Editorial published in the February 2026 issue of "Agriculture & Industry Survey" magazine
Why farmers require early signals on prices and demand
Even basic charts illustrating how crop prices fluctuate across seasons and regions can influence behaviour—turning guesswork into judgement.
As a farmer, I sow a crop months before harvest, investing labour, capital, water, fertiliser, and hope. Yet, at harvest time—the moment when any business expects clarity—I do not know what price I will receive. The market determines it for me, often overnight, often arbitrarily, and nearly always outside my control.
In a country that proudly speaks of data, digital platforms, and artificial intelligence, this fundamental uncertainty faced by farmers is striking. Is agriculture still a gamble, even in an age overflowing with information?
To be fair, farmers are not entirely without signals. Information does exist in rural India—but much of it travels by word of mouth, trader talk, local gossip, and informal networks. A neighbour says prices are good. A trader suggests demand may rise. Someone returning from the mandi shares what he heard that morning. Like much else in rural India, market information spreads socially, not scientifically.
The issue is not the lack of information, but the absence of reliable, verifiable, data-backed market signals. What farmers receive today are fragments of intelligence. What they need are clear signals—before sowing, not after harvest.
Growing first, discovering prices later
In most sectors of the economy, producers set a price, launch a product, and then discover whether the market accepts it. If sales are slow, production can be adjusted. If unsold stock remains, it can be stored, discounted, or repurposed.
Agriculture does not operate this way.
Once a crop is planted, the decision is fixed for months. Capital is committed. Land is dedicated. When harvest arrives, many crops—especially perishables—must be sold immediately, regardless of price. There is no option to “wait and see.” This is what makes price uncertainty in agriculture fundamentally different from uncertainty in other sectors.
Islands of certainty in Indian agriculture
India does have pockets where farmers benefit from some degree of price or buyer certainty.
Wheat and paddy farmers in Punjab and Haryana benefit from Minimum Support Prices backed by assured procurement. Sugarcane farmers supply mills where, although the final price may be settled later, a guaranteed buyer exists. In horticulture and plantation crops—coconut, arecanut, spices, fruits, vegetables—many farmers can pre-sell their produce to traders or processors, often with a known price range or buyback agreement.
These systems are not perfect, but they share one key feature: farmers are not producing blindly.
However, for the vast majority of Indian farmers, especially those growing cereals, pulses, oilseeds, vegetables, and other open-market crops, decisions are made without any reliable indication of demand or price. They cultivate first and discover the market later—often when it is too late to respond.
The missing link: advance demand–supply signals
What Indian agriculture lacks is not markets, mandis, or traders. It is advance market intelligence.
Farmers are not asking the government to fix prices for every crop. They are seeking guidance—signals that help them decide what to grow and how much to produce. Even imperfect signals are better than none.
With today’s computing power, it is entirely feasible to develop systems that answer three basic questions before sowing:
How much of crop X is likely to be needed in the upcoming season?
How much of crop X is already being produced, region by region?
Based on historical data, what price range is plausible under similar conditions?
This is not about controlling markets. It is about informing them.
Lessons from e-NAM: technology alone is insufficient
India has already tried market integration through platforms such as the e-National Agriculture Market (e-NAM), launched in 2016 to facilitate pan-India electronic trading of agricultural commodities.
A 2017 research study by Sudha Narayanan, Nidhi Aggarwal, and Sargam Jain, examining Karnataka’s early market reforms, offers valuable lessons. Read more: https://bit.ly/3YCD4L0
Karnataka’s reforms yielded clear benefits from automation—faster auctions, fewer disputes, reduced waiting times for farmers, and lower transaction costs. But the deeper promise of market unification—new buyers, cross-mandi bidding, transparent price discovery—largely failed to materialise.
Traders preferred visual inspection over remote assaying. Farmers distrusted grading systems, fearing lower prices. Commission agents resisted reforms that weakened their role as aggregators, financiers, and risk-bearers. E-payments disrupted established credit relationships.
The key lesson is this: agricultural marketing is not merely a technological challenge. It is an institutional system shaped by trust, incentives, and long-standing relationships.
A change in approach: intelligence before trading
Expecting every farmer and trader to transact on a national platform may be premature.
But utilising the power of the state to collect, analyse, and transparently publish demand–supply intelligence is both practical and urgently needed.
Imagine starting with a pilot—one crop, one region—where data on acreage, yields, consumption, processing capacity, exports, imports, and price history are combined. Data science tools could then generate seasonal outlooks—not fixed predictions, but informed estimates.
Once this information is made public, markets will respond naturally. Traders will move where opportunity exists. Processors will signal requirements. Logistics will follow volume flows. Farmers will make more informed decisions.
A new generation of farmer leaders needed
For this transformation to occur, India requires a new generation of farmer leaders—individuals who understand farming realities, appreciate the power of computing and data, and can translate ideas into action.
These leaders must do more than propose technically sound solutions. To gain traction, they must contextualise these issues within India’s socio-political realities. Policy change does not happen in a vacuum. We are still a nation where reforms need to demonstrate clear benefits—whether that wins electoral support or enhances popularity.
