本文選題：濃香型白酒基酒　切入點：分子光譜技術(shù)　出處：《江蘇大學》2017年碩士論文

【摘要】：白酒作為六大蒸餾酒之一,是我國的特色酒類,已逐漸成為人們?nèi)粘Ｉ詈徒浑H過程中重要的食品�，F(xiàn)有的白酒質(zhì)量等級評定方法主要包括人工感官評定和常規(guī)理化分析,這些方法因主觀性強、方法繁瑣、時效性差和成本昂貴等不足而無法實現(xiàn)實時快速檢測。近年來,光譜檢測技術(shù)因其操作簡便、檢測快速、靈敏度高和重現(xiàn)性好等優(yōu)點,在食品品質(zhì)檢測領域得到廣泛應用。本研究主要采用了四種分子光譜技術(shù)(近紅外光譜、中紅外光譜、紫外-可見光譜、拉曼光譜)對不同等級的濃香型白酒基酒及其主要酯類化合物(己酸乙酯、乳酸乙酯、丁酸乙酯、乙酸乙酯)含量進行檢測,旨在建立一套較為完整的濃香型白酒基酒質(zhì)量等級的無損快速檢測體系,具體研究內(nèi)容和相關(guān)結(jié)論如下:(1)濃香型白酒基酒樣本的收集及感官等級評定。收集了不同車間、不同班組的白酒基酒樣本共75個,經(jīng)車間工人初步等級劃分后獲得一級酒、二級酒和三級酒。經(jīng)初步劃分的白酒基酒樣本再由專業(yè)的感官評定人員進行嚴格的等級評定,最終獲得一級好酒樣本10個,一級差酒樣本22個,二級好酒樣本10個,二級差酒樣本14個,三級酒樣本19個。(2)不同等級濃香型白酒基酒樣本的快速判別。研究采集了不同等級白酒基酒樣本的四種光譜信息,并分別結(jié)合主成分分析(PCA)、線性判別分析(LDA)、反向傳播人工神經(jīng)網(wǎng)絡分析(BPANN)三種化學計量學方法建立不同等級白酒基酒的等級判別模型,并比較各模型效果。結(jié)果表明,四種光譜技術(shù)均能對不同等級樣本進行區(qū)分,模型效果較好。其中,中紅外光譜的LDA和BPANN模型的訓練集和測試集識別率均達到100%,模型效果最好,近紅外、紫外和拉曼光譜雖未達到100%,但識別率均較高,也能達到判別目的,能夠?qū)Σ煌燃墲庀阈桶拙苹七M行判別區(qū)分。(3)濃香型白酒基酒中主要酯類化合物含量的快速檢測。研究采用氣相色譜法測定白酒基酒樣本中各酯類化合物的含量,所測得的酯類含量作為參考值分別與四種光譜建立聯(lián)合區(qū)間偏最小二乘(SiPLS)定量模型。結(jié)果表明,四種光譜技術(shù)均能實現(xiàn)白酒基酒中主要酯類化合物含量的快速測定,其中中紅外光譜技術(shù)對白酒基酒中己酸乙酯、乳酸乙酯、乙酸乙酯三種酯類的定量模型效果最好,其訓練集和測試集的相關(guān)系數(shù)分別為0.9866和0.9847、0.9942和0.9937、0.9908和0.9852;近紅外光譜技術(shù)對丁酸乙酯的定量模型效果最好,其訓練集和測試集的相關(guān)系數(shù)為0.9262和0.9707,各模型均能滿足白酒生產(chǎn)過程中各酯類化合物含量的檢測要求。本研究實現(xiàn)了不同等級濃香型白酒基酒的準確判別,同時所建的酯類化合物快速定量模型的效果較好,能滿足白酒生產(chǎn)中的分析檢測要求,為濃香型白酒基酒等級的快速判別提供一種客觀而準確的分析方法,有效提升了白酒的智能化生產(chǎn)水平。
[Abstract]:As one of the six distilled wines, liquor is the characteristic liquor of our country, and it has gradually become an important food in people's daily life and communication.The existing methods of liquor quality grade evaluation mainly include artificial sensory evaluation and routine physical and chemical analysis. These methods can not realize real-time and rapid detection because of their strong subjectivity, cumbersome methods, poor timeliness and high cost.In recent years, the spectral detection technology has been widely used in the field of food quality detection because of its advantages of simple operation, rapid detection, high sensitivity and good reproducibility.In this study, four kinds of molecular spectroscopic techniques (near infrared spectrum, middle infrared spectrum, UV-Vis spectrum, Raman spectrum) were applied to Luzhou-flavor liquor and its main ester compounds (ethyl caproate, ethyl lactate).The content of ethyl butyrate and ethyl acetate was determined in order to establish a complete nondestructive and rapid detection system for the quality grade of Luzhou-flavor liquor.The specific research contents and related conclusions are as follows: 1) the collection and sensory grade evaluation of Luzhou-flavor liquor base liquor.A total of 75 samples of liquor base liquor were collected from different workshops and groups. The first grade, the second grade and the third grade liquor were obtained after the preliminary grading of the workers in the workshop.The samples of liquor base liquor were evaluated strictly by professional sensory assessors. Finally, 10 samples of first grade good wine, 22 samples of first grade good wine, 10 samples of second grade good liquor and 14 samples of second grade good liquor were obtained.The rapid discrimination of base liquor samples with different grades of Luzhou-flavor liquor was obtained from 19 samples of third grade liquor.Four kinds of spectral information of liquor samples of different grades were collected.Combined with three chemometrics methods, principal component analysis (PCA), linear discriminant analysis (LDAA) and backpropagation artificial neural network (Ann), three chemometrics methods were used to establish the grade discriminant models of liquor base liquor of different grades, and the effects of each model were compared.The results show that the four spectral techniques can distinguish the samples of different grades and the model is effective.Among them, the training set and test set of the LDA and BPANN models of the mid-infrared spectrum have the highest recognition rate, and the model has the best effect. Although the near infrared, ultraviolet and Raman spectra are not up to 100, the recognition rate is high, and the recognition rate can also reach the purpose of discrimination.The content of main ester compounds in Luzhou-flavor liquor could be detected quickly by discriminating and distinguishing the base liquor of Luzhou-flavor liquor.The determination of ester compounds in liquor samples by gas chromatography was studied. The measured esters were used as reference values to establish a combined interval partial least square siprs quantitative model with four kinds of spectra.The results showed that the four spectral techniques could be used to determine the contents of main ester compounds in liquor, and the content of ethyl caproate and ethyl lactate in liquor was determined by mid-infrared spectroscopy.The correlation coefficients between the training set and the test set were 0.9262 and 0.9707 respectively. Each model could meet the requirements of the determination of the contents of ester compounds in liquor production.This study realized the accurate discrimination of Luzhou-flavor liquor base liquor with different grades, and established the fast quantitative model of ester compounds, which can meet the requirements of analysis and detection in liquor production.It provides an objective and accurate analysis method for the fast discrimination of liquor grade of Luzhou-flavor liquor, and effectively improves the level of intelligent production of liquor.
【學位授予單位】：江蘇大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：O657.3;TS262.3

