Mung bean is a leguminous crop with specific trait in its diet, namely in the form of anti-nutrient components. The sprouting process is commonly done for better nutritional acceptance of mung bean as it presents better nutritional benefits. Sprouted mung bean serves as a cheap source of protein and ascorbic acid, which are dependent on the sprouting process, hence the importance of following the biological process. In larger production scale, there has not been a definite standard for mung bean sprouting, raising the need for quick and effective mung bean sprout quality checks. In this regard, near-infrared spectroscopy (NIRS) has been recognized as a highly sensitive technique for quality control that seems suitable for this study. The aim of this paper was to describe quality parameters (water content, pH, conductivity, and ascorbic acid by titration) during sprouting using conventional analytical methods and advanced NIRS techniques as correlative methods for modelling sprouted mung beans’ quality and ascorbic acid content. Mung beans were sprouted in 6 h intervals up to 120 h and analyzed using conventional methods and a NIR instrument. The results of the standard analytical methods were analyzed with univariate statistics (analysis of variance (ANOVA)), and the NIRS spectral data was assessed with the chemometrics approach (principal component analysis (PCA), discriminant analysis (DA), and partial least squares regression (PLSR)). Water content showed a monotonous increase during the 120 h of sprouting. The change in pH and conductivity did not describe a clear pattern during the sprouting, confirming the complexity of the biological process. Spectral data-based discriminant analysis was able to distinctly classify the bean sprouts with 100% prediction accuracy. A NIRS-based model for ascorbic acid determination was made using standard ascorbic acid to quantify the components in the bean extract. A rapid detection technique within sub-percent level was developed for mung bean ascorbic acid content with R² above 0.90. The NIR-based prediction offers reliable estimation of mung bean sprout quality

中文翻译：

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耳红外光谱法和水生物组学用于监测绿豆（Vigna radiata）新芽的生长和抗坏血酸含量的验证

绿豆是一种豆类作物，其饮食具有特定的特征，即以抗营养成分的形式存在。绿豆芽通常会发芽，以更好地吸收绿豆，因为它具有更好的营养价值。发芽的绿豆是廉价的蛋白质和抗坏血酸来源，它们依赖于发芽过程，因此遵循生物学过程非常重要。在较大的生产规模中，没有确定绿豆芽的明确标准，从而需要进行快速有效的绿豆芽质量检查。在这方面，近红外光谱（NIRS）已被认为是一种高度敏感的质量控制技术，似乎适合本研究。本文的目的是描述质量参数（水含量，pH，电导率，使用常规分析方法和先进的NIRS技术作为发芽绿豆质量和抗坏血酸含量的相关方法，可在发芽过程中使用滴定法和抗坏血酸滴定法）。绿豆以6小时的间隔发芽直至120小时，并使用常规方法和NIR仪器进行分析。使用单变量统计（方差分析（ANOVA））分析标准分析方法的结果，并使用化学计量学方法（主成分分析（PCA），判别分析（DA）和偏最小二乘法）评估NIRS光谱数据回归（PLSR））。在发芽的120小时内，水分含量单调增加。pH和电导率的变化在萌芽过程中没有描述出清晰的图案，这证实了生物过程的复杂性。基于光谱数据的判别分析能够以100％的预测准确度对豆芽进行分类。使用标准抗坏血酸建立了基于NIRS的抗坏血酸测定模型，以量化豆类提取物中的成分。开发了一种在R％以下水平的绿豆抗坏血酸含量快速检测技术²高于0.90。基于NIR的预测提供了可靠的绿豆芽品质评估