A business owner wants to know how something will save them money, time, or at least reduce their input costs. More importantly, they want specific information on HOW to do this, without impacting the yield or quality of their crop.
The big picture
Although 84% of reported acreage of strawberries grown in the US are from California and Florida, strawberry revenue makes up a vital portion of small farms across the country (USDA-ERS, 2012). Since strawberries are one of the earliest crops in the spring, they can provide much needed revenue after winter. Also, with the growing popularity of the “local” movement, strawberries provide a good opportunity for growers to start or expand their market share by participating in farmers markets, or community supported agriculture. As more growers decide to grow or expand strawberry production, it could make sense for them to consider using wireless sensor networks (WSNs) to help with reducing fertilizer and irrigation applications for their operation.
How can WSNs help?
As part of this project, we are looking at a number of factors to help us determine the economic value of WSNs. First, we are developing baseline values for production costs and revenue for each of our growers, using their specific practices for the past several years. During the project, we will keep detailed records about the costs of production and revenue using WSNs. We will then be able to compare the baseline values to the values using WSNs to determine the economic benefits of producing strawberries using WSNs. For example, using a WSN, growers may use 50% less water and fertilizer, but also spend less time (labor) monitoring and watering their fields, perhaps with increased yields or earlier berry production. More berries a few weeks earlier in the season will increase revenue, because those berries are worth more. By adding these benefits up, and subtracting the cost of the sensors, we can determine how valuable WSNs are for a particular grower. We can also calculate how long it would take to pay for a WSN, with the increase in profits (the payback period).
Based on prior research with ornamental crops, we believe that WSNs will be able to help growers in a number of ways. The ability to more accurately monitor water and fertilizer levels should lead to lower water, fertilizer and labor costs during the project. This is particularly true for frost protection, which can use 136,000 gallons per acre for 8 hours of frost protection. Since WSNs provide real-time information on leaf and air temperature, relative humidity (dew point) and wind speed, growers may be able to water for fewer hours because of the more accurate data they have. The WSNs can also send out text and email alerts when critical temperatures are reached, which are set by the grower. We believe that WSNs will provide more accurate climatic information from their own fields, to reduce labor and water substantially for the growers involved in this project.
Grower benefits of WSNs
We recently completed a five year project looking at the benefits of WSNs for the production of ornamental plants. Details about that project, as well as more information about WSNs can be found at www.smart-farms.net. We found that each grower that we worked with derived different benefits from WSNs, including reductions in production time, disease, labor, and inputs (water, fertilizer, etc.). Each benefit had a different value based on the particular operation, but we found that all operations benefited from WSNs.
We believe that the same types of benefits will be seen for strawberry growers. The additional benefit in strawberry production is that better management and better growth should also lead to increased fruit yields, and therefore profits. We also think that fruit quality can be increased with better irrigation and fertilization management. Better timing of frost protection methods could also lead to greatly reduced floral damage and increased overall yield
Cost of WSNs
There are many factors which determine the cost of WSNs including your location, the size of the network that you would like to purchase, and the additional services that you purchase. The company that we work with Decagon Devices Inc. (www.decagondevices.com), does not sell directly to growers. They work with a network of consultants and distributors, who help with sensor selection, placement and setup to best meet the grower’s particular needs. We recommend that growers start with a small network (a weather node, and 2-4 nodes with soil moisture, EC, water meters etc.) to familiarize them with the use of WSNs, and the types of information which they can provide. More information about the costs and benefits of WSNs can be found in the following learning module https://myelms.umd.edu/courses/1110342
Return on investment
In our work with commercial ornamental producers, we have found that WSNs have a return on investment (payback period) of anywhere from a few months to 2.5 years, depending on the growers particular situation. Your particular return on investment is dependent on a number of factors, such has your current practices, how much you change practice using the information from a WSN, and the value of the crops you are growing. We have seen increases in profits from 30% to more than 256%, depending on the particular operation and crop, for the ornamental growers we have worked with.
As part of this project, we will be providing information on the cost and benefits and return on investment information for strawberry production.
We have seen a number of ways that WSNs have provided economic benefits to ornamental growers. We believe that many of those benefits will be applicable to strawberry production also. We are developing baseline cost and revenue information for growers “typical” production practices, which we will compare with cost and revenue information based on sensor controlled irrigation to determine the benefits (if any) that we see by using WSNs. Stay tuned as we gather more information!
USDA-ERS. 2013. U.S. strawberry harvested acreage, yield per acre, and production, 13 States, 1970–2012. 4 Dec, 2014. <http://usda.mannlib.cornell.edu/usda/ers/95003/table04.xls>