Precision Farming: Technologies, Benefits and Challenges – Explained, pointwise

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Introduction

India has one of the highest arable lands globally with over 155 million hectares and is one of the key agricultural producers. In 2019, the agricultural sector generated approximately INR 19 lakh crores (US$ 265 billion) business comprising 18% of India’s Gross Domestic Product (GDP) and employs more than half of India’s population. However, there are structural challenges plaguing the agriculture sector including low productivity, uneconomic landholding size, sub-optimal input use efficiency, high biotic losses, and a low level of mechanisation. In the wake of climate change, depletion of natural resources and an imminent food crisis, India must move beyond aggressive farming and towards precision farming. According to estimates, the global precision farming market is forecasted to reach US$ 14.6 billion by 2026 at CAGR of ~8%. Precision farming, although at a nascent stage in India, can help the country become the top agricultural producer across the globe by maximising farm productivity and profitability.

What is Precision Farming?

Precision farming is an approach where inputs are utilised in precise amounts to get increased average yields, compared to traditional cultivation techniques. It is the science of improving crop yields using high technology sensor and analysis tools. Precision Farming utilizes multitude of advanced technologies and tools to monitor several parameters and collect information related to crop growth (like soil moisture, pH etc.). The information is used for targeted interventions. It is referred to as ‘precision’ because it is focused on performing the right intervention (e.g., providing water to crops), in the right place, at the right time, responding to the specific demands of individual crops and individual areas of land with superior levels of precision.

The precise nature of targeted interventions help to improve efficacy of the inputs and hence increase the yields. Precision Farming is being adopted throughout the world to increase production, reduce labor time, and ensure the effective management of fertilizers and irrigation processes. It uses a large amount of data and information to improve the use of agricultural resources, yields, and the quality of crops.

What technologies are used in Precision Farming?

Global Positioning System: GPS is used to identify the location of farm equipment in the field. It provides an accurate positioning system necessary for field implementation of variable rate technology in agricultural input management. The internet enables the creation of a system for efficient remote sensing-based agricultural management.

Grid sampling: It is a technique for segmenting fields into small units (~0.5–5 hectares). Soil samples from those grids are used to calculate the proper application rates for crop inputs. Each grid has many samples collected, combined, and delivered to the lab for evaluation.

Variable-rate technology: Variable-rate technology (VRT) consists of farm field equipment with the ability to precisely control the rate of application of crop inputs that can be varied in their application including fertilizers, irrigation, tillage, insect control etc.

Yield monitors: Crop yield measuring tools fitted on harvesting machinery are called yield monitors. Along with the positioning data from the GPS device, the yield data from the monitor is recorded and saved. Utilizing the yield data, GIS software creates yield maps. The data helps in decisions related to the requirement of targeted intervention.

Remote sensors: Remote sensing (in agriculture terms) means viewing crops from overhead (from a satellite or low-flying aircraft/drone) without coming into contact, recording and displaying the image. This technique provides the map to pinpoint the field problems more effectively. Remote sensors can be categorised as aerial or satellite sensors.

Proximate sensors: Proximate sensors can be used to measure soil parameters (Nitrogen content, pH etc.) and crop properties as the tractor passes over the field.

Computer hardware and software: Computer support is required to analyse the data gathered by other components of precision farming technology and to make it accessible in formats such as maps, graphs, charts, or reports.

What are the benefits of Precision Farming?

Increase agriculture productivity: Precise agriculture inputs (like fertilizers, water) determined scientifically through analysis of data captured by sensors enhances the agriculture output and promotes the yield.

Reduction of chemical application in crop production: Amount of input is determined based on requirement. Fertilizers are supplied only where specific nutrients are missing. Similarly weedicides are used at location of weeds. Drones can be used for targeted delivery of chemicals with desired precision. This reduces unnecessary usage and cuts down waste.

Use of Drones in Precision Farming UPSC

Source: aces.edu (Alabama A&M University, US)

Prevents soil degradation: Since over-use of chemicals is avoided, prevents the leaching of undesired chemicals into soil, preventing their harmful impact on soil.

Efficient use of water resources: Targeted delivery of water through techniques like fertigation reduces water usage. Fertigation is the process of directly applying fertilizer to a crop through the irrigation system.

Fertigation Technique in Precision Farming UPSC

Source: aces.edu (Alabama A&M University, US)

Improvement in Farm Incomes: Increase in productivity, reduction in use of inputs and wastage improves farm incomes and helps in raising the socio-economic conditions of farmers.

