Robustness of the RGB image-based estimation for rice above-ground biomass by utilizing the dataset collected across multiple locations

Above-ground biomass (AGB) is a critical phenotype representing crop growth. Non-invasive evaluations of AGB, including deep-learning-based red-green-blue (RGB) image analyses, are often specific to the training data. The robustness of the estimation model across untrained conditions is essential to...

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Bibliographic Details

Main Authors:	Nakajima, Kota, Saito, Kazuki, Tsujimoto, Yasuhiro, Takai, Toshiyuki, Mochizuki, Atsushi, Yamaguchi, Tomoaki, Ibrahim, Ali, Mairoua, Salifou Goube, Andrianary, Bruce Haja, Katsura, Keisuke, Tanaka, Yu
Format:	Journal Article
Language:	Inglés
Published:	Elsevier 2025
Subjects:	above ground biomass crop growth crop monitoring data collection field experiments transplanting machine learning remote sensing
Online Access:	https://hdl.handle.net/10568/175950