基于近紅外和高光譜檢測(cè)雞蛋粉摻假的研究
發(fā)布時(shí)間：2018-08-10 22:22
【摘要】：雞蛋粉有高品質(zhì)的蛋白質(zhì)、均衡的礦物質(zhì)和維生素等優(yōu)良的營(yíng)養(yǎng)特性,在食品工業(yè)和畜產(chǎn)工業(yè)中發(fā)揮著非常重要的作用。但是,有些商家為了降低生產(chǎn)成本向蛋粉中摻入廉價(jià)物質(zhì)以獲得更大的利潤(rùn)。所以,本文以雞蛋粉(全蛋粉、蛋清粉、蛋黃粉)為研究對(duì)象,使用具有快速、無(wú)損檢測(cè)等優(yōu)點(diǎn)的近紅外光譜技術(shù)和高光譜技術(shù)并結(jié)合有效的化學(xué)計(jì)量學(xué)方法對(duì)雞蛋粉二元摻假體系和多元摻假體系進(jìn)行了檢測(cè)。同時(shí)采用兩種光譜技術(shù)建立了全蛋粉中重要營(yíng)養(yǎng)物質(zhì)蛋白質(zhì)和脂肪含量的檢測(cè)模型,主要研究結(jié)果如下:(1)應(yīng)用近紅外光譜技術(shù)檢測(cè)雞蛋粉二元體系摻假。將摻偽物淀粉、大豆蛋白、麥芽糊精分別按比例摻入到三種雞蛋粉中,構(gòu)成雞蛋粉的二元摻假體系。在三種雞蛋粉的摻假檢測(cè)中均建立定性判別模型(偏最小二乘判別模型)和定量檢測(cè)模型(偏最小二乘回歸模型)。結(jié)果顯示,在三種雞蛋粉摻假的判別分析中,偏最小二乘判別模型(PLS-DA)均可有效的將純雞蛋粉和摻假雞蛋粉進(jìn)行區(qū)分。在全蛋粉摻假的定量模型中,摻入淀粉、大豆蛋白和麥芽糊精的檢測(cè)最佳模型均為回歸系數(shù)-偏最小二乘回歸模型(RC-PLSR),預(yù)測(cè)相關(guān)系數(shù)(Rp2)分別達(dá)到0.990、0.996和0.998;在蛋清粉摻假的定量模型中,摻入大豆蛋白和麥芽糊精的最佳檢測(cè)模型為RC-PLSR,Rp2分別達(dá)到0.962和0.979,而對(duì)于摻入淀粉的蛋清粉的檢測(cè)模型,經(jīng)過(guò)回歸系數(shù)法(RC)獲得的特征波長(zhǎng)所建立的RC-PLSR在性能上顯著降低,因此選擇全波段波長(zhǎng)建立的PLS模型,獲得的Rp2為0.921;在蛋黃粉摻假的定量模型中,摻入淀粉、大豆蛋白和麥芽糊精的RC-PLSR相較于最佳波段獲得的PLS模型性能均有所降低,因此均選用最佳波段下獲得的模型,Rp2分別達(dá)到0.998、0.997和0.986。(2)近紅外光譜技術(shù)檢測(cè)雞蛋粉多元體系摻假。將淀粉、大豆蛋白和麥芽糊精三種摻雜物兩兩或者三者的混合物按比例摻入到雞蛋粉中,構(gòu)成雞蛋粉的多元摻假體系。分別建立雞蛋粉中淀粉、大豆蛋白、麥芽糊精摻偽量和總摻偽量的定量模型,并比較了不同預(yù)處理方式和不同波段對(duì)于各個(gè)模型的影響�；谧罴杨A(yù)處理方式和最優(yōu)波段建立主成分回歸(PCR)定量模型并與PLSR模型性能進(jìn)行比較。結(jié)果發(fā)現(xiàn),淀粉摻偽量模型和麥芽糊精摻偽量模型效果不佳,而大豆蛋白摻偽量和總摻偽量模型的預(yù)測(cè)性能良好,Rp2均達(dá)到0.950以上,PLSR模型檢測(cè)性能優(yōu)于PCR模型。(3)應(yīng)用高光譜技術(shù)檢測(cè)雞蛋粉二元體系摻假。通過(guò)采集純樣品和摻假樣品的高光譜圖像并提取平均光譜,建立支持向量機(jī)(SVM)模型對(duì)純蛋粉和摻假蛋粉進(jìn)行判別,結(jié)果表明三種雞蛋粉摻假的判別正確率都達(dá)到90%以上。為了定量檢測(cè)摻入物的含量,采用偏最小二乘回歸模型建立光譜數(shù)據(jù)與摻假含量之間的關(guān)系。結(jié)果顯示全蛋粉摻假的研究中,摻入淀粉、大豆蛋白、麥芽糊精所建立的PLSR模型的Rp2分別達(dá)到0.931、0.981、0.990;蛋清粉摻假的研究中,摻入淀粉、大豆蛋白、麥芽糊精所建立的PLSR模型的Rp2分別達(dá)到0.832、0.994和0.984;蛋黃粉摻假的研究中,摻入淀粉、大豆蛋白、麥芽糊精所建立的PLSR模型的Rp2分別達(dá)到0.998、0.986和0.975,說(shuō)明模型具有良好性能。通過(guò)RC法和連續(xù)投影法(SPA)提取了摻假的重要特征波長(zhǎng),分別建立RC-PLSR和SPA-PLSR簡(jiǎn)化模型。結(jié)果表明,模型在性能上沒(méi)有顯著差別,但是由于減少了波長(zhǎng)的數(shù)量,使得運(yùn)算的時(shí)間縮減、效率提高。(4)高光譜技術(shù)檢測(cè)雞蛋粉多元體系摻假。在摻假檢測(cè)中,定性判別模型采用了隨機(jī)森林(RF)和支持向量機(jī)(SVM)的方法,結(jié)果顯示二者均能對(duì)純蛋粉和摻假蛋粉進(jìn)行有效判別,且RF的效果略?xún)?yōu)于SVM。在摻入混合物的全蛋粉、蛋清粉、蛋黃粉的定量模型中建立蛋粉實(shí)際含量與預(yù)測(cè)含量之間的關(guān)系,Rp2分別可以達(dá)到0.986、0.992、0.989,說(shuō)明模型性能良好。為了簡(jiǎn)化模型,根據(jù)RC法和SPA法提取特征波長(zhǎng),分別建立了RC-PLSR、RC-MLR及SPA-PLSR、SPA-MLR模型,所建立的模型表現(xiàn)出了良好的性能。(5)采用近紅外光譜和高光譜技術(shù)建立全蛋粉中蛋白質(zhì)和脂肪含量的定量模型,并比較了兩種方法的性能。在近紅外光譜測(cè)定中,蛋白質(zhì)檢測(cè)的最優(yōu)模型為回歸系數(shù)-PLSR,Rp2達(dá)到0.996,脂肪檢測(cè)的最優(yōu)模型為基于全波段所建立的模型,Rp2達(dá)到0.974;在高光譜測(cè)定中,蛋白質(zhì)檢測(cè)的最優(yōu)模型為載荷系數(shù)-PLSR,Rp2達(dá)到0.995,脂肪檢測(cè)的最優(yōu)模型為回歸系數(shù)-PLSR,Rp2達(dá)到0.964。兩種方法均表現(xiàn)出良好的性能,近紅外光譜檢測(cè)技術(shù)的性能優(yōu)于高光譜。
