Rapid Determination of β -Glucan Content of Hulled and Naked Oats Using near Infrared Spectroscopy Combined with Chemometrics.

Abstract

The quantification of β -glucan in oats is of immense importance for plant breeders and food scientists to develop plant varieties and food products with a high quantity of β -glucan. However, the chemical analysis of β -glucan is time consuming, destructive, and laborious. In this study, near-infrared (NIR) spectroscopy in conjunction with Chemometrics was employed for rapid and non-destructive prediction of β -glucan content in oats. The interval Partial Least Square (iPLS) along with correlation matrix plots were employed to analyze the NIR spectrum from 700-1300 nm, 1300-1900 nm, and 1900-2500 nm for the selection of important wavelengths for the prediction of β -glucan. The NIR spectral data were pre-treated using Savitzky Golay smoothening and normalization before employing partial least square regression (PLSR) analysis. The PLSR models were established based on the selection of wavelengths from PLS loading plots that present a high correlation with β -glucan content. It was observed that wavelength region 700-1300 nm is sufficient for the satisfactory prediction of β -glucan of hulled and naked oats with R 2 c of 0.789 and 0.677, respectively, and RMSE < 0.229.

Plant phenotyping relevance

オーツ種子のβ-グルカン含量をNIR分光とケモメトリクスで非破壊推定する手法の開発・検証が研究の中心であり、植物形質の測定法に該当する。

Code and data availability

The paper's β-glucan reference data and NIR spectral data are not publicly deposited; the Data Availability Statement states they are available only upon request. No author code, models, or public dataset URLs are provided.

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