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.     

Novel quality control methods in conjunction with chemometrics (multivariate analysis) for detecting honey authenticity

The importance of honey has been recently upgraded because of its nutrient and therapeutic effect. The adulteration of honey increased exponentially in terms of both geographic and/or botanical origin. Therefore, the need has arisen for more effective quality control methods aiming at detecting adulteration. Various novel, fast, and accurate methods like AAS, HPLC, GC-MS, ES-MS, TLC, HPAED-PAD, NMR, FT-Raman, and NIR have enriched the arsenal of analytical chemist in this direction. However, apart from these novel methods, the application of multivariate analysis and, in particular, PCA, CLA, and CA, proved to be extremely useful for grouping and detecting honey of various origins. Mineral and trace element analysis were repeatedly shown to be a very effective means for the classification purposes of honey of various origins (geographical and botanical).     

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).     

Physicochemical and sensory analysis of dry bean landraces in conjunction with multivariate analysis: an exploratory approach

Five landraces of Greek common dry bean (Phaseolus vulgaris L.), were analysed for thirteen physico‐chemical and eighteen sensory variables. Brightness, acceptance, odour and hardness were the most important sensory variables for the overall acceptability of the cooked product. Application of principal component analysis revealed a rather weak relationship between the sensory attributes and the physico‐chemical variables. However, a certain grouping of cultivars with corresponding properties [(PC1 vs. PC2, Kastoria with saltiness, hardness, grassiness, intensity, protein and metal; Byzitsa bushy with fat, odour and sourness; Ksanthi and Belestino with tenaciousness, chroma, pH and overall impression), (PC1 vs. PC3 Byzitsa bushy with odour and acridness; Ksanthi with metal, hardness and pH; Kastoria with colour, protein and intensity)] was made. On the contrary, cluster analysis showed a much more satisfactory grouping of dry bean varieties based on their geographical origin. The multiple regression equation explained 72.3% of the variation in total acceptance of dry beans. The relative importance of brightness, acceptance, smell and hardness in predicting the overall impression of dry beans was 13%, 13.7%, 26% and 10%, respectively. These results may indicate that smell, brightness and acceptance are the most important factors determining dry bean total acceptability, so effort should be directed at improving these attributes in an attempt to satisfy consumer experience.     

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.     

Implementation of quality control methods in conjunction with chemometrics toward authentication of dairy products

The implementation of novel and accurate quality and safety control methods in conjunction with chemometrics in various fields of science, particularly in food science, showed that this combination stands for a very powerful tool for detecting food authenticity. The latter reflects both geographic origin and variety. Dairy products, in particular, have repeatedly worried the public authorities in terms of authentication regarding origin and in view of the many illnesses occasionally due to products of specific origin. Therefore, the development of a robust and reliable system endowed with this discriminatory power (varietal and/or geographic) is of great importance, both in terms of public health and consumer protection.     

Agricultural produces: synopsis of employed quality control methods for the authentication of foods and application of chemometrics for the classification of foods according to their variety or geographical origin

A review of quality control methods and applications of multivariate statistical techniques on the authentication and classification of agricultural products is presented. The products reported within the frame of this article were vegetables, fruits, juices, jams, wines, cereals, bakery products, oils, tea, coffee, honey, sugar-syrups, salad dressings, and gums. The perspective of multivariate statistics as a promising tool to authenticate and classify these food products according to their geographical origin or variety was demonstrated. Several representative figures and informative synoptical tables for agricultural food products were provided both for the quality control methods employed and the multivariate analyses implemented.     

Implementation of chemometrics for quality control and authentication of meat and meat products

Multivariate analysis has been established as a very powerful and effective tool in classifying and grouping individual products. Principal Component Analysis, Canonical analysis, Cluster and Partial Least Squares were found to be indispensable for classifying food products according to variety and/or geographical origin. Meat and meat products were correctly classified for authentication purposes to various groups following instrumental and/or sensory analyses.     

Effect of irradiation and chilled storage on the microbiological and sensory quality of a ready meal

The sensory and microbiological quality of both non-irradiated and irradiated cook-chill ready meals consisting of roast beef and gravy, cauliflower and sauce together with roast and mashed potatoes were assessed at intervals during 15 d storage at 2–3°C.
Growth of Pseudomonas spp. caused obvious spoilage of the non-irradiated meals after storage, whereas spoilage was not apparent in the irradiated meals. Irradiation (2 and 3 kGy) reduced the number of microorganisms in the meal to <100 g⁻¹ initially and significant microbial growth did not occur during storage.
Using sensory profiling techniques a trained panel found that the effects of irradiation and chilled storage were most apparent in the cauliflower and potato components and occurred most often in the colour, appearance and textural attributes.
The combination of low dose irradiation and chilled storage effectively controlled microbial growth but changes in the sensory characteristics may limit the potential of irradiation to extend the shelf-life and enhance the safety of this ready meal.     

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.     

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.     

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.     

