Union Agriculture Ministry Urges Punjab to Plan Ahead for Stubble Fire Control

The Union agriculture ministry has urged Punjab to develop an advance plan to manage stubble fires during the upcoming October-November harvest season. This directive follows a meeting in New Delhi between Agriculture Secretary Manoj Ahuja, Punjab officials led by Special Chief Secretary KAP Sinha, and Punjab Agricultural University (PAU) Vice-Chancellor SS Gosal.

Despite a 26% reduction in farm fire incidents last year—down from 49,922 in 2022 to 36,623—the area affected by stubble burning increased from 15 lakh acres to 19 lakh acres. Approximately 20 million tonnes of paddy straw are generated during the harvest, including 3.3 million tonnes from the premium aromatic basmati variety. The state managed 11.5 million tonnes through in-situ methods and 4.67 million tonnes by ex-situ measures.

The ministry emphasized the need for early planning to mitigate air pollution from stubble burning, which contributes to severe smog over northern India, particularly the National Capital Region. Punjab was asked to submit a detailed action plan, including applications from farmers for subsidized machinery for in-situ stubble management. So far, 11,000 farmers have applied, with a target of 25,000-26,000 applications by June 20.

In the meeting, experts from the International Rice Research Institute (IRRI) were also present to guide research on rice varieties. The state had previously sought a ₹500 crore grant from the Centre for stubble management, with the Union ministry committing to fund 60% of the costs.

Since 2018, the Centre has funded the Crop Residue Management (CRM) program, transitioning last year to a 60:40 cost-sharing model. In the last season, the Centre contributed ₹350 crore, and the state added ₹140 crore. A total of ₹1,370 crore has been allocated from 2018-2022 for machinery purchases, with 1.17 lakh machines distributed. For the upcoming season, Punjab plans to increase the supply of in-situ management machines and potentially enhance ex-situ measures based on need.