دورية أكاديمية
أعرض في EDS

A Preliminary Method for Tracking In-Season Grapevine Cluster Closure Using Image Segmentation and Image Thresholding

التفاصيل البيبلوغرافية
العنوان: A Preliminary Method for Tracking In-Season Grapevine Cluster Closure Using Image Segmentation and Image Thresholding
المؤلفون: Manushi Trivedi, Yuwei Zhou, Jonathan Hyun Moon, James Meyers, Yu Jiang, Guoyu Lu, Justine Vanden Heuvel
المصدر: Australian Journal of Grape and Wine Research, Vol 2023 (2023)
بيانات النشر: Hindawi-Wiley, 2023.
سنة النشر: 2023
المجموعة: LCC:Plant culture
LCC:Special industries and trades
مصطلحات موضوعية: Plant culture, SB1-1110, Special industries and trades, HD9000-9999
الوصف: Mapping and monitoring cluster morphology provides insights for disease risk assessment, quality control in wine production, and understanding environmental influences on cluster shape. During the progression of grapevine morphology, cluster closure (CC) (also called bunch closure) is the stage when berries touch one another. This study used mobile phone images to develop a direct quantification method for tracking CC in three grapevine cultivars (Riesling, Pinot gris, and Cabernet Franc). A total of 809 cluster images from fruit set to veraison were analyzed using two image segmentation methods: (i) a Pyramid Scene Parsing Network (PSPNet) to extract cluster boundaries and (ii) Otsu’s image thresholding method to calculate % CC based on gaps between the berries. PSPNet produced high accuracy (mean accuracy = 0.98, mean intersection over union (mIoU) = 0.95) with mIoU > 0.90 for both cluster and noncluster classes. Otsu’s thresholding method resulted in
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1755-0238
Relation: https://doaj.org/toc/1755-0238
DOI: 10.1155/2023/3923839
URL الوصول: https://doaj.org/article/2af08b1233fa424da8dc9ee18836a520
رقم الأكسشن: edsdoj.2af08b1233fa424da8dc9ee18836a520
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:17550238
DOI:10.1155/2023/3923839