In the last decade or so, almost every industry in our country has undergone a major technological overhaul. Indian agriculture has also experienced a paradigm shift with the introduction of several technologies that find their relevance in food value chains. It is now an indisputable fact that advanced technologies like AI, machine learning and IoT, are transforming the lives of countless agro-actors and agro-industries across the country.
Leveraging AI to Address Gaps in the Post-Harvest System
The penetration of advanced technologies is disrupting and redefining agriculture, especially post-harvest systems.
Take the example of wheat. The water content is an important parameter to assess the quality and longevity of the product. It has a direct impact on the pricing of a transaction.
However, when the quality assessment is done manually, it is mostly subjective and leads to uncertainty in determining the exact quality values, resulting in losses for both buyers and sellers. In addition, conventional quality assessment takes time, resulting in delayed trade and increased costs.
Replacing this system with AI-based spectroscopic analysis has been found to be essential in eliminating manual errors by removing subjectivity from the process. The technology enables rapid quality testing, reducing testing time to less than a minute while ensuring that the various delays in quality reporting no longer occur. Using this technology, various physical and chemical factors that affect the quality of food can be determined transparently and reliably.
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With accurate estimation of food quality, mapping quality control along the value chain becomes easier.
Traditionally, decision makers and stakeholders have relied on individual manual crop expertise to accurately assess the quality of different products. Spectroscopy can drastically reduce these problems in post-harvest agricultural processes by removing bias and standardizing the entire operation.
Real-time visibility into the value chain
The agricultural sector abounds in wealth of data. However, it is buried in written records that are unable to provide meaningful value to stakeholders.
By digitizing food quality, sophisticated AI-powered data analysis solutions can help calculate this information and generate unique business insights. At the same time, technology can solve one of the most critical problems in food systems in the modern world: traceability.
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From regulators to consumers, everyone wants to know the source of food down to the farm level. By digitizing quality, it becomes easy to map the supply and movement of commodities to track their journey through all intervals of the value chain. Such a data-driven system can be used to integrate next-generation technology to map in real time parameters specific to the quality and quantity of products such as milk, tea, grains, oilseeds, legumes and spices. With such visibility, we can establish transparency and hence greater trust among buyers and sellers at every intersection of the food trade.
Over time, this database can generate immense value by enabling assessments at the micro and macro levels to measure productivity and profitability. Using an AI-powered SaaS platform in agriculture is a neglected proposition, but having a live dashboard with custom metrics to track, track and monitor the food trade in real time. can transform the agricultural sector as we know it today.
Agriculture 4.0 and post-harvest requirements
With population growth and climate change, pressures on farming systems will increase and create demand for more production, even with limited resources. Indian agriculture with its diverse agro-climates has enormous growth potential to increase its contribution to the world’s food production and trade. In the post-harvest space, stakeholders demand better logistics and supply chain management, predictive models to drive trade, faster payment processing, better market relations and services storage, as well as real-time monitoring and management of product warranties.
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This can be effectively addressed by integrating digital technologies with existing systems to gradually eliminate the legacy problems of agriculture. Not only can this help prevent food waste, but also limit wasted time, resources, efficiency and trust.
The future is Agritech
Remarkable technological optimizations of the new era have not only improved agricultural production, but have also helped successfully address persistent legacy issues in post-harvest value chains. This change is being driven by the emerging agricultural technology sector, which is at the forefront of agricultural transformation. This is supported by the strong investor interest in agtech funding and the growing number of agtech start-ups in recent years. It is estimated that by 2025, Indian agrotech companies will be able to receive investments worth $ 30-35 billion.
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Several issues such as food quality assessment, supply chain delays, and real-time operational visibility are successfully addressed by agtechs by leveraging advanced technologies to enable efficient decision making these last time. More importantly, these essential technological interventions help build greater trust among stakeholders at all levels of value chains.
(The author is the CEO and founder of AgNext Technologies)