Decision support system for Lespedeza cuneata production and quality evaluation: a WebGIS dashboard approach to precision agriculture - Panda, Sudhanshu S.; Siddique, Aftab; Terrill, Thomas H.; Mahapatra, Ajit K.; Morgan, Eric; Pech-Cervantes, Andres A.; van Wyk, Jan A. (Frontiers in Plant Science, 2025)
Small-scale farmers in the southeastern United States face increasing challenges in sustaining forage production due to erratic rainfall, poor soils, and limited access to precision agricultural tools. These constraints demand site-specific solutions that integrate climate resilience with sustainable land use. This study introduces a pioneering Site-Specific Fodder Management Decision Support System (SSFM-DSS) designed to optimize the cultivation of Lespedeza cuneata (sericea lespedeza), a drought-tolerant, nitrogen-fixing legume well-suited for marginal lands. By integrating high-resolution geospatial technologies—Geographic Information Systems (GIS), Global Navigation Satellite Systems (GNSS), and remote sensing—with empirical field data and predictive modeling, we have developed an automated suitability framework for SL cultivation across Alabama, Georgia, and South Carolina. The model incorporates multi-criteria environmental parameters, including soil characteristics, topography, and climate variability, to generate spatially explicit recommendations. To translate these insights into actionable strategies, we also developed a farmer-focused WebGIS Dashboard that delivers real-time, location-based guidance for SL production. Our findings underscore the significant potential of SSFM-DSS to enhance fodder availability, improve system resilience under climate stress, and promote sustainable livestock production. This integrative approach offers a promising pathway for climate-smart agriculture, supporting broader food security objectives in vulnerable agroecosystems.