Quantitative prediction of rice starch digestibility using Raman spectroscopy and multivariate calibration analysis

[Display omitted] •Rice starch digestibility depends on the genetic background the growing environment.•Prediction of digestibility of rice starch by Raman scattering measurement.•The factors that determine the digestibility of rice starch are cultivar specific.•Predictive models should be construct...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Food chemistry 2024-03, Vol.435, p.137505-137505, Article 137505
Hauptverfasser: Ichinose, Junya, Oba, Kenji, Arase, Yuya, Kaneshiro, Junichi, Tate, Shin-ichi, Watanabe, Tomonobu M
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 137505
container_issue
container_start_page 137505
container_title Food chemistry
container_volume 435
creator Ichinose, Junya
Oba, Kenji
Arase, Yuya
Kaneshiro, Junichi
Tate, Shin-ichi
Watanabe, Tomonobu M
description [Display omitted] •Rice starch digestibility depends on the genetic background the growing environment.•Prediction of digestibility of rice starch by Raman scattering measurement.•The factors that determine the digestibility of rice starch are cultivar specific.•Predictive models should be constructed for each cultivar.•Digestibility determinants fluctuate maintaining a unique balance for each cultivar. Digestibility is an important characteristic of rice starch. It is affected by the growing environment, such as temperature and soil, so that even in the same genetic cultivar the digestibility of each product will be different. Here, we predicted rice starch digestibility by Raman scattering spectroscopy. A partial least squares (PLS) regression analysis was performed between biochemically quantified digestibility index values and Raman scattering spectra of purified starch from rice samples of different cultivars and growing conditions. The prediction model obtained by analyzing the individual cultivars was able to predict digestibility with a high accuracy, with an R2 of 0.95 and RMSEP of 0.43, whereas a mixture of all cultivars resulted in more than two times worse accuracy. Our finding suggests that the molecular structures affecting digestibility fluctuate depending on the growing environment while maintaining a unique balance regulated by cultivar-specific starch synthesis mechanisms.
doi_str_mv 10.1016/j.foodchem.2023.137505
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2877381520</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0308814623021234</els_id><sourcerecordid>2877381520</sourcerecordid><originalsourceid>FETCH-LOGICAL-c345t-bd658f156da76e517d09994978d86a4e643a4a59ce810008b1ef4168c07d87a63</originalsourceid><addsrcrecordid>eNqFkMtOHDEQRa2ISBkIv4C8zKYndj9s9y4I5SUhIRCsrRq7GmrU3e7YbqT5e0wG1qxqc-9R3cPYhRRbKaT6vt8OIXj3hNO2FnWzlY3uRPeJbaTRTaWFrk_YRjTCVEa26gs7TWkvhKiFNBuWbleYM2XI9Ix8iejJZQozDwOP5JCnDNE9cU-PmDLtaKR84Gui-ZHfwQQzTwu6HENyYTlwmD2f1rHAIBJk5A5G2kX4j4QZxkOi9JV9HmBMeP52z9jDr5_3V3-q65vff68uryvXtF2udl51ZpCd8qAVdlJ70fd922vjjYIWVdtAC13v0Miyx-wkDq1UxgntjQbVnLFvR-4Sw7-1vG8nSg7HEWYMa7K10boxsqtFiapj1JUlKeJgl0gTxIOVwr5atnv7btm-WrZHy6X441jEMuSZMNrkCGdXPMbixfpAHyFeAI6mi-M</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2877381520</pqid></control><display><type>article</type><title>Quantitative prediction of rice starch digestibility using Raman spectroscopy and multivariate calibration analysis</title><source>Access via ScienceDirect (Elsevier)</source><creator>Ichinose, Junya ; Oba, Kenji ; Arase, Yuya ; Kaneshiro, Junichi ; Tate, Shin-ichi ; Watanabe, Tomonobu M</creator><creatorcontrib>Ichinose, Junya ; Oba, Kenji ; Arase, Yuya ; Kaneshiro, Junichi ; Tate, Shin-ichi ; Watanabe, Tomonobu M</creatorcontrib><description>[Display omitted] •Rice starch digestibility depends on the genetic background the growing environment.•Prediction of digestibility of rice starch by Raman scattering measurement.•The factors that determine the digestibility of rice starch are cultivar specific.•Predictive models should be constructed for each cultivar.