Big data has become an integral part of various industries, agriculture not being an exception. The constantly growing food demand has forced agriculture to come up with ways of becoming more efficient, which implies getting the most out of every acre while preserving the environment. To make this possible, in the past, farmers had to assess and analyze huge volumes of data, which traditional analysis techniques couldn’t cope with. This spawned the use of such big data technologies as drones, satellites, and IoT devices in farming. All of these help farmers improve productivity by making fast and reliable data-based decisions. But what is the practical assistance all of these technologies can give? These are the main questions we aim to answer in this piece.
The Ways in Which Big Data Assists Agriculture
Big data offers an endless amount of opportunities to farmers. Here we have listed the key ones of those.
Cover Crops Monitoring
A cover crop is the common name for any crop that is planted before the “main” crop, to basically serve as a “shield” for the soil, preventing it from erosion, preserving moisture levels and nutrients content, and providing weed control. Depending on the time of planting, there are two types of cover crops: winter cover crops and summer cover crops.
When planting a cover crop for winter, the first thing a farmer needs to consider is its resistance to frosts. And with summer crops, it’s critical to pay attention to the crop’s heat tolerance and the need for soil moisture.
To make the right choice of a crop and its planting time, farmers can enjoy big data opportunities via using online tools like Crop Monitoring. The platform offers access to historical data on the weather, precipitation, and temperature to help farmers make reliable decisions regarding cover crops.
Crop Yield Forecasting
Another opportunity big data delivers to farming is the accurate yield prediction, which is possible due to analysis of data on previous yields, weather, chemical application, and plant health on a particular field to statistically build the next yield forecast.
Having the ability to predict yield, farmers can make fast and reliable decisions on crops management throughout the entire growing season and, as a result, take all the necessary measures when needed. Ultimately, they can basically “adjust” the yield thanks to the timely detection and eliminations of any issues that prevent the yield from increasing.
Ensuring Food Safety
Collecting data on temperature, moisture, chemicals, and vegetation not only helps farmers make smart decisions, but also allows for crops health evaluation. Having all the needed information on their plants, growers can predict and prevent any spoilage, improving the food safety overall. That is beneficial not only for the people that are provided with healthy and nutritious food, but also for the agronomists due to the growing popularity of organic farming and high prices for organic products.
Ultimately, one thing that unites all of the mentioned ways in which big data assists agriculture is smart farming. Let’s see what that is and what role big data plays in it.
Big Data Contribution to Smart Farming
Today, smart farming is one of the major goals that modern agriculture aims to achieve. Its main principle is the use of modern technology with the purpose to increase the quality and quantity of the grown products, while preserving the environment and optimizing the use of resources. And big data is what plays a huge part in achieving this. The key big data technologies that assist smart farming include:
- Software applications for farm management
- Weather, soil, water, light, and other sensors
- GPS and satellite monitoring
- Robotics (autonomous equipment, IoT-based solutions)
All these technologies are designed to help farmers collect and analyse data, managing the fields remotely.
Based on everything we’ve covered above, it’s easy to see that data is the major force behind it all. And the more data there is, the more effort is needed for its collection and analysis. Luckily, modern big data technologies successfully cope with these tasks, opening new possibilities for agriculture in general and for smart farming in particular.