Application of N-PLS to gas chromatographic and sensory data of traditional balsamic vinegars of modena

Durante, Caterina; Cocchi, Marina; Grandi, Margherita; Marchetti, Andrea; Bro, Rasmus

doi:10.1016/j.chemolab.2006.01.004

Cited by 72 publications

(38 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…These plots can provide insight into the extent of participation of a particular depth, chemical variable and sampling site in the model. Small SSR and high leverage value indicates positive influence of an attribute, whereas higher SSR and small leverage value for a negative influence on the model (Smilde et al, 2004;Durante et al, 2006). The leverage versus SSR plot (Fig.…”

Section: Resultsmentioning

confidence: 96%

“…sampling depths, chem- ical variables and sampling sites. A higher value of SSR for an attribute indicates its low contribution to the model and vice versa (Smilde et al, 2004;Singh et al, 2006b;Durante et al, 2006). Further, the behaviour of the Tucker3 model was studied in terms of leverage contribution for the first (h A ), second (h B ) and third (h C ) modes corresponding to the depths, chemical variables and sites, respectively.…”

Section: Resultsmentioning

confidence: 99%

“…Such an influence in multi-way component analysis can be evaluated through computation of the leverage (Smilde et al, 2004;Durante et al, 2006). For the data set (X array), leverage (h) for different modes were computed as below;…”

Section: Model Diagnosticmentioning

confidence: 99%

See 2 more Smart Citations

Vertical characterization of soil contamination using multi-way modeling – A case study

Singh

Malik

Basant

et al. 2007

Environ Monit Assess

View full text Add to dashboard Cite

This study describes application of chemometric multi-way modeling approach to analyze the dataset pertaining to soils of industrial area with a view to assess the soil/sub-soil contamination, accumulation pathways and mobility of contaminants in the soil profiles. The three-way (sampling depths, chemical variables, sampling sites) dataset on heavy metals in soil samples collected from three different sites in an industrial area, up to a depth of 60 m each was analyzed using three-way Tucker3 model validated for stability and goodness of fit. A two component Tucker3 model, explaining 66.6% of data variance, allowed interpretation of the data information in all the three modes. The interpretation of core elements revealing interactions among the components of different modes (depth, variables, sites) allowed inferring more realistic information about the contamination pattern of soils both along the horizontal and vertical coordinates, contamination pathways, and mobility of contaminants through soil profiles, as compared to the traditional data analysis techniques. It concluded that soils at site-1 and site-2 are relatively more contaminated with heavy metals of both the natural as well as anthropogenic origins, as compared to the soil of site-3. Moreover, the accumulation pathways of metals for upper shallow layers and deeper layers of soils in the area were differentiated. The information generated would be helpful in developing strategies for remediation of the contaminated soils for reducing the subsequent risk of ground-water contamination in the study region.

show abstract

Section: Resultsmentioning

confidence: 96%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Vertical characterization of soil contamination using multi-way modeling – A case study

Singh

Malik

Basant

et al. 2007

Environ Monit Assess

View full text Add to dashboard Cite

show abstract

“…It attempts to maximize the covariance between X and Y and searches for the factor space most congruent to both matrices [23]. Detailed description of the PLSR method and its algorithms could be found elsewhere [24], however, in brief, it can be expressed as a bilinear decomposition of both X and Y as [25,26];…”

Section: Partial Least Squares Regression (Plsr) Modelingmentioning

confidence: 99%

Modeling the performance of “up-flow anaerobic sludge blanket” reactor based wastewater treatment plant using linear and nonlinear approaches—A case study

Singh

Basant

Malik

et al. 2010

Analytica Chimica Acta

View full text Add to dashboard Cite

“…Analytical platforms, such as Gas Chromatography-Mass Spectrometry (GC-MS), Liquid Chromatography-Mass Spectrometry (LC-MS), Capillary Electrophoresis-Mass Spectrometry (CE-MS), Nuclear Magnetic Resonance spectroscopy (NMR), Infrared Spectroscopy (IR), Near-Infrared Spectroscopy (NIR), and Raman spectroscopy, are frequently employed in various foodomics studies and allow semi-quantitative and quantitative detection of broad range of molecules, which in turn may provide insight into biology and/or food process related changes. Foods are complex heterogeneous systems food control (DURANTE et al, 2006), foodomics (BIANCHI et al, 2001), and nutritional metabolomics (ZAFRA-GOMEZ et al, 2010) applications. LC-MS is a technique that allows mass spectrometric detection of metabolites that are separated in liquid phase due to their different mobile (solvent)-stationary (column) phase partitioning coeffi cients.…”

Section: Introductionmentioning

confidence: 99%

Trends in the application of chemometrics to foodomics studies

Khakimov¹,

Gürdeniz²,

Engelsen³

2015

Acta Alimentaria

View full text Add to dashboard Cite

There is an ever-increasing trend in advanced food analysis and foodomics to use more and more sophisticated analytical platforms that generate large and complex data structures, which in turn require more and more sophisticated data analysis tools for converting data into information. The choice of multivariate chemometric methods is primarily determined by the design of the study, type of the data, and the conclusions sought. In order to validate multivariate models, scientists are required to have basic chemometric knowledge and to be familiar with the variance structure of the investigated data. This review outlines some of the key aspects of applying common chemometric methods used within foodomics and provides selected examples of current applications. The review aims to provide simple insight into various multivariate methods and to illustrate pros and cons of unsupervised and supervised methods. The main analytical platforms used in foodomics are briefl y discussed from the application point of view and the utilization of the generated data is illustrated. In addition, advanced data pre-processing tools, prior to multivariate analysis, are explained and relevant tools are demonstrated.

show abstract

Application of N-PLS to gas chromatographic and sensory data of traditional balsamic vinegars of modena

Cited by 72 publications

References 25 publications

Vertical characterization of soil contamination using multi-way modeling – A case study

Vertical characterization of soil contamination using multi-way modeling – A case study

Modeling the performance of “up-flow anaerobic sludge blanket” reactor based wastewater treatment plant using linear and nonlinear approaches—A case study

Trends in the application of chemometrics to foodomics studies

Contact Info

Product

Resources

About