This workshop is supported by JST (Japan), NSF (U.S.A), and USDA-NIFA (U.S.A)

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.

  • Proceedings: Coming soon.
  • Date: JST (UTC +9) Tue, 2 Nov 2021 21:00 ~ JST (UTC +9) Thu, 4 Nov 2021 23:00
  • Venue: online
What's new:

(updated Oct 26, 2021)

Program online! Oct 26, 2021

Submission deadline extended to Oct 15, 2021

Submission will open at Sept 1, 2021

Call for Papers

Target Participants

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.

Guidelines
  • Guidelines for Extended abstract submissions: Up to 2 pages including figures and tables (excluding references). Extended abstract template.
  • Submission Guidelines: Submissions are through Microsoft CMT. If you do not have an Microsoft CMT account, please create one first. If you already have an Microsoft CMT account, please login to your account and enter as an author for MLCAS 2021 by following this link.
  • Guidelines for Poster presentations: Poster Size: A0 (width around 84.1 cm and height around 118.9 cm) or you can use
    poster template (to be released).
Procedure

Comming soon.

Publication of Papers

Select papers from the workshop will be published in the special issue of journal "Plant Phenomics".

Important Dates
  • Submission open: Wednesday, September 1st, 2021
  • Paper (extended abstract) deadline: Friday, October 15th, 2021
  • Decision sent to authors: later in October, 2021
  • Workshop date: November 2nd~4th, 2021

Workshop Organization

Organizing Committee
  • Wei Guo, Assistant Professor, Field Phenomics Laboratory, Graduate School of Agriculture and Life Sciences, The University of Tokyo.
  • Masayuki Hirafuji,Project Professor, Field Phenomics Laboratory, Graduate School of Agriculture and Life Sciences, The University of Tokyo.
  • Seishi Ninomiya, Project Professor, Field Phenomics Laboratory, Graduate School of Agriculture and Life Sciences, The University of Tokyo.
  • Soumik Sarkar, Associate Professor, Mechanical Engineering, Iowa State University.
  • Baskar Ganapathysubramanian, Professor, Mechanical Engineering, Iowa State University
  • Asheesh K. Singh, Professor, Department of Agronomy, Iowa State University.
  • Arti Singh, Assistant Professor, Department of Agronomy, Iowa State University

Keynote Speakers

Click button to see details, click again to hide
alternative
Professor
Tanaka Yuzuru
Bio

Title: Advanced Application Technologies to Boost Big Data Utilization for Multiple-Field Scientific Discovery and Social Problem Solving

alternative
Professor
Ninomiya Seishi
Bio

Title: Long-term Policy of Japan toward Sustainable and Productive Agriculture with Smart Farming

alternative
Professor
George Kantor
Bio

Title: Bringing Robotic Intelligence to the Field: Moving from Perception to Manipulation

alternative
Professor
James Schnable
Bio

Title: Learning to lead the target: plant breeding in an unpredictable world

Program

Day 1-1

JST (UTC +9) Tue, 2 Nov 2021 21:00 ~ 23:00

Day 1-2

JST (UTC +9) Tue, 2 Nov 2021 21:00 ~ 23:00

Day 2-1

JST (UTC +9) Tue, 2 Nov 2021 21:00 ~ 23:00

Day 2-2

JST (UTC +9) Tue, 2 Nov 2021 21:00 ~
Opening remarks and Introduction of communication tools Introduction of communication tools Farmers Conversation Free discussion on slack
Keynote by
Prof. Yuzuru TANAKA
Prof. Seishi NINOMIYA
Keynote by
Prof. George KANTOR
Prof. James SCHNABLE
Presentations from competition winners
Long Presentation x 4 Long Presentation x 4 Award ceremony for competition winners
Flash talk x 8 Flash talk x 10 Closing remarks

Proceedings

Time zone:
01

Haozhou Wang,Tang Li,Erika Nishida,Yuya Fukano,Yoichiro Kato,Wei Guo

Graduate School of Agricultural and Life Sciences, The University of Tokyo;

01

Haozhou Wang,Tang Li,Erika Nishida,Yuya Fukano,Yoichiro Kato,Wei Guo

Graduate School of Agricultural and Life Sciences, The University of Tokyo;Graduate School of Agricultural and Life Sciences, The University of Tokyo;Graduate School of Agricultural and Life Sciences, The University of Tokyo;Graduate School of Agricultural and Life Sciences, The University of Tokyo;Graduate School of Agricultural and Life Sciences, The University of Tokyo;Graduate School of Agricultural and Life Sciences, The University of Tokyo

01

Haozhou Wang,Tang Li,Erika Nishida,Yuya Fukano,Yoichiro Kato,Wei Guo

Graduate School of Agricultural and Life Sciences, The University of Tokyo;Graduate School of Agricultural and Life Sciences, The University of Tokyo;Graduate School of Agricultural and Life Sciences, The University of Tokyo;Graduate School of Agricultural and Life Sciences, The University of Tokyo;Graduate School of Agricultural and Life Sciences, The University of Tokyo;Graduate School of Agricultural and Life Sciences, The University of Tokyo

Competition

Topic

Crop Yield Prediction Integrating Genotype and Weather Variables Using Machine Learning . The competition details for participation are provided here.

Important Dates
  • Sep 3: Start Date
  • Sep 18: Team composition Deadline
  • Oct 25: Final Submission Deadline
  • Oct 28: Announcement of Results
Award amounts
  • 1st prize : $2000
  • 2nd prize : $1500
  • 3rd prize: $1000
Datasets

Datasets will be made available here.

Disclaimer

Paricipant teams must finalize their team members before the composition deadline is on September 18. teams joining after September 18 cannot change their team member composition during the competition phase. Prizes will be awarded to the winning teams. Funds will be paid in the most efficient manner, typically a check to winners living in the US with payment to each team member (up to 5 participants maximum). The team contact can suggest the distribution for the team members. If a team has more than five participants, five or fewer participants need to be identified to receive the prize money. For teams outside the US, prize money will be wired to a single individual representing the team. We will need full wire instructions in an appropriate format. Please note that there will be a wire fee on the receiving end of the transaction based on the recipient's bank/financial institution. At this time, we are unable to send wires to Iran, Cuba, North Korea, or Syria, therefore no prizes will be awarded there. Please note that prizes are tax reportable in the United States. Tax forms are required for payment recipients. US Citizens or permanent US residents: Form W9 including social security number and Foreign individuals: Form W-8BEN

Contacts

For details regarding the competition, please contact us:

  • Tryambak Gangopadhyay, PhD candidate, Mechanical Engineering, Iowa State University: tryambak@iastate.edu
  • Koushik Nagasubramanian, PhD candidate, Electrical Engineering, Iowa State University: koushikn@iastate.edu