Proceedings
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| Filter results5 paper(s) found. |
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1. Economic Assessment of Soil Sampling Densities for Variable-Rate Fertilizer PrescriptionSoil sampling and laboratory analysis represent a substantial share of operational costs in precision agriculture, making sampling density a crucial management parameter. Sampling density defines the resolution at which soil spatial variability is captured and directly influences the accuracy of spatial interpolation and fertilizer prescription maps. Due to high operational costs, reduced sampling densities are commonly adopted in practice, despite their known effects on map quality. This study... L. Delgado Bejarano, B. , A. Novaes Da Silva, L.R. Amaral |
2. Sensor-based Variable Rate Nitrogen Recommendations: Comparing Proximal, Drone, and Satellite Sensors in CornNitrogen (N) represents 20–25% of corn (Zea mays L.) production costs, yet 15–65% is lost through volatilization and leaching. Conventional uniform-rate application ignores spatial variability and seasonal demand. Sensor-based variable rate nitrogen (VRN) addresses this by using real-time reflectance data, but the influence of sensing platform proximal, drone, or satellite on economic outcomes under varying N stress remains under-researched. The objective of this study at Iron Horse,... A. Jakhar, L. Bastos, A. Bhattarai, K. Poudel, A. Dhaliwal |
3. A Canopy-based Decision Framework for Selecting Sensor Platform and Vegetation Index in Variable-rate Nitrogen Management of Irrigated CornSensor-based variable-rate nitrogen (VRN) management promises field-specific N optimization, yet the choice of sensing platform fundamentally alters N recommendations. At early growth stages, a "double penalty" emerges: nitrogen-deficient plants produce smaller canopies, exposing more bare soil, which deflates vegetation index (VI) values and inflates N recommendations where accuracy matters most. This study developed a canopy coverage-based decision framework for selecting optimal sensor... A. Jakhar, L. Bastos, R. Roth, S. Virk, A. Bhattarai, K. Poudel, A. Dhaliwal |
4. Predicting Yield Stability Classes Using Satellite Imagery in the Absence of Yield Monitor DataSite-specific management is essential for improving agricultural productivity while reducing input costs and minimizing environmental impacts. Although yield monitor data are commonly used to characterize within-field yield variability, their availability is often limited by technological and economic constraints. The primary objective of this study was to compare spatial–temporal stability classes derived from yield monitor data and satellite imagery in cotton production... K. Poudel, A. Bhattarai, A. Jakhar, L. Bastos, A. Dhaliwal |
5. Evaluation of the DeepLab Family of Architectures in Segmentation Internal Brachiaria Seed Structures by X-ray ImagesSeed vigor is an essential factor for the uniform emergence of seedlings and for the proper establishment of crops, being directly associated with the productive potential of agricultural crops. Accurate evaluation of this vigor is therefore fundamental for decision-making in seed management and production. Among the methods used for the analysis of physiological quality, the use of X-ray images stands out for allowing the non-destructive visualization of internal morphological structures of seeds,... L.K. Gomes Maia, E. Freitas, W.V. Dias, J.F. Da Silva , B.D. Silva , H.F. Abud, D. G. Gomes, P. Dos Santos E Silva |