Neural network in rice grading: How Malaysian rice can be graded?
Rice grading plays an important role in the determination of rice quality and its subsequent price in the market.It is an important process applied in the rice production industry with the purpose ensuring that the rice produced for the market meets the quality requirements of consumer. Two importan...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2016
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| Subjects: | |
| Online Access: | https://repo.uum.edu.my/id/eprint/23521/1/ICT4T2016%20252%20256.pdf |
| _version_ | 1825804938563813376 |
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| author | Che Pa, Noraziah Yusoff, Nooraini Ahmad, Nor Hayati |
| author_facet | Che Pa, Noraziah Yusoff, Nooraini Ahmad, Nor Hayati |
| author_sort | Che Pa, Noraziah |
| collection | UUM |
| description | Rice grading plays an important role in the determination of rice quality and its subsequent price in the market.It is an important process applied in the rice production industry with the purpose ensuring that the rice produced for the market meets the quality requirements of consumer. Two important aspects that need to be considered in determining rice grades; grading technique and factors to be used for grading (usually referred as rice attributes).This article proposes how Malaysian rice can be graded. Twenty one features are proposed to be used.Combination of extensive literature review and series of interview were used in determining the features. A Neural Network (NN) model is proposed to be used with the identified features.For evaluation purpose, expert review has been carried out.The proposed model is believed to be beneficial not only for BERNAS but also to other researchers in the same domain. BERNAS can use the NN model to facilitate their inspection for rice quality.The model can be used as guidance or reference for similar grading works. |
| first_indexed | 2024-07-04T06:23:48Z |
| format | Conference or Workshop Item |
| id | uum-23521 |
| institution | Universiti Utara Malaysia |
| language | English |
| last_indexed | 2024-07-04T06:23:48Z |
| publishDate | 2016 |
| record_format | eprints |
| spelling | uum-235212020-11-02T01:31:28Z https://repo.uum.edu.my/id/eprint/23521/ Neural network in rice grading: How Malaysian rice can be graded? Che Pa, Noraziah Yusoff, Nooraini Ahmad, Nor Hayati QA75 Electronic computers. Computer science Rice grading plays an important role in the determination of rice quality and its subsequent price in the market.It is an important process applied in the rice production industry with the purpose ensuring that the rice produced for the market meets the quality requirements of consumer. Two important aspects that need to be considered in determining rice grades; grading technique and factors to be used for grading (usually referred as rice attributes).This article proposes how Malaysian rice can be graded. Twenty one features are proposed to be used.Combination of extensive literature review and series of interview were used in determining the features. A Neural Network (NN) model is proposed to be used with the identified features.For evaluation purpose, expert review has been carried out.The proposed model is believed to be beneficial not only for BERNAS but also to other researchers in the same domain. BERNAS can use the NN model to facilitate their inspection for rice quality.The model can be used as guidance or reference for similar grading works. 2016-04-05 Conference or Workshop Item NonPeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/23521/1/ICT4T2016%20252%20256.pdf Che Pa, Noraziah and Yusoff, Nooraini and Ahmad, Nor Hayati (2016) Neural network in rice grading: How Malaysian rice can be graded? In: International Conference on ICT for Transformation 2016, 05-07 April 2016, Center for postgraduate UMS Sabah Malaysia. (Unpublished) |
| spellingShingle | QA75 Electronic computers. Computer science Che Pa, Noraziah Yusoff, Nooraini Ahmad, Nor Hayati Neural network in rice grading: How Malaysian rice can be graded? |
| title | Neural network in rice grading: How Malaysian rice can be graded? |
| title_full | Neural network in rice grading: How Malaysian rice can be graded? |
| title_fullStr | Neural network in rice grading: How Malaysian rice can be graded? |
| title_full_unstemmed | Neural network in rice grading: How Malaysian rice can be graded? |
| title_short | Neural network in rice grading: How Malaysian rice can be graded? |
| title_sort | neural network in rice grading how malaysian rice can be graded |
| topic | QA75 Electronic computers. Computer science |
| url | https://repo.uum.edu.my/id/eprint/23521/1/ICT4T2016%20252%20256.pdf |
| work_keys_str_mv | AT chepanoraziah neuralnetworkinricegradinghowmalaysianricecanbegraded AT yusoffnooraini neuralnetworkinricegradinghowmalaysianricecanbegraded AT ahmadnorhayati neuralnetworkinricegradinghowmalaysianricecanbegraded |