January 3, 2007 | By: Laura Skillman

An international research team developing a model to predict yield loss from Asian soybean rust has found that damaged leaves can greatly impact the crop’s ability to absorb radiant energy, reducing yields.

The team is made up of members from Brazil and Louisiana State University and led by University of Kentucky College of Agriculture crop physiologist Saratha Kumudini. They began their work in 2005 in Brazil by mimicking the disease – removing leaves from noninfected plants at the same pace as infected plants. Their initial thoughts were that defoliation was the prime culprit, but it was found that simply mimicking defoliation did not have a good one-to-one correlation with the actual yield losses from infected fields.

Measurements were also taken on the amount of necrotic lesions from soybean rust on leaves that remained on the plant. Using a healthy area leaf index that takes into account necrotic lesions and defoliation, the researchers got a much closer relationship between yields in their test plots and plots with soybean rust.

“We didn’t want to stop there, we wanted to know if there was a one-to-one correlation between necrotic lesions and plant productivity, so we went to Quincy, Fla.,” Kumudini said. “What we were looking for were leaves with the necrotic lesions and its impact on the plant’s photosynthetic capacity – productivity level.”

Field work included looking at leaves in the fields, finding the lesion and taking a photosynthesis measurement – the plants’ ability to take radiant energy and turn it into biomass.

“The point is that when we look at these plants with necrotic lesions, those lesions have a bigger impact (on photosynthetic capacity) than what you can see visually,” Kumudini said.

Based on their first year of data, these researchers believe that soybean rust-induced yield loss is dependent on growth stage, defoliation injury and the lesions on the intact leaves.

“So what we are doing in Kentucky and Louisiana is developing a yield loss prediction model that looks at healthy leaf area and relates healthy leaf area to yield,” she said. “We are looking at different maturity groups, different row widths and saying can we develop a valid yield loss model. Right now, we are in the model development stage.”

The yield loss model will be used to develop an interactive software tool that would determine the farmer’s yield potential and the predicted yield loss if rust should defoliate or damage the leaves of the crop.

The model would allow a producer to weigh the potential yield loss against the cost of fungicide applications to make sound management decisions. This risk management tool should improve producers’ net economic return and guard against unnecessary fungicide applications that can impact the environment and increase the risk of developing fungicide resistance, Kumudini said.

Additional research will be conducted in 2007 with the hopes of having a yield-loss prediction model ready for use within the next two to three years.


Saratha Kumudini, 859-257-5020, ext. 80752