“Precision Agriculture” is one of the more significant trends in modern farming. An early example was “auto-steer” technology which was a spinoff from work at NASA. It uses GPS or other georeferencing input to guide tractors and other equipment in a way that prevents overlaps or misses with seed, fertilizer or pest control and can even ensure that all “wheel traffic” is limited to certain tracks so that most of a field is never compacted. Other applications have included detailed, variable delivery of seed, pest control products or fertilizers based on spatial data from satellite or drone-based aerial imagery or yield data from previous harvests. All these tools help farmers maximize productivity while minimizing inputs and their associated costs.
There are other examples of precision agriculture based on real-time data collected by equipment as it moves through a field. One example is the “See and Spray” technology from John Deer that uses an on-board camera and A.I. to identify specific weeds for spot spraying.
New precision ag technology that uses real time camera-based data, but in this case, it is being used to visualize how spray droplets are forming on plant surfaces. A former student at MIT named Vishnu Jayaprakash had some family exposure to the process of spraying crops and recognized that the basic challenge in that process is how to get a water-based delivery system to interact efficiently with the very waxy surface of a plant.
There is a whole list of variables that influence this process including the effects of surfactants in the spray mixture on the surface tension of the liquid, the pressure, flow and nozzle configuration of the application device, and the temperature, sunlight intensity, wind and humidity at the time of spraying. One does not often think of MIT as a place that develops agricultural technologies, but it turned out to be a good place to work on the specific imaging technology and on the A.I. needed to translate that into a practical solution for farmers. Jayaprakash formed a venture-backed company called AgZen and developed a two camera system that can be connected to typical spraying equipment and use imaging of the sprayed solution on the target plant(s) in order to work out the adjustments needed to get an optimal degree of coverage with appropriately sized droplets.
This system can be used to make on-the-go adjustments in order to get the spray coverage “just right.” This can often allow a farmer to get excellent efficacy of a spray using only 20-30% as much of a product per acre. The farmer has an obvious incentive to save money on the treatment as long as it is still as efficacious in terms of pest control, fertilization, plant growth modification or other goals. The technology has been tested for use in cotton defoliation in trials at Texas A&M and it worked at 50% of the lowest use rate on the normal product label. It is being tested on wine grapes where a 30% reduction in rate was still efficacious. Susan Scheufele, an extension researcher at the University of Massachusetts has conducted field trial work with this technology on vegetable crops. Her testing has confirmed the pesticide cost savings and the level of crop protection that can still be achieved in that system.
AgZen’s REALCOVERAGE system can be integrated with most existing sprayer equipment and the company is leasing the equipment on 65,000 acres, working towards 100 units retrofitted next year.
Perspective
It should be noted that the primary benefit of this technology is in the cost savings for farmers rather than any safety issue associated with pesticides and other products. Those important farming tools are very well regulated by the EPA to insure that by the time crops get to the consumer or animal feed level, any residues of the chemicals or their metabolites are well below any hazardous concentrations. The EPA takes the voluminous and very expensive toxicity and environmental fate data it requires from the party seeking a registration and sets use-pattern limitations designed to ensure that residues will be below a crop/product-specific tolerance. That is a complicated way of explaining how the EPA label is designed to make sure that the product can be used safely (e.g. how much can be used total and in each application, how close to the time when a farmworker will reenter the field, and how long before harvest). Each year the USDA goes out to the wholesale level of the consumer market and gathers 10,0000 samples of an assortment of fruits and vegetables in what is called the Pesticide Data Program. Those are taken to labs and analyzed for synthetic pesticide residues. This is essentially a “report card” for how well the farmers of our food are complying with the EPA label. Year after year this monitoring program has demonstrated an excellent record for the industry including the most recent results which were published early this year in which over 99% of the 10,665 samples from 23 commodities had no residues above the conservative tolerances. This track record may get even better with the increasing implementation of Precision Agriculture methods now including the AgZen innovation.
Source: Forbes