绍兴黄酒的陈酿特性与指纹图谱检测方法及装置研究
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摘要
黄酒是我国最古老的独有酒种,集营养和保健为一体,被誉为“国粹”。然而目前针对黄酒的基础研究较为薄弱,对黄酒陈酿过程中风味成分的陈酿机理缺乏全面系统的研究；且检测水平落后,对黄酒产品的质量控制仅局限在几项常规指标,如酒精度、总糖、总酸,对与黄酒风味形成密切相关的微量功能性组分了解甚少,与消费者对黄酒品质越来越高的要求极不相称,阻碍了黄酒产业进一步的发展与壮大。本研究是对本课题组前期研究(基于近红外光谱的绍兴黄酒风味成分与酒龄的检测分析)的进一步深入和拓展,目的是建立黄酒不同陈酿阶段以及酒龄的指纹图谱快速检测方法,为黄酒产品质量控制、风险评估提供新手段、新装备。
本文以绍兴黄酒为研究对象,综合利用仪器分析、可见/近红外、近红外和中红外光谱技术,对绍兴黄酒的陈酿特性及其酒龄和品质的指纹图谱检测方法和装置开展了研究,获取了基于黄酒中多类化学组分以及近红外光谱的黄酒酒龄特征指纹图谱；建立并对比了黄酒多种风味成分的近红外、中红外光谱定量分析模型；分析了温度对黄酒品质可见/近红外光谱检测精度的影响,确定了最佳检测温度水平,在此基础上开发了基于温度控制的黄酒品质实时检测系统。
本文的主要研究结果和结论如下：
(1)对2007年冬酿绍兴黄酒在陈酿3至45个月时间范围内,各种特征风味成分的含量变化进行了动态追踪检测。结果表明,在黄酒陈酿过程中：①6项常规指标中,酒精度和总糖含量呈下降趋势,非糖固形物和总酸含量则稳步上升,氨基酸态氮和pH的变化趋势不明显。除pH外,其余指标的含量随陈酿过程存在显著差异；②乳酸与总酸一致,含量不断增加,并存在显著性差异；③5个糖类指标中,葡萄糖含量变化趋势不明显,未检测出显著性差异。麦芽糖、异麦芽糖、潘糖和异麦芽三糖则存在显著性差异,但无明显变化趋势；④黄酒中的9种主要金属离子元素(Na、Mg、 A1、K、Ca、Mn、Fe、Cu、Zn)的含量在陈酿过程中均存在一定波动,无明显增加或降低趋势。除Ca与Cu外,其它7种元素均存在显著性差异；⑤16种游离氨基酸指标中,天门冬氨酸、谷氨酸、脯氨酸、异亮氨酸、亮氨酸、酪氨酸、赖氨酸、组氨酸、精氨酸及总氨基酸含量在陈酿过程中均有降低趋势,其余7种氨基酸(苏氨酸、丝氨酸、甘氨酸、丙氨酸、缬氨酸、蛋氨酸、苯丙氨酸)含量总体保持稳定。除天门冬氨酸、甘氨酸、丙氨酸、亮氨酸、酪氨酸和苯丙氨酸外,其余氨基酸的含量均存在显著差异；⑥11种挥发性成分指标(异丁醇、异戊醇、2,3-丁二醇、β-苯乙醇、丙三醇、乙酸乙酯、丁酸乙酯、乳酸乙酯、壬醛、苯甲醛、癸酸乙酯)中,异丁醇、异戊醇、壬醛、苯甲醛含量在陈酿中有所降低,丙三醇含量出现上升,其余指标含量均出现一定波动,无显著变化规律。
结果表明,黄酒中的大部分常规指标、乳酸、金属离子、氨基酸等化学组分,在陈酿过程中均参与了复杂的物理化学变化,使得其含量经历了显著的变化。但黄酒中主要糖类指标,葡萄糖的含量未检测出显著性差异,可推断糖类指标在陈酿过程中变化不大。由于所用检测方法的限制,11种挥发性成分中大部分指标未发现有明显变化趋势,其陈酿机理有待进一步研究。
(2)建立了基于以上各类化学组分的黄酒酒龄判别模型。结果如下：①基于6项常规指标主成分得分的SLDA1、以及基于其组分含量的SLDA2和PLS-DA酒龄判别正确率分别为50.6%,48.7%和75.7%；②基于5种糖类指标的SLDA1、SLDA2和PLS-DA酒龄判别模型的判别正确率分别为39.3%,36.4%和66.5%；③基于9种金属离子的SLDA1、SLDA2和PLS-DA酒龄判别模型的判别正确率分别达到72.7%,73.4%和81.4%；④综合常规指标、乳酸、糖类以及金属离子四类化学指标,所建立的SLDA1、 SLDA2和PLS-DA判别模型对酒龄的判别正确率分别为91.0%,86.6%和91.2%；⑤基于16种氨基酸指标的SLDA1、SLDA2和PLS-DA酒龄判别模型的判别正确率达到86.4%,85.6%和91.2%；⑥基于11种挥发性成分指标所建立的SLDA1、SLDA2和PLS-DA模型对酒龄的判别正确率分别为90.6%,90.6%和92.1%。
结果表明,综合常规指标、乳酸、糖类和金属离子,以及氨基酸、挥发性成分所建立的酒龄判别模型,最佳判别正确率均超过90%,可用于黄酒酒龄鉴别和酒龄指纹图谱检测方法的建立。
(3)分析了不同陈酿阶段黄酒基酒以及不同标注酒龄勾兑酒在800nm-2500nm范围内的近红外光谱,发现两者的光谱吸收特征一致,主要吸收峰均位于1455nm、1692nm、1776nm、2266nm、2302nm以及1900-1950nm处,与黄酒中的糖、酸、氨基酸等风味成分中的主要基团C-H、O-H、N-H等的吸收密切相关。主成分分析结果显示,不同酒龄的基酒和勾兑酒样品的均有明显聚类趋势。基于LDA、LS-SVM以及PLS-DA三种模式识别方法所建立的基酒酒龄判别模型,其建模集判别正确率分别为93.6%,98.7%和94.4%,预测集判别正确率分别为96.3%,91.3%和95.2%；勾兑酒酒龄的LDA、LS-SVM、PLS-DA以及DPLS模型的建模集判别正确率分别为85.0%,100%,99.2%和100%,预测集判别正确率分别为72.5%,87.5%,86.3%和95.0%。
结果表明近红外光谱能提取不同酒龄黄酒的整体差异信息,可用于基酒以及勾兑酒的酒龄的检测分析和指纹图谱的建立。
(4)建立了黄酒中的6项常规指标、乳酸、5种糖、16种氨基酸及总氨基酸含量的近红外、中红外光谱PLSR定量分析模型。①对常规指标和乳酸的分析结果表明,所建近红外、中红外光谱分析模型均可用于总糖、非糖固形物以及氨基酸态氮的定量分析(模型RPD>2.0),以及总酸、pH值、乳酸的定性分析(模型RPD>1.5)。除乳酸外,近红外光谱分析模型的性能均优于中红外光谱。②对糖类指标的分析结果表明,所建近、中红外光谱分析模型可用于葡萄糖含量的定量检测(模型RPD>2.0),异麦芽三糖的近红外光谱分析结果较优(模型RPD=1.95),而麦芽糖的中红外光谱分析结果较优(模型RPD=1.97),其余指标检测精度不佳,模型鲁棒性欠缺(模型RPD<1.5)。③对氨基酸指标的分析结果表明,近红外光谱分析模型性能普遍较优,除脯氨酸、苯丙氨酸、组氨酸以及总氨基酸外,其余指标定量分析模型的RPD值均超过1.5,其中,天门冬氨酸、异亮氨酸、酪氨酸、精氨酸模型的RPD值大于2.0。而中红外模型的鲁棒性普遍欠缺,仅天门冬氨酸、谷氨酸、异亮氨酸、苯丙氨酸模型的RPD值大于或等于1.5,丝氨酸模型的RPD值接近1.5,具有定性分析能力,其它指标均低于1.50。除脯氨酸和精氨酸外,近红外光谱模型的整体性能均优于中红外光谱。
结果表明,近红外、中红外光谱均可用于黄酒中主要常规指标、葡萄糖、乳酸,以及部分氨基酸指标的定量定性检测分析,近红外光谱分析模型的性能总体优于中红外光谱。
