Ingredients Network

Artificial Intelligence in Agriculture

Agriculture is the primary source of income for approximately 58 percent of India’s population. It has a huge impact on the country’s economic progress. For the first time in 17 years, this industry contributed up to 20 percent of the country’s GDP in the years 2020-2021. In comparison to the United States, India today has a net sown area of roughly 140 million hectares. After China, India has the world’s second-largest irrigated area. Irrigation policies and technological advancements have been good, but they cannot compete with the current situation.

It should be noted that even as India’s income rises, farming revenues will not increase significantly. Regardless of per capita income, the ratio of total agricultural income to total population is relatively flat across countries. Rising GDP means rising non-agricultural earnings. The demographics of the world’s population will change dramatically in the coming decades.

By 2050, the world’s population is expected to reach 10 billion. So the question here is whether we can achieve the required production increases in light of already scarce land and water resources, as well as the negative effects of climate change. Is agriculture capable of meeting unprecedented food demand?

Today’s agricultural policies ignore the interdependence of crop selection, input costs, and the supply chain, perpetuating marginal farming. There is a need for more than policies that can foment a change in Indian agriculture. With an increasing population, the demand for food and employment is also increasing. The traditional methods which the farmers used are not sufficient enough to fulfill these requirements. 

This era has been dominated by smart technology of large-scale machine-to-machine communication  (M2M) and the internet of things (IoT) are integrated for increased automation. There has been a drastic transformation in many industries across the world, with the advent of technologies. From self-driving cars to healthcare, AI has begun to play a significant role in our daily lives. It may surprise you to learn that, despite being the least digitised sector, AI plays a significant role in the development and commercialization of agriculture.

What Can AI Do?  

AI-based technologies can help improve efficiency in a variety of industries. It can be used in crop yield, soil content sensing, irrigation, weeding, crop monitoring, and pest control in the agricultural sector.

Zion Market research has published a report on how AI and other technologies have impacted the agriculture market. According to the report, global AI in the agriculture market was valued at around USD 545 million in 2017 and is expected to reach approximately USD 2,075 million by 2024, at a CAGR of slightly above 21% between 2018 and 2024.

AI can enable farmers to collect large amounts of data from government and public websites, analyse it, and this provides farmers with solutions to many ambiguous issues. It can also provide us with a smarter method of irrigation,  resulting in a higher yield for farmers.

As a result of artificial intelligence, farming will soon be found as a combination of technological and physiological skills. AI in agriculture can be used in a variety of ways to automate processes, reduce risks, and provide farmers with relatively simple and efficient farming.

SkySquirrel Technologies, a Canada-based start-up, develops drone-based imaging technology for monitoring crop health, with a primary focus on improving crop yields and reducing losses from the disease at commercial vineyards. The drone captures data from fields and then data is transferred via a USB drive from the drone to a computer and analyzed by experts.

This enables farmers to identify pests and bacteria, allowing them to use pest control and other methods to take action on time.

AI can Improve Harvest?

Variety selection and seed quality set the maximum performance level for all crops. Emerging technologies have helped the best selection of the crops and even have improved the selection of hybrid seed choices which are best suited for farmer’s needs. It has been implemented by understanding how the seeds react to various weather conditions, different soil types.

By collecting this information, the chances of plant diseases are reduced. Precision agriculture utilises AI to aid in the detection of plant diseases, pests, and poor plant nutrition on farms. AI sensors can detect and target weeds before determining which herbicides to apply within the appropriate buffer zone. This helps to prevent the overuse of herbicides and the accumulation of toxins in our food.

Farmers are also utilising AI to develop seasonal forecasting models to improve agricultural accuracy and productivity. These models can forecast upcoming weather patterns months in advance, assisting farmers in making decisions. Farmers are using drones to monitor their farms in addition to ground data. Data captured by drones flying over their fields are processed using computer vision and deep learning algorithms. 

