Though much of the conversation around precision agriculture is focused on drones, the reality is that the unmanned aerial vehicles are not being used on many farms. Other tools that involve risk prediction are more easily implemented and at a fraction of the cost.

MSU researchers are working with industry to design new laboratory and field tests, and build on the breakthrough in DNA technologies first used in human medicine, to name just a few. One example is an app to inform soybean growers of a major disease threat.

Since the 1970s, soybean growers in Michigan and across the Midwest have been battling white mold, a chronic disease that also affects other crops. Once a spotty problem in mostly localized areas, white mold has exploded, affecting well over a dozen states.

Scientists haven’t isolated the exact reason for the spread of the disease, which thrives in areas with abundant moisture and moderate temperatures. High-yield soybeans are especially susceptible. One theory points to potential vulnerabilities in the genetics of some modern, high-performing varieties.

When the fungus that causes white mold germinates, apothecia appear, which resemble small mushrooms. These release spores that are carried by the wind to soybean flower petals. By the time growers observe white mold symptoms, it’s too late to treat.

Closely planted rows promote white mold because of low light and air movement under the canopy. The combination creates a moist environment conducive to apothecia formation and plant infection.

Martin Chilvers, an associate professor in the MSU Department of Plant, Soil and Microbial Sciences, set out to identify the precise weather conditions conducive to spread of the disease.

Throughout 2016 and 2017, Chilvers and his team of students and postdoctoral researchers visited fields known to have white mold, mainly at the Montcalm Research Center in Lakeview, Michigan. On hands and knees, the group counted apothecia and recorded temperature and moisture data.

“The Montcalm Research Center was great for this because it’s an area with a lot of white mold,” Chilvers said. “It’s a lot of hard work, but ironically, the payoff from doing this really laborious job by hand is that we got a lot of data that was used in the production of a mobile app. It was really applied field work that went into this technology.”

The app — which was publicly released in 2018 and is free to download— is called Sporecaster. The project was led by Damon Smith, an Extension field crops pathologist at the University of Wisconsin–Madison (UW-Madison).

Jaime Willbur, now a potato and sugar beet pathologist at MSU, worked on the project with Smith for her doctoral degree from UW-Madison. Chilvers and his team were one of several partners providing field data for development and validation of the app’s model.

On the app’s home screen, users are asked to input a new field or choose from an existing list once fields have been created. After giving the field a name, the user must choose a row spacing of 15 or 30 inches, indicate whether irrigation is used, and identify a location based on coordinates. The app then asks if flowers are present and if canopy row closure is under or over the given threshold.

Using the previous 30 days of weather data from Dark Sky, particularly factoring in moisture and temperature, Sporecaster assigns a risk percentage for development of apothecia. Scientists have found that applying fungicide is most effective during flowering, when plants are susceptible to infection.

“In 2017, we tested the model in 33 commercial fields across the soybean-growing region of Wisconsin, with additional validation in Iowa, Michigan and Nebraska,” Willbur said. “There was a lot of scouting and field work, but thanks to an excellent team of researchers and collaborators, we were able to develop an accurate, award-winning tool for growers to make more effective and economical decisions.

“We received anecdotal feedback that growers were pleased with its performance, and in 2018 we had over 1,600 downloads of Sporecaster.”

Soybean white mold is a predominantly northern U.S. issue, but another problematic pathogen persists across all soybean-growing states: soybean sudden death syndrome (SDS). Its economic effect is massive, and in its worst years, it can result in a nearly total crop loss.

Like white mold, SDS is caused by a fungus and thrives in wet conditions. Because the disease prefers cooler weather, Michigan is an ideal spot for it to flourish. SDS is soil-borne, so once it’s established, battling the problem can feel almost impossible.

“SDS is really tricky, and management is difficult,” Chilvers said. “Once it’s in a field, there aren’t a lot of great options. Growers need as much information as possible on which varieties to plant and when to consider a seed treatment. The key is being proactive.”

The best defense is planting a resistant variety. Growers must also keep in mind that irrigation, soil compaction and growing soybeans in low-lying fields tend to enhance the likelihood of disease.

Researchers note that SDS is more prevalent in soil inhabited by soybean cyst nematodes, parasitic roundworms that feed on the vascular tissue of plants. Controlling soybean cyst nematode has shown some promise in reducing SDS severity.

Chilvers indicated that knowing when SDS is first present in a field — and to what extent — could give growers more opportunity to determine management tactics. Alongside students in his lab, he’s created a soil test that detects SDS fungal DNA. The group took a series of soil samples over the course of multiple growing seasons and found a correlation between the amount of DNA in the soil and SDS disease development.

Researchers are continuing to validate the test across a variety of fields, and it’s already being used in numerous diagnostic labs, including MSU Diagnostic Services.

“SDS is one of the primary diseases affecting soybean growers, so we need ways to get out in front of it,” Chilvers said. “This DNA technology is also a tool that can help us study the characteristics of the disease and hopefully develop more effective control measures.”

Planting the seed

Protecting crops from diseases and pests is a necessity, but there’s a crucial step before that. Planting is the first stage on a grower’s journey to a successful season, and seed placement is of highest importance.

Maninder Singh, an assistant professor in the MSU Department of Plant, Soil and Microbial Sciences, is investigating the role that seed placement can play in enhancing the productivity and profitability of Michigan’s corn, soybeans and winter wheat crops.

“Seed placement sets the tone for the entire season,” Singh said. “Farmers can dictate yield potential by making sure that seed spacing and depth are such that the plants are placed in the best position to flourish. Everything after that point, such as disease and pest management, is about protecting that potential.”

For corn and soybeans, precision planters are already adept at delivering uniform spacing and depth. Where improvement is needed, however, is in identifying and understanding the field variability that can be managed with different plant populations. Singh is exploring variable rate seeding in on-farm trials.

On the basis of historical yield data, soil properties, topography and aerial imagery, among other information, Singh is hoping to make prescriptive recommendations.

“When you’re working with fields that can be hundreds of acres, there’s a lot of variability in things such as temperature, moisture, elevation and nutrients,” Singh said. “Uniform planting is not using resources in the most efficient way. We’re thinking about the cost of seed, water, nutrients — all of the inputs that make farming expensive.”

In corn fields, for example, growers plant roughly 30,000 to 40,000 seeds per acre. For soybeans, that number is around 150,000. And growers of winter wheat plant about 1.5 million seeds per acre. With any of these crops, precision planting is a challenging prospect. Singh said the technology for small grain production isn’t as far along as it is for corn and soybeans, and he’s looking at different types of planters.

“We’re working with various equipment manufacturers on technologies that improve seed placement in small grains,” Singh said. “There are lots of opportunities to improve the technology. The companies, growers and researchers all want the same thing — more efficient use of resources to optimize crop productivity and profitability.”