(5)分析了5℃,10℃,15℃,20℃,25℃,30℃,35℃温度水平下黄酒样品的可见／近红外光谱(303-1700nm)的变化规律。原始光谱中,在1340-1480nm波段范围内,在高频(短波)波段,吸收峰随着温度的上升而逐渐增高,反之,在低频(长波)波段,吸收峰随着温度上升而不断降低。二阶微分光谱中,在1320nm和1358nm处的吸收峰值随温度上升而增强,而1404nm处峰值随温度上升而降低。主成分分析结果显示不同温度下的样品光谱有较明显的聚类趋势,表明温度对黄酒的可见／近红外光谱影响显著。由于氢键结合会使得水分子的伸缩振动向高频转移,而弯曲振动则向低频转移。温度越高会促使氢键发生结合,从而伸缩振动会向高频(短波)转移,由此造成样品光谱发生变化。
建立了不同温度下黄酒品质指标的SMLR定量分析模型,确定了酒精度、总糖、非糖固形物、总酸以及氨基酸态氮的最佳检测温度分别为：15℃,20℃,20℃,15℃和20℃。酒精度、总糖模型的精度较高,鲁棒性优(模型RPD>2.5),总酸模型精度一般,仅具有定性分析能力(模型RPD>1.5),非糖固形物以及氨基酸态氮模型精度不佳(模型RPD<1.5)。运用7个温度下的黄酒样品光谱建立了酒精度、总糖和总酸的温度补偿检测模型。结果表明,酒精度的温度补偿效果较优(模型RPD=3.81),而总糖和总酸温度补偿效果不佳(模型RPD<1.5)。
利用蔡司便携式光谱仪及其外部程序开发包、光纤、控温样品池,构建和开发了基于可见／近红外光谱的黄酒品质(酒精度、总糖以及总酸)实时检测的软、硬件系统,并对该检测装置的性能进行了实验验证。在15℃水平下,对37个样品的检测结果为：①酒精度的预测相关系数rp、RMSEP以及RPD值分别为0.979,0.464%和3.78；②总糖的rp, RMSEP以及RPD值分别为0.766,5.78g/L和1.50；③总酸的rp、RMSEP以及RPD值分别为0.630,0.664g/L和1.24。结果表明该检测系统可用于酒精度的准确定量检测,但总糖和总酸指标的检测精度不佳,模型精度有待提升。
Chinese rice wine is the most ancient unique wine kind of nutrition and health in China, and be honored as "essence" of the country. However, at present, the basic research towards rice wine is relative weak. The detailed changes in various flavor components during rice wine aging still remain uncertain. In additional, due to the backward technologies used in quality control of rice wine, only a few routine chemical parameters, such as alcohol degree, total sugars, total acids, were analyzed in conventional testes. Little is known about the small amounts of functional components that are closely related to its flavor, which cannot meet consumers'higher requirements towards rice wine products. It also remains as a barrier for the growth of rice wine industry. This study is a further extension of the former research projects carried out by our group members (flavor components quantification and age discrimination of rice wines based on NIR spectroscopy), with its aim to establish analytical methods and devices based on fingerprint techniques for aging status characterization as well as quality control and risk assessment of rice wine products.
The object of this research is Shaoxing rice wine, which is the best representation of Chinese rice wine. Multiple technologies based on instrument analysis, VIS/NIR, NIR and MIR spectroscopy were applied as fingerprint techniques for quality evaluation of rice wine. Fingerprints of rice wine of various ageing status based on chemical compositions as well as NIR spectra were obtained. Quantification of flavor components in rice wine based on both NIR and MIR spectroscopy was also undertaken and compared. The effect of temperature on the performance for rice wine quality determination based on VIS/NIR spectroscopy was investigated, and the optimal temperature level was determined. A hardware and software system for quality determination of rice wine products based on temperature control was then developed.
The main contents and conclusions were:
