Preprint Communication Version 1 Preserved in Portico This version is not peer-reviewed

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

Version 1 : Received: 3 June 2021 / Approved: 4 June 2021 / Online: 4 June 2021 (11:25:04 CEST)

How to cite: Quille-Mamani, J.; Porras-Jorge, R.; Saravia-Navarro, D.; Herrera, J.; Chavez-Galarza, J.; Arbizu, C.I. Prediction of Biometric Variables Through Multispectral Images Obtained From Uav in Beans (Phaseolus vulgaris L.) During Ripening Stage. Preprints 2021, 2021060139 (doi: 10.20944/preprints202106.0139.v1). Quille-Mamani, J.; Porras-Jorge, R.; Saravia-Navarro, D.; Herrera, J.; Chavez-Galarza, J.; Arbizu, C.I. Prediction of Biometric Variables Through Multispectral Images Obtained From Uav in Beans (Phaseolus vulgaris L.) During Ripening Stage. Preprints 2021, 2021060139 (doi: 10.20944/preprints202106.0139.v1).

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.

Subject Areas

Vegetation indices; precision agriculture; RGB images

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