scholarly journals SensoMaker: a tool for sensorial characterization of food products

2013 ◽  
Vol 37 (3) ◽  
pp. 199-201 ◽  
Author(s):  
Ana Carla Marques Pinheiro ◽  
Cleiton Antônio Nunes ◽  
Vladimir Vietoris
Keyword(s):  
Consumer Preferences ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Free Software ◽  
Preference Mapping ◽  
Good Product ◽  
External Preference Mapping ◽  
User Friendly ◽  
Temporal Dominance

SensoMaker is a free software for data analysis from sensory studies, which has modules with user-friendly interface. Data acquisition can be performed using different methods, such as category scale, linear scale, temporal dominance of sensations (TDS), and time-intensity (TI). Results can be analyzed by a variety of methods, such as conventional internal and external preference mapping, three-way internal and external preference mapping, principal component analysis, hierarchical cluster analysis, TDS and TI curves, in addition to Tukey and Dunnett tests. High quality graphics are easily obtained and exported to several formats. The software is useful during the development or improvement of products, when it is important to carefully note consumer preferences and to relate it to descriptive characteristics in order to ensure good product acceptance.

scholarly journals A Methodology Based on FT-IR Data Combined with Random Forest Model to Generate Spectralprints for the Characterization of High-Quality Vinegars

Foods ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 1411
Author(s):  
José Luis P. Calle ◽  
Marta Ferreiro-González ◽  
Ana Ruiz-Rodríguez ◽  
Gerardo F. Barbero ◽  
José Á. Álvarez ◽  
...  
Keyword(s):  
Random Forest ◽  
Raw Materials ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Raw Material ◽  
Support Vector ◽  
Protected Designation Of Origin ◽  
Ft Ir

Sherry wine vinegar is a Spanish gourmet product under Protected Designation of Origin (PDO). Before a vinegar can be labeled as Sherry vinegar, the product must meet certain requirements as established by its PDO, which, in this case, means that it has been produced following the traditional solera and criadera ageing system. The quality of the vinegar is determined by many factors such as the raw material, the acetification process or the aging system. For this reason, mainly producers, but also consumers, would benefit from the employment of effective analytical tools that allow precisely determining the origin and quality of vinegar. In the present study, a total of 48 Sherry vinegar samples manufactured from three different starting wines (Palomino Fino, Moscatel, and Pedro Ximénez wine) were analyzed by Fourier-transform infrared (FT-IR) spectroscopy. The spectroscopic data were combined with unsupervised exploratory techniques such as hierarchical cluster analysis (HCA) and principal component analysis (PCA), as well as other nonparametric supervised techniques, namely, support vector machine (SVM) and random forest (RF), for the characterization of the samples. The HCA and PCA results present a clear grouping trend of the vinegar samples according to their raw materials. SVM in combination with leave-one-out cross-validation (LOOCV) successfully classified 100% of the samples, according to the type of wine used for their production. The RF method allowed selecting the most important variables to develop the characteristic fingerprint (“spectralprint”) of the vinegar samples according to their starting wine. Furthermore, the RF model reached 100% accuracy for both LOOCV and out-of-bag (OOB) sets.

Characterization of Physical and Chemical Evaluation on Six Apple Varieties

2013 ◽  
Vol 807-809 ◽  
pp. 1954-1959
Author(s):  
Li Yan Gong ◽  
Bin Li ◽  
Jin Feng Bi ◽  
Sha Sha Bai ◽  
Xian Jun Meng
Keyword(s):  
Chemical Properties ◽  
Chemical Characterization ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Soluble Solids ◽  
Physical And Chemical Properties ◽  
Apple Varieties ◽  
Physical And Chemical ◽  
And Chemical Properties

Physical and chemical characterization of 6 apple varieties (Early Golden Delicious, Jonagold, Hanfu, Ralls, Rainier and Fuji) from China was performed using pattern recognition tools. Measurements were taken on 12 parameters including weigh, colour, fruit firmness, crude fiber, total soluble solids, titration acid, water, Vitamin C, edible rate and juice yield .The results showed that physical and chemical properties existed different variance in apple varieties. The coefficient of variance of 12 properties was from 2.15% to 69.04%. The different apple varieties were investigated by principal component analysis (PCA) and hierarchical cluster analysis (HCA). PCA revealed that the first four components represented 95.13% of the total variability in properties and different apple groups. HCA classified samples into three groups on the basis of the physical and chemical properties.

scholarly journals Fruit characterization of 36 cape gooseberry hybrids for identification of potential industrial or fresh consumption uses