[Abstract]:Egg powder has high quality protein, balanced mineral and vitamin nutritional properties and plays a very important role in the food industry and livestock industry. However, in order to reduce production costs, some businesses add cheap substances into egg powder to obtain greater profits. Egg yolk powder (Egg yolk powder) was studied by near infrared spectroscopy (NIRS) and hyperspectral techniques with the advantages of rapid and non-destructive detection, combined with effective chemometrics to detect the binary adulteration system and multicomponent adulteration system of egg powder. The main results are as follows: (1) Near-infrared spectroscopy was used to detect the adulteration of egg powder binary system. Adulterated starch, soybean protein and maltodextrin were mixed into three kinds of egg powder in proportion to form a binary adulteration system of egg powder. The results showed that the partial least squares discriminant model (PLS-DA) could distinguish the pure egg powder from the adulterated egg powder in the discriminant analysis of three kinds of egg powder adulteration. In the quantitative model of egg powder adulteration, starch and soybean protein were added. The best detection models for soybean protein and maltodextrin were both regression coefficient-partial least squares regression model (RC-PLSR), and the predictive correlation coefficient (Rp2) was 0.990, 0.996 and 0.998, respectively. In the quantitative model of egg white powder adulteration, the best detection models for soybean protein and maltodextrin were RC-PLSR, Rp2 was 0.962 and 0.979, respectively, and for starch adulteration. In the detection model of egg yolk powder, the characteristic wavelengths obtained by regression coefficient method (RC) significantly reduced the performance of RC-PLSR, so the PLS model with full-band wavelength was selected, and the Rp2 was 0.921. In the quantitative model of egg yolk powder adulteration, the RC-PLSR with starch, soybean protein and maltodextrin was obtained at the optimum band. The performances of PLS models were decreased, so the best band models were selected, and Rp2 was 0.998, 0.997 and 0.986 respectively. (2) Near infrared spectroscopy was used to detect the adulteration of egg powder. The quantitative models of starch, soybean protein, maltodextrin adulteration and total adulteration in egg powder were