Equations generated to predict iodine value of pork carcass back, belly, and jowl fat

Data from existing literature were used to generate equations to predict finishing pig back, belly, and jowl fat iodine values (IV) and an experiment was conducted to evaluate these equations. The final database included 24, 21, and 29 papers for back, belly, and jowl fat IV, respectively. For exper...

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Veröffentlicht in:Journal of animal science 2015-04, Vol.93 (4), p.1666-1678
Hauptverfasser: Paulk, C B, Bergstrom, J R, Tokach, M D, Dritz, S S, Burnett, D D, Stephenson, E W, Vaughn, M A, DeRouchey, J M, Goodband, R D, Nelssen, J L, Gonzalez, J M
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container_issue 4
container_start_page 1666
container_title Journal of animal science
container_volume 93
creator Paulk, C B
Bergstrom, J R
Tokach, M D
Dritz, S S
Burnett, D D
Stephenson, E W
Vaughn, M A
DeRouchey, J M
Goodband, R D
Nelssen, J L
Gonzalez, J M
description Data from existing literature were used to generate equations to predict finishing pig back, belly, and jowl fat iodine values (IV) and an experiment was conducted to evaluate these equations. The final database included 24, 21, and 29 papers for back, belly, and jowl fat IV, respectively. For experiments that changed dietary fatty acid composition, initial (INT) diets were defined as those fed before the change in diet composition and final (FIN) diets were those fed after. The predictor variables tested were divided into 5 groups: 1) diet fat composition (dietary percent C16:1, C18:1, C18:2, C18:3, EFA, unsaturated fatty acids, and IV product) for both INT and FIN diets, 2) day feeding the INT and FIN diets, 3) ME or NE of the INT and FIN diet, 4) live performance criteria (initial BW, final BW, ADG, ADFI, and G:F), and 5) carcass criteria (HCW and backfat thickness). The PROC MIXED procedure of SAS (SAS Inst., Inc., Cary, NC) was used to develop regression equations. Evaluation of models with significant terms was then conducted based on the Bayesian information criterion. The optimum equations to predict back, belly, and jowl fat IV were backfat IV = 84.83 + (6.87 × INT EFA) - (3.90 × FIN EFA) - (0.12 × INT days) - (1.30 × FIN days) - (0.11 × INT EFA × FIN days) + (0.048 × FIN EFA × INT days) + (0.12 × FIN EFA × FIN days) - (0.0060 × FIN NE) + (0.0005 × FIN NE × FIN days) - (0.26 × backfat depth); belly fat IV = 106.16 + (6.21 × INT EFA) - (1.50 × FIN days) - (0.11 × INT EFA × FIN days) - (0.012 × INT NE) + (0.00069 × INT NE × FIN days) - (0.18 × HCW) - (0.25 × backfat depth); and jowl fat IV = 85.50 + (1.08 × INT EFA) + (0.87 × FIN EFA) - (0.014 × INT days) - (0.050 × FIN days) + (0.038 × INT EFA × INT days) + (0.054 × FIN EFA × FIN days) - (0.0066 × INT NE) + (0.071 × INT BW) - (2.19 × ADFI) - (0.29 × backfat depth). Dietary treatments from the evaluation experiment consisted of a corn-soybean meal control diet with no added fat or a 3 × 3 factorial arrangement with main effects of fat source (4% tallow, 4% soybean oil, or a blend of 2% tallow and 2% soybean oil) and feeding duration (d 0 to 42, 42 to 84, or 0 to 84). The back, belly, and jowl fat IV equations tended to overestimate IV when observed IV were less than approximately 65 g/100 g and underestimate belly fat IV when actual IV are greater than approximately 74 g/100 g or when the fat blend was fed from d 0 to 84 or 42 to 84. Overall, with the exceptions noted, the regression equations were
doi_str_mv 10.2527/jas.2014-8400
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The final database included 24, 21, and 29 papers for back, belly, and jowl fat IV, respectively. For experiments that changed dietary fatty acid composition, initial (INT) diets were defined as those fed before the change in diet composition and final (FIN) diets were those fed after. The predictor variables tested were divided into 5 groups: 1) diet fat composition (dietary percent C16:1, C18:1, C18:2, C18:3, EFA, unsaturated fatty acids, and IV product) for both INT and FIN diets, 2) day feeding the INT and FIN diets, 3) ME or NE of the INT and FIN diet, 4) live performance criteria (initial BW, final BW, ADG, ADFI, and G:F), and 5) carcass criteria (HCW and backfat thickness). The PROC MIXED procedure of