本文關(guān)鍵詞： 蜂蜜 摻假識別 近紅外 流變 二維相關(guān)分析 主成分分析 神經(jīng)網(wǎng)絡(luò)　出處：《南京農(nóng)業(yè)大學(xué)》2016年博士論文　論文類型：學(xué)位論文

【摘要】：我國作為世界養(yǎng)蜂大國,其蜂蜜生產(chǎn)、消費(fèi)、出口都位居世界前列。但蜂蜜品質(zhì),尤其是屢禁不止的蜂蜜摻假現(xiàn)象一直制約著中國蜂業(yè)的健康發(fā)展。有必要大力發(fā)展蜂蜜品質(zhì)及摻假鑒別技術(shù),尤其是廉價便捷的現(xiàn)代無損鑒別技術(shù)。本文研究摻假蜂蜜的鑒別方法,深入探究近紅外(NIR)、流變(RHE)分析方法及其融合在摻假蜂蜜識別上的應(yīng)用,可以推進(jìn)我國蜂蜜檢測技術(shù)發(fā)展,維護(hù)百姓食品安全,為中國蜂業(yè)健康發(fā)展及增強(qiáng)國產(chǎn)蜂蜜競爭力作出貢獻(xiàn)。本研究豐富了真假蜂蜜在NIR和RHE分析方法上的基礎(chǔ)數(shù)據(jù),所實現(xiàn)的多種分析方法下的摻假蜂蜜二維(2D)指紋譜圖不僅可以對真假蜂蜜進(jìn)行模式識別,還為摻假蜂蜜提供了直觀上的指紋譜圖,為多維度鑒別蜂蜜摻假提供了技術(shù)支持。本論文以拓展傳統(tǒng)的NIR和RHE方法的分析維度,實現(xiàn)多種分析方法下的摻假蜂蜜二維指紋譜圖,并建模識別摻假蜂蜜為基本目的。研究揭示了摻假蜂蜜的NIR和RHE特性,包括溫度、水分、摻假對蜂蜜相關(guān)特性的影響。在成功實現(xiàn)蜂蜜的NIR和RHE檢測方法及近紅外-流變(NIR-RHE)融合技術(shù)的二維指紋譜圖同時對摻假蜂蜜進(jìn)行了建模識別的比較研究。主要研究內(nèi)容和結(jié)論如下:1、運(yùn)用主成分分析和二維相關(guān)分析相結(jié)合的方法研究了溫度、水、摻假對蜂蜜短波NIR光譜影響,給出了脫水蜜和摻水蜜的二維-近紅外(2D-NIR)指紋譜圖,展示出水分在蜂蜜中的光學(xué)指紋。在NIR及2D-NIR譜圖的特征提取,相關(guān)分析和主成分分析基礎(chǔ)上,對不同類型樣本用BP-神經(jīng)網(wǎng)絡(luò)進(jìn)行了真假蜂蜜模式識別和摻假蜂蜜摻假程度預(yù)測的數(shù)學(xué)建模�；窘Y(jié)論為:(1)利用廉價便捷的短波近紅外技術(shù)實現(xiàn)蜂蜜摻假識別在技術(shù)上具有可行性。難以區(qū)分的蜂蜜差異可在溫度擾動下被放大。2D-NIR同步相關(guān)譜圖可揭示微擾中特征波段之間的關(guān)聯(lián)變化,展示不同蜂蜜的光學(xué)指紋,從直觀上以指紋譜圖方式展現(xiàn)蜂蜜差異。(2)2D-NIR同步相關(guān)譜圖可通過升溫過程中吸收峰峰位和峰強(qiáng)的改變放大水合差異,并呈現(xiàn)出清晰的光學(xué)指紋,據(jù)此可以區(qū)分不同脫水和摻水程度蜂蜜。(3)基于近紅外分析和BP神經(jīng)網(wǎng)絡(luò)的真假蜂蜜模式識別效果好,摻假蜂蜜摻假程度預(yù)測則績效不高。2、在實驗基礎(chǔ)上確立了真假蜂蜜樣本的流變模型和黏度變化經(jīng)驗公式,并對黏度經(jīng)驗公式中的兩常數(shù):溫度活化能和水分活化能予以理論解釋。運(yùn)用二維-流變(2D-RHE)譜圖新方法研究了摻假對蜂蜜的影響。在RHE特征及2D-RHE譜圖特征提取,相關(guān)分析和主成分分析基礎(chǔ)上,用BP神經(jīng)網(wǎng)絡(luò)對不同輸入變量進(jìn)行了真假蜂蜜模式識別和摻假蜂蜜摻假程度預(yù)測的數(shù)學(xué)建模�；窘Y(jié)論為:(1)蜂蜜摻假未能改變蜂蜜的Newton體和無觸變的流變特性,也未能改變黏溫、黏水及黏度隨溫度水分兩者的指數(shù)衰減規(guī)律。常數(shù)U0和活化能Ea既隨原蜜樣本也隨摻假度不同而不同,但不隨摻假度單調(diào)變化。(2)溫度活化能和水分活化能可通過度量流體有效流動的閾能差異,來折射流體內(nèi)部結(jié)構(gòu)組成的微觀差異。(3 )蜂蜜的2D-RHE譜圖能反映溫度微擾中各樣本在外力剪切下的細(xì)節(jié)差異,可直觀展示溫度微擾下剪切率遞增情況下表觀黏度變化情況。(4)基于流變分析和BP神經(jīng)網(wǎng)絡(luò)的真假蜂蜜模式識別可行,摻假蜂蜜摻假程度預(yù)測則績效低。3、運(yùn)用二維近紅外-流變(2D NIR-RHE)融合相關(guān)譜圖新方法,揭示溫度擾動下NIR和RHE兩分析方法下特征的關(guān)聯(lián)變化。對近紅外-流變(NIR-RHE)和2D NIR-RHE融合特征建立了真假蜂蜜模式識別和摻假蜂蜜摻假程度預(yù)測的數(shù)學(xué)模型,探討了多信息融合技術(shù)進(jìn)行蜂蜜摻假識別的可能性�；窘Y(jié)論為:(1)蜂蜜的2D NIR-RHE譜圖指紋特征明顯,能直觀展示溫度微擾下NIR和RHE兩種分析方法對應(yīng)特征的關(guān)聯(lián)變化,可用來反映摻假樣本細(xì)節(jié)特征。(2)基于融合技術(shù)和BP神經(jīng)網(wǎng)絡(luò)的真假蜂蜜模式識別可行,摻假蜂蜜摻假程度預(yù)測績效不高。4、提出引進(jìn)包括模型結(jié)果范圍、平均值、50%閾值和90%閾值這些統(tǒng)計參數(shù)在內(nèi)的網(wǎng)絡(luò)績效綜合評判方法。比較研究發(fā)現(xiàn):蜂蜜真假的模式識別以近紅外方法最優(yōu),總識別率平均值可達(dá)92.06%,50%閾值93.9%,90%閾值83.3%;流變方法和融合方法總識別率均值可達(dá)83%,50%閾值85.2%,90%閾值81.5%。二維分析則以2D NIR-RHE方法略勝,其總識別率均值可達(dá)83.7%,50%閾值85.2%,90%閾值 79.6%。
[Abstract]:China as the world's largest country of beekeeping, its honey production, consumption, exports are among the highest in the world. But the quality of honey, especially honey adulteration phenomenon repeated has been restricting the healthy development of China apiculture. It is necessary to vigorously develop and adulteration of honey quality technology, especially modern non-destructive identification technology of cheap and convenient identification method. This paper explores the adulteration of honey, near infrared (NIR), rheological (RHE) analysis method and its