基于高光谱反射特性的猪肉新鲜度和腐败程度的对比分析

Comparative Analysis of Pork Freshness and Spoilage Based on Hyperspectral Reflection Characteristics

为有效评价猪肉在贮藏过程中的品质变化,分析相同猪肉样品在相同环境条件下挥发性盐基氮(total volatile basic nitrogen,TVB-N)含量与菌落总数(total viable count,TVC)的变化规律。结果显示,在4℃冷藏15 d猪肉TVB-N含量与冷藏时间成“J”型变化规律,而TVC与冷藏时间成“S”变化规律。当TVB-N含量在第7.5天达到国家标准规定新鲜度限定值(15 mg/100 g)时,TVC已远超国家标准限定值(6(lg(CFU/g))),达到7.92(lg(CFU/g))。当TVC在第5.5天达到国家标准限定值时,TVB-N含量仅为10.65 mg/100 g;即在相同贮藏条件下,依据国标TVC指标判定猪肉为“腐败肉”时,而根据TVB-N含量猪肉仍被判定为“新鲜肉”。在此基础上,利用可见-短波近红外高光谱反射技术采集猪肉高光谱数据,建立不同预处理的TVB-N含量与TVC偏最小二乘回归模型。结果表明,利用多元散射校正预处理建立的TVB-N含量模型与1阶导数预处理建立的TVC模型预测效果最好。R_(p)分别为0.9572与0.9682,预测集标准误差分别为2.8025 mg/100 g与0.3327(lg(CFU/g)),实测值的标准偏差与预测集的标准误差比值分别为3.0937和3.4341;外部验证集相关系数分别为0.9283与0.9305,标准误差分别为3.5562 mg/100 g和0.5157(lg(CFU/g))。本研究能为高光谱技术更好地应用于猪肉的品质检测提供一定理论依据。

The quality change of pork during storage was evaluated by measuring the changes in total volatile basic nitrogen(TVB-N)content and total viable count(TVC).The results showed that TVB-N content of pork refrigerated for up to 15 days at 4℃exhibited a J-shaped curve,while TVC exhibited an S-shaped curve.On day 15,TVB-N content reached the maximum limit for freshness stipulated in the national standard(15 mg/100 g),while TVC reached 7.92(lg(CFU/g)),far higher than the maximum limit stipulated in the national standard,6(lg(CFU/g)).While TVC reached 6(lg(CFU/g))on day 5.5,TVB-N content was only 10.65 mg/100 g.Pork meat judged to be spoiled meat based on TVC was found to be still fresh according to TVB-N content.Furthermore,visible short-wave near-infrared hyperspectral reflection technology was used to collect hyperspectral data for pork samples,and partial least squares regression(PLSR)models for the prediction of TVB-N content and TVC were established using different spectral pretreatments.The results showed that the model established using multiplicative scatter correction(MSC)preprocessing displayed the best prediction performance for TVB-N content,while the model established using first derivative preprocessing exhibited the best prediction performance for TVC.The correlation coefficients of prediction set(R_(p))were 0.9572 and 0.9682,the standard errors of prediction(SEP)were 2.8025 mg/100 g and 0.3327(lg(CFU/g)),the relative percent deviation(RPD)was 3.0937 and 3.4341,the correlation coefficients of external validation set were 0.9283 and 0.9305,and the standard errors were 3.5562 mg/100 g and 0.5157(lg(CFU/g))for the TVB-N and TVC prediction models, respectively. In conclusion, this study can provide a theoretical basis for better application of hyperspectral technology in pork quality detection.