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Current IssueEditorial BoardOnline First Articles
Agricultural Science Digest
Print ISSN: 0253-150X
Online ISSN: 0976-0547
NASS Rating
5.52
SJR
0.176
CiteScore
0.357

Chief Editor:
Arvind kumar
Rani Lakshmi Bai Central Agricultural Uni., Jhansi, U.P., INDIA
Frequency:Bi-monthly
Indexing:
BIOSIS Preview, Biological Abstracts, Elsevier (Scopus and Embase), AGRICOLA, Google Scholar, CrossR...

Research Article

Agricultural Science Digest, volume 40 issue 4 (december 2020) : 376-381

Potato Classification by using Ultrasonic Sensor with LabVIEW

Abdullah Beyaz, Dilara Gerdan
1Ankara University, Faculty of Agriculture, Department of Agricultural Machinery and Technologies Engineering, 06110, Diskapi, Ankara, Turkey.
Cite article:- Beyaz Abdullah, Gerdan Dilara (2020). Potato Classification by using Ultrasonic Sensor with LabVIEW. Agricultural Science Digest. 40(4): 376-381. doi: 10.18805/ag.D-173.

ABSTRACT

Background: Agricultural product classification is an essential and widely working issue in the agriculture industry. There is a lot of work to be done in this area and the agriculture industry is looking for new applications. The reason is that the software and hardware Technologies are always developing, and the latest technologies giving better results parallel to these developments. Also, the costs of the new technologies are decreasing with the help of low-cost sensor and device technologies. New technique and technology usage also directly related to classification efficiency. The primary data on agriculture are agricultural products, so these technologies and techniques use for agricultural production. 
Methods: The primary data on agriculture are agricultural products, because of this reason, this research aimed to make ultrasonic sensor measurements with the help of a software which is developed in LabVIEW platform for potato classifications and showing the efficiency of the method for the potato classification, which has different sizes.
Result: According to the regression coefficient results, the regression between caliper length measurement (CL) and static ultrasonic sensor length measurement (SUL) found as 95.5%, the regression between caliper length measurement (CL) and dynamic ultrasonic sensor length measurement (DUL) found as 86.9%, the regression between static ultrasonic sensor length measurement (SUL) and dynamic ultrasonic sensor length measurement (DUL) found as 87.9% for potato classification.

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