%; Willmott’s d-index (d) ≥ 0.998), biomass accumulation (R2 ≥ 0.900; RMSE ≤ 10.45%; d ≥ 0.850), harvest index (R2 ≥ 0.902; RMSE ≤ 7.17%; d ≥ 0.987) and yield (R2 ≥ 0.945; RMSE ≤ 3.53%; d ≥ 0.783) well for all genotypes and planting dates after calibration. AquaCrop over-estimated biomass and crop yield. The relatively good simulations produced by the minimum data input calibration confirm AquaCrop’s simplicity and suitability for use in places where extensive datasets may be unavailable. Biomass and yield overestimation resulting from the use of the minimum data input calibration suggests that other parameters (water productivity, canopy sensitivity to water stress and water stress coefficient) are required to improve canopy and yield predictions for sorghum genotypes