How is Machine Learning used as a Game Changer in Agritech Industry?

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Machine Learning in Agriculture

Machine learning has disrupted the agriculture sectors in the last few years with its high-precision algorithm.

If we check the past of farming in India, it’s always been challenging. When we talk about agribusiness, it’s not the hard work and dedication that will bring profit. Apart, several natural and physical factors conclude the returns.

Looking at flummox of the growth and profitability of this sector, several farmers and startups redirected their way from farming.

Now years passed, and technology got advanced. Just like other sectors, the farming industry got transformed. The perception of farmers and entrepreneurs toward this sector changed. 

Even the government is taking the initiative to revolutionize this sector with tech innovations, accessibility, and education. 

Now young entrepreneurs who are about to start their startups are putting more interest in agritech. Moreover, looking at the demand, investors are investing more in this sector.

India’s growing tech ecosystem has revolutionized the agriculture sector. Currently, there are more than 1000 agritech startups in India.

As per a report from Fintrackr, about 100 Indian agritech startups have raised close to $1.33 billion in funding since 2020. Some startups are even at the doorstep of getting unicorn status.

If you have any ideas based on the agriculture segment, it’s time for you to start and bloom. 

Let’s discuss the mainstream of our Blog. How is Machine Learning impacting Agritech Industry?

Agriculture has drastically changed and expects to witness more in the coming years. The introduction of advanced technology has unlocked numerous game-changing opportunities.

It’s not only Machine learning but Intelligent Automation like Artificial intelligence and the IoT(internet of things) that helps to provide real-time data algorithms that increase agricultural efficiencies and improve crop yields.

If you are already in this industry, you must know how machine learning can change the shape of your business.

Here are some of the ways Machine learning has the potential to change your game.

 

#1: Automatic Irrigation Systems:-

When dealing with large open spaces, irrigation systems are complicated. You need to find resources for that. Moreover, the major problem lies in organizing the work based on the weather and soil conditions.

Here is how Machine learning can help you with an automatic irrigation system. It refers to a method of switching water flow from bays without the presence of an irrigator using a device to control irrigation structures.

The irrigation system model builds using a machine-learning algorithm called a Decision Tree. As a result, a model will be set up based on a portion of the collected data, and the remaining data will be examined and predicted based on that model.

The automation system helps in various ways, like using supply channel outlets to start and stop irrigation and managing the water flow from one irrigation area.

You do not need to have any direct manual effort for this. Nevertheless, it may take time to prepare the irrigation system and to maintain the components to work efficiently.

There are several benefits of automatic irrigation:

  • Minimum labour.
  • On-time irrigation.
  • Water and nutrient runoff gets reduced.
  • Water cut-off is more accurate than manual checks.

 

#2: Surveillance systems:-

Machine learning can help you from preventing domestic and wild animals from destroying your crops by sending an alert immediately.

Video surveillance systems based on machine learning give advanced video analytics that let everyone involved in farming protect their fields. The ML-based surveillance system is programmed and trained to identify the people and the vehicles involved in the work.

Benefits of surveillance systems:

  • Secure remote facilities. 
  • Crop optimization.
  •  Identify trespassers.

 

#3: Smart sensors & Drones:-

Drones and smart sensors are making significant improvements in the agro-arena. Smart sensors capture data, and drones provide real-time video that helps Agri experts to access unseen data.

Machine learning is one of the perfect technology that can combine massive data and provide the most effective advice for improving crop productivity.

Data provided by advanced devices like ground moisture, fertilizer, and nutrient levels are combined and help to analyze growth patterns for each crop over time. 

Benefits of sensors and drones:

  • Provide insights about improving crop health and yields.
  • Soil monitoring.
  • Irrigation monitoring.
  • Collecting soil and water samples.

 

#4: Automatic Harvesting:-

The agriculture industry spends a lot on harvesting. Several farmers face crop loss due to a lack of human labour and equipment. Moreover, some vegetables and fruits need intensive care while harvesting.

Technology has come up with a solution for automatic harvesting. 

Automatic harvesting takes the help of a robot that trains using a machine learning algorithm to recognize different types of fruits and vegetables.

