Nagaland identifies 524 ineligible beneficiaries of PM-KISAN scheme

The Nagaland government has identified 524 ineligible beneficiaries of Prime Minister Kisan Samman Nidhi (PM-KISAN) scheme and has started the process to recover Rs 45.08 lakh from them, a senior official of the state Agriculture department said.

After Union Agriculture Minister Narendra Singh Tomar in July 2021 informed Parliament about the existence of bogus farmers in Nagaland, the state Agriculture department initiated measures to identify such farmer, Agriculture Production Commissioner, Nagaland, Y Kikheto Sema told media persons here on Wednesday.

In the process, he said that the department had detected that the list contains names of retired government servants, students and urban dwellers.

The 524 bogus beneficiaries were detected from 10 districts and sub-divisions and their registration have been cancelled, he said.

The department has directed all agriculture officers in the districts and sub-divisions to immediately initiate the recovery and the process is going on, he said, adding that the department has so far recovered more than Rs 5 lakh.

"We have also directed to further identify bogus beneficiaries in all the remaining districts and sub-divisions," he said.

Against detection of bogus beneficiaries, genuine farmers shall be registered/replaced, he said.

Under PM-KISAN, a farmer's welfare scheme, eligible farmers, irrespective of land holding received Rs 6,000 per year from Central Government as income support to meet the farming input expenses.

The fund is transferred by the Union Ministry of Finance directly to the farmers account in three installments.

In Nagaland, PM-KISAN scheme was launched on February 25, 2019 and as on Wednesday, altogether 2,02,113 farmers have received a total amount of Rs 316,12,16,000, he said.

The e-KYC done so far is 1,51,365 which is 74.89 per cent of the total beneficiaries and one of the highest e-KYC verified beneficiaries in the country.

(This story has not been edited by Devdiscourse staff and is auto-generated from a syndicated feed.)