2021 ◽  
Vol 15 (2) ◽  
Author(s):  
Tulio César Lagos-Burbano ◽  
Diego Fernando Mejía-España ◽  
Oscar Arango-Bedoya ◽  
Zulma Yizeth Villaquirán-Samboni ◽  
Liz Katherine Lagos-Santander ◽  
...  
Keyword(s):  
Nutritional Quality ◽  
Genetic Improvement ◽  
Agricultural Research ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Seed Content ◽  
Total Variability ◽  
Cape Gooseberry ◽  
Transformation Processes

The cape gooseberry is the second most exported fruit in Colombia. There are, however, little information available on genetic improvement processes and limited research on the fruit components. The objective of this study was to characterize the fruits of 36 hybrids, obtained from double haploid cape gooseberry lines from the Tibaitatá Research Center of the Colombian Corporation for Agricultural Research. Hybrids with potential uses in transformation processes or for fresh consumption were identified using Hierarchical Cluster (HC) and Principal Component Analysis (PCA) with 20 physical, physicochemical, compositional, and physiological fruit descriptors, obtained from four trials in the Andean region of southern Colombia. According to the PCA, three components represented 73.6% of the total variability: postharvest (37.5%), sensory and nutritional quality (21.3%) and cracking percentage (14.8%). Six conglomerates were identified. Groups two, four, and six had aptitude for fresh consumption because of the size of the berry, high vitamin C content, maturity index and low cracking levels. Group one showed aptitude for processing and fresh consumption. Groups three and five registered a high seed content, low maturity rates, and a high cracking percentage.

scholarly journals Chemometric approach to quality characterization of milk-based kombucha beverages

Mljekarstvo ◽  
2021 ◽  
Vol 71 (2) ◽  
pp. 83-94
Author(s):  
Jasmina Vitas ◽  
Keyword(s):  
Fatty Acids ◽  
Milk Fat ◽  
Unsaturated Fatty Acids ◽  
Principal Component ◽  
Unknown Origin ◽  
Hierarchical Cluster ◽  
Monounsaturated Fatty Acids ◽  
Data Set ◽  
Linear Discriminant

Milk-based kombucha beverages were obtained conducting kombucha lead fermentation of milk. In order to discriminate the analysed samples and to detect similarities or dissimilarities among them in the space of experimentally determined variables, hierarchical cluster analysis (HCA) and principal component analysis (PCA) were applied. Linear discriminant analysis (LDA) was conducted on the raw data set in order to find a rule for allocating a new sample of unknown origin to the correct group of samples. In the space of the variables analysed by HCA, the dominant discriminating factor for the studied samples of kombucha beverages is the milk fat (MF) content, followed by total unsaturated fatty acids content (TUFA), monounsaturated fatty acids content (MUFA) and polyunsaturated fatty acids content (PUFA). The samples with 0.8 and 1.6% milk fat belong to the same cluster in the space of the analysed variables due to similarities in their AADPPH. It was determined by LDA that there was the biggest difference in quality between the groups of products with winter savoury and stinging nettle, while the highest similarity is between groups of products with wild thyme and peppermint regarding their pH values and antioxidant activity expressed as AADPPH.

scholarly journals A Multi-Level Strategy Based on Metabolic and Molecular Genetic Approaches for the Characterization of Different Coptis Medicines Using HPLC-UV and RAD-seq Techniques

Molecules ◽  
2018 ◽  
Vol 23 (12) ◽  
pp. 3090 ◽  
Author(s):  
Furong Zhong ◽  
Chan Shen ◽  
Luming Qi ◽  
Yuntong Ma
Keyword(s):  
High Performance ◽  
Molecular Genetic ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Chinese History ◽  
Nucleotide Polymorphisms ◽  
Additional Information ◽  
Multi Level ◽  
Coptis Herbs

Coptis plants (Ranunculaceae) to have played an important role in the prevention and treatment human diseases in Chinese history. In this study, a multi-level strategy based on metabolic and molecular genetic methods was performed for the characterization of four Coptis herbs (C. chinensis, C. deltoidea, C. omeiensis and C. teeta) using high performance liquid chromatography-ultraviolet (HPLC-UV) and restriction site-associated DNA sequencing (RAD-seq) techniques. Protoberberine alkaloids including berberine, palmatine, coptisine, epiberberine, columbamine, jatrorrhizine, magnoflorine and groenlandicine in rhizomes were identified and determined based on the HPLC-UV method. Among them, berberine was demonstrated as the most abundant compound in these plants. RAD-seq was applied to discover single nucleotide polymorphisms (SNPs) data. A total of 44,747,016 reads were generated and 2,443,407 SNPs were identified in regarding to four plants. Additionally, with respect to complicated metabolic and SNP data, multivariable statistical methods of principal component analysis (PCA) and hierarchical cluster analysis (HCA) were successively applied to interpret the structure characteristics. The metabolic variation and genetic relationship among different Coptis plants were successfully illustrated based on data visualization. Summarily, this comprehensive strategy has been proven as a reliable and effective approach to characterize Coptis plants, which can provide additional information for their quality assessment.