基于聚类分析的浓缩苹果汁风味品质分析与评价

通过对浓缩苹果汁主要风味物质进行分析,建立其风味品质的客观评价方法,为生产者合理调整工艺提供参考。分别选取风味较好和风味较差的浓缩苹果汁样品,对其挥发性风味物质、有机酸、氨基酸、糖类等主要风味物质进行分析,采用主成分分析、因子分析综合打分、聚类分析等方法筛选出能够有效区分不同风味品质浓缩苹果汁样品的主要风味化合物。选取12批次浓缩苹果汁样品,检测样品中39种主要挥发性风味物质、14种主要氨基酸、6种主要有机酸以及4种主要的糖类等风味物质。根据因子分析综合打分结果,从29种组合中,筛选出能够区分浓缩苹果汁风味的5种主要风味物质,分别为天冬氨酸、丝氨酸、蛋氨酸、果糖和葡萄糖。利用不同年份的8个批次浓缩苹果汁样品对该结果进行了验证,结果表明,这5种风味物质能够有效区分A、B两类浓缩苹果汁。利用筛选出的5种主要风味物质,能够对浓缩苹果汁风味品质进行客观、准确的判别。     

Proteome Comparison of Grains from Two Maize Genotypes,with Colorless Kernel Pericarp (P1-ww) and Red Kernel Pericarp (P1-rr)

Maize genotypes P1-rr (R) and P1-ww (W) have high and low flavonoid content, respectively. Grain proteome profiles of these maize genotypes were compared. Two-dimensional gel electrophoresis (2-DE) was performed from three soluble protein extracts of each maize genotype and 55 proteins spots were differentially expressed using univariate analysis. Differentially expressed protein spots were analyzed by mass spectrometry-peptide mass fingerprint (MS-PMF) and eight of them were identified on the Zea mays L. database. Additionally, grouping of proteomic data was evaluated by principal component analysis (PCA) using 135 matched spots in all six analyzed gels. First component (PC1) represented 46.5% of total variation and second component (PC2) referred to 22.5%. This multivariate analysis showed the separation of the two maize genotypes proteome profiles using 2-DE data. The data presented in this study shows that 2-DE complemented with PCA is applicable to food analysis.     

Development of a flavour fingerprint by GC‐MS and GC‐O combined with chemometric methods for the quality control of Korla pear (Pyrus serotina Reld)

Based on solid‐phase micro‐extraction/gas chromatography‐mass spectrometry (SPME/GC‐MS) and gas chromatography‐olfactometry (GC‐O), a new method was described for the first time to establish flavour fingerprint for the quality control of Korla pear. Twenty‐three batches of Korla pear collected from different regions in Xinjiang, China were analysed via GC‐MS, among which 21 were selected to establish the fingerprint. The results of the analysis were combined with GC‐O assessment to obtain 26 common odour‐active compounds as the characteristics of the Korla pear flavour fingerprint. The method for flavour fingerprint analysis was then validated on the basis of the relative retention time and relative peak area of the common peaks, sample stability and similarity analysis. The similarities in the 21 Korla pear samples were more than 0.80, thereby indicating that the samples from different batches were consistent to a particular extent. The chemometrics method (principal component analysis, PCA) was performed to develop a flavour fingerprint that is suitable for identifying and differentiating Korla pears and can be used for quality control.     

Geographical origin identification and quality control of Chinese chrysanthemum flower teas using gas chromatography–mass spectrometry and olfactometry and electronic nose combined with principal component analysis

Aroma profiles and volatile profiles were established based on volatile and aroma ‐ active components identified by gas chromatography–mass spectrometry and olfactometry (GC–MS–O) and electronic nose (E ‐ nose). The two profiles were used for quality control and origin identification of chrysanthemum flower teas. Results showed that 86 volatile components were identified in five chrysanthemum flower teas, including terpenes, alcohols, ketones, aldehydes, esters and others. Of them, 33 aroma ‐ active components were recognised, including 10 aroma categories. The aroma profiles and volatile profiles were established by 10 aroma categories and E ‐ nose. Chrysanthemum flower teas were divided into five groups on PCA score plots based on their aroma profiles and volatile profiles, and the key volatile (aroma ‐ active) components resulting in the tea sample differences were determined. The quality of chrysanthemum flower teas could be evaluated according to aroma ‐ active components and aroma profiles and origins could be discriminated by PCA combined with GC–MS–O and E ‐ nose.     

高寒荒漠区延后栽培葡萄品质分析

为评价鲜食葡萄在高寒荒漠区延后栽培条件下的品质表现,以适应性较好的8个品种为研究对象,测定葡萄感官品质、内在品质、功效成分和糖酸品质,采用主成分分析法对果实品质进行综合分析和评价。结果表明,‘红地球’和‘紫地球’单果质量10 g以上,果粒大,能够保持原有的大果特征;无核品种较有核品种果粒小;8个品种果实果形指数均> 1,呈长椭圆形,除绿色品种外,果实着色较深;果皮颜色越深的品种,果皮花青素、类黄酮、总酚含量越高。2个无核品种(‘红宝石无核’和‘紫甜无核’)和‘红地球’可溶性固形物含量较高,在21%以上;糖酸组分及含量方面,果实中的糖分主要是果糖和葡萄糖,蔗糖未检出;酒石酸和苹果酸是主要有机酸,柠檬酸和草酸含量极微。酸甜风味方面,‘红宝石无核’口感最甜,其次为‘红地球’,‘瑞都香玉’和‘紫地球’口感较淡,‘摩尔多瓦’口感偏酸。通过主成分分析法提取了5个独立的主成分,累计贡献率87. 396%,以主成分为评价指标,对浆果品质进行综合评价,‘红宝石无核’、‘红地球’和‘玫瑰香’果实综合品质最好。