'It' in Agriculture

https://krishiscience.in/ Chaurasia et al., 2020 KS-1536

Popular article EMERGING TRENDS IN AGRITECH – IMPACT OF ‘IT’ IN AGRICULTURE Akansha Chaurasia and Harmeet Kaur* ICAR-National Institute of Plant Biotechnology, Pusa Campus, New Delhi – 110012, Delhi, India * Corresponding author: [email protected] Received: Aug 22, 2020; Accepted: Sep 25, 2020

Introduction Information Technology (IT) is that essential branch of engineering which involves the usage of resources like computers, telecommunication, internet, hardware, software, satellite and broadcasting technologies (including radio and television) to retrieve, deposit, store and handle information. IT not only has its uses in modern lifestyle and urban infrastructures but it is also a budding tool for improvising the agriculture. Agriculture, which is one of the most salient branches in India, can be benefitted immensely by IT. The contribution of agriculture towards economic growth of our nation is vast. However, despite enormous attempts the agricultural production and productivity in few developing countries like ours, has shown a relative decrement. One of the possible reasons for this reduced output is the unawareness of farmers about different modern agricultural techniques. The use of ultra-modern technologies such as robots, temperature sensor, aerial images, artificial intelligence automation and GPS technology in the present agricultural practices will be revolutionary. Thus, such massive implications of Information and Communications Technology (ICTs) in agricultural sector is becoming progressively perceptible and very well might drive changes to socio-economic situations of farmers even in remote areas.

Automated and Connected Agriculture The principal idea is to transform our systems for automation by plying mechanics and electronics. Farm automation, also known as smart farming is a boon of technology that has successfully automated the livestock maintenance as well. The impetus has led to innovations like robotic harvesters, autonomous tractors and automatic watering-seeding robots.

• Seeding and Planting Seed sowing is considered to be an arduous physical task. But seeding machines have made the work easier. They cover more area in less time versus if done manually. The effective point is dependent upon two variables: sowing seeds at accurate depth and the spacing amongst the plant for optimal maturation. Complete pastureland can be planted with single human inputs that to over digital control dashboard on a tablet/mobile with multiple appliances operational at the same time. Integrating geo- mapping and sensor data analysing quality of soil, its density and nutrient level provides an opportunity for all the seeds to sprout and grow.

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• Autonomous Tractors Tractors are considered to be the lifeline of farming, hence is the primary machines to be transfigured. Over the time period, autonomous tractors will become proficient and adequate by entailing GPS for navigation and for examining remote areas and radar. These tractors can run either by remote or via pre-installed programs to offer brimming autonomy to all the customers. There is a great feature of these machines to communicate to one another and co-ordinate various tasks. Most importantly, these machines are well equipped with adequate sensors to determine obstacles and elude them thus maintaining the safety requirements.

Fig.1: Driverless Tractors by Rabbit Tractor’s (extreme left) and Robots developed by Harvest CROO Robotics (centre and right).  Weeding and Maintenance of Crops The most crucial stage for plant maintenance is weed and pests control. For this autonomous robots have been designed which are about the size of a car and can navigate through the fields using video, LiDAR and satellite GPS. Bonirob, as they are named are trained with the machine learning approach to spot weeds and eliminate them.

Fig.2: Robots designed for weeding, weeder (left), Weedobot (centre) and Bonirob (right). • Automatic Watering and Irrigation Subsurface Drip Irrigation (SDI), the most notable method of irrigation which allows farmers to regulate the timing and amount of water received by crops. By amalgamating the SDI system with IoT (internet of things) for examining plant health and dampness levels, the system enables to work autonomously relying on the figures from sensors stationed surrounding the fields. The supremacy of this strategy is that it diminishes the loss of water owing to evaporation and runoff. Artificial Intelligence in Agriculture IT today is incomplete without Artificial intelligence which has applications in almost all conceivable areas and has important roles towards different sectors of agriculture. In the modern era, more and more companies are adopting AI-based approaches to enhance the overall productivity and optimization of manpower without completely eluding one another. Some examples illustrating the widening use of AI based technologies in modern agriculture are outlined below.

