Optimization of total phenolic content extracted from Garcinia mangostana Linn. hull using response surface methodology versus artificial neural network

Cheok, Choon Yoong; Chin, Nyuk Ling; Yusof, Yus Aniza; Talib, Rosnita A.; Law, Chung Lim

doi:10.1016/j.indcrop.2012.03.019

Cited by 102 publications

(49 citation statements)

References 24 publications

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“…In this study, 8 neurons in the hidden layer were determined from the lowest value of mean squared errors (MSE) of 0.020. The choice of one hidden layer is usually sufficient for the purpose of approximation of continuous nonlinear function as more hidden layers may cause over-fitting (Madadlou et al 2009;Rai et al 2005;Torrecilla et al 2004, Cheok et al 2012. Besides the number of neurons in hidden layers, the momentum and learning rate are two important settings for this MLP network.…”

Section: Artificial Neural Network (Ann)mentioning

confidence: 99%

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Chemical composition and temperature influence on honey texture properties

et al. 2015

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The aim of this study is to evaluate the chemical composition and temperatures (20, 30, 40, 50 and 60°C) influence on the honey texture parameters (hardness, viscosity, adhesion, cohesiveness, springiness, gumminess and chewiness). The honeys analyzed respect the European regulation in terms of moisture content and inverted sugar concentration. The texture parameters are influenced negatively by the moisture content, and positively by the°Brix concentration. The texture parameters modelling have been made using the artificial neural network and the polynomial model. The polynomial model predicted better the texture parameters than the artificial neural network.

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Section: Artificial Neural Network (Ann)mentioning

confidence: 99%

“…and Y i,cal are the experimental and calculated responses, and P is the number of the experimental run. Absolute average deviation (AAD) in this study is a measure of how much the predicated data from models deviates from the experimental data (Cheok et al 2012).…”

Section: Polynomial Modelling Of Textural Propertiesmentioning

confidence: 99%

Chemical composition and temperature influence on honey texture properties

et al. 2015

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“…Analysis using ANN predicted data, which showed a higher R 2 value of 0.945 and average absolute deviation (ADD) values of 4.01% versus 5.37% for the RSM. The results suggested that ANN is a better modeling technique for non-linear data for predicting TPC extracted from mangosteen hull powder compared to the RSM [29].…”

Section: T Mangosteenmentioning

confidence: 99%

Artificial Neural Networks in Fruits: A Comprehensive Review

Goyal¹

2014

IJIGSP

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Abstract-This review discusses the application of artificial neural networks (ANN) modeling in fruits. It covers all fruits in which ANN modeling has been applied. ANN is quite a new and easy computational modeling approach used for prediction, which has become popular and accepted by food industry, researchers, scientists and students. ANNs have been applied in almost every field of science and technology, viz., speech synthesis & recognition, pattern classification, adaptive interfaces between humans & complex physical systems, clustering, function approximation, image data compression, non-linear system modeling, associative memory, combinatorial optimization, control and several others, as they have proved valuable tools for obtaining the required output. ANN provides an exciting alternative method for solving a variety of problems in different areas of science and engineering. The aim of this communication is to discover the recent advances of ANN technology implemented in fruits, and discuss the critical role that ANN plays in predictive modelling.

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“…Prasad et al [8] obtained highest phenolic content from Mangifera pajang when carried out extraction at 58 °C for 30 minutes. Extraction of phenolic compounds from mangosteen hull carried out by Cheok et al [9] at room temperature required 2 hour of extraction duration to obtained highest phenolic content. Contradictory, this study achieved highest phenolic content after 10 minutes of extraction at 70 °C.…”

Section: Resultsmentioning

confidence: 99%

“…The use of response surface methodology (RSM) in the process optimization is a time and cost saving approach because the number of experimental trials required to evaluate multiple variables and their interactions is reduced [6]. Most of previous studies on optimization of phenolic content extraction employed central composite design (CCD) as their experimental design [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Application of Response Surface Methodology in Extraction of Bioactive Component from Palm Leaves (Elaeis guineensis)

et al. 2013

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-The hydroxyl groups of the polyphenols are capable to act as reducing agent for reduction reaction. The effect of drying temperature, extraction temperature and extraction duration were evaluated using central composite design which consists of 20 experimental runs. Response surface methodology (RSM) was used to estimate the optimum parameters in extracting polyphenols from the palm leaves. The correspondence analysis of the results yielded a quadratic model which can be used to find optimum conditions of extraction process. The optimum extraction condition of drying temperature, extraction temperature and extraction duration are 70°C, at 70°C of 10 minutes, respectively. Total polyphenols were determined by application of the Folin-Ciocalteu micro method and the extract was found contain of 8 mg GAE/g dry palm leaves at optimum conditions.

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Optimization of total phenolic content extracted from Garcinia mangostana Linn. hull using response surface methodology versus artificial neural network

Cited by 102 publications

References 24 publications

Chemical composition and temperature influence on honey texture properties

Chemical composition and temperature influence on honey texture properties

Artificial Neural Networks in Fruits: A Comprehensive Review

Application of Response Surface Methodology in Extraction of Bioactive Component from Palm Leaves (Elaeis guineensis)

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