Statistical designs and response surface techniques for the optimization of chromatographic systems

Ferreira, Sérgio Luís Costa; Bruns, Roy E.; Silva, Erik Galvão Paranhos da; Santos, Walter Nei Lopes dos; Quintella, Cristina M.; David, Jorge; Andrade, Jaílson Bittencourt de; Breitkreitz, Márcia Cristina; Jardim, Isabel Cristina Sales Fontes; Neto, B.B.

doi:10.1016/j.chroma.2007.03.051

Cited by 539 publications

(314 citation statements)

References 88 publications

Supporting

Mentioning

290

Contrasting

Unclassified

Order By: Relevance

“…(2) [12], [13] for whole fruits can be seen in Table III (number of peaks) and Table IV (total area). Regression model for the number of peaks (1) was not statistically significant (F calculated < F tabulated ), but the regression obtained for total area (2) was significant at 10% (F calculated > F tabulated ) indicating the existence of an appropriate model for the variable studied.…”

Section: Resultsmentioning

confidence: 99%

“…For this experiment, the regression model for the number of peaks (3) was significant at 5%, and was not significant for total area (4). However, it can also be seen that the models did not present evidence of significant lack of fit for the response variable, showing that they can be accepted as providing an adequate representation of the data [12]. The contour plots of the response surfaces were the starting point for the establishment of optimal conditions for volatile isolation by HS-SPME.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Isolation of Volatiles Compounds in Banana by HS-SPME: Optimization for the Whole Fruit and Pulp

Facundo¹,

Garruti²,

Cordenunsi³

et al. 2013

IJBBB

View full text Add to dashboard Cite

Abstract-The best conditions for the isolation of banana volatiles by headspace solid phase microextraction (HS-SPME) were determined for the intact whole fruit (with peel) and for the pulp only. Optimization of isolation conditions was carried out using a Central Composite Rotational Design based on Response Surface Methodology with two factors: time needed to reach equilibrium in the headspace and the fiber exposure time. Samples were analyzed by GC-MS. The criteria were higher number of peaks and greater total area of the chromatogram. The best conditions for isolating volatiles from the headspace of whole fruits were 140 min headspace equilibrium and 120 min fiber exposure, while for the banana pulp the best conditions were 15 and 60 min for equilibrium and exposure times, respectively. The results suggest that the whole fruit and pulp have very similar qualitative volatile profile in ripe banana.Index Terms-Central composite rotational design, musa acuminata L., response surface methodology.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Isolation of Volatiles Compounds in Banana by HS-SPME: Optimization for the Whole Fruit and Pulp

Facundo¹,

Garruti²,

Cordenunsi³

et al. 2013

IJBBB

View full text Add to dashboard Cite

show abstract

“…To optimize the ultrasound-assisted extraction method of metals (Cu, Mn, Ni and zn) in ration samples for chicken nutrition, we used two types of experimental design: a simplex centroid mixture design (Bruns et al 2006, Massart et al 1997 to optimize the ratio of extracting solutions (HCl, hNO 3 and H 3 COOh), and a doehlert design (Ferreira et al 2007) for optimization of method variables (final concentration of acid, sample mass, and sonication time).…”

Section: Preliminary Treatments Of Samplesmentioning

confidence: 99%

Multivariate optimization of an ultrasound-assisted extraction procedure for Cu, Mn, Ni and Zn determination in ration to chickens

Barros

Bezerra

Valasques

et al. 2013

An. Acad. Bras. Ciênc.

View full text Add to dashboard Cite

In this work, multivariate optimization techniques were used to develop a method based on the ultrasoundassisted extraction for copper, manganese, nickel and zinc determination from rations for chicken nutrition using flame atomic absorption spectrometry. The proportions of extracting components (2.0 mol.L -1 nitric, hydrochloric and acetic acid solutions) were optimized using centroid-simplex mixture design. The optimum proportions of this mixture taken as percentage of each component were respectively 20%, 37% and 43%. variables of method (sample mass, sonication time and final acid concentration) were optimized using Doehlert design. The optimum values found for these variables were respectively 0.24 g, 18s and 3.6 mol.L -1 . The developed method allows copper, manganese, nickel and zinc determination with quantification limits of 2.82; 4.52; 10.7; e 9.69 µg.g -1, and precision expressed as relative standard deviation (%RSd, 25 µg.g -1 , N = 5) of 5.30; 2.13; 0.88; and 0.83%, respectively. This method was applied in the analytes determination from chicken rations collected from specialized commerce in Jequié city (Bahia State/Brazil). Application of paired t-test at the obtained results, in a confidence level of 95%, does not show significant difference between the proposed method and the microwave-assisted digestion.

show abstract

“…The most commonly used clean methods are SPME, SFE, and static and dynamic headspace extraction. The multivariate statistical techniques applied to chromatographic methods have been basically employed for the optimization of the sample preparation and sample analysis steps [10].…”

Section: Introductionmentioning

confidence: 99%

HS-SPME/GC-MS Analysis of VOC and Multivariate Techniques Applied to the Discrimination of Brazilian Varieties of Mango

Benevides¹,

Bezerra²,

Pereira³

et al. 2014

AJAC

Self Cite

View full text Add to dashboard Cite

The present study analyzed the volatile compounds of three mango varieties (Tommy Atkins, Rosa and Espada) using the static headspace technique with SPME coupled to CG-MS. Multivariate methodologies, such as factorial design and response surface methodology, were used to optimize the conditions of adsorption and desorption of these substances. The data were evaluated by using principal components analysis (PCA) and hierarchical grouping analysis, in order to visualize grouping tendencies of volatile compounds. Thirty-seven volatile compounds belonging to different chemical classes, such as esters, terpenes, alcohols and others, were tentatively identified in the three varieties of mango. Amongst them, twenty-three presented chromatographic peaks with relative areas larger than 2%. The multivariate analysis made it possible to visualize the grouping tendencies of the mango samples, according to the presence of their respective volatile substances, and enabled the identification of the groups of substances responsible for the discrimination among the three varieties.

show abstract

Statistical designs and response surface techniques for the optimization of chromatographic systems

Cited by 539 publications

References 88 publications

Isolation of Volatiles Compounds in Banana by HS-SPME: Optimization for the Whole Fruit and Pulp

Isolation of Volatiles Compounds in Banana by HS-SPME: Optimization for the Whole Fruit and Pulp

Multivariate optimization of an ultrasound-assisted extraction procedure for Cu, Mn, Ni and Zn determination in ration to chickens

HS-SPME/GC-MS Analysis of VOC and Multivariate Techniques Applied to the Discrimination of Brazilian Varieties of Mango

Contact Info

Product

Resources

About