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• Agricultural Robots –These robots are developed to perform function of harvesting crops and weed control which is at higher momentum than humans. E.g. Blue River Technology offers robotics-based weed control whereas Harvest CROO Robotics is a Crop Harvesting solution provider through robotics.

Fig.3: Examples of agricultural robots. • Crop and Soil Monitoring – AI based technologies allow real time monitoring of various defects and nutrient deficiencies in the soil by capturing images via drones and processing through technical software. E.g. PEAT is one such machine designed for Pests / Soil Defects. Trace Genomics and Sky Squirrel Technologies Inc. provide diagnostic solutions for Soil Defects and Crop Analysis respectively by Machine Learning.

Fig. 4: A drone by SkySquirrel Technologies which can scrutinize nearly 50 acres in 24 minutes and present data with 95% accuracy. • Predictive Analytics – Weather prediction through satellite based models are introduced to familiarize the farmers with weather forecasting e.g. aWhere are the satellites for forecasting weather and FarmShots are Satellites which scrutinize Crop Health along with Sustainability thus avoiding the risks posed by variable environmental impacts on crops.

Fig.5: Farm Shots focuses on scanning agricultural data captured by satellites and drones.

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Importance of IT in Agricultural Technology There is a great potential for widespread use of IT for direct benefaction to agricultural communities. Using some of the significant technologies of agronomy and soil science like satellite technology, geographic information systems have direct impact on agricultural production. There is possibility of timely information on weather forecasts and calamities leading to better and impetuous agricultural practices. Agronomists advocate the judicious supply of water, fertilizers and pesticides across the fields based on soil and plant health data analysis which is made possible by these technologies. This allows minimum quantities of resources required and target only the specific affected areas and provide treatment individually and effectually. These have resulted in minimum impact on the environment and ecosystems as well. The problem of runoff of excess fertilizers and pesticides is also resolved thus maintaining the quality of ground-water. The service provided by the ICTs can intensify rural opportunities by enhancing access to market information and by reducing the transaction efforts of farmers and traders. This will lead to better market exposure and pricing with fewer risks and augmented incomes. There has also been introduction of online trading which has improved the decision making and better pricing. Overall use of IT in agriculture technology has inflated the food production and productivity across the globe. Challenges  Availability of reliable internet services  Technological illiteracy of farmers  High input costs thus feasible for industrial farms only  High cost of regular maintenance of machines

Conclusion IT-driven up gradation of modern agriculture is evolving and has boosted the efficiency of farming practices. It is projected that agricultural robots and technological interventions like satellite machine vision will become ordinary for industrial farms in time to come. Although we are at a premature stage of automation right now nonetheless, we are headed in the right direction to remodel our farming and agriculture.

References Chetan Dwarkani M, Ganesh Ram R, Jagannathan S and Priyatharshini R. (2015). Smart farming system using sensors for agricultural task automation. IEEE Technological Innovation in ICT for Agriculture and Rural Development (TIAR). Kodimalar Palanivel, Chellammal Surianarayanan (2019). An Approach for Prediction of Crop Yield Using Machine Learning and Big Data Techniques. International Journal of Computer Engineering and Technology 10(3): 110-118 Nehra K and Jangra, Mukesh and Jangra, Sumit and Kumar, Raj. (2018). Role of Information Technology in Agriculture. Patel, Sami. (2014). Impact of information technology in agriculture sector. 4: 17-22. Talaviya T, Shah D, Patel N, Yagnik H, and Shah M. (2020). Implementation of artificial intelligence in agriculture for optimisation of irrigation and application of pesticides and herbicides. Artificial Intelligence in Agriculture 4: 58–73. Tan L. (2016). Cloud-based Decision Support and Automation for Precision Agriculture in Orchards. IFAC-PapersOnLine 49(16): 330–335.

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