The Impact of Changing Weather Patterns on Maize Yield in South Africa: Evidence From Quantile Regression

Background The ongoing shifts in climate are harming maize harvests, food safety, and the economic well-being of small farmers in many low-income countries. As global heat rises, extreme weather becomes more frequent, complicating agricultural practices and food manufacturing. Farming systems in sub-Saharan Africa that rely on rain are prone to failure because of environmental pressures and poor soil quality. Future variations in weather and heat are predicted to alter nutrient cycles, crop maturation, and yields. These obstacles have grave impacts on society, leading to malnutrition and social unrest, thus positioning environmental change as a top priority for political leaders. This study investigated the impact of climate change on maize yields in South Africa context. Methods The annual data for maize yield were collected from the Food and Agriculture Organization (FOA) from 1981 to 2022. Monthly data covering the period 1981–2022 for maximum temperature, minimum temperature, and precipitation were collected from the power access (NASA Power Data Viewer) database. Both the annual and monthly data were transformed into quarterly data to ensure that the series had the same number of observations. Stata 14.0 was utilized to estimate the quantile regression model. Results The findings showed that maize yield was positively influenced by maximum temperature, precipitation, and temperature change on land. The minimum temperatures showed mixed findings, where a negative effect was observed at the lowest quantile (25th), whereas a positive relationship was found at the highest quantiles (90th and 95th). These results imply that provinces with lower maize production were severely affected by declining minimum temperatures. In contrast, rising minimum temperatures were beneficial for provinces with higher maize production. Conclusion There is a need to modify planting schedules to prevent exposure to low temperatures during essential growth phases. Farmers should employ accuracy agricultural technologies to monitor temperature fluctuations and adapt to the management strategies.