Validation of consensus between proteomic and clinical chemistry datasets by applying a new randomisation F-test for generalised procrustes analysis

Wu, Wen; Roberts, Sophie; Armitage, James R.; Tooke, P.; Cordingley, Hayley C.; Wildsmith, S.E.

doi:10.1016/s0003-2670(03)00336-2

Cited by 7 publications

(3 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Specifically, GPA constructs the consensus configuration of a group of data sets by applying transforms in an attempt to superimpose them. In this work we used the Gower algorithm that minimizes the within-samples variance by applying translation, scaling, and rotation to generate a p -dimensional average configuration Y c. Following this, a q -dimensional group average space ( q ≤ p ) is constructed from Y c by PCA . Therefore, GPA theory and algorithms can be applied to match wine elemental and isotopic data to the corresponding soil data.…”

Section: Methodsmentioning

confidence: 99%

Fingerprints for Main Varieties of Argentinean Wines: Terroir Differentiation by Inorganic, Organic, and Stable Isotopic Analyses Coupled to Chemometrics

Paola-Naranjo

Baroni

Podio

et al. 2011

J. Agric. Food Chem.

151

108

View full text Add to dashboard Cite

Our main goal was to investigate if robust chemical fingerprints could be developed for three Argentinean red wines based on organic, inorganic, and isotopic patterns, in relation to the regional soil composition. Soils and wines from three regions (Mendoza, San Juan, and Córdoba) and three varieties (Cabernet Sauvignon, Malbec, and Syrah) were collected. The phenolic profile was determined by HPLC-MS/MS and multielemental composition by ICP-MS; (87)Sr/(86)Sr and δ(13)C were determined by TIMS and IRMS, respectively. Chemometrics allowed robust differentiation between regions, wine varieties, and the same variety from different regions. Among phenolic compounds, resveratrol concentration was the most useful marker for wine differentiation, whereas Mg, K/Rb, Ca/Sr, and (87)Sr/(86)Sr were the main inorganic and isotopic parameters selected. Generalized Procrustes analysis (GPA) using two studied matrices (wine and soil) shows consensus between them and clear differences between studied areas. Finally, we applied a canonical correlation analysis, demonstrating significant correlation (r = 0.99; p < 0.001) between soil and wine composition. To our knowledge this is the first report combining independent variables, constructing a fingerprint including elemental composition, isotopic, and polyphenol patterns to differentiate wines, matching part of this fingerprint with the soil provenance.

show abstract

Section: Methodsmentioning

confidence: 99%

Fingerprints for Main Varieties of Argentinean Wines: Terroir Differentiation by Inorganic, Organic, and Stable Isotopic Analyses Coupled to Chemometrics

Paola-Naranjo

Baroni

Podio

et al. 2011

J. Agric. Food Chem.

151

108

View full text Add to dashboard Cite

show abstract

“…Specifically, GPA constructs the consensus configuration of a group of data sets by applying transforms in an attempt to superimpose them. In this work, we used the Gower algorithm that minimizes within-sample variance by applying translation, scaling, and rotation to generate a p -dimensional average configuration Y c. Following this, a q -dimensional group average space ( q ≤ p ) is constructed from Y c by principal component analysis (PCA) . Therefore, GPA theory and algorithms can be applied to match meat elemental and isotopic data to the corresponding soil and drinking water data.…”

Section: Methodsmentioning

confidence: 99%

How Much Do Soil and Water Contribute to the Composition of Meat? A Case Study: Meat from Three Areas of Argentina

Baroni

Podio

Badini

et al. 2011

J. Agric. Food Chem.

View full text Add to dashboard Cite

The main goal of this study was to propose a reliable method to verify the geographical origin of meat, establishing the influence of soil and water on its isotopic and elemental composition. Thus, beef meat, soil, and water samples were collected from three major cattle-producing regions of Argentina (Buenos Aires, Córdoba, and Entre Ríos). Multielemental composition was determined on these three matrices by inductively coupled plasma mass spectrometry (ICP-MS), δ(13)C and δ(15)N by isotope-ratio mass spectrometry (IRMS), and the (87)Sr/(86)Sr ratio by thermal ionization mass spectrometry (TIMS). Soil and drinking water samples could be characterized and clearly differentiated by combining the isotopic ratios and elements, demonstrating differences in geology and climatic conditions of three regions. Similarly, meat originating at each sampling area was characterized and differentiated using only five key variables (Rb, Ca/Sr, δ(13)C, δ(15)N, and (87)Sr/(86)Sr). Generalized procrustes analysis (GPA), using the three studied matrices (soil, water, and meat) shows consensus between them and clear differences between studied areas. Furthermore, canonical correlation analysis (CCA) demonstrates significant correlation between the chemical-isotopic profile of meat with those corresponding to both soil and water (r(2) = 0.93, p < 0.001; and r(2) = 0.83, p < 0.001, respectively). So far, there are clear coincidences between the meat fingerprint and those from soil/water where cattle grew, presenting a good method to establish beef provenance. To the authors' knowledge this is the first report linking the influence of soil and water all together on the composition of beef, presenting the basis for the authentication of Argentinean beef, which could be extended to meat from different provenances.

show abstract

“…The most important problem with sensory analysis is the wide variability in assessments of the same food sample by different panellists. Especially, the most important source of variability is the lack of consensus in describing a sample between panellists (Wu et al, 2003). The Generalized Procrustes Analysis (GPA) is a multi-variate statistical method that is used for the evaluation of sensory analysis in the food industry.…”

Section: Introductionmentioning

confidence: 99%

Using Generalized Procrustes Analysis for Evaluation of Sensory Characteristic Data of Lamb Meat

Ser

2019

Turkish JAF Sci.Tech.

View full text Add to dashboard Cite

Generalized Procrustes Analysis (GPA) is a multivariate statistic method that is used at the evaluation of sensory analyses in the food industry. GPA provides benefit in terms of decreasing the difference between the panellists and bringing the data obtained from different panellists together. In this study, the aim was to determine the effect of a pre-slaughter fasting period on sensory characteristics of lambs fed with different rations using GPA. Semi-trained panellists formed from twenty-six persons were requested for evaluation of the meat samples such as tenderness, juiciness, flavour and overall liking rated on a scale of 1(extremely dislike) to 9 (extremely good). The first two factors obtained by GPA explained 66.74% of total variability. As a result of the analysis, it was determined that 12 h and 24 h fasting of lambs fed barley supplemented with alfalfa hay were less preferable when compared to lambs fed alfalfa hay only. In addition, lambs in both groups with 48 h fasting were preferred less by the panellists. In conclusion, GPA analysis provides useful data concerning the sensitivity of each panellist in a sensory panel test.

show abstract

Validation of consensus between proteomic and clinical chemistry datasets by applying a new randomisation F-test for generalised procrustes analysis

Cited by 7 publications

References 36 publications

Fingerprints for Main Varieties of Argentinean Wines: Terroir Differentiation by Inorganic, Organic, and Stable Isotopic Analyses Coupled to Chemometrics

Fingerprints for Main Varieties of Argentinean Wines: Terroir Differentiation by Inorganic, Organic, and Stable Isotopic Analyses Coupled to Chemometrics

How Much Do Soil and Water Contribute to the Composition of Meat? A Case Study: Meat from Three Areas of Argentina

Using Generalized Procrustes Analysis for Evaluation of Sensory Characteristic Data of Lamb Meat

Contact Info

Product

Resources

About