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Description / Abstract
Submitted to the Department of Mathematics and Computer Science in partial fulfillment of the requirements for the degree of Bachelor of Science/Arts
Idaho farmers face the challenge of hiring manual laborers during the harvesting season due to the shortage of workers. This challenge creates financial problems, one of which is that many unharvested fruits are left in the orchards at the end of the agricultural season. Predicting fruit yield count early in the season allows farmers to have a general idea of how many manual laborers to acquire before harvesting. The use of a mobile application with integrated image processing tools can assist in predicting fruit yield before harvest. This project developed a farmer-friendly app for mobile devices to count blossoms on apple trees. Results from field evaluation demonstrate a positive correlation between the number of blossoms detected and the final fruit count. The following method of predicting fruit yield count displays a promising approach with time efficiency and simplicity.
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Download as a PDF: Prediction of Fruit Yield using Blossom Counting App
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Copyright Notes
This material is used by permission of the rightsholder in accordance with the terms of the relevant content release. As a user, you have permission to use this content and download a copy for non-commercial use only. Downloading multiple quantities of this resource is expressly forbidden.
KeywordsMobile application, Fruit yield estimation, Image processing
Degree AwardedBachelor of Science/Arts
Awarding InstitutionNorthwest Nazarene University
Committee MembersDuke Bulanon, Barry L. Myers
Supervisor or ChairKevin McCarty
Peer Reviewed?No
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NNU Computer Science Theses
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- Physical Sciences and Mathematics
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