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

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作者
Charles Farber
Lee Sanchez
Stanislav Rizevsky
Alexei Ermolenkov
Bill McCutchen
John Cason
Charles Simpson
Mark Burow
Dmitry Kurouski
机构
[1] Department of Biochemistry and Biophysics,
[2] Texas A&M University,undefined
[3] Department of Biotechnology,undefined
[4] Binh Duong University,undefined
[5] Texas A&M AgriLife Research,undefined
[6] Texas A&M AgriLife Research,undefined
[7] The Institute for Quantum Science and Engineering,undefined
[8] Texas A&M University,undefined
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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.
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