AI in Agriculture: 7 Ways to Enhance Your Business

Farming and agriculture are some of the oldest and most vital niches in the world. Healthcare, transportation, finance, energy are increasingly using artificial intelligence. Today, agribusiness isn’t staying away from adoption AI in agriculture. Artificial intelligence in agriculture provides new opportunities to achieve and maintain a competitive advantage as well as to deliver new services and products to the market.

AI in Agriculture 7 Ways to Enhance Your Business

The agro-industrial complex should look for more innovative approaches to protect and increase productivity. According to recent UN forecasts, global population will grow from 6.8 billion to 9.1 billion in 2050. The search for the right answers is one of the most pressing problems of humankind. AI for farming may save the day.

In this article, OpenGeeksLab has highlighted seven ways AI is enhancing agribusiness. Keep on reading to find some great insights!

Stats and Facts

stats and facts

Needs for food and water will never disappear. Smart agribusiness is spreading rapidly worldwide. Businesses aim to automate all the processes related to this niche specifics to increase yield, product supply, profit, harvesting crop with fewer workers, and tech stuff than were needed before.

AI in farming is expected to reach the 1550 million U.S. dollars mark by the end of 2025, with a CAGR of 25.0% during 2019-2025.

These are major factors driving the AI growth in agriculture market:

  • Increasing demand for agricultural production owing to the growing population.
  • Widening information management systems as well as new advanced technologies adoption for improving crop productivity.
  • Increasing crop productivity via deep learning techniques integration.
  • Rising initiatives by worldwide governments supporting renovated agricultural techniques adoption.

Apurva Agarwal, the Associate Director of research company MarketsandMarkets, states that merging IoT with AI tech solutions like machine learning, computer vision, predictive analytics allows analyzing data on weather conditions, temperature, soil moisture, plant health, crop prices in real-time.

Ways AI is Transforming Agriculture

Today, farmers use AI applications in agriculture in new surprising ways. By upgrading almost everything in the agricultural process, they revolutionize food cultivation. Here are some core challenges of artificial intelligence in agriculture:

1. Image Recognition

image recognition

Artificial intelligence has advanced in image processing. Gadgets can now see a whole picture, almost like people do. Introducing AI-powered smart technologies alongside computer vision, farmers can find weeds to destroy them instead of spraying the entire crop. Besides obviously saving enormous amounts of money, such an approach allows making foods much cleaner. Drone-based images with artificial intelligence features allow identifying pest disease plus crop damage, monitoring acreage far more quickly and accurately than ever before, generating real-time alerts to speed up precision farming, increase and monitor crop growth.

2. Connected Sensors and IoT

connected sensors and iot

Connecting sensors to IoT is the most effective in agribusiness. IoT agriculture sensors can be ground, aerial, or machine-based—all of them help farmers share data, make improvements in input, efficiencies, operations processes due to AI-driven solutions.

3. Identifying Plant Disease and Pest Infestations

identifying plant disease and pest infestations

Farmers have always suffered from grasshoppers, locusts, as well as other insects, crop devouring. But AI provides agricultural workers with weapons against hungry bugs, helps in diseases identifying and poor plant nutrition on farms. Artificial intelligence sensors can detect pests, weeds, help prevent over-application of herbicides or excessive toxins that find their way in our food.

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4. Crop and Soil Monitoring

crop and soil monitoring

AI in agriculture helps increase efficiency and solve specific challenges the industry is facing. All that means productivity, herbicide resistance, soil health. Below are some of them:

  • Disease detection. Preliminary leaf image processing, including its background, incurable part, affected part, helps in identifying pests, recognizing nutritional deficiencies, and much more.
  • Crop readiness identification. Determining green fruits maturity under white or ultraviolet radiation helps farmers create various levels of preparedness depending on crops, fruits, or vegetable categories.
  • Field management. High-definition images from drones or helicopters made during the cultivation period allow mapping fields and identifying areas in which crops require water, fertilizers, or pesticides.

5. Automating Farm Equipment

automating farm equipment

AI-based agricultural equipment can collect estimated yield data, which allows forecasting sales, overflow, or shortages. Robotic harvesting equipment with integrated AI is used to collect ripe fruits and vegetables. That allows saving time, labor, waste.

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

Face recognition technology built-in physical tracking devices makes it easy controlling a whole world of livestock with minimal human interaction. Farmers are able to monitor individual group behavior, detection lameness in advance, record accurately eating habits.

6. Predictive Analytics

predictive analytics

AI technologies allow creating seasonal forecasting models for agricultural accuracy as well as productivity improvement. These models can predict upcoming weather conditions months and allow farmers to make crucial decisions regarding planting and harvesting.

7. Driverless Vehicle Technology

driverless vehicle technology

Agribusiness is using driverless technologies for tillage or other targets. Vehicles are performing their tasks with a supervisor and are programmed to independently monitor their position, determine speed, plus avoid obstacles, such as animals, people, or other objects in the field. They are remotely controlled from a control station.

Future of AI in Agriculture

AI technologies promise a continuous transformation of agribusiness, and they are of great importance to all of humanity. Using AI, SMEs can prevent ecosystem destruction by reducing the use of fertilizers and pesticides that deplete the soil, decreasing water wastage, automating the labor force. All that will help to save money and lower food prices. Feeding the population and preserving nature is difficult, but AI may be a win-win option.

We at OpenGeeksLab know how to deliver AI-powered solutions that best suit your niche and solve specific issues. Contact us! We will be happy to help you build a product that will reinvent your business opportunities.

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