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Marginal Agricultural Land Identification In The Lower Mississippi Alluvial Valley, Prakash Tiwari
Marginal Agricultural Land Identification In The Lower Mississippi Alluvial Valley, Prakash Tiwari
Theses and Dissertations
This study identified marginal agricultural lands in the Lower Mississippi Alluvial Valley using crop yield predicting models. The Random Forest Regression (RFR) and Multiple Linear Regression (MLR) models were trained and validated using county-level crop yield data, climate data, soil properties, and Normalized Difference Vegetation Index (NDVI). The RFR model outperformed MLR model in estimating soybean and corn yields, with an index of agreement (d) of 0.98 and 0.96, Nash-Sutcliffe model efficiency (NSE) of 0.88 and 0.93, and root mean square error (RMSE) of 9.34% and 5.84%, respectively. Marginal agricultural lands were estimated to 26,366 hectares using cost and sales …
Sustainable Sidedress Nitrogen Applications For Early Corn And Cotton Crops Using Small Unmanned Aerial Systems, James Nolan Parker
Sustainable Sidedress Nitrogen Applications For Early Corn And Cotton Crops Using Small Unmanned Aerial Systems, James Nolan Parker
Theses and Dissertations
Nitrogen run-off from agriculture have been linked to human health problems on a global level. Large-scale conventional producers struggle to redefine themselves as sustainable because reducing nitrogen (N) inputs without justification or validation may lead to severe profit losses. Small unmanned aerial systems (sUAS) sensing may allow for decreased N runoff. Failure to address this problem will exacerbate already excessive N runoff into the Mississippi River and beyond. The purpose of this study was to reduce fertilizer N input using sUAS technology to assess crop canopy needs. In 2020 and 2021, variable rate nitrogen (VRN) side-dress N application maps were …