【參考文獻】

相關(guān)期刊論文 前10條

1 田婷;邱樹毅;文聆吉;秦方園;陶菡;;電子舌在不同輪次醬香型白酒區(qū)分識別中的應用[J];中國釀造;2016年12期

2 曲云龍;;淺談白酒的感官評定[J];黑龍江科技信息;2016年31期

3 張正勇;宋超;沙敏;劉軍;王海燕;;紫外可見光譜結(jié)合化學計量學方法用以古井貢酒年份快速鑒別[J];釀酒科技;2016年11期

4 王芳;楊延榮;楊仁杰;單慧勇;王雪峰;李如斯;;應用紫外-可見吸收光譜測定葡萄酒中合成色素胭脂紅[J];農(nóng)技服務;2016年06期

5 門洪;張曉婷;丁力超;陳棟琳;劉晶晶;;基于電子鼻/舌融合技術(shù)的白酒類別辨識[J];現(xiàn)代食品科技;2016年05期

6 徐晚秀;李臻峰;張振;李靜;宋飛虎;浦宏杰;;基于電子鼻的中國白酒酒齡檢測[J];食品與發(fā)酵工業(yè);2016年02期

7 劉建學;張衛(wèi)衛(wèi);韓四海;李璇;李佩艷;楊國迪;楊瑩;徐寶成;羅登林;;白酒基酒中己酸、乙酸的近紅外快速檢測[J];食品科學;2016年04期

8 張衛(wèi)衛(wèi);劉建學;韓四海;潘奕鷗;李璇;李佩艷;徐寶成;羅登林;;白酒基酒中醛類物質(zhì)的傅里葉變換近紅外光譜檢測[J];食品科學;2016年06期

9 陸藝瑩;張覃軼;龍海仙;姜曉彤;張順平;;基于便攜式電子鼻的白酒快速識別[J];釀酒科技;2016年01期

10 孫寶國;吳繼紅;黃明泉;孫金沅;鄭福平;;白酒風味化學研究進展[J];中國食品學報;2015年09期

相關(guān)博士學位論文 前1條

1 孫宗保;鎮(zhèn)江香醋揮發(fā)性成分分析及醋齡的識別研究[D];江蘇大學;2014年

，

本文編號：1723714