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Top 5 ways to solve traditional farming problems

Top 5 ways to solve traditional farming problems

Traditional farming has created a huge number of problems for farmers. But we can solve these pain points by creating a new vision for farming methods. Technology has come a long way since days of traditional farming. Modern technology and new approaches have made farming more convenient, safer, and efficient. Below are top ways to solve conventional farming problems.

Gminsights says the global precision farming market is estimated to be worth over USD4 billion in 2018 and is likely to grow at a CAGR of around 15% from 2019 to 2025.

Source : gminsights

1. Stones in coffee beans 

Machine vision enhances coffee production by drying beans on a tarp, raking them up, and hoisting them into containers. When raking coffee beans, rocks or gravel quickly get mixed in. The beans need to be packaged before these stones are sorted out. If coffee beans are packaged together with stones, grinding process can break coffee grinders, causing sanitary issues. Machine vision allows them to tell items apart based on their shapes.

A camera and detector placed throughout the line can help us detect materials based on their SWIR spectra, allowing us to tell coffee beans from stones. After drying process, coffee bean vendors pack beans to be sent to coffee companies.

They use integrated vision-assisted systems to separate good and bad beans, including identifying foreign objects such as stones.

To separate good beans from bad ones coffee sorters use integrated vision-assisted systems to detect foreign objects in coffee beans. Then they use machine vision to separate good coffee beans from bad ones and remove foreign objects.

2. Moisture on vegetables

The moisture content of certain foods can significantly affect their quality and shelf life. A slightly moist surface often indicates an early stage of mold. A bruise marks a piece of fruit caused when air gets into skin. Bruised fruit or vegetables will eventually turn brown. Bruised fruit is not appealing to eye and might be overripe.

It is good to place fast cameras on a conveyor belt to improve food sorting process. The cameras will scan your vegetables and alert you if any defects are present before fruits and vegetables reach store.

When apples pass by a conveyor belt, they’re scanned using infrared and CMOS cameras. The InGaAs camera can detect skin defects that human eye can’t. The CMOS camera will show you any visible defects.

2.1.How defects in packaging are detected?

When food goes into packaging and put into boxes, defects previously discovered now detected using a CCD/CMOS industrial camera. When large volumes of consumer-packaged goods move down production process line, cameras detect visible defects in packaging, such as dents or punctures. While designing a camera solution, adding high-speed and high-resolution features is essential. A few leaks can occur underneath a package that an InGaAs camera can detect. Defective products should sorted out and not allowed to make it to store. Multiple cameras allow inspectors to examine each container’s contents and fill levels in a process line. InGaAs cameras can detect improperly filled containers.

3. Silicon Image sensors for UV-VIS

We have a wide selection of CMOS image sensors for use in food inspection, including linear arrays and area arrays. Now Using Image sensors have no complications because all the necessary signal processing circuits integrated into a chip with improvements in CMOS technology,. In food production to inspect packaging, such as labels and dented merchandise we use high-speed CMOS image sensors

4. Cameras for SWIR imaging and InGaAs detectors

InGaAs linear image sensors suit well to high-speed in-line sorting of agricultural products. They come in various wavelengths, numbers of pixels and line-readout speeds. Some linear image sensors have metal packages others come with a flexible plastic cable.

5. Almond grading

SWIR hyperspectral imaging has been in development for more than a decade, creating a new generation of food processing applications that can detect foreign objects and grade almonds or identify ingredients.

Another use of hyperspectral imaging technology is to monitor crops, produce, and even fruit. The image sensor module, a common platform for these applications with a wide range of wavelength options (e.g., up to 2.55 µm) for hyperspectral imaging, teams with dedicated optics.

The InGaAs area image sensor is ideal for SWIR hyperspectral imaging. Food inspection needs high-speed area arrays with low read-out noise and high sensitivity.


We hope above ways inspired you and can use them to create a more efficient farming system. Adapted over time to needs of your local community. We believe our planet will continue to depend on farming. So we are taking first step towards helping farmers learn how they can grow their crops and grade them. Hopefully our ways give you tools to detect unwanted objects in grains and how you can detect them.

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