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Estimating Yield-Related Traits Using UAV-Derived Multispectral Images to Improve Rice Grain Yield Prediction

Rice grain yield prediction with UAV-driven multispectral images are re-emerging interests in precision agriculture, and an optimal sensing time is an important factor. The aims of this study were to (1) predict rice grain yield by using the estimated aboveground biomass (AGB) and leaf area index (L...

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Principais autores: Maria Victoria Bascon, Tomohiro Nakata, Satoshi Shibata, Itsuki Takata, Nanami Kobayashi, Yusuke Kato, Shun Inoue, Kazuyuki Doi, Jun Murase, Shunsaku Nishiuchi
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2022-08-01
Serier:Agriculture
Fag:
multispectral
rice yield prediction
remote sensing
Online adgang:https://www.mdpi.com/2077-0472/12/8/1141
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