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Mintesinot, S.M
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Authors
Mintesinot, S.M
Santana, C.C
Queiroz, D
Pereira, M.H
Coelho, A.L
Santana, C.C
Mintesinot, S.M
Queiroz, D
Santos, F.S
Coelho, A.L
Topics
Remote and Proximal Sensing of Soils and Crops
Artificial Intelligence, Big Data, and Advanced Analytics in Agriculture
Type
Oral
Poster
Year
2026
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1. Hyperspectral Estimation of Corn Leaf Chlorophyll Index Using a Wavelet-Guided Spectral Index Optimization Framework

The corn leaf chlorophyll index (LCI) is a proxy indicator of plant photosynthetic capacity and nitrogen nutritional status, thereby supporting precision nutrient management and data-driven agronomic decision-making. Conventional methods, such as handheld chlorophyll meters, provide accurate leaf-level measurements but are labor-intensive, time-consuming, and inherently limited in their ability to represent field-scale spatial variability due to their point-based sampling nature. Hyperspectral... S.M. Mintesinot, C.C. Santana, D. Queiroz, M.H. Pereira, A.L. Coelho

2. Estimation of Leaf Chlorophyll Index in Corn Using Smartphone Images and Machine Learning

Accurate estimation of the Leaf Chlorophyll Index (LCI) in corn is fundamental for nitrogen management in precision agriculture, as nitrogen availability directly affects chlorophyll production and photosynthetic capacity. Conventional field assessment techniques are time-consuming and labor-intensive, while smartphone use provides a practical and low-cost alternative for obtaining high-resolution data in near-real-time. The objective of this study was to develop and validate a non-destructive... C.C. Santana, S.M. Mintesinot, D. Queiroz, F.S. Santos, A.L. Coelho