With the most recent FAA UAV announcement my phone has been ringing with excited potential UAV users. Two points always comes up in the conversation. NDVI (normalized difference vegetation index) and image resolution. This blog will address the use of NDVI, resolution will come later. Before getting into the discussion, what NDVI is should be addressed. As described by Wikipedia, NDVI is a simple graphical indicator that can be used to analyze remote sensing measurements, typically but not necessarily from a space platform, and assess whether the target being observed contains live green vegetation or not. NDVI is a mathematical function of the reflectance values of two wavelengths regions, near-infrared (NIR) and visable (commonly red).
The index NDVI has been tied to a great number of crop factors, the most important being biomass. Biomass being important as most things in the plant world impact biomass and biomass is related to yield. The most challenging issue with NDVI is it is highly correlated with biomass and a plants biomass is impacted by EVERYTHING!!!! Think about it, how many things can impact how a plant grows in a field.
The kicker that most do not know is that all NDVI’s values are not created equal. The source of the reