文献类型： 外文期刊

第一作者： Cui Hao-fan

作者： Cui Hao-fan;Liu Hong-zhi;Guo Qin;Gu Feng-ying;Wang Qiang;Zhang Yu

作者机构：

关键词： Near-infrared spectroscopy; Peanuts; Protein components; Subunit content; Partial least squares method

期刊名称：SPECTROSCOPY AND SPECTRAL ANALYSIS （ 影响因子：0.7； 五年影响因子：0.6 ）

ISSN： 1000-0593

年卷期： 2024 年 44 卷 7 期

页码：

收录情况： SCI

摘要： Peanut is a high-quality plant protein resource. The content of peanut protein components and subunits significantly affects its functional characteristics and determines its application range in the food field. Peanut proteins mainly include arachin and arachin. Among them, arachin contains four subunits (40.5, 37.5, 35.5, 23.5 kDa), arachin I contains three subunits (15.5, 17, 18 kDa), and arachin II contains only one 61 kDa subunit. To realize the rapid, non-destructive, high-throughput and high-sensitivity detection of peanut protein's main components and subunits, 145 high-quality peanut samples in China were used as the research object. Firstly, the portable near-infrared peanut quality rapid tester was used to collect the spectra of different peanut samples in the wavelength range of 900 similar to 1 700 nm. Then, the peanut protein components and subunits were determined by polyacrylamide gel electrophoresis. The subunit content of arachin was between 44.3% and 67.3%. The content of arachin subunits was between 35.2% and 55.7%. The 61 kDa subunit content ranged from 13.5% to 25.3%. The content of 40.5 kDa subunit was between 6.8% and 16.0%. The content of 37.5 kDa subunit was between 6.9% and 17.4%. The content of 35.5 kDa subunit was between 5.7% and 19.2%. The 23.5 kDa subunit content was between 18.7% and 27.4%. The content of the 18 kDa subunit was between 5.9% and 11.7%. The content of the 17 kDa subunit was between 6.9% and 13.6%. The content of the 15.5 kDa subunit was 4.5%similar to 11.9%. The near-infrared spectral models of two protein components and two subunits (arachin, arachin, 37.5, 23.5 kDa) were optimized by comparing seven spectral pretreatment methods, including normalization, first derivative (FD) and second derivative (SD), baseline calibration, detrend, multiple scattering corrections (MSC) and data element resolution (Deresolve), combined with principal component analysis (PCA) and partial least squares (PLSR). The near-infrared spectroscopy models of six subunits (61, 40.5, 35.5, 18, 17, 15.5 kDa) were constructed, and the simultaneous detection of the above 10 indicators was realized. The results showed that the calibration set's correlation coefficient (Rcal) 0.90 similar to 0.96, and the corrected root mean square error (SEC) was 0.25%similar to 1.27%. The prediction set's correlation coefficient (Rcp) was 0.76 similar to 0.96, and the root mean square error of prediction (SEP) was 0.50%similar to 1.81%. It has good predictive ability and can be used for rapid detection of protein components and subunit content in peanut varieties, which provides a new method for fast evaluation of peanut protein quality.

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