Physico‐chemical and sensory attributes in conjunction with multivariate analysis of two potato (Solanum tuberosum L.) cultivars after 90 days of storage: an exploratory authentication study

Two cultivars of potato (Spunta and Agria), were studied in terms of their physico‐chemical and sensory characteristics. These cultivars were cultivated in three geographical regions of Greece (Macedonia, North Greece; Thessaly, Central Greece; Peloponnese, South Greece) and were stored for 90 days after harvesting. The physico‐chemical characteristics of the tubers determined, were pH, total acidity, firmness, dry matter and content in Ν, in Κ, P, Cu, Mn, Zn and Fe. The sensory characteristics measured for raw tubers of potato after storage, were skin colour, skin brightness, internal colour, surface roughness, odour intensity, moistness, surface wrinkling and stains while the sensory characteristics measured for the boiled tubers of potato were odour intensity, moistness, special taste, sweet taste, aftertaste persistence, metal taste, pastiness, mastication, flavour intensity, elasticity and overall acceptability. The application of multivariate analysis (principal component analysis, cluster analysis and discriminant analysis), revealed a variety of relations between the various parameters and resulted in satisfactory grouping either per geographical region or per cultivar.     

Implementation of quality control methods (physico-chemical, microbiological and sensory) in conjunction with multivariate analysis towards fish authenticity

Nowadays authenticity of foods and fish in particular has become of crucial importance because of high number of adulteration cases. Authenticity control has gained ground thanks to the development of several rapid physico‐chemical and microbiological methods aiming at distinguishing one species from another based on solid scientific evidence. It has been proven that despite the precision and accuracy of robust analytical and protein and DNA‐based techniques, detection of authenticity could not be claimed without resorting to multivariate analysis. This review summarizes both the most advanced and state of the art used techniques for detecting fish and seafood authenticity (both in terms of species and geographical origin). Another issue reported in this review is the preservation of fish and seafood through the implementation of old and novel techniques (ice, modified atmosphere packaging). Several informative tables were included in this paper referring to the employed quality control and sensory analysis methods and multivariate analysis for fish and seafood.     

Implementation of physicochemical and sensory analysis in conjunction with multivariate analysis towards assessing olive oil authentication/adulteration

The authenticity of products labeled as olive oils, and in particular as virgin olive oils, stands for a very important issue both in terms of its health and commercial aspects. In view of the continuously increasing interest in virgin olive oil therapeutic properties, the traditional methods of characterization and physical and sensory analysis were further enriched with more advanced and sophisticated methods such as HPLC-MS, HPLC-GC/C/IRMS, RPLC-GC, DEPT, and CSIA among others. The results of both traditional and "novel" methods were treated both by means of classical multivariate analysis (cluster, principal component, correspondence, canonical, and discriminant) and artificial intelligence methods showing that nowadays the adulteration of virgin olive oil with seed oil is detectable at very low percentages, sometimes even at less than 1%. Furthermore, the detection of geographical origin of olive oil is equally feasible and much more accurate in countries like Italy and Spain where databases of physical/chemical properties exist. However, this geographical origin classification can also be accomplished in the absence of such databases provided that an adequate number of oil samples are used and the parameters studied have "discriminating power."     

Potato: a comparative study of the effect of cultivars and cultivation conditions and genetic modification on the physico-chemical properties of potato tubers in conjunction with multivariate analysis towards authenticity

Potato (Solanum tuberosum L.) is a highly nutritious, mild flavored, easy to blend food that has many possibilities for "building in" desired nutrients. Varietal and environmental differences are known to exist in the shape, size, and nutritional content of potatoes. Different populations opt for varying sensory properties in relation to their diets. Potatoes are a low energy food in comparison to cereals and legumes. The aim of this review was to present an update of the currently conducted studies both on the characterization of several potato varieties (physical, chemical, and sensory analysis) and by means of genetic modification. Towards this target, five comprehensive tables were compiled where all recent data (physicochemical properties) and GM varieties were presented in conjunction with multivariate analysis (chemometrics). The latter was shown to be effectively used towards authenticity purposes (identification of geographical origin, variety, GM).     

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.     

