In the last decade or so, almost every sector in our country has witnessed a significant technological overhaul. Indian agriculture has also witnessed a paradigmatic shift with the induction of several technologies finding relevance across food value chains. It is now an indisputable fact that frontier technologies like AI, machine learning and IoT, are transforming the lives of countless agri-stakeholders and agribusinesses across the nation.
Banking on AI to plug post-harvest system gaps
Penetration of deep-tech is disrupting and redefining agriculture, particularly the post-harvest systems.
Let us take wheat as an example. Moisture content is an important parameter to assess the quality and longevity of the commodity. It has a direct impact on price-setting during a transaction.
However, when quality assessment is carried out manually, it is primarily subjective and leads to uncertainty in determining exact quality values, causing losses for both buyers and sellers. Additionally, conventional quality evaluation is time-consuming which leads to delayed trade and increased costs.
Replacing this system with AI-based spectroscopic analysis has proven to be instrumental in eliminating manual-errors by removing subjectivity from the process. The technology enables rapid quality testing, reducing the testing time to less than one minute while ensuring that the various lags in quality reporting no longer occur. Using this technology, various physical and chemical factors that affect food quality can be determined seamlessly and reliably.
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With precise food quality estimation, mapping quality control across the value chain becomes easier.
Traditionally, decision-makers and stakeholders have always relied on individual crop-wise manual expertise for accurately assessing the quality of different products. Spectroscopy can significantly reduce such issues in post-harvest agricultural processes by removing biases, and making the entire operation standardised.
Real-time visibility in the value chain
The agriculture sector is teeming with data-wealth. However, it is buried in paper trails which are unable to provide any significant value to stakeholders.
By digitising food quality, sophisticated AI-based data analytics solutions can help compute this information and generate unique business insights. At the same time, technology can solve one of the most critical issues of food systems in the modern world — traceability.
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From regulators to consumers, everyone wants to know the source of the food right to the farm level. By digitising quality, it becomes easy to map procurement and movement of commodities to trace its journey across all intervals in the value chain. Such a data-driven system can be used to integrate new-age tech to map quality and quantity-specific parameters for commodities such as milk, tea, grains, oilseeds, pulses, and spices in real-time. With such stark visibility, we can establish transparency and, consequently, greater trust among buyers and sellers at every intersection of food trade.
Over time, this database can generate immense value by allowing micro and macro-level assessments to measure productivity and profitability. Use of an AI-driven SaaS platform in agriculture is an overlooked proposition but having a live dashboard with customised parameters to trace, track and monitor food trade in real-time can transform the agriculture sector as we know it today.
Agriculture 4.0 and post-harvest requirements
With growing populations and climate change, the stresses on agriculture systems will increase and create demand for more output even with limited resources. Indian agriculture with its diverse agro-climates has huge growth potential to increase its contribution to world’s food production and trade. In post-harvest space, stakeholders are demanding better logistics and supply chain management, predictive models to boost trade, faster payment processing, better market linkages and efficient storage services along with real-time monitoring and management of commodity collateral.
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This can be effectively addressed by integrating digital technologies with existing systems to phase out legacy issues in agriculture. Not only can this help to prevent food waste, but also curb loss of time, resources, efficiency and trust.
Future is Agritech
Remarkable new-age tech optimisations have not only improved agricultural output but have also helped in successfully addressing persistent legacy issues in post-harvest value chains. This shift is being driven by the emerging agtech sector which is at the forefront of agricultural transformation. This is supported by the significant interest in agtech funding by investors, and the increasing number of agtech start-ups in the last few years. It is estimated that by 2025, Indian agtech companies can receive investments worth $ 30-35 billion.
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Several concerns such as food quality evaluation, supply chain lags and real-time operational visibility are being successfully resolved by agtechs by leveraging cutting-edge technologies to enable effective decision-making in recent times. Most importantly, these pivotal technological interventions are helping to establish greater trust among stakeholders across the value chains at every level.
(The writer is the CEO and Founder, AgNext Technologies)
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