scholarly journals Multi-Sensor Characterization of Sparkling Wines Based on Data Fusion

Chemosensors ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 200
Author(s):  
Anais Izquierdo-Llopart ◽  
Javier Saurina
Keyword(s):  
Data Fusion ◽  
Organic Acids ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Sensor Data ◽  
Data Set ◽  
Total Antioxidant ◽  
Red Grape ◽  
Grape Varieties

This paper is focused on the assessment of a multi-sensor approach to improve the overall characterization of sparkling wines (cava wines). Multi-sensor, low-level data fusion can provide more comprehensive and more accurate vision of results compared with the study of simpler data sets from individual techniques. Data from different instrumental platforms were combined in an enriched matrix, integrating information from spectroscopic (UV/Vis and FTIR), chromatographic, and other techniques. Sparkling wines belonging to different classes, which differed in the grape varieties, coupages, and wine-making processes, were analyzed to determine organic acids (e.g., tartaric, lactic, malic, and acetic acids), pH, total acidity, polyphenols, total antioxidant capacity, ethanol, or reducing sugars. The resulting compositional values were treated chemometrically for a more efficient recovery of the underlaying information. In this regard, exploratory methods such as principal component analysis showed that phenolic compounds were dependent on varietal and blending issues while organic acids were more affected by fermentation features. The analysis of the multi-sensor data set provided a more comprehensive description of cavas according to grape classes, blends, and vinification processes. Hierarchical Cluster Analysis (HCA) allowed specific groups of samples to be distinguished, featuring malolactic fermentation and the chardonnay and red grape classes. Partial Least Squares-Discriminant Analysis (PLS-DA) also classified samples according to the type of grape varieties and fermentations. Bar charts and complementary statistic test were performed to better define the differences among the studied samples based on the most significant markers of each cava wine type. As a conclusion, catechin, gallic, gentisic, caftaric, caffeic, malic, and lactic acids were the most remarkable descriptors that contributed to their discrimination based on varietal, blending, and oenological factors.

scholarly journals GC-MS and HPLC-ESI-MS-MS Characterization of Sanchezia oblonga (Acanthaceae) Extracts

2020 ◽  
Vol 9 (1) ◽  
pp. 57
Author(s):  
Juliana Mourão Ravasi ◽  
Giuseppina Negri ◽  
Antonio Salatino ◽  
Maria Luiza Faria Salatino ◽  
Marco Aurelio Sivero Mayworm
Keyword(s):  
Sinapic Acid ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Lilium Longiflorum ◽  
Potential Health ◽  
Esi Ms ◽  
Aerial Parts ◽  
Sorghum Grain ◽  
New Compounds

The genus Sanchezia (Acanthaceae) comprises neotropical herbs and shrubs with showy flowers. Sanchezia oblonga (syn. S. nobilis) is a shrub of the rainforests of central and south America. The ethanolic extracts of leaves and stems from S. oblonga were analyzed by GC-EI-MS and RPHPLC-DAD-ESI-MS/MS. Fatty acids (free and esterified) and phytosterols were detected by the former method. Benzyl alcohol glycosides (21 and 25), sinapic acid glycoside esters (29 and 31), ethyl rosmarinate (24), sinapic acid-O-glucoside (28), dihydrosinapic acid-O-glucoside (26), catechin-O-arabinoside (36), in addition to flavonols glycosides (23, 32, 33 and 35) and rosmarinic acid-3’-O-glucoside (34) were detected by RPHPLC-DAD-ESI-MS/MS. Three new compounds, detected only in leaves, were tentatively identified as phenylpropane glyceride derivatives 1-O-coumaroyl-2-hydroxy propanal (20) and 1-O-coumaroyl-2-O-glycosyl propanal (22, 30). Compounds 20, 22 and 30 from S. oblonga are similar with phenylpropane glycerides present in red sorghum (Sorghum bicolor L. (Moench) and Lilium longiflorum Thunb. It is noteworthy that S. oblonga could be used in cooking as a complement after more detailed studies. Sorghum grain foods exhibit potential health benefits against chronic diseases related to over-nutrition. Lilium longiflorum possess flower buds and bulbs that are used for both culinary and medicinal purposes in many parts of the world. Studies on chemical composition and biological activity of the genus Sanchezia are scarce. The presence of phytosterols and flavonol glycosides were recently reported in leaves from this species. However, the chemical profile of the extracts analyzed in this work differs from that previously reported for aerial parts of S. nobilis (sin. S. oblonga). Further studies, including statistical methods, such as principal component analysis and hierarchical cluster analysis will be needed to evaluate chemical markers for this species.

