Zobrazeno 1 - 10
of 2 268
pro vyhledávání: '"yield estimation"'
Autor:
Liguo Jiang, Hanhui Jiang, Xudong Jing, Haojie Dang, Rui Li, Jinyong Chen, Yaqoob Majeed, Ramesh Sahni, Longsheng Fu
Publikováno v:
Artificial Intelligence in Agriculture, Vol 13, Iss , Pp 117-127 (2024)
Accurate watermelon yield estimation is crucial to the agricultural value chain, as it guides the allocation of agricultural resources as well as facilitates inventory and logistics planning. The conventional method of watermelon yield estimation rel
Externí odkaz:
https://doaj.org/article/88fc89968922491b9bd2c240d08e9a5d
Autor:
B. Ambrus, G. Teschner, A.J. Kovács, M. Neményi, L. Helyes, Z. Pék, S. Takács, T. Alahmad, A. Nyéki
Publikováno v:
Heliyon, Vol 10, Iss 20, Pp e37997- (2024)
The aim of this study was to estimate field-grown tomato yield (weight) and quantity of tomatoes using a self-developed robot and digital single lens reflex (DSLR) camera pictures. The authors suggest a new approach to predicting tomato yield that is
Externí odkaz:
https://doaj.org/article/f430a883807e4e87bfc90d5d49d1e70b
Publikováno v:
Crops, Vol 4, Iss 2, Pp 115-133 (2024)
Remote sensing technology currently facilitates the monitoring of crop development, enabling detailed analysis and monitoring throughout the crop’s growing stages. This research analyzed the winter wheat growth dynamics of experimental plots at the
Externí odkaz:
https://doaj.org/article/a0ec30978bbc4a9ab9016cd4098ded66
Autor:
Jian Lu, Hongkun Fu, Xuhui Tang, Zhao Liu, Jujian Huang, Wenlong Zou, Hui Chen, Yue Sun, Xiangyu Ning, Jian Li
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-19 (2024)
Abstract Accurately estimating large-area crop yields, especially for soybeans, is essential for addressing global food security challenges. This study introduces a deep learning framework that focuses on precise county-level soybean yield estimation
Externí odkaz:
https://doaj.org/article/b553cc3485c24f2a9f801d3181e13ba6
Akademický článek
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Akademický článek
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Autor:
Andrea Marcone, Giorgio Impollonia, Michele Croci, Henri Blandinières, Niccolò Pellegrini, Stefano Amaducci
Publikováno v:
Smart Agricultural Technology, Vol 8, Iss , Pp 100513- (2024)
Remote sensing and machine learning are widely used to estimate crop yield. The use of these technologies for yield estimation of bulbous vegetables is challenging because the yield is underground and can't be directly monitored by remote sensing ima
Externí odkaz:
https://doaj.org/article/1b11e85ce0a64e88a904372ff5dc73bf
Autor:
Mengli Zhang, Wei Chen, Pan Gao, Yongquan Li, Fei Tan, Yuan Zhang, Shiwei Ruan, Peng Xing, Li Guo
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
IntroductionCotton yield estimation is crucial in the agricultural process, where the accuracy of boll detection during the flocculation period significantly influences yield estimations in cotton fields. Unmanned Aerial Vehicles (UAVs) are frequentl
Externí odkaz:
https://doaj.org/article/533632f10f5a4634b4d2e9a10c528d30
Publikováno v:
IEEE Access, Vol 12, Pp 157854-157871 (2024)
In the culturally and economically vital date palm sector of the Arab world, precise assessment of fruit maturity, type, and disease is crucial for optimizing yield, quality, and palm health. This work pioneers a novel paradigm: machine learning (ML)
Externí odkaz:
https://doaj.org/article/5893f9d00ce04ec99acf4f06449c6544
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 19067-19077 (2024)
The global food supply system is under increasing pressure due to population growth and more extreme climate events. Developing forecast models for accurate prediction of crop yields is helpful for early warning of food crises. Amid the different env
Externí odkaz:
https://doaj.org/article/ace66ee6489349b8b12d0b3c0cd10221