eNAM Integration Helping Farmers Get Better Prices: BITS Goa Professor
The integration of Agricultural Produce Marketing Committee (APMC) mandis with the National Agriculture Market (eNAM) is helping farmers receive better prices for their produce, says R. Leshma Manogna, Assistant Professor at BITS Pilani, Goa.
“The integration of mandis with eNAM is a major benefit for farmers. They can now view real-time prices on the eNAM platform, which prevents middlemen from exploiting them,” Manogna said in an online interview with BusinessLine.
Manogna led a NABARD-sponsored project that collected primary data in Goa to study the price gaps caused by the lack of linkage between mandis and the eNAM platform.
Previously, farmers had little choice but to accept the prices dictated by middlemen—or take their produce back home if the price was too low. But with the rise of smartphones, this is changing.
“Now, if a buyer quotes a low price, farmers can simply refer to the prices on their phones and reject the offer,” she explained. This also helps ensure that farmers don’t sell below the Minimum Support Price (MSP) for certain crops.
Also Read | How many farmers are aware of the Minimum Support Price (MSP)?
Two Main Concerns
Farmers still face two major concerns:
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Not receiving fair prices, even when supplying high-quality produce.
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Middlemen still being part of the system, though their influence is shrinking.
“Our study aimed to help farmers connect directly with buyers and remove middlemen. While that was the original goal of eNAM, it’s taken time to show real results,” Manogna said.
According to her, 60–70% of middlemen have been eliminated. Once a farmer registers with eNAM, they receive price updates directly on their smartphones. The integration has also led to standardized quality assessments of farm produce.
Initially, eNAM wasn’t available everywhere, but things have improved significantly in the last five years. Also Read | Centre to link six online agri portals with eNAM to increase trading volumes
Survey Insights and Research
Manogna and her team submitted a draft report to NABARD, studying price realization across 23 agricultural commodities. They surveyed farmers in the western coastal region, developing over 40 key questions for the analysis.
Manogna has been researching agricultural price forecasting, using traditional models, machine learning, and deep learning on daily wholesale price data from the past 15 years.
She noted that although new financial tools based on agricultural commodities are emerging, prices often don’t reflect true supply and demand due to various government interventions. This sometimes results in farmers or consumers missing out on full benefits.
“eNAM has improved how agricultural markets function. But technologies like machine learning are now playing a key role in better price prediction,” she said.
New Research and AI Models
“While standard statistical models are still in use, machine learning and AI models are outperforming them in terms of accuracy, capturing seasonal patterns, climate changes, and even soil data,” said Manogna.
Her team recently published a paper on a hybrid model for price forecasting and is now incorporating ground-level variables like climate, soil, and trade tariffs.
They experimented with various algorithms and found that recurrent neural networks (RNNs) performed better than traditional artificial neural networks (ANNs) for price prediction. Their study used the last 10–15 years of data, split into 70% for training and 30% for testing.
“Climate change is definitely impacting crop prices. We need solutions that support climate-resilient agriculture, and that’s what we’re working on,” Manogna concluded.
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