•Digestibility determinants fluctuate maintaining a unique balance for each cultivar. Digestibility is an important characteristic of rice starch. It is affected by the growing environment, such as temperature and soil, so that even in the same genetic cultivar the digestibility of each product will be different. Here, we predicted rice starch digestibility by Raman scattering spectroscopy. A partial least squares (PLS) regression analysis was performed between biochemically quantified digestibility index values and Raman scattering spectra of purified starch from rice samples of different cultivars and growing conditions. The prediction model obtained by analyzing the individual cultivars was able to predict digestibility with a high accuracy, with an R2 of 0.95 and RMSEP of 0.43, whereas a mixture of all cultivars resulted in more than two times worse accuracy. Our finding suggests that the molecular structures affecting digestibility fluctuate depending on the growing environment while maintaining a unique balance regulated by cultivar-specific starch synthesis mechanisms.</description><identifier>ISSN: 0308-8146</identifier><identifier>EISSN: 1873-7072</identifier><identifier>DOI: 10.1016/j.foodchem.2023.137505</identifier><language>eng</language><publisher>Elsevier Ltd</publisher><subject>Amylopectin ; Digestibility ; Partial least squares ; Raman spectroscopy ; Rice ; Starch</subject><ispartof>Food chemistry, 2024-03, Vol.435, p.137505-137505, Article 137505</ispartof><rights>2023 Elsevier Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c345t-bd658f156da76e517d09994978d86a4e643a4a59ce810008b1ef4168c07d87a63</citedby><cites>FETCH-LOGICAL-c345t-bd658f156da76e517d09994978d86a4e643a4a59ce810008b1ef4168c07d87a63</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.foodchem.2023.137505$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>315,781,785,3551,27928,27929,45999</link.rule.ids></links><search><creatorcontrib>Ichinose, Junya</creatorcontrib><creatorcontrib>Oba, Kenji</creatorcontrib><creatorcontrib>Arase, Yuya</creatorcontrib><creatorcontrib>Kaneshiro, Junichi</creatorcontrib><creatorcontrib>Tate, Shin-ichi</creatorcontrib><creatorcontrib>Watanabe, Tomonobu M</creatorcontrib><title>Quantitative prediction of rice starch digestibility using Raman spectroscopy and multivariate calibration analysis</title><title>Food chemistry</title><description>[Display omitted] •Rice starch digestibility depends on the genetic background the growing environment.•Prediction of digestibility of rice starch by Raman scattering measurement.•The factors that determine the digestibility of rice starch are cultivar specific.•Predictive models should be constructed for each cultivar.•Digestibility determinants fluctuate maintaining a unique balance for each cultivar. Digestibility is an important characteristic of rice starch. It is affected by the growing environment, such as temperature and soil, so that even in the same genetic cultivar the digestibility of each product will be different. Here, we predicted rice starch digestibility by Raman scattering spectroscopy. A partial least squares (PLS) regression analysis was performed between biochemically quantified digestibility index values and Raman scattering spectra of purified starch from rice samples of different cultivars and growing conditions. The prediction model obtained by analyzing the individual cultivars was able to predict digestibility with a high accuracy, with an R2 of 0.95 and RMSEP of 0.43, whereas a mixture of all cultivars resulted in more than two times worse accuracy. Our finding suggests that the molecular structures affecting digestibility fluctuate depending on the growing environment while maintaining a unique balance regulated by cultivar-specific starch synthesis mechanisms.</description><subject>Amylopectin</subject><subject>Digestibility</subject><subject>Partial least squares</subject><subject>Raman spectroscopy</subject><subject>Rice</subject><subject>Starch</subject><issn>0308-8146</issn><issn>1873-7072</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNqFkMtOHDEQRa2ISBkIv4C8zKYndj9s9y4I5SUhIRCsrRq7GmrU3e7YbqT5e0wG1qxqc-9R3cPYhRRbKaT6vt8OIXj3hNO2FnWzlY3uRPeJbaTRTaWFrk_YRjTCVEa26gs7TWkvhKiFNBuWbleYM2XI9Ix8iejJZQozDwOP5JCnDNE9cU-PmDLtaKR84Gui-ZHfwQQzTwu6HENyYTlwmD2f1rHAIBJk5A5G2kX4j4QZxkOi9JV9HmBMeP52z9jDr5_3V3-q65vff68uryvXtF2udl51ZpCd8qAVdlJ70fd922vjjYIWVdtAC13v0Miyx-wkDq1UxgntjQbVnLFvR-4Sw7-1vG8nSg7HEWYMa7K10boxsqtFiapj1JUlKeJgl0gTxIOVwr5atnv7btm-WrZHy6X441jEMuSZMNrkCGdXPMbixfpAHyFeAI6mi-M</recordid><startdate>20240301</startdate><enddate>20240301</enddate><creator>Ichinose, Junya</creator><creator>Oba, Kenji</creator><creator>Arase, Yuya</creator><creator>Kaneshiro, Junichi</creator><creator>Tate, Shin-ichi</creator><creator>Watanabe, Tomonobu