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作 者:李业国[1] 周光宏[2] 高峰[1] 徐幸莲[2] 张楠[2]
机构地区:[1]南京农业大学动物科技学院 [2]南京农业大学农业部农畜产品加工与质量控制重点开放实验室,南京210095
出 处:《中国农学通报》2006年第2期5-8,共4页Chinese Agricultural Science Bulletin
基 金:国家科技攻关项目"肉制品加工关键技术研发与新产品开发("2001BA501A11);江苏省科技攻关项目(BE2004314);江苏省攻关招标项目(BS2002051)。
摘 要:为实现优质优价的生猪收购体系,屠宰线上快速预测胴体的瘦肉率,选择6月龄左右阉割的良种杂交商品猪114头,分别测其瘦肉率、热胴体重、背膘厚度等指标。以瘦肉率为因变量,其它指标为自变量,采用SAS8.2软件建立了预测良种杂交猪胴体瘦肉率不同变量的回归方程。结果表明,多元线性方程y=58.496-0.1046x1-0.513x7+0.273x10(R2=0.8290,RMSE=2.07336)能很好的拟合良种杂交猪的胴体瘦肉率,腰荐膘厚(x7)、M厚度(指臀中肌末端到脊髓管边缘处距离,x10)被选为良种杂交商品猪分级中需要直尺测量的2个指标。In order to predict pig carcasses lean-percentage as soon as possible on the slaughtering line, finally the price policy that much content lean with a little fat carcass will be pay much money and little content lean with much fat will be pay a little money is coming true. This study was to assess carcass lean-percentage (y) calibration equation on crossbreed of ab extra pigs, and indexes which measured were chosen for pig carcases grading. Number of 114 samples about half yearly age was selected in this study. The usual predictors have been used: hot carcass weight, backfat of different parts and other characteristics measured on each carcass with ruler. By commercial cutting, multiple regression analysis of dissectible lean meat (%) on linear form based on the variables with different indexes was performed by SAS (SAS version 8.2). The results suggested that the seventh equation: y=58.496-0.1046 x1-0.513 x7+0.273 x10 is the best multiple linear regression prediction model,in the model R2 is 0.8290 and RMSE is 2.07336. Backfat between sacrum & lumbar vertebra (x7) and M (M is the distance between the end of musculus gluteus medius and the edge of spinal cord canal ,x10)will be measured by ruler for pig carcasses grading in the future.
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