Three-Dimensional Imaging in Agriculture: Challenges and Advancements in the Phenotyping of Japanese Quinces in Latvia

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dc.contributor.authorKaufmane, Edīte
dc.contributor.authorEdelmers, Edgars
dc.contributor.authorSudars, Kaspars
dc.contributor.authorNamatevs, Ivars
dc.contributor.authorNikulins, Arturs
dc.contributor.authorStrautiņa, Sarmīte
dc.contributor.authorKalniņa, Ieva
dc.contributor.authorPeter, Astile
dc.contributor.institutionMedical Education Technology Centre
dc.date.accessioned2023-12-19T13:15:02Z
dc.date.available2023-12-19T13:15:02Z
dc.date.issued2023-12-17
dc.descriptionPublisher Copyright: © 2023 by the authors.
dc.description.abstractThis study presents an innovative approach to fruit measurement using 3D imaging, focusing on Japanese quince (Chaenomeles japonica) cultivated in Latvia. The research consisted of two phases: manual measurements of fruit parameters (length and width) using a calliper and 3D imaging using an algorithm based on k-nearest neighbors (k-NN), the ingeniously designed “Imaginary Square” method, and object projection analysis. Our results revealed discrepancies between manual measurements and 3D imaging data, highlighting challenges in the precision and accuracy of 3D imaging techniques. The study identified two primary constraints: variability in fruit positioning on the scanning platform and difficulties in distinguishing individual fruits in close proximity. These limitations underscore the need for improved algorithmic capabilities to handle diverse spatial orientations and proximities. Our findings emphasize the importance of refining 3D scanning techniques for better reliability and accuracy in agricultural applications. Enhancements in image processing, depth perception algorithms, and machine learning models are crucial for effective implementation in diverse agricultural scenarios. This research not only contributes to the scientific understanding of 3D imaging in horticulture but also underscores its potential and limitations in advancing sustainable and productive farming practices.en
dc.description.statusPeer reviewed
dc.format.extent4728574
dc.identifier.citationKaufmane, E, Edelmers, E, Sudars, K, Namatevs, I, Nikulins, A, Strautiņa, S, Kalniņa, I & Peter, A 2023, 'Three-Dimensional Imaging in Agriculture: Challenges and Advancements in the Phenotyping of Japanese Quinces in Latvia', Horticulturae, vol. 9, no. 12, 1347. https://doi.org/10.3390/horticulturae9121347
dc.identifier.doi10.3390/horticulturae9121347
dc.identifier.issn2311-7524
dc.identifier.urihttps://dspace.rsu.lv/jspui/handle/123456789/15062
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85180492652&partnerID=8YFLogxK
dc.language.isoeng
dc.relation.ispartofHorticulturae
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectChaenomeles japonica
dc.subjectgermplasm
dc.subjectgenotypes
dc.subjectfruit size
dc.subjectcharacterization
dc.subjectvolumetric data
dc.subjectpoint cloud
dc.subject1.2 Computer and information sciences
dc.subject1.6 Biological sciences
dc.subject4.4 Agricultural biotechnology
dc.subject1.1. Scientific article indexed in Web of Science and/or Scopus database
dc.titleThree-Dimensional Imaging in Agriculture: Challenges and Advancements in the Phenotyping of Japanese Quinces in Latviaen
dc.type/dk/atira/pure/researchoutput/researchoutputtypes/contributiontojournal/article

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