Digital or precision agriculture: Beyond agriculture

(The writer is Director, Dibrugarh University Institute of Engineering & Technology. He can be reached at drmukulcbora@gmail.com)

The whole world is now under the implementation of Industry 4.0/4th Industrial Revolution which is mainly focused on the digitalization of industries starting from manufacturing to the logistics or supply chain management. The impact of this revolution will be visible in each and every sphere of our life and education. In the last Industrial Revolution, we observed that agriculture was no longer a way to just feed the families of farmers, but also a business to a great extent and its contribution is mainly responsible for the growth of Gross Domestic Product (GDP). India is an agricultural nation and hence, if the growth of agriculture does not take place its contribution towards GDP will come down and this is the major concern for all the citizens of this great nation. The GDP contribution of agriculture has come down from 59% in 1950-51 to 16.11% in 2011-12 and is now gaining its contribution to 20.19% in 2022-21. In 21st century, farming is not only a way of cultivation but also an industry at par with other industries and it can be taken up by educated youth of the country as it includes all the skills of the 4th Industrial Revolution. It is also required to reduce the toxicity present in the fruits and vegetables which is an indirect gift of the Green Revolution.

DEFINITIONS OF DIGITAL OR PRECISION AGRICULTURE

There are differences in how different entities define digital agriculture or digital farming, precision agriculture/farming and smart agriculture/farming and AI in Agriculture.

The International Society for Precision Agriculture, which claims to be the sole international scientific society completely devoted to Precision Agriculture, defined it thus: "It is a management strategy that gathers, processes and analyzes temporal, spatial and individual data and combines it with other information to support management decisions according to estimated variability for improved resource use efficiency, productivity, quality, profitability and sustainability of agricultural production."

According to the EU-funded BIOPRO Baden-Württemberg GmbH project (2018), "Precision farming is an agricultural concept involving new production and management methods that make intensive use of data about a specific location and crop. Sensor technologies and application methods are used to optimize production processes and growth conditions. In contrast to conventional agricultural methods, using digital data can increase resource and cost efficiency as well as reduce environmental impact. Further, Smart farming (also known as Farming 4.0 and digital farming) is the application of information and data technologies for optimizing complex farming systems. The integration of smart agricultural technologies and modern data technologies enables seed planting to be adapted to a specific field to ensure an efficient production process. The application of information and data technologies supports farmers in making informed decisions based on concrete data."

The media organization specializing in IoT, IoT for All describes that "Smart farming as an emerging concept that refers to managing farms using modern Information and Communication Technologies like IoT, robotics, drones and AI to increase the quantity and quality of products while optimizing the human labour required by production. They specifically identify sensors, software, connectivity, location (GPS, satellites etc.,), robotics and data analytics as the technologies that can be used for smart agriculture. Further they specify Precision Farming or agriculture, as "an umbrella concept for IoT-based approaches that make farming more controlled and accurate. In simple words, plants and cattle get precisely the treatment they need, determined by machines with superhuman accuracy. The biggest difference from the classical approach is that precision farming allows decisions to be made per square meter or even per plant/animal rather than for a field."

Smart Farming is a farming management concept using Digital Technology to increase the quantity and quality of agricultural products and the farmers in the 21st century have access to GPS, soil scanning, data management, and Internet of Things technologies. With the precise measurement of variations within a field and adapting the appropriate measures, farmers can increase the effectiveness of pesticides and fertilizers, and use them more judiciously as per crop requirements. Furthermore, use of Smart Farming techniques, empower the farmers to monitor the needs of individual animals and adjust their nutrition correspondingly and thereby preventing disease and saving life of those animals.

According to Emerj AI Research, Artificial Intelligence (AI) is steadily emerging as part of the technological evolution in agriculture and can be categorized into 3 main groups:

n Agricultural Robots – to replace human labour-intensive tasks by robots.

n Crop and Soil Monitoring – leverage computer vision and deep-learning algorithms to monitor crop and soil health.

n Predictive Analytics – develop and use machine learning models to track and predict various environmental impacts on crop yield such as weather changes.

European Agricultural Machinery Association (CEMA) defines Agriculture 4.0 as "Integrated internal and external networking of farming operations. This means that information in digital form exists for all farm sectors and processes; communication with external partners such as suppliers and end customers is likewise carried out electronically; and data transmission, processing and analysis are (largely) automated. The use of Internet-based portals can facilitate the handling of large volumes of data, as well as networking within the farm and with external partners."

Thus, if we carefully look at the above definitions of Agriculture 4.0 or Digital Agriculture or Precision Agriculture and Smart Agriculture, we find that these are overlapping concepts and a clear compartmentalized definition is difficult to establish. The concepts of Agriculture 4.0 and 5.0, AI in Agriculture area also constitute Digital Agriculture.

Applications of Digital Farming:

There are a wide variety of applications available now and it uses the digital technology in Agriculture and few of them are briefly described below.

AgroPad: IBM developed AI-powered technology are helping the farmers to check soil and water health and AgroPad10, is a paper device and is the size of a business card. The microfluidics chip inside the card performs on the spot a chemical analysis of the sample, providing results in less than 10 seconds. A drop of water or soil sample is placed on the AgroPad and the set of circles on the back of the card provide colorimetric test results; the color of each circle represents the amount of a particular chemical in the sample and it can be monitored by an ordinary smartphone and the farmer can get all the using a chemical test results of soil in a dedicated mobile application.

