Development of rapid method to assess microbial quality of minimally processed pomegranate arils using FTIR

被引：15

作者：

Adiani, Vanshika ^{[1
]}

Gupta, Sumit ^{[1
]}

Ambolikar, Rupali ^{[1
]}

Variyar, Prasad S. ^{[1
,2
]}

机构：

[1] Bhabha Atom Res Ctr, Food Technol Div, Bombay 400085, Maharashtra, India

[2] Homi Bhabha Natl Inst, Bombay, Maharashtra, India

来源：

SENSORS AND ACTUATORS B-CHEMICAL | 2018年 / 260卷

关键词：

FTIR; Microbial quality; Pomegranate; Partial least square regression; Artificial neural networks; QUANTITATIVE DETECTION; SPECTROSCOPY DATA; SPOILAGE; CHEMOMETRICS; PREDICTION; JUICE;

D O I：

10.1016/j.snb.2018.01.095

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

Fourier transform infrared spectroscopy (FTIR) spectra were correlated with microbial quality of minimally processed pomegranate (Punica granatum) arils stored at 10 degrees C using chemometrics. FTIR data processed in three ways i.e. FTIR spectrum, first derivative for FTIR spectrum and peak integrated data of FTIR spectrum was used as independent variables for preparing regression models by partial Least Square Regression (PLS-R) and artificial neural networks (ANN) for predicting the total viable count (TVC) and yeast and mold count (Y&M). Models built with both ANN and PLS-R using FTIR data demonstrated a high correlation value of R-2 > 0.85. Analysis of PLS-R results suggested the production of alcohols and acids with utilization of sugars during storage. This is a first report demonstrating use of FTIR as a nondestructive rapid method for microbial quality analysis of minimally processed fruits. (C) 2018 Elsevier B.V. All rights reserved.

引用

页码：800 / 807

页数：8

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