Until recently, processors of fresh-cut produce have relied on labor-intensive manual inspection to remove defects and foreign material (FM). But tightening restrictions on pesticide use and the growth of organic products are making defects more common while the scarcity and cost of labor and consumers’ increasing scrutiny of fresh-cut product quality is rising. Given these market dynamics, processors are looking for methods to improve inspection.

Advancing technology and experience in other food segments have ushered in a new set of solutions. Automated optical inspection systems (also called sorters), which have been widely adopted for decades in the potato processing and processed vegetable industries, have recently been developed for fresh-cut produce. Compared to manual inspection, which is inconsistent and subjective, sorters are able to assure product quality and food safety by more effectively identifying and removing defects and foreign material, while at the same time reducing labor costs and improving operating efficiencies.


In this white paper, we will explore a wide range of sorting technology. The objective is to help fresh-cut processors understand what tools can be leveraged to maximize product quality and identify the criteria they should consider when selecting the ideal sorter for their products and applications.


Sorting Basics


From on-belt to in-air systems, sorters typically handle up to 7.5 metric tons per hour when sorting leafy greens and up to 28 metric tons per hour when sorting cut vegetables. Some sorters rely on cameras, others on lasers, and some combine cameras and lasers to view product from the top only or both top and bottom. Some sorters inspect only an object’s color, others inspect an object’s color, size, and shape, and some sort based on the object’s structural properties, including differing levels of chlorophyll. The processor’s products and business objectives determine the suitable sorter configuration.


Regardless of configuration, each sorter contains similar basic elements. The material handling component presents the product in the optimal method to the sensors. The sensors capture data, which is analyzed by the image-processing system. Defective product and foreign material are either ejected by mechanical paddles or air jets.


Although sorters are designed for continuous, 100 percent, in-line inspection at full production speeds, they can also be used in a batch-feed mode.


Cameras and Lasers and Wavelengths


The ideal sorter for any given application combines the lights, cameras, lasers, and image processing software that most effectively differentiate good product from defects and foreign material. To maximize that differentiation, it is important to identify the wavelengths that produce unique “signatures” for each object of interest. The sorter manufacturer might use a spectrophotometer on the customer’s products, defects and foreign material to see how these objects respond to different wavelengths. Armed with this data, the manufacturer will identify the ideal wavelengths or sets of wavelengths from infrared (IR) to visible to ultraviolet (UV) for the specific application and recommend the most appropriate technology to achieve the desired results.


Tri-chromatic cameras can be set to inspect within the visible range (red, green, and blue) or a combination of visible and IR or UV spectrums. These cameras capture product information based primarily on material reflectance and, depending on the image processing software, can recognize defects and foreign material based on color, size, and shape.


Sorting systems can also use lasers, sometimes in conjunction with cameras, to inspect product. Lasers are used primarily to inspect a material’s structural properties, which make them ideal for detecting a wide range of foreign material and some product defects. Like cameras, lasers can be designed to inspect only within the visible range or within the IR or UV spectrums too.


If multiple sets of wavelengths are needed to detect the range of defects and foreign material for any given product, the sorter can be equipped with multiple cameras set at differing wavelengths and/or multiple lasers or a combo-laser that simultaneously inspects at more than one set of wavelengths. Similarly, if multiple products are run on the line and each product is most effectively inspected at a unique wavelength, selecting a sorter that inspects at all these wavelengths is desirable.


Size, Shape, and Color


All sorters, even the simplest systems that rely only on monochromic (black and white) cameras, can detect differences in color (if only on the gray scale) to distinguish good product from defects and foreign material. But most sorters are capable of much more. Sophisticated color cameras are capable of detecting millions of subtle color differences to better distinguish good from bad objects. And the resolution of cameras and lasers differ with the highest resolution sensors able to detect the smallest defects and foreign material. The resolution of commonly available cameras and lasers detect defects and objects down to 3-5mm. Ultra-high resolution systems can detect defects and objects as small as 1mm.


Enhanced capabilities can be added if the sorter’s image processing software offers “object-based recognition,” enabling it to analyze objects based on size and shape as well as the location of the defect on the product, if desired. Some sorters even allow the


user to define a defective product based on the total defective surface area of any given object. These object-based considerations put more power into the processor’s hands to produce optimal product quality.


Fresh-Cut Applications


A wide range of leaf defects can be identified by sorters equipped with color cameras. If the defects can be seen on both the sides of the product, a sorter with only top-mounted cameras is effective. To detect and remove single-sided defects, and in situations where product overlap occurs at higher capacities, sorters with top- and bottom-mounted cameras are often recommended.