AI-enabled cameras mounted on drones can capture images of the entire farm and analyse them in near-real-time to identify problem areas and potential improvements. AI systems use satellite images and compare them to historical data using AI algorithms to determine whether or not an insect has landed and what type of insect has landed, such as a locust or a grasshopper. And send alerts to farmers’ smartphones to take necessary precautions and use necessary pest control, thus AI aids farmers in pest control. Now we can meet the market trends, yearly outcomes, consumer needs, therefore farmers are efficiently able to maximize the return on crops. 

A tech start-up based in Germany PEAT has developed Plantix, an AI-based application that can identify nutrient deficiencies in the soil as well as plant pests and diseases, giving farmers ideas on how to use fertiliser to improve harvest quality. This app makes use of image recognition technology. Smartphones can be used by the farmer to photograph plants. Through short videos on this application, we can also see soil restoration techniques, tips, and other solutions. Also, Trace Genomics, a machine learning-based company helps farmers to do a soil analysis. This type of app helps farmers to monitor soil and crop health conditions and produce healthy crops with a higher level of productivity. 

Robotics in Agriculture

AI firms are creating robots that can efficiently perform multiple tasks in agricultural fields. This type of robot is programmed to control weeds and harvest crops at a faster and higher volume than humans. Robots are used in a  variety of farm activities, including fruit picking and lettuce thinning. These robots are also programmed to inspect crop quality and detect weeds while picking and packing crops at the same time. These robots are capable of overcoming the challenges that agricultural labour faces. This can result in long-term productivity gains with indefatigability, consistent work quality, and cost savings.

In a country like India, where agriculture provides income to a large part of its population and is a significant contributor to the country’s GDP, adopting these smart technologies is essential. The government of India is also promoting the use of AI in agriculture. To promote technological advancements in agriculture, India has recently unveiled the country’s first drone policy which is expected to drive the growth of AI in agriculture in the country. It has to be noted that in 2018, NITI Aayog partnered with IBM to use AI for developing crop yield prediction models. The government of India is launching a new AGRI UDAAN program to mentor start-ups and connect them with potential investors to boost agricultural innovation and entrepreneurship. 

Artificial intelligence-based agri-tech applications are poised to unlock value in agriculture, particularly in light of recent farm reforms that have opened the door to private-sector investment in agriculture. During the fiscal year 2019- 20, Indian agrifood tech start-ups raised more than $1 billion in 133  transactions. India’s agricultural product exports increased to $37.4 billion in  2019 and are expected to rise further with investments in the supply chain and better storage and packaging.

All of these steps will go a long way toward ensuring fair prices for farmers and reducing agrarian stress. So, the smart implementation of AI in agriculture would help ensure the industry’s long-term viability. 

References: 

1. https://www.sciencedirect.com/science/article/pii/S258972172030012X 2. https://emerj.com/ai-sector-overviews/artificial-intelligence-in-indian agriculture-an-industry-and-startup-overview/ 

3. https://www.craaq.qc.ca/documents/files/Evenements/EPER1401/08_G upta_Manish_ang.pdf 

4. Agricultural Policies in India: Retrospect and Prospect by V.P.S. Arora 5. https://indianexpress.com/article/opinion/columns/artificial intelligence-farmer-agriculture-7069520/ 

6. https://www.forbes.com/sites/cognitiveworld/2019/07/05/how-ai-is transforming-agriculture/?sh=57a0caee4ad1

7. https://www.analyticsvidhya.com/blog/2020/11/artificial-intelligence in-agriculture-using-modern-day-ai-to-solve-traditional-farming problems/ 

8. https://medium.com/star-gazers/role-of-artificial-intelligence-in agriculture-70cdf5b2be2e 

9. https://www.livemint.com/technology/tech-news/ai-to-play-a-key-role in-india-s-growth-in-agriculture-nasscom-ey-report 

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10.https://www.globenewswire.com/en/news-release/2018/11/30/1659883/0/en/Global-AI-In-Agriculture-Market-Will-Reach-USD-2-075-Million-By-2024-Zion-Market-Research.html