| Autor: |
Chen Chen, Lin Wang, Huimin Liu, Jing Liu, Wanyu Xu, Mengzhen Huang, Ningning Gou, Chu Wang, Haikun Bai, Gengjie Jia, Tana Wuyun |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
Horticultural Plant Journal, Vol 10, Iss 2, Pp 387-397 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2468-0141 |
| DOI: |
10.1016/j.hpj.2023.02.007 |
| Popis: |
Apricot has a long history of cultivation and has many varieties and types. The traditional variety identification methods are time-consuming and labor-consuming, posing grand challenges to apricot resource management. Tool development in this regard will help researchers quickly identify variety information. This study photographed apricot fruits outdoors and indoors and constructed a dataset that can precisely classify the fruits using a U-net model (F-score: 99%), which helps to obtain the fruit's size, shape, and color features. Meanwhile, a variety search engine was constructed, which can search and identify variety from the database according to the above features. Besides, a mobile and web application (ApricotView) was developed, and the construction mode can be also applied to other varieties of fruit trees. Additionally, we have collected four difficult-to-identify seed datasets and used the VGG16 model for training, with an accuracy of 97%, which provided an important basis for ApricotView. To address the difficulties in data collection bottlenecking apricot phenomics research, we developed the first apricot database platform of its kind (ApricotDIAP, http://apricotdiap.com/) to accumulate, manage, and publicize scientific data of apricot. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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