What’s letting down the farmer?
After saving Kishori Prajapati from committing suicide, the residents of <g data-gr-id="105">Majhguan</g> Kalan village did something unimaginable. Living in the drought-prone region of Bundelkhand, they knew it very well how difficult it is to get compensation for crop damages. They knew the officials would not visit the village to assess the loss. So the next day, when they discovered the hail was still intact in the fields, they <g data-gr-id="106">heaped</g> those in a tractor trolley and marched to the district headquarters of Chhatarpur. It had an impact. Three days later the patwari, or village accountant, reached the village with his team. When Down To Earth visited the tehsil office in the last week of April, officials were disbursing compensation to affected farmers of <g data-gr-id="107">Majhguan</g> Kalan and Jaitpur—the only two villages in Chhatapur that were hit by the freak hailstorm of March 30. Yet a sense of betrayal was palpable among the farmers.
While reasons for such freak weather are riddled with meteorological mysteries, the ways in which the government calculates the damage and disburses compensation are not simple either.
As per the damage report prepared by the patwari of Chhatarpur, 128 of the 294 farmers in <g data-gr-id="110">Majhguan</g> Kalan faced over 50 per cent crop loss; 55 suffered crop loss between 25 and 50 percent; and the remaining 111 suffered less than 25 percent loss. As per the state government norms, small farmers (owning less than two ha) who faced 50 percent crop damage would receive Rs 15,000 per ha, while big farmers (who own more than two ha) would get Rs 11,000 per ha. Those who lost 25 to 50 percent of crops would receive between Rs 9,000 and Rs 6,500 per ha, depending on the farm size. Those who lost 25 percent crop are not eligible for compensation.
Farmers in <g data-gr-id="84">Majhguan</g> Kalan, however, claim that most families in the village lost 70 to 90 percent of the crop and complain that leaving out 111 families without any compensation is unfair. “The entire village was covered with hail. So how could the damage be different for different farms,” asks Arjun Kushwaha, a farmer.
Farmers also complain that the compensation is meager. On an average, a farmer in <g data-gr-id="85">Majhguan</g> Kalan harvests 3,500 kg of wheat from a hectare. Selling the produce at the minimum Rs 1,200 per 100 kg, he would earn Rs 42,000. Yet the maximum compensation they receive is Rs 15,000 per ha, or 70 percent less than the market value of the crop lost.
“Compensation should be calculated based on the income a crop generates for a farmer,” says Dayanand Punia, secretary of the All India Kisan Sabha (AIKS), Haryana chapter. On an average, a farmer harvests 4,000 kg of wheat or 2,000 kg of mustard from one hectare. Going by the government procurement rate of Rs 1,450 for 100 kg of wheat and Rs 3,200 per 100 kg of mustard, he would earn between Rs 58,000 and Rs 64,000 from a hectare. So, AIKS has demanded that the government should increase the compensation amount to Rs 50,000 per hectare for all the crops.
Increasing compensation rate would not help farmers until crop loss is assessed correctly.
Unfortunately, the assessment solely depends on the whims and fancies of only one official: the patwari. “They still follow the manual assessment procedure introduced in the 11th century for revenue collection,” says <g data-gr-id="87">Jagveer</g> Rawat of Lala Lajpat Rai University of Veterinary and Animal Sciences, Hissar. Patwaris have no knowledge of crop varieties and how temperature and humidity impact crops, nor do they follow modern scientific techniques for assessing crop loss, Rawat says.
“There is no mechanism to gauge crop loss due to natural calamities,” admits Nand Kishore, a patwari in Mathura district of Uttar Pradesh, one of the worst affected districts of the state during the hailstorm this year. “We rely on our years of experience and individual skill to determine the loss.
Information provided by our contacts in villages also comes handy,” says Kishore, who is busy making sense of a 60-year-old village map made of fabric. Dense with rectangular markings, each representing a landholding, the map is the sole guide for him to figure out whose farm has to be marked for compensation. He has a problem: landholdings have fragmented at least hundred times in the past 60 years and the official record hardly takes note of that. Besides, on an average, a patwari has to assess 5,000-10,000 ha. With multiple landholdings and ownerships, this would take more than a month to physically verify the land and ascertain the damage. In this situation, it’s an uphill task for any person to assess crop pattern, let alone crop loss. So, the crop loss assessment is pure guess work. Based on this guess work of the patwari, the Union Ministry of Agriculture decides crop damage and disburses compensation. No wonder then there is always contention on compensation and damage assessment.
Such archaic way of crop loss assessment also affects insurance claims. As per the government norms, banks must provide crop insurance to all the farmers who avail Kisan Credit Card (KCC) benefits. But most farmers complain that they do not receive the damages in case of crop losses. “The insurance is not meant to protect the farmer,” says S SRaju, principal scientist with the National Centre for Agricultural Economics and Policy Research (NCAP), Delhi. “Banks treat insurance premium as collateral security to the sanctioned credit. In case of crop loss, they directly deduct the credit money from the compensation money paid by insurance companies.”
The 70th round of survey by the National Sample Survey Organisation (NSSO) shows that more than half of agriculture households are in debt, but only four per cent of them have crop insurance coverage. This is despite the government running three flagship schemes for crop insurance.
“All the three schemes have their own limitations which do not encourage farmers to go for crop insurance,” explains Gopal Naik, who teaches agro-economy at the Indian Institute of Management, Bengaluru. The National Agriculture Insurance Scheme (NAIS), introduced in 1999, is ideal for small farmers as the premium is low. But it offers coverage against damages caused only between sowing and harvest, explains P C Sudhakar of Alternative Investments and Credits Limited (AICL). In 2007, the government introduced Weather Based Crop Insurance Scheme (WBCIS) and Modified National Agriculture Insurance Scheme (MNAIS), widening the coverage against damages caused during pre-sowing and post-harvesting period, and due to weather-related anomaly. But banks charge a high premium for such schemes, and mostly cash farmers choose these schemes. “The issue with WBCIS is more complex as we do not have enough weather stations and infrastructure at the panchayat level,” says Raju.
These schemes have another flaw: they are based on the average crop loss reported in an area rather than the crop loss faced by individual farmers. Worse, these areas are demarcated as per administrative units, usually a block, a circle or tehsil, and not as per agro-climatic zones. This makes crop loss assessment difficult as administrative units may experience different weather conditions. “In urban areas, insurance companies have plans to cover individuals, houses, and automobiles, but crop loss is assessed at the block level. Then why would a farmer buy crop insurance?” asks agriculture analyst Devinder Sharma.
“We do not have the infrastructure to take insurance to the panchayat or individual level,” says Surya Swaroop Saxena of AICL. Even the private insurance companies’ Down To Earth spoke to showed reluctance in insuring individual farmers. Naik says companies are reluctant because India does not have good data system of landholdings. M Mahadevappa, former Vice Chancellor of Agriculture University Dharwad, Karnataka, agrees. “The government should adopt new technologies like remote sensing to accurately assess crop damage and good data system of plots so that farmers can be insured at the individual level,” he suggests.
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