Each year, roughly two million beehives are trucked in to California for almond pollination. Do you ever wonder where all those bees are actually coming from? Well, you may be surprised to learn that not only do they head down from the summer honey haven of the Dakotas, many hives begin the trek from as far away as Florida! Now, Florida’s a hefty 2,900-mile road trip away from California. That’s a long way to go!
Most of the bees get loaded up for shipment in the fall, just before the weather gets too cold and the bees shut down for the winter. Beekeepers will do some last minute "quality assurance" checks to make sure only the best bees make the journey out west. Those who don't reach the Golden State before Christmas will take part in a mad rush to get them dropped in the orchards in time for the almond pollination.
Bee trucking math
For the top ten states that ship bees to California for almond pollination, it can cost anywhere from $1,360--if you're coming from nearby Oregon--to over $8,000! Floridian beekeepers enjoy one of the country's best climates for keeping bees, but they dish out the big bucks to truck their bees for pollination. And that’s just a one-way ticket.
Not only do beekeepers in Florida have to pay extra for their bee transport, but they also need to carefully navigate strict state laws governing interstate bee travel. Bee Culture recounts a tale of how one Florida beekeeper got himself in trouble over all the red tape involved.
Despite the high cost, bees are still being sent from Florida out to California each year because the high pollination prices are still worth the trucking expense. But as the supply of agriculture truckers continues to dwindle, that may not be the case any longer. Uncertainty over new regulations like the Electronic Logging Device Mandate (ELD) left some beekeepers wondering whether the cost of trucking would spike. For now, agriculture truckers are exempt from the ELD mandate and Hours of Service limitations, but who knows if or when that may change.
It's just one more thing to keep an eye on as the almond industry continues to grow and the logistical challenges become increasingly strained.
For the final post in our series covering our new direction (links to part 1 & part 2), I’d like to share my thoughts on how it all went.
Our team spent months planning out every meticulous detail to deliver Verifli to our customers. Since pollination season last just a few short weeks, we had to work around a very small window with no time for mistakes. If you’ve ever experienced a product launch, you know there are a lot of emotions involved, whether you’re the customer or the one launching the product.
For me, it was interesting to reflect on what the experience felt like before, during, and after product launch. Here are some of my quick journal-entry style notes:
By the numbers
To wrap up, here are some eye-popping stats from our 20-day stint in California:
Last week, I wrote about why we decided to pursue a new direction. Now I want to give you a behind-the-scenes look at how we did it. Strap yourselves in, this one’s a bit longer than usual.
Our “Aha!” moment was liberating, but it introduced a new set of challenges. Almond pollination only happens once a year, and at the time of our “Aha!” moment, the next pollination season was less than 10 months away. We had to get something out there, otherwise we’d wait 22 months until bringing new revenue in the door.
With less than a year to build something our target market was willing to pay for, we had to focus. As much as we wanted to develop that beautiful product we envisioned, complete with all the fancy bells and whistles, there simply wasn’t enough time.
We couldn’t afford to be good at all the things—we had to be exceptional at one or two important things. We narrowed in on two guiding principles: the product had to be accurate and it had to be faster than manual inspections.
Much of our time during the development phase was spent on customer discovery. We found a handful of almond growers who weren’t annoyed by our monthly phone calls. These folks were our sounding board. They would tell us if we were still on the right track or whether a course-correction was needed. Ultimately, we had to strike a balance between what they told us and what was achievable.
Accuracy is our first guiding principle for a good purpose. If it’s not accurate, it doesn’t matter how fast the product works. Before we began to think about building speedy software, we started outlining the predictive hive strength model.
The first step towards building an accurate model is to gather data. From May to November, several times a week, we’d set out at the crack of dawn to image hives under infrared. Over the course of this time, we’d end up capturing tens of thousands of infrared images. But it wasn’t as simple as taking a photo and moving on. There were a lot of variables to test in order to find what produced the best results.
That leads into a story about one of my wildest experiences in my 3+ years with The Bee Corp. In order to test the accuracy of our model over time, we conducted a handful of "marathon" data collection studies. This entailed capturing IR images of the same hives every few minutes over the course of several hours.
One muggy summer night, I was tasked with doing a marathon study all by myself from dusk to dawn. I loaded up Ellie’s car with enough sugary snacks and Red Bull to cause a heart murmur and set out to our bee yard tucked away in the rolling hills of Southern Indiana. No cell reception, no WiFi signal, no escape from the dense humidity; just me and all the bugs you can imagine.
I wish I could say it was eventful. It wasn’t. It became a dreary routine: pause my podcast, turn on the camera, grab my flashlight, exit the car, take photo 1, photo 2… get back in the car, shut off the camera, play my podcast for 10 minutes and repeat. By the time the sun came up, there was a visible rut in the grass from tracing the same path 50 plus times that night.
The worst part honestly wasn’t even all that bad. Running on 20+ hours without sleep and with tablespoons of sugar and caffeine coursing through my veins, paranoia set in rapidly. Anytime I heard a strange noise in the woods, I was certain an axe murderer or a grizzly bear was just steps away. But I had a secret weapon: my infrared camera. Equipped with the superpower of night vision, I had confidence that I’d be able to get the jump on any bears looking for a quick snack.
A fun note: I ended up doing 2 overnight marathon studies, once in August and again in October. The second time was during Game 3 of the ALDS—and I’m a HUGE Red Sox fan. In the middle of the woods I was somehow able to tune into Nate Eovaldi and the Sox dish out the most lopsided pounding in Yankees postseason history 😊.
Thanks for sticking through to the end on this one. I hope you enjoyed it. Check back next week to read about Ellie’s takeaways from the February launch.
Last month signaled the climax of nearly 10 months of radical change for our company. In February, we launched our new product: an infrared hive grading solution called Verifli.
