A hybrid simulation framework for predicting virus impacts on Chinese cabbage yields

Abstract

Sustainable production of Chinese cabbage (Brassica rapa L.) is essential for the economy and food security in South Korea. However, climate change poses significant threats to its growth and quality. Changes in precipitation patterns, such as drought and heavy rain, can affect the development of crop, leading to stunted growth or disease. This can lead to significant losses in crop yield. In this study, a hybrid modeling system was developed to predict the incidence of viral disease and evaluate impacts of combination of virus infection and environmental variabilities (including climate and location) on marketable cabbage yields. The crop growth model was successfully developed using a limited number (n = 7) of previous studies (root mean square error 0.25–0.33 Mg ha−1, R2 = 0.87–0.99). The developed hybrid modeling system was composed of a virus incident model and a crop growth model. According to simulated results, all study locations had around 20% incidence rates. However, based on the simulation results, the rates of viral disease incidence varied depending on the climate of each year. Among several climatic factors, precipitation had the greatest effect on virus outbreaks. Jeju Island, which had relatively high rainfall, had a higher disease incidence rate than other provinces. According to shared socioeconomic pathways (SSPs), in SSP245 (an intermediate development pathway), the yield of 1.58 Mg ha−1 was reduced to 1.26 Mg ha−1 due to a 25% viral disease outbreak. In SSP585 (a high development pathway), with an incidence of 23%, the yield was reduced by 0.2 Mg ha−1. These results will be useful for efficiently cultivating crops under various climatic conditions and seeking management methods to minimize damage from viral disease. © 2023 The Authors. Agronomy Journal © 2023 American Society of Agronomy.