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利用可见/近红外反射光谱法测定毛豆(L. ssp.)的质量参数。

Determination of Quality Parameters in Mangetout ( L. ssp. ) by Using Vis/Near-Infrared Reflectance Spectroscopy.

机构信息

Department of Agro-Food Engineering and Technology, IFAPA Centro La Mojonera, CAGPDS, 04745 Almería, Spain.

ETSIIT, Campus Aynadamar, University of Granada, 18071 Granada, Spain.

出版信息

Sensors (Basel). 2022 May 28;22(11):4113. doi: 10.3390/s22114113.

Abstract

L. ssp. , is colloquially called or mangetout because it is eaten whole; its pods are recognized as a delicatessen in cooking due to its crunch on the palate and high sweetness. Furthermore, this legume is an important source of protein and antioxidant compounds. Quality control in this species requires the analysis of a large number of samples using costly and laborious conventional methods. For this reason, a non-chemical and rapid technique as near-infrared reflectance spectroscopy (NIRS) was explored to determine its physicochemical quality (color, firmness, total soluble solids, pH, total polyphenols, ascorbic acid and protein content). Pod samples from different cultivars and grown under different fertigation treatments were added to the NIRS analysis to increase spectral and chemical variability in the calibration set. Modified partial least squares regression was used for obtaining the calibration models of these parameters. The coefficients of determination in the external validation ranged from 0.50 to 0.88. The RPD (standard deviation to standard error of prediction ratio) and RER (standard deviation to range) were variable for quality parameters and showed values that were characteristic of equations suitable for quantitative prediction and screening purposes, except for the total soluble solid calibration model.

摘要

L. ssp. ,俗称“毛豆”或“枝豆”,因其可整颗食用;因其口感清脆、甜度高,其豆荚在烹饪中被视为美味佳肴。此外,这种豆类是蛋白质和抗氧化化合物的重要来源。该物种的质量控制需要使用昂贵且繁琐的传统方法分析大量样本。出于这个原因,人们探索了一种非化学的快速技术——近红外反射光谱(NIRS),以确定其物理化学特性(颜色、硬度、总可溶性固体、pH 值、总多酚、抗坏血酸和蛋白质含量)。来自不同品种的豆荚样本和在不同施肥处理下种植的豆荚样本被添加到 NIRS 分析中,以增加校准集中的光谱和化学变异性。使用修正的偏最小二乘回归来获得这些参数的校准模型。外部验证中的决定系数在 0.50 到 0.88 之间。RPD(预测标准差与预测误差标准差之比)和 RER(标准差与范围之比)因质量参数而异,表现出适合定量预测和筛选目的的方程的特征,除了总可溶性固体校准模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4445/9185268/00bc745aeb14/sensors-22-04113-g001.jpg

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