by Stephen Nuske, Ph.D. Research article – Steve (adapted from “The Grapes of Nuske” by Olivia O’Connor, Carnegie Mellon Today January, 2014)
The USDA estimates that there are nearly 800,000 fruit-bearing grape acres in California, an area equivalent to some 605,000 football fields. This vast spread of land, encompassing table grapes, wine grapes, and raisin grapes, takes an equally vast upkeep effort. Grapes must be given the proper amount of water and fertilizer. They must be sprayed with insecticides to deter insects and fungicides to prevent disease. They must be harvested at the proper point in their growing cycle and transported at a temperature that disallows fermentation or freezing. A considerable amount of the work that goes into maintaining these conditions happens at night, when temperatures cool.
Stephen Nuske, a “Systems Scientist” at Carnegie Mellon’s Robotics Institute is working on a robotic system that could revolutionize the routine in vineyards. As part of an USDA/NIFA Specialty Crop Research Initiative grant titled Efficient Vineyard, his team is working to improve both the quality and quantity of ripening grapes through something called High-Resolution Spatiotemporal Crop Load Measurement and Management.
In essence, Nuske is conducting a trial of an automated grape-counting system that will allow vineyard managers to track variations in their fields and more accurately estimate their harvest sizes. Ideally, the system will allow managers to make changes to their growing practices during the season to improve their overall yields as well as the quality of the fruit.
In 2012, he collaborated with Research Professor Sanjiv Singh on a project designed to test “Automated Crop Yield Estimation for Apple Orchards.” The program caught the attention of the National Grape and Wine Initiative, a coalition that coordinates grape research and growing practices across the United States. The NGWI reached out to Nuske to see whether the technology he was working on could be adapted to the grape industry, and Nuske jumped on board, partnering with Cornell researchers as well as his CMU colleagues to pioneer the new grape-counting technology.
Of course, “grape counting” is a simplification of what Nuske’s system actually does. The rig involves a camera (to take photos of the vines, from which a computer system will later detect and count the fruit), a laser scanner (which takes a three-dimensional measurements of vine foliage), a computer system (which tracks the data as it comes in), and the vehicle itself (which allows the team to quickly cover large areas of the vineyard). One person can operate the system in the field and then data is taken back to office to process and extract the vineyard performance metrics. Although if needed the system can be configured to output processed data live on the vehicle. The result is an odd-looking contraption, futuristic in function but humble in design. The rumbling vehicle rolls through the vineyard, sending out bright camera flashes at a rate of five per second.
When the predicted harvest yield (gathered by the grape-counting system) is compared to the actual harvest yield (determined months later), the overall error is less than 5%; in comparison, current industry standard predictions may be in error as high as 20-30%, says Nuske.
It’s an impressive improvement, and it’s not the only use of Nuske’s system. The most important aspect of the technology is its ability to show variation within the vineyards. He explains that viticulture (the study of grapes) is all about vine balance: the amount of leaf area as compared to the amount of fruit. The idea is summed up in a concept called “crop load,” which refers to both the amount of fruit and the health of the vine. Terry Bates, the director of Cornell University’s Lake Erie Research and Extension Lab and Effective Vineyard project director, compares crop load to the process of losing weight. A large number of leaves mean that a large amount of photosynthates are in the vine, available to the fruit. These photosynthates, Bates explains, are the “calories in.” And the grapes drawing the photosynthates from the vine are the “calories out.” In a healthy vine, the calories in and calories out are balanced. Too little or too much leaf area and the grapes suffer, leading to consequences that can go far beyond a bad glass of vino. According to the NGWI, grapes are the sixth-largest crop in the United States, supporting an industry that is valued at $4.9 billion and contributes $162 billion to the U.S. economy (and $33 billion in wages) each year. These numbers illustrate why the NGWI is concerned about maximizing crop yield.
Once all the data are collected, Nuske creates a spatial map of the parts of the vineyard through which his equipment has travelled. The spatial maps are constructed with a combination of each area’s crop load number, determined by the mathematical relationship between the amount of fruit and the amount of leaf area. The maps show which parts of the vineyards are doing well, and which aren’t. Growers can then adjust their methods to improve the balance between each area’s foliage and fruit. “This is kind of the cutting edge in viticulture,” Nuske explains. “A hundred years ago, if you wanted to grow a really good bottle of wine … you’d want to actually reduce the amount of fruit.” So farmers would remove grapes from the vine. But, in fact, Nuske explains, the past 20 years have shown that “you can produce a really good-quality crop with a lot of fruit with really big plants. … It’s not the old case of less gives you better quality.” As long as leaf and fruit weight are balanced, a large crop can be a quality crop.
This is good news for growers, Bates explains, because competition from domestic and foreign markets means that the price paid for grapes has not increased very much during the past 40 years. The result, he says, is that growers have been forced to become more efficient to offset rising expenses such as fuel and labor over the years, so they can still make a profit. And Nuske is putting the tools for greater efficiency in the palms of their hands, literally. His spatial maps can be downloaded to smartphones, so that growers can walk through their fields along the course of the maps, look at the high- and low-yield areas in person, and determine how to improve the crop load: water here, prune here, fertilize here. In an industry that is endlessly variable, the information that Nuske’s system offers insight that enables growers to adapt with the season, rather than rely on the conditions of previous years.
Multiple fields intersect to make Nuske’s work possible: biology, computer programming, engineering, robotics, agriculture. The system is complex, and Nuske acknowledges that the process of research and development can be tiring, even tedious.
“I think what we’re doing is probably not anywhere near as tough as what they’re doing,” he says referring to the vineyard laborers. Yet, despite the difficulty of farm labor, some critics question the future of agricultural technology, worrying that the human component of farming will be phased out, that jobs will suffer. But Nuske points out that his system isn’t taking over anyone’s livelihood. There aren’t any workers counting grapes full-time. But he’s still conscious of the ethical implications of precision agriculture. In general, he believes it will do far more good than harm.