Infrared spectroscopy for the quality assessment of Habanero chilli: a proof-of-concept study
Habanero chillies ( Capsicum chinense cv Habanero) are a popular species of hot chilli in Australia, with production steadily increasing. However, there is limited research on this crop due to its relatively low levels of production at present. Rapid methods of assessing fruit quality could be great...
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description | Habanero chillies (
Capsicum chinense
cv Habanero) are a popular species of hot chilli in Australia, with production steadily increasing. However, there is limited research on this crop due to its relatively low levels of production at present. Rapid methods of assessing fruit quality could be greatly beneficial both for quality assurance purposes and for use in breeding programs or experimental growing trials. This work investigated the potential of using infrared spectroscopy for the quality assessment of 20 Australian Habanero chilli samples, including the prediction of dry matter content, total phenolic content, ferric reducing antioxidant potential and capsaicin/dihydrocapsaicin content. Near-infrared spectra (908–1676 nm) taken from the fresh fruit showed strong potential for the estimation of dry matter content, with a root mean standard error of cross-validation (RMSECV) of 0.50% FW. A moving-window partial least squares regression model was applied to optimise the spectral window used for dry matter content prediction, with the best-performing window being between 1224 and 1422 nm. However, the near-infrared spectra of fresh fruit could not be used to estimate the total phenolic content or capsaicin/dihydrocapsaicin content of the samples. Mid-infrared spectra (4000 − 400 cm
− 1
) collected from the dried, powdered material showed slightly more promise for the prediction of total phenolics and the ratio of capsaicin:dihydrocapsaicin, with a R
2
cv
of 0.45 and RMSECV of 0.32 for the latter parameter. Although further refinement is required, this method may be able to detect samples with high/low contents of total phenolics or for the estimation of the capsaicin:dihydrocapsaicin ratio. |
doi_str_mv | 10.1007/s11694-022-01743-1 |
format | Article |
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Capsicum chinense
cv Habanero) are a popular species of hot chilli in Australia, with production steadily increasing. However, there is limited research on this crop due to its relatively low levels of production at present. Rapid methods of assessing fruit quality could be greatly beneficial both for quality assurance purposes and for use in breeding programs or experimental growing trials. This work investigated the potential of using infrared spectroscopy for the quality assessment of 20 Australian Habanero chilli samples, including the prediction of dry matter content, total phenolic content, ferric reducing antioxidant potential and capsaicin/dihydrocapsaicin content. Near-infrared spectra (908–1676 nm) taken from the fresh fruit showed strong potential for the estimation of dry matter content, with a root mean standard error of cross-validation (RMSECV) of 0.50% FW. A moving-window partial least squares regression model was applied to optimise the spectral window used for dry matter content prediction, with the best-performing window being between 1224 and 1422 nm. However, the near-infrared spectra of fresh fruit could not be used to estimate the total phenolic content or capsaicin/dihydrocapsaicin content of the samples. Mid-infrared spectra (4000 − 400 cm
− 1
) collected from the dried, powdered material showed slightly more promise for the prediction of total phenolics and the ratio of capsaicin:dihydrocapsaicin, with a R
2
cv
of 0.45 and RMSECV of 0.32 for the latter parameter. Although further refinement is required, this method may be able to detect samples with high/low contents of total phenolics or for the estimation of the capsaicin:dihydrocapsaicin ratio.