Impact of thermal, high‐pressure and ultra‐shear pasteurisation technologies on beetroot juice metabolites using untargeted nuclear magnetic resonance spectroscopy
Summary The impact of three food pasteurisation technologies, namely thermal, high‐pressure and ultra‐shear processing, on the metabolites of beetroot juice was evaluated using a processomics approach with nuclear mass resonance (NMR) as an analytical technique. Two batches of beetroots acquired fro...
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description | Summary
The impact of three food pasteurisation technologies, namely thermal, high‐pressure and ultra‐shear processing, on the metabolites of beetroot juice was evaluated using a processomics approach with nuclear mass resonance (NMR) as an analytical technique. Two batches of beetroots acquired from different local grocery stores were used for this study. Beetroot juice obtained from these batches was subjected to high‐pressure processing (HPP) at 600 MPa and 25 °C for 5 min, ultra‐shear technology processing (UST) at 400 MPa and 30 °C and thermal processing (TP) at 96 °C for 12 min. Principal component analysis (PCA) for the two batches indicated that both extrinsic factors such as processing parameters (temperature, pressure, shear and holding time) and intrinsic factors such as the origin of the beetroot influenced the PCA plot. When the influence of intrinsic parameters was minimised by studying a single batch processed by TP, HPP and UST, distinct clusters for different processing methods were formed, indicating that processing influenced the metabolites. While processing is not the main factor determining the final composition, as indicated by PCA with different batches, supervised techniques like orthogonal partial least‐squares discriminant analysis (OPLS‐DA) and random forest (RF) demonstrated that processing does impact the beetroot juice metabolome. Seven metabolites (leucine, alanine, valine, glutamine, gamma‐aminobutyric acid, fructose and glucose) were identified as potential process‐induced biomarkers.
Beetroot metabolites showed varying sensitivities to the intensity of thermal, high‐pressure and shear treatments, as well as their selective combinations. |
doi_str_mv | 10.1111/ijfs.17326 |
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The impact of three food pasteurisation technologies, namely thermal, high‐pressure and ultra‐shear processing, on the metabolites of beetroot juice was evaluated using a processomics approach with nuclear mass resonance (NMR) as an analytical technique. Two batches of beetroots acquired from different local grocery stores were used for this study. Beetroot juice obtained from these batches was subjected to high‐pressure processing (HPP) at 600 MPa and 25 °C for 5 min, ultra‐shear technology processing (UST) at 400 MPa and 30 °C and thermal processing (TP) at 96 °C for 12 min. Principal component analysis (PCA) for the two batches indicated that both extrinsic factors such as processing parameters (temperature, pressure, shear and holding time) and intrinsic factors such as the origin of the beetroot influenced the PCA plot. When the influence of intrinsic parameters was minimised by studying a single batch processed by TP, HPP and UST, distinct clusters for different processing methods were formed, indicating that processing influenced the metabolites. While processing is not the main factor determining the final composition, as indicated by PCA with different batches, supervised techniques like orthogonal partial least‐squares discriminant analysis (OPLS‐DA) and random forest (RF) demonstrated that processing does impact the beetroot juice metabolome. Seven metabolites (leucine, alanine, valine, glutamine, gamma‐aminobutyric acid, fructose and glucose) were identified as potential process‐induced biomarkers.
Beetroot metabolites showed varying sensitivities to the intensity of thermal, high‐pressure and shear treatments, as well as their selective combinations.</description><identifier>ISSN: 0950-5423</identifier><identifier>EISSN: 1365-2621</identifier><identifier>DOI: 10.1111/ijfs.17326</identifier><language>eng</language><publisher>Oxford: Wiley Subscription Services, Inc</publisher><subject>Alanine ; Beetroot ; beets ; Biomarkers ; chemometrics ; Discriminant analysis ; fructose ; gamma-aminobutyric acid ; glucose ; Glutamine ; high pressure ; Juices ; least squares ; Leucine ; Magnetic resonance spectroscopy ; Metabolites ; metabolome ; NMR ; NMR spectroscopy ; Nuclear magnetic resonance ; nuclear magnetic resonance spectroscopy ; pasteurisation ; Pasteurization ; principal component analysis ; Principal components analysis ; Process parameters ; processing ; Shear ; Sugar beets ; temperature ; thermal ; Valine</subject><ispartof>International journal of food science & technology, 2024-08, Vol.59 (8), p.5754-5766</ispartof><rights>2024 The Author(s). published by John Wiley & Sons Ltd on behalf of Institute of Food Science & Technology (IFST).