Classification and characterization of Japanese consumers' beef preferences by external preference mapping

2017 ◽  
Vol 97 (10) ◽  
pp. 3453-3462 ◽  
Author(s):  
Keisuke Sasaki ◽  
Motoki Ooi ◽  
Naoto Nagura ◽  
Michiyo Motoyama ◽  
Takumi Narita ◽  
...  
Keyword(s):  
Preference Mapping ◽  
External Preference Mapping

scholarly journals Impact of fermented whey addition on resulting sensory characteristics and consumer preference of ripened cheeses

2019 ◽  
pp. 449
Author(s):  
Saris Ulises Ramos-Gabriel ◽  
José Andrés Herrera- Corredor ◽  
José Guadalupe Gamboa- Alvarado ◽  
Emmanuel de Jesús Ramírez- Rivera
Keyword(s):  
Descriptive Analysis ◽  
Consumer Preference ◽  
Fermented Milk ◽  
Sensory Characteristics ◽  
Quantitative Descriptive Analysis ◽  
Preference Mapping ◽  
External Preference Mapping ◽  
Quantitative Descriptive ◽  
The Impact ◽  
Temporal Dominance

The objective of this research was to evaluate the impact of fermented whey on the sensory characteristics of ripened cheeses and consumer preference. Ripened cheeses from 24, 25, 26, 27 and 28 months were characterized. The sensory techniques used were: Quantitative Descriptive Analysis®, Temporal Dominance of Sensations and External Preference Mapping. The results showed that the ripened cheeses of 24 to 27 months they were characterized by white color, acidified milk smell, fat aroma and acidified cream smell. The cheese of 28 months of ripened was perceived as fermented milk smell, cow smell and fat smell. The dominant attributes were fat aroma, bitter aftertaste, acid aftertaste and salty. Consumers preferred cheeses from 26 and 27 months of ripening. These results demonstrate the potential use of fermented whey as an alternative to produce ripened cheeses with sensory characteristics and their relation to consumer preference.

scholarly journals Characterization of two closely related citrus cultivars using UPLC-ESI-MS/MS-based widely targeted metabolomics

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254759
Author(s):  
Fu Wang ◽  
Lin Chen ◽  
Shiwei Chen ◽  
Hongping Chen ◽  
Youping Liu
Keyword(s):  
Effective Means ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Morphological Identification ◽  
Targeted Metabolomics ◽  
Esi Ms ◽  
Orthogonal Signal Correction ◽  
Widely Targeted Metabolomics ◽  
Quality Difference

Citrus cultivars are widely spread worldwide, and some of them only differ by specific mutations along the genome. It is difficult to distinguish them by traditional morphological identification. To accurately identify such similar cultivars, the subtle differences between them must be detected. In this study, UPLC-ESI-MS/MS-based widely targeted metabolomics analysis was conducted to study the chemical differences between two closely related citrus cultivars, Citrus reticulata ‘DHP’ and C. reticulata ‘BZH’. Totally 352 metabolites including 11 terpenoids, 35 alkaloids, 80 phenolic acids, 25 coumarins, 7 lignans, 184 flavonoids and 10 other compounds were detected and identified; Among them, 15 metabolites are unique to DHP and 16 metabolites are unique to BZH. Hierarchical cluster analysis (HCA), principal component analysis (PCA), and orthogonal signal correction and partial least squares-discriminant analysis (OPLS-DA) can be used to clearly discriminate between DHP and BZH. 93 metabolites including 36 down-regulated and 57 up-regulated are significantly different in DHP and BZH. They are mainly involved in the biosynthesis of flavonoids, flavones, flavonols, and isoflavonoids. In addition, the relative content levels of flavonoids, alkaloids, and terpenoids are much higher in the peel of DHP than that of BZH, the presence of which may correlate with the quality difference of the peels. The results reported herein indicate that metabolite analysis based on UPLC-ESI-MS/MS is an effective means of identifying cultivars with different genotypes, especially those that cannot be distinguished based on traditional identification methods.

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