Fuzzy Model for Risk Characterization in Avocado Crops for Index Insurance Configuration

Climate change has caused strong variations in agroclimatic parameters such as precipitation, temperature, and relative humidity, accelerating the phytosanitary conditions associated with agricultural crops, mainly in insect pests, since these generate an alteration in their life cycle and an increase in their population. This causes significant economic damage to important crops such as the Hass avocado, which has had a growing development and demand in national and international markets, which has generated significant income for small and medium-sized farmers and exporters of this fruit in the country. To mitigate the impacts of climate change on agricultural production, it is possible to implement digital agriculture technologies. These technologies allow estimating the incidence of climate variations on crops through the monitoring of agroclimatic and phytosanitary variables that affect fruit growth. Therefore, a variable dispersion model with fuzzy characterization is proposed that seeks to establish a correlation between rainfall and the aggregate distribution of losses in the Hass avocado crop. In order to analyze and validate the proposed model, the random variables related to phytosanitary risk were taken and characterized. Subsequently, the frequency and severity random variables were modeled as linguistic random variables using fuzzy logic concepts. The results indicate that rainfall is the key variable to correlate in the search for an index insurance model based on agricultural risk, as well as in the characterization of qualitative and quantitative risks, promoting the improvement of financial and environmental sustainability by reducing agricultural losses through better crop management.