【摘要】：隨著畜禽肉和肉制品食用量的迅速增長(zhǎng),人們對(duì)肉品質(zhì)量提出了更高的要求;對(duì)于肉制品,消費(fèi)者最為關(guān)心是肉品質(zhì)量,當(dāng)前中國(guó)對(duì)肉品品質(zhì)在線檢測(cè)方面的研究和應(yīng)用則相對(duì)較少,尚無(wú)針對(duì)肉品品質(zhì)在線無(wú)損檢測(cè)開(kāi)發(fā)的設(shè)備。也沒(méi)能真正投入到肉品的生產(chǎn)加工過(guò)程。研究不同肉品脂肪的近紅外快速檢測(cè)模型。并采用標(biāo)準(zhǔn)化學(xué)方法進(jìn)行差異分析。通過(guò)近紅外技術(shù)對(duì)豬肉、牛肉、羊肉進(jìn)行掃描,采用國(guó)標(biāo)法(索氏提取法)對(duì)鮮肉脂肪含量進(jìn)行化學(xué)值的測(cè)定,以PLS(偏最小二乘法)作為建模方法,并通過(guò)不同的光譜預(yù)處理手段分別建立了豬牛羊肉的近紅外光譜參數(shù)與樣品的脂肪含量之間的對(duì)應(yīng)關(guān)系模型。結(jié)果表明,對(duì)于豬肉來(lái)說(shuō),選擇4 260~6 014cm~(-1)波段+一階導(dǎo)+Norris所建的模型效果最好,其校正相關(guān)系數(shù)和預(yù)測(cè)相關(guān)系數(shù)分別為0.955 6和0.961 6;對(duì)于牛肉來(lái)說(shuō),選擇5 226~7 343cm~(-1)波段+一階導(dǎo)+S-G所建的模型效果最好,其校正相關(guān)系數(shù)和預(yù)測(cè)相關(guān)系數(shù)分別為0.923 5和0.942 7;對(duì)于羊肉來(lái)說(shuō),選擇5 207~7 362cm~(-1)波段+一階導(dǎo)+Norris所建的模型效果最好,其校正相關(guān)系數(shù)和預(yù)測(cè)相關(guān)系數(shù)分別為0.915 7和0.939 6;對(duì)于鮮肉來(lái)說(shuō),選選用波段為5 156~6 065cm~(-1)+二階導(dǎo)+S-G所建模型效果最好,其校正相關(guān)系數(shù)和預(yù)測(cè)相關(guān)系數(shù)分別為0.916 3和0.919 4。以上所有模型的校正相關(guān)系數(shù)均大于0.91,模型都具有較高的精密度,符合不同肉制品在實(shí)際生產(chǎn)的需求,具有分析速度快、檢測(cè)成本低、分辨率高、無(wú)損的優(yōu)點(diǎn)。
[Abstract]:With the rapid increase in the consumption of livestock and poultry meat and meat products, people have put forward higher requirements for meat quality. For meat products, consumers are most concerned about meat quality. At present, the research and application of meat quality online inspection in China is relatively few, and there is no equipment developed for meat quality online nondestructive testing. Also did not really invest in the meat production and processing process. The near infrared fast detection model of fat in different meat products was studied. The difference analysis was carried out by standard chemical method. The pork, beef and mutton were scanned by near-infrared technique. The chemical value of fresh meat fat was determined by Soxhlet extraction method. PLS (partial least square method) was used as modeling method. The model of the relationship between the near infrared spectrum parameters and the fat content of pig beef and mutton was established by different spectral pretreatment methods. The results showed that, for pork, the model with the first order guide Norris in the band of 4 260 0 014 cm ~ (-1) was the best, its corrected correlation coefficient and predictive correlation coefficient were 0.955 6 and 0.961 6, respectively, while for beef, the correlation coefficient of correction and prediction were 0.955 6 and 0.961 6, respectively. The model established by selecting the first order guide S-G in the band of 5226 ~ (7 343cm ~ (-1) was the best, the calibration correlation coefficient and the predictive correlation coefficient were 0.923 5 and 0.942 7, respectively. For mutton, the model of the first order guide Norris in the band of 52077 367 cm ~ (-1) was the best. The corrected correlation coefficient and predicted correlation coefficient were 0.915 7 and 0.939 6, respectively, and for fresh meat, the model with second-order derivative S-G was the best, the calibration correlation coefficient and prediction correlation coefficient were 0.916 3 and 0.919 4, respectively. The calibration correlation coefficient of all the above models is greater than 0.91.The model has higher precision and meets the needs of different meat products in actual production. It has the advantages of fast analysis, low detection cost, high resolution and nondestructive.
【作者單位】： 山西出入境檢驗(yàn)檢疫局;中北大學(xué);
【基金】：山西省科技攻關(guān)項(xiàng)目(20150313015)資助
【分類(lèi)號(hào)】：O657.33;TS251.7

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