Prediction of chemical,physical and sensory data from process parameters for frozen cod using multivariate analysis

Physical, chemical and sensory quality parameters were determined for 115 cod (Gadus morhua) samples stored under varying frozen storage conditions. Five different process parameters (period of frozen storage, frozen storage temperature, place of catch, season for catching and state of rigor) were varied systematically at two levels. The data obtained were evaluated using the multivariate methods, principal component analysis (PCA) and partial least squares (PLS) regression. The PCA models were used to identify which process parameters were actually most important for the quality of the frozen cod. PLS models that were able to predict the physical, chemical and sensory quality parameters from the process parameters of the frozen raw material were generated. The prediction abilities of the PLS models were good enough to give reasonable results even when the process parameters were characterised by ones and zeroes only. These results illustrate the application of multivariate analysis as an effective strategy for improving the quality of frozen fish products. © 1998 Society of Chemical Industry.     

牛肉酶解物对牛肉特征香味形成的影响研究

以五种不同水解度牛肉酶解物分别制备得到5种热反应牛肉香精。利用定量感官分析和GCMS-O分析考察了5种热反应牛肉香精香气成分的变化。结果显示,添加DH29.13%酶解液的牛肉香精样品其牛肉味、肉香味和仿真度相比于其它样品是最强的。GC-O分析也发现DH29.13%的牛肉酶解液赋予形成了种类较多的香气活性化合物,而没有添加牛肉酶解物的肉味香精缺失了这些特征化合物。利用PLSR进行了香气活性化合物、感官评价和牛肉酶解液的肽分子量分布之间的相关性分析,进一步解释了DH为29.13%的牛肉酶解液是赋予热加工牛肉风味的最合适风味前体。     

Sensory flavour discrimination of Greek dry red wines

Aroma (16) and oral (17)—flavour by mouth, after‐taste and mouthfeel—attributes were separately profiled in 27 Greek red wines, products of single Greek indigenous grapes (Aghiorghitiko and Xinomavro) and international (Syrah and Cabernet Sauvignon) varieties and blends. From univariate analysis (ANOVA) of assessor data, 6 of 16 aroma and 16 of 17 oral attributes were significant (P < 0.05) in discriminations. Principal component analysis (PCA) product spaces of aroma and oral attributes explained 40% and 71% variance respectively. Discriminant partial least‐squares regression (DPLS), ANOVA and PCA discerned similar influences of variety and region of origin. Coding DPLS2 for variety, 76% and 38% of oral and aroma attribute variance respectively, and 39% and 18% category respectively were explained. Aghiorghitiko usage conferred fruity and sweet tastes and after‐tastes and smooth mouthfeel, typical of Peleponnese wines where this cultivar dominates. In contrast, Xinomavro products were bitter and sour in taste and bitter in after‐taste, with astringent and dry/dehydrating mouthfeel, but this was not characteristic of all wines from Macedonia. Copyright © 2003 Society of Chemical Industry     

地沟油模式识别技术的研究

借鉴中药指纹图谱的研究思路,在优选的色谱条件下,采用气相色谱法对16个样品进行分析,利用相似度软件筛选出12个共有峰,通过方法学验证,12个共有峰精密度、稳定性的RSD分别小于2.6%和6.1%。在此基础上,采用主成分分析（PAC）和偏最小二乘判别（PLS-DA）,对16个样品的12个共有峰进行化学计量学研究,建立地沟油模式识别模型。利用所建立的地沟油模式识别模型对16个样品（7个正品油,9个地沟油）进行判别分析,结果表明:所建立的模式识别模型能较好的区分地沟油和正品油。本方法仅使用气相色谱（GC）,结合化学计量学分析,简单快速,便于推广,可用于地沟油的快速鉴别。      

化学计量学方法在果蔬领域的应用

果蔬富含维生素、矿物质和膳食纤维等营养物质,是人们补充营养必不可少的食品之一。但果蔬在加工储存过程中存在农药残留、营养成分损失、品质下降等一系列问题,如何保证果蔬的食用安全和食用品质一直是果蔬研究领域的焦点。测定果蔬的营养理化指标是评价果蔬品质的有效手段,然而过多的指标通常会产生大量繁杂冗余的数据,需要专门的工具对数据进行分析处理。化学计量学方法是进行数据处理的有效手段,近年来在果蔬生产加工方面已得到广泛应用。本文综述了主成分分析、偏最小二乘和人工神经网络等化学计量学方法在果蔬品质差异评价、果蔬农药残留检测、果蔬理化分析、果蔬保鲜效果优劣及果蔬生产工艺优化等方面的应用,讨论了各种方法的优缺点,为化学计量学方法在果蔬领域中的应用提供参考。     

