投影地图法在食品研究与开发中的研究现状

随着感官分析方法在食品工业中的广泛应用,研究人员对分析技术的要求不断提高,快速感官分析方法应运而生,投影地图法（Projective Mapping）是其中之一。投影地图法能够快速收集产品的感官属性,分析产品之间感官特征的相似性或差异性;也可以结合喜好问卷,区分人群类别并探究影响消费者喜好的因素。本文对近年来投影地图法相关文献进行研究,介绍了该方法的实验流程、影响因素及数据处理、优势与局限性、衍生方法及其在不同类型食品中的研究等,并展望了这一方法的发展前景,以期为食品感官评价相关领域的研究人员和企业提供借鉴。     

开放式提问调查在食品研究与开发中的研究现状

开放式提问调查（Open-ended questions）应用于食品感官分析中,一般要求评价人员用自己的语言描述产品,旨在理解消费者对产品主要特征的感知;也可以结合喜好度调查,探究影响消费者喜好和购买意向的因素。本文主要介绍了开放式提问调查的定义、实施、数据预处理、数据分析、在食品研究中的应用、此方法的优势和局限性以及与其他快速感官分析方法的比较,并展望这一方法的发展前景,以期对需要进行产品感官分析的企业或相关领域科学研究人员提供借鉴。     

归类法在食品研究与开发中的应用及研究现状

感官分析方法广泛应用于食品工业中,由于传统感官分析方法具有培训时间长、投入大等局限性,因此多种快速分析方法得到发展,归类法（Sorting）就是其中一种。归类法要求评价人员根据产品感官特征的相似性进行归类,利用因子分析和聚类分析等多元统计方法分析数据,从而快速获得产品的感官分布图。本文主要对归类法的实验设计、数据处理、发展情况、在食品研究中的应用以及优势和局限性进行综述,并对归类法的发展趋势进行了展望,旨在为该方法在食品工业中的进一步研究和应用提供借鉴。     

基于网络大数据研究不同区域消费者对红烧肉感官属性及其描述的差异性

以8 个不同省市的红烧肉为研究对象,通过网络爬虫获取消费者对其关键感官属性的评价数据,绘制食品风味图谱,建立红烧肉感官分析描述词汇表,采用大数据分析和相关性分析等多元统计分析方法,从多维角度探究消费者的喜好性和不同省市间红烧肉感官属性特征的相关性和差异性规律。结果表明：近两年来消费者更加倾向于追求肉质入口即化、烂糊、肥而不腻、滋味新鲜、香且味道稍甜的红烧肉,不同省市间红烧肉感官属性的主体特征明显且差异较大,肥而不腻（不腻）是所有省市红烧肉感官属性的主体特征,烂和糯是“腻口性”的标度词,甜味、辣味和咸味对该标度词影响显著（P＜0.05）,具体表现为甜味与烂的相关系数为0.707,辣味、咸味与糯的相关系数分别为0.815和－0.654,说明消费者喜好具有甜味、质地较烂或者具有辣味、质地软糯且咸味适宜的红烧肉。     

基于脑电波分析的消费者啤酒饮用喜好度研究

该研究将新型的消费者脑电波提取分析技术与传统感官评测相结合，建立一种智能消费者啤酒喜好度测试方法。通过建立标准化的品酒流程，收集消费者在品酒过程中脑电波的实时变化，并经过去伪、滤波、特征提取等步骤进行数据清洗，整理出8种不同类型脑电波数据和2种情绪数据，并将其进行建模得到饮酒综合情绪指数(index of alcohol-drinking analysis, IAA)。通过IAA赋分进行消费者饮酒喜好度的判断，并将其与感官问卷数据进行对比分析。研究发现，IAA指数消费者啤酒饮用喜好度的评价与感官问卷结果的一致性为83%,且能快速分析消费者在不同饮酒阶段喜好度的实时变化，有很好的实用性，对现有感官测评方式是很好的补充和改善。     

板栗面皮品质评价模型的建立

为建立板栗面皮品质评价模型,对15份板栗面皮进行品质评价方法研究。经逐步回归、拟合检验及相关性分析,将色泽、质感及滋味确定为新的感官评价指标,拟合检验表明新的感官评价方程(R^2=0.97)可代替原评价方法。经因子分析及多元线性回归分析,以L值、硬度、感官弹性为模型自变量,新感官评价得分为因变量,并建立品质评价模型,方差扩大因子检验VIF<10,表明其无多重共线性。新的评价方法优化了品质评价体系,可为板栗面皮工业生产提供相关理论指导。     