(1) Continuous tracing of the changes in various flavor components in Shaoxing wines during the aging period of3to45months was undertaken. The results showed that,①Among six routine parameters, the content of alcohol degree and total sugar decreased, while the content of non-sugar solid and total acid increased. The change of pH and amino acid nitrogen was not clear. Besides pH, the remaining five indexes were all found to be significant different.②The content of lactic acid increased, similar to total acid. Significant difference was also detected.③Among five sugars, the change of glucose was not obvious, and no significant difference between different aging status was detected. The remaining four sugar parameters were all significant different, but their changes were also not obvious.④The content of Na, Mg, Al, K, Ca, Mn, Fe, Cu and Zn in rice wines fluctuated during aging, no obvious increase or decrease trend was observed. Besides Ca and Cu, other elements were all found to be significantly modified during ageing.⑤Among16free amino acids, the content of aspartic acid, glutamic acid, proline, isoleucine, leucine, tyrosine, lysine, histidine, arginine and total amino acids decreased, while the remaining threonine, serine, glycine, alanine, valine, methionine, phenylalanine remained relative stable. Besides aspartic acid, glycine, alanine, leucine, tyrosine and phenylalanine, other amino acids were all found to be significant different.⑥Among11volatile components, the content of isobutanol, isoamylol, nonanal and benzaldehyde decreased, while the content of glycerol increased. The changes of others were not obvious. Significant different was detected for all volatile parameters.
The results indicated that most of routine parameters, lactic acid, elements, and amino acids, were involved in the complicated physical and chemical reactions in rice wine, and went through significant changes during aging. However, glucose was detected not to be significant different, which suggested that sugars might not go through obvious changes. The changes of most volatile compounds were not obvious, and further research was needed.
(2) Aging status discrimination models were established based on the above chemical compositions. The results showed:①The accuracy obtained by SLDA1(base on PCs), SLDA2(based on chemical compositions) and PLS-DA models was50.6%,48.7%and 75.7%, respectively based on six routine parameters.②The accuracy obtained by SLDA1, SLDA2and PLS-DA models was39.3%,36.4%and66.5%, respectively based on sugars.③Based on nine mineral elements, the accuracy obtained by SLDA1, SLDA2and PLS-DA models was72.7%,73.4%and81.4%, respectively.④The accuracy obtained by SLDA1, SLDA2and PLS-DA models was91.0%,86.6%and91.2%, respectively based on routine parameters, lactic acid, sugars and elements.⑤SLDA1, SLDA2and PLS-DA models based on16amino acids gave the accuracy of86.4%,85.6%and91.2%, respectively.⑥The accuracy obtained by SLDA1, SLDA2and PLS-DA models was90.6%,90.6%and92.1%, respectively based on11volatile compounds.
