【摘要】：揮發(fā)性鹽基氮(TVB-N)含量是評(píng)價(jià)豬肉新鮮度的重要理化指標(biāo)。為了實(shí)現(xiàn)快速、無(wú)損檢測(cè)豬肉的新鮮度,優(yōu)選出與豬肉中TVB-N含量相關(guān)的特征波長(zhǎng),將包含特征波長(zhǎng)的發(fā)光二極管(LED)光源用于多光譜檢測(cè)系統(tǒng),測(cè)定了豬肉中TVB-N的含量。首先利用可見(jiàn)-近紅外(VIS-NIR)高光譜系統(tǒng)對(duì)豬肉進(jìn)行檢測(cè),獲取高光譜反射率數(shù)據(jù),并采用一階導(dǎo)數(shù)(FD)法、標(biāo)準(zhǔn)正態(tài)變量變換(SNV)以及其他預(yù)處理方法建立豬肉中TVB-N含量的偏最小二乘回歸(PLSR)模型;然后分別利用逐步回歸算法(SWA)、連續(xù)投影算法(SPA)、基因遺傳算法(GA)篩選出與TVB-N含量相關(guān)的特征波長(zhǎng),利用篩選出的特征波長(zhǎng)分別建立PLSR模型與多元線性回歸(MLR)模型,比較模型結(jié)果后進(jìn)一步優(yōu)選特征波長(zhǎng);最后,將含有特征波長(zhǎng)的LED光源用于多光譜檢測(cè)系統(tǒng),并建立PLSR模型與MLR模型,從而完成對(duì)豬肉中TVB-N含量的測(cè)定。實(shí)驗(yàn)結(jié)果表明:利用SWA、SPA、GA這3種算法篩選出的特征波長(zhǎng)能夠很好地反映全光譜的信息,建立的模型效果較好,變量數(shù)大大減少;包含優(yōu)選特征波長(zhǎng)的LED光源在多光譜檢測(cè)系統(tǒng)中能很好地檢測(cè)豬肉中的TVB-N含量;MLR模型結(jié)果好于PLSR模型結(jié)果,MLR模型的校正集相關(guān)系數(shù)和校正集均方根誤差分別為0.9050和3.63×10-5,預(yù)測(cè)集相關(guān)系數(shù)和預(yù)測(cè)集均方根誤差分別為0.9040和3.81×10-5。
[Abstract]:Volatile base nitrogen (TVB-N) content is an important physical and chemical index to evaluate the freshness of pork. In order to realize fast and nondestructive detection of pork freshness, the characteristic wavelengths related to the content of TVB-N in pork were selected. The light-emitting diode (LED) light source containing characteristic wavelength was used in the multispectral detection system to determine the content of TVB-N in pork. Firstly, the hyperspectral reflectance data of pork were detected by using VIS-NIR hyperspectral system, and the first derivative (FD) method was used to obtain the hyperspectral reflectance data. The partial least squares regression (PLSR) model of TVB-N content in pork was established by standard normal variable transformation (SNV) and other pretreatment methods. Then the stepwise regression algorithm (SWA), continuous projection algorithm (SPA), gene genetic algorithm (GA) was used to screen the characteristic wavelengths related to the TVB-N content. The PLSR model and the multivariate linear regression (MLR) model were established by using the selected characteristic wavelengths. Finally, the LED light source with characteristic wavelength was applied to the multispectral detection system, and the PLSR model and MLR model were established to determine the content of TVB-N in pork. The experimental results show that the characteristic wavelengths selected by SWA-SPAGA can well reflect the information of the whole spectrum, the model is effective and the number of variables is greatly reduced. The LED light source with optimized characteristic wavelengths can be used to detect the TVB-N content in pork in a multispectral detection system. The results of MLR model are better than those of PLSR model. The correlation coefficient of correction set and the root mean square error of correction set are 0.9050, respectively. The correlation coefficient of prediction set and the root mean square error of prediction set are 0.9040 and 3.81 脳 10 ~ (-5), respectively.
【作者單位】： 中國(guó)農(nóng)業(yè)大學(xué)工學(xué)院國(guó)家農(nóng)產(chǎn)品加工技術(shù)裝備研發(fā)分中心;
【基金】：國(guó)家重點(diǎn)研發(fā)計(jì)劃(2016YFD0401205)
【分類(lèi)號(hào)】：O657.33;TS251.51

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