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Behavioral Adjustments to Automated Agricultural Technology: The Use of Disease Forecasting by Grape Growers in California

By Olena Sambucci

The primary task of the economics team is to evaluate the costs and benefits associated with the new technology being developed in the Efficient Vineyard project. It sounds simple—figure out how much things cost and how long they last, and whether the benefits from the new technology justify the costs. Of course, it is anything but simple, especially in an industry as diverse as grape growing.

Costs and benefits from adopting a new technology will differ widely among growers of different categories of grapes—whether for table, juice, or wine production—and in various grape growing regions of the United States. Within the wine industry, production systems and costs and benefits of particular technologies also will vary across growers serving market segments that range from large-scale bulk wine to artisan ultra-premium producers. In California alone, for example, the average price per ton of wine grapes ranges from around $500 per ton in Central Valley counties to over $3,500 per ton in the Napa Valley (and over $20,000 per ton for some vineyards).

Source: Alston, Anderson, and Sambucci (2015)

Yield per acre, typical weather patterns, and terrain also vary, and these aspects, along with farm, size, and marketing considerations all play a role in the choices of varieties and the production system being employed. All of these variables factor into the applicability of particular technological options, and in calculating both costs and returns from any new technology. As a result, we spend a lot of our time contemplating questions such as: What does quality mean for a grower of Cabernet Sauvignon in the Central Valley versus the Napa Valley? And how do we measure it? Or what are the considerations facing a table grape grower in deciding what varieties to grow, when to irrigate, and when to initiate harvest in a particular block?

In addition to operating costs and returns per ton, economists also consider the role of growers’ preferences: when individual growers make decisions about the use of a new technology, their choices and the consequences of those choices may differ among growers, and they may be very different from those of scientists testing the technology in controlled experimental settings. For instance, a recent research project in our Department (the Department of Agricultural and Resource Economics at UC Davis) examined the use of a powdery mildew forecasting index by grape growers in California, and the adjustments growers made to their powdery treatment program as a result of an online continuing education course. The results were unexpected!

The powdery mildew index (PMI) provides information about powdery mildew pressure to growers based on daily weather observations, and the index was designed to change the timing of fungicide applications to allow the growers to save on the use of fungicides when the pressure of an outbreak is low. Instead, a study by Lybbert, Magnan, and Gubler (2016) found that growers responded to the PMI by changing not only the timing of the treatment but also their choice of fungicide and dosage rates. Similarly, after completing an online course on the use of the PMI, most growers increased the number of fungicide applications they made over the course of the growing season, and also adjusted their choice of product and dosage rates. As a result, the annual costs of managing powdery mildew increased in three out of four grape growing regions sampled.

Source: Sambucci and Lybbert (2016)

The increase in the use of fungicides by the growers is a result of a risk-averse response to high levels of powdery mildew pressure as forecasted by the PMI—the growers chose to treat powdery mildew more aggressively when the disease pressure was forecasted to be high, but at the same time did not reduce the number or intensity of treatments when the disease pressure was forecasted to be low. This response is not surprising considering that an outbreak of powdery mildew could be disastrous.

We found that growers use the forecasting technology differently than the researchers expected them to, but what does that mean? Is the increase in costs and the number of fungicide treatments a bad thing? Not necessarily, because as any grower will tell you, they know exactly what their production practices and materials cost them, and the observed increase in the costs of managing powdery mildew can be viewed as an indication of the corresponding increase in private benefits to the growers from the new powdery mildew strategy.

The main lesson here is that we as researchers can’t always predict that what growers will do with technology in their own fields and the resulting outcomes will be the same as when the technology is used in experimental trials. Therefore, in order to assess the economic value of a new technology we not only collect data and measure outcomes, but also try to learn as much as we can about the possible differences in use that may result from individual preferences of technology adopters. This project is designed with those ends in mind.  Sensor data is gathered and sensor results are modeled by scientists.  Decision-making for managing variation is ultimately left to the grower and farm-manager.

 

References:

Alston, Julian, Kym Anderson, and Olena Sambucci. 2015. “Drifting Towards Bordeaux? The Evolving Varietal Emphasis of U.S. Wine Regions.” Journal of Wine Economics 10 (03): 349–78.

Lybbert, Travis J., Nicholas Magnan, and W. Douglas Gubler. 2016. “Multidimensional Responses to Disease Information: How Do Winegrape Growers React to Powdery Mildew Forecasts and To What Environmental Effect?” American Journal of Agricultural Economics 98 (2): 383–405.

Sambucci, Olena, and Lybbert, Travis J. 2016. “Behavioral Responses to Disease Forecasts: From Precision to Automation in Powdery Mildew Management.” ARE Update 20 (1).

 

 

 

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