The robots use a computer vision system to capture photographs of the farming field and analyze the image to identify whether the products are ripe for picking or ignored.

It is possible to cultivate a much greater area for more time using autonomous crop handling systems.

Benefits of automatic harvesting:

  • Low operating cost and high efficiency.
  • Reduce the damage to fruits and vegetables.
  • A less need for manual labour.

 

#5: Crop Monitoring Systems:-

Undoubtedly, crop monitoring is a challenging part of agribusiness and incredibly consumes more time.

The advancement of technology has introduced an IoT-assisted crop monitoring system using a machine learning algorithm. 

The monitoring system can help farmers meet the day-to-day challenges associated with farming, such as soil conditions, weather monitoring, crop rotation, irrigation management, pest control, and more.

Furthermore, it can predict yield prediction, crop quality, disease detection, and others.

The agriculture monitoring system consists of a network of wireless sensors. These sensors collect data from several nodes placed on the field that further is analyzed by experts.

Benefits of Monitoring Systems:

  • Maximize productivity.
  • Reduces manual labour requirements to observe crops.
  • Minimize the use of pesticides.
  • Higher sales price.

 

#6: Precision Agriculture:

Precision Agriculture, or smart farming, has emerged as a promising solution to address current challenges in agricultural sustainability. This farming management concept is based on observing, measuring, and responding to inter and intra-field variability in crops.

Machine learning is the mechanism that drives this cutting-edge technology. The traditional farming method involves performing the same task for a large area, whereas this method uses real-time and historical data and machine-learning algorithms to make specific decisions on a small scale.

Benefits of Precision Agriculture:

  • Improves the efficiency of crops.
  • Saves financial costs.
  • Lessons on the chemical application in crop production.
  • Ensure the effective management of fertilizers and irrigation processes.

 

#7: Price Prediction:-

When defining pricing strategies for a given crop, forecasting prices based on yield rates can be extremely useful.

Every business wants to make a profit, and machine learning can help. Price prediction uses a machine learning algorithm to analyze a product or service based on its characteristics, demand, and current market trends.

Using automated price prediction, the optimal price point is determined without human input at any given time.

Benefits of Price Prediction:

  • Manage their price risk and take informed decisions.
  • Analyze multiple data sources at once.
  • Improve your profit margin.

 

#8: Health Monitoring:-

Nowadays, livestock farmers face cattle health problems around the world because of the continuous temperature rise.

The variations in temperature on animal health have harmful effects on animals and lead to various diseases.

This is the reason why you need to monitor continuously on animal health and prevent the eruption of diseases on a large scale.

To tackle such problems, Machine learning has introduced a monitoring system, that can enable you to track livestock health, activity level, and food intake, along with their health.

For businesses that are related to cows and livestock, this is one that they need the most. They can get completely new insights into how their business can be more profitable.

 Benefits of Health Monitoring:

  • Monitor the health and vitality of livestock in real-time
  • Increase productivity.
  • Prevents the possible need for medical treatment.
  • Enable farmers to quickly treat animals and prevent the spread of illness or disease.

 

How can we help you?

Gloify is a leading machine learning development company. Apart from providing services for machine learning, we provide services for other advanced technology like Artificial Intelligence and the Internet of things.

Our ML developers design intelligent solutions that can help your startup to solve multiple problems. 

If you are in the agritech business and want to implement any of the above machine-learning technology in your business, for sure, we have

that dedication and expertise that you may be looking for.

 

Wrapping Up:

Machine learning is playing a major role in the Agritech industry to optimize crop production and increase its yield with less time consumption for producing the crop. 

By utilizing machine learning, farmers can manage their resources more efficiently and produce more excellent products with less effort. 

Moreover, machine learning powers intelligent farming technology that helps farmers to keep track of their workflow by understanding where their crop requires a change, etc.

Many problems surrounding farming and food production can be solved with advanced data analysis and predictive technology. 

Machines are getting improved at a faster rate than humans, and the introduction of this technology will likely continue to improve efficiency in all aspects of agriculture.

 

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