Optimization of HS-SPME Using Artificial Neural Network and Response Surface Methodology in Combination with Experimental Design for Determination of Volatile Components by Gas Chromatography-Mass Spectrometry in Korla Pear Juice

Zhang, Fang; Zhan, Ping; Tian, Honglei; Wei, Zhisheng; Wang, Peng

doi:10.1007/s12161-018-1173-6

Cited by 11 publications

(5 citation statements)

References 33 publications

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“…Esters and alcohols were detected as the main aroma compounds as reported in European (Occidental) pears and Asiatic (Oriental) pears, such as “ Niitaka ” ( P. pyrifolia ) and Korla pear ( P. bretschneideri Rehd.). 17 − 19 …”

Section: Introductionmentioning

confidence: 99%

Chemical Composition of Juices Made from Cultivars and Breeding Selections of European Pear (Pyrus communis L.)

Laaksonen

Tian

et al. 2022

J. Agric. Food Chem.

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The phenolic profiles and other major metabolites in juices made from fruits of 17 cultivars and selections of European pears were investigated using UHPLC-DAD-ESI-QTOF-MS and GC-FID, respectively. A total of 39 phenolic compounds were detected, including hydroxybenzoic acids, hydroxycinnamic acids, flavan-3-ols, procyanidins, flavonols, and arbutin. Among these compounds, 5- O -caffeoylquinic acid was the most predominant, accounting for 14–39% of total quantified phenolic contents (TPA) determined in this study. The variations were mainly cultivar dependent. The genetic background effect on the chemical compositions is complex, and breeding selections from the same parental cultivars varied dramatically in chemical compositions. Putative perry pears contained more 4- O -caffeoylquinic acid, 5- O -caffeoylquinic acid, caffeoyl N -trytophan, caffeoylshikimic acid, coumaroylquinic acid isomer, syringic acid hexoside, procyanidin dimer B2, (+)-catechin, and malic acid, whereas putative dessert pears had higher esters, alcohols, and aldehydes. The results will be helpful in providing industry with phytochemical compositional information, assisting pear selections in commercial utilization.

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Section: Introductionmentioning

confidence: 99%

Chemical Composition of Juices Made from Cultivars and Breeding Selections of European Pear (Pyrus communis L.)

Laaksonen

Tian

et al. 2022

J. Agric. Food Chem.

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“…The SPME technique efficiency depends on the polarity and thickness of the fiber coating, the extraction time and temperature, the agitation and pH of the sample solution, the addition of salt to the sample, and on the concentration of analyte in a sample [15]. Therefore, several studies about fruits and juices have been dedicated to the optimization of SPME parameters for volatile compounds isolation from jambolan fruits [16], Korla pear juice [17], soursop pulp [18] [19], berry [20], and blackberry fruits [21]. Response Surface Methodology (RSM) is a tool for multivariate optimization commonly used for HS-SPME optimization.…”

Section: Solid-phase Microextraction (Spme) Is a Green Sample Preparamentioning

confidence: 99%

Method Optimization Study on Isolation of Volatile Compounds by Headspace Solid-Phase Microextraction (HS-SPME) from Custard Apple (<i>Annona squamosa</i> L.) Pulp.

Galvão¹,

Santana²,

Nogueira³

et al. 2020

JASMI

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Aroma is an important quality parameter, which can help in delaying degradative processes and hence understanding the volatile compounds that are part of an aroma is extremely important. Thus, the aim of this study was to isolate the volatile compounds present in custard apple (Annona squamosa L.) pulp by solid-phase microextraction (SPME) technique using 3 different fibers (DVB/CAR/PDMS, PDMS and PDMS/DVB). An experimental design was set up to evaluate the best extraction conditions wherein the variables were extraction temperature (minimum 28˚C, maximum 62˚C), ionic strength (minimum 0, maximum 30.0%) and sample concentration (min 1, max 99.0%). The separation of volatiles was achieved in chromatographic columns of different polarity (polar and non-polar) while identification of volatile compounds was performed by high resolution gas chromatography system coupled with mass spectrometry. The results obtained using 3 different fibers revealed the isolation of 71 compounds with fiber DVB/CAR/PDMS, while only 30 and 21 compounds were isolated using fibers PDMS/DVB and PDMS, respectively. The major classes of compounds identified were terpenes, esters, alcohols and aldehydes. Optimum conditions for obtaining higher number of volatiles for non-polar column were 45˚C for extraction temperature, 15% of sodium chloride and 50% of pulp amount which resulted in isolation of a maximum of 78 peaks.

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“…Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), RSM combined with ANN, can be used as the main tool to simulate and optimize the processes of metals removal from aqueous solutions [16]. ANN models, combined with GA, show more accurate predictions, improve generalization possibilities, and calculate more optimal conditions for the flow of simulated processes than RSM models [17].…”

Section: Neural Network In Chemical Processes Controlmentioning

confidence: 99%

Resource and Energy Saving Neural Network-Based Control Approach for Continuous Carbon Steel Pickling Process

Bezsonov¹,

Ilyunin²,

Kaldybaeva³

et al. 2019

J. sustain. dev. energy water environ. syst.

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Optimization of HS-SPME Using Artificial Neural Network and Response Surface Methodology in Combination with Experimental Design for Determination of Volatile Components by Gas Chromatography-Mass Spectrometry in Korla Pear Juice

Cited by 11 publications

References 33 publications

Chemical Composition of Juices Made from Cultivars and Breeding Selections of European Pear (Pyrus communis L.)

Chemical Composition of Juices Made from Cultivars and Breeding Selections of European Pear (Pyrus communis L.)

Method Optimization Study on Isolation of Volatile Compounds by Headspace Solid-Phase Microextraction (HS-SPME) from Custard Apple (<i>Annona squamosa</i> L.) Pulp.

Resource and Energy Saving Neural Network-Based Control Approach for Continuous Carbon Steel Pickling Process

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Optimization of HS-SPME Using Artificial Neural Network and Response Surface Methodology in Combination with Experimental Design for Determination of Volatile Components by Gas Chromatography-Mass Spectrometry in Korla Pear Juice

Cited by 11 publications

References 33 publications

Chemical Composition of Juices Made from Cultivars and Breeding Selections of European Pear (Pyrus communis L.)

Chemical Composition of Juices Made from Cultivars and Breeding Selections of European Pear (Pyrus communis L.)

Method Optimization Study on Isolation of Volatile Compounds by Headspace Solid-Phase Microextraction (HS-SPME) from Custard Apple (&lt;i&gt;Annona squamosa&lt;/i&gt; L.) Pulp.

Resource and Energy Saving Neural Network-Based Control Approach for Continuous Carbon Steel Pickling Process

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Product

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Method Optimization Study on Isolation of Volatile Compounds by Headspace Solid-Phase Microextraction (HS-SPME) from Custard Apple (<i>Annona squamosa</i> L.) Pulp.