Optical sensors attached to sprayers and sidedress machines collect and use data in real time, giving no-tillers and strip-tillers the ability to tailor nitrogen (N) prescriptions for fields. 

But while the evolution of the technology has the capability to give farmers the tools and data to make timely, sometimes real-time management decisions, some wariness, understandably, remains as to the true value of remote sensing technology.

At its best, information generated by sensor technology offers, “a real, well-rounded perspective on how the soil and plant are interacting within any given season, any environmental interaction,” says Dr. Ray Asebedo, former assistant professor of precision agriculture at Kansas State University, and current agronomic consultant for Topcon Agriculture. 

The ultimate goal, he says, is to keep the focus on farming, “and at the same time put technology to work by good agronomic sciences improving profit-per-acre.”

Step by Step

Interest in optical sensor technologies, or sensor technology in general, has increased in precision agriculture because of rising input costs. With profit margins tighter, nutrient management specialists must have acute knowledge of nutrient variability seen on farms. 

“What happens is, we have to be able to make nutrient recommendations that are just the right rate applied at the right time, in order to help reduce our input cost without sacrificing yield,” Asebedo says, “which ultimately will improve profit per acre.”

An understanding of the benefits of this technology for nutrient management requires a step back to first look at core fertility. Sensor technology or not, soil sampling is still a highly recommended practice that can improve the quality of  nutrient management programs. “We're not to the point with sensor technology where we don't have to soil sample,” Asebedo says. 

Measuring soil pH, along with the levels of phosphorous (P) and potassium (K), are among the first important steps. “Soil pH is the most nutrient-limiting factors in the soil,” he says. “If our soil does not have the appropriate pH levels, it can reduce the availability of nitrogen, phosphorous, potassium and on the whole, bring down our entire nutrient management program and reduce profitability.”

Non-mobile nutrients in the soil often requires either grid soil sampling, or soil sampling by zone, or even a composite sample, which can help get no-tillers and strip-tillers on the right track for what they have for P or K levels. 

Asebedo notes, this is a critical step, prior to applying sensing technology to N and sulfur management. “The temptation is to jump right into nitrogen and sulfur, or just nitrogen alone. But the deal is, if our soil pH and P and K are not in the right spot, no matter how good we make that nitrogen program, it's always going to be lagging in yield and profitability because the lower ranks of the nutrient management ladder haven't been taken care of yet.”

He adds that if farmers don’t have their pH, P and K in the right order, they’re not going to see as much profitability from newer optical sensor technology, especially with N management and N prescriptions.

Next come secondary and micronutrient need, followed by in-season crop response. Optical sensor data collected from drones or sensing technology on a sprayer can show in-field variability to the crop’s response to soil according to weather. 

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LOOK & LEARN. Dr. Ray Asebedo breaks down the different resolutions and data that can be derived from remote sensing imagery, including plant temperature, soil texture and yield variation.

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For example, excessive rainfall in northern states in 2018 may have drastically changed N management plans for no-tillers and strip-tillers. 

“If we were just doing a pre-applied fertility program, we would never be able to take into consideration what's happening in-season,” Asebedo says. “By utilizing optical sensor technologies, we can read what the crop is telling us, and develop multiple nutrients and variable-rate applications. This is where we can really start to hone in to improving profit per-acre on the farm.”

Visual Communication

For an agronomist like Asebedo, the science behind optical sensor technology starts with the premise that plants are visual communicators that “speak” in wavelengths of light. Lush greens are usually indicators of good health, a sign of enough N in the soil system. Yellowing can signal stress. 

Optical sensor technologies go a step further and allow for the analysis of light beyond what’s visible to farmers or their agronomists walking the field, scouting crops. For instance, near infrared light has a strong reaction with plant cells and gives a good gauge of plant biomass. 

Red and red edge light commonly used from satellite technology, or Trimble’s GreenSeeker or Topcon’s CropSpec, can measure photosynthesis. 

“Since red light is heavily absorbed by chlorophyll, it gives us a gauge of photosynthetic capacity,” Asebedo explains. “So between red light, red edge, and the infrared, we can start to see how big that plant factory is, and how efficient it's operating at to produce yield.”

Optical sensor technologies, then, can provide a broader view of what a plant is “telling” us about its interaction with the environment. Also, the introduction of drone technology as a tool about 5 years ago provided a bird’s eye view of a field to get a better sense of variability, Asebedo says. 

Today, the ability to integrate data from different sources make machine systems more intelligent and bring them closer to thinking like an agronomist, he says. Results from different analysis can be layered visually atop a bird’s eye view of a field on a monitor. 

Using electrical conductivity offers a view of soil texture within the first foot or 3- feet depths across a field. In these cases, deep reds or yellows may indicate sandier soils, with lower water-holding capacity, while greens and blues indicate more loamy soils. 

Data from electrical conductivity provides us insight to soil texture variability across a field.  How we conduct nutrient management on sandier soils as opposed to silt loam soils will be considerably different due to differences in water holding capacity, water availability and nutrient loss factors.

Adding in optical sensor data sets, like thermal imagery, can show thermal signatures, or how much heat is coming up from a plant. Thermal imagery can provide critical data about heat and water stress and assist agronomists to make more informed decisions.

For instance, blues will indicate where plants are running cooler, which can coincide with loamier sections of soil, where more water may be available. There is a similar correlation in looking at near infrared (NDVI) and red edge (NDRE) imagery, which looks at plant biomass and photosynthetic capacity.

