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Screening of the alterations in qualitative characteristics of grape under the impacts of storage and harvest times using artificial neural network

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Abstract

The tested model showed that high reliability based on the obtained inputs for achieved data for RMSE and correlation coefficient between the obtained experimental and predicted values. An enhancement in the storage time, reduced the pH value and flavor index (fruit maturation), but boosted the acidity value of the fruits. On the other hand retardation in the harvest time led to an increase in pH value, total soluble solids and dextrose contents as well as flavor index of the samples. Artificial neural network design has been applied to predict the process of alterations during storage time. Back propagation feed forward neural network with the arrangement of 5:8:2 with a high correlation coefficient value (˃ 0.989) and low root mean square error value (< 0.0019) as well as sigmoid hyperbolic tangent activation function with Levenberg–Marquardt learning and learning cycle of 1000 were detected as the most reliable and appropriate neural network model in storage process.

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Acknowledgements

The present work is a part of PhD studies of Vahid Farzaneh, We gratefully appreciate Erasmus Mundus Program SALAM for the financial supports and Food Science Lab of University of the Algarve for facilities provided during this study. Our great thanks to Golestan Agricultural and Natural Recourses Research Center, Gorgan, Iran, Agricultural Engineering.

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Authors and Affiliations

  1. MeditBio, Food Science Laboratory, Faculty of Sciences and Technology, University of Algarve, Campus de Gambelas, 8005-139, Faro, Algarve, Portugal

    Vahid Farzaneh & Isabel S. Carvalho

  2. Agricultural Engineering Research Department, Golestan Agricultural and Natural Resources Research and Education Center, Gorgan, Iran

    Alireza Ghodsvali

  3. Department of Food Science and Technology, Gonbad Kavoos Branch, Islamic Azad University, Gonbad Kavoos, Iran

    Hamid Bakhshabadi

  4. Young Researchers and Elites Club, Sabzevar Branch, Islamic Azad University, Sabzevar, Iran

    Zahra Dolatabadi

  5. Department of Obstetrics and Gynecology, Infectious Diseases and Tropical Medicine Research Center, Zahedan University of Medical Sciences, Zahedan, Iran

    Farahnaz Farzaneh

  6. Department of Food Chemistry, University of Agricultural Sciences and Natural Resources, Gorgan, Iran

    Khashayar Sarabandi

Authors
  1. Vahid Farzaneh
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  2. Alireza Ghodsvali
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  3. Hamid Bakhshabadi
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  4. Zahra Dolatabadi
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  5. Farahnaz Farzaneh
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  6. Isabel S. Carvalho
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  7. Khashayar Sarabandi
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Correspondence to Vahid Farzaneh.

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Farzaneh, V., Ghodsvali, A., Bakhshabadi, H. et al. Screening of the alterations in qualitative characteristics of grape under the impacts of storage and harvest times using artificial neural network. Evolving Systems 9, 81–89 (2018). https://doi.org/10.1007/s12530-017-9212-x

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  • DOI: https://doi.org/10.1007/s12530-017-9212-x

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