The results indicated that the discrimination models based on routine parameters, lactic acid, sugars and elements, as well as amino acids and volatile compounds reached a relative high accuracy over90%. These flavor components could be applied as fingerprint for aging status characterization of rice wine.
(3) NIR spectra of base and blended rice wines in the range of800-2500nm were analyzed and compared. The main absorption peaks were all found to be at round1455nm,1692nm,1776nm,2266nm,2302nm and1900-1950nm, related to C-H, O-H, N-H functional groups in sugars, acids, amino acids of rice wines. PCA results showed that both base and blended rice wines of different aging status could be separated clearly. LDA, LS-SVM and PLS-DA were used to establish models for base rice wine age discrimination. The accuracy obtained were93.6%,98.7%and94.4%, respectively in calibration, and96.3%,91.3%and95.2%in prediction. For blended rice wine discrimination, the accuracy obtained in calibration were85.0%,100%,99.2%and100%by LDA, LS-SVM, PLS-DA and DPLS. And were72.5%,87.5%,86.3%and95.0%in prediction.
The results indicated that NIR spectroscopy can obtain the holistic difference between samples, and can be used to establish fingerprint of rice wine of different aging status or ages.
(4) PLSR quantification of routine parameters, lactic acid, sugars and amino acids in rice wine based on NIR and MIR spectroscopy was carried out. The results showed:①For the determination of routine parameters and lactic acid, both NIR and MIR spectroscopy could be used for quantitative analysis of total sugar, non-sugar solid and amino acid nitrogen. The RPD values of the models were all above2.0. Total acid, pH and lactic acid could be qualitative analyzed with RPD values above1.5. Besides lactic acid, the performances of NIR models were superior to MIR models.②For the determination of sugars, the quantification of glucose was satisfactory by both NIR and MIR spectroscopy with an RPD value above2.0. NIR was more suitable for analysis of isomaltotriose (RPD=1.95), while MIR was more suitable for analysis of maltose (RPD=1.97). For other parameters, the performance of the models was not satisfactory.③For the determination of amino acids, the performance of NIR models were generally much superior. Besides proline, phenylalanine, histidine and total amino acids, the RPD values of NIR models were all over1.5. In addition, the RPD values obtained for aspartic acid, isoleucine, tyrosine, and arginine were over2.0. The robustness of most MIR models was not satisfactory. RPD values obtained for aspartic acid, glutamic acid, isoleucine, phenylalanine and serine were above or close to1.5. For other amino acids, the robustness of the models was low (RPD<1.5).
The results indicated that both NIR and MIR spectroscopy could be used for the analysis of routine parameters, lactic acid, sugars and some amino acids. But the performances of NIR models were generally better than MIR models.
(5) The VIS/NIR spectra of rice wine samples in the range of303-1700nm under different temperature levels (5℃,10℃,15℃,20℃,25℃,30℃,35℃) were investigated. In high frequency (short-wave) region of1340-1480nm of raw spectra, the absorption increased when the temperature raised. On the contrary, in low frequency region, the absorption decreased when the temperature dropped. In second derivative spectra, the absorption at1320nm and1358nm increased with temperature. However, at1404nm, the absorption decreased with temperature. PCA results indicated that the samples under different temperature levels could be clearly separated. Because the hydrogen bonding will cause a shift of stretching vibration of water molecular to high frequency. As the temperature rises, it will promote hydrogen bonding, which might cause a change in the sample spectra.
The determination of five routine parameters in rice wine was carried out by SMLR method under different temperature levels. The optimal temperature for quantification of alcohol degree, total sugar, non-sugar solid, total acid and amino acid nitrogen was found to be15℃,20℃,20℃,15℃and20℃, respectively. The model developed for alcohol degree and total sugar were relative robustness with an RPD value over2.5. The total acid model was moderate with an RPD value over1.5. However, the determination of non-sugar solid and amino acid nitrogen was not satisfactory due to low a RPD value (RPD<1.5). Temperature compensation models were established for alcohol degree, total sugar and total acid based on the spectra obtained under seven temperature levels. The compensation for alcohol degree showed good performance with a RPD value of the model to3.81. However, the compensation for total sugar and total acid was not satisfactory and needed to be improved (RPD<1.5).