M</creator><general>Elsevier Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20240301</creationdate><title>Quantitative prediction of rice starch digestibility using Raman spectroscopy and multivariate calibration analysis</title><author>Ichinose, Junya ; Oba, Kenji ; Arase, Yuya ; Kaneshiro, Junichi ; Tate, Shin-ichi ; Watanabe, Tomonobu M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c345t-bd658f156da76e517d09994978d86a4e643a4a59ce810008b1ef4168c07d87a63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Amylopectin</topic><topic>Digestibility</topic><topic>Partial least squares</topic><topic>Raman spectroscopy</topic><topic>Rice</topic><topic>Starch</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ichinose, Junya</creatorcontrib><creatorcontrib>Oba, Kenji</creatorcontrib><creatorcontrib>Arase, Yuya</creatorcontrib><creatorcontrib>Kaneshiro, Junichi</creatorcontrib><creatorcontrib>Tate, Shin-ichi</creatorcontrib><creatorcontrib>Watanabe, Tomonobu M</creatorcontrib><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Food chemistry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ichinose, Junya</au><au>Oba, Kenji</au><au>Arase, Yuya</au><au>Kaneshiro, Junichi</au><au>Tate, Shin-ichi</au><au>Watanabe, Tomonobu M</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Quantitative prediction of rice starch digestibility using Raman spectroscopy and multivariate calibration analysis</atitle><jtitle>Food chemistry</jtitle><date>2024-03-01</date><risdate>2024</risdate><volume>435</volume><spage>137505</spage><epage>137505</epage><pages>137505-137505</pages><artnum>137505</artnum><issn>0308-8146</issn><eissn>1873-7072</eissn><abstract>[Display omitted] •Rice starch digestibility depends on the genetic background the growing environment.•Prediction of digestibility of rice starch by Raman scattering measurement.•The factors that determine the digestibility of rice starch are cultivar specific.•Predictive models should be constructed for each cultivar.•Digestibility determinants fluctuate maintaining a unique balance for each cultivar. Digestibility is an important characteristic of rice starch. It is affected by the growing environment, such as temperature and soil, so that even in the same genetic cultivar the digestibility of each product will be different. Here, we predicted rice starch digestibility by Raman scattering spectroscopy. A partial least squares (PLS) regression analysis was performed between biochemically quantified digestibility index values and Raman scattering spectra of purified starch from rice samples of different cultivars and growing conditions. The prediction model obtained by analyzing the individual cultivars was able to predict digestibility with a high accuracy, with an R2 of 0.95 and RMSEP of 0.43, whereas a mixture of all cultivars resulted in more than two times worse accuracy. Our finding suggests that the molecular structures affecting digestibility fluctuate depending on the growing environment while maintaining a unique balance regulated by cultivar-specific starch synthesis mechanisms.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.foodchem.2023.137505</doi><tpages>1</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0308-8146
ispartof Food chemistry, 2024-03, Vol.435, p.137505-137505, Article 137505
issn 0308-8146
1873-7072
language eng
recordid cdi_proquest_miscellaneous_2877381520
source Access via ScienceDirect (Elsevier)
subjects Amylopectin
Digestibility
Partial least squares
Raman spectroscopy
Rice
Starch
title Quantitative prediction of rice starch digestibility using Raman spectroscopy and multivariate calibration analysis
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-16T14%3A57%3A31IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Quantitative%20prediction%20of%20rice%20starch%20digestibility%20using%20Raman%20spectroscopy%20and%20multivariate%20calibration%20analysis&rft.jtitle=Food%20chemistry&rft.au=Ichinose,%20Junya&rft.date=2024-03-01&rft.volume=435&rft.spage=137505&rft.epage=137505&rft.pages=137505-137505&rft.artnum=137505&rft.issn=0308-8146&rft.eissn=1873-7072&rft_id=info:doi/10.1016/j.foodchem.2023.137505&rft_dat=%3Cproquest_cross%3E2877381520%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2877381520&rft_id=info:pmid/&rft_els_id=S0308814623021234&rfr_iscdi=true