Loamier areas, typically highlighted in blue, indicate more productive plants getting plenty of water. Sandier areas will have lower biomass, likely indicating yield reduction if the plants don’t get more moisture.  

Practical Application

While there is still plenty of theoretical outcomes, farmers are most interested in practical impacts that sensing technology can provide. Asebedo explains how agronomists working with no-tillers and strip-tillers can leverage collected sensor data to refine fertilizer prescriptions through what he calls the “agronomist nitrogen recommendation algorithm.”

“An agronomist uses this data, along with observations from scouting, to come up with a N recommendation,” Asebedo says. “But input from the farmer will be just as critical a factor in the process. Some of the agronomist’s first questions should be about yield, including, ‘What’s the average from year to year?’ and  ‘What’s the current yield goal, and why?’ Final grain yield is the end result of all the interactions observed between crop, soil and weather.”

Then the agronomist will make a visual determination of N stress in crops. They will consider soil type, soil textural changes and soil test analysis data, if available throughout the field, along with weather. 


“We're not to the point with sensor technology where we don't have to soil sample…”


But crop physiology is another factor to weigh, Asebedo says, because different growth stages are linked with specific yield determining factors. “For instance, with corn at V6 to V12 stage, I'm going to be very attentive to making sure that my corn crop is not nitrogen stressed during that period. Why is that? Because ear size determination takes place,” he says.

Then it’s time to decide whether the sensing data warrants additional N application. “For example, say we come in at V14 stage for corn and it's been clearly stressed, and was stressed through V10, through V12,” Asebedo says. “Odds are pretty good that we have suffered permanent yield loss, and shouldn't be applying high rates of an additional 150 pounds of N because it's never going to improve our yield. I'd be better off pulling that nitrogen recommendation back and only apply N rates again for what we can actually truly obtain for yield."    

Overcoming Adoption Obstacles

While the benefits of sensing technology are emerging, there are obstacles to more widespread use. In-the-field computing power and connectivity have been limited a factor.  

“Ten years ago, when the GreenSeeker first came out, there was no cloud or machine-to-machine kind of communications. That just didn’t happen,” Asebedo says. “Think about how tough it once was — or even can still be — to get a cell phone call in the field." 

However, current crop sensing tools including Topcon CropSpec, an active optical sensor technology, can connect to cloud platforms via APIs to transfer its data to be readily used by the farmer or agronomist. Easy access and use of optical sensor data will help farmers and agronomists find in-field variability and save considerable amount of time through more focused crop scouting. 

 

Corn-comparison

CORN COMPARISON. In a remote sensing study, Dr. Ray Asebedo evaluated ear-size differences pulled in different spots of a corn field, based on different fungicide test strips in corn. Areas that received fungicide vs. those that did not, revealed as much as a 40 bushel difference in corn yields — 220 to 260 bushels per acre.

An additional obstacle has been the lack of a unifying software platform, which makes analysis more time consuming, especially for farmers who may not have as much expertise in GIS and analytics. 

“The complexity of old software required high levels of training to properly process each layer of soil data, imagery, yield and many others in order to integrate them together to generate agronomic outputs such as variable-rate nitrogen prescriptions,” Asebedo says.

Today’s systems are more seamless. Improvements in connectivity have made it easier to integrate sensors and create an “Internet of Things” in the field. This allows for better communication, more computing power and automated processing that could be beneficial for no-tillers and strip-tillers and help them focus on farming rather than the deep science.

Broadening Application

Still, one of the biggest hindrances in the adoption of sensor technologies is a lack of trust. “Farmers don't understand how sensor technologies can improve agronomy,” Asebedo says. “And the very people that are trying to sell these sensors often don't understand it themselves.” 

But that’s changing. Asebedo says he has been dealing with different universities and precision ag dealers developing extension programs to provide better support for integrating remote sensing technologies into farm operations and demonstrating their agronomic impacts. 

“Helping ag dealers and farmers understand this technology will allow them to apply multiple aspects of farming, such as planting, fertility and crop protection,” he says. “Therefore, greatly increasing the potential ROI for the farmer.”

One area where Asebedo sees potential is with crop protection. “One of the things that always bothered me when we were having a great looking crop and our nutrient management program was being managed to a T, is somebody would always forget to apply some fungicide when weather conditions were conducive for disease pressure,” he says. “Then we would have some serious issues.”

In one sensing study, Asebedo evaluated ear-size differences pulled in different spots of a corn field, based on different fungicide test strips in corn. He also evaluated kernel depth, and the physiological development and grain fill from R1 stage, to maturity and up to abscission, or black layer stage.

“I can't stress enough the importance of sustaining photosynthetic capacity all the way through to black layer,” Asebedo says. “When we start looking at this, utilizing NDVI or our NDRE, seeing what we can't see with the human eye, there is still a considerable amount of photosynthetic activity that was taking place where we applied our strips of fungicide in comparison to where we didn’t make an application.” 

The end result revealed as much as a 40 bushel difference in corn yields — 220 to 260 bushels per acre — based on where fungicide was and wasn’t applied. 

“At the time, the farmer whose field this belonged to, was completely happy with their 220 bushel yield,” Asebedo says. “It was right on par with what they normally do. They thought they were doing great until we actually started utilizing our optical sensor technologies to determine if they were optimizing productivity across the entire field. 

Even though they were doing their nutrient management right, there was room for improvement in protecting the crop and applying fungicide to more areas to increase production. The utilization of optical sensors can have a positive impact of multiple aspects on farming and help no-tillers determine where they need to make changes to their farm management practices.