This calls for leaders who can bridge three worlds simultaneously: the field, the spreadsheet, and the political arena. People who understand the everyday risks faced by farmers, the opportunities offered by technology, and the nuances of India’s political system. Without this translation layer, even the best ideas risk remaining theoretical or pilot-stage experiments.
How agriculture universities can support
Agricultural universities have a vital role in building this bridge. Professors should actively identify students capable of working at the intersection of agriculture, economics, and data science, and support PhD research that examines a single crop from sowing to market—covering weather, yields, mandi arrivals, consumption, and prices.
Such focused research can gradually evolve into practical forecasting and decision-support tools that farmers, traders, and policymakers can genuinely utilise. Over time, this body of work can form the backbone of reliable demand–supply intelligence systems.
Institutions like the Indian Council of Agricultural Research, state agricultural universities, and the Ministry of Agriculture are well-placed to lead this effort—provided bright minds within these organisations are given the freedom and support to innovate, collaborate, and operate beyond rigid silos.
How banks can assist
Local banks are another crucial yet often overlooked link in the agricultural decision-making chain.
Farmers frequently approach banks for crop loans and working capital. These moments are not just financial transactions; they are decision moments.
If simple demand–supply dashboards were available at bank branches, loan discussions could be grounded in market realities. Farmers would see which crops are in rising demand and which face oversupply. Banks, in turn, would lend with better information, reducing risks.
Over time, this alignment between credit and market intelligence could lessen distress, improve repayment rates, and make agricultural lending more sustainable for both farmers and banks.
If share markets feature charts, why shouldn’t farmers?
Investors rely on charts—price histories, trends, volumes. They accept risk but do so with information. There is no reason why farmers shouldn’t have access to similar tools.
Even basic charts showing crop price fluctuations across seasons and regions can influence behaviour. They turn guesswork into judgement.
Price guarantees are emergency measures—not long-term solutions.
Price guarantees and procurement have their role. In times of crisis, they are vital—like emergency treatment in a hospital. But no sector can always depend on emergency measures.
Long-term prosperity for farmers will only be sustainable if they can cultivate crops in demand. This requires better information, not just intervention.
Agriculture is too vital to leave to chance. With the data, computing power, and institutional experience India already possesses, farmers can be supported to move from blind risk to informed decision-making. The question is no longer whether this is achievable—but whether we are prepared to act.
Editorial published in the February 2026 issue of "Agriculture & Industry Survey" magazine
Why farmers require early signals on prices and demand
Even basic charts illustrating how crop prices fluctuate across seasons and regions can influence behaviour—turning guesswork into judgement.
As a farmer, I sow a crop months before harvest, investing labour, capital, water, fertiliser, and hope. Yet, at harvest time—the moment when any business expects clarity—I do not know what price I will receive. The market determines it for me, often overnight, often arbitrarily, and nearly always outside my control.
In a country that proudly speaks of data, digital platforms, and artificial intelligence, this fundamental uncertainty faced by farmers is striking. Is agriculture still a gamble, even in an age overflowing with information?
To be fair, farmers are not entirely without signals. Information does exist in rural India—but much of it travels by word of mouth, trader talk, local gossip, and informal networks. A neighbour says prices are good. A trader suggests demand may rise. Someone returning from the mandi shares what he heard that morning. Like much else in rural India, market information spreads socially, not scientifically.
The issue is not the lack of information, but the absence of reliable, verifiable, data-backed market signals. What farmers receive today are fragments of intelligence. What they need are clear signals—before sowing, not after harvest.
Growing first, discovering prices later
In most sectors of the economy, producers set a price, launch a product, and then discover whether the market accepts it. If sales are slow, production can be adjusted. If unsold stock remains, it can be stored, discounted, or repurposed.
Agriculture does not operate this way.
Once a crop is planted, the decision is fixed for months. Capital is committed. Land is dedicated. When harvest arrives, many crops—especially perishables—must be sold immediately, regardless of price. There is no option to “wait and see.” This is what makes price uncertainty in agriculture fundamentally different from uncertainty in other sectors.
Islands of certainty in Indian agriculture
India does have pockets where farmers benefit from some degree of price or buyer certainty.
Wheat and paddy farmers in Punjab and Haryana benefit from Minimum Support Prices backed by assured procurement. Sugarcane farmers supply mills where, although the final price may be settled later, a guaranteed buyer exists. In horticulture and plantation crops—coconut, arecanut, spices, fruits, vegetables—many farmers can pre-sell their produce to traders or processors, often with a known price range or buyback agreement.
These systems are not perfect, but they share one key feature: farmers are not producing blindly.
However, for the vast majority of Indian farmers, especially those growing cereals, pulses, oilseeds, vegetables, and other open-market crops, decisions are made without any reliable indication of demand or price. They cultivate first and discover the market later—often when it is too late to respond.