established, and the effects of different pretreatment methods and different wave bands on each model were compared. The results showed that starch adulteration model and maltodextrin adulteration model were not effective, while soybean protein adulteration and total adulteration model had good predictive performance, Rp2 was above 0.950, and PLSR model had better detection performance than PCR model. (3) Detection of egg powder adulteration by Hyperspectral technique. Supporter Vector Machine (SVM) model was established to discriminate pure egg powder and adulterated egg powder. The results showed that the correct discriminant rate of three kinds of egg powder adulteration was above 90%. In order to quantitatively detect the content of adulterated egg powder, partial least squares regression model was used to establish spectral data and adulterated egg powder. The results showed that the Rp2 of the PLSR models with starch, soybean protein and maltodextrin were 0.931, 0.981, 0.990 respectively, and that of the PLSR models with starch, soybean protein and maltodextrin were 0.832, 0.994 and 0.984 respectively. In the study, the Rp2 of PLSR model with starch, soybean protein and maltodextrin was 0.998, 0.986 and 0.975 respectively, which showed that the model had good performance. The important characteristic wavelengths of adulteration were extracted by RC method and continuous projection method (SPA), and the simplified models of RC-PLSR and SPA-PLSR were established respectively. No, but because the number of wavelengths is reduced, the calculation time is shortened and the efficiency is improved. (4) Hyperspectral technique is used to detect the adulteration of egg powder. In order to simplify the model, RC-PLSR, RC-M were established according to the characteristic wavelengths extracted by RC and SPA methods. LR, SPA-PLSR and SPA-MLR models showed good performance. (5) Quantitative models of protein and fat content in egg powder were established by near infrared spectroscopy and hyperspectral techniques, and the performances of the two methods were compared. 96, the optimal model for fat detection is based on the full-band model, Rp2 reaches 0.974; in hyperspectral measurement, the optimal model for protein detection is load coefficient-PLSR, Rp2 reaches 0.995, the optimal model for fat detection is regression coefficient-PLSR, Rp2 reaches 0.964. Both methods show good performance, and near-infrared spectroscopy detection technology. The performance of the technique is better than that of hyperspectral imaging.
