Context:

Centre to invest Rs 6,000 crore in smart farming with AI, drones, and data to boost crop yields.

What is precision farming?

Precision farming is also known as site-specific crop management. It merges data collection and remote sensing with Global Positioning Systems (GPS) and Geographic Information Systems (GIS) to allow farmers to respond to in-field variability with their crop management.
Farmers can get extremely precise in their crop management while not sacrificing crop yields.

Advantages:

Reduced nutrient runoff:

By making more precise decisions, farmers can manage their inputs and nutrients more carefully.
This results in less wasted fertiliser and nutrient runoff.

Reduced Herbicides and fungicides usage:

By using remote sensing, farmers can know exactly where disease and pest pressures are high, applying chemicals only where they are needed rather than the entire field, reducing the volume of herbicides and fungicides they use.

Effective production management:

By collecting and attaching data to crop production, starting at the seed production stage and following a crop until it reaches a consumer’s table, agribusinesses can create traceability and accountability that reveal further insights they can manage for even more efficient production.

Efficient resource utilisation:

Smart and precision agriculture maximises the use of resources like water, fertilisers and pesticides to increase production quality and quantity.
Efficient resource use will prevent farmers from the vagaries of climate change and other uncertainties, besides ensuring sustainable farming.

Increased profits:

Farmers can increase yields and thus profits with the same amount of inputs or achieve an equivalent yield with fewer inputs.

Challenges in adopting precision farming in India:

High up-front acquisition costs: Acquisition costs for the latest technologies can be prohibitive for farmers with limited resources or access to capital.
Farm data sharing and ownership issues: Concerns regarding farm data sharing and ownership can pose obstacles to the widespread use of AI in agriculture.
Lack of standards: An absence of uniform standards can hamper interoperability between different precision agriculture technologies.
Lack of technical know-how: Farmers generally are not trained to use precision tools, interpret data, and implement the findings in their agricultural practices.
Digital Divide:
- - Merely 23.4% of adult Indians living in rural areas lack even the most basic knowledge of digital literacy, according to a 2022 World Bank survey.
  - Farmers find it challenging to use digital tools efficiently, traverse online platforms, and obtain important information due to their lack of digital fluency.

Government Initiatives to Promote Precision Farming:

Budgetary allocation:

The Centre is planning to earmark Rs 6,000 crore to promote precision farming, a modern approach that uses smart technology such as the Internet of Things, Artificial Intelligence, drones and data analytics to boost production through maximal use of resources while minimising environmental impact.

Smart Precision Horticulture Programme

The Union Ministry of Agriculture is planning a Smart Precision Horticulture Programme under the existing Mission for Integrated Development of Horticulture (MIDH) scheme.
It will cover 15,000 acres of land in five years from 2024-25 to 2028-29 and is expected to benefit about 60,000 farmers.

Agriculture Infrastructure Fund (AIF)

At present, the Agriculture Infrastructure Fund (AIF), launched during Covid-19, has provisions for financing infrastructure projects for smart and precision agriculture.
Under AIF, individual farmers, as well as farmers’ communities such as Farmer Producer Organizations, Primary Agricultural Credit Societies and SHGs, are eligible for loans with interest subvention of 3% for using technological solutions in farm practices.
These practices include farm/ harvest automation; purchase of drones, putting up specialised sensors on the field; use of blockchain and AI in agriculture; remote sensing and the Internet of Things (IoT).

International Collaborations:

Centre is also considering collaborating with the Netherlands and Israel, where tech-based modern farming solutions are being used, through Centres of Excellences (CoEs).
The number of CoEs is likely to be 100 in the next five years.
Under the Indo-Israel Agriculture Project, 32 CoEs have already been set up across 14 states.

Precision Farming Development Centres (PFDCs)

The Centre has also set up 22 Precision Farming Development Centres (PFDCs) across the country to test new technologies and modify them according to local needs.
These 22 PFDCs are located across State/Central Agricultural Universities, ICAR Institutes and IITs in TN, Karnataka, Madhya Pradesh, Odisha, Rajasthan, Haryana, Telangana, West Bengal, Ladakh, UP, Punjab, Gujarat, Uttrakhand, Maharashtra, Chhattisgarh, Jharkhand, Bihar, Himachal Pradesh, Kerala, Manipur and Assam.

Support to states:

The funds are released to states/UTs for projects involving the use of AI and machine learning, under schemes like the National e-Governance Plan in Agriculture.

Other initiatives:

The National Mission on Sustainable Agriculture (NMSA), Pradhan Mantri Krishi Sinchayee Yojana (PMKSY), etc focus on water-use efficiency and soil health monitoring.
Recently announced a Digital Public Infrastructure (DPI) for agriculture aims to provide farmers with access to technology and information.

Way ahead:

Widespread Adoption of IoT and AI: There should be integration of Internet of Things (IoT) devices and artificial intelligence in farming practices by involving private players and also training should be imparted to farmers.
Government Support and Subsidies: Increased governmental policies and subsidies for precision farming technologies could drive adoption. Programs like the Pradhan Mantri Krishi Sinchai Yojana aim to promote efficient water use, and similar initiatives can expand to cover precision tools and training for farmers.
Enhanced Training and Education: Training centres and online platforms for farmers to learn about precision farming techniques that can facilitate knowledge transfer should be established.
Collaboration with Agritech Startups: Partnerships between traditional agricultural sectors and agritech startups can enhance innovation. Initiatives that support startups in developing affordable precision farming solutions could lead to broader access and implementation.
Sustainability and Climate Resilience: Future precision farming practices will increasingly focus on sustainable methods to cope with climate change.

Case studies of Private Players Involved in precesion farming in India

Aibono, a Bangalore-based startup, uses AI and IoT to provide farmers with real-time insights about soil health and crop conditions. By 2030, it aims to help thousands of farmers optimize yields through data-driven decisions.

Ninjacart, a supply chain startup, partners with farmers to implement precision farming technologies. This collaboration helps improve yield and reduces wastage, benefiting both farmers and consumers.

Tata Trusts is promoting sustainable agriculture through initiatives that integrate precision farming techniques with climate-resilient practices, such as rainwater harvesting and organic farming. Their projects aim to reduce greenhouse gas emissions by promoting these methods in various states.

For further study on the agreement refer the following article:

NBFC and Its types.

Nidhi companies, Nidhi Vs NBFC

Sources:

https://indianexpress.com/article/india/govt-plans-rs-6000-cr-scheme-to-boost-precision-farming-9571571/

https://www.sciencedirect.com/topics/earth-and-planetary-sciences/precision-agriculture#:~:text=Precision%20agriculture%20(PA)%20is%20the,of%20fertilizers%20and%20irrigation%20processes.

https://www.ceew.in/publications/sustainable-agriculture-india/precision-farming

PRACTICE QUESTION

Q.Critically examine importance precision farming in enhancing agricultural productivity India. Also analyse the challenges in adopting precision farming by the framers. (250 words)