Today, efficient and cost-effective sensors as well as high performance computing technologies are looking to transform traditional plant-based agriculture into an efficient cyber-physical system. The easy availability of cheap, deployable, connected sensor technology has created an enormous opportunity to collect vast amount of data at varying spatial and temporal scales at both experimental and production agriculture levels. Therefore, both offline and real-time agricultural analytics that assimilates such heterogeneous data and provides automated, actionable information is a critical needed for sustainable and profitable agriculture.
Data analytics and decision-making for Agriculture has been a long-standing application area. The application of advanced machine learning methods to this critical societal need can be viewed as a transformative extension for the agriculture community. In this workshop, we intend to bring together academic and industrial researchers and practitioners in the fields of machine learning, data science and engineering, plant sciences and agriculture, in the collaborative effort of identifying and discussing major technical challenges and recent results related to machine learning-based approaches. It will feature invited talks, oral/poster presentation of accepted papers, and a panel discussion.
We invite extended 2-page-abstract for oral and/or poster presentations on topics Including but not limited to machine learning applications to plant phenotyping, plant pathology (e.g., disease scouting), plant breeding (e.g., yield prediction) and enabling smart farm management practices. We particularly encourage ML concepts applied to plant breeding, field-based experiments, production agriculture as well as lab based controlled experiments. We also encourage work that result in creating annotated benchmark datasets for ML in agriculture.
Select papers from the workshop will be published in the special issue of journal "Plant Phenomics".
Title:Cyber-Agricultural Systems in Crop Breeding and Production
Title: Plant Phenotyping Technology Leading to Data-driven Agriculture
Title: AI for Agriculture R&D; Insights from Bayer Crop Science
Title: Kubota’s Smart Agriculture and Future Directions
Title:Introduction of robotic tractors expected for upland farming in Hokkaido
JST (UTC +9) 3 July 2023 09:00 ~ 17:00
JST (UTC +9) 4 July 2023 09:00 ~ 17:00
JST (UTC +9) 5 July 09:00 ~ 12:00
|Opening remarks and Welcome Message from CIGR(CIGR nternational Commission of Agricultural and Biosystems Engineering) President||Keynote by
Dr. Ruth Wagner
Dr. Satoshi Iida
Dr. Asheesh K Singh
|Invited Talk by
Dr. Arti Singh
Dr. Scott Chapman
|Invited Talk by
Dr. Bénédicte Fontez
Dr. Iwata Hiroyoshi
|Presentation x N||Presentation x N|
|Presentation x N||Banquet at 農家バル FOODBABY (The bar is operated by Matsuhashi Farm, which has been raising livestock and farming in Sarabetsu Village for about 100 years.)|
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