Characterisation of Slovenian honeys on the basis of sensory and physicochemical analysis with a chemometric approach

The purpose of this study was sensory and physicochemical characterisation of Slovenian honeys with a chemometric approach. Honey samples were obtained from the beekeepers in different natural geographical macroregions of Slovenia. The sensory characteristics of the seven main types of Slovenian honeys are described, together with the physicochemical analyses. The average results of electrical conductivity (0.19–1.61 mS cm^?1), pH (4.01–5.51), free acidity (13.3–30.9 meq kg^?1), proline content (317–558 mg kg^?1), protein content (1.70–3.53 g kg^?1), optical rotation (–19.6 to 12.6), phenolic content (44.9–232.5 mg GAE kg^?1) and antioxidant activity [69.6–456.4 μm Fe(II)] show wide variability among analysed honey types. Statistically significant differences were obtained among different honey types, generally lower values of the analysed parameters were determined in the light honeys, as the acacia, linden and multifloral honeys, while the higher values are characteristic for darker honeys, as the chestnut, fir, spruce and forest honeys. Linear discriminant analysis was performed to classify the honey samples according to their botanical origin and proved that physicochemical parameters analysed can provide enough information for the classification and distinction of acacia, linden, multifloral and chestnut honeys, and the group of honeydew honeys (fir, spruce and forest honeys).     

基于主成分分析、神经网络对啤酒感官评价的预测

该研究运用主成分分析(PCA)结合误差反向传播(BP)神经网络对啤酒感官评价进行了预测。把啤酒中11种理化及风味指标进行主成分分析,以除去数据之间的线性相关性,提取后的理化及风味指标做为输入数据,感官评价得分作为输出数据,运用BP神经网络建立啤酒感官评价预测的模型。使用此模型对50种啤酒的感官得分进行预测,预测最大相对误差为2.68%。结果表明,主成分分析和神经网络相结合的这种方法能够准确预测啤酒感官评价得分。     

Principal component and multivariate analysis of milk long-chain fatty acid composition during diet-induced milk fat depression

The objective of this study was to assess the relationship between individual milk fatty acids (FA) and diet-induced milk fat depression (MFD) using principal component analysis (PCA) and multivariate analysis (MA). Cow treatment observations (n = 63) from 3 published feeding experiments with lactating dairy cows were used in the analyses. In the PCA, principal component loading plots 1 (PC1) and 2 (PC2) described 55.9% of the total variation in milk FA and fat concentrations. Saturated FA (14:0, 16:0, and 17:0) and milk fat percentage showed negative loading for PC1. Trans-18:1 isomers (trans-6+7+8 to trans-15), trans-7, cis-9 conjugated linoleic acid (CLA), and trans-10, cis-12 CLA showed positive (opposite) loading, suggesting a negative relationship between these isomers and milk fat percentage. Cis-11, trans-13 CLA and cis-9, trans-11 CLA were associated with the PC2 axes (neutral), indicating that they were not associated with MFD. Multivariate analysis with milk fat percentage as the dependent variable and individual PC1 positive loading variables showed a breakpoint relationship for trans-6+7+8-, trans-9-, trans-10-, and trans-13+14-18:1 and a linear relationship for trans-11-, trans-12-, trans-15-18:1, trans-10, cis-12 CLA, and trans-7, cis-9 CLA. Subsequent MA was conducted on 41 treatment means from 12 independent experiments from the literature, in which concentrations of trans-6+7+8-, trans-9-, trans-10-, and trans-11-18:1, and cis-9 trans;-11, and trans-10, cis-12 CLA were reported. Significant negative effects of trans-9-18:1, trans-10-18:1, and trans-10, cis-12 CLA on milk fat percentage were observed. In this study, the PCA and MA showed that among trans-18:1 isomers, trans-10-18:1 was the most negatively correlated to milk fat percentage. However, the threshold concentration related to maximum MFD indicated that the relative potency was greatest for trans-6+7+8- and lowest for trans-10-18:1. These results suggested that trans-6+7+8-18:1 might be more important than trans-10-18:1 in MFD. Principal component analysis also showed that trans-10, cis-12 and trans-7, cis-9 CLA were the isomers most negatively correlated to milk fat percentage, implying a possible role of trans-7, cis-9 CLA in MFD. Additional experiments are needed to establish whether trans-7-18:1 is involved in MFD or that its effects are mediated via the endogenously synthesized trans-7, cis-9 CLA.     

Maturity and ripening effects on chemical and sensory properties of apple juice

The effects of harvest maturity and ripening on the chemical composition and sensory characteristics of ‘McIntosh’ and ‘Spartan’ apple juice were evaluated. Juice was extracted from fruit harvested at seven weekly intervals beginning 3–4 weeks before commercial harvest and from fruit held in air storage (1°C) for 1 to 3 months. Internal ethylene concentration and starch index were used as maturity indices. Principal component analysis of juice data (pH. titratable acidity, organic acids, soluble solids, sugars, phenols, turbidity, and Hunterlab colour) showed a distinctive maturity effect on the characteristics of juice extracted from fruit immediately after harvest or after storage. Triangle testing showed aroma and flavour differences in both ‘McIntosh’ and ‘Spartan’ to be first discernable when ethylene was first detected (internal ethylene concentration ≥ 0.1 μl litre^?1) and starch hydrolysis evident (starch index 3.0–5.0 for ‘McIntosh’, 1.5–3.0 for ‘Spartan’), or after 2–3 months of air storage. Sensory profiling of fruity aroma, total aroma, fruit flavour by mouth, sweetness, and sourness in the juices showed increased fruitiness and sweetness and decreased sourness with advancing maturity.     