application in the identification of the fusion of adulterated honey, can promote the development of detection technology of Chinese honey, people maintain food safety, contribute to the healthy development and enhance the competitiveness of domestic honey bee China. This study enriches the basic data true honey in the NIR and RHE analysis methods, a variety of the two-dimensional analysis method under the adulteration of honey (2D) fingerprint can not only be used in pattern recognition of the true and false honey Also, provide a visual on fingerprint for the adulteration of honey, which provides technical support for multi dimension detecting honey adulteration. Analysis of this paper to expand the dimension NIR and the traditional RHE method, to achieve a variety of fingerprint analysis method under the adulteration of honey 2D spectra, and identify the adulteration of honey for the basic purpose of modeling. The study reveals the NIR and RHE properties, adulteration of honey including temperature, moisture, effect of honey adulteration related characteristics. After the successful implementation of NIR and RHE for detection of honey and the near infrared - rheological (NIR-RHE) 2-D fingerprint fusion technology spectrum also makes a comparative study on identification of adulteration of honey modeling. The main research contents and conclusions are as follows: 1, using the method of principal component analysis and two-dimensional correlation analysis on the combination of temperature, water, influence of honey adulteration of HF NIR spectra, given honey and honey water dehydration by two dimensional infrared (2D-NIR) refers to Pattern spectrum shows water optical fingerprint in honey. In the NIR and 2D-NIR spectrum feature extraction, correlation analysis and principal component analysis on the basis of different types of samples by BP- neural network for pattern recognition and false honey adulteration of honey adulteration level prediction mathematical modeling. The main conclusions are as follows: (1) using cheap and convenient short near infrared technology honey adulteration identification is feasible in technology. It is difficult to distinguish the difference of honey in the temperature perturbations are amplified.2D-NIR synchronous spectrum can reveal the relation between the characteristics of the perturbation in band change, show the optical fingerprint of different kinds of honey, from the visual to fingerprint way honey. (2) 2D-NIR synchronous amplification hydration difference peak position and peak intensity of the absorption spectra can be through the heating process, and showing a clear optical fingerprint, which can distinguish the different off Water and water level of honey. (3) based on the true and false pattern recognition results of near infrared analysis and BP neural network, the adulteration of honey adulteration to predict the extent is not high performance.2, on the basis of experiment established the rheological model and the viscosity change of empirical formula of true and false honey samples, and the viscosity in the empirical formula of two constants: the activation energy and water temperature