Comparing the analytical performances of Micro-NIR and FT-NIR spectrometers in the evaluation of acerola fruit quality, using PLS and SVM regression algorithms

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• 作者：Cristina Malegori^a ; ^{cristina.malegori@unimi.it} ; ^{cristina.malegori@gmail.com} ; Emanuel José ; Nascimento Marques^b ; Sergio Tonetto de Freitas^c ; Maria Fernanda Pimentel^d ; Celio Pasquini^e ; Ernestina Casiraghi^a
• 关键词：Acerola ; Malpighia emarginata DC. ; MicroNIR ; Partial Least Squares (PLS) ; Support Vector Machines (SVM) ; Passing-Bablok regression
• 刊名：Talanta
• 出版年：2017
• 出版时间：1 April 2017
• 年：2017
• 卷：165
• 期：Complete
• 页码：112-116
• 全文大小：300 K
• 卷排序：165

文摘

Accuracy in term of prediction ability of a state-of-the-art portable NIR is discussed. For the first time, acerola (Malpighia emarginata DC.) is studied by NIR spectroscopy. Titratable acidity and ascorbic acid are modelled with the NIR handle-held device. A linear (PLS) and a non-linear (SVM) regression algorithm are critically compared. Passing-Balblok regression compared the two devices and them to the reference data.