Development and validation of climatic hazard indicators for roselle (Hibiscus sabdariffa L.) crop in dryland agriculture

Abstract

Two of the major challenges in achieving food security in the future are: (1) the increase in demand for food due to constant high population growth and (2) the increase in adverse climatic conditions, due to global climate change, that will affect crops. Currently, no universal indicators are available to identify the effect of extreme climate events on specific crops of nutritional and commercial importance, as they need to be developed according to each species’ physiology. Likewise, it is necessary to develop production qualifiers that allow us to identify whether the agricultural year presents high or low climatic hazards for a specific crop. In this study of roselle (Hibiscus sabdariffa L.) grown in dryland agricultural conditions in the Bajo Balsas, Michoacán, Mexico, we aimed to 1) generate and validate climatic hazard indicators and 2) propose an equation to calculate annual climatic hazards, considering the different phenological crop stages.We present both phenological and climatic information that is used for the development of 13 agroclimatic hazard indicators that have been proposed for the roselle crop in La Huacana a municipality in Michoacán. Artificial intelligence and neural networks were used for both weight variable identification in the equation and to validate the annual classification, which is derived from the proposed equation. Our proposed equation for the quick assessment of agroclimatic hazards for the roselle crop is a new tool that helps in planning and decision-making in the face of the growing presence of extreme climate events.

Keywords

• Meteorological conditions
• Extreme events
• Climate change adaptation
• Field crops
• Artificial intelligence
• Climatic hazard equation