can be activated theoretically. By using two-dimensional flow (2D-RHE) was studied on the spectrum of adulterated honey. In the new method of RHE and 2D-RHE spectrum feature extraction, correlation analysis and principal component analysis based on mathematical modeling and pattern recognition and honey adulteration of honey adulteration degree on forecast different input variables by using BP neural network. The main conclusions are as follows: (1) honey adulteration of honey and the body does not change Newton without thixotropic rheological properties, also failed to change the viscosity temperature, viscosity and viscosity of water with temperature and water The attenuation law of both constant and activation energy index. U0 Ea with both the original honey samples with different degrees of adulteration, but not with the degree of adulteration varies. (2) the temperature activation energy and water activation energy by measuring effective flow threshold difference, to reflect the internal structure of the micro fluid group differences honey. (3) the 2D-RHE spectrum can reflect the details of each sample perturbation in shear force under temperature, can display the temperature perturbation under the shear rate increasing under the condition of apparent viscosity changes. (4) based on the true and false honey rheological analysis pattern recognition and BP neural network is feasible, the adulteration of honey adulteration degree the prediction performance of low.3, using two-dimensional near-infrared (2D NIR-RHE) - rheological fusion correlation spectra method, reveal the change of temperature perturbation associated NIR and RHE two analysis method. Characteristics of near infrared (NIR-RHE) and 2D - rheological characteristics of the establishment of NIR-RHE fusion The mathematical model of the true and false honey pattern recognition and adulteration of honey adulteration level prediction, discusses the multi information fusion technology for the possibility of honey adulteration identification. The main conclusions are as follows: (1) 2D NIR-RHE honey fingerprints characteristic is obvious, can change related visual display two analysis method of temperature perturbation NIR and RHE corresponding features that can be used to reflect the sample adulteration minutiae. (2) based on the true and false pattern recognition fusion technology and BP neural network is feasible, the adulteration of honey adulteration prediction performance is not high degree of.4, proposed the introduction including the model results, the average, the 50% threshold and the 90% threshold of these statistical parameters, comprehensive evaluation of network performance comparison research method. Found: the optimal pattern recognition method of near infrared and honey, the average value of the total recognition rate can reach 92.06%, 50% 93.9% 90% 83.3% threshold, threshold; rheological method and fusion method of the total recognition rate The average value is 83%, 50% threshold 85.2%, 90% threshold 81.5%., two-dimensional analysis is slightly better than 2D NIR-RHE method, the total recognition rate is 83.7%, 50% threshold 85.2%, 90% threshold 79.6%..