The missing link: advance demand–supply signals
What Indian agriculture lacks is not markets, mandis, or traders. It is advance market intelligence.
Farmers are not asking the government to fix prices for every crop. They are seeking guidance—signals that help them decide what to grow and how much to produce. Even imperfect signals are better than none.
With today’s computing power, it is entirely feasible to develop systems that answer three basic questions before sowing:
How much of crop X is likely to be needed in the upcoming season?
How much of crop X is already being produced, region by region?
Based on historical data, what price range is plausible under similar conditions?
This is not about controlling markets. It is about informing them.
Lessons from e-NAM: technology alone is insufficient
India has already tried market integration through platforms such as the e-National Agriculture Market (e-NAM), launched in 2016 to facilitate pan-India electronic trading of agricultural commodities.
A 2017 research study by Sudha Narayanan, Nidhi Aggarwal, and Sargam Jain, examining Karnataka’s early market reforms, offers valuable lessons. Read more: https://bit.ly/3YCD4L0
Karnataka’s reforms yielded clear benefits from automation—faster auctions, fewer disputes, reduced waiting times for farmers, and lower transaction costs. But the deeper promise of market unification—new buyers, cross-mandi bidding, transparent price discovery—largely failed to materialise.
Traders preferred visual inspection over remote assaying. Farmers distrusted grading systems, fearing lower prices. Commission agents resisted reforms that weakened their role as aggregators, financiers, and risk-bearers. E-payments disrupted established credit relationships.
The key lesson is this: agricultural marketing is not merely a technological challenge. It is an institutional system shaped by trust, incentives, and long-standing relationships.
A change in approach: intelligence before trading
Expecting every farmer and trader to transact on a national platform may be premature.
But utilising the power of the state to collect, analyse, and transparently publish demand–supply intelligence is both practical and urgently needed.
Imagine starting with a pilot—one crop, one region—where data on acreage, yields, consumption, processing capacity, exports, imports, and price history are combined. Data science tools could then generate seasonal outlooks—not fixed predictions, but informed estimates.
Once this information is made public, markets will respond naturally. Traders will move where opportunity exists. Processors will signal requirements. Logistics will follow volume flows. Farmers will make more informed decisions.
A new generation of farmer leaders needed
For this transformation to occur, India requires a new generation of farmer leaders—individuals who understand farming realities, appreciate the power of computing and data, and can translate ideas into action.
These leaders must do more than propose technically sound solutions. To gain traction, they must contextualise these issues within India’s socio-political realities. Policy change does not happen in a vacuum. We are still a nation where reforms need to demonstrate clear benefits—whether that wins electoral support or enhances popularity.
This calls for leaders who can bridge three worlds simultaneously: the field, the spreadsheet, and the political arena. People who understand the everyday risks faced by farmers, the opportunities offered by technology, and the nuances of India’s political system. Without this translation layer, even the best ideas risk remaining theoretical or pilot-stage experiments.
How agriculture universities can support
Agricultural universities have a vital role in building this bridge. Professors should actively identify students capable of working at the intersection of agriculture, economics, and data science, and support PhD research that examines a single crop from sowing to market—covering weather, yields, mandi arrivals, consumption, and prices.
Such focused research can gradually evolve into practical forecasting and decision-support tools that farmers, traders, and policymakers can genuinely utilise. Over time, this body of work can form the backbone of reliable demand–supply intelligence systems.
Institutions like the Indian Council of Agricultural Research, state agricultural universities, and the Ministry of Agriculture are well-placed to lead this effort—provided bright minds within these organisations are given the freedom and support to innovate, collaborate, and operate beyond rigid silos.
How banks can assist
Local banks are another crucial yet often overlooked link in the agricultural decision-making chain.
Farmers frequently approach banks for crop loans and working capital. These moments are not just financial transactions; they are decision moments.
If simple demand–supply dashboards were available at bank branches, loan discussions could be grounded in market realities. Farmers would see which crops are in rising demand and which face oversupply. Banks, in turn, would lend with better information, reducing risks.
Over time, this alignment between credit and market intelligence could lessen distress, improve repayment rates, and make agricultural lending more sustainable for both farmers and banks.
If share markets feature charts, why shouldn’t farmers?
Investors rely on charts—price histories, trends, volumes. They accept risk but do so with information. There is no reason why farmers shouldn’t have access to similar tools.
Even basic charts showing crop price fluctuations across seasons and regions can influence behaviour. They turn guesswork into judgement.
Price guarantees are emergency measures—not long-term solutions.
Price guarantees and procurement have their role. In times of crisis, they are vital—like emergency treatment in a hospital. But no sector can always depend on emergency measures.
Long-term prosperity for farmers will only be sustainable if they can cultivate crops in demand. This requires better information, not just intervention.
Agriculture is too vital to leave to chance. With the data, computing power, and institutional experience India already possesses, farmers can be supported to move from blind risk to informed decision-making. The question is no longer whether this is achievable—but whether we are prepared to act.
Editorial published in the February 2026 issue of "Agriculture & Industry Survey" magazine