Practical means for estimating pork carcass composition
Three hundred sixty-one market-weight barrow and gilt carcasses were physically dissected into bone, skin, fat and muscle. A three-variable multiple linear regression equation containing the same independent variables (warm carcass weight, 10th rib loin muscle area and 10th rib fat depth) used (U.S....
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| Veröffentlicht in: | Journal of animal science 1990-12, Vol.68 (12), p.3987-3997 |
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| container_issue | 12 |
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| container_title | Journal of animal science |
| container_volume | 68 |
| creator | Orcutt, M.W. (Viskase Corporation, Chicago, IL) Forrest, J.C Judge, M.D Schinckel, A.P Kuei, C.H |
| description | Three hundred sixty-one market-weight barrow and gilt carcasses were physically dissected into bone, skin, fat and muscle. A three-variable multiple linear regression equation containing the same independent variables (warm carcass weight, 10th rib loin muscle area and 10th rib fat depth) used (U.S.) to determine pork carcass lean weight was found to be the most practical means for predicting weight of muscle standardized to 10% fat. Multiple linear regression equations containing more than three independent variables produced only slight improvements in R2 values; however, the standard deviation about the regression line was not greatly improved by the addition of more independent variables to this three-independent-variable regression model. A single multiple linear regression equation using the three independent variables above may not be adequate to describe variation over the entire live-weight range for all hogs marketed in the U.S. For most accurate muscle weight prediction, different equations should be used for weight subclasses with one equation for carcasses under 100 kg and another for those heavier than 100 kg. A single prediction equation for muscle weight was adequate for carcasses of both barrows and gilts. |
| doi_str_mv | 10.2527/1990.68123987x |
| format | Article |
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(Viskase Corporation, Chicago, IL) ; Forrest, J.C ; Judge, M.D ; Schinckel, A.P ; Kuei, C.H</creator><creatorcontrib>Orcutt, M.W. (Viskase Corporation, Chicago, IL) ; Forrest, J.C ; Judge, M.D ; Schinckel, A.P ; Kuei, C.H</creatorcontrib><description>Three hundred sixty-one market-weight barrow and gilt carcasses were physically dissected into bone, skin, fat and muscle. A three-variable multiple linear regression equation containing the same independent variables (warm carcass weight, 10th rib loin muscle area and 10th rib fat depth) used (U.S.) to determine pork carcass lean weight was found to be the most practical means for predicting weight of muscle standardized to 10% fat. Multiple linear regression equations containing more than three independent variables produced only slight improvements in R2 values; however, the standard deviation about the regression line was not greatly improved by the addition of more independent variables to this three-independent-variable regression model. A single multiple linear regression equation using the three independent variables above may not be adequate to describe variation over the entire live-weight range for all hogs marketed in the U.S. For most accurate muscle weight prediction, different equations should be used for weight subclasses with one equation for carcasses under 100 kg and another for those heavier than 100 kg. A single prediction equation for muscle weight was adequate for carcasses of both barrows and gilts.</description><identifier>ISSN: 0021-8812</identifier><identifier>EISSN: 1525-3163</identifier><identifier>DOI: 10.2527/1990.68123987x</identifier><identifier>PMID: 2286542</identifier><language>eng</language><publisher>Savoy, IL: Am Soc Animal Sci</publisher><subject>Adipose Tissue - anatomy & histology ; Animals ; Biological and medical sciences ; BODY LEAN MASS ; CANAL ANIMAL ; CARCASS COMPOSITION ; CARCASSE ; CARCASSES ; CERDO ; COMPOSICION DE LA CANAL ; COMPOSITION DE LA CARCASSE ; ESTIMATION ; Female ; Food industries ; Fundamental and applied biological sciences. Psychology ; Male ; Meat - standards ; Meat and meat product industries ; MEAT YIELD ; Muscles - anatomy & histology ; Organ Size ; PESO ; POIDS ; PORCIN ; Regression Analysis ; RENDEMENT EN VIANDE ; RENDIMIENTO CARNICO ; SWINE ; Swine - anatomy & histology ; WEIGHT</subject><ispartof>Journal of animal science, 1990-12, Vol.68 (12), p.3987-3997</ispartof><rights>1991 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c371t-840f6cfea6818acd4d346b6d9e2ccef6c419f8411aaaf785fbe76ce4ac42f233</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,778,782,27907,27908</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=19745586$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/2286542$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Orcutt, M.W. 