5 problem areas in a greenhouse that can be optimized by data
After talking to more than 30 greenhouse growers, I could see a pattern of common problems among the greenhouses. And the interesting part is that they already possess the means to solve these problems. They are still facing these problems because they don’t know that the data they are collecting on a day-to-day basis has the solution hidden in it.
Traditional industries like logistics, construction, maintenance, agriculture have seen a huge uprise after switching from legacy style operation to a more data-driven approach. Greenhouses are no different to that. A greenhouse is only mimicking a natural environment. And you need the right information to create the best environment for your plants to thrive in.
In this post, I will cover the problems associated with the 5 major areas in a greenhouse and how it can be optimized to run more efficiently by using the data, the growers and the management are already collecting on a daily basis.
Labor Training
One of the biggest problems I saw while talking to those greenhouse growers was that on average it takes 2–3 years for a new grower to get familiar with the growing style and get completely integrated into the growing operation. Not only is the greenhouse spending money to integrate the new employees, but there are also other senior employees who are putting more effort into training those new employees. Comparing that to a software company, it takes 2–3 weeks to completely integrate a new employee.
I know! I know! Building software is not equal to growing plants in a greenhouse. Growing plants is a much more laborious and challenging task compared to writing codes while sipping a cup of coffee.
I am not comparing software to growing plants in a greenhouse. But what I am saying is that the way the software companies document their data and information helps a new employee to get integrated quickly into the working process. It will definitely take more time to onboard a new grower, but it shouldn’t take years.
Now you will ask me, well how does that information apply in a greenhouse scenario?
Greenhouses are collecting a lot of data each and every day. They collect information regarding their irrigation process, soil mix, plants at different stages, insect count, Ph, EC, temperature, humidity and the list goes on. If growers can take that information and create standardized documentation of all data, not only are they making that data valuable to make a short term decision but also valuable enough to train new growers for years to come.
Recently, I came across the growing practices of Jennifer Webber, head grower of Rambo Nursery, where she has documented 22-years of growing experience into a handbook and every new grower that walks through the door of that greenhouse, gets this handbook to start. The practical information regarding growing plants, specifically in Rambo Nursery, makes Jennifer’s handbook more valuable than any other theoretical textbook.
A centralized grower platform can take all the information that the growers are currently collecting and consolidate into a central repository across a growing cycle. Greenhouses can then take that information and automate the creation of grow journals (the equivalent of Jennifer’s handbook). Using these grow journals, new growers can rapidly acquire knowledge regarding how that particular greenhouse is growing a plant.
Unit Economics
Every business has an eye on their unit economics to figure out if they are making a profit. And greenhouses are no different from his practice.
In basic terms,
Unit Economics = Gross Revenue - Production CostAs you can see, we can either increase the gross revenue or decrease production costs. Or do both.
Let's not get too ambitious now. Or can we! Let's see ….
The production cost comprises of labor, nutrients, electricity (fans, grow lights), heat, water, soil mix, growth regulators, etc. can optimize one or more of these factors, significantly bringing down the production cost. On top of that, growers can also use the operational data to optimize the performance of the crops. Doing that, they are automatically growing higher quality plants and increasing their plant count by decreasing plant loss. Both of which add significantly to the gross margins.
This is a photo I took at the farmer’s market which shows that ugly tomatoes are priced at 50% the cost of a higher quality tomato. By increasing the plant count on the pile of higher quality tomatoes, you are instantly increasing your gross margins by 50%.
But I promised you, that we will increase the unit economics, which means, the production cost needs to be lowered.
To decrease the production cost, one or more of the factors that contribute to the production cost need to be optimized. And the biggest factor contributing to production cost is electricity. Climate control and heating play a vital part in mimicking the natural environment.
Jeff Brower, Co-owner of J&N Greenhouses, uses data to track his return on investment over time. He uses weather data to predict the number of cold days and solar gain days and then compares that data to his historical heating data, to predict his expenses on heating for a certain growing cycle. Not only can he plan in advance, but he can also tweak his production planning to put all the plants, requiring high heat, in one greenhouse, thereby saving on heating expenses.
Growers can use historical climate control and heating data for the plant and correlate it with the weather forecast to get a weekly prediction for electricity consumption. Growers can also take advantage of time-varying electricity rates by correlating their light usage with the electricity rates and plant requirements. Greenhouses can save more than $50–70k/year by optimizing their energy usage.
Production
The core engine of a greenhouse is production. Plants growing at scale, detailed plant scouting, daily harvest are some of the key tasks driving the engine of a greenhouse.
As a grower, it is their sole responsibility to provide the best of conditions, for the raw materials like seeds, soil mix, and nutrients to perform and flower the best quality plants. And the less you know about what you are doing wrong, the more likely you are gonna do it again. You need to see the problems in order to solve it.
So how will a grower know more about his/her operation than he/she already knows?
Greenhouses can use years of historical data on soil mixes, plant roots, temperature, humidity, soil ph, and many more, that they have been collecting, to identify the operational frailties when X condition occurs. As a result, growers can take proactive action to prevent the problem when the data starts showing the occurrence of condition X.
Last month, I met a greenhouse grower, who is growing tomatoes hydroponically and collects ph, EC, temperature and humidity data on a regular basis to keep track of the nutrient composition of the water. He is also sending the plant samples to the laboratory to get the information of micronutrients in the plant leaves. But as the data is scattered across different notebooks, it is hard for him to correlate the information among each other and find out the right decision to make. As a result, there is a loss of money and plants.
If he takes all that data, documents it on a centralized data platform and then tries to correlate the ph levels with the nutrient usage, he can instantly find the pivot points in his nutrient usage which creates an undesirable ph scenario for the plant and leads to tomato loss.