SAS (SAS Inst., Inc., Cary, NC) was used to develop regression equations. Evaluation of models with significant terms was then conducted based on the Bayesian information criterion. The optimum equations to predict back, belly, and jowl fat IV were backfat IV = 84.83 + (6.87 × INT EFA) - (3.90 × FIN EFA) - (0.12 × INT days) - (1.30 × FIN days) - (0.11 × INT EFA × FIN days) + (0.048 × FIN EFA × INT days) + (0.12 × FIN EFA × FIN days) - (0.0060 × FIN NE) + (0.0005 × FIN NE × FIN days) - (0.26 × backfat depth); belly fat IV = 106.16 + (6.21 × INT EFA) - (1.50 × FIN days) - (0.11 × INT EFA × FIN days) - (0.012 × INT NE) + (0.00069 × INT NE × FIN days) - (0.18 × HCW) - (0.25 × backfat depth); and jowl fat IV = 85.50 + (1.08 × INT EFA) + (0.87 × FIN EFA) - (0.014 × INT days) - (0.050 × FIN days) + (0.038 × INT EFA × INT days) + (0.054 × FIN EFA × FIN days) - (0.0066 × INT NE) + (0.071 × INT BW) - (2.19 × ADFI) - (0.29 × backfat depth). Dietary treatments from the evaluation experiment consisted of a corn-soybean meal control diet with no added fat or a 3 × 3 factorial arrangement with main effects of fat source (4% tallow, 4% soybean oil, or a blend of 2% tallow and 2% soybean oil) and feeding duration (d 0 to 42, 42 to 84, or 0 to 84). The back, belly, and jowl fat IV equations tended to overestimate IV when observed IV were less than approximately 65 g/100 g and underestimate belly fat IV when actual IV are greater than approximately 74 g/100 g or when the fat blend was fed from d 0 to 84 or 42 to 84. Overall, with the exceptions noted, the regression equations were an accurate tool for predicting carcass fat quality based on dietary and pig performance factors.</description><identifier>EISSN: 1525-3163</identifier><identifier>DOI: 10.2527/jas.2014-8400</identifier><identifier>PMID: 26020188</identifier><language>eng</language><publisher>United States</publisher><subject>Abdomen ; Adipose Tissue - chemistry ; Animal Nutritional Physiological Phenomena - physiology ; Animals ; Back ; Bayes Theorem ; Body Composition - physiology ; Body Fat Distribution ; Cheek ; Diet - veterinary ; Female ; Iodine - analysis ; Male ; Models, Biological ; Models, Statistical ; Muscle, Skeletal - chemistry ; Regression Analysis ; Swine - physiology</subject><ispartof>Journal of animal science, 2015-04, Vol.93 (4), p.1666-1678</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26020188$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Paulk, C B</creatorcontrib><creatorcontrib>Bergstrom, J R</creatorcontrib><creatorcontrib>Tokach, M D</creatorcontrib><creatorcontrib>Dritz, S S</creatorcontrib><creatorcontrib>Burnett, D D</creatorcontrib><creatorcontrib>Stephenson, E W</creatorcontrib><creatorcontrib>Vaughn, M A</creatorcontrib><creatorcontrib>DeRouchey, J M</creatorcontrib><creatorcontrib>Goodband, R D</creatorcontrib><creatorcontrib>Nelssen, J L</creatorcontrib><creatorcontrib>Gonzalez, J M</creatorcontrib><title>Equations generated to predict iodine value of pork carcass back, belly, and jowl fat</title><title>Journal of animal science</title><addtitle>J Anim Sci</addtitle><description>Data from existing literature were used to generate equations to predict finishing pig back, belly, and jowl fat iodine values (IV) and an experiment was conducted to evaluate these equations. The final database included 24, 21, and 29 papers for back, belly, and jowl fat IV, respectively. For experiments that changed dietary fatty acid composition, initial (INT) diets were defined as those fed before the change in diet composition and final (FIN) diets were those fed after. The predictor variables tested were divided into 5 groups: 1) diet fat composition (dietary percent C16:1, C18:1, C18:2, C18:3, EFA, unsaturated fatty acids, and IV product) for both INT and FIN diets, 2) day feeding the INT and FIN diets, 3) ME or NE of the INT and FIN diet, 4) live performance criteria (initial BW, final BW, ADG, ADFI, and G:F), and 5) carcass criteria (HCW and backfat thickness). The PROC MIXED procedure of SAS (SAS Inst., Inc., Cary, NC) was used to develop regression equations. Evaluation of models with significant terms was then conducted based on the Bayesian information criterion. The optimum equations to predict back, belly, and jowl fat IV were backfat IV = 84.83 + (6.87 × INT