Fourier-transform infrared spectroscopy combined with chemometrics for detection of pork in beef meatball formulation
Objective: This research focused to analyze the pork content in beef meatball. Pork analysis in beef meatball using Fourier-transform infrared (FTIR) spectroscopy combined with chemometrics. Methods: Beef meatball and pork meatball were determined by FTIR spectroscopy. The FTIR spectrum was used to...
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description | Objective: This research focused to analyze the pork content in beef meatball. Pork analysis in beef meatball using Fourier-transform infrared (FTIR) spectroscopy combined with chemometrics. Methods: Beef meatball and pork meatball were determined by FTIR spectroscopy. The FTIR spectrum was used to detect pork in beef meatball combined with chemometrics method such as partial least square (PLS) and principal component analysis (PCA). Results: In this study, we developed FTIR spectroscopy using multivariate chemometrics. Chemometrics which is used is PLS to analyze pork in beef meatball, and PCA is used to classify pork and beef in meatball. The result PLS is linear regression equation which is a relationship between actual value and FTIR predicted value, y = 0.9984x + 0.0758 with a determination coefficient (R2) 0.9984. Root mean square error calibration (RMSEC) is 1.09%, root mean square external error calibration is 0.04%, and root mean square error external cross-validation is 0.48%. PCA successfully used to classify meatball in the market between beef meatball and pork meatball. Conclusion: Result of pork detection in meat meatballs using FTIR has determination coefficient of 0.9984 with RMSEC of 1.09%. Pork meatball and Beef meatballs can be distinguished using the chemometrics method. |
doi_str_mv | 10.22377/ijgp.v12i03.1945 |
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Pork analysis in beef meatball using Fourier-transform infrared (FTIR) spectroscopy combined with chemometrics. Methods: Beef meatball and pork meatball were determined by FTIR spectroscopy. The FTIR spectrum was used to detect pork in beef meatball combined with chemometrics method such as partial least square (PLS) and principal component analysis (PCA). Results: In this study, we developed FTIR spectroscopy using multivariate chemometrics. Chemometrics which is used is PLS to analyze pork in beef meatball, and PCA is used to classify pork and beef in meatball. The result PLS is linear regression equation which is a relationship between actual value and FTIR predicted value, y = 0.9984x + 0.0758 with a determination coefficient (R2) 0.9984. Root mean square error calibration (RMSEC) is 1.09%, root mean square external error calibration is 0.04%, and root mean square error external cross-validation is 0.48%. PCA successfully used to classify meatball in the market between beef meatball and pork meatball. Conclusion: Result of pork detection in meat meatballs using FTIR has determination coefficient of 0.9984 with RMSEC of 1.09%. Pork meatball and Beef meatballs can be distinguished using the chemometrics method.</description><identifier>ISSN: 0973-8258</identifier><identifier>EISSN: 1998-4103</identifier><identifier>DOI: 10.22377/ijgp.v12i03.1945</identifier><language>eng</language><publisher>Mandsaur: Mandsaur Institute of Pharmacy, Mandsaur University Campus</publisher><subject>Beef ; Pork ; Spectrum analysis</subject><ispartof>International journal of green pharmacy, 2018-07, Vol.12 (3)</ispartof><rights>Copyright Mandsaur Institute of Pharmacy, Mandsaur University Campus 2018</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Guntarti, A</creatorcontrib><title>Fourier-transform infrared spectroscopy combined with chemometrics for detection of pork in beef meatball formulation</title><title>International journal of green pharmacy</title><description>Objective: This research focused to analyze the pork content in beef meatball. Pork analysis in beef meatball using Fourier-transform infrared (FTIR) spectroscopy combined with chemometrics. Methods: Beef meatball and pork meatball were determined by FTIR spectroscopy. The FTIR spectrum was used to detect pork in beef meatball combined with chemometrics method such as partial least square (PLS) and principal component analysis (PCA). Results: In this study, we developed FTIR spectroscopy using multivariate chemometrics. Chemometrics which is used is PLS to analyze pork in beef meatball, and PCA is used to classify pork and beef in meatball. The result PLS is linear regression equation which is a relationship between actual value and FTIR predicted value, y = 0.9984x + 0.0758 with a determination coefficient (R2) 0.9984. Root mean square error calibration (RMSEC) is 1.09%, root mean square external error calibration is 0.04%, and root mean square error external cross-validation is 0.48%. PCA successfully used to classify meatball in the market between beef meatball and pork meatball. Conclusion: Result of pork detection in meat meatballs using FTIR has determination coefficient of 0.9984 with RMSEC of 1.09%. Pork meatball and Beef meatballs can be distinguished using the chemometrics method.