Aerial Identification of Fruit Maturity in Amazonian Palms via Plant-Canopy Modeling

Abstract

UAV-based multispectral imagery was used to characterize and associate the canopy features of the Moriche palm with the maturity state of its fruits, by correlating variations in the palm’s reflectance at different wavelengths throughout the phenological cycle. Several approaches for feature extraction were compared based on vegetation indices and graph-based models. A comprehensive dataset was collected and labeled, containing spatial–temporal variations in the features. Experimental results reported an accuracy of 72% in the estimation of the fruit maturity state, applying the proposed system to the dense forests of Colombia Amazonian region. Also, this UAV-based vision system enables monitoring, inventorying, palm identification, and fruit maturity identification, providing support to the local indigenous organizations of the Amazon.

Plant phenotyping relevance

UAVマルチスペクトル画像からヤシの果実成熟状態を推定する特徴抽出・モデル比較が中心であり、植物状態の定量的フェノタイピング手法に該当する。

Code and data availability

The supplied blocks describe a UAV multispectral dataset of Moriche palms (1758/1770 instances, two plots, 60 flights) and Mask R-CNN/ML models, but contain no public deposit, repository, or availability statement for the paper's imagery, labeled dataset, trained models, or analysis code. The only URLs are the article/

No evidence-backed public reproduction asset is currently recorded.