</description><identifier>ISSN: 2193-4126</identifier><identifier>EISSN: 2193-4134</identifier><identifier>DOI: 10.1007/s11694-022-01743-1</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Capsaicin ; Chemistry ; Chemistry and Materials Science ; Chemistry/Food Science ; Dry matter ; Engineering ; Food Science ; Fruits ; Infrared spectra ; Infrared spectroscopy ; Least squares method ; Near infrared radiation ; Original Paper ; Peppers ; Phenolic compounds ; Phenols ; Predictions ; Production methods ; Quality assessment ; Quality assurance ; Quality control ; Regression models ; Spectroscopic analysis ; Spectrum analysis ; Standard error</subject><ispartof>Journal of food measurement & characterization, 2023-04, Vol.17 (2), p.1764-1774</ispartof><rights>The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-5cb5fc43c5cd26bffa76a1ea2eddcb7dc426d162450c5068d06dca529c8676bd3</citedby><cites>FETCH-LOGICAL-c319t-5cb5fc43c5cd26bffa76a1ea2eddcb7dc426d162450c5068d06dca529c8676bd3</cites><orcidid>0000-0002-9172-8587</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11694-022-01743-1$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11694-022-01743-1$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,777,781,27905,27906,41469,42538,51300</link.rule.ids></links><search><creatorcontrib>Johnson, Joel B.</creatorcontrib><creatorcontrib>Mani, Janice S.</creatorcontrib><creatorcontrib>Walsh, Kerry B.</creatorcontrib><creatorcontrib>Naiker, Mani</creatorcontrib><title>Infrared spectroscopy for the quality assessment of Habanero chilli: a proof-of-concept study</title><title>Journal of food measurement & characterization</title><addtitle>Food Measure</addtitle><description>Habanero chillies (
Capsicum chinense
cv Habanero) are a popular species of hot chilli in Australia, with production steadily increasing. However, there is limited research on this crop due to its relatively low levels of production at present. Rapid methods of assessing fruit quality could be greatly beneficial both for quality assurance purposes and for use in breeding programs or experimental growing trials. This work investigated the potential of using infrared spectroscopy for the quality assessment of 20 Australian Habanero chilli samples, including the prediction of dry matter content, total phenolic content, ferric reducing antioxidant potential and capsaicin/dihydrocapsaicin content. Near-infrared spectra (908–1676 nm) taken from the fresh fruit showed strong potential for the estimation of dry matter content, with a root mean standard error of cross-validation (RMSECV) of 0.50% FW. A moving-window partial least squares regression model was applied to optimise the spectral window used for dry matter content prediction, with the best-performing window being between 1224 and 1422 nm. However, the near-infrared spectra of fresh fruit could not be used to estimate the total phenolic content or capsaicin/dihydrocapsaicin content of the samples. Mid-infrared spectra (4000 − 400 cm
− 1
) collected from the dried, powdered material showed slightly more promise for the prediction of total phenolics and the ratio of capsaicin:dihydrocapsaicin, with a R
2
cv
of 0.45 and RMSECV of 0.32 for the latter parameter. Although further refinement is required, this method may be able to detect samples with high/low contents of total phenolics or for the estimation of the capsaicin:dihydrocapsaicin ratio.</description><subject>Capsaicin</subject><subject>Chemistry</subject><subject>Chemistry and Materials Science</subject><subject>Chemistry/Food Science</subject><subject>Dry matter</subject><subject>Engineering</subject><subject>Food Science</subject><subject>Fruits</subject><subject>Infrared spectra</subject><subject>Infrared spectroscopy</subject><subject>Least squares method</subject><subject>Near infrared radiation</subject><subject>Original Paper</subject><subject>Peppers</subject><subject>Phenolic compounds</subject><subject>Phenols</subject><subject>Predictions</subject><subject>Production methods</subject><subject>Quality assessment</subject><subject>Quality assurance</subject><subject>Quality control</subject><subject>Regression models</subject><subject>Spectroscopic analysis</subject><subject>Spectrum analysis</subject><subject>Standard error</subject><issn>2193-4126</issn><issn>2193-4134</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNp9kE1LxDAQhoMouKz7BzwFPEfz1bT1Jou6Cwte9CghzYfbpdt0k_TQf2-0ojdhYObwvO_MvABcE3xLMC7vIiGi5ghTijApOUPkDCwoqRnihPHz35mKS7CK8YAxJpnjgi3A-7Z3QQVrYBysTsFH7YcJOh9g2lt4GlXXpgmqGG2MR9sn6B3cqEb1Nnio923XtfdQwSF471Au7XtthwRjGs10BS6c6qJd_fQleHt6fF1v0O7lebt-2CHNSJ1QoZvCac50oQ0VjXOqFIpYRa0xuimN5lQYIigvsC6wqAwWRquC1roSpWgMW4Kb2TefcRptTPLgx9DnlZKWFcVcVJRlis6Uzm_GYJ0cQntUYZIEy68k5ZykzEnK7yQlySI2i2KG-w8b_qz_UX0CJ7Z3pg</recordid><startdate>20230401</startdate><enddate>20230401</enddate><creator>Johnson, Joel B.</creator><creator>Mani, Janice S.</creator><creator>Walsh, Kerry B.