An Open-Source Package for Thermal and Multispectral Image Analysis for Plants in Glasshouse.

Abstract

Advanced plant phenotyping techniques to measure biophysical traits of crops are helping to deliver improved crop varieties faster. Phenotyping of plants using different sensors for image acquisition and its analysis with novel computational algorithms are increasingly being adapted to measure plant traits. Thermal and multispectral imagery provides novel opportunities to reliably phenotype crop genotypes tested for biotic and abiotic stresses under glasshouse conditions. However, optimization for image acquisition, pre-processing, and analysis is required to correct for optical distortion, image co-registration, radiometric rescaling, and illumination correction. This study provides a computational pipeline that optimizes these issues and synchronizes image acquisition from thermal and multispectral sensors. The image processing pipeline provides a processed stacked image comprising RGB, green, red, NIR, red edge, and thermal, containing only the pixels present in the object of interest, e.g., plant canopy. These multimodal outputs in thermal and multispectral imageries of the plants can be compared and analysed mutually to provide complementary insights and develop vegetative indices effectively. This study offers digital platform and analytics to monitor early symptoms of biotic and abiotic stresses and to screen a large number of genotypes for improved growth and productivity. The pipeline is packaged as open source and is hosted online so that it can be utilized by researchers working with similar sensors for crop phenotyping.

Plant phenotyping relevance

植物の熱画像・マルチスペクトル画像を用いた表現型取得と解析のためのオープンソース計算パイプラインを開発しており、画像補正・共登録・解析が中心的な方法論的貢献である。

Code and data availability

保存済みの本文根拠を更新済みルールで再検証し、公開資産2件を確認しました。