Artificial Intelligence (AI) is prone to play a key function in relieving India’s agriculture sector from its nerve-racking enter circumstances, catalysing a shift in direction of data-driven farming, mentioned a brand new Nasscom-EY report on Thursday.
With elevated authorities assist, rising agritech suppliers, burgeoning start-up ecosystem, and rising AI adoption among the many rural farming inhabitants, a powerful transformation impetus is underway, mentioned the report titled “Leveraging AI to maximise India’s agriculture output.”
Data consolidation (each at macro and real-time farm-level), lack of infrastructure consciousness in information processing, and its availability have been among the key challenges confronted by the sector at present.
In addition to this, ignorance on agricultural inputs particular to the produce, entry to high quality seeds, lack of sufficient mechanisation and irrigation infrastructure, shortage of farmer capital, frequent illness outbreak, and insufficient storage services are the opposite worth chain challenges confronted by the sector.
“The Indian agriculture sector can utilise the potential of AI’s transformative capabilities through effective data practices,” Debjani Ghosh, President, Nasscom, mentioned in a press release.
“The Netherlands is a stellar example of effective AI adoption in agriculture. With just a small arable land, the country has become the world’s 2nd largest exporter of agricultural products by value leveraging technology and AI.
“For India to realise the full potential of AI, a coalition of government, industries, and startups in providing necessary infrastructure and policy support, enabling AI innovation across sectors, and mentoring and providing financial support to startups is imperative,” she mentioned.
Leveraging macro in addition to farm-level information collected by way of sensors may assist maximise yields and optimise the usage of accessible sources, mentioned the report.
Several AI-led use instances, comparable to precision agriculture and farm administration, agricultural robots, automated weeding, crop high quality and readiness identification, pest prediction and prevention, livestock monitoring and administration, crop yield estimation, and so on. can resolve bettering farm productiveness.
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