【學(xué)位授予單位】：南京農(nóng)業(yè)大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2016
【分類號】：S896.1

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 黃蘊(yùn)芝;祁龍凱;林勵;吳澤青;譚東山;;蜂蜜中氨基酸類成分高效液相指紋圖譜研究[J];廣州中醫(yī)藥大學(xué)學(xué)報;2015年04期

2 賈洪鋒;李維;段麗麗;何蓮;鄧紅;;電子舌對摻入果葡糖漿摻假蜂蜜的識別[J];食品與機(jī)械;2015年04期

3 殷耀;陳`u蘭;陳磊;別小妹;丁濤;張曉燕;吳斌;沈崇鈺;張睿;;超高效液相色譜-高分辨質(zhì)譜法測定蜂蜜中的3種馬桑內(nèi)酯[J];色譜;2015年07期

4 孫旭東;董小玲;;蜂蜜中樂果農(nóng)藥殘留的表面增強(qiáng)拉曼光譜定量分析[J];光譜學(xué)與光譜分析;2015年06期

5 李莉;王慶振;孫穎平;;近紅外漫反射光譜結(jié)合主成分回歸法快速測定黑果小檗皮中鹽酸小檗堿含量[J];中國現(xiàn)代應(yīng)用藥學(xué);2015年03期

6 吳燕濤;穆同娜;王紹清;于曉瑾;許瑋;;現(xiàn)代分析技術(shù)在蜂蜜摻假鑒別中應(yīng)用研究進(jìn)展[J];食品研究與開發(fā);2015年05期

7 王文林;;淺說活化能[J];化學(xué)教學(xué);2015年02期

8 員玉良;盛文溢;;基于主成分回歸的莖直徑動態(tài)變化預(yù)測方法[J];農(nóng)業(yè)機(jī)械學(xué)報;2015年01期

9 裴高璞;史波林;趙鐳;高海燕;尹京苑;汪厚銀;支瑞聰;;典型摻假蜂蜜的電子鼻信息變化特征及判別能力[J];農(nóng)業(yè)工程學(xué)報;2015年S1期

10 陳桂云;吳威;黃玉萍;陳坤杰;;基于短波近紅外光譜技術(shù)的原蜜高果糖漿摻假度鑒別[J];南京農(nóng)業(yè)大學(xué)學(xué)報;2014年06期

相關(guān)博士學(xué)位論文 前3條

1 陳輝;基于微量元素和穩(wěn)定同位素比值的蜂蜜檢測與溯源技術(shù)研究[D];燕山大學(xué);2014年

2 陳蘭珍;蜂蜜品質(zhì)近紅外光譜評價技術(shù)研究[D];中國農(nóng)業(yè)科學(xué)院;2010年

3 曾哲靈;蜂蜜的熱穩(wěn)定性及流變和真空脫水特性研究[D];南昌大學(xué);2007年

相關(guān)碩士學(xué)位論文 前6條

1 葉夢迪;油菜蜂蜜成熟過程中蛋白質(zhì)和糖分變化的研究[D];浙江工商大學(xué);2015年

2 張艷平;基于伏安型電子舌的蜂蜜鑒別[D];東北電力大學(xué);2014年

3 宋珊;蜂蜜品質(zhì)中近紅外光譜檢測技術(shù)研究[D];天津科技大學(xué);2014年

4 徐賢;蜂蜜種類與品質(zhì)的鑒別研究[D];浙江工商大學(xué);2014年

5 雷鳴;六種單花種蜂蜜摻假情況的分析檢測研究[D];浙江工業(yè)大學(xué);2013年

6 任振鋒;糖類熔體的脆性研究[D];山東大學(xué);2011年

，

本文編號：1462702