Altieri Giuseppe, Genovese Francesco, Tauriello Antonella, Di Renzo Giovanni Carlo
SAFE - Scuola di Scienze Agrarie, Forestali, Alimentari ed Ambientali, Università degli Studi della Basilicata, Potenza, Italy.
J Sci Food Agric. 2017 Dec;97(15):5302-5310. doi: 10.1002/jsfa.8416. Epub 2017 Jun 13.
Visible-near-infrared spectrometry is a technique suitable for assessing chemical and physiological properties of fruit. Some models of calibration/prediction have been tested in order to assess the feasibility of a visible-near-infrared sensor in order to monitor persimmon fruit colour, firmness, soluble solids, titratable acidity and soluble tannins.
Five regression models were investigated: principal component, partial least squares, stepwise, support vector machines and ensembles of trees. These models were assessed by a 10-fold cross-validation with a new strategy for both outlier removal and wavelength reduction; furthermore, their statistical significance was evaluated by 100 Monte Carlo simulation runs. Principal component regression allowed us to build excellent and/or very good fit/prediction models. The results (in terms of RPD as standard deviation to performance standard error ratio) are: 9.23 (±0.26) for colour index, 10.18 (±0.37) for firmness, 7.15 (±0.28) for soluble solids content, 7.87 (±0.31) for titratable acidity and 8.91 (±0.33) for soluble tannins content.
The proposed strategy, for outlier removal and wavelength reduction, allowed the achievement of useful results. Principal component regression fit/prediction capability produced excellent results. Conversely, partial least squares regression showed fair/poor results and the remaining tested models performed badly on real data. © 2017 Society of Chemical Industry.
可见-近红外光谱法是一种适用于评估水果化学和生理特性的技术。为了评估可见-近红外传感器监测柿子果实颜色、硬度、可溶性固形物、可滴定酸度和可溶性单宁的可行性，已经测试了一些校准/预测模型。
研究了五种回归模型：主成分回归、偏最小二乘法回归、逐步回归、支持向量机和随机森林。通过10折交叉验证对这些模型进行评估，采用了一种新的异常值去除和波长缩减策略；此外，通过100次蒙特卡洛模拟运行评估了它们的统计显著性。主成分回归使我们能够建立出色和/或非常好的拟合/预测模型。结果（以RPD作为标准偏差与性能标准误差之比表示）如下：颜色为9.23（±0.26），硬度为10.18（±0.37），可溶性固形物含量为7.15（±0.28），可滴定酸度为7.87（±0.31），可溶性单宁含量为8.91（±0.33）。
所提出的异常值去除和波长缩减策略取得了有用的结果。主成分回归的拟合/预测能力产生了出色的结果。相反，偏最小二乘法回归显示出一般/较差的结果，其余测试模型在实际数据上表现不佳。©2017化学工业协会。