Plantix and crop disease identification over WhatsApp: Developed by PEAT, a German startup, Plantix11 is a mobile application, which is a massive database of pictures of plant disease that can be used for comparison. This helps in identification and subsequent diagnosis and treatment. PEAT aims to support farmers across the world to enhance their agricultural output through timely and informed disease treatment. The facility is now also available over WhatsApp where just an image of the infected leaf is required to be sent to the Plantix WhatsApp number and the diagnosis is messaged back to the sender via WhatsApp in real time and many farmers in India are using this service.

Use of drones to fight locusts in India: Locusts have been attacking and destroying large swathes of India's crops on a regular basis since the winter months of 2019 and the attack is continuing. The Agriculture Ministries both at the Central level and the state levels have been using drones for anti-locust spraying. They are proving to be effective solution in an otherwise challenging scenario where India stares at large amounts of crop loss in the states of Rajasthan, Gujarat, Madhya Pradesh and Uttar Pradesh.

Use of drones for rural property mapping in India: The Government of India recently launched the 'Swamitva18 scheme' under which drones will draw a digital map of every property falling within the geographical limits of a village and demarcate the boundaries of every revenue area. Property card for every property in the village will be prepared by states using accurate measurements delivered by such drone-mapping.

CSD Working Paper Series: Towards a New Indian Model of Information and Communications Technology-Led Growth and Development well as non-land-owning farmers would stand a chance to access formal and cheaper financing by using their property as collateral.

Grain Bank Model of 'Ergos': Ergos has one of the most unique models in the Agri-tech landscape. They have a "Grain Bank model" that is providing doorstep access to end-to-end post-harvest supply chain solutions to small and marginal farmers, i.e. enabling farmers to convert their grains into tradable digital assets, avail credit against those assets through partner NBFCs and Banks, and get better prices for their produce. The Ergos model offers farmers the flexibility to store/ withdraw a single bag of grains. Farmers get immediate liquidity and better income, as they don't have to sell all their produce at once at the prevailing market rates during harvest season. Through an efficient use of technology and direct farmer engagement, they provide the following services to farmers at the farmgate presently in the state of Bihar.

Quality Assessment using technology: AgNext19 produced a technology platform Qualix, to assess trade quality and safety parameters for multiple commodities (grains, pulses, tea, spices, herbs, milk and honey etc.,) in a minute. It is a platform for introducing rapid quality estimations in agriculture and food value chain through technologies like AI based spectral and AI based image analytics using a mix of hardware, software and data analytics. Thus their solution, they claim, helps in identifying chemical and physical composition of grains such as wheat, rice, pulses, maize and oilseeds in less than a minute with the help of a small pocket sized device. Using the same Bluetooth enabled, battery-operated hand-held device, which works in coherence with a mobile application, the chemical composition of milk and honey can be identified to detect the presence of adulterants. The same device also checks fat percentage, protein, lactose and SNF content in a milk sample.

Digital tools for agriculture farm monitoring and risk management: The Bangaluru based Yuktix Technologies is an Agritech start-up based in Bangalore that focuses on creating digital tools for agriculture farm monitoring and risk management. The solution helps growers make decisions and implement best practices that increase yield and cut losses. Yuktix Green Sense is an off-grid remote monitoring and analytics solution for CSD Working Paper Series: Towards a New Indian Model of Information and Communications Technology-Led Growth and Development agriculture.

CONTEXTUALIZING DIGITAL AGRICULTURE IN INDIA:

To understand the challenges associated with digital agriculture in India, let us consider a typical Indian farm and how it compares with the average farm in the US, Australia and Europe.

The average farm in US in hectares is 179, in Australia it is 433121 and in Europe, it is 16.1 while that in India, it is 1.08 hectares. This disparity implies huge implications for how Digital Agriculture can be implemented in India. It means that Digital Agriculture has to be customized to be applicable to a typical Indian small farm if we want Digital Agriculture to be scalable and be available to a majority of Indian farms.

Business Insider Intelligence projects nearly 12 million agricultural sensors installed globally by 2023. Additionally, tech giant IBM estimates that the average farm can generate half a million data points per day – helping farmers to improve yields and increase profits. Even though the typical Indian farm is very small and it may generate substantially lesser data points, yet millions of data points to suitably aggregate and analyze, would require computing, storage and processing power which would come at a cost; there is still some distance to be travelled here for Indian farms. Thus, for the success of Digital Agriculture in India we must focus on the innovations of low-cost device and technologies.

LOW-COST TECHNOLOGY: Lowering of cost of technology to be used in Digital Farming is of great need as it must be affordable for the smaller farmers too. The average income of a farmer in India is estimated at Rs 77,976 (approx. 1,000 US dollars) per year, according to the Dalwai Committee report. This figure is self-explanatory to the point mentioned above and only then the Digital Farming will grow in India. Thus the innovations for Digital Farming must be at par with the financial conditions of the farmers and hence the Technical Institutes of India have to contribute a lot towards the development of low cost technology and services. It is worth mentioning that the 5G network in India will also boost the farmers to get the real time farm management information in no time due to its speed and minimum lag time.

(n To be concluded)