Transformative Agricultural Practice -Application of Artificial Intelligence

Almost a decade back, I was interacting with some of the research students in a leading agricultural university in India. Whenasked if they would be interested to takeagriculture as a profession, all of them denied even to think on the possibility. Today,Agri-Tech companies are burgeoning in every part of the country. What has changed over the last two decades? Isit the perception about agriculture?Traditionally the agricultural activities were limited to food and crop production, thus yielding very low income and poor standard of life. Today the scopeisnot only limited to production but also involves processing, marketing, distribution,and livestock management. Figure 1: Perceptual change in Agricultural activities, source Grus & GradeTheintegration of various actors and activities in Agrivalue chain has attracted a lot of interest in youth towards agriculture. Though the sector still faces plutonic problem, the silver lining is the use cases of latest innovative industry 4.0 technological solutions in agricultural sector. Moreover, with the penetration of mobile and internetinto semi urban and rural areas, policy advocacy due to various digital strategies oftheGovernmentsas well as increasing youth population, the stage is all set for adoption of technological innovations in what we expect to be the next economic and social revolution of the country. As per researchconducted by Grus & Grade team in eight states of India, the COVID 19 has acted as a catalyst for digital penetration and adoption in rural India.

 

Figure 1: Perceptual change in Agricultural activities, source Grus & Grade

The integration of various actors and activities in Agrivalue chain has attracted a lot of interest in youth towards agriculture. Though the sector still faces plutonic problem, the silver lining is the use cases of latest innovative industry 4.0 technological solutions in agricultural sector. Moreover, with the penetration of mobile and internetinto semi urban and rural areas, policy advocacy due to various digital strategies oftheGovernmentsas well as increasing youth population, the stage is all set for adoption of technological innovations in what we expect to be the next economic and social revolution of the country. As per researchconducted by Grus & Grade team in eight states of India, the COVID 19 has acted as a catalyst for digital penetration and adoption inruralIndia. 

Figure 2: Scope for Digitalization of Agri Value Chain, Source: Grus & Grade

Application of artificial intelligence along with introduction of IoT devices, robotics, big data science, data analytics and availability of cheap sensors, cameras, drone technology,etc.have triggered a quantum change in sourcing, production,and distribution cycles of the Agrivalue chain. Interpretation and application of various structured, semi-structured and unstructured data sources such as air density, temperature, humidity, moisture, weather, soil analysis, cropping pattern, crop performance, demand sensitivity, price variations, labouravailability, cash flow patterns, crop wastages, pest infections, etc. provide predictive insights for optimal production techniques, price optimization and demand-supply management. Data driven insights helps in improving crop yield while mitigating various risk in farm practices. The optimal use of water, fertilizers, pesticides, power, etc. not only helps a farmer reduce his cost to production, but also helps in adopting sustainable farm practices which are ecologically and environmentally sensitive.

Figure 3:Grus & Grade investigated the application of AI in four major areas

AI in agriculture is in its formative years and would face the following challenges in near future:
   1.Response time and accuracy
   2.Needs Big Data which is still elusive in agri sector
   3.Challenges in implementation and adoption
   4.High cost of data and its application
   5.Lack of flexibility

Despite these challenges, adoption of AI in agriculture is improving and with change in mindset, the acceptance and adoption has seen a positive trend. Grus & Grade team has been conducting research and development of various technologies to be adopted in our 360-degreesolutions for the entire agricultural ecosystem. A causal loop diagram and solutionreinforcing,and balancing loop has been described in figure 4below.

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