The fifth webinar of the Innovation & Science @Bharat series with Pune knowledge Cluster named AI in Agriculture was conducted on 21st May. The event witnessed speakers from industry and academia talk about using AI for agriculture.

Agriculture and its allied sectors account for the biggest source of livelihood in India. Recent policies have called for enabling the implementation of digital technologies at the grass root levels to boost this sector. Artificial Intelligence is playing an essential role in revamping India’s agriculture to make it more robust. A number of agriculture technology start-ups are innovating to implement affordable AI-based solutions to solve issues that are uniquely faced by Indian agriculture. 

The application of AI in agriculture includes its subdomains of crop management, pest management, disease management, monitoring products’ storage, management of soil and irrigation, and prediction of yield.

The session had speakers sharing their AI-based initiatives that are bringing about positive transformations in the way farming is done. Having more sustainable practices is no more a choice; however, a necessity and hence various techniques that would reduce food wastage were also discussed and attracted attendees’ attention.

The session started with Mr. Munish Soni, Head Strategy & Digital, Crop Science division, Bayer India, Bangladesh, and Sri Lanka. With more than two decades of having worked in the field of dairy & agriculture. Munish is passionate about improving the lives of smallholder farmers and bring them to the mainstream by adopting modern practices. He is also a strong supporter of sustainable agriculture and believes that technology and precision agriculture can improve the quality of food, reduce efforts on the farm, make agriculture more predictable and improve farmer profitability.

He shared insights on how Bayer is using AI/ML in managing different dimensions of business and provide sustainable solutions to farmers. Munish elaborated on working in collaboration with Cropin with an objective of integrating remote sensing technologies in monitoring farmer plots @10*10 m resolution to get insights around crop health and yield. 

Munish “a specific problem that Indian agriculture is faced with is that we have too many farms and too many farmers all scattered, which makes it difficult to monitor them.” The AI intervention in areas such as breeding, crop planning, crop management, and supply chain management is the foundation of a more sustainable future of agriculture. 

dThe next speaker in the session was Dr. Irad Ben-Gal, Professor & Head, Tel Aviv University. Irad is the head of the Laboratory for AI, Machine learning, Business, and Data Analytics (LAMBDA) at Tel Aviv University. He held a visiting professor position at Stanford University, teaching “analytics in action” and co-heading the TAU/Stanford “Digital Living 2030” research initiative that focuses on future challenges of modern digital life. Irad is a world-renowned expert in practical machine learning, statistical process control, and predictive analytics with more than 20 years of experience in the field.

Dr. Noam Koenigstein, Assistant Professor (Senior Lecturer), Tel Aviv University, also presented his thoughts on the usage of AI in forecasting grapes quality in commercial storage. He discussed details of the project, which aims to predict the future quality of fresh produce stored in commercial refrigerators. “In the US it is estimated that 31% of the food supply goes to waste which is over 100kg per person annually,” they shared. They explained how the production of the grapes could be made more sustainable and its supply more consistent throughout the year, all by using AI/ ML techniques. The presentation showed that various parameters such as weight, color, firmness of berries and grapes are critical to training the models for better prediction.

Irad and Noam presented their model to improve grapes farming with better predictions and more data collection. They believe AI/ML-based approaches would improve agriculture practices globally in the long run.

The session concluded with a QnA session where the attendees witnessed insightful discussion. The speakers also touched upon the need for having a uniform AI in the agriculture ecosystem. Too many tools and solutions might hinder the progress in the long run. More global regulations and policies will create a more healthy and effective AI intervention in agriculture. 

These initiatives truly bring forth the work going on in the direction of AI and a sustainable food chain. This will encourage more participation from academia, students, organizations, and governing bodies.