Use of near-infrared spectroscopy for screening the oil content, protein, phytic acid, glucosinolates, and fatty acid profile in oilseed Brassica species.

Abstract

The escalating global demand for vegetable oils underscores the need to enhance the quality and yield of oilseed crops with Brassica species, due to their rich oil content and nutritional benefits. Traditional methods for assessing seed quality traits are often slow and destructive, limiting their scalability in breeding programs. This study presents Fourier transform near-infrared (FT-NIR) spectroscopy as a rapid, non-destructive alternative to evaluate these critical traits across 80 diverse Brassica genotypes, including three species, namely, Brassica juncea, Brassica napus , and Brassica rapa . By integrating FT-NIR with principal component analysis and partial least squares regression, we developed robust calibration models, achieving high predictive accuracy (R 2 > 0.85 for key fatty acids; R 2 = 0.92 for oil content) and low error rates (MAE Brassica cultivars with optimized nutritional profiles high in beneficial polyunsaturated fatty acids and low in anti-nutritional factors.

Plant phenotyping relevance

FT-NIR分光法を用いてBrassica種子の品質・組成形質を非破壊推定し、校正モデルの精度を評価することが研究の中心であるため、植物フェノタイピング手法に該当する。

Code and data availability

The article describes FT-NIR calibration models for Brassica seed quality traits, but the supplied blocks contain no public phenotype dataset, spectra, code, or model deposit. No data availability statement with an authors' public URL is present; the supplementary material link is generic and its contents are not shown

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