7 ways AI in agriculture is transforming as never before

AI in Agriculture: Artificial Intelligence (AI), is certainly expanding its footprints in every sector of the system, be it education, agriculture or working. However, we’ve already discussed the role of AI in education and working sectors. We recommend you to go through those blogs further reading this.

Source: Wall Street General

Amid ongoing agrarian crisis, India has certainly found a ray of hope emerging with Artificial Intelligence in Agriculture taking the reins. So, AI is successfully paving its way in the world’s most vital sector – Agriculture. It is subsequently providing cutting-edge technology for harvesting with better productivity and crop yield. Therefore, AI in agriculture would lead to more agricultural output from limited land in a more sustainable manner.

Source: MarketsandMarkets

Also, according to Apurva Agarwal, Associate Director, Electronics and Semiconductor, MarketsandMarkets, “The combination of the Internet of Things (IoT) and artificial intelligence technologies, such as machine learning, computer vision, and predictive analytics, allow farmers to analyze real-time data of weather conditions, temperature, soil moisture, plant health, and crop prices in real-time.”

So, without consuming any extra minutes, let’s dive deeper in out today’s topic: 7 ways AI is transforming the face of agriculture.

Stats and analysis

"AI in Agriculture"
Source: The News Minute

As per the Confederation of Indian Industry (CII), India certainly can’t accomplish the global need of 50% more food by the end of 2050 if it continues to limit its resources on the 4% land under cultivation.

For this reason, artificial intelligence along with other digital technologies will subsequently act a crucial role in modernizing agricultural activities. This will therefore lead to doubling the farmers’ income with limited land by the end of 2022. The global “AI in Agriculture” market size is also expected to be worth USD 2.6 billion by the end of 2025.

CII is determined to upgrade the technology quotient in agriculture and, therefore, developing this sector in line with the country’s aspiration.

Ways AI is transforming agriculture

AI in agriculture is not only helping farmers to automate their farming but also shifting to smart or precision farming for higher crop yield and better quality while using fewer resources. So, here are seven such ways in which AI in agriculture is acting as a miracle:

1. Image recognition

"Image recognition for agriculture"
Source: Pakistan Makers Lab

Image processing is one of the most advanced branches of AI in agriculture. Likewise, humans, gadgets can now see and analyze the whole condition of any farmland more efficiently. The introduction of AI-powered smart technologies alongside computer vision consequently can help farmers to find weeds more specifically. Thus, avoiding the unnecessary spraying on the entire crop. Besides its user-friendly and cost-effective nature, this approach avails food in a much cleaner means. Similarly, Drone-based images with AI features allow it to identify various pest disease and crop damage. Monitoring acreage far more quickly as a result will generate real-time alerts to fasten up precision farming and crop growth monitoring.

Companies like Blue River Technology and Harvest CROO Robotics are certainly some prominent examples.

Google is also working to train AI to recognize 5,000 species of plants and animals, which would improve drone ability to detect pest disease and crop damage.

2. IoT and connected sensors

"IoT and sensors for agriculture"
Source: Biz4intellia

It’s another credential required for a successful agribusiness. Smart farming subsequently permits the use of both hardware (IoT) and software (SaaS) sensor technologies to monitor the field conditions from anywhere anytime. These conditions, for example, temperature, humidity, rainfall, sunlight and others can provide more efficient water usage, optimization and output productivity. These further help the farmers to share data, make improvements via AI-driven solutions.

John Deere, an agricultural IoT equipment manufacturer, helps farmers maximize their output. Sensors that are built-in machines can measure soil moisture to assist in planning field irrigation. They also have the technology of planting and harvesting, which can guide the equipment during operation.

3. Identification of plant disease and pest infestations

Source: Sciencedirect

None of us is unaware of the locust attack on the Indian crop fields this year. The locusts not only devoured valuable standing crops but also devastated livelihoods of farmers and those linked with the agricultural supply chain.

In this extreme situation, AI in agriculture is a miracle. It provides agro-workers with weapons against hungry bugs, and also identifies plant diseases and their nutrition values. Additionally, one can also get rid of the excess application of herbicides which consequently finds its way to our food. Thus, prevailing several health issues.

4. Soil and crop monitoring

Source: Xyonix

AI in agriculture can solve the most faced challenges of the farmers, for example, productivity, soil health and herbicide resistance.

A German-based startup PEAT has developed a deep learning-based application called Plantix that can identify the potential defects and nutrient deficiencies in the soil including plant pests and diseases.

Also, some challenges solved by AI in agriculture are:

A. Crop readiness identification: Determining the right time of maturation of green fruits can be a bit difficult. However, AI-infused white or ultraviolet radiations aids farmers to analyze the exact preparative stage of any fruit or vegetable.

B. Field management: High-definition images from drones made meanwhile the cultivation period, also identifies the area which needs more water, fertilizer or pesticides than others.

5. Automation in farm equipment

Source: AI Magazine

AI-based agricultural equipment can collect estimated yield data and also allows forecasting sales, overflow and shortages. Robotic harvesting types of equipment integrated with AI are further used to collect ripened fruits and vegetables. This as a result is zero labor-intensive and saves much time for other important stuff.

Agrobot: Certainly the first pre-commercial robotic harvesters build smart farming machinery from disruptive but practical approaches. They have also recently launched the new Bug Vacuum (an insect vacuum robot).

Companies involved in perishable product processing and transportation for instance milk use AI-based smart information systems to automate the process of pumping milk from tanker trucks to silos. They can further monitor quality and create a vibrant data trail so one could track liquid delivery from farms to stores.

6. Predictive analysis

Source: MIT News

AI technologies can create seasonal forecasting models for accuracy and productivity in agriculture. Such models can therefore predict any upcoming drought or flood. Thus, farmers are allowed to make crucial decisions regarding planting and harvesting in those spans.

Skymet: This is considered India’s largest weather monitoring and agri-risk solutions. As per their website, they’re experts in measuring, predicting, and limiting climate risk to agriculture, thus reducing losses incurred due to bad weather conditions.

7. Driverless vehicle technology

Source: Tech Startups

With evolving techniques, agribusiness is consequently using driverless technologies for tillage or other targets. Such vehicles are programmed firstly to independently monitor their position, secondly maintain their speed, thirdly avoid hurdles in the path such as animals, people or other such objects. For example, the tractors use GPS and other wireless technologies to farmland without the need of a driver. They consequently are operated simply with the aid of a supervisor monitoring the progress at a control station.

Wrapping up

Therefore, the companies involved in improving the machine learning or AI-based products like training data for agriculture, drone and automated machine masking will get technological advancements in future. As a result, they’ll provide more useful apps to this sector. And, thus it will help the world to deal with food production issues for the ever-increasing population.

So, this was the end of our today’s blog. Hope you liked it, also please share this with your kith and kin. Meanwhile don’t forget to go through our other interesting related technological blogs below. Also, keep reading, keep supporting!

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