消费者Check-all-that-apply和喜好度测试在植物近水饮料感官评定中的应用研究

本研究采用check-all-that-apply（CATA）法与喜好9点标度法相结合的消费者快速感官评价方法,对马尾松、淡竹叶、桑叶、菊花、桂花、薄荷、紫苏、桦树汁露8种草本植物近水饮料的感官特征进行分析。消费者在19个口感和24个气味属性描述词中勾选,对8款近水饮料样品进行感官和喜好度评定。喜好度分析结果表明,消费者对8款植物近水饮料的喜好度存在差异,消费者对薄荷露和桂花露整体喜好度较高,两者差异不显著（P<0.05）。Cochran’s Q test分析结果表明,样品在41个感官属性中均存在显著性差异（P<0.05）。对应分析（Correspondence Analysis,CA）结果说明了8种植物近水饮料之间感官特征的差异,薄荷露感官特征突出,具有清凉、薄荷的特征属性;桂花露感官属性主要表现为桂花香、桃香、甜香;菊花露、紫苏露、桑叶露具有相似的绿茶、甘草、菊花等感官属性;马尾松与淡竹叶露感官特征相似;桦树汁露感官特征不明显。结合消费者李克特量表数据进行惩罚分析（Penalty Analysis,PA）,本研究发现注重健康人群并未对产品中草药气味表现出显著的不接受;有饮水添加助饮物习惯的人群更偏好甜香、清凉、金银花的感官特征。因此,消费者快速感官评价CATA法能够有效测试产品的感官属性和消费者偏好,并在新产品开发和市场调研方向展现出广阔的应用前景。     

多元因子分析在卷烟风格特征剖析中的应用

为了剖析卷烟风格特征,将上海、云南和河南6种卷烟的烟气化学成分按照香味特征分为辛香、甜香、果香和清香4类,应用多元因子分析(Multiple Factor Analysis,MFA)法对分类化学成分与感官评价结果进行了综合分析,并比较了采用化学成分和感官评价两种方法剖析卷烟风格特征时的一致性.结果表明:①不同的卷烟具有各自的风格特征;②MFA综合模型优于单独的化学成分和感官评价主成分分析(Principal Component Analysis,PCA);③辛香成分与感官评价结果的一致性较好,果香和甜香成分次之,清香成分差异较大.该方法适用于卷烟的质量评价与控制,可辅助卷烟生产.     

挤压型速冻青稞鱼面品质评价模型的建立

为准确评价速冻青稞鱼面的品质,以不同配方和加工工艺制作出的63份鱼面为试验材料,进行鱼面的品质评价方法研究。经相关性分析、逐步回归分析及拟合检验,精简鱼面感官评价项目,其品质评价指标可以被简化为4项,分别为色泽、光滑性、韧性、适口性,其权重分别为15.15%、8.5%、42.85%、33.5%,拟合检验表明新方法(R2=0.998)可代替原始方法。鱼面的质构指标和蒸煮品质指标作为自变量,感官评价新方法的得分为因变量建立模型,对各指标进行多元线性回归和因子分析,选取咀嚼性、硬度、弹性为模型的自变量,建立多元线性回归方程,该模型各系数无明显多重共线性(VIF10),模型拟合较好。新的品质评价方法简化了原有品质评价体系,具有感官指标较少、差异易被区别、准确性和可行性较高的特点,为速冻青稞鱼面工业化规模生产提供理论指导。     

特香型白酒风味轮的构建及典型感官特性描述研究

参照国内外酒类风味轮的建立的方法及国际标准ISO11035感官描述语选择方法,对31种特香型酒样,包括不同年份原酒、典型成品酒等进行感官描述分析,获得特香型白酒风味描述语,首次绘制得特香型白酒风味轮。进一步利用多元统计分析方法确定了重要的、具有典型差异的风味轮廓描述语,包括9种味觉描述语和11种嗅觉描述语。这些描述语经由品评小组应用于特香型白酒描述分析,表明可以表征特香型白酒主要的风味感官特征,可用于特香型白酒描述性感官分析。     

Investigation of Microfibril Angle of Flax Fibers Using X-Ray Diffraction and Scanning Electron Microscopy

ABSTRACT

Microfibril angle (MFA) of secondary cell wall has an important effect on the mechanical properties of flax fibers. It is therefore essential to study the relationships between MFA and mechanical properties. This paper investigated MFA of seven flax fibers by using X-ray diffraction (0.6T method) and scanning electron microscopy (SEM; direct observation). The results showed that there is no significant difference between MFA obtained by X-ray diffraction (6.2–7.2°) and SEM (5.8–7.3°). Correlation analysis results showed a good linear correlation (>0.9) between two methods.     

