Using genotypic diversity to enhance climate resilience of peanut cropping in Limpopo Province

Abstract

Groundnut or peanut (Arachis hypogaea L.) is mostly grown by small-holder farmers in semi-arid regions of sub-Saharan Africa, particularly South Africa. As with other crops, not all groundnut cultivars respond equally well to the various climatic conditions in the South African province of Limpopo due to different environmental factors. Abiotic stress factors such as drought, extremely high temperatures, unpredictable and insufficient rainfall with annual variation that cannot be accurately predicted are limiting groundnut production in South Africa. In order to increase groundnut production, it is necessary to design properly the management practices, such as season and site-specific exploitation of cultivar x location x management (C x L x M) interactions, which will minimize the impact of the low rainfall and high temperature that characterize the production, particularly in Limpopo Province. The objective of this study was to assess the effects of groundnut cultivar on groundnut performance, soil water use and mineral nitrogen levels under different climatic conditions in Limpopo Province. A further objective was to validate the performance of Agricultural Production Systems Simulators (APSIM) model to predict the observed yields of groundnut cultivar yields under variable environmental and climatic conditions in Limpopo Province. Field experiments were conducted at two locations, the University of Limpopo (Syferkuil farm) and the University of Venda experimental farm during the 2018/2019 and 2019/2020 growing seasons. The experiments were laid out in randomized complete block design (RCBD) consisting of four treatments (groundnut cultivars: Kwarts, Sellie, Opal and Oleic) replicated four times to give a total of 16 plots each measuring 4 m × 3 m (12m2). Soil mineral nitrogen and dry biomass were determined at 50 % flowering and harvest maturity. Grain yield was collected at maturity and soil water content was determined every two weeks during the growing period using the gravimetric method. The APSIM-groundnut model (version 7.10) was used to simulate groundnut cultivars grain yield and biomass production to assess the risks associated with different climate conditions on the yield production of groundnut crops. The results obtained from this study showed that the groundnut cultivar influenced measured parameters (grain, nodulation and yield components) at both locations, whereas the effect of cultivar on biomass, soil moisture and mineral nitrogen was significant only at Syferkuil site. There was a significant difference in the cultivar and cultivar x location interaction on pods and seeds yield, harvest index and shelling percentages. Sellie produced a higher seed yield at Univen, while at Syferkuil Oleic produced the highest seed yield. The cultivar Opal performed well while Kwarts produced low yield in both seasons and locations. Irrespective of cultivar performance, Syferkuil produced less biomass and grain yield compared to Univen due to prolonged dry conditions over the seasons. The results further showed significant variation in soil water content at different depths among the cultivars and soil water content increased with soil depth. Cultivars with high biomass had high soil water content than those with low biomass at all soil depths. It was notable that cultivars with higher biomass showed a higher level of NO3--N and NH4+-N at all depths. At Univen, the soil NO3--N and NH4+-N levels increased at harvest while at Syferkuil NO3--N and NH4+-N decreased at harvest. The results demonstrated the benefits of soil moisture content on groundnut growth and soil mineral nitrogen. APSIM-model showed some capabilities of simulating groundnut grain and biomass yield in response to groundnut cultivar and different environments over the two locations that were simulated in both seasons. Therefore, in these locations, the APSIM model might be a helpful tool for predicting groundnut productivity.