Speakers: Jasmine Neupane, PhD

Jasmine Neupane, PhD

Assistant Professor of Agricultural Systems Technology
Division of Plant Science and Technology
University of Missouri

 

Dr. Jasmine Neupane is an Assistant Professor of Agricultural Systems Technology in the Division of Plant Science and Technology. She received her PhD from Texas Tech University where she worked with producers in the region to explore challenges around water management in semi-arid production systems. Before starting her position at University of Missouri-Columbia, Neupane was serving as an Assistant Research Professor of Precision Agriculture at Montana State University. Dr. Neupane’s research is at the forefront of agricultural innovation, focusing on seamless integration of advanced agricultural technologies into cropping systems. Her work is driven by a deep commitment to addressing the complex challenges facing modern agriculture, such as increasing food production to feed a growing population while minimizing environmental impact. Her research explores the application of digital agriculture technologies, including sensors, IoT devices, and advanced geospatial data analytics in different elements of crop production with the goal of improving production profitability and sustainability of agroecosystems.

 

Data-Driven Precision Water Management in High-Value Agricultural Systems

Increasing climate variability, pronounced within-field heterogeneity in soil and topography, and limited water resources underscore the need for precise and sustainable agricultural water management. While sensors and data analytics offer significant potential for precision irrigation, especially in high-value specialty crops, adoption remains limited due to the challenges of integrating diverse digital tools into practical management strategies. To address these challenges, we conducted a study in grape and blueberry systems, implementing irrigation guided by a field-based IoT sensing network and validating it with UAS-based remote sensing to manage within-field variability and optimize water use under variable conditions. We further examined the potential for water conservation and the feasibility of adoption among regional producers. By combining sensor integration, data analytics, and field-scale validation, this study aims to advance precision water management strategies that enhance productivity, resource efficiency, and resiliency of our crop production systems.