Finally, a hardware and software system was developed for quality determination of rice wine based on VIS/NIR spectroscopy, with the use of Zeiss portable spectrometer, optical fiber and temperature-controlled cuvette holder. The performance of the detection device was validated by37additional samples under temperature level of15℃. The results showed that:①For the determination of alcohol degree, the correlation coefficient in prediction, RMSEP and RPD was found to be0.979,0.464%and3.78, respectively.②For total sugar parameter, the correlation coefficient in prediction, RMSEP and RPD was0.766,5.78g/L and1.50, respectively.③The correlation coefficient in prediction, RMSEP and RPD was0.630,0.664g/L and1.24, respectively for total acid. The results indicated that the device might be suitable for alcohol degree detection in rice wine. But the precision for total sugar and total acid determination needed improvement.
本文以绍兴黄酒为研究对象,综合利用仪器分析、可见/近红外、近红外和中红外光谱技术,对绍兴黄酒的陈酿特性及其酒龄和品质的指纹图谱检测方法和装置开展了研究,获取了基于黄酒中多类化学组分以及近红外光谱的黄酒酒龄特征指纹图谱；建立并对比了黄酒多种风味成分的近红外、中红外光谱定量分析模型；分析了温度对黄酒品质可见/近红外光谱检测精度的影响,确定了最佳检测温度水平,在此基础上开发了基于温度控制的黄酒品质实时检测系统。
本文的主要研究结果和结论如下：
(1)对2007年冬酿绍兴黄酒在陈酿3至45个月时间范围内,各种特征风味成分的含量变化进行了动态追踪检测。结果表明,在黄酒陈酿过程中：①6项常规指标中,酒精度和总糖含量呈下降趋势,非糖固形物和总酸含量则稳步上升,氨基酸态氮和pH的变化趋势不明显。除pH外,其余指标的含量随陈酿过程存在显著差异；②乳酸与总酸一致,含量不断增加,并存在显著性差异；③5个糖类指标中,葡萄糖含量变化趋势不明显,未检测出显著性差异。麦芽糖、异麦芽糖、潘糖和异麦芽三糖则存在显著性差异,但无明显变化趋势；④黄酒中的9种主要金属离子元素(Na、Mg、 A1、K、Ca、Mn、Fe、Cu、Zn)的含量在陈酿过程中均存在一定波动,无明显增加或降低趋势。除Ca与Cu外,其它7种元素均存在显著性差异；⑤16种游离氨基酸指标中,天门冬氨酸、谷氨酸、脯氨酸、异亮氨酸、亮氨酸、酪氨酸、赖氨酸、组氨酸、精氨酸及总氨基酸含量在陈酿过程中均有降低趋势,其余7种氨基酸(苏氨酸、丝氨酸、甘氨酸、丙氨酸、缬氨酸、蛋氨酸、苯丙氨酸)含量总体保持稳定。除天门冬氨酸、甘氨酸、丙氨酸、亮氨酸、酪氨酸和苯丙氨酸外,其余氨基酸的含量均存在显著差异；⑥11种挥发性成分指标(异丁醇、异戊醇、2,3-丁二醇、β-苯乙醇、丙三醇、乙酸乙酯、丁酸乙酯、乳酸乙酯、壬醛、苯甲醛、癸酸乙酯)中,异丁醇、异戊醇、壬醛、苯甲醛含量在陈酿中有所降低,丙三醇含量出现上升,其余指标含量均出现一定波动,无显著变化规律。
结果表明,黄酒中的大部分常规指标、乳酸、金属离子、氨基酸等化学组分,在陈酿过程中均参与了复杂的物理化学变化,使得其含量经历了显著的变化。但黄酒中主要糖类指标,葡萄糖的含量未检测出显著性差异,可推断糖类指标在陈酿过程中变化不大。由于所用检测方法的限制,11种挥发性成分中大部分指标未发现有明显变化趋势,其陈酿机理有待进一步研究。
(2)建立了基于以上各类化学组分的黄酒酒龄判别模型。结果如下：①基于6项常规指标主成分得分的SLDA1、以及基于其组分含量的SLDA2和PLS-DA酒龄判别正确率分别为50.6%,48.7%和75.7%；②基于5种糖类指标的SLDA1、SLDA2和PLS-DA酒龄判别模型的判别正确率分别为39.3%,36.4%和66.5%；③基于9种金属离子的SLDA1、SLDA2和PLS-DA酒龄判别模型的判别正确率分别达到72.7%,73.4%和81.4%；④综合常规指标、乳酸、糖类以及金属离子四类化学指标,所建立的SLDA1、 SLDA2和PLS-DA判别模型对酒龄的判别正确率分别为91.0%,86.6%和91.2%；⑤基于16种氨基酸指标的SLDA1、SLDA2和PLS-DA酒龄判别模型的判别正确率达到86.4%,85.6%和91.2%；⑥基于11种挥发性成分指标所建立的SLDA1、SLDA2和PLS-DA模型对酒龄的判别正确率分别为90.6%,90.6%和92.1%。
结果表明,综合常规指标、乳酸、糖类和金属离子,以及氨基酸、挥发性成分所建立的酒龄判别模型,最佳判别正确率均超过90%,可用于黄酒酒龄鉴别和酒龄指纹图谱检测方法的建立。
(3)分析了不同陈酿阶段黄酒基酒以及不同标注酒龄勾兑酒在800nm-2500nm范围内的近红外光谱,发现两者的光谱吸收特征一致,主要吸收峰均位于1455nm、1692nm、1776nm、2266nm、2302nm以及1900-1950nm处,与黄酒中的糖、酸、氨基酸等风味成分中的主要基团C-H、O-H、N-H等的吸收密切相关。主成分分析结果显示,不同酒龄的基酒和勾兑酒样品的均有明显聚类趋势。基于LDA、LS-SVM以及PLS-DA三种模式识别方法所建立的基酒酒龄判别模型,其建模集判别正确率分别为93.6%,98.7%和94.4%,预测集判别正确率分别为96.3%,91.3%和95.2%；勾兑酒酒龄的LDA、LS-SVM、PLS-DA以及DPLS模型的建模集判别正确率分别为85.0%,100%,99.2%和100%,预测集判别正确率分别为72.5%,87.5%,86.3%和95.0%。
