Optimizing Sericea Lespedeza Fodder Production in the Southeastern US: A Climate-Informed Geospatial Engineering Approach

Sudhanshu S. Panda, Thomas H. Terrill, Ajit K. Mahapatra, Eric R. Morgan, Aftab Siddique (), Andres A. Pech-Cervantes and Jan A. van Wyk
Additional contact information
Sudhanshu S. Panda: Institute for Environmental Spatial Analysis, University of North Georgia, 3820 Mundy Mill Road, Oakwood, GA 30566, USA
Thomas H. Terrill: Department of Agricultural Sciences, Fort Valley State University, 1005 State University Drive, Fort Valley, GA 31030, USA
Ajit K. Mahapatra: Department of Agricultural Sciences, Fort Valley State University, 1005 State University Drive, Fort Valley, GA 31030, USA
Eric R. Morgan: Institute for Global Food Security, Queen’s University, University Road, Belfast BT7 1NN, UK
Aftab Siddique: Department of Agricultural Sciences, Fort Valley State University, 1005 State University Drive, Fort Valley, GA 31030, USA
Andres A. Pech-Cervantes: Department of Agricultural Sciences, Fort Valley State University, 1005 State University Drive, Fort Valley, GA 31030, USA
Jan A. van Wyk: Department of Veterinary Tropical Diseases, Faculty of Veterinary Science, University of Pretoria, Private Bag X04, Onderstepoort 0110, South Africa

Agriculture, 2023, vol. 13, issue 9, 1-15

Abstract: Lack of attention to rural healthcare for livestock in the southeastern United States has led to a focus on small ruminant farming, mainly using sericea lespedeza [SL; Lespedeza cuneata (Dum-Cours) G. Don], a drought-resistant forage species with nutraceutical benefits. Climate change has increased land availability for SL cultivation, further expanding the potential of this bioactive (anti-parasitic) legume. This study aims to create a geospatial engineering and technology-assisted model for identifying suitable SL production areas for supporting profitable small ruminant farming. The cultivation of SL depends on specific weather conditions and soil properties, with minimum requirements for temperature and rainfall, non-clay soil with reduced bulk density, and open land cover. The main objective was to develop an automated geospatial model using ArcGIS Pro ModelBuilder to assess SL production suitability. This model also aimed to identify appropriate locations for small ruminant production in Georgia in the southeastern United States, characterized by increasing temperature fluctuations. A web-based geographic information system (webGIS) platform was developed using the ArcGIS Online dashboard interface, allowing agriculturalists to access decision support for SL production suitability tailored to their land. This forage production suitability analysis, conducted in the context of climate change, offers valuable guidance for pasture managers in other nations with similar environmental attributes, promoting global adaptability and resilience.

Keywords: bioactive forage; ArcGIS Pro ModelBuilder; production suitability model; climate change (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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