The economic model unveiled

Leafy greens and herbs have unique responses to light, temperature and CO₂. We’ve covered those responses in depth in the four previous articles in this series. But how economically feasible is it to maintain optimal environmental conditions in a commercial leafy green and herb operation? In this final article of the series, that is the question we will answer.

But that answer doesn’t come easy. It’s a tricky question to answer, requiring us to translate what we see in a research setting to a real-world commercial operation. There are a lot of factors to consider, so clear-cut recommendations are hard to make. Luckily, our team here at Michigan State University has been developing an economic model assessing the trade-offs between costs and revenues associated with the implementation of optimal conditions in a commercial indoor farm. So, we’ll break down what goes into this economic model and lay out some of the key cost factors the model considers to arrive at strategies for growers when managing their operations.

Making the calculations

The first thing we addressed in this series was how light and temperature influence the growth of red-leaf lettuce ‘Rouxai’ and green butterhead lettuce ‘Rex’. We reported that the economic outcomes for both cultivars improved at higher temperatures, but only the red lettuce benefited from the high light intensity (Figure 1). While increasing the light intensity from low to high intensity enhanced lettuce growth rates and therefore the overall revenue for both cultivars, the increase was not proportionate to the doubled electricity and packaging expenses for the green lettuce.

The economic model we used looked at several critical factors: space optimization, electricity costs, labor costs, consumables and packaging costs and revenues. These components are pivotal in calculating the overall economic efficiency of indoor growing operations. Let’s look closer at these factors individually.

Space optimization

Factors taken into consideration for space optimization are the number of days from seeding to transplant (propagation stage) and from transplant to harvest (production stage), the resulting plant mass and the planting density. The time each plant spends in propagation and production stages affects not only the turnover rate of harvests but also operational planning and costs. By fine-tuning these aspects, a grower can significantly reduce wasted space and resources and improve overall productivity and efficiency.

Practical steps include utilizing vertical farming techniques to increase usable growing space, optimizing plant spacing based on specific crop needs and adjusting space usage with the growth cycle timing to ensure continuous production. These strategies help in creating a more streamlined and economically viable operation, enabling growers to produce more with less and achieve better market competitiveness.

Energy costs

The cost of electricity is a significant operating expense that can account for about 30% of total variable operating costs. It’s also directly affected by adjustments for optimal environmental conditions.

For example, in our study looking at lettuce production under daily light integrals (DLI) of 9 or 18 mol·m⁻²·d⁻¹, we found that the increase in marketable fresh mass for the green lettuce cultivar did not meet the doubling energy requirement that arose from operating additional LED fixtures. Due to this, we recommended growing under the lower DLI for green lettuce. For the red lettuce, the fresh mass increased enough from the additional DLI that the added energy costs were compensated by improved revenue from larger plants. However, the application of this information is dependent on the conditions of a given facility.

Heating, ventilation and air conditioning (HVAC) systems used for temperature control can also account for large energy costs, especially when it comes to cooling an indoor farm. The high energy requirement for cooling can be exacerbated by the extra heat released from additional LED fixtures, requiring even more HVAC use. Due to these nuances, we recommend looking at the optimal conditions from our research in combination with your operation. The model simulations used a 30% loading on energy costs, but this can change depending on individual farm structures and growing conditions. If the optimal temperature is cooler than your operation currently runs, consider how much of a yield benefit we reported and compare it to how much more your HVAC would have to run to get closer to that optimum. These are not simple considerations, but they are important to have in mind.

Labor costs

Labor costs are the most significant operating costs in indoor farms. In this partial budget analysis, total electricity costs varied between 39% and 56% of total variable operating costs. In the economic model, labor costs were estimated in five production-related activities: seeding, transplanting, harvesting, packaging and cleaning. Of these activities, harvesting was estimated to take 32% of total labor time, packaging 25%, cleaning 16%, transplanting 16% and seeding 11%. Labor costs accounted for about 30% of total variable operating costs. Strategies to optimize labor can include implementing automation for improving labor efficiency, providing training or optimizing workflow to reduce downtime.

Consumables costs

In the model, we included seeds and growing media (Figure 2), which represent about 20% of total variable production costs. Seeds were priced at $0.03 each, while 1-inch rockwool hydroponic grow cubes are $0.035 per unit, based on average wholesale and market prices, respectively. It’s important to note here that our study considered prices that a small grower would face, but these prices can be lower for larger quantities. These inputs are crucial in the propagation stage and are factored into the cost analysis per square meter based on plant density before transplant.

Additional consumable costs could include CO₂ injection if amending is pursued — varying depending on targeted rate and the source of the CO₂. In the future, the economic model will also account for the economic impact of various CO₂ concentrations through harvest, considering the additional cost of supplementing and the resulting yield increase.

Packaging costs

While only a relatively small part of total operating costs, about 7%, packaging costs can vary significantly according to the type of packaging used. For our study, we used a unit cost of $0.04 considering amorphous polyethylene terephthalate (APET) clear plastic clamshell container, suitable for 4.5 ounces of lettuce. Packaging costs were applied to the daily harvest weight and analyzed to assess the impact of higher yields on the need for additional packaging materials. This approach allows for an annualized view of the packaging expenses based on yield and market prices.

Revenues

Consider the daily harvest, which we calculated by multiplying the plant density per square meter, individual plant fresh mass and the production area size harvested daily. The grower’s annual revenue was then determined by multiplying this daily harvest across a financial year and applying the retail price per pound after adjusting for retailers’ margin. This adjustment allows the model to account for fluctuations in market prices.

To analyze the impact of changes in environmental control settings on economic results in this base model, we kept aside any crop loss or shrinkage effects and assumed 100% of the harvest being sold. The model used an average price of $13.41 per pound of lettuce, with wholesale prices calculated by applying a standard industry gross margin of 50% over the cost of goods sold.

Using the model and its limitations

When we use the model, we can compare how expected economic outcomes shift based upon the adjustment of different environmental conditions. For example, using the data from our light and temperature study, we increased DLI, which increased electricity costs and increased revenue from the greater fresh mass. This can be done with other conditions, such as CO₂ concentration and temperature. However, the model does not account for more nuanced changes, such as how marketability could change when a higher temperature reduces the redness of your red lettuce (Figure 3). The model is a useful tool for assessing the relative value of implementing a change, but all tools have limitations.

As we see from all the inputs going into the economic model, whether it’s worth pursuing the "optimal" environmental conditions in CEA isn’t a straightforward yes or no. It depends. Changes can be beneficial, but the actual benefit is estimated using a complex equation that requires careful consideration of your operation, its input costs and its market.

The CEA landscape is ever evolving, and so are the strategies for navigating it successfully. By applying the insights from developing research, you can be better equipped to make these informed decisions that enhance both the productivity and profitability of your operation.

Sean Tarr was an M.S. student at (now a graduate of) Michigan State University (MSU), Simone Valle de Souza is an assistant professor of horticulture economics and Roberto Lopez is an associate professor and controlled environment/floriculture extension specialist in MSU's Department of Horticulture. The authors gratefully acknowledge Fluence Bioengineering for LEDs, JR Peters for fertilizer, Rijk Zwaan for seeds, Grodan for rockwool, Hydrofarm for hydroponic tanks and the USDA National Institute of Food and Agriculture Hatch project nos. MICL02472 and USDA-NIFA Specialty Crop Research Initiative award no. 2019-51181-30017.