结果表明近红外光谱能提取不同酒龄黄酒的整体差异信息,可用于基酒以及勾兑酒的酒龄的检测分析和指纹图谱的建立。
(4)建立了黄酒中的6项常规指标、乳酸、5种糖、16种氨基酸及总氨基酸含量的近红外、中红外光谱PLSR定量分析模型。①对常规指标和乳酸的分析结果表明,所建近红外、中红外光谱分析模型均可用于总糖、非糖固形物以及氨基酸态氮的定量分析(模型RPD>2.0),以及总酸、pH值、乳酸的定性分析(模型RPD>1.5)。除乳酸外,近红外光谱分析模型的性能均优于中红外光谱。②对糖类指标的分析结果表明,所建近、中红外光谱分析模型可用于葡萄糖含量的定量检测(模型RPD>2.0),异麦芽三糖的近红外光谱分析结果较优(模型RPD=1.95),而麦芽糖的中红外光谱分析结果较优(模型RPD=1.97),其余指标检测精度不佳,模型鲁棒性欠缺(模型RPD<1.5)。③对氨基酸指标的分析结果表明,近红外光谱分析模型性能普遍较优,除脯氨酸、苯丙氨酸、组氨酸以及总氨基酸外,其余指标定量分析模型的RPD值均超过1.5,其中,天门冬氨酸、异亮氨酸、酪氨酸、精氨酸模型的RPD值大于2.0。而中红外模型的鲁棒性普遍欠缺,仅天门冬氨酸、谷氨酸、异亮氨酸、苯丙氨酸模型的RPD值大于或等于1.5,丝氨酸模型的RPD值接近1.5,具有定性分析能力,其它指标均低于1.50。除脯氨酸和精氨酸外,近红外光谱模型的整体性能均优于中红外光谱。
结果表明,近红外、中红外光谱均可用于黄酒中主要常规指标、葡萄糖、乳酸,以及部分氨基酸指标的定量定性检测分析,近红外光谱分析模型的性能总体优于中红外光谱。
(5)分析了5℃,10℃,15℃,20℃,25℃,30℃,35℃温度水平下黄酒样品的可见／近红外光谱(303-1700nm)的变化规律。原始光谱中,在1340-1480nm波段范围内,在高频(短波)波段,吸收峰随着温度的上升而逐渐增高,反之,在低频(长波)波段,吸收峰随着温度上升而不断降低。二阶微分光谱中,在1320nm和1358nm处的吸收峰值随温度上升而增强,而1404nm处峰值随温度上升而降低。主成分分析结果显示不同温度下的样品光谱有较明显的聚类趋势,表明温度对黄酒的可见／近红外光谱影响显著。由于氢键结合会使得水分子的伸缩振动向高频转移,而弯曲振动则向低频转移。温度越高会促使氢键发生结合,从而伸缩振动会向高频(短波)转移,由此造成样品光谱发生变化。
建立了不同温度下黄酒品质指标的SMLR定量分析模型,确定了酒精度、总糖、非糖固形物、总酸以及氨基酸态氮的最佳检测温度分别为：15℃,20℃,20℃,15℃和20℃。酒精度、总糖模型的精度较高,鲁棒性优(模型RPD>2.5),总酸模型精度一般,仅具有定性分析能力(模型RPD>1.5),非糖固形物以及氨基酸态氮模型精度不佳(模型RPD<1.5)。运用7个温度下的黄酒样品光谱建立了酒精度、总糖和总酸的温度补偿检测模型。结果表明,酒精度的温度补偿效果较优(模型RPD=3.81),而总糖和总酸温度补偿效果不佳(模型RPD<1.5)。
利用蔡司便携式光谱仪及其外部程序开发包、光纤、控温样品池,构建和开发了基于可见／近红外光谱的黄酒品质(酒精度、总糖以及总酸)实时检测的软、硬件系统,并对该检测装置的性能进行了实验验证。在15℃水平下,对37个样品的检测结果为：①酒精度的预测相关系数rp、RMSEP以及RPD值分别为0.979,0.464%和3.78；②总糖的rp, RMSEP以及RPD值分别为0.766,5.78g/L和1.50；③总酸的rp、RMSEP以及RPD值分别为0.630,0.664g/L和1.24。结果表明该检测系统可用于酒精度的准确定量检测,但总糖和总酸指标的检测精度不佳,模型精度有待提升。
Chinese rice wine is the most ancient unique wine kind of nutrition and health in China, and be honored as "essence" of the country. However, at present, the basic research towards rice wine is relative weak. The detailed changes in various flavor components during rice wine aging still remain uncertain. In additional, due to the backward technologies used in quality control of rice wine, only a few routine chemical parameters, such as alcohol degree, total sugars, total acids, were analyzed in conventional testes. Little is known about the small amounts of functional components that are closely related to its flavor, which cannot meet consumers'higher requirements towards rice wine products. It also remains as a barrier for the growth of rice wine industry. This study is a further extension of the former research projects carried out by our group members (flavor components quantification and age discrimination of rice wines based on NIR spectroscopy), with its aim to establish analytical methods and devices based on fingerprint techniques for aging status characterization as well as quality control and risk assessment of rice wine products.
