Prediction of Biometric Variables Through Multispectral Images Obtained From Uav in Beans ( Phaseolus vulgaris L. ) During Ripening Stage

Abstract

Here, we report the prediction of vegetative stages variables of canary bean crop by means of RGB and multispectral images obtained from UAV during the ripening stage, correlating the vegetation indices with biometric variables measured manually in the field. Results indicated a highly significant correlation of plant height with eight RGB image vegetation indices for the canary bean crop, which were used for predictive models, obtaining a maximum correlation of R2 = 0.79. On the other hand, the estimated indices of multispectral images did not show significant correlations.

Plant phenotyping relevance

UAVのRGB・マルチスペクトル画像からインゲンの植物高などの生育形質を予測する手法が研究の中心であり、画像ベースの形質推定に該当する。

Code and data availability

The supplied blocks describe UAV RGB/multispectral image acquisition and field biometric measurements for canary bean phenotyping, but contain no public phenotype dataset, image deposit, author code repository, or data availability statement. All URLs in the text are references to prior work or generic software (R/RStu

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