Council on Energy, Environment and Water Integrated | International | Independent

CEEW Explains: Why are Punjab’s Farmers Averse to Using Machinery and Continue Stubble Burning?
Most farmers have stayed away from these machines for reasons ranging from inadequate training to higher operating costs

Malyaban Ghosh
03 November 2021

Every winter, parts of north India, including the national capital New Delhi, remain engulfed in a thick blanket of smog. The burning of agricultural residue in the neighbouring Punjab and Haryana is being perceived as one of the contributing factors to this recurring problem. This year will be no different, as climate scientists have already warned about a rapid deterioration in air quality in the coming weeks.

The centre and the state governments hoped mass adoption of crop residue management (CRM) machines by farmers will help reduce instances of crop residue burning. To their dismay, most farmers have stayed away from these machines for reasons ranging from inadequate training to higher operating costs to social hierarchy. CEEW Explains elucidates the reasons behind this poor uptake and the probable solutions which can make these machines an attractive proposition for farmers.

Did CRM machines help reduce instances of crop residue burning?

In 2018, the Government of India launched the Promotion of Agricultural Mechanization scheme to push the adoption of in-situ CRM machines - Happy and Super Seeder - among farmers through subsidies. By 2020, Punjab had established 19,834 Custom Hiring Centres and deployed 76,626 CRMs, which included 13,316 Happy Seeders and 17,697 Super Seeders. The existing stock of machines can be used to manage nearly 17 lakh hectares which correspond to 66 per cent of the non-basmati farmland sown in 2021. In reality, though most machines remain underutilised. For instance, in 2020, farmers in 12 out of 22 districts in Punjab burnt crop residue on more than 50 per cent of their land. However, all these districts had a stock of CRM machines that could be used to manage more than 40–50 per cent of the non-basmati farms.

Why are farmers not adopting CRM machines?

Most farmers in Punjab aren’t trained adequately to use these machines and are apprehensive of the impact on the wheat crop yields sowed by these seeders. These two factors are the primary reason behind the low utilisation rate of these machines. High private ownership – 37 per cent – has also led to limited usage of these machines. The rental model – CHC – has also failed to win over the farmers due to delays in the availability of machines and inefficient logistics management. The awareness of the FARMS app - launched to popularise the CHC model and create an online marketplace for renting CRM machines - has been quite poor among the farmers.

What has been the impact of the fuel price increase?

Substantial increase in diesel prices over the last two years could prove to be an impediment for farmers since fuel-related costs account for 25% of the total operating cost of CRM machines. The operating cost of a Happy Seeder machine has risen by 8 per cent compared to 2019, while the same for a Super Seeder has jumped by 5 per cent compared to 2020.

What are the possible solutions available for the short- and long-term?

Governments - both centre and state - should provide cash incentives to compensate for the high operating cost of the CRM machines as high fuel cost is proving to be an impediment. Public campaigns should be launched to educate farmers about the benefits of using these machines through the rental model. Promoting the FARMS app to familiarise farmers with its interface and services could help drive adoption among the farming community.

Existing stock of Happy and Super Seeders can manage up to 17 lakh hectares that correspond to 66 per cent of area sown under non-basmati in 2021, if deployed at full capacity.

Source: Why Paddy Stubble Continues to be Burnt in Punjab? Meeting Challenges with Solutions.

This Explainer has been curated by Malyaban Ghosh, Communications Specialist at CEEW, with extensive inputs from L.S. Kurinji, Programme Associate at CEEW.

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