文章基本信息

标题：Analysis of Moisture Content in Beetroot using Fourier Transform Infrared Spectroscopy and by Principal Component Analysis
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作者：Noel Nesakumar ; Chanthini Baskar ; Srinivasan Kesavan 等
期刊名称：Scientific Reports
电子版ISSN：2045-2322
出版年度：2018
卷号：8
期号：1
页码：7996
DOI：10.1038/s41598-018-26243-5
语种：English
出版社：Springer Nature
摘要：The moisture content of beetroot varies during long-term cold storage. In this work, we propose a strategy to identify the moisture content and age of beetroot using principal component analysis coupled Fourier transform infrared spectroscopy (FTIR). Frequent FTIR measurements were recorded directly from the beetroot sample surface over a period of 34 days for analysing its moisture content employing attenuated total reflectance in the spectral ranges of 2614–4000 and 1465–1853 cm−1 with a spectral resolution of 8 cm−1. In order to estimate the transmittance peak height (T p ) and area under the transmittance curve $$({\int }_{{\bar{\nu }}_{i}}^{{\bar{\nu }}_{f}}{T}_{p}d\bar{\nu })$$ ( ∫ ν ¯ i ν ¯ f T p d ν ¯ ) over the spectral ranges of 2614–4000 and 1465–1853 cm−1, Gaussian curve fitting algorithm was performed on FTIR data. Principal component and nonlinear regression analyses were utilized for FTIR data analysis. Score plot over the ranges of 2614–4000 and 1465–1853 cm−1 allowed beetroot quality discrimination. Beetroot quality predictive models were developed by employing biphasic dose response function. Validation experiment results confirmed that the accuracy of the beetroot quality predictive model reached 97.5%. This research work proves that FTIR spectroscopy in combination with principal component analysis and beetroot quality predictive models could serve as an effective tool for discriminating moisture content in fresh, half and completely spoiled stages of beetroot samples and for providing status alerts.