Machine Vision in Agriculture: New Technology and Trends

machine vision in agricultureDemand for food is outpacing agricultural production capacity, making farmer’s jobs more and more difficult as they try to maximize yields. According to the World Bank, the global population will require about 50% more food by 2050 to feed nearly 9 billion people.

This means agricultural practices need to improve dramatically to keep up with demand. With investors, integrators, entrepreneurs and manufacturers all seeing major potential in the agricultural industry, farming practices are undergoing a major automated revolution.

What’s New in Machine Vision and Agriculture?

Machine vision has actually been deployed in the agricultural industry in one form or another for almost 20 years, but  the renewed focus and profit-potential in the industry are swiftly advancing machine vision capabilities.

Mainly, advances in microprocessors and high speed data transmission – primarily in embedded and smart vision systems – have enabled all new levels of automation and insight into farming practices that can lead to higher efficiency and better crop yields.

New Machine Vision Applications in Agriculture

Machine vision is being deployed in a number of different ways in the agricultural industry, but there are a few ways that have proved particularly revolutionary.

Drones have proven extremely useful for farmers. Nearly 80% of drone sales go to the agricultural industry. Machine vision systems and drone technology make the perfect match for applications like monitoring crop health. 

For example, hyperspectral or multispectral machine vision systems embedded in a drone can monitor the intensity of light reflected in two different frequencies to determine the normalized vegetation index (NDVI) to make an accurate determination of crop health.

Machine vision can also be used for things such as automated harvesting, where vision systems detect and harvest only healthy crops that are ready for picking, and can even determine optimal times to perform additional rounds of harvesting to reduce the amount of crops left in the ground at the end of the season.

Machine vision can be used in many different ways in the agricultural industry – the above examples are just a few of the methods farmers use to improve their processes, just like any manufacturer would.

It’s vitally important that the agricultural industry adopt cutting edge technology to realize maximum crop yields and improved process efficiency. Machine vision is playing a major role in farmers’ ability to bring agriculture into the 21st century.

To get a deeper dive on this subject, visit our educational section on Agriculture and Machine Vision.

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