</rights><rights>2024. This article is published under http://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c2236-bddfe1621a93e3fa8c91846b568bb15f2a861ec398b0f2fbb2d9dc768c4f598a3</cites><orcidid>0000-0002-1540-4273 ; 0000-0002-6400-9528</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fijfs.17326$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fijfs.17326$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids></links><search><creatorcontrib>Guduru, Sai Sasidhar</creatorcontrib><creatorcontrib>Balasubramaniam, V.M.</creatorcontrib><creatorcontrib>Hatzakis, Emmanuel</creatorcontrib><title>Impact of thermal, high‐pressure and ultra‐shear pasteurisation technologies on beetroot juice metabolites using untargeted nuclear magnetic resonance spectroscopy</title><title>International journal of food science & technology</title><description>Summary
The impact of three food pasteurisation technologies, namely thermal, high‐pressure and ultra‐shear processing, on the metabolites of beetroot juice was evaluated using a processomics approach with nuclear mass resonance (NMR) as an analytical technique. Two batches of beetroots acquired from different local grocery stores were used for this study. Beetroot juice obtained from these batches was subjected to high‐pressure processing (HPP) at 600 MPa and 25 °C for 5 min, ultra‐shear technology processing (UST) at 400 MPa and 30 °C and thermal processing (TP) at 96 °C for 12 min. Principal component analysis (PCA) for the two batches indicated that both extrinsic factors such as processing parameters (temperature, pressure, shear and holding time) and intrinsic factors such as the origin of the beetroot influenced the PCA plot. When the influence of intrinsic parameters was minimised by studying a single batch processed by TP, HPP and UST, distinct clusters for different processing methods were formed, indicating that processing influenced the metabolites. While processing is not the main factor determining the final composition, as indicated by PCA with different batches, supervised techniques like orthogonal partial least‐squares discriminant analysis (OPLS‐DA) and random forest (RF) demonstrated that processing does impact the beetroot juice metabolome. Seven metabolites (leucine, alanine, valine, glutamine, gamma‐aminobutyric acid, fructose and glucose) were identified as potential process‐induced biomarkers.
Beetroot metabolites showed varying sensitivities to the intensity of thermal, high‐pressure and shear treatments, as well as their selective combinations.</description><subject>Alanine</subject><subject>Beetroot</subject><subject>beets</subject><subject>Biomarkers</subject><subject>chemometrics</subject><subject>Discriminant analysis</subject><subject>fructose</subject><subject>gamma-aminobutyric acid</subject><subject>glucose</subject><subject>Glutamine</subject><subject>high pressure</subject><subject>Juices</subject><subject>least squares</subject><subject>Leucine</subject><subject>Magnetic resonance spectroscopy</subject><subject>Metabolites</subject><subject>metabolome</subject><subject>NMR</subject><subject>NMR spectroscopy</subject><subject>Nuclear magnetic resonance</subject><subject>nuclear magnetic resonance spectroscopy</subject><subject>pasteurisation</subject><subject>Pasteurization</subject><subject>principal component analysis</subject><subject>Principal components analysis</subject><subject>Process parameters</subject><subject>processing</subject><subject>Shear</subject><subject>Sugar beets</subject><subject>temperature</subject><subject>thermal</subject><subject>Valine</subject><issn>0950-5423</issn><issn>1365-2621</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><recordid>eNp9kTuOFDEQhi0EEsNCwgkskSBEL36M-xGi1S4MWokAiC23u9ztkdtu_BCajCNwC-7FSfAwRAQ4Kdn11V-u-hF6Tsk1reeNPZp0TTvO2gdoR3krGtYy-hDtyCBII_aMP0ZPUjoSQhjv9jv087BuSmccDM4LxFW513ix8_Lr-48tQkolAlZ-wsXlqOpjWkBFvKmUoUSbVLbB4wx68cGF2ULC9T4C5BhCxsdiNeAVshqDs7lmS7J-xsVnFWfIMGFftDtLrmr2kK3GtWvwyte6tIGuOkmH7fQUPTLKJXj2N16hL3e3n2_eN_cf3x1u3t43mjHeNuM0GaB1ZDVw4Eb1eqD9vh1F248jFYapvqWg-dCPxDAzjmwaJt21vd4bMfSKX6GXF90thq8FUparTRqcUx5CSZJTUbcqBtZV9MU_6DGU6OvvJCfdMAhW112pVxdK10lSBCO3aFcVT5ISefZMnj2TfzyrML3A36yD039Iefhw9-lS8xs4r6EA</recordid><startdate>202408</startdate><enddate>202408</enddate><creator>Guduru, Sai Sasidhar</creator><creator>Balasubramaniam, V.M.