EFA) - (3.90 × FIN EFA) - (0.12 × INT days) - (1.30 × FIN days) - (0.11 × INT EFA × FIN days) + (0.048 × FIN EFA × INT days) + (0.12 × FIN EFA × FIN days) - (0.0060 × FIN NE) + (0.0005 × FIN NE × FIN days) - (0.26 × backfat depth); belly fat IV = 106.16 + (6.21 × INT EFA) - (1.50 × FIN days) - (0.11 × INT EFA × FIN days) - (0.012 × INT NE) + (0.00069 × INT NE × FIN days) - (0.18 × HCW) - (0.25 × backfat depth); and jowl fat IV = 85.50 + (1.08 × INT EFA) + (0.87 × FIN EFA) - (0.014 × INT days) - (0.050 × FIN days) + (0.038 × INT EFA × INT days) + (0.054 × FIN EFA × FIN days) - (0.0066 × INT NE) + (0.071 × INT BW) - (2.19 × ADFI) - (0.29 × backfat depth). Dietary treatments from the evaluation experiment consisted of a corn-soybean meal control diet with no added fat or a 3 × 3 factorial arrangement with main effects of fat source (4% tallow, 4% soybean oil, or a blend of 2% tallow and 2% soybean oil) and feeding duration (d 0 to 42, 42 to 84, or 0 to 84). The back, belly, and jowl fat IV equations tended to overestimate IV when observed IV were less than approximately 65 g/100 g and underestimate belly fat IV when actual IV are greater than approximately 74 g/100 g or when the fat blend was fed from d 0 to 84 or 42 to 84. Overall, with the exceptions noted, the regression equations were an accurate tool for predicting carcass fat quality based on dietary and pig performance factors.</description><subject>Abdomen</subject><subject>Adipose Tissue - chemistry</subject><subject>Animal Nutritional Physiological Phenomena - physiology</subject><subject>Animals</subject><subject>Back</subject><subject>Bayes Theorem</subject><subject>Body Composition - physiology</subject><subject>Body Fat Distribution</subject><subject>Cheek</subject><subject>Diet - veterinary</subject><subject>Female</subject><subject>Iodine - analysis</subject><subject>Male</subject><subject>Models, Biological</subject><subject>Models, Statistical</subject><subject>Muscle, Skeletal - chemistry</subject><subject>Regression Analysis</subject><subject>Swine - physiology</subject><issn>1525-3163</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNo1kE1Lw0AYhBdBbK0evcoePTR1P7LJ5iilVaHgxZ7Du1-SNM2muxul_96A9TQwPMwMg9ADJSsmWPncQlwxQvNM5oRcoTkVTGScFnyGbmNsCaFMVOIGzVhBJk7KOdpvTiOkxvcRf9neBkjW4OTxEKxpdMKNN01v8Td0o8Xe4cGHA9YQNMSIFejDEivbdeclht7g1v902EG6Q9cOumjvL7pA--3mc_2W7T5e39cvu2xgkqZpZl5pYRRxpCilkYYbrlzuQFICophMo6hyiuQll1Qa4nKrq4KXilaak5Iv0NNf7hD8abQx1ccm6mkP9NaPsabFVMFLWYkJfbygozpaUw-hOUI41_9X8F_YRl2f</recordid><startdate>201504</startdate><enddate>201504</enddate><creator>Paulk, C B</creator><creator>Bergstrom, J R</creator><creator>Tokach, M D</creator><creator>Dritz, S S</creator><creator>Burnett, D D</creator><creator>Stephenson, E W</creator><creator>Vaughn, M A</creator><creator>DeRouchey, J M</creator><creator>Goodband, R D</creator><creator>Nelssen, J L</creator><creator>Gonzalez, J M</creator><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>7X8</scope></search><sort><creationdate>201504</creationdate><title>Equations generated to predict iodine value of pork carcass back, belly, and jowl fat</title><author>Paulk, C B ; Bergstrom, J R ; Tokach, M D ; Dritz, S S ; Burnett, D D ; Stephenson, E W ; Vaughn, M A ; DeRouchey, J M ; Goodband, R D ; Nelssen, J L ; Gonzalez, J M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p281t-8449c5db0f0678d8d3d3bf4fa810a56067db1bfb0473818d0f4ec9637b19c3073</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Abdomen</topic><topic>Adipose Tissue - chemistry</topic><topic>Animal Nutritional Physiological Phenomena - physiology</topic><topic>Animals</topic><topic>Back</topic><topic>Bayes Theorem</topic><topic>Body Composition - physiology</topic><topic>Body Fat Distribution</topic><topic>Cheek</topic><topic>Diet - veterinary</topic><topic>Female</topic><topic>Iodine - analysis</topic><topic>Male</topic><topic>Models, Biological</topic><topic>Models, Statistical</topic><topic>Muscle, Skeletal - chemistry</topic><topic>Regression Analysis</topic><topic>Swine - physiology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Paulk, C B</creatorcontrib><creatorcontrib>Bergstrom, J R</creatorcontrib><creatorcontrib>Tokach, M D</creatorcontrib><creatorcontrib>Dritz, S S</creatorcontrib><creatorcontrib>Burnett, D D</creatorcontrib><creatorcontrib>Stephenson, E