Tri Setiyono, far left, an assistant professor with the LSU AgCenter focusing on precision agriculture, works with his graduate students in a test plot of corn at the AgCenter Central Research Station with a few tools of their trade, including drones and sensors. Students, from left, include Dulis Duron, Rejina Adhikari, Bhawana Acharya and Farner Rontani. Photo by Olivia McClure

From drones to sensors, many farmers already use precision agriculture technologies to help them make management decisions for their crops.

But the large amount of data these tools gather has even greater potential, and LSU AgCenter scientists are studying the best ways to use it.

Tri Setiyono, an assistant professor with the AgCenter focusing on precision agriculture, wants to see whether these technologies can help mitigate challenges related to changing weather patterns.

“The weather is becoming less favorable for growers,” he said. “The timing of rain often does not come when they want it to, and the rainfall is getting more intense.”

Rain can affect when farmers apply nitrogen fertilizer, an expensive but crucial investment for a successful crop, particularly with corn.

Farmers often have to take advantage of dry spells to put out fertilizer, even if a heavy rain is forecast for the next day. Ill-timed or excessive rainfall can wash away fertilizer, and it also can contribute to uneven crop emergence, which leads to lower yields.

Setiyono is conducting studies simulating flooding, which can stress plants and limit yield potential, in corn and soybeans. Using drones and remote sensing, he wants to find out if these technologies can shed light on the crops’ response to excessive rainfall and help inform decisions about whether to reapply lost fertilizer.

“We equip drones with sensors to map the fields,” he said. “We scan the crops and assess whether the stand is uniform. We are implementing some algorithms, including artificial intelligence, to see if we can convert those images into plant stand counts.”

He hopes to use the data to help farmers be more resilient to climate challenges.

“Traditionally when making our nitrogen fertilization recommendations, we look at the yields at the end and work backwards and say, ‘the optimum N rate is this much.’ In this study, we will do that, but also, can we scan it soon after fertilization or after flooding to see indication of potential yield reduction,” he said.

By catching deficiencies early, it’s possible to correct those problems and recover yields. Sensors can pick up on certain leaf characteristics and other indicators of stress.

“Remote sensing can detect what our eyes cannot see,” Setiyono said. “It can see if a plant is experiencing stress, like not having enough nutrients, and from that respect, the idea is that if we can capture this early enough, we can develop correlations for how much nitrogen we need to put back.”

Whether adding that extra fertilizer is worthwhile must be considered on a case-by-case basis.

“The question in the end is economics,” Setiyono said. “Is it still profitable to put the fertilizer back in? We are actually going to include that in our analysis — how much of a yield boost will we get and does that offset the cost?”