肉类研究
肉類研究
육류연구
MEAT RESEARCH
2012年
5期
6-9
,共4页
张宏博%李云%靳烨%袁倩%贾雪晖
張宏博%李雲%靳燁%袁倩%賈雪暉
장굉박%리운%근엽%원천%가설휘
巴美肉羊%净肉质量%净肉率%预测回归方程
巴美肉羊%淨肉質量%淨肉率%預測迴歸方程
파미육양%정육질량%정육솔%예측회귀방정
Bamei lamb%retail product weight%retail product weight percent%predicted regression model
在羊肉生产加工的屠宰线上,为了较快地预测胴体净肉质量和净肉率,并按照不同产肉性能对肉羊胴体进行等级划分,以建立科学合理的优质优价收购体系,本实验选取30头4~8月龄巴美肉羊,对其进行屠宰、冷却、分割,并分别测定其宰前羊体活质量(X1)、热胴体质量(X2)、眼肌面积(X3)、背肉厚度(X4)等指标。将数据采用SPSS 16.0软件进行相关分析和线性回归,最终得到以X1、X2和X3三因子共同预测净肉质量(Y1)的线性方程Y1=-1.113+1.088X2-0.141X1-0.004X3(R2=0.996)和预测净肉率(Y2)的线性方程Y2=31.187+2.362X2-1.090X1+0.068X3(R2=0.920),结果表明这两个方程均可在实际生产中用于巴美肉羊净肉质量和净肉率的预测。
在羊肉生產加工的屠宰線上,為瞭較快地預測胴體淨肉質量和淨肉率,併按照不同產肉性能對肉羊胴體進行等級劃分,以建立科學閤理的優質優價收購體繫,本實驗選取30頭4~8月齡巴美肉羊,對其進行屠宰、冷卻、分割,併分彆測定其宰前羊體活質量(X1)、熱胴體質量(X2)、眼肌麵積(X3)、揹肉厚度(X4)等指標。將數據採用SPSS 16.0軟件進行相關分析和線性迴歸,最終得到以X1、X2和X3三因子共同預測淨肉質量(Y1)的線性方程Y1=-1.113+1.088X2-0.141X1-0.004X3(R2=0.996)和預測淨肉率(Y2)的線性方程Y2=31.187+2.362X2-1.090X1+0.068X3(R2=0.920),結果錶明這兩箇方程均可在實際生產中用于巴美肉羊淨肉質量和淨肉率的預測。
재양육생산가공적도재선상,위료교쾌지예측동체정육질량화정육솔,병안조불동산육성능대육양동체진행등급화분,이건립과학합리적우질우개수구체계,본실험선취30두4~8월령파미육양,대기진행도재、냉각、분할,병분별측정기재전양체활질량(X1)、열동체질량(X2)、안기면적(X3)、배육후도(X4)등지표。장수거채용SPSS 16.0연건진행상관분석화선성회귀,최종득도이X1、X2화X3삼인자공동예측정육질량(Y1)적선성방정Y1=-1.113+1.088X2-0.141X1-0.004X3(R2=0.996)화예측정육솔(Y2)적선성방정Y2=31.187+2.362X2-1.090X1+0.068X3(R2=0.920),결과표명저량개방정균가재실제생산중용우파미육양정육질량화정육솔적예측。
This study was conducted to establish mathematical models for quick prediction of retail product weight and percentage on lamb slaughtering line with the aim of providing references for lamb carcass grading for high-quality favorable-price purchase. Thirty Bamei lambs aged 4--8 months were selected for slaughtering, chilling and cutting. Pre-slaughter body weight (X1), warm carcass weight (X2), loin eye area (X3) and back meat thickness (X4) were determined. Correlation analysis and linear regression analysis were carried out with SPSS 16.0 software. A linear equation for retail product weight (Y1) or retail product percentage (Y2) as a function of pre-slaughter body weight (X1), warm carcass weight (X2), loin eye area (X3) was obtained as Y1= - 1.113 + 1.088X2 - 0.141X1 - 0.004X3(R^2 = 0.996) and Y2 = 31.187 + 2.362X2 -- 1.090X1 + 0.068X3(R^2= 0.920), respectively. It was found that both equations could be used to predict retail product weight and percentage in Bamei lamb.