W</creatorcontrib><creatorcontrib>Vaughn, M A</creatorcontrib><creatorcontrib>DeRouchey, J M</creatorcontrib><creatorcontrib>Goodband, R D</creatorcontrib><creatorcontrib>Nelssen, J L</creatorcontrib><creatorcontrib>Gonzalez, J M</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of animal science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Paulk, C B</au><au>Bergstrom, J R</au><au>Tokach, M D</au><au>Dritz, S S</au><au>Burnett, D D</au><au>Stephenson, E W</au><au>Vaughn, M A</au><au>DeRouchey, J M</au><au>Goodband, R D</au><au>Nelssen, J L</au><au>Gonzalez, J M</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Equations generated to predict iodine value of pork carcass back, belly, and jowl fat</atitle><jtitle>Journal of animal science</jtitle><addtitle>J Anim Sci</addtitle><date>2015-04</date><risdate>2015</risdate><volume>93</volume><issue>4</issue><spage>1666</spage><epage>1678</epage><pages>1666-1678</pages><eissn>1525-3163</eissn><abstract>Data from existing literature were used to generate equations to predict finishing pig back, belly, and jowl fat iodine values (IV) and an experiment was conducted to evaluate these equations. The final database included 24, 21, and 29 papers for back, belly, and jowl fat IV, respectively. For experiments that changed dietary fatty acid composition, initial (INT) diets were defined as those fed before the change in diet composition and final (FIN) diets were those fed after. The predictor variables tested were divided into 5 groups: 1) diet fat composition (dietary percent C16:1, C18:1, C18:2, C18:3, EFA, unsaturated fatty acids, and IV product) for both INT and FIN diets, 2) day feeding the INT and FIN diets, 3) ME or NE of the INT and FIN diet, 4) live performance criteria (initial BW, final BW, ADG, ADFI, and G:F), and 5) carcass criteria (HCW and backfat thickness). The PROC MIXED procedure of SAS (SAS Inst., Inc., Cary, NC) was used to develop regression equations. Evaluation of models with significant terms was then conducted based on the Bayesian information criterion. The optimum equations to predict back, belly, and jowl fat IV were backfat IV = 84.83 + (6.87 × INT EFA) - (3.90 × FIN EFA) - (0.12 × INT days) - (1.30 × FIN days) - (0.11 × INT EFA × FIN days) + (0.048 × FIN EFA × INT days) + (0.12 × FIN EFA × FIN days) - (0.0060 × FIN NE) + (0.0005 × FIN NE × FIN days) - (0.26 × backfat depth); belly fat IV = 106.16 + (6.21 × INT EFA) - (1.50 × FIN days) - (0.11 × INT EFA × FIN days) - (0.012 × INT NE) + (0.00069 × INT NE × FIN days) - (0.18 × HCW) - (0.25 × backfat depth); and jowl fat IV = 85.50 + (1.08 × INT EFA) + (0.87 × FIN EFA) - (0.014 × INT days) - (0.050 × FIN days) + (0.038 × INT EFA × INT days) + (0.054 × FIN EFA × FIN days) - (0.0066 × INT NE) + (0.071 × INT BW) - (2.19 × ADFI) - (0.29 × backfat depth). Dietary treatments from the evaluation experiment consisted of a corn-soybean meal control diet with no added fat or a 3 × 3 factorial arrangement with main effects of fat source (4% tallow, 4% soybean oil, or a blend of 2% tallow and 2% soybean oil) and feeding duration (d 0 to 42, 42 to 84, or 0 to 84). The back, belly, and jowl fat IV equations tended to overestimate IV when observed IV were less than approximately 65 g/100 g and underestimate belly fat IV when actual IV are greater than approximately 74 g/100 g or when the fat blend was fed from d 0 to 84 or 42 to 84. Overall, with the exceptions noted, the regression equations were an accurate tool for predicting carcass fat quality based on dietary and pig performance factors.</abstract><cop>United States</cop><pmid>26020188</pmid><doi>10.2527/jas.2014-8400</doi><tpages>13</tpages></addata></record>
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source MEDLINE; Oxford University Press Journals All Titles (1996-Current)
subjects Abdomen
Adipose Tissue - chemistry
Animal Nutritional Physiological Phenomena - physiology
Animals
Back
Bayes Theorem
Body Composition - physiology
Body Fat Distribution
Cheek
Diet - veterinary
Female
Iodine - analysis
Male
Models, Biological
Models, Statistical
Muscle, Skeletal - chemistry
Regression Analysis
Swine - physiology
title Equations generated to predict iodine value of pork carcass back, belly, and jowl fat
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