Agristack

In Context

  • India’s largest agri-trading marketplace Agribazaar has recently announced that it will be offering a ‘remote sensing crop model’ to farmers.

What is a remote sensing crop model?

  • Remote sensing refers to the process where scientific data and observations are collected about an object without needing to be at the same location physically. 
  • This exercise is often carried out through a variety of instruments, including measuring an object’s reflected and emitted radiation through a satellite.

Significance

  • Remote sensing in agriculture refers to the process of collecting information about soil and the land. 
  • Through the Remote Sensing model, scientists and agricultural experts are able to measure characteristics like nutrient deficiencies, water deficiency or surplus, weed infestations, insect damage, hail damage, wind damage, herbicide damage, plant populations and presence of diseases.
  • The collection of this data allows for the easy implementation of precision farming. 
    • Precision farming refers to a farming management concept where inputs are carefully chosen to increase average yields.
    • Precision farming leads to a higher average yield per unit of land when compared to traditional farming while also using available resources and inputs judiciously.

What is Agristack?

  • About:
    • The AgriStack is a collection of technologies and digital databases proposed by the Central Government focusing on India’s farmers and the agricultural sector.
    • The central government has claimed that these new databases are being built to primarily tackle issues such as poor access to credit and wastage in the agricultural supply chain.
  • Features:
    • Under AgriStack’, the government aims to provide ‘required data sets’ of farmers’ personal information to Microsoft to develop a farmer interface for ‘smart and well-organized agriculture’.
    • The digital repository will aid precise targeting of subsidies, services and policies.
    • Under the programme, each farmer of the country will get what is being called an FID, or a farmers’ ID, linked to land records to uniquely identify them. India has 140 million operational farmland holdings.

Benefits

  • Information flow: Agristack will provide all information about farmers and their farming easily to corporations who look at farmers as a consumer base. It will give data to machinery companies or fintech companies and to those for whom farmers were suppliers like the food industry, garment industry, etc.
  • Marketing Network: FPOs had become the new data collection points as well as market channels for the seed and agrochemical industry and Agri commodity traders. This data can be sold by the companies to private input dealers and input companies to aid their marketing network.
  • Increasing Commercialisation: The formation of ‘Agristack’ also implies the commercialisation of agriculture extension activities as they will shift into a digital and private sphere.
  • Provides Indemnity: There is a non-disclosure agreement in the MoU, there is also a clause on ‘limitation of liability which essentially provides indemnity for breach of contract.

Challenges

  • Information asymmetry: This can lead to information asymmetry, tilted towards the technology companies. This can further exploit farmers, especially small and marginal ones.
  • Data Sharing: In all the MoUs, there are provisions under which the agriculture ministry will enter into a data-sharing agreement with the private companies of the likes of Amazon, Microsoft and Patanjali. This can lead to a breach of privacy.
  • Data privacy: The project was being implemented in the absence of data protection legislation. It might end up being an exercise where private data processing entities may know more about a farmer’s land than the farmer himself. Without the safeguards, private entities would be able to exploit farmers’ data to whatever extent they wish to.
  • Financial exploitation: Once Fintech companies are able to collect granular data about the farmers’ operations, they may offer them exorbitant rates of interest precisely when they would be in the direst need of credit.
  • No fixed selection criteria: The government has now invited more technology / agritech players for collaboration, even though there is no information on the process or criteria of selecting the first five companies.
  • Exclusions: Making land records the basis for farmer databases would mean excluding tenant farmers, sharecroppers, women and agricultural labourers. This could also exclude those associated with allied activities such as fishing, beekeeping, poultry, animal husbandry, pastoralism, sericulture, vermiculture and agroforestry from accessing these services on the digital platform because they may not own agricultural land.

Suggestions

  • The government should make further decisions after running various pilot projects and consulting results with other stakeholders.
  • The potential in data and technology in empowering farmers could be realised with a balanced flow of information.
  • The State governments have to make efforts to mitigate their differences over land ownership with private firms working on pilot projects. There is a need for effective cooperation among state governments and private firms.

Source: Tribune

 
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