This was not your typical product launch. We didn’t send out endless email blasts begging everyone and their mother to try our shiny new thing. We didn’t make a media push to reach millions of eyes. We didn’t slap any sexy branding around it.
In fact, we hardly made much noise at all. We kept our heads down. If you’ve only been following us publicly, you probably have no clue what our company even does anymore. Well, we’re writing this to catch our faithful followers up to speed.
Around last May, our team had a collective “Aha!” moment. In the months leading up to that lightbulb flash, we worked tirelessly trying to figure out how to scale our company, our technology and obviously, our bottom line. We landed on almond pollination.
Each February, three quarters of the nation’s beehives are shipped to California, where 80% of the world’s almond are grown. Over 2 million beehives congregate in California’s Central Valley to pollination roughly 1 million acres of almond trees. At an average fee of $200 per hive, beekeepers in the US gain a healthy influx of cash early in the season while their bees enjoy a head start to the year.
But there are a few key issues. Although bees don’t “hibernate” as we usually think of it, they close up shop for the winter—shutting down the queen’s egg laying, booting non-essential bees from the hive, conserving nutritional storage and clustering tightly to retain heat. Since many big-time bee operations are located in areas with harsh winters, most beehives are at their weakest point in the year around the start of almond pollination.
But the best pollination comes from hives that are in mid-season form, not fresh out of spring training. To compensate for this, growers reward the beekeepers who can build hives to mid-season form by paying top dollar for strong bees.
But this highlights another key issue: the only one way to verify that you’ve got strong bees is by cracking hives open and checking. If you rent thousands of hives, this process can take days, perhaps longer if the weather doesn’t cooperate (like this season). What’s worse, a strong hive can contain anywhere from 10 to 15 THOUSAND bees. There’s simply no way the human eye can distinguish an 11,000-bee colony from a 14,000-bee colony—but there’s a significant difference in terms of pollination output. At the end of the day, an inaccurate hive strength assessment means someone’s leaving money on the table.
Now, to break up the wall of text, here are some amazing photos from our first pollination season (photo credit: Deftly Creative):
We saw this disconnect between beekeepers who are doing everything they can to build strong hives and growers who are willing to pay whatever it costs to get them. We figured there had to be a better way to reconcile their interests and evoke transparency and understanding.
We decided to develop a product to help growers and beekeepers measure the strength of their bees faster and with greater accuracy and objectivity. Our product, Verifli, uses infrared image analysis to map out the heat signature given off by the bees. Using physics and data science paired with real-time weather information, we can deliver an accurate assessment of each beehive with a single infrared photo of the outside of a hive.
With Verifli, there’s no last-second panic when a beekeeper finds high winter losses in mid-January; he can check the bees throughout the winter and give a heads up to his grower if they need to rent extra hives. With Verifli, a grower can set up a true incentive program to reward his beekeeper for every high-strength hive, not just what they find in a 10% sample. With Verifli, a grower can know exactly which parts of the orchard have low-strength hives, so he can shuffle around pallets to maximize pollination.
Our goal with Verifli is to foster transparency. Growers and beekeepers depend on each other— and for the most part, they share similar goals. By creating a common language around how we measure pollination, we hope that Verifli can become a resource for growers and beekeepers to communicate expectations and avoid conflict.
Now that you see the rationale behind our decision to pivot, I want to tell you about how we came up with a plan to launch a product in under 10 months. Check back next week for part 2!
Hey readers! It’s been quite a while since my last update. Hope you’ve all had a great start to your 2019! For the growers out there, I hope your pollination season hasn’t been bogged too much by all the rain. We’ve been quite busy here at The Bee Corp with the launch of our digital hive grading product, Verifli. Speaking of hive grading, let’s talk frame counts.
How we measure colony size
For those of you not familiar, frame count is the metric used by growers and beekeepers to measure the population size of a hive. The concept is simple enough: if seven of the frames inside a hive are covered by bees, it’s a seven-frame hive. The tricky thing about this method is accuracy. A single deep frame supposedly holds about 1,500 bees. But what if the frame is only partially covered by bees? What if they’re only covering one side of the frame? What if it’s a medium or shallow frame?
Then there are other factors like weather and timing. What if it’s peak flight time and 1/3 of the bees are out foraging? What if it’s a little chilly and the bees are clustered tightly? What if I've done hundreds of frame counts today and I can't really distinguish between a 6-frame and a 7-frame hive anymore?
As a data scientist, all these variables troubled me as Wyatt and I collected more than 500 frame counts last summer.
A better measure... using SCIENCE
I hereby propose a new way to measure frame strength. Over are the days of ripping open hives, slaving over frames overflowing with bees, with the succor of smoke to yield the path! Now is the time for innovative methods to claim their rightful seat to the throne!
Aside from sounding like the ramblings of a madman, hear me out. Remember, quite a while ago, my post about how hot a bee is? That, as it turns out, is around 30-38 degrees Celsius. That got me thinking: we know there are roughly 1,500 bees on an average deep frame. We know the general heat output of an individual bee. Why not calculate colony size in terms of energy output?
How to measure bee energy
I propose a new unit of measurement for frame strength: the Bee Power Unit (BPU). Since we know how many bees we expect in an average healthy hive, and we know the average energy output of a bee, we’re able to calculate the average energy output. However, we’re not interested in some theoretical average, we want concrete details. How many bees are in that hive?
But how does one measure energy output? Which technology do we even use? If you've been following us this past year, you may already know the answer. Everything in the universe emits Infrared radiation, which is the heat energy output that can be measured with an infrared camera. Simple enough? Well, there’s a little more to it then that... Next time, I will be exploring infrared and how we can use technology to outclass the human mind.
Check back shortly for my follow-up post on this!