【學(xué)位授予單位】：華中農(nóng)業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：O657.3;TS253.7
[Abstract]:Egg powder has high quality protein, balanced mineral and vitamin nutritional properties and plays a very important role in the food industry and livestock industry. However, in order to reduce production costs, some businesses add cheap substances into egg powder to obtain greater profits. Egg yolk powder (Egg yolk powder) was studied by near infrared spectroscopy (NIRS) and hyperspectral techniques with the advantages of rapid and non-destructive detection, combined with effective chemometrics to detect the binary adulteration system and multicomponent adulteration system of egg powder. The main results are as follows: (1) Near-infrared spectroscopy was used to detect the adulteration of egg powder binary system. Adulterated starch, soybean protein and maltodextrin were mixed into three kinds of egg powder in proportion to form a binary adulteration system of egg powder. The results showed that the partial least squares discriminant model (PLS-DA) could distinguish the pure egg powder from the adulterated egg powder in the discriminant analysis of three kinds of egg powder adulteration. In the quantitative model of egg powder adulteration, starch and soybean protein were added. The best detection models for soybean protein and maltodextrin were both regression coefficient-partial least squares regression model (RC-PLSR), and the predictive correlation coefficient (Rp2) was 0.990, 0.996 and 0.998, respectively. In the quantitative model of egg white powder adulteration, the best detection models for soybean protein and maltodextrin were RC-PLSR, Rp2 was 0.962 and 0.979, respectively, and for starch adulteration. In the detection model of egg yolk powder, the characteristic wavelengths obtained by regression coefficient method (RC) significantly reduced the performance of RC-PLSR, so the PLS model with full-band wavelength was selected, and the Rp2 was 0.921. In the quantitative model of egg yolk powder adulteration, the RC-PLSR with starch, soybean protein and maltodextrin was obtained at the optimum band. The performances of PLS models were decreased, so the best band models were selected, and Rp2 was 0.998, 0.997 and 0.986 respectively. (2) Near infrared spectroscopy was used to detect the adulteration of egg powder. The quantitative models of starch, soybean protein, maltodextrin adulteration and total adulteration in egg powder were established, and the effects of different pretreatment methods and different wave bands on each model were compared. The results showed that starch adulteration model and maltodextrin adulteration model were not effective, while soybean protein adulteration and total adulteration model had good predictive performance, Rp2 was above 0.950, and PLSR model had better detection performance than PCR model. (3) Detection of egg powder adulteration by Hyperspectral technique. Supporter Vector Machine (SVM) model was established to discriminate pure egg powder and adulterated egg powder. The results showed that the correct discriminant rate of three kinds of egg powder adulteration was above 90%. In order to quantitatively detect the content of adulterated egg powder, partial least squares regression model was used to establish spectral data and adulterated egg powder. The results showed that the Rp2 of the PLSR models with starch, soybean protein and maltodextrin were 0.931, 0.981, 0.990 respectively, and that of the PLSR models with starch, soybean protein and maltodextrin were 0.832, 0.994 and 0.984 respectively. In the study, the Rp2 of PLSR model with starch, soybean protein and maltodextrin was 0.998, 0.986 and 0.975 respectively, which showed that the model had good performance. The important characteristic wavelengths of adulteration were extracted by RC method and continuous projection method (SPA), and the simplified models of RC-PLSR and SPA-PLSR were established respectively. No, but because the number of wavelengths is reduced, the calculation time is shortened and the efficiency is improved. (4) Hyperspectral technique is used to detect the adulteration of egg powder. In order to simplify the model, RC-PLSR, RC-M were established according to the characteristic wavelengths extracted by RC and SPA methods. LR, SPA-PLSR and SPA-MLR models showed good performance. (5) Quantitative models of protein and fat content in egg powder were established by near infrared spectroscopy and hyperspectral techniques, and the performances of the two methods were compared. 96, the optimal model for fat detection is based on the full-band model, Rp2 reaches 0.974; in hyperspectral measurement, the optimal model for protein detection is load coefficient-PLSR, Rp2 reaches 0.995, the optimal model for fat detection is regression coefficient-PLSR, Rp2 reaches 0.964. Both methods show good performance, and near-infrared spectroscopy detection technology. The performance of the technique is better than that of hyperspectral imaging.
【學(xué)位授予單位】：華中農(nóng)業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：O657.3;TS253.7
【參考文獻(xiàn)】
相關(guān)期刊論文 前10條
1 王文秀;彭彥昆;孫宏偉;王凡;田芳;陳興海;;基于可見(jiàn)/近紅外光譜生鮮肉多品質(zhì)參數(shù)檢測(cè)裝置研發(fā)[J];農(nóng)業(yè)工程學(xué)報(bào);2016年23期
2 羅微;杜焱U，
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