Johnny Sanchez, left, a graduate student at the University of Maine, in Orono and his faculty advisor, Eric Gallandt, professor of weed ecology, right, field test Franklin Robotics' Tertill, a solar-powered, autonomous garden weeder in a greenhouse on campus.Sanchez recently obtained a $14,660 SARE grant to use RFID tags, GPS and other inexpensive mobile monitoring technology to analyze real-time on-farm asset tracking on a functioning, small farm.

ORONO, Maine — On any given day, farmers spend time dealing with everything from daily chores to equipment failures.

“All of these smaller organic farmers have a wealth of knowledge when it comes to farming because it’s what they do,” said Johnny Sanchez, a University of Maine graduate student in Ecology and Environmental Sciences. “It’s knowledge that’s been passed down generations in a lot of cases. It’s often not the actual farming and growing plants that’s the difficult part; it’s figuring out the best way to stay economically viable that’s really difficult.”

In pursuit of that goal, Sanchez developed a graduate research project: Automated Net Return Mapping: Using Inexpensive Technology for Maximizing Profit of Small-Scale Farms, which has been awarded $14,660 by the Sustainable Agriculture Research and Education Grants. The project began Aug. 1, 2019 and ends July 31.

“The way most farmers track all their assets and their finances, normally, is through pen and paper, journal-type things,” Sanchez said. “I’m trying to, one, automate that and, two, make it a lot faster and efficient; especially at the end of the season,” by focusing on labor efficiency.

To track, collect and analyze labor efficiency data in the field, Sanchez will be tracking farm workers with GPS units, RFID tags placed around the farm, GIS to create a visual representation of the farm, and other “existing open-source farm input monitoring software” to “allow the farmer to be able to track where inefficiencies exist within the operation, “ Sanchez stated in the SARE Grant Project Abstract.

“Right now, I’m going to be testing the four different experiments, or treatments, as I’m calling them,” Sanchez said. “The first one is a pen and paper (system) as a sort of control. The second will be using GPS devices and, for the third, using RFID tags to create a network throughout the farm and the forth will be using an open-source farm tracking website.”

The field research will be conducted on the Rogers Farm, one of two farm sites, part of the J. Franklin Witter Teaching and Research Center, operated by the College of Natural Sciences, Forestry, and Agriculture’s Livestock and Forage Crops Research Facilities. University students, who work on the farm during the summer, will be fulfilling the role of “farmers” for the project, Sanchez said.

“The farmers will be wearing a GPS device and RFID tags,” Sanchez said. “That way, we can get an idea of where most of the labor is being allocated. The open-source software is called Farm OS, (which) can be used to track a bunch of different things, using a network of sensors set up throughout the farm. I’m going to be trying to compile all of this data, using GIS, and some other spatial analysis methods to try to create this visual and interactive representation.”

Labor data can be entered into Farm OS by the task, location, date and time; the amount of time involved; and can be noted “completed” or “not completed,” Sanchez said. Other data, such as employee hourly wage rates can be analyzed by specific task performed. Labor costs are calculated by time spent by individual workers on various activities and time-stamped movements of workers on the farm will provide a digitized, geo-referenced map identifying where and how labor was being utilized-managing crops, working on equipment and more.

“That way, (labor data) is super-easy to access,” Sanchez said. “Farmers can look back and see a heat map-like visual, and say ‘I’m spending way too much money and not putting too much labor into my carrots when the market is really for kale.’ It’s going to be like an aerial shot of your farm, something that you might see on Google Maps. Each of the fields will be labeled with whatever crop is growing and then I’m going to try to overlay that data, using all of those different methods. That way you can see where all of the labor is being allocated.”

Sanchez hopes that his project will provide a foundation for the development of more complex data-based systems to allow farmers to “holistically see what’s happening on the farm” and where they should best invest labor and money. It provides both data and visual representations to help farmers develop ways to maximize labor usage.

“It’s helping farmers compare their enterprises that way,” Sanchez said. “If the ultimate goal is to stay economically viable, then it’s good to know what’s helping you do that.”

Lancaster Farming