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

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15d猪肉TVB-N含量与冷藏时间成J型变化规律,而TVC与冷藏...

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

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 (Rp) were 0.957 2 and 0.968 2, the standard errors of prediction (SEP) were 2.802 5 mg/100 g and 0.332 7 (lg(CFU/g)), the relative percent deviation (RPD) was 3.093 7 and 3.434 1, the correlation coefficients of external validation set were 0.928 3 and 0.930 5, and the standard errors were 3.556 2 mg/100 g and 0.515 7 (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.