</description><subject>Beef</subject><subject>Pork</subject><subject>Spectrum analysis</subject><issn>0973-8258</issn><issn>1998-4103</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNotj01LAzEYhIMoWKs_wFvA89a8yW4-jlKsFQpeei9JNrGpu5s1ySr-e7foaWB4ZoZB6B7IilImxGM4vY-rL6CBsBWourlAC1BKVjUQdokWRAlWSdrIa3ST84kQToGKBZo2cUrBpaokPWQfU4_D4JNOrsV5dLakmG0cf7CNvQnD7H6HcsT26PrYu5KCzXhO4daVGQ5xwNHjMaaPuQYb5zzunS5Gd90Z66dOn6FbdOV1l93dvy7RfvO8X2-r3dvL6_ppV41KlsoRaS0FBbblxnHJeANG1krWjaW-kQBKGg1ECFo7TxVrPVfEECt8zWowbIke_mrHFD8nl8vhNL8d5sUDBU6IUoJw9gvMOGDV</recordid><startdate>20180701</startdate><enddate>20180701</enddate><creator>Guntarti, A</creator><general>Mandsaur Institute of Pharmacy, Mandsaur University Campus</general><scope>3V.</scope><scope>7XB</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BVBZV</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>M2O</scope><scope>MBDVC</scope><scope>PADUT</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope></search><sort><creationdate>20180701</creationdate><title>Fourier-transform infrared spectroscopy combined with chemometrics for detection of pork in beef meatball formulation</title><author>Guntarti, A</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p98t-e08cc2191cd6be683651b849845c2f581198ba107724ef293df690b0c7f4341b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Beef</topic><topic>Pork</topic><topic>Spectrum analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Guntarti, A</creatorcontrib><collection>ProQuest Central (Corporate)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>East & South Asia Database</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>Research Library</collection><collection>Research Library (Corporate)</collection><collection>Research Library China</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 Basic</collection><jtitle>International journal of green pharmacy</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Guntarti, A</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fourier-transform infrared spectroscopy combined with chemometrics for detection of pork in beef meatball formulation</atitle><jtitle>International journal of green pharmacy</jtitle><date>2018-07-01</date><risdate>2018</risdate><volume>12</volume><issue>3</issue><issn>0973-8258</issn><eissn>1998-4103</eissn><abstract>Objective: This research focused to analyze the pork content in beef meatball. Pork analysis in beef meatball using Fourier-transform infrared (FTIR) spectroscopy combined with chemometrics. Methods: Beef meatball and pork meatball were determined by FTIR spectroscopy. The FTIR spectrum was used to detect pork in beef meatball combined with chemometrics method such as partial least square (PLS) and principal component analysis (PCA). Results: In this study, we developed FTIR spectroscopy using multivariate chemometrics. Chemometrics which is used is PLS to analyze pork in beef meatball, and PCA is used to classify pork and beef in meatball. The result PLS is linear regression equation which is a relationship between actual value and FTIR predicted value, y = 0.9984x + 0.0758 with a determination coefficient (R2) 0.9984. Root mean square error calibration (RMSEC) is 1.09%, root mean square external error calibration is 0.04%, and root mean square error external cross-validation is 0.48%. PCA successfully used to classify meatball in the market between beef meatball and pork meatball. Conclusion: Result of pork detection in meat meatballs using FTIR has determination coefficient of 0.9984 with RMSEC of 1.09%. Pork meatball and Beef meatballs can be distinguished using the chemometrics method.</abstract><cop>Mandsaur</cop><pub>Mandsaur Institute of Pharmacy, Mandsaur University Campus</pub><doi>10.22377/ijgp.v12i03.1945</doi><oa>free_for_read</oa></addata></record> |
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subjects | Beef Pork Spectrum analysis |
title | Fourier-transform infrared spectroscopy combined with chemometrics for detection of pork in beef meatball formulation |
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