How well-respected Washington State vertical FirstFruits Farms streamlined their fruit sizing process, optimized storage decisions, and made better-informed sales and packing decisions by utilizing Hectre’s early fruit sizing technology, Spectre Top Down.

Enhanced Storage Management. Better Informed Storage, Sales, and Packing Decisions. Time Savings. Quick & Easy Early Fruit Sizing. Highly Accurate Results.

FirstFruits Farms is a collaborative apple marketing company located in Washington State. They are known for their commitment to sustainable farming practices and for providing daycare, scholarships, and summer camps for their employees and their families.

 

The team at FirstFruits grows a variety of apples, including conventional and organic options. They operate as a single-grower system, meaning they don’t rely on outside growers for fruit. Everything they pack is grown in their orchards.

 

Initially, FirstFruits Farms used Hectre’s Spectre Hand-Held app to receive a size profile for the apples arriving at their packhouse. The app provided valuable insights, and they saw the potential for a greater impact by obtaining a larger dataset. This led to the adoption of Hectre’s Spectre Top Down app, increasing their bins sampled at receiving from four to thirty per truckload.

We spoke with Andy Zhu, the Post Harvest QC Manager at FirstFruits Farms.

Andy’s main responsibilities include determining the acceptable fruit for packing, sorting fruit for different processes such as juice production, and managing the storage of fruit in available controlled atmosphere (CA) rooms.

Why Did You Decide To Implement Spectre Top Down?

When we were initially approached about having the capability to scan bins and receive a size profile, what intrigued me was how quickly we were able to snap a photo and get results within a matter of minutes. I wanted to have that ability, but I was a bit skeptical at first, thinking, “How is it going to do all that by just scanning the top of the bin?” It seemed somewhat far-fetched, or at least very interesting.

Accurate size data in less than a minute by just taking a picture of the top of the bin? Spectre seemed a little far-fetched at first!

Being curious, and always looking for the next big thing, I didn’t want to miss out on the opportunity, so we signed up for a Spectre trial. I wanted to give Spectre a shot because the fruit industry, particularly the apple industry, is more progressive now. Things are moving along, with a more data-driven approach and technology being heavily involved. We also received a lot of positive feedback from Hectre customers using Spectre, which contributed to our decision to give Spectre a try.

Before Spectre

Before we had Spectre’s early-fruit-sizing technology, we used a manual system to assess fruit size. This method involved using information from our field manager, weighing fruit, and relying on our experience to judge the size of the fruit. Typically, as the apples arrived during harvest, we would lay bins out on the pavement and do an overview of the fruit. We would get an idea of whether the fruit was consistently small, medium, or large by looking at them. We then took notes and used spreadsheets to create size profiles for each CA room.

Enhanced Storage Management

We utilize Spectre Top Down in our receiving area to gather information about the incoming fruit bins, and ultimately to help decide which room to store the fruit in. The process begins with an apple truck passing under the Top Down camera, which provides us with a size profile for each particular variety or lot. We then create a Tableau file that records the size profile against specific rooms and lots.

Spectre’s early fruit size data allows us to quickly and effortlessly choose the appropriate CA room for a particular fruit size – eliminating any guesswork.

We aim to create a blend of different sizes within each room, as it ensures a more balanced inventory and prevents potential sales difficulties that could arise from having rooms filled exclusively with large or small fruit. Typically, we open only one room at a time, as opening multiple rooms simultaneously could lead to the fruit being exposed to regular atmospheric oxygen, which could negatively affect the storage conditions.

 

Spectre’s data helps ensure a balanced distribution of different sizes, while also providing valuable data to help identify the CA room we should open when we are looking for a particular fruit size. It helps eliminate the need for guesswork in determining what’s in a room, making it a valuable tool to have when making these storage decisions. Additionally, we can break down Spectre’s data by receiving dates to identify any inconsistencies or differences in sizing related to the date the fruit was received.

Time Savings

Now that we have Spectre, I can easily open the Tableau file containing Spectre’s dataset, look for a specific room, and get a general overview of things. The dataset generated by Spectre is already in a CSV file, which means I can easily import it and then create a worksheet for myself. This is more efficient than scrolling through a spreadsheet and looking for a range of sizes. Instead, I now have a breakdown of the percentage of each individual size in a particular bin, making the process more efficient.

Having Spectre’s data already in a CSV file allows for easy importing, making decisions around storage even easier.

Before Spectre, it would take me up to half an hour to go through the rooms and with my spreadsheet get an idea of the sizing in each room. With Spectre’s data and the Tableau worksheet, I can now go through that information in about five minutes.

Spectre provides me with a breakdown of the percentage of each individual size in a particular bin, which saves me time every week.

Better Informed Sales Decisions

When there is market demand for a particular size, the sales team may ask for information on the size profile of a particular variety. We use the data we collect with Spectre for making informed sales decisions, particularly when it comes to promotions.

Spectre’s data simplifies sales decisions, quickly locating fruit sizes for targeted promotions and campaigns.

If a marketing campaign requires specific sizes, Spectre’s data helps identify the room that is storing the required fruit. By analyzing the data for a specific CA room and considering the number of bins in that room, the team can gain insights into how many boxes of a particular size will be available. This information is then shared with the sales staff, who can compare it to the requirements of the promotion.

Supporting Packing Line Decisions

We generally have one packing line dedicated to larger fruit and another for smaller fruit due to their different capabilities, such as bagging and bulk filling or tray packing. We use Spectre’s data in tandem with manually evaluating the consistency of the fruit before we run it. By combining Spectre data with our visual assessment of the bins, we are able to make better informed decisions about which packing line to use for the fruit.

Next: Spectre for Cherries

With the success of Spectre for Apples, and with the expectation it will be just as beneficial, we will soon be implementing Spectre for Cherries in our packhouses. If Spectre for Cherries proves to be as effective and beneficial as it has been for apples, it will be another fantastic addition to our process.

More than satisfied with Spectre for Apples, we expect a similar impact when we implement Spectre for Cherries later this year.

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