TILIA HONEY’S FRUCTOSE, GLUCOSE AND SUCROSE CONTENT PREDICTION USING FT-IR SPECTRA WITH PARTIAL LEAST SQUARES REGRESSION

The aim of this study was to assess the usefulness of Fourier transform infrared (FT-IR) spectroscopy coupled with partial least squares regression (PLS-R) to predict the fructose, glucose and sucrose content of tilia honeys. In order to achieve the aim of this study, 22 samples of tilia honey were...

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Autores principales:	Daniela PAULIUC, Paula CIURSA, Florina DRANCA, Sorina ROPCIUC, Mircea OROIAN
Formato:	article
Lenguaje:	EN
Publicado:	Stefan cel Mare University of Suceava 2020
Materias:	tilia honey fructose glucose sucrose ft-ir prediction Food processing and manufacture TP368-456
Acceso en línea:	https://doaj.org/article/552549585d2b42c9871f6c55ff8282cb
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spelling	oai:doaj.org-article:552549585d2b42c9871f6c55ff8282cb2021-12-02T17:50:23ZTILIA HONEY’S FRUCTOSE, GLUCOSE AND SUCROSE CONTENT PREDICTION USING FT-IR SPECTRA WITH PARTIAL LEAST SQUARES REGRESSION2068-66092559-6381https://doaj.org/article/552549585d2b42c9871f6c55ff8282cb2020-12-01T00:00:00Zhttp://fia-old.usv.ro/fiajournal/index.php/FENS/article/view/748/669https://doaj.org/toc/2068-6609https://doaj.org/toc/2559-6381The aim of this study was to assess the usefulness of Fourier transform infrared (FT-IR) spectroscopy coupled with partial least squares regression (PLS-R) to predict the fructose, glucose and sucrose content of tilia honeys. In order to achieve the aim of this study, 22 samples of tilia honey were purchased from Suceava, Neamt and Iasi County in the year of 2020. The fructose, glucose and sucrose content was determined prior the PLS-R prediction using high-performance liquid chromatography coupled with refractive index detector (HPLC-RID). The fructose content of tilia honeys ranged from 31.94 to 35.22%, the glucose content ranged between 26.76 and 33.15%, while sucrose content ranged between 0 and 2.20%. For the prediction of fructose, glucose and sucrose it was used the 3000 - 2800 + 1700 - 1600 +1540 -700 cm-1 spectral range. The spectral data was submitted to different mathematical pretreatments in order to reduce the noise and to improve the prediction of results. For the prediction of fructose content the suitable pretreatment was Multiplicative Scatter Correction – MSC, for glucose prediction the suitable pretreatment was Standard Normal Variate – SNV, while for the prediction of sucrose the suitable pretreatment was 1st derivate.Daniela PAULIUCPaula CIURSAFlorina DRANCASorina ROPCIUCMircea OROIANStefan cel Mare University of Suceavaarticletilia honeyfructoseglucosesucroseft-irpredictionFood processing and manufactureTP368-456ENFood and Environment Safety, Vol 19, Iss 4, Pp 260-266 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	tilia honey fructose glucose sucrose ft-ir prediction Food processing and manufacture TP368-456
spellingShingle	tilia honey fructose glucose sucrose ft-ir prediction Food processing and manufacture TP368-456 Daniela PAULIUC Paula CIURSA Florina DRANCA Sorina ROPCIUC Mircea OROIAN TILIA HONEY’S FRUCTOSE, GLUCOSE AND SUCROSE CONTENT PREDICTION USING FT-IR SPECTRA WITH PARTIAL LEAST SQUARES REGRESSION
description	The aim of this study was to assess the usefulness of Fourier transform infrared (FT-IR) spectroscopy coupled with partial least squares regression (PLS-R) to predict the fructose, glucose and sucrose content of tilia honeys. In order to achieve the aim of this study, 22 samples of tilia honey were purchased from Suceava, Neamt and Iasi County in the year of 2020. The fructose, glucose and sucrose content was determined prior the PLS-R prediction using high-performance liquid chromatography coupled with refractive index detector (HPLC-RID). The fructose content of tilia honeys ranged from 31.94 to 35.22%, the glucose content ranged between 26.76 and 33.15%, while sucrose content ranged between 0 and 2.20%. For the prediction of fructose, glucose and sucrose it was used the 3000 - 2800 + 1700 - 1600 +1540 -700 cm-1 spectral range. The spectral data was submitted to different mathematical pretreatments in order to reduce the noise and to improve the prediction of results. For the prediction of fructose content the suitable pretreatment was Multiplicative Scatter Correction – MSC, for glucose prediction the suitable pretreatment was Standard Normal Variate – SNV, while for the prediction of sucrose the suitable pretreatment was 1st derivate.
format	article
author	Daniela PAULIUC Paula CIURSA Florina DRANCA Sorina ROPCIUC Mircea OROIAN
author_facet	Daniela PAULIUC Paula CIURSA Florina DRANCA Sorina ROPCIUC Mircea OROIAN
author_sort	Daniela PAULIUC
title	TILIA HONEY’S FRUCTOSE, GLUCOSE AND SUCROSE CONTENT PREDICTION USING FT-IR SPECTRA WITH PARTIAL LEAST SQUARES REGRESSION
title_short	TILIA HONEY’S FRUCTOSE, GLUCOSE AND SUCROSE CONTENT PREDICTION USING FT-IR SPECTRA WITH PARTIAL LEAST SQUARES REGRESSION
title_full	TILIA HONEY’S FRUCTOSE, GLUCOSE AND SUCROSE CONTENT PREDICTION USING FT-IR SPECTRA WITH PARTIAL LEAST SQUARES REGRESSION
title_fullStr	TILIA HONEY’S FRUCTOSE, GLUCOSE AND SUCROSE CONTENT PREDICTION USING FT-IR SPECTRA WITH PARTIAL LEAST SQUARES REGRESSION
title_full_unstemmed	TILIA HONEY’S FRUCTOSE, GLUCOSE AND SUCROSE CONTENT PREDICTION USING FT-IR SPECTRA WITH PARTIAL LEAST SQUARES REGRESSION
title_sort	tilia honey’s fructose, glucose and sucrose content prediction using ft-ir spectra with partial least squares regression
publisher	Stefan cel Mare University of Suceava
publishDate	2020
url	https://doaj.org/article/552549585d2b42c9871f6c55ff8282cb
work_keys_str_mv	AT danielapauliuc tiliahoneysfructoseglucoseandsucrosecontentpredictionusingftirspectrawithpartialleastsquaresregression AT paulaciursa tiliahoneysfructoseglucoseandsucrosecontentpredictionusingftirspectrawithpartialleastsquaresregression AT florinadranca tiliahoneysfructoseglucoseandsucrosecontentpredictionusingftirspectrawithpartialleastsquaresregression AT sorinaropciuc tiliahoneysfructoseglucoseandsucrosecontentpredictionusingftirspectrawithpartialleastsquaresregression AT mirceaoroian tiliahoneysfructoseglucoseandsucrosecontentpredictionusingftirspectrawithpartialleastsquaresregression
_version_	1718379349519892480

TILIA HONEY’S FRUCTOSE, GLUCOSE AND SUCROSE CONTENT PREDICTION USING FT-IR SPECTRA WITH PARTIAL LEAST SQUARES REGRESSION

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