Insights and protocols for discrimination of sugarcane clones by dissimilarity measures on RGB and NIR data.

Abstract

In sugarcane breeding, dense experiments have been considered in the initial phase (T1), such as the Simplified System (SS) of genotype selection. In this method, the seedlings of each family are transplanted directly from the seed box to the field, forming a kind of carpet. Despite the practical aspect of the method, selection problems are common, as stalks from the same individual within the family are subject to being taken to later evaluation stages, to the detriment of stalks from different individuals. To facilitate the discrimination of stalks of the same family in SS, we evaluated using RGB images (red:green:blue) and NIR (near infrared) spectra. We applied Euclidean distance (D) and Mahalanobis distance (D2) dissimilarity measures to the image and spectral data to distinguish stalks with different genotypes. RGB and NIR data were taken from type +1 leaf samples collected from two experimental blocks, totaling 31 evaluated families. The analyzes were carried out in two stages. In the first stage, we sought to evaluate the classification capacity using RGB images and NIR spectra, using D as a measure of dissimilarity. In the second step, we developed and validated a protocol using RGB images to classify clones, with D2 as a dissimilarity measure. Preliminary results, with distance D, allowed to discriminate clones based on the distance of the evaluated attributes and their combinations. In addition, with the analyzes using the D distance, it was identified that only the use of the R attribute (red band) would give satisfactory results for the second stage, which was the proposed analysis protocol, applying the D2 distance. The D2 statistic and associated p-value confirmed the protocol's usefulness in discriminating stalks in SS, especially stalks from the same families.

Plant phenotyping relevance

サトウキビのRGB画像・NIRデータからクローンを識別する解析手法を開発し、距離指標と分類プロトコルを検証しており、表現型取得・抽出手法が研究の中心である。

Code and data availability

The article describes RGB/NIR phenotyping of sugarcane leaves and an R-based analysis, but no public phenotype dataset, image collection, or author code repository is deposited or linked. The R script and custom functions are mentioned without availability language or URL; the acervodigital.ufpr.br link is a cited UFPR

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