MEVA SHARBATLARINI INFRAQIZIL SPEKTROSKOPIYA (IR/FTIR) USULIDA TAHLIL QILISH VA XEMOMETRIK MODELLASH ORQALI SIFAT KO‘RSATKICHLARINI BAHOLASH
DOI:
https://doi.org/10.5281/zenodo.22875702Abstract
This work analyses the quality indicators of fruit juices produced in Denmark using infrared spectroscopy (IR) and Fourier-transform infrared spectroscopy (FTIR). A total of 99 juice samples were measured on a SensIR device, and the resulting multivariate spectral data were processed using principal component analysis (PCA) and partial least squares regression (PLS). The models were built with LatentiX and Python software and were evaluated for reference indicators such as Brix, vitamin C, corrected Brix, acidity (Syre), ratio and sugar content (Gear). In addition, the conformity of the reference data to a normal distribution was checked in the “Statistica” software using the Kolmogorov-Smirnov and Shapiro-Wilk criteria. The results showed that the models built from IR spectra were not sufficiently accurate for most indicators, but the model could be used to a limited extent for the acidity and ratio indicators.Keywords
infrared spectroscopy, FTIR, fruit juice, chemometrics, principal component analysis (PCA), PLS regression, normal distribution, quality controlReferences
Nielsen, S. S. (2017). Food Analysis. 5th ed. - Springer, 2017. - 664 p. ISBN 978-3-319-45774-1.
Stuart, B. H. (2004). Infrared Spectroscopy: Fundamentals and Applications. - John Wiley & Sons, 2004. - 244 p. ISBN 978- 0-470-85428-0.
Rinnan, Å. (2009). van den Berg F., Engelsen S.B. Review of the most common pre-processing techniques for near-infrared spectra. TrAC Trends in Analytical Chemistry. -, 28(10), 1201–1222.
Snedecor, G. W., & Cochran, W. G. (1989). Statistical Methods. 8th ed. - Iowa State University Press, 1989. - 503 p.
Wold, S., Sjöström, M., & Eriksson, L. (2001). PLS-regression: a basic tool of chemometrics. Chemometrics and Intelligent Laboratory Systems. -, 58(2), 109–130.
Montgomery, D. C., & Runger, G. C. (n.d.). Applied Statistics and Probability for Engineers. - John Wiley & Sons. ePub ISBN 978-1-119-40036-3.
Hastie, T., Tibshirani, R., & Friedman, J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction. 2nd ed. - Springer, 2009. - 745 p.
Bureau, S., Cozzolino, D., & Clark, C. J. (2019). Contributions of Fourier-transform mid infrared (FT-MIR) spectroscopy to the study of fruit and vegetables. Postharvest Biology and Technology. -, 148, 1–14.
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