The object of this research is Shaoxing rice wine, which is the best representation of Chinese rice wine. Multiple technologies based on instrument analysis, VIS/NIR, NIR and MIR spectroscopy were applied as fingerprint techniques for quality evaluation of rice wine. Fingerprints of rice wine of various ageing status based on chemical compositions as well as NIR spectra were obtained. Quantification of flavor components in rice wine based on both NIR and MIR spectroscopy was also undertaken and compared. The effect of temperature on the performance for rice wine quality determination based on VIS/NIR spectroscopy was investigated, and the optimal temperature level was determined. A hardware and software system for quality determination of rice wine products based on temperature control was then developed.
The main contents and conclusions were:
(1) Continuous tracing of the changes in various flavor components in Shaoxing wines during the aging period of3to45months was undertaken. The results showed that,①Among six routine parameters, the content of alcohol degree and total sugar decreased, while the content of non-sugar solid and total acid increased. The change of pH and amino acid nitrogen was not clear. Besides pH, the remaining five indexes were all found to be significant different.②The content of lactic acid increased, similar to total acid. Significant difference was also detected.③Among five sugars, the change of glucose was not obvious, and no significant difference between different aging status was detected. The remaining four sugar parameters were all significant different, but their changes were also not obvious.④The content of Na, Mg, Al, K, Ca, Mn, Fe, Cu and Zn in rice wines fluctuated during aging, no obvious increase or decrease trend was observed. Besides Ca and Cu, other elements were all found to be significantly modified during ageing.⑤Among16free amino acids, the content of aspartic acid, glutamic acid, proline, isoleucine, leucine, tyrosine, lysine, histidine, arginine and total amino acids decreased, while the remaining threonine, serine, glycine, alanine, valine, methionine, phenylalanine remained relative stable. Besides aspartic acid, glycine, alanine, leucine, tyrosine and phenylalanine, other amino acids were all found to be significant different.⑥Among11volatile components, the content of isobutanol, isoamylol, nonanal and benzaldehyde decreased, while the content of glycerol increased. The changes of others were not obvious. Significant different was detected for all volatile parameters.
The results indicated that most of routine parameters, lactic acid, elements, and amino acids, were involved in the complicated physical and chemical reactions in rice wine, and went through significant changes during aging. However, glucose was detected not to be significant different, which suggested that sugars might not go through obvious changes. The changes of most volatile compounds were not obvious, and further research was needed.
(2) Aging status discrimination models were established based on the above chemical compositions. The results showed:①The accuracy obtained by SLDA1(base on PCs), SLDA2(based on chemical compositions) and PLS-DA models was50.6%,48.7%and 75.7%, respectively based on six routine parameters.②The accuracy obtained by SLDA1, SLDA2and PLS-DA models was39.3%,36.4%and66.5%, respectively based on sugars.③Based on nine mineral elements, the accuracy obtained by SLDA1, SLDA2and PLS-DA models was72.7%,73.4%and81.4%, respectively.④The accuracy obtained by SLDA1, SLDA2and PLS-DA models was91.0%,86.6%and91.2%, respectively based on routine parameters, lactic acid, sugars and elements.⑤SLDA1, SLDA2and PLS-DA models based on16amino acids gave the accuracy of86.4%,85.6%and91.2%, respectively.⑥The accuracy obtained by SLDA1, SLDA2and PLS-DA models was90.6%,90.6%and92.1%, respectively based on11volatile compounds.
