Main Article Content
This research was aimed to design inspection system of the rice grain phenotypic quality, by using digital images combining machine learning. The research methodology divided into two part were hardware, and software. The research objective was developed rice grain phenotypic quality inspection system prototype. Hardware development was created shooting device for reducing noise, and burden for improving image quality before importing images into the process. And created geometric reference ruler to define the object size on the image, set to width of 0.5 centimeters, length of 1.5 centimeters. Software development was to created system to check the rice grain phenotype quality by using digital images combined with machines learning for classifying rice grain quality group according to the Thai jasmine rice standard product criteria under the Ministry of Commerce 2016. The research found that, the classification between the full rice grain and the stomach egg rice grain with only a small amount of egg contents was only characteristic that makes the discriminant characteristics of both naked eye specialist and the system designed.
Article Accepting Policy
The editorial board of Thai-Nichi Institute of Technology is pleased to receive articles from lecturers and experts in the fields of business administration, languages, engineering and technology written in Thai or English. The academic work submitted for publication must not be published in any other publication before and must not be under consideration of other journal submissions. Therefore, those interested in participating in the dissemination of work and knowledge can submit their article to the editorial board for further submission to the screening committee to consider publishing in the journal. The articles that can be published include solely research articles. Interested persons can prepare their articles by reviewing recommendations for article authors.
Copyright infringement is solely the responsibility of the author(s) of the article. Articles that have been published must be screened and reviewed for quality from qualified experts approved by the editorial board.
The text that appears within each article published in this research journal is a personal opinion of each author, nothing related to Thai-Nichi Institute of Technology, and other faculty members in the institution in any way. Responsibilities and accuracy for the content of each article are owned by each author. If there is any mistake, each author will be responsible for his/her own article(s).
The editorial board reserves the right not to bring any content, views or comments of articles in the Journal of Thai-Nichi Institute of Technology to publish before receiving permission from the authorized author(s) in writing. The published work is the copyright of the Journal of Thai-Nichi Institute of Technology.
 The rice trader, “10th The Rice Trader World Rice Conference.” [Online]. Available: https://thericetrader.com/conferences/2018-wrc-hanoi/worlds-best-rice/. [Accessed: 14-Nov-2018].
 Thai PBS News, "Thai Jasmine Rice 105 get the best taste of rice in the world.” (In Thai). [Online]. Available: https://news.thaipbs.or.th/content/267574. [Accessed: 9-Nov-2018].
 THAIBIOTECH.INFO. “What is Phenotype?.” (In Thai). [Online]. Available: https://www.thaibiotech.info/what-is-phenotype.php. [Accessed: 5-Feb-2018].
 Committee drafts strategic Foreign Agriculture Ministry of Agriculture and Cooperatives, Strategic Foreign Agriculture Ministry of Agriculture and Cooperatives 2017-2021. (In Thai). Bangkok: Office of Agricultural Economics, 2017.
 Export Commodity Standards Act, Subject: Standard product Thai Jasmine Rice and standard for Thai Jasmine Rice (Issue 3) 2016 Page 5, book 133, special episode 243 d, Bangkok: Ministry of Commerce, 2016.
 V. D. Daygon et al., “Understanding the Jasmine phenotype of rice through metabolite profiling and sensory evaluation,” Metabolomics, vol. 12, no. 4, pp. 63, Mar. 2016.
 S. Tilley and H. J. Rosenblatt, Systems Analysis and Design, 11thed. Boston, MA: Cengage Learning, 2016.
 O. Jitpakde. Digital Image processing. (In Thai). Bangkok: Sakhonkit Printing & Media, 2009.
 “Machine Learning & Supervised, Method combination of variables.” [Online]. Available: https://media.licdn.com/dms/image/C4E12AQGPze 4iPMbjAA/articleinline_imageshrink_1000_1488/0?e=2125872000&v=beta&t=HS40LIm4NrA7nINDDthjoXlpgVbNPQUmH9wPZ1xnlaM. [Accessed: 5-Feb-2018].
 S. Tilley and H. J. Rosenblatt, Systems Analysis and Design, 11th ed. Boston, MA: Cengage Learning, 2016.
 S. Adulkasem, J. Preechasuk, and W. Adulkasem, “A System Prototype for Accurate Measurement Size of Object in X-ray Image,” (In Thai). The Journal of KMUTNB, Vol. 22, No. 1, pp. 90-98, 2012.
 K. Tanwong, P. Suksawang, and Y. Punsawad, “Using Digital Image to Classify Phenotype of the Rice Grain Quality under Agricultural Standards Act.” in The 22nd International Computer Science and Engineering Conference (ICSEC) 2018. Chiang Mai, Thailand, pp. 79-82, 2018.
 K. Tanwong, P. Suksawang, and Y. Punsawad, "Development of Rice Grain Phenotype Quality Verification System using Machine Learning," EAU Heritage Journal Science and Technology, Vol. 13, No. 1, pp. 76-94, 2019.