Defects associated with water exposure, sun exposure, chemical burn, insect damage, rodent damage, rot, disease, bacteria, and fungus, as well as problems in the outer wrap of iceberg, romaine, and cabbage due to bruise damage or wilt, can all be removed with color camera-based sorters. Typically, color cameras that inspect within the visible spectrum are most effective for detecting leaf defects in iceberg, romaine, and cabbage. Vis/IR (a combination of visible and IR) cameras are usually most effective for baby spinach and spring mix.


But much more is possible with color sorting. One processor that packs peach slices in glass jars learned that customers prefer the color of the slices to be consistent. Mix yellow and orange slices in one jar and customers perceived the yellow slices as unripe and left the jar on the shelf. This processor used color sorting to separate the slices by color. The technology allowed them to pack jars with only yellow slices and jars with only orange slices. All the jars sold well and their sales increased.


Shape sorting has been used in the processed vegetable industry for years to differentiate green beans from same-color stems and knuckles. Extend this shape-sorting capability further and consider using the technology to separate straight green beans from curved ones. Such a separation would enable the processor to package straight beans in single serve packs and price them at a high mark-up while diverting curved beans to bulk product, thus increasing the overall value of the green beans.


Processors of leafy greens such as iceberg, romaine, cabbage, spinach, spring mix, mâche, butter leaf, arugula, and oakleaf often find sorting with a combination of cameras and lasers most effective. The cameras detect leaf defects based on color while the lasers detect insects and animal parts as well as sticks, rocks, cardboard, plastic, metal, and glass, even if they are the same color as the good product, based on the object’s structural properties.


One type of laser sorter that is very effective for a variety of fresh-cut products is fluorescence-sensing laser sorters. These sorters detect objects’ differing levels of chlorophyll to detect and remove foreign material. This technology is so powerful, it can sort leafy greens and identify and remove leafy green product left over from the prior crop as well as leaves from trees, even if they have similar color, texture, and shape as good product.


Fluorescence-sensing laser sorters are also useful to some processors of cut vegetables. For example, carrot processors interested in identifying and removing carrot tops with stems remaining on the crown or even embedded in the crown can achieve this sort with fluorescence-sensing lasers.


Sorters that combine color cameras and infrared lasers can be effectively used to detect and remove core from cut iceberg and romaine lettuce, along with leaf defects and foreign material. This powerful capability allows processors to cut the un-cored head with conventional cutting technology and then use the sorter to remove the core. It enables processors to eliminate manual cutting and outer leaf removal, which reduces labor costs and improves yields. And because the core is not removed in the field, the shelf life of the product improves.


Sorter Selection Criteria


When searching for the perfect sorter for any given application, several variables should be considered beyond throughput, cameras, lasers, and wavelengths.


The value of the sorter manufacturer’s experience cannot be underestimated. Their expertise helps identify the ideal wavelengths and sensors to use to achieve the customer’s sorting objectives given the products and applications. Their expertise also guides them to consider custom-engineered product handling components that minimize product damage and sanitation features such as clean-in-place systems that minimize bacteria and


keep the sorter operating at peak performance.


Of course, the effectiveness of the sorter relies not only on the hardware but on the software – the algorithms – that manipulate raw data and categorize information based on the customer-defined accept/reject thresholds. The art and science of image processing lies in developing computerized routines that improve the effectiveness of the operation while presenting a simple user-interface to the operator. Thus, the sorter manufacturer’s expertise in developing algorithms for the customer’s products affects both the sorter’s performance and ease of use.


When comparing competitive systems, consider the resolution of the cameras and lasers because higher resolution allows the sorter to detect and remove smaller defects. Compare cameras and their ability to detect possibly millions of subtle color differences. Compare the illumination system (usually either fluorescent, LEDs, or HID), understanding that superior lighting leads to superior sorter performance.


Sorters are sophisticated pieces of equipment based on technology that advances at a rapid rate. As technology advances, the capabilities of sorters grow, which can be used to the processor’s advantage. To continue to get the most from a sorter and maximize the return on investment, look for a modular sorter that is designed to be easily upgraded, or reconfigured in the field.


Last but not least, it is important to consider the level of service a supplier can provide in a specific region – from engineering to after-sales support.


The Bottom Line


With the arrival of sorters designed specifically for fresh-cut produce, processors now have a highly effective tool for removing defects and foreign material while reducing labor costs and improving operating efficiencies. Processors that select and install the ideal sorter for their application are better able to consistently assure product quality and food safety. But most importantly, they are safeguarding their customers and protecting their brands.

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