CAJ | 학술논문

通过采集牛霖、牛柳、牛腩3个部位牛肉样品的近红外光谱并对其蛋白质、脂肪、水分和灰分等化学指标进行测定,应用偏最小二乘法分别建立蛋白质、脂肪、水分和灰分的校正模型。牛霖样品的灰分和水分校正模型相关系数分别为0.9843、0.9740,预测相关系数分别为0.9502、0.9342;牛柳样品的蛋白质和水分校正模型相关系数分别是0.9540、0.7752,预测相关系数分别为0.9500、0.9060;牛腩样品的灰分和脂肪校正模型相关系数分别是0.9746、0.9218,预测相关系数分别是0.9560、0.9233;牛霖和牛柳样品的水分总校正模型相关系数为0.7504,预测相关系数是0.9737;牛腩和牛霖样品的灰分总校正模型相关系数是0.8770,预测相关系数为0.9777。结果表明：近红外光谱分析法预测准确度较高,可以用于评价牛肉品质。
통과채집우림、우류、우남3개부위우육양품적근홍외광보병대기단백질、지방、수분화회분등화학지표진행측정,응용편최소이승법분별건립단백질、지방、수분화회분적교정모형。우림양품적회분화수분교정모형상관계수분별위0.9843、0.9740,예측상관계수분별위0.9502、0.9342;우류양품적단백질화수분교정모형상관계수분별시0.9540、0.7752,예측상관계수분별위0.9500、0.9060;우남양품적회분화지방교정모형상관계수분별시0.9746、0.9218,예측상관계수분별시0.9560、0.9233;우림화우류양품적수분총교정모형상관계수위0.7504,예측상관계수시0.9737;우남화우림양품적회분총교정모형상관계수시0.8770,예측상관계수위0.9777。결과표명：근홍외광보분석법예측준학도교고,가이용우평개우육품질。
Beef thick flank,fillet and brisket were scanned using a near infrared spectrophotometer and their chemical parameters such as protein,fat,water and ash were measured.A calibration model for each of these parameters was set up by means of partial least squares（PLS） regression.The correlation coefficients of calibration for ash and water contents in beef thick flank were 0.9843 and 0.9740,respectively,and the correlation coefficients of validation were 0.9502 and 0.9342,respectively.The correlation coefficients of calibration for protein and water contents in beef fillet were 0.9540 and 0.7752,respectively,and the correlation coefficients of validation were 0.9500 and 0.9060,respectively.The correlation coefficients of calibration for ash and fat contents in beef brisket were 0.9746 and 0.9218,and the correlation coefficients of validation were 0.9560 and 0.9233,respectively.The correlation coefficients of calibration and validation for total water content in beef thick flank and fillet was 0.7504 and 0.9737,respectively,while those for total ash content in beef brisket and thick flank were 0.8770 and 0.9777,respectively.This study shows that near infrared spectroscopy allows accurate predictions of chemical parameters of beef and therefore can be used to evaluate beef quality.