Application of Artificial Neural Network and Non-Destructive CT scan Test in Estimating the Amount of Pear Bruise Due To External Loads

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

AZADBAKHT MOHSEN; Vahedi Torshizi Mohammad

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Research and Innovation in Food Science and Technology Year:2019 | Volume:8 | Issue:2 Page(s): 177-188

Download Full-Text

Persian Verion

View:

582

Download:

Cites:

Information Journal Paper

Title

Application of Artificial Neural Network and Non-Destructive CT scan Test in Estimating the Amount of Pear Bruise Due To External Loads

Author(s)

AZADBAKHT MOHSEN | Vahedi Torshizi Mohammad | Issue Writer Certificate

Keywords

LoadingQ1

Neural NetworkQ1

Nondestructive MethodQ1

Pear BruisingQ1

Abstract

Pear damage is one of the main causes of the loss of fruit quality. Bruises occur during dynamic and quasi-static Loading, which causes damage to the healthy tissue of the fruit. In this research, pears were placed under quasi-static Loading (thin edge and wide edge) and dynamic Loading. Then they were stored in 5, 10 and 15 days and after each storage period, using the CT-Scan non-destructive technique the bruise percentage was estimated. In this study, multi-layer perceptron artificial Neural Network (MLP) by 2 hidden layers and 3, 5, 7 and 9 neurons hidden layers was selected for modeling of Loading force and storage period to predict bruise rate. The highest R2 values for training and testing for quasi-static Loading of thin edge and wide edge in a 9-Neural Network were training Thinedge= 0. 91, test Thin-edge =0. 99 and training Wide-edge=0. 95, test Wide-edge =0. 99. For the dynamic Loading of a network with 3 neurons in the hidden layer has the highest value (training Wideedge= 0. 98, test Wide-edge =0. 99). For learning (9 neurons) quasi-static Loading thin edge (7 neurons) quasi-static Loading wide edge and dynamic Loading (7 neurons) have been the best network. According to the results obtained for R2, RMSE and learning cycle, it can be said that the Neural Network has the ability to predict the bruise percentage to an acceptable level for pears.

Cites

No record.

References

No record.

Cite

APA: Copy

AZADBAKHT, MOHSEN, & Vahedi Torshizi, Mohammad. (2019). Application of Artificial Neural Network and Non-Destructive CT scan Test in Estimating the Amount of Pear Bruise Due To External Loads. JOURNAL OF RESEARCH AND INNOVATION IN FOOD SCIENCE AND TECHNOLOGY, 8(2 ), 177-188. SID. https://sid.ir/paper/234061/en

Vancouver: Copy

AZADBAKHT MOHSEN, Vahedi Torshizi Mohammad. Application of Artificial Neural Network and Non-Destructive CT scan Test in Estimating the Amount of Pear Bruise Due To External Loads. JOURNAL OF RESEARCH AND INNOVATION IN FOOD SCIENCE AND TECHNOLOGY[Internet]. 2019;8(2 ):177-188. Available from: https://sid.ir/paper/234061/en

IEEE: Copy

MOHSEN AZADBAKHT, and Mohammad Vahedi Torshizi, “Application of Artificial Neural Network and Non-Destructive CT scan Test in Estimating the Amount of Pear Bruise Due To External Loads,” JOURNAL OF RESEARCH AND INNOVATION IN FOOD SCIENCE AND TECHNOLOGY, vol. 8, no. 2 , pp. 177–188, 2019, [Online]. Available: https://sid.ir/paper/234061/en

Related Journal Papers