Home > III Southeast Asia Symposium on Quality Management in Postharvest Systems > Improving the accuracy of intercellular space volume of citrus prediction by artificial neural networks

Articles

Improving the accuracy of intercellular space volume of citrus prediction by artificial neural networks

Article number

1179_7

Pages

37 – 44

Language

English

Abstract

Publication

III Southeast Asia Symposium on Quality Management in Postharvest Systems

Authors

A. Dirpan, Y. Hikida, H. Chiba, G.K. Aji, A.N. Rahman

Keywords

citrus, prediction, intercellular space volume, artificial neural network

Full text

https://doi.org/10.17660/ActaHortic.2017.1179.7

Groups involved

Online Articles (53)

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22. Development of novel sanitizers for fresh vegetables

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28. Effects of modified atmosphere packaging on the quality and shelf life of tomatoes in Nepal

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32. Cauliflower handling trials integrating best practice and developed technologies to reduce postharvest losses in Nepal

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50. Evaluation of AVRDC advanced tomato lines with long shelf life and processing ability in Cambodia

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