基于电子舌技术区分酸奶的滋味

为探索应用电子舌区分酸奶滋味的可行性,以原味酸奶和风味酸奶为研究对象,应用电子舌交叉选择型传感器进行检测,获得酸奶响应信号值,采用主成分分析(PCA)、判别因子分析(DFA)对酸奶响应信号值进行分类辨别,并通过PCA、偏最小二乘法(PLSR)将感官评定值与响应值做相关性分析。结果表明:基于PCA、DFA方法分析响应信号值,电子舌技术能很好地辨别不同的酸奶。PLSR模型可以较好的预测酸奶的滋味品质,HA传感器与甜和鲜味具有相关性,以PC1为轴,它们呈显著负相关(p<0.05),苦味与BB和JB两根传感器以PC1轴呈显著正相关(p<0.05)。      

化学计量学——光度法在食品多组份分析中的应用评述

本文对化学计量学光度法在食品多组分分析中的应用进行了评述,并简要介绍和讨论了多元线性回归、因子分析法、主成分回归、偏最小二乘法、卡尔曼滤波、人工神经网络及其在食品分析中的应用。引用文献90篇。     

基于PLSR鹰嘴豆蛋白美拉德风味肽最适底物的研究

本实验以鹰嘴豆蛋白为原料,通过双酶定向酶解制备一系列不同水解度(DH%)鹰嘴豆蛋白酶解液,以此为底物采用描述性感官分析(DSA)和气质联用技术(GC-MS)分析比较经模式美拉德反应体系制备所获得风味肽产品的风味特征,以期获得美拉德风味肽最适鹰嘴豆蛋白酶解体系。结果表明:由不同DH%鹰嘴豆蛋白酶解液为底物制备的美拉德风味肽产品在感官属性和形成的香气成分上呈现显著差异,当添加DH%为23.03%~26.02%的酶解液制得的美拉德风味肽其所形成的香气种类和数量相对较多,同时呈现明显的肉味、鲜味和较长的持续感。结合偏最小二乘回归(PLSR)对其香气物质、感官分析数据和电子鼻响应值进行相关性分析,进一步表明DH%为23.03%~26.02%的鹰嘴豆蛋白酶解液可作为风味肽产品热反应最适反应底物。     

Application of multivariate statistical methods to extend the authenticity control of flavour constituents of apple juice

 The distribution of 15 aroma constituents, including the (R)- and (S)-enantiomers of ethyl 2-methylbutanoate, in 30 commercially available and laboratory prepared apple juices was evaluated by multivariate statistical methods. Principal component analysis and cluster analysis revealed ethyl 3-methylbutanoate, 3-methylbutyl acetate and (R)-ethyl 2-methylbutanoate as key components for the differentiation of apple juices. In freshly pressed and some commercial juices ethyl 3-methylbutanoate and 3-methylbutyl acetate were not present, and the (S):(R) ratio of ethyl 2-methylbutanoate was found to be >99 : 1%. Another group of commercial products was separated in which the amounts of ethyl 3-methylbutanoate and 3-methylbutyl acetate exceeded 1 μg/l and 180 μg/l, respectively, and in which the (S):(R) ratio of ethyl 2-methylbutanoate was <97 : 3%. The statistical data confirmed the high selectivity of apple fruit tissue in biosynthesizing 2-methylbutyl and 2-methylbutanoate esters, and could also be used to extend the results of enantio-multidimensional gas chromatography and other authenticity analyses. Received: 20 April 1998 / Revised version: 23 June 1998     

Development of a model for intensity of flavour character in blackcurrant concentrates

The feasibility of routine quantification of flavour character intensity in fruit concentrates by chromatography was studied. A set of 37 volatile components, previously identified as flavour-active by gas chromatography-olfactometry, were quantified in 133 different blackcurrant concentrates from three seasons, by gas chromatography with flame ionisation detection. Sensory data on intensities of flavour character in these concentrates were obtained using ratio scaling. Partial least squares regression (PLS) was employed to develop models describing relationships between intensity of flavour character and concentrations of specific flavour components. Separate models were obtained for concentrates produced within three single seasons. Individual concentrates varied in: geographical origin; post-harvest fruit storage (chilled or frozen); and concentration strategy, either conventional thermal or freeze technology. Cross-validation (by PLS) determined the number of correlation factors required to reach minimum prediction error for each model. The final model had a regression coefficient of 0.80, dependent upon 10 flavour components, and was suited for predicting flavour character intensity in blackcurrant drinks from concentrates. © 1999 Society of Chemical Industry     

Identification of Drivers of Liking for Bar‐Type Snacks Based on Individual Consumer Preference