</creator><creator>Naiker, Mani</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X2</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M0K</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><orcidid>https://orcid.org/0000-0002-9172-8587</orcidid></search><sort><creationdate>20230401</creationdate><title>Infrared spectroscopy for the quality assessment of Habanero chilli: a proof-of-concept study</title><author>Johnson, Joel B. ; Mani, Janice S. ; Walsh, Kerry B. ; Naiker, Mani</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c319t-5cb5fc43c5cd26bffa76a1ea2eddcb7dc426d162450c5068d06dca529c8676bd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Capsaicin</topic><topic>Chemistry</topic><topic>Chemistry and Materials Science</topic><topic>Chemistry/Food Science</topic><topic>Dry matter</topic><topic>Engineering</topic><topic>Food Science</topic><topic>Fruits</topic><topic>Infrared spectra</topic><topic>Infrared spectroscopy</topic><topic>Least squares method</topic><topic>Near infrared radiation</topic><topic>Original Paper</topic><topic>Peppers</topic><topic>Phenolic compounds</topic><topic>Phenols</topic><topic>Predictions</topic><topic>Production methods</topic><topic>Quality assessment</topic><topic>Quality assurance</topic><topic>Quality control</topic><topic>Regression models</topic><topic>Spectroscopic analysis</topic><topic>Spectrum analysis</topic><topic>Standard error</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Johnson, Joel B.</creatorcontrib><creatorcontrib>Mani, Janice S.</creatorcontrib><creatorcontrib>Walsh, Kerry B.</creatorcontrib><creatorcontrib>Naiker, Mani</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Agricultural Science Collection</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Agricultural Science Database</collection><collection>Engineering Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><jtitle>Journal of food measurement & characterization</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Johnson, Joel B.</au><au>Mani, Janice S.</au><au>Walsh, Kerry B.</au><au>Naiker, Mani</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Infrared spectroscopy for the quality assessment of Habanero chilli: a proof-of-concept study</atitle><jtitle>Journal of food measurement & characterization</jtitle><stitle>Food Measure</stitle><date>2023-04-01</date><risdate>2023</risdate><volume>17</volume><issue>2</issue><spage>1764</spage><epage>1774</epage><pages>1764-1774</pages><issn>2193-4126</issn><eissn>2193-4134</eissn><abstract>Habanero chillies (
Capsicum chinense
cv Habanero) are a popular species of hot chilli in Australia, with production steadily increasing. However, there is limited research on this crop due to its relatively low levels of production at present. Rapid methods of assessing fruit quality could be greatly beneficial both for quality assurance purposes and for use in breeding programs or experimental growing trials. This work investigated the potential of using infrared spectroscopy for the quality assessment of 20 Australian Habanero chilli samples, including the prediction of dry matter content, total phenolic content, ferric reducing antioxidant potential and capsaicin/dihydrocapsaicin content. Near-infrared spectra (908–1676 nm) taken from the fresh fruit showed strong potential for the estimation of dry matter content, with a root mean standard error of cross-validation (RMSECV) of 0.50% FW. A moving-window partial least squares regression model was applied to optimise the spectral window used for dry matter content prediction, with the best-performing window being between 1224 and 1422 nm. However, the near-infrared spectra of fresh fruit could not be used to estimate the total phenolic content or capsaicin/dihydrocapsaicin content of the samples. Mid-infrared spectra (4000 − 400 cm
− 1
) collected from the dried, powdered material showed slightly more promise for the prediction of total phenolics and the ratio of capsaicin:dihydrocapsaicin, with a R
2
cv
of 0.45 and RMSECV of 0.32 for the latter parameter. Although further refinement is required, this method may be able to detect samples with high/low contents of total phenolics or for the estimation of the capsaicin:dihydrocapsaicin ratio.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s11694-022-01743-1</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-9172-8587</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Capsaicin Chemistry Chemistry and Materials Science Chemistry/Food Science Dry matter Engineering Food Science Fruits Infrared spectra Infrared spectroscopy Least squares method Near infrared radiation Original Paper Peppers Phenolic compounds Phenols Predictions Production methods Quality assessment Quality assurance Quality control Regression models Spectroscopic analysis Spectrum analysis Standard error |
title | Infrared spectroscopy for the quality assessment of Habanero chilli: a proof-of-concept study |
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