Mapping climate suitability index for rainfed cultivation of medicinal plants by developing an AI-based probabilistic framework
Year: 2024
Type: article
Abstract: The Climate Suitability Index (CSI) can increase agricultural efficiency by identifying the high-potential areas for cultivation from the climate perspective. The present study develops a probabilistic framework to calculate CSI for rainfed cultivation of 12 medicinal plants from the climate perspective of precipitation and temperature. Unlike the ongoing frameworks based on expert judgments, this formulation decreases the inherent subjectivity by using two components: frequency analysis and Particle Swarm Optimization (PSO). In the first component, the precipitation and temperature layers were prepared by calculating the occurrence probability for each plant, and the obtained probabilities were spatially interpolated using geographical information system processes. In the second component, PSO quantifies CSI by classifying a study area into clusters using an unsupervised clustering technique. The formulation was implemented in the Lake Urmia basin, which was distressed by unsustainable water resources management. By identifying clusters with higher CSI values for each plant, the results provide deeper insights to optimize cultivation patterns in the basin. These insights can help managers and farmers increase yields, reduce costs, and improve profitability.
Source: Scientific Reports
Authors: Sina Sadeghfam, Mohammad Sina Rahmani, Marjan Moazamnia, Mohammad Reza Morshedloo
Institutions: University of Maragheh, University of Bonab
Language: English
Subfield: Management, Monitoring, Policy and Law
Field: Environmental Science
Domain: Physical Sciences
SDGs: Zero hunger, Climate action
Open Access status: gold
Estimated APC paid: $2,590
OpenAlex ID: W4402122236