Spatiotemporal prediction and optimization of environmental suitability in citrus-producing areas

Abstract

The increasing need for citrus has driven the rapid expansion of citrus planting areas. However, not all areas are suitable for growing citrus. It is necessary to understand the future changing trend of environmental suitability in citrus-producing areas. Here, based on the soil nutrient data of citrus cultivation from 2006 to 2018, the spatiotemporal kriging method was used to predict the spatiotemporal distribution of soil nutrients in Zigui County, Hubei Province. Then, geographical and meteorological conditions were combined to evaluate the suitability for citrus cultivation at temporal and spatial levels, and the results were verified by the yield and quality data of citrus. The results showed that from 2018 to 2027, the overall suitability of the citrus-producing area displayed a gradually rising trend, with the “suitable” producing area increasing from 4.5% to 20.16%. The validation results indicated that the mean relative errors of spatiotemporal predictors were less than 30% except for the effective iron. Correlation analysis revealed that the proportion of “moderately suitable” and “suitable” orchards had significant positive correlations with annual yield. The low suitability of Maoping town was mainly attributed to its soil acidification and available P content, and that of Shazhenxi town was ascribed to its low soil contents of available P and N. The optimal fertilization scheme was constructed by an artificial neural network to optimize the fertilization status of some citrus producing areas. This study has created a dynamic assessment of the environmental suitability of citrus production areas to support improvements in citrus production.