Smart Vision: Accurate Potato Defect Detection using X-Ray Cameras
Accounting for a quarter of all fruit and vegetable production in the United States, potatoes are one of the most important crops globally. That’s what makes the potato processing industry, involving the optical grading and sorting of all the potatoes consumed, one of the world's largest.
Defect Detection
Unfortunately, millions of dollars worth of potatoes and other root vegetables are wasted annually in the US because of their defects. Anyone in the agricultural processing industry knows grading is necessary to detect these defects and reduce the amount of crop loss. However, they also know that time equals money, and with the demands of today's hungry consumers, produce processors also know that efficiency and accuracy are a must— and something human hands can't keep up with.
Potato sorting and grading is a high-stakes process for potato farmers, who must ensure that their potatoes are of the highest quality, , sizes and shapes, and are disease-free for . This process has been traditionally done by hand. However, technological advances such as , , in conjunction with digital cameras, and x-ray technology within the agricultural processing and farming industries have replaced much of the human labor spent in potato processing.
Read on to learn more about using cameras and x-rays to grade and detect defects and how you can implement x-ray cameras and other high-tech optical grading systems in your potato processing warehouse to reduce waste and increase productivity while keeping costs down.
A Brief History of the Potato X-ray Camera
Potato grading is a process that has existed for centuries, but it wasn't until the early 1900s that scientists began to develop ways to automate the process. The first machine used an X-ray source and film to capture images of potatoes. This technology allowed potato graders to see inside a potato without cutting it open and damaging its flesh.
In the 1920s, using a screen instead of film improved x-ray technology, making it possible to view an image of the potato immediately instead of waiting for processing time before seeing what was inside it. In addition, this technology did not require as much light or electricity as earlier models required.
By the 1940s, advances were made on these machines so that they could take multiple pictures at once with different focal points. With these advancements, all potato parts could be photographed from several angles before being graded based on appearance alone rather than just size alone.
Potato grading technology has evolved and continues to be a major area of focus for growers and processors alike. With the advancement of in the produce-processing industry, potato cameras and x-rays are sharper, more intelligent, and more accurate than ever.
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Optical Grading and Sorting
The camera’s x-ray vision combines optical grading and machine learning to look inside of potato and detect defects such as internal rot or insect infestation. Potato grading cameras are typically mounted onto a forklift and are used to inspect large quantities of potatoes.
What processes happen when grading potatoes with cameras and x-ray?
Step 1: The potatoes are placed into a machine that uses x-rays to image the internal structure of the potato. A machine operator then grades the potatoes based on their shape, density, and coloration.
Step 2: A camera then captures an image of each potato's surface and coloration. The camera allows for detailed analysis of these characteristics that weren't detected with an x-ray alone.
Step 3: Finally, these two sets of images are compared and analyzed by an expert who grades all potatoes as "Grade 1," "Grade 2," or "Grade 3."
X-ray imaging for hollow heart
Imagine looking at a potato and determining if it had hollow heart or not BEFORE slicing it open. That's precisely what an x-ray camera with artificial intelligence could do for the nation's potato farmers, who deal with up to 15% of their crop being wasted from hollow heart each year.
It's important to note that using cameras and x-ray for grading is not necessarily the same as using them to detect hollow heart with the exception of the, which is integrated with the visual grading system.
The other benefits of the Bantam Vision Hollow Heart X-ray are:
- Simple controls
- Proprietary cooling and temperature monitoring system on the x-ray tubes
What to look for in potato grading and sorting x-ray camera technology
As we've mentioned before, using technology for a high-speed grading and sorting of produce isn't anything new, but produce processing machinery is quickly adapting and innovating to meet the demands of consumers. But, not all machinery and technology are equal.
When choosing the best x-ray camrea technology for a potato grading, you should look for one that has the following features:
- A high-resolution camera: The higher the camera's resolution, the better it will reveal defects in your potatoes.
- A large display screen: This allows you to see the images clearly so that you can ensure that they are being graded accurately.
- A user-friendly interface: Warehouse managers and operators aren't all trained in complex technology, so the interface should be easy to learn and operate.
Not many companies can offer all of these features, which makes the a step above the rest.
How is the Bantam Vision Grading System different from traditional systems?
Traditional systems require a lot of time and effort to set up, which makes it hard for companies to use them in their daily operations. The Bantam Vision Grading System uses artificial intelligence and x-ray technologies as an -all-in-one system for grading and sorting produce, particularly root vegetables like potatoes.
The Bantam Vision Grading System is different from traditional systems in the following ways:
- The Bantam Vision AI System is easy to use and understand. It can be integrated into your workflow quickly, so you don't have to stop what you're doing to learn how the system works.
- The system works by comparing a potato image with thousands of images that it has already seen before. It then determines which of those images most closely matches the one being analyzed.
How exactly does the Bantam Vision Grading System work for potato grading and sorting?
The Bantam Vision Grading System Process:
- The Bantam Vision AI System uses deep learning algorithms to process images taken by cameras installed in potato grading and sorting machines.
- The x-ray cameras detect internal potato defects and uses this information to operate the potato sorting process.
Using this process, Bantam Vision AI can track each potato's condition as it moves through the optical sorting and grading process so that it knows whether a potato is good enough for sale or needs further inspection by an employee.
Bantam Vision's deep learning architecture allows it to learn from the ground up and understand the complex nature of the crop, from leaf to table. Bantam Vision Grading System's neural networks analyze high-resolution cameras capturing photos.
Produce warehouses that have implemented the Bantam Vision Grading System have reported:
- The reduction of up to 60% of labor costs
- Consistent sorting
- Reliable grading
- An average of 98.5% cull line accuracy
- Increased output
Watch how the Bantam Grading System works 👇
As you've probably gathered, agriculture and production processing technology is here to stay; it's getting smarter, faster, and more agile every day.
Implementing an all-in-one AI grading and optical sorting system, like the Bantam Vision AI system, into your warehouse will provide a consistent, quality product to your consumers, increase efficiency, and decrease human error and product waste.
Want more for your potato processing needs? Pepper Equipment Co. has custom artificial intelligence, machine learning, and automation solutions in grading, sizing, packaging, palletizing, and washing for any size of potato warehouse. We consult, install and maintain Pepper-provided equipment.
today for more information.