Version 1
: Received: 7 March 2024 / Approved: 8 March 2024 / Online: 8 March 2024 (10:04:43 CET)
How to cite:
Panda, S.; Siddique, A.; Terrill, T.H.; Mahapatra, A.K.; Morgan, E.R.; PechCervantes, A.; Van Wyk, J.A. Decision Support System for Lespedeza Cuneata Production and Quality Evaluation: A WebGIS Dashboard Approach to Precision Agriculture. Preprints2024, 2024030512. https://doi.org/10.20944/preprints202403.0512.v1
Panda, S.; Siddique, A.; Terrill, T.H.; Mahapatra, A.K.; Morgan, E.R.; PechCervantes, A.; Van Wyk, J.A. Decision Support System for Lespedeza Cuneata Production and Quality Evaluation: A WebGIS Dashboard Approach to Precision Agriculture. Preprints 2024, 2024030512. https://doi.org/10.20944/preprints202403.0512.v1
Panda, S.; Siddique, A.; Terrill, T.H.; Mahapatra, A.K.; Morgan, E.R.; PechCervantes, A.; Van Wyk, J.A. Decision Support System for Lespedeza Cuneata Production and Quality Evaluation: A WebGIS Dashboard Approach to Precision Agriculture. Preprints2024, 2024030512. https://doi.org/10.20944/preprints202403.0512.v1
APA Style
Panda, S., Siddique, A., Terrill, T.H., Mahapatra, A.K., Morgan, E.R., PechCervantes, A., & Van Wyk, J.A. (2024). Decision Support System for Lespedeza Cuneata Production and Quality Evaluation: A WebGIS Dashboard Approach to Precision Agriculture. Preprints. https://doi.org/10.20944/preprints202403.0512.v1
Chicago/Turabian Style
Panda, S., Andres PechCervantes and Jan A. Van Wyk. 2024 "Decision Support System for Lespedeza Cuneata Production and Quality Evaluation: A WebGIS Dashboard Approach to Precision Agriculture" Preprints. https://doi.org/10.20944/preprints202403.0512.v1
Abstract
This study examines the capacity of a Site-Specific Fodder Management Decision Support System (SSFM-DSS) model to assist in successful cultivation of sericea lespedeza [SL; Lespedeza cuneata (Dum.-Cours.) G. Don.], with a specific focus on small-scale agricultural systems in the southeastern United States (U.S.). The study emphasizes incorporating advanced geospatial technologies, such as Geographic Information Systems (GIS), remote sensing, and Global Navigation Satellite Systems (GNSS), to improve fodder production. The research showcases the versatility of SL under varying environmental conditions, underscoring its significance in promoting sustainable livestock production. The methodology integrates empirical field data, geospatial analysis, and predictive modeling to formulate an SSFM strategy customized to address the distinct difficulties climate change presents, such as sudden and severe drought conditions. The study introduces an automated geospatial model for assessing the appropriateness of SL production throughout Alabama, Georgia, and South Carolina. The model uses many environmental criteria, including soil properties, climate fluctuations, and terrain. Furthermore, the research was instrumental in development of a WebGIS Dashboard, which offers farmers a decision assistance system to enhance the sustainable production of SL. The results highlight the significant impact that a SSFM-DSS can have on promoting sustainable agricultural practices, providing a solution to address the issues of food security and environmental concerns in agriculture.
Keywords
Site-specific Fodder Management; Sericea Lespedeza; Geographic Information Systems; Remote Sensing
Subject
Biology and Life Sciences, Agricultural Science and Agronomy
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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