</creator><creator>Hatzakis, Emmanuel</creator><general>Wiley Subscription Services, Inc</general><scope>24P</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7QR</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7ST</scope><scope>7T7</scope><scope>7TA</scope><scope>7TB</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>JG9</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>P64</scope><scope>SOI</scope><scope>7S9</scope><scope>L.6</scope><orcidid>https://orcid.org/0000-0002-1540-4273</orcidid><orcidid>https://orcid.org/0000-0002-6400-9528</orcidid></search><sort><creationdate>202408</creationdate><title>Impact of thermal, high‐pressure and ultra‐shear pasteurisation technologies on beetroot juice metabolites using untargeted nuclear magnetic resonance spectroscopy</title><author>Guduru, Sai Sasidhar ; Balasubramaniam, V.M. ; Hatzakis, Emmanuel</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2236-bddfe1621a93e3fa8c91846b568bb15f2a861ec398b0f2fbb2d9dc768c4f598a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Alanine</topic><topic>Beetroot</topic><topic>beets</topic><topic>Biomarkers</topic><topic>chemometrics</topic><topic>Discriminant analysis</topic><topic>fructose</topic><topic>gamma-aminobutyric acid</topic><topic>glucose</topic><topic>Glutamine</topic><topic>high pressure</topic><topic>Juices</topic><topic>least squares</topic><topic>Leucine</topic><topic>Magnetic resonance spectroscopy</topic><topic>Metabolites</topic><topic>metabolome</topic><topic>NMR</topic><topic>NMR spectroscopy</topic><topic>Nuclear magnetic resonance</topic><topic>nuclear magnetic resonance spectroscopy</topic><topic>pasteurisation</topic><topic>Pasteurization</topic><topic>principal component analysis</topic><topic>Principal components analysis</topic><topic>Process parameters</topic><topic>processing</topic><topic>Shear</topic><topic>Sugar beets</topic><topic>temperature</topic><topic>thermal</topic><topic>Valine</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Guduru, Sai Sasidhar</creatorcontrib><creatorcontrib>Balasubramaniam, V.M.</creatorcontrib><creatorcontrib>Hatzakis, Emmanuel</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Environment Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environment Abstracts</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>International journal of food science & technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Guduru, Sai Sasidhar</au><au>Balasubramaniam, V.M.</au><au>Hatzakis, Emmanuel</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Impact of thermal, high‐pressure and ultra‐shear pasteurisation technologies on beetroot juice metabolites using untargeted nuclear magnetic resonance spectroscopy</atitle><jtitle>International journal of food science & technology</jtitle><date>2024-08</date><risdate>2024</risdate><volume>59</volume><issue>8</issue><spage>5754</spage><epage>5766</epage><pages>5754-5766</pages><issn>0950-5423</issn><eissn>1365-2621</eissn><abstract>Summary
The impact of three food pasteurisation technologies, namely thermal, high‐pressure and ultra‐shear processing, on the metabolites of beetroot juice was evaluated using a processomics approach with nuclear mass resonance (NMR) as an analytical technique. Two batches of beetroots acquired from different local grocery stores were used for this study. Beetroot juice obtained from these batches was subjected to high‐pressure processing (HPP) at 600 MPa and 25 °C for 5 min, ultra‐shear technology processing (UST) at 400 MPa and 30 °C and thermal processing (TP) at 96 °C for 12 min. Principal component analysis (PCA) for the two batches indicated that both extrinsic factors such as processing parameters (temperature, pressure, shear and holding time) and intrinsic factors such as the origin of the beetroot influenced the PCA plot. When the influence of intrinsic parameters was minimised by studying a single batch processed by TP, HPP and UST, distinct clusters for different processing methods were formed, indicating that processing influenced the metabolites. While processing is not the main factor determining the final composition, as indicated by PCA with different batches, supervised techniques like orthogonal partial least‐squares discriminant analysis (OPLS‐DA) and random forest (RF) demonstrated that processing does impact the beetroot juice metabolome. Seven metabolites (leucine, alanine, valine, glutamine, gamma‐aminobutyric acid, fructose and glucose) were identified as potential process‐induced biomarkers.
Beetroot metabolites showed varying sensitivities to the intensity of thermal, high‐pressure and shear treatments, as well as their selective combinations.</abstract><cop>Oxford</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1111/ijfs.17326</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0002-1540-4273</orcidid><orcidid>https://orcid.org/0000-0002-6400-9528</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Alanine Beetroot beets Biomarkers chemometrics Discriminant analysis fructose gamma-aminobutyric acid glucose Glutamine high pressure Juices least squares Leucine Magnetic resonance spectroscopy Metabolites metabolome NMR NMR spectroscopy Nuclear magnetic resonance nuclear magnetic resonance spectroscopy pasteurisation Pasteurization principal component analysis Principal components analysis Process parameters processing Shear Sugar beets temperature thermal Valine |
title | Impact of thermal, high‐pressure and ultra‐shear pasteurisation technologies on beetroot juice metabolites using untargeted nuclear magnetic resonance spectroscopy |
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