The fresh produce packline is a powerful tool for objective, physical sorting, but it is a reactive instrument. Its settings and operational decisions are a response to a complex web of market forces, business logistics, and quality standards that often exist outside the machine's view.
While the optical sorter is the "brain" of the packline, its decisions are deeply influenced by external factors that it cannot "see" or measure. These are primarily driven by the business of selling and distributing fresh fruit. Packline operators have the very difficult task of balancing quality and inventory realities with sales team and market demands.
This article is the first in a two-part series where we'll outline the main factors influencing how a piece of fruit ends up in the box it does, and some of the ways decisions about packing can be improved with more quality data prior to packing.
What the packline cannot “see”
Many of the factors that influence how a piece of fruit or vegetable ends up in a specific box have little to do with what the packline can “see” or “know.” This information is organized and taken into account by packline operators when planning packing in order to put the right fruit in the best package to improve profit margins.
Market and sales demands
The packline's settings and priorities are constantly adjusted to meet specific market demands. What is on order or promotion now? Packline drops or outlets are determined in part by incoming demands from the sales team and planned campaigns from the marketing team. Specific buyers often have strict requirements for how the fruit is packaged which will dictate the flow and setup of the packline. Some of these things need to be planned months in advance when the season contracts are being signed, and indeed they often need to be in order for packaging materials to be purchased in time and the right quantities, but the packline operator must often also be able to accommodate last minute changes to orders.
Packing Configurations
When a buyer orders for a retailer who only accepts a certain grade, the packline is adjusted to create this specific grade of fruit. For example, a supermarket chain might have a contract for "Extra Fancy" apples in a specific carton count (e.g., 88-count). The packline operator will program the machine to be more selective, setting tighter tolerances for color, size, and defects. A packline might be set up to pack fruit into:
- Pre-packaged bags (e.g., 3-pound bags for retail)
- Custom trays (e.g., a 4-pack of large peaches)
- Loose cartons for wholesale (e.g., 88-count)
In the context of fresh fruit, a "carton count" (or simply "count") is a standardized method of sorting and packaging fruit based on the number of individual pieces that will fit into a standard-sized shipping container, typically a cardboard carton or box.
This system is particularly common for fruits that are graded and packed individually, such as apples, pears, peaches, and citrus fruits. It is a crucial part of the fruit industry's supply chain because it provides a reliable, uniform way for buyers (retailers, wholesalers, and processors) to order, sell, and manage inventory. A retailer can order a pallet of "88-count apples" with the assurance that every box will contain 88 apples of a very similar size. This makes it easy to price products and create uniform displays.
Logistics and supply chain issues
Logistics and post-harvest handling are critical variables the packline cannot account for and require the coordination and communication of many parts of the supply chain. The origin of fruit being packed, the storage and shipping history before it arrives to be packed, and its ultimate destination will all impact how fruit is packed.
Shelf Life and Transportation:
A fruit intended for a long-distance shipment (e.g., by sea freight) will have different packing requirements than fruit for a local market. The packline doesn't "know" its destination. However, the packing operator will need to adjust the settings to ensure that fruit for a long journey is slightly less ripe and of a firmer texture to withstand the rigors of transit and have an adequate shelf life at the destination. Linking shipping destinations to packing planning better informs pack line operators, ensuring quality at its destination.
Controlled Atmosphere (CA) Storage:
The packline doesn't "know" if the fruit it is sorting has just been harvested or if it has been in cold storage for six months. This is a critical factor. Fruit that has been in CA storage has been held in a low-oxygen, high-carbon-dioxide environment to slow down ripening and respiration. It comes out of storage in a firm, under-ripe state. The packline's color and firmness sensors need to be recalibrated to handle this.
Additionally, in long term storage facilities at harvest time, the opening and closing of rooms is a complicated and logistically challenging process. Both the opening and closing of a CA room take a lot of time and expensive resources. Pre-planning is required and it is a costly mistake to have to re-seal a room that does not have the fruit required in it for an order. Knowledge about what is in a room when it is closed greatly enhances a pack line operator's ability to coordinate inventory movement for the best packing outcomes.
Traceability and Lot Management:
The packline itself is a big part of the traceability process. Every box or pallet must be tied back to a specific lot number, grower, and harvest date. This is a key food safety and quality control measure. The packline's computer system must be given this data by its operators and be able to report back nearly instantly the history of pack lots in the event of a recall or audit.
Lot traceability is key often in grower payment processes as well. Sometimes a packline is paused and re-started to ensure that a new lot of fruit is not mixed with the previous one. However, packing operations who source from smaller growers may need to combine incoming harvest lots from various growers to create a pack lot large enough.
When the grower payment is based on packed fruit quality and quantity, a packline operator must be able to account for the ratio of what each grower contributed to the packed lot totals.
Internal quality
The biggest factor influencing how fruit is packed is of course quality, and there's a significant part of fresh produce quality that a packline is unable to “see.” Despite its advanced technology, there are crucial quality attributes that are invisible to the packline's cameras and sensors.
Taste, Flavor, and Aroma:
The packline can measure ripeness by proxies like color and firmness, but it cannot measure the subjective qualities of a fruit's flavor, sweetness (Brix level), or aroma. These are typically measured by a human quality control team who perform destructive testing on a sample of fruit from each lot. A packline will not sort fruit based on taste, but a buyer's decision to re-order from a grower will be heavily impacted by it.
Dry Matter and Internal Sugars:
While some advanced NIR systems can measure dry matter, this is not a universal metric. For fruits like kiwifruit or mangoes, the dry matter content is a key indicator of quality and how well the fruit will store. This is often measured manually or with separate handheld devices before the fruit even goes onto the packline.
Juiciness and Firmness (Beyond Surface-Level):
While optical sensors can measure surface firmness, they may not be able to detect the nuanced texture of the fruit's flesh. A fruit could appear firm on the outside but be mealy or dry on the inside. This is another area where human inspectors and destructive testing are essential.
Most packline operations will rely on the quality control and receiving teams to gather and provide this information on available inventory so it can be grouped and packed appropriately.
The factors that truly influence a packline's decisions are often invisible to the machine itself. Market demands, logistical constraints, and critical internal quality metrics all exist in a world the sorter cannot "see." The human operator is the bridge, synthesizing this external data to guide the machine's output. In our next article, we will examine what the packline can see—the physical attributes it measures—and how a more data-driven approach to the entire packing process can transform a reactive operation into a proactive, profitable strategy.