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Multiple linear regression equations containing more than three independent variables produced only slight improvements in R2 values; however, the standard deviation about the regression line was not greatly improved by the addition of more independent variables to this three-independent-variable regression model. A single multiple linear regression equation using the three independent variables above may not be adequate to describe variation over the entire live-weight range for all hogs marketed in the U.S. For most accurate muscle weight prediction, different equations should be used for weight subclasses with one equation for carcasses under 100 kg and another for those heavier than 100 kg. A single prediction equation for muscle weight was adequate for carcasses of both barrows and gilts.</description><subject>Adipose Tissue - anatomy & histology</subject><subject>Animals</subject><subject>Biological and medical sciences</subject><subject>BODY LEAN MASS</subject><subject>CANAL ANIMAL</subject><subject>CARCASS COMPOSITION</subject><subject>CARCASSE</subject><subject>CARCASSES</subject><subject>CERDO</subject><subject>COMPOSICION DE LA CANAL</subject><subject>COMPOSITION DE LA CARCASSE</subject><subject>ESTIMATION</subject><subject>Female</subject><subject>Food industries</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Male</subject><subject>Meat - standards</subject><subject>Meat and meat product industries</subject><subject>MEAT YIELD</subject><subject>Muscles - anatomy & histology</subject><subject>Organ Size</subject><subject>PESO</subject><subject>POIDS</subject><subject>PORCIN</subject><subject>Regression Analysis</subject><subject>RENDEMENT EN VIANDE</subject><subject>RENDIMIENTO CARNICO</subject><subject>SWINE</subject><subject>Swine - anatomy & histology</subject><subject>WEIGHT</subject><issn>0021-8812</issn><issn>1525-3163</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1990</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpFkEtLAzEURoMoWh9bF4IwG3U1Ne9JllJ8gaCgrsNtmtTozKQmU9R_b0qLru7iOzn35kPomOAxFbS5JFrjsVSEMq2a7y00IoKKmhHJttEIY0pqVcI9tJ_zO8aECi120S6lSgpOR6h5SmCHYKGtOgd9rnxMlctD6GAI_bxaxPRRWUgWcq5s7BYxhyHE_hDteGizO9rMA_Ryc_0yuasfHm_vJ1cPtWUNGWrFsZfWOygXKrAzPmNcTuVMO2qtKxEn2itOCAD4Rgk_dY20joPl1FPGDtD5WrtI8XNZ7jJdyNa1LfQuLrNRmAqONS3geA3aFHNOzptFKn9IP4ZgsyrKrIoyf0WVB6cb83Laudkfvmmm5GebHHJpxyfobcj_Vt1wIZQs3MWaewvzt6-QnMkdtG2xEvMOWSpDqFmtLOTJmvQQDcxTsb0-a0KYEJz9Anuahj0</recordid><startdate>19901201</startdate><enddate>19901201</enddate><creator>Orcutt, M.W. 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Multiple linear regression equations containing more than three independent variables produced only slight improvements in R2 values; however, the standard deviation about the regression line was not greatly improved by the addition of more independent variables to this three-independent-variable regression model. A single multiple linear regression equation using the three independent variables above may not be adequate to describe variation over the entire live-weight range for all hogs marketed in the U.S. For most accurate muscle weight prediction, different equations should be used for weight subclasses with one equation for carcasses under 100 kg and another for those heavier than 100 kg. A single prediction equation for muscle weight was adequate for carcasses of both barrows and gilts.</abstract><cop>Savoy, IL</cop><pub>Am Soc Animal Sci</pub><pmid>2286542</pmid><doi>10.2527/1990.68123987x</doi><tpages>11</tpages></addata></record> |
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| subjects | Adipose Tissue - anatomy & histology Animals Biological and medical sciences BODY LEAN MASS CANAL ANIMAL CARCASS COMPOSITION CARCASSE CARCASSES CERDO COMPOSICION DE LA CANAL COMPOSITION DE LA CARCASSE ESTIMATION Female Food industries Fundamental and applied biological sciences. Psychology Male Meat - standards Meat and meat product industries MEAT YIELD Muscles - anatomy & histology Organ Size PESO POIDS PORCIN Regression Analysis RENDEMENT EN VIANDE RENDIMIENTO CARNICO SWINE Swine - anatomy & histology WEIGHT |
| title | Practical means for estimating pork carcass composition |
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