Modelling the respiration rate of guava (Psidium guajava L.) fruit using enzyme kinetics, chemical kinetics and artificial neural network

Wang, Zhiwei; Duan, Hua-Wei; Hu, Chaofan

doi:10.1007/s00217-009-1079-z

Cited by 40 publications

(20 citation statements)

References 34 publications

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“…However, experimental evidence suggests that the significant (p < 0.05) influence of time and temperature on the observed high RQ for Pomegranate arils (cv. "Bhagwa") occurred under aerobic conditions, similar to the findings reported by Wang et al, (2009) for guava fruit.…”

Section: Effect Of Time and Temperature On The Respiration Ratesupporting

confidence: 87%

Effect of Time and Temperature on Respiration Rate of Pomegranate arils (cv. ‘Bhagwa’)

Ramasamy¹,

Joyner²

2017

Int.J.Curr.Microbiol.App.Sci

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Section: Effect Of Time and Temperature On The Respiration Ratesupporting

confidence: 87%

Effect of Time and Temperature on Respiration Rate of Pomegranate arils (cv. ‘Bhagwa’)

Ramasamy¹,

Joyner²

2017

Int.J.Curr.Microbiol.App.Sci

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“…All of the developed models showed good agreement with actual observations. As regards fidelity, the ANN model with topologic structure of 3×9×1 trained by the LevenbergMarquardt algorithm, evaluation results were such that the mean absolute percentage error (MAPE) and the two-tailed Pearson correlation coefficient (r) were 5. indicated that the ANN approach is a more precise method, and can be used for predicting the respiration rate of guava fruit [24].…”

Section: P Guavamentioning

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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“…As regards fidelity the ANN model with topologic structure of 3 × 9×1 trained by the LevenbergMarquardt algorithm, evaluation results were such that the mean absolute percentage error (MAPE) and the two-tailed Pearson correlation coefficient (r) were 5.31 and 0.997 for 12 °C, 4.85 and 0.995 for 22 °C, had superiority over the two other models. The results indicated that the ANN approach is a more precise method, and can be used for predicting the respiration rate of guava fruit [27].…”

Section: Guavamentioning

confidence: 95%

Artificial neural networks (ANNs) in food science – A review

Goyal¹

2013

International Journal of Scientific World

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Artificial Neural Networks (ANNs) have been applied in several areas, viz., science and technology, engineering, agriculture, life sciences and medicine as they have a remarkable ability to provide accurate results. This communication highlights the systematic information available in the literature concerning the implementation of ANN models for predicting properties of dairy products, fruits, vegetables and meat. The information presented in this review paper shows that over the last decade research related to ANN based predictive modelling in food science has picked up.

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Modelling the respiration rate of guava (Psidium guajava L.) fruit using enzyme kinetics, chemical kinetics and artificial neural network

Cited by 40 publications

References 34 publications

Effect of Time and Temperature on Respiration Rate of Pomegranate arils (cv. ‘Bhagwa’)

Effect of Time and Temperature on Respiration Rate of Pomegranate arils (cv. ‘Bhagwa’)

Artificial Neural Networks in Fruits: A Comprehensive Review

Artificial neural networks (ANNs) in food science – A review

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