Raman Spectroscopy Enables Non-Invasive Identification of Peanut Genotypes and Value-Added Traits.

Abstract

Identification of specific genotypes can be accomplished by visual recognition of their distinct phenotypical appearance, as well as DNA analysis. Visual identification (ID) of species is subjective and usually requires substantial taxonomic expertise. Genotyping and sequencing are destructive, time- and labor-consuming. In this study, we investigate the potential use of Raman spectroscopy (RS) as a label-free, non-invasive and non-destructive analytical technique for the fast and accurate identification of peanut genotypes. We show that chemometric analysis of peanut leaflet spectra provides accurate identification of different varieties. This same analysis can be used for prediction of nematode resistance and oleic-linoleic oil (O/L) ratio. Raman-based analysis of seeds provides accurate genotype identification in 95% of samples. Additionally, we present data on the identification of carbohydrates, proteins, fiber and other nutrients obtained from spectroscopic signatures of peanut seeds. These results demonstrate that RS allows for fast, accurate and non-invasive screening and selection of plants which can be used for precision breeding.

Plant phenotyping relevance

ラマン分光とケモメトリクスを用いて、ピーナッツの遺伝型や線虫抵抗性、油脂比などの植物形質を非破壊推定する手法が研究の中心であり、育種選抜への応用も示している。

Code and data availability

The article describes Raman spectra of peanut leaves/seeds analyzed with PLS-DA/OPLS-DA in SIMCA, MATLAB, and PLS_Toolbox, but no public phenotype dataset, spectral data deposit, or author analysis code is mentioned. Raw spectra are only shown as figures in the supplementary information, and no repository, accession,或公

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