CCB-Center for Chemistry and Biomedicine, Institute of Analytical Chemistry and Radiochemistry, University of Innsbruck, Innrain 80/82, 6020 Innsbruck, Austria.
Chemical devision, HBLFA für Landwirtschaft und Ernährung, Lebensmittel und Biotechnologie Tirol,Rotholz 50a, 6200 Strass im Zillertal, Austria.
Molecules. 2019 Jan 24;24(3):428. doi: 10.3390/molecules24030428.
The performance of a newly developed pocket-sized near-infrared (NIR) spectrometer was investigated by analysing 46 cheese samples for their water and fat content, and comparing results with a benchtop NIR device. Additionally, the automated data analysis of the pocket-sized spectrometer and its cloud-based data analysis software, designed for laypeople, was put to the test by comparing performances to a highly sophisticated multivariate data analysis software. All developed partial least squares regression (PLS-R) models yield a coefficient of determination (R²) of over 0.9, indicating high correlation between spectra and reference data for both spectrometers and all data analysis routes taken. In general, the analysis of grated cheese yields better results than whole pieces of cheese. Additionally, the ratios of performance to deviation (RPDs) and standard errors of prediction (SEPs) suggest that the performance of the pocket-sized spectrometer is comparable to the benchtop device. Small improvements are observable, when using sophisticated data analysis software, instead of automated tools.
研究了新开发的袖珍近红外(NIR)光谱仪的性能,通过分析 46 个奶酪样品的水分和脂肪含量,并将结果与台式 NIR 设备进行比较。此外,还通过将袖珍光谱仪的自动数据分析及其专为非专业人士设计的基于云的数据分析软件与高度复杂的多元数据分析软件的性能进行比较,对其进行了测试。所有开发的偏最小二乘回归(PLS-R)模型的确定系数(R²)均超过 0.9,表明两种光谱仪和所有采用的数据分析方法的光谱与参考数据之间具有高度相关性。总体而言,对磨碎奶酪的分析比整块奶酪的分析结果更好。此外,性能与偏差比(RPD)和预测标准误差(SEP)表明,袖珍光谱仪的性能可与台式设备相媲美。使用复杂的数据分析软件而不是自动化工具时,可以观察到一些小的改进。