Job creation: Precision farming has potential to create a lot of employment opportunities e.g., operating drones is a specialised skillset. Youth in rural areas can be trained and employed as certified drone operators. According to one estimate, these new-age technologies have a potential to create 2.1 million jobs in rural areas.

Moreover, it leads to dissemination of modern farm practices which are more sustainable and climate-friendly.

What are the challenges in Precision Farming?

High Cost: Precision farming is dependent on technologies like GPS, drones, and sensors. All these technologies are capital intensive and require large investments in the beginning. Spending the requisite amounts is beyond the capacity of small and marginal farmers.

Lack of technical expertise knowledge and technology: Deploying and using the technologies, interpreting the captured data require high level of awareness and skills.

Not viable for small land holdings: Precision farming require high investments. Moreover, proximate sensors (say to capture information/samples of soils) are generally deployed on farm machinery like tractors. Thus precision farming is more conducive with mechanized farming. High investments and mechanzied farming are viable only in large holdings. Return in small landholding are too little (due to low absolute output even though yield may be high) to justify high investments required in precision farming.

Furthermore, technology behind the practices is creating opportunities for extremists, terrorists and adversarial governments to attack farming machinery, with the aim of disrupting food production. For example, in 2021 a ransomware attack forced ~20% of the beef processing plants in the U.S. to shut down, with one company paying nearly US$ 11 million to cybercriminals.

What steps have been taken to promote use of Technology in Agriculture in India?

Digital Agriculture Mission 2021–2025’. The initiative aims to leverage a wide range of technologies from AI, blockchain along with drone technology to improve the sector’s overall performance.

At present, ICRISAT (International Crop Research Institute for Semi-Arid Tropics) is working with Microsoft to develop an AI Sowing App to send sowing advisories to farmers for telling the optimal date to sow. The sowing date is very critical when it comes to ensure the best yield and this app aims to eradicate the guesswork from the process.

Crop yield prediction model using AI: In May 2018, NITI Aayog partnered with IBM to develop a crop yield prediction model using AI to provide real-time advisory to farmers. The partnership aims to provide insights to enhance crop productivity, increase soil yield, and control agricultural inputs with the goal of improving farmers’ income. It aims to identify systems of crop monitoring, early warning on pest and disease outbreak based on advanced AI innovations. It also includes deployment of weather advisory rich satellite and enhanced weather forecast information along with IT and mobile applications with a focus on improving the crop yield and cost savings through better farm management.

AI sensors for smart farming: The Government of India, in collaboration with Microsoft, has begun empowering small-holder farmers in India to increase income through higher crop yield and greater price control using AI sensors. Microsoft is engaging with multiple stakeholders including farmers, State Governments, the Ministry of Electronics and Information Technology (MeitY) and the Ministry of Agriculture and Farmers Welfare to create an ecosystem for AI into farming. Microsoft is also engaging with Escorts (Farm equipment manufacturer) to enable precision agriculture capabilities.

Drones to monitor crop and soil health: The project entitled ‘SENSAGRI: Sensor-based Smart Agriculture‘ is being undertaken by the Indian Council of Agricultural Research (ICAR) along with 6 partner institutes. Its objective is to develop indigenous prototype for drone based crop and soil health monitoring system using remote sensors. This technology could also be integrated with satellite-based technologies for large scale applications.

What should be the approach going ahead?

Precision farming can be promoted for specific progressive farmers who have sufficient risk bearing capacity as this technology may require capital investment. The agriculture research institutes can provide technical back-up to farmers to develop the models. The learnings can then be utilized to replicate the models at a larger scale.

Given the current status of agriculture in India, precision farming is not viable on an immediate basis. In the meantime, the Government can encourage the farmers to adopt more judicious water-use practices. Micro level irrigation systems and water saving techniques can be promoted among the farmers.

Conclusion

The main objective of precision agriculture is to obtain a maximum yield with a minimum input while also reducing environmental harm. Better preparation of the roadmap in this sphere would be helpful for India to enhance farmers’ income, be able to produce enough food to support the rising population, and also  able to fulfil the commitments under SDGs.

Syllabus: GS III, Different Types of irrigation and irrigation systems, Conservation.

Source: Indian Express, Down to Earth, The Hindu BusinessLine, The Conversation

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