Understanding consumer hedonic responses on food products are of greatest interests in global food industry. A global partial least square regression (GPLSR) had been well accepted method for understanding consumer preferences. Recently, individual partial least square regression (IPLSR) was accepted as an alternative method of predicting consumer preferences on given food product, because it utilizes the individual differences on product acceptability. To improve the understanding of what constitutes bar‐type snack preference, the relationship between sensory attributes and consumer overall liking for 12 bar‐type snacks was determined. Sensory attributes that drive consumer product likings were analyzed using averaged‐consumer data by GPLSR. To facilitate the interpretation of individual consumer liking, a dummy matrix for the significant weighted regression coefficients of each consumer derived from IPLSR was created. From the application of GPLSR and IPLSR, current study revealed that chocolate and cereal‐flavored bars were preferred over fruit‐flavored bars. Attributes connected to chocolate flavor positively influenced consumer overall likings on the global and individual consumer levels. Textural attributes affected liking only on the individual level. To fully capture the importance of sensory attributes on consumer preference, the use of GPLSR in conjunction with IPLSR is recommended.     

近红外技术对不同动物来源肉掺假的检测

采用近红外光谱结合主成分分析法(PCA)、判别分析法,分别建立了牛肉和羊肉中掺杂其它动物肉的定性鉴别模型,根据鉴别准确率评价模型的预测性能。采用近红外光谱结合PCA、偏最小二乘法(PLS),建立了掺假物的定量检测模型,根据模型对预测集样品的预测均方差(RMSEP)以及预测值与实测值间的相关系数(r)验证模型的预测能力。结果,牛肉掺猪肉模型对训练集和预测集的鉴别准确率分别为97.86%和91.23%,羊肉掺猪肉模型对训练集和预测集的鉴别准确率分别为98.28%和92.98%,羊肉掺鸭肉模型对训练集和预测集的鉴别准确率分别为99.59%和93.97%,羊肉掺假模型对训练集和预测集的鉴别准确率分别为97.57%和90.76%。牛肉掺假定量模型对训练集的交互验证均方差(RMSECV)和预测集的RMSEP分别为3.87%和4.13%,r分别为0.9505和0.9134;羊肉掺假定量模型对训练集的RMSECV和预测集的RMSEP分别为4.48%和4.86%,r分别为0.9306和0.9082。表明近红外技术结合一定的化学计量学方法可实现不同动物来源肉掺假的鉴别,且能够对掺假物进行定量检测。      

油桃采后衰老与病害发生中品质与活性氧代谢相关性分析

探讨油桃果实在采后衰老与病害发生中近果核和近表皮处的品质与活性氧代谢的相关性。结果显示油桃采后衰老与病害发生中膜完整性、过氧化物酶(p er o x id as e,P O D)活性呈下降趋势,岀汁率、脂氧合酶(lipoxygenase,LOX)活性、H2O2含量呈升高趋势,过氧化氢酶(catalase,CAT)、抗坏血酸过氧化物酶(ascorbateperoxidase,APX)、多酚氧化酶(polyphenol oxidase,PPO)比活力呈先升高后下降的趋势。偏最小二乘回归分析结果表明:膜完整性与岀汁率、H2O2、LOX呈负相关,与POD、APX呈正相关。通径分析得出APX、POD、PPO对H2O2含量变化有强的负直接作用,其作用由强到弱为APX>POD>LOX。为进一步探讨相关酶在采后油桃果实抵抗病原菌侵染过程中所起的作用提供理论依据。     

盐池滩羊肉脂肪含量的高光谱预测模型构建

本文利用可见-近红外高光谱成像技术预测冷鲜滩羊肉脂肪含量,优选最佳预测模型。测定90个滩羊背最长肌的脂肪含量并采集其光谱图像,对原始光谱进行不同种预处理后,构建了全波段下的偏最小二乘回归(PLSR)和主成分回归(PCR)的光谱预测模型。为减少模型运算次数,在预处理效果最优的全波段模型上采用连续投影算法(SPA)、应用竞争性自适应重加权(CARS)、变量组合集群分析(VCPA)和波长空间迭代收缩(IVISSA)方法提取特征波长,构建脂肪含量的光谱预测模型。结果表明:采用归一化(Normlize)预处理后光谱构建的PLSR全波段模型效果最好,校正集模型相关系数(Rc)达到0.921;采用多元散射校正(MSC)预处理后光谱构建的PCR全波段模型效果最好,其校正集模型相关系数(Rc)达到0.850;在4种提取特征波长过程中,IVISSA算法所提取特征波长的交互验证均方根误差(RMSECV)最低,为0.0072;Normlize-IVISSA-PLSR模型较其他3种算法所构建的PLSR模型效果最优,其校正集相关系数(Rc)和预测集相关系数(Rp)值分别为0.931和0.754,表明利用高光谱技术对盐池滩羊肉脂肪含量进行预测是可行的。研究成果为冷鲜滩羊肉品质在线光谱快速无损检测系统开发提供理论依据。     