The results indicated that the discrimination models based on routine parameters, lactic acid, sugars and elements, as well as amino acids and volatile compounds reached a relative high accuracy over90%. These flavor components could be applied as fingerprint for aging status characterization of rice wine.
(3) NIR spectra of base and blended rice wines in the range of800-2500nm were analyzed and compared. The main absorption peaks were all found to be at round1455nm,1692nm,1776nm,2266nm,2302nm and1900-1950nm, related to C-H, O-H, N-H functional groups in sugars, acids, amino acids of rice wines. PCA results showed that both base and blended rice wines of different aging status could be separated clearly. LDA, LS-SVM and PLS-DA were used to establish models for base rice wine age discrimination. The accuracy obtained were93.6%,98.7%and94.4%, respectively in calibration, and96.3%,91.3%and95.2%in prediction. For blended rice wine discrimination, the accuracy obtained in calibration were85.0%,100%,99.2%and100%by LDA, LS-SVM, PLS-DA and DPLS. And were72.5%,87.5%,86.3%and95.0%in prediction.
The results indicated that NIR spectroscopy can obtain the holistic difference between samples, and can be used to establish fingerprint of rice wine of different aging status or ages.
(4) PLSR quantification of routine parameters, lactic acid, sugars and amino acids in rice wine based on NIR and MIR spectroscopy was carried out. The results showed:①For the determination of routine parameters and lactic acid, both NIR and MIR spectroscopy could be used for quantitative analysis of total sugar, non-sugar solid and amino acid nitrogen. The RPD values of the models were all above2.0. Total acid, pH and lactic acid could be qualitative analyzed with RPD values above1.5. Besides lactic acid, the performances of NIR models were superior to MIR models.②For the determination of sugars, the quantification of glucose was satisfactory by both NIR and MIR spectroscopy with an RPD value above2.0. NIR was more suitable for analysis of isomaltotriose (RPD=1.95), while MIR was more suitable for analysis of maltose (RPD=1.97). For other parameters, the performance of the models was not satisfactory.③For the determination of amino acids, the performance of NIR models were generally much superior. Besides proline, phenylalanine, histidine and total amino acids, the RPD values of NIR models were all over1.5. In addition, the RPD values obtained for aspartic acid, isoleucine, tyrosine, and arginine were over2.0. The robustness of most MIR models was not satisfactory. RPD values obtained for aspartic acid, glutamic acid, isoleucine, phenylalanine and serine were above or close to1.5. For other amino acids, the robustness of the models was low (RPD<1.5).
The results indicated that both NIR and MIR spectroscopy could be used for the analysis of routine parameters, lactic acid, sugars and some amino acids. But the performances of NIR models were generally better than MIR models.
(5) The VIS/NIR spectra of rice wine samples in the range of303-1700nm under different temperature levels (5℃,10℃,15℃,20℃,25℃,30℃,35℃) were investigated. In high frequency (short-wave) region of1340-1480nm of raw spectra, the absorption increased when the temperature raised. On the contrary, in low frequency region, the absorption decreased when the temperature dropped. In second derivative spectra, the absorption at1320nm and1358nm increased with temperature. However, at1404nm, the absorption decreased with temperature. PCA results indicated that the samples under different temperature levels could be clearly separated. Because the hydrogen bonding will cause a shift of stretching vibration of water molecular to high frequency. As the temperature rises, it will promote hydrogen bonding, which might cause a change in the sample spectra.
The determination of five routine parameters in rice wine was carried out by SMLR method under different temperature levels. The optimal temperature for quantification of alcohol degree, total sugar, non-sugar solid, total acid and amino acid nitrogen was found to be15℃,20℃,20℃,15℃and20℃, respectively. The model developed for alcohol degree and total sugar were relative robustness with an RPD value over2.5. The total acid model was moderate with an RPD value over1.5. However, the determination of non-sugar solid and amino acid nitrogen was not satisfactory due to low a RPD value (RPD<1.5). Temperature compensation models were established for alcohol degree, total sugar and total acid based on the spectra obtained under seven temperature levels. The compensation for alcohol degree showed good performance with a RPD value of the model to3.81. However, the compensation for total sugar and total acid was not satisfactory and needed to be improved (RPD<1.5).
Finally, a hardware and software system was developed for quality determination of rice wine based on VIS/NIR spectroscopy, with the use of Zeiss portable spectrometer, optical fiber and temperature-controlled cuvette holder. The performance of the detection device was validated by37additional samples under temperature level of15℃. The results showed that:①For the determination of alcohol degree, the correlation coefficient in prediction, RMSEP and RPD was found to be0.979,0.464%and3.78, respectively.②For total sugar parameter, the correlation coefficient in prediction, RMSEP and RPD was0.766,5.78g/L and1.50, respectively.③The correlation coefficient in prediction, RMSEP and RPD was0.630,0.664g/L and1.24, respectively for total acid. The results indicated that the device might be suitable for alcohol degree detection in rice wine. But the precision for total sugar and total acid determination needed improvement.
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