藤茶感官特征定量描述分析与风味轮构建

采用感官定量描述分析法研究藤茶的感官风味特征,并绘制藤茶风味轮.研究结果表明,经培训的评茶小组确定了藤茶的5个外形描述词、5个汤色描述词、7个香气描述词、10个滋味描述词及其定义,之后通过方差分析(P<0.05)结合主成分分析(贡献率>80％),确定所列的27个藤茶感官描述词均可较好评价藤茶样品的感官品质,结合聚类分析...     

Sensory characteristics of british sausages: Relationships with composition and mechanical properties

The appearance, texture and flavour of cooked British sausages were assessed by 11 trained panellists using their analytical profile of 19 attributes, each of which was rated on an unstructured line scale. Five independent components were isolated, accounting for 86% of the sensory variation. ‘Saltiness’ was the only independent attribute. A map of sausage quality showed that ‘skin toughness’, ‘firmness’ and ‘meatiness’ were related closely to the principal sensory axis, and ‘juiciness’ and ‘fattiness’ to the second principal axis. The attributes of appearance describing the degree of doneness, and those describing comminution in appearance and in texture, were related to both principal axes. Mapping instrumental measurements into the sensory space showed that puncture and compressive strengths and nitrogen content were the best measures of variation on the first principal axis, indicating a toughness/tenderness component influenced by lean meat content. Fat increased juiciness, but, as salt or rusk increased, sausages were drier and more cohesive. Adhesion and cohesion were assessed as ‘cohesiveness’. ‘Fattiness’ and ‘saltiness’ were related poorly to fat and salt contents, respectively. ‘Fattiness’ decreased in tough, dry sausages of low pH, and ‘saltiness’ decreased as pH, fat and ‘dryness’ increased. In commercial sausages, the effects of comminution on eating quality could override those of formulation.     

A review on tomato authenticity: quality control methods in conjunction with multivariate analysis (chemometrics)

Authenticity and traceability have been two of the most important issues in the food chain. Authenticity in particular, is closely related with both food quality and safety issues. Vegetables stand for a category of foods heavily affected by adulteration either in terms of geographic origin (national or international level) or production methods (organic or conventional production, fertilizers, pesticides, genetically modified vegetables). This review aims at addressing most of the currently applied methods for ensuring quality control of vegetables; a) instrumental: ion chromatography, high pressure liquid chromatography, atomic absorption spectrophotometry, electronic nose and mass spectroscopy and b) sensory analysis. The results of all the above mentioned methods were analyzed by means of multivariate analysis (principal component analysis, discriminant analysis, cluster analysis, canonical analysis, and factor analysis). All ensuing results and conclusions are summarized in eight comprehensive tables.     

黑米馒头的制备及其力学特性主成分分析

采用主成分分析的方法,以馒头的力学指标为依据,结合感官评定对黑米馒头的食用品质进行评价.从样本相关矩阵出发,对黑米馒头的主要力学指标进行分析,由累积贡献率达到79.45%以上,确定反映馒头食用品质的2个主成分,并获得各品种的综合评分.感官评定得出黑米超微粉添加量为20%时感官得分较高,与主成分分析结果基本一致,表明应用主成分分析的方法、利用馒头的力学指标评定黑米馒头的食用品质具有可行性.     

Prediction of sensory quality by near infrared reflectance analysis of frozen and freeze dried green peas (Pisum sativum)

Frozen, green peas (Pisum sativum L ) of different varieties and different levels of maturity were evaluated by sensory analysis using a panel of ten trained judges. Two texture variables (hardness and mealiness) and four flavour variables (pea flavour, sweetness, fruity flavour, off flavour) were considered. Near infiared reflectance ( N I R ) analysis was performed with the same material, on both the fiozen and fieeze dried peas. The N I R instrument was calibrated to predict the sensory variables using the multivariate analytical method of principal component regression. Tenderometer readings of the same peas were also calibrated to predict the sensory variables. N I R analysis on the fieeze dried peas showed relative ability of prediction (RAP) values for the sensory variables which were higher than those for the tenderometer readings. The sensory attributes pea flavour and hardness were predicted with higher RAP values by tenderometer readings than by N I R analysis on fiozen peas. For the rest of the attributes, N I R analysis on fiozen peas gave higher RAP values than tenderometer readings. N I R generally gave high RAP values, and this tentative study suggests that N I R analysis could be a useful tool in instrumentally assessing the quality of frozen peas.     

