Yield Prediction in Soybean Crop Grown under Different Levels of Water Availability Using Reflectance Spectroscopy and Partial Least Squares Regression

Yield Prediction in Soybean Crop Grown under Different Levels of Water Availability Using Reflectance Spectroscopy and Partial Least Squares Regression

Soybean grain yield has regularly been impaired by drought periods, and the future climatic scenarios for soybean production might drastically impact yields worldwide. In this context, the knowledge of soybean yield is extremely important to subsidize government and corporative decisions over techni...

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Bibliographic Details
Main Authors: Luís Guilherme Teixeira Crusiol, Marcos Rafael Nanni, Renato Herrig Furlanetto, Rubson Natal Ribeiro Sibaldelli, Everson Cezar, Liang Sun, José Salvador Simonetto Foloni, Liliane Marcia Mertz-Henning, Alexandre Lima Nepomuceno, Norman Neumaier, José Renato Bouças Farias
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Remote Sensing
Subjects:
<i>Glycine max</i> (L.) Merrill
drought stress
soybean genotypes
leaf-based data
hyperspectral reflectance
Online Access:https://www.mdpi.com/2072-4292/13/5/977

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https://www.mdpi.com/2072-4292/13/5/977

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