We are killing two birds with one stone. Not only is he saving tomatoes and increasing his revenue, but he also can optimize his operational practices which increases the efficiency to grow a more high-quality crop.
Ben Blake and Marley Lovell, Co-owners/cultivators, Esensia Farms, tell that data can help you plan for the future. They are cannabis growers and have seen a huge improvement in their planning and production efficiency, once they started creating a centralized database for their data and use that data in making future decisions.
We input all these things for each strain over the course of the season. We mark when they get planted, when they are given nutrients and what nutrients they’re given, take notes on recipes, note when they’re pruned, when we support a plant, when things are harvested. We’ve been doing that for years, and it’s allowed us to see … a profile — or like a graph — that can be attributed to each strain.
This a quote from Ben Blake in an article covered by Jillian Kramer of Greenhouse Management. This article covers the testimony of four cannabis growers regarding the benefits they saw after creating a data-driven decision-making culture at their greenhouse. I highly recommend to check out this article.
Plant Trials
Every grower does trials before adopting a any new product into production. It can be a plant, seeds, soil mix, pesticide, herbicide, etc.
But does the grower actually takes full advantage of the trials? Can the grower say hand-on-heart that the product will perform exactly the same in production like it did in trials? Let’s find out….
Some growers will trial the plant from seed to harvest on a single setup and then validate the harvest quality and move on to accept/reject the plant for the production. If the harvest was at par or above their expectations, the plant is accepted else, rejected. Now, the problem with this kind of evaluation is that the production setup is incoherent with the trial setup. In general, growers tend to compare apples to oranges while trialing and that creates a mismatch in the results you get while trialing a plant and growing that same plant at scale.
Now you will ask me, what do you mean by comparing apples to oranges?
For example, a grower is using a soil mix with a water retention capacity of 40% in production and trialing a new soil mix with a water retention capacity of 60% percent. If both soil mixes are growing the same plant and are watered equally, the plant in the trial will suffer from overwatering. Ultimately, the harvest results will show that the growing mix is not suitable to grow that particular plant. But, the reason behind the bad result was that the grower watered the plants incorrectly without taking its water retention capacity into consideration. The harvest comparison data will not show incorrect watering. Hence, the soil mix will be rejected by the greenhouse.
I can’t tell you if the harvest will be of high quality if the watering was done correctly taking the water retention capacity of the soil mix into consideration. But what I can say is that the raw materials are not always at fault, we also need to look at our practices in evaluating them.
This is where having consolidated data of plant characteristics, soil characteristics, watering practices, water usage, climate conditions, etc in one place from production and trial can help the growers correlate information between different verticals. Even though the final score was low for the new soil mix, growers can easily see a mismatch in their irrigation practices. On top of that, a correlation of factors like ph, EC, soil temperature, will provide a robust evaluation structure for the grower before accepting/rejecting a new product.
If you want to know more about plant trials, this is a great article by Peter Konjoian, President of Konjoian’s Floriculture Education Services Inc.
Supply Chain
The most important part of any business is sales. You can build the best quality of products, but if you are not selling then your business dead in water. So, we need to make sure the plants are getting to market in the best of conditions and we are earning the best bucks for our high-quality products.
How can greenhouses use the data they have been collecting, to improve their supply chain management?
Greenhouses send produce and flowers to long distances before they are actually sold to the consumers. And there are many factors that influence the pricing of the market, pricing of the logistics and the purchasing decision of the consumers. Greenhouses have been collecting these data for years now. It is time to use some of those data to get ahead in the game.
What sparked this scattering wildfire of supply chain innovation?
Dave Malenfant, Director at the Center for Supply Chain Innovation, recently said
Do you think Amazon has Amazon Prime because they love you? No, they have Prime because they know what you want to buy before you do.
Greenhouses may not possess the volume of data that Amazon has, but they do have years of data comprising sales, logistics, risks, demand, etc. While talking to the greenhouse owners, I found out that they use this data at the end of the season to identify the markets and the plants that brought in the most money. The problem here is the reactive nature of using valuable data that can be flipped into a more proactive approach.
Today’s consumer puts product freshness and speed of delivery above all else during product evaluations, and they’ll even pay more for it, too. For this reason, the greenhouses need to optimize their supply chain network and create a more proactive approach towards providing the best quality produce and flowers.
With the use of historical data, greenhouses can correlate sales of certain plants with the time of the year, giving them an estimate of production size ahead of time. They can also use the fluctuation in market pricing to forecast the demand from consumers. Using this valuable information, greenhouses can plan their inventory well advance in time. For network optimization, the correlation of sales information with the distance of the store identifies the stores that bring in the most revenue and are closest to the growing operation. Prioritizing supply to those stores brings in more revenue, reduces logistics cost and diminishes the probability of spoilage.
Vegard Flovik has written a great article on Artificial Intelligence in Supply Chain Management. It's more technical than explanatory. If you are into the technical side of supply chain management, I recommend you give it a read.
Conclusion
With so many problems, greenhouse growers still continue to provide the freshest of produce and most amazing flowers for the consumer. The effort and desire to provide for their customers deserve big applause. But, as the industry is moving forward, the volume of demand for the highest quality product is increasing day by day. And greenhouses need to adopt data-driven decision making to make the best use of their resources to increase their production without affecting the quality.
At FarmatroniX, we aim to equip greenhouse growers with tools that leverage the data to help them make data-driven proactive decisions, so that, they can focus on what they do best, which is growing the highest quality plants.
Can you think of any other areas that greenhouses can benefit from leveraging data? Comment below!