Use of multivariate analysis to extract latent variables related to level of production and lactation persistency in dairy cattle

Multivariate factor analysis and principal component analysis were used to decompose the correlation matrix of test-day milk yields of 48,374 lactations of 21,721 Italian Simmental cows. Two common latent factors related to level of production in early lactation and lactation persistency, and 2 principal components associated with the whole lactation yield and persistency were obtained. Factor and principal component scores were treated as new quantitative phenotypes related to prominent features of lactation curve shape. Genetic parameters were estimated by univariate and bivariate animal models. Estimates of heritability were moderately low for both latent factors (0.13 for persistency and yield early in lactation). Heritabilities of the principal component related to total lactation yield and 305-d yield were similar (0.19 and 0.20, respectively). Finally, heritability was quite low for the principal component related to lactation persistency (0.07). Repeatabilities between lactations were about 0.27 for both latent factors, around 0.4 for the first principal component and 305-d yield, and 0.11 for the second principal component. Moderate genetic correlation among common factors (0.26) and their high genetic correlation with total lactation yield (>0.60) suggest that selection can be used to change the shape of lactation curve as well as improve yield. Scores of the second principal component can be used to genetically improve persistency while maintaining constant total lactation yield.     

Relationships between antioxidant activity and quality indices of soy sauce: an application of multivariate analysis

Antioxidant activities (AA) and quality indices including the contents of total nitrogen, amino nitrogen, total acidity, sodium chloride, total solids (TS), non-salt soluble solids and Browning Index (BI) were determined in forty-one commercial soy sauces. The relationships between quality indices and AA were elucidated by multivariate analysis techniques. Results showed that production location, fermentation process and styles had significant ( P <  0.05) impacts on the characteristics of soy sauces. Satisfactory discrimination between dark and light soy sauces was achieved by principal component analysis. Using cluster analysis, the group of dark soy sauce with strong AA was obtained. Results from partial least squares regression (PLS) showed that TS and BI were two major indices contributing to the AA of soy sauce. Moreover, a PLS model was constructed to effectively predict AA of soy sauces based upon quality indices.     

Near infra-red analysis: The use of multivariate statistics for investigation of variables in sample preparation and presentation of tea leaf

A data analysis procedure involving principal component and canonical variate analyses was used to investigate the effects of three sample variables (particle size, temperature and sample rotation) on the near infra-red spectra of six teas of different geographical origin. The effects of milling method were shown to be much larger than those of sample temperature or rotation. The analysis provided a rational basis for the choice of a milling technique and sample presentation for a study of the possible relationship between tea quality and near infra-red spectroscopic data.     

Characteristics of gelling agent substituted fruit jam: studies on the textural,optical, physicochemical and sensory properties

A series of mango jams were prepared using different hydrocolloid solutions (high methoxyl pectin (HMP), carboxymethyl cellulose (CMC), and sago starch) as gelling agents to investigate the effect of hydrocolloid type, hydrocolloid concentration, and freeze‐thaw treatment on the physicochemical, optical, textural, and sensory characteristics. The optical properties results revealed that the total colour change (ΔE) of the sago starch‐based mango jam samples displayed higher values in comparison with samples prepared with HMP and CMC. The textural parameters (hardness, work of shear, stickiness, and work of adhesion) increased with hydrocolloid concentration but decreased with the freeze‐thaw treatment except for sago starch‐based mango jams. The overall acceptability of mango jams containing 6% sago starch was rated similarly to the samples prepared with 0.7% HMP and 0.5% CMC. Principle component analysis revealed that it could be used as an effective tool to segregate characteristics related to fruit jam manufacture.     

Water retention properties and solubility of the myofibrillar proteins: Interrelationships and possible value as indicators of the gel strength in cod surimi by a multivariate data analysis

The quality of surimi made from fish aged on ice for up to 14 days was evaluated by compression test on a model product. Water holding capacity (WHC) and pH in the fish mince, and protein content, pH, salt solubility of the myofibrillar proteins and hydration index of the insoluble proteins (HUP) in the surimi, were determined. Their interrelationships and utility as indicators of surimi quality were evaluated by a multivariate data analysis. The main tendencies of variation among the chemical parameters were examined by the use of principal component analysis. Correlations between the chemical parameters (X-variables) and the gel strength of surimis (Y-variable) were studied by the use of partial least squares regression. Age of the raw material and protein content of the surimi seemed to be the main determinants of the gel strength. Among the remaining variables only HIIP showed a potential value as indicator of the gel strength. WHC and HIIP seemed to reflect two different water retention properties of the proteins.