Prediction of methane emission from lactating dairy cows using milk fatty acids and mid‐infrared spectroscopy

Enteric methane (CH₄) production is among the main targets of greenhouse gas mitigation practices for the dairy industry. A simple, robust and inexpensive measurement technique applicable on a large scale to estimate CH₄ emission from dairy cattle would therefore be valuable. Milk fatty acids (MFA) are related to CH₄ production because of the common biochemical pathway between CH₄ and fatty acids in the rumen. A summary of studies that investigated the predictive power of MFA composition for CH₄ emission indicated good potential, with predictive power ranging between 47% and 95%. Until recently, gas chromatography (GC) was the principal method used to determine the MFA profile, but GC is unsuitable for routine analysis. This has led to the application of mid‐infrared (MIR) spectroscopy. The major advantages of using MIR spectroscopy to predict CH₄ emission include its simplicity and potential practical application at large scale. Disadvantages include the inability to predict important MFA for CH₄ prediction, and the moderate predictive power for CH₄ emission. It may not be sufficient to predict CH₄ emission based on MIR alone. Integration with other factors, like feed intake, nutrient composition of the feed, parity, and lactation stage may improve the prediction of CH₄ emission using MIR spectra. © 2016 Society of Chemical Industry     

Precise metabolic flux analysis of coryneform bacteria by gas chromatography-mass spectrometry and verification by nuclear magnetic resonance

Precise metabolic flux analysis (MFA) by gas chromatography-mass spectrometry (GC-MS) and computer calculation was performed, and the consistency of the estimated results was verified by independently performed nuclear magnetic resonance (NMR) analysis. The precise estimation of flux by the integration method of the mass isotopomer signal, defined as the coefficient of variance (CV) of multiple determination, was investigated, and the results estimated using different data sets with the same magnitude of error were confirmed. The CV of multiple determinations was sufficiently small to discuss and compare the fluxes of a metabolic pathway. The estimated fluxes using the GC-MS data were cross-validated with the NMR data that were independently measured and not used for MFA. The developed method was successfully applied to the MFA of the growth phase of two different glutamate-producing coryneform bacteria, Corynebacterium glutamicum and C. efficiens. The difference in the growth rate between these two bacterial species was discussed while considering the results of MFA, including forward and backward (exchange) fluxes.     

分子印迹技术在食品化学污染物检测分析中的应用

分子印迹技术是源于20世纪中期的一种新的方法。由于其结构可预测性、广泛适用性、特异识别性3大特点,发展极为迅速,被广泛运用于生物工程、临床医学、天然药物分离、环境科学及食品工业等多个领域。近年来分子印迹技术由于其高选择性、简便快速性、高稳定性以及低成本和环保被大量的应用到了食品中化学污染物的检测中。本文从分子印迹技术的概念、基本原理、制备方法以及在食品化学污染物检测中的应用及发展趋势进行总结,为将分子印迹技术更好地应用于食品中化学污染物的分析检测领域提供参考。     

从菌丝体中提取壳聚糖的研究进展

壳聚糖可应用于水处理、医疗卫生、食品及保健等领域。其制备通常是从虾、蟹壳提取的，但由于原料的不稳定性，使壳聚糖的产量和质量受到影响。因此，从80年代后期，日本和美国先后开始研究用微生物发酵的方法生产壳聚糖。本文对壳聚糖的性质、生产及应用进行了综述。     

Simultaneous determination of two Monascus metabolites in red yeast rice by HPLC using fluorescence detection

A reversed-phase HPLC method with fluorescence detection for the determination of two Monascus metabolites, monasfluore A (MFA) and monasfluore B (MFB), in red yeast rice was carried out. Optimum conditions for the extraction and chromatographic separation were investigated. The method was validated through the following performance criteria: linearity, stability, limit of detection (LOD), quantification (LOQ), etc. This assay was successfully used for determination of the MFA and MFB in 20 samples inoculated from different Monascus sp. The results revealed that significant variations were demonstrated in the contents of the MFA and MFB in these samples. The high contents of both MFA and MFB in sample 13 were found to be 81.400 and 26.300 mg g^?1, respectively. The low contents of both MFA and MFB in sample 14 were also found to be 0.010 and 0.003 mg g^?1, respectively.     

Hierarchical Multiple Factor Analysis: application to the comparison of sensory profiles

An extension of Multiple Factor Analysis (MFA) to the case where the data at hand are organized into a hierarchical structure is discussed. It is called Hierarchical Multiple Factor Analysis (HMFA). This method of analysis balances the role of the groups of variables at each level of the hierarchy and provides outputs that may be interpretable from an overall perspective (overall hierarchical structure) as well as from various perspectives pertaining to the various levels of the hierarchy. It is illustrated on the basis of a real data set which stems from a sensory profiling experiment involving, on the one hand, several trained panels and, on the other hand, an untrained panel. The results of the analysis are reported and with respect to our data they show the extent to which profiles provided by an untrained panel are similar to those provided by trained panels.     

改善卷烟纸包灰性能助剂的开发研究

开发研究了一种烟灰调节剂MFA用于改善卷烟纸的包灰性能。当烟灰调节剂MFA添加浓度达到3．0％时,从包灰分析测试结果显示该助剂能明显改善卷烟纸的静态和动态包灰效果,灰柱美观,烟灰不散落,无明显出角现象。添加烟灰调节剂MFA的卷烟纸物理指标没有显著变化。卷制香烟后,卷烟烟气指标相比于没有加入MFA的卷烟,焦油量和CO量都有所增加,但幅度不大,烟气指标受控,经评吸认为在吸味方面无明显差异。应用红外光谱仪分析助剂MFA的结构,并进一步分析在改善卷烟纸包灰性能的原理。     

Methane prediction based on individual or groups of milk fatty acids for dairy cows fed rations with or without linseed

Milk fatty acids (MFA) are a proxy for the prediction of CH₄ emission from cows, and prediction differs with diet. Our objectives were (1) to compare the effect of diets on the relation between MFA profile and measured CH₄ production, (2) to predict CH₄ production based on 6 data sets differing in the number and type of MFA, and (3) to test whether additional inclusion of energy-corrected milk (ECM) yield or dry matter intake (DMI) as explanatory variables improves predictions. Twenty dairy cows were used. Four diets were used based on corn silage (CS) or grass silage (GS) without (L0) or with linseed (LS) supplementation. Ten cows were fed CS-L0 and CS-LS and the other 10 cows were fed GS-L0 and GS-LS in random order. In feeding wk 5 of each diet, CH₄ production (L/d) was measured in respiration chambers for 48 h and milk was analyzed for MFA concentrations by gas chromatography. Specific CH₄ prediction equations were obtained for L0-, LS-, GS-, and CS-based diets and for all 4 diets collectively and validated by an internal cross-validation. Models were developed containing either 43 identified MFA or a reduced set of 7 groups of biochemically related MFA plus C16:0 and C18:0. The CS and LS diets reduced CH₄ production compared with GS and L0 diets, respectively. Methane yield (L/kg of DMI) reduction by LS was higher with CS than GS diets. The concentrations of C18:1 trans and n-3 MFA differed among GS and CS diets. The LS diets resulted in a higher proportion of unsaturated MFA at the expense of saturated MFA. When using the data set of 43 individual MFA to predict CH₄ production (L/d), the cross-validation coefficient of determination (R²_CV) ranged from 0.47 to 0.92. When using groups of MFA variables, the R²_CV ranged from 0.31 to 0.84. The fit parameters of the latter models were improved by inclusion of ECM or DMI, but not when added to the data set of 43 MFA for all diets pooled. Models based on GS diets always had a lower prediction potential (R²_CV = 0.31 to 0.71) compared with data from CS diets (R²_CV = 0.56 to 0.92). Models based on LS diets produced lower prediction with data sets with reduced MFA variables (R²_CV = 0.62 to 0.68) compared with L0 diets (R²_CV = 0.67 to 0.80). The MFA C18:1 cis-9 and C24:0 and the monounsaturated FA occurred most often in models. In conclusion, models with a reduced number of MFA variables and ECM or DMI are suitable for CH₄ prediction, and CH₄ prediction equations based on diets containing linseed resulted in lower prediction accuracy.