Rapid Identification of Amino Acid Contents in Wuzhumuqin Sheep Meat by Near Infrared Spectroscopy
ZHAO Cun, XIE Yuchun, YANG Feng, CHE Tianyu, SU Xin, GUO Juntao, YONG Quan, LIU Zhihong, WANG Zhixin, LI Jinquan
1. Goat Genetics and Breeding Technology Research Center, Inner Mongolia Autonomous Region, Key Laboratory of Mutton Sheep Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Key Laboratory of Animal Genetics, Breeding and Reproduction, Inner Mongolia Autonomous Region, College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China; 2.Animal Disease Prevention and Control Center of East Wuzhumuqin Banner, Xilingol 026000, China
摘要利用近红外光谱分析技术快速检测乌珠穆沁羊肉中不同氨基酸含量。选取42 只相同饲喂条件、体质量相近的6 月龄乌珠穆沁羊，采集背最长肌、臂三头肌、股二头肌3 个部位共126 块肌肉样本，采集样本近红外光谱并测定氨基酸含量。采用偏最小二乘法关联光谱与氨基酸数据，建立乌珠穆沁羊肉中17 种氨基酸的定量预测模型，最后以模型交叉验证均方根及校正决定系数（R2校正）、验证决定系数（R2验证）、预测模型的验证集标准偏差与预测标准偏差比值（ratio of standard deviation of the validation set to standard error of prediction，RPD）作为评价模型的参数。结果表明：所建立的氨基酸含量预测模型准确度较高，其中总氨基酸（total amino acid，TTA）、必需氨基酸（essential amino acid，EAA）、组氨酸、赖氨酸含量的近红外光谱预测模型的R2验证分别为0.818、0.803、0.861和0.858。分别对预测模型进行外部验证，其中EAA、组氨酸、精氨酸、丝氨酸、谷氨酸、甘氨酸、赖氨酸验证结果的RPD值均超过1.74，TAA验证结果的RPD值为2.60，预测模型准确度达到应用水平，可作为一种快速、准确测定羊肉中氨基酸含量的方法。
Abstract：The purpose of this study was to quickly detect the contents of various amino acids in mutton by near infrared spectroscopy. Forty-two 6-month-old Wuzhumuqin sheep with similar body mass under the same feeding conditions were slaughtered to collect 126 muscle samples of Longissimus dorsi, Triceps brachii and Biceps femoris. Near infrared spectra of these samples were collected and the contents of amino acids in them were measured using an amino acid analyzer. A model for the quantitative prediction of 17 amino acids in Wuzhumuqin sheep meat was established by establishing correlation between the spectral data and the amino acid data using partial least squares (PLS) regression. Finally, the performance of the model was evaluated by root mean square error of cross-validation, determination coefficient of calibration, determination coefficient of validation, and ratio of the standard deviation of the validation set to the standard error of prediction (RPD). The model established in this study presented high predictive accuracy, and the determination coefficients of validation for the contents of total amino acids (TTA), essential amino acids (EAA), histidine (His) and lysine (Lys) were 0.818, 0.803, 0.861 and 0.858, respectively. The external verification of the prediction model showed that the RPD values for EAA, histidine, arginine, serine, glutamic acid, glycine and lysine contents were all higher than 1.74, and the value for TAA content was 2.60. Due to its high accuracy, the prediction model is applicable to rapidly determine amino acid contents in mutton.
赵 存，谢遇春，杨 峰，车天宇，苏 馨，郭俊涛，永 泉，刘志红，王志新，李金泉. 近红外光谱快速检测乌珠穆沁羊肉氨基酸含量[J]. 肉类研究, 2020, 34(9): 46-51.
ZHAO Cun, XIE Yuchun, YANG Feng, CHE Tianyu, SU Xin, GUO Juntao, YONG Quan, LIU Zhihong, WANG Zhixin, LI Jinquan. Rapid Identification of Amino Acid Contents in Wuzhumuqin Sheep Meat by Near Infrared Spectroscopy. Meat Research, 2020, 34(9): 46-51.
2020, Vol. 34 
