Digitalised phenotyping of pepper (Capsicum spp.) using effective RGB imaging and optimised camera positioning.

Abstract

Recent technological advancements employ imaging techniques to examine the morphological, physiological, and genetic differences among plant accessions, enhancing precision and productivity. High-throughput phenotyping serves as an essential method for selecting traits and reducing errors tied to manual data collection. However, the effects of camera-to-object distance in imaging acquisition for plant phenomics have received less attention. We analyzed the imaging parameters that define well the morphological characteristics of pepper and the effects of camera-to-object distance on the imaging of plant growth, leaf dimensions, fruit, and seed characteristics. Three camera-to-object distances (0.8, 1.0, and 1.2 m) were studied for the vegetative stage, and six camera-to-object distances (0.35-0.85 m) were used for the reproductive stages. The results demonstrated that imaging parameters such as Major (the longest line that can be drawn within the leaf) and Minor (the shortest line perpendicular to the major axis) are more effective for assessing canopy spread, while imaging Height provides a strong correlation (r = 0.9) for actual plant height measurement. An optimal camera-to-object distance of 0.8 m yielded better correlations for vegetative traits across all pepper genotypes, likely due to resolution factors at different growth stages. For fruit and seed traits, shorter distances of 0.55 m and 0.65 m were suitable. Additionally, the weights of fresh and dry fruit correlated highly with image area (r = 0.94 and 0.89, respectively, at 0.55 m). The studied pepper genotypes exhibited distinct seed characteristics, including variations in Roundness, Solidity, and Circularity. The imaging approach can accurately capture various plant characteristics and has the potential to replace traditional methods for assessing plants.

Plant phenotyping relevance

RGB画像による植物形質取得を中心に、カメラ距離と撮像パラメータを最適化・検証しており、方法開発および技術検証に該当する。

Code and data availability

The paper describes RGB imaging of pepper and an ImageJ macro 'created locally' plus R analysis, but no public deposit, availability statement, or authors' URL for images, phenotype data, or code is provided. The only URLs are generic (R, CRAN agricolae, a cited ImageJ plugin reference) and do not host this paper's own

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