DeFENS Department of Food, Environmental and Nutritional Sciences, Università degli Studi di Milano, Milano, Italy.
Department of Fundamental Chemistry, Federal University of Pernambuco, Recife (PE), Brazil.
Talanta. 2017 Apr 1;165:112-116. doi: 10.1016/j.talanta.2016.12.035. Epub 2016 Dec 21.
The main goal of this study was to investigate the analytical performances of a state-of-the-art device, one of the smallest dispersion NIR spectrometers on the market (MicroNIR 1700), making a critical comparison with a benchtop FT-NIR spectrometer in the evaluation of the prediction accuracy. In particular, the aim of this study was to estimate in a non-destructive manner, titratable acidity and ascorbic acid content in acerola fruit during ripening, in a view of direct applicability in field of this new miniaturised handheld device. Acerola (Malpighia emarginata DC.) is a super-fruit characterised by a considerable amount of ascorbic acid, ranging from 1.0% to 4.5%. However, during ripening, acerola colour changes and the fruit may lose as much as half of its ascorbic acid content. Because the variability of chemical parameters followed a non-strictly linear profile, two different regression algorithms were compared: PLS and SVM. Regression models obtained with Micro-NIR spectra give better results using SVM algorithm, for both ascorbic acid and titratable acidity estimation. FT-NIR data give comparable results using both SVM and PLS algorithms, with lower errors for SVM regression. The prediction ability of the two instruments was statistically compared using the Passing-Bablok regression algorithm; the outcomes are critically discussed together with the regression models, showing the suitability of the portable Micro-NIR for in field monitoring of chemical parameters of interest in acerola fruits.
本研究的主要目的是研究一种最先进的设备（市场上最小的色散近红外光谱仪之一）的分析性能，并与台式 FT-NIR 光谱仪进行关键比较，以评估预测精度。特别是，本研究旨在以非破坏性方式估计樱桃番茄果实在成熟过程中的可滴定酸度和抗坏血酸含量，以期直接适用于这种新型小型手持式设备的领域。樱桃番茄（Malpighia emarginata DC.）是一种超级水果，其抗坏血酸含量相当高，范围从 1.0%到 4.5%。然而，在成熟过程中，樱桃番茄的颜色会发生变化，果实的抗坏血酸含量可能会损失一半。由于化学参数的变化遵循非严格线性的规律，因此比较了两种不同的回归算法：PLS 和 SVM。使用 SVM 算法，从近红外光谱获得的回归模型对两种物质（抗坏血酸和可滴定酸度）的估计效果更好。使用 FT-NIR 数据，使用 SVM 和 PLS 算法都可以得到可比的结果，而 SVM 回归的误差更小。使用 Passing-Bablok 回归算法对两种仪器的预测能力进行了统计学比较；结果与回归模型一起进行了批判性讨论，表明便携式 Micro-NIR 非常适合在田间监测樱桃番茄果实中感兴趣的化学参数。