Refining the Prediction of Potential Malt Fermentability by Including an Assessment of Limit Dextrinase Thermostability and Additional Measures of Malt Modification,Using Two Different Methods for Multivariate Model Development

Prediction of malt fermentability (apparent attenuation limit — AAL) by measurement of the diastatic power enzymes (DPE), α‐amylase, total limit dextrinase, total β‐amylase, β‐amylase thermostability, and the Kolbach index (KI or free amino nitrogen — FAN) is superior to the conventional use of diastatic power (DP) alone. The thermostability of β‐amylase is known to be an important factor in determining fermentability, thus the thermostability of the other relatively thermolabile enzyme, limit dextrinase, was investigated to determine if it was also useful in predicting fermentability. To facilitate this aim, methods were developed for a rapid and cost efficient assay of both β‐amylase and limit dextrinase thermostability. Internationally important Australian and international malting varieties were compared for their total limit dextrinase and β‐amylase activity and thermostability. Interestingly, the level of limit dextrinase thermostability was observed to be inversely correlated with total limit dextrinase activity. The prediction of malt fermentability was achieved by both forward step‐wise multi‐linear regression (MLR) and the partial least squares (PLS) multivariate model development methods. Both methods produced similar identifications of the parameters predicting wort fermentability at similar levels of predictive power. Both models were substantially better at predicting fermentability than the traditional use of DP on its own. The emphasis of this study was on the identification of predictive factors that can be consistently used in models to predict fermentability, because the model parameter estimates will subtly vary depending on mashing conditions, yeast strain/fermentation conditions and malt source. The application of these multivariate model development methods (PLS and MLR) enabled the identification of further potential fermentability predicting factors. The analyses divided the predictive parameters into those defined by DP enzymes and those associated with modification (KI, FAN, fine/coarse difference, wort β‐glucan and friability). Surprisingly, limit dextrinase thermostability was not a substantial predictor of fermentability, presumably due to its negative correlation with total limit dextrinase activity. The application of these insights in the malting and brewing industries is expected to result in substantial improvements in brewing consistency and enable more specific quality targets for barley breeder's progeny selection cut‐off limits to be more precisely defined.     

NIR高光谱成像技术联用SPA算法 快速检测五花肉的过氧化值

利用近红外(NIR)高光谱成像技术结合连续投影算法(SPA)快速、无损检测五花肉的过氧化值。通过高光谱成像系统采集样品的光谱图像,提取其反射光谱信息,经过基线校正(BC)、高斯滤波平滑(GFS)、中值滤波平滑(MFS)、卷积平滑(SGS)、移动平均值平滑(MAS)、标准正态变量变换(SNV)、多元散射校正(MSC)七种预处理后,利用偏最小二乘(PLS)建立预测模型。使用SPA筛选最优波长,重新预算,构建优化的PLS模型和多元线性回归(MLR)模型。结果显示,经过BC预处理(R_P=0.960,RMSEP=5.15×10^-4g/100 g)和原始数据RAW(R_P=0.960,RMSEP=4.89×10^-4g/100 g)的全波段PLS模型(F-PLS)预测过氧化值效果较好。优化结果显示,RAW的MLR模型(R_P=0.968,RMSEP=4.12×10^-4 g/100 g)预测效果更好。研究表明,NIR高光谱成像技术联用SPA算法可潜在实现对五花肉过氧化值的快速无损检测。     

基于LF-NMR弛豫特性的煎炸油总极性化合物含量定量建模方法

将低场核磁共振（low field nuclear magnetic resonance,LF-NMR）分析技术应用于煎炸油脂总极性化合物（total polar compounds,TPC）含量的预测。采用柱层析方法测定油脂样品的TPC含量作为测定值,采集油脂样品的LF-NMR弛豫特性（峰起始时间T21、T22、T23相应的峰面积比例S21、S22、S23、单组分弛豫时间T2W）,分别利用向后筛选多元回归分析、主成分回归分析和偏最小二乘回归分析建立LF-NMR弛豫特性与TPC含量的回归方程,比较3 种模型的校正集和预测集的决定系数与均方根误差,最终确定最优模型为偏最小二乘回归模型。应用此模型预测预测集样品TPC含量,决定系数R2可达0.928,预测集均方根误差为0.568%,模型稳定。