Your VCCA in India

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Type. data.org project

Funding. This project is funded by the MasterCard Center for Inclusive GrowthThe Rockefeller Foundation.

Duration. 2 years (2020-2022)

Collaborations. BASE, and local service providers in India.

Contact. Thijs Defraeye (principal investigator).

Project background. 

In India, a third of all fresh produce is lost in post-harvest due to improper storage facilities, unreliable electricity, poor distribution, and poor processing for farmers. Most perishable food such as fruits and vegetables are produced in remote areas, with long distances between the farm and the market.  Due to the lack of access to a cooling facility for the fresh produce at the farm-gate, the quality of the fresh produce that is sold in the nearest market is often quite low and also at a very low price. In fact, 68% of the crops in India are sold below market prices and there is up to a 90% deficit of cold storage facilities in the country. Off-grid cooling as a service is available nowadays, however, many of them still rely on paper methods for keeping the inventory and pricing, and there is little information passed on to the farmer about the quality of their products or about the market prices. To help solve this complex problem, we aim to develop an open-access data-science mobile application called Coldtivate, for both small-holder farmers and cooling service providers in India. This application will serve as a digital inventory and also as an assistant to help farmers decide when and where to sell their produce in order to increase their profit and reduce food loss.

Publications. 

Li D., Gajardo J., Volpi M., Defraeye T. (2022), Using machine learning to generate an open-access cropland map from satellite images time series in the Indian Himalayan Region, preprint DOI.

 - Interactive map, and its documentation



Mobile app to help smallholders in India. Image: BASE

Funding agency:


Staff:

 Daniel Onwude
 Scientist
 (Coordinator/Machine learning)


 

 Chandrima Shrivastava

 PhD student
 (Physics-based digital twins)




 Kanaha Shoji

 Research assistant
 (Data collection and physics-based digital twins)

 
 

 Joaquin Gajardo Castillo
 Scientist
 (Machine learning and Mobile app development)


 

 Jörg Schemminger
 PhD student
 (Mobile app development)



 Manuel Knott 
 PhD student
 (Machine learning)



Yuyan Lu
Master student
(Machine learning)




 Danya Li
 Master student
 (Machine learning)



 Seraina Schudel
 Scientific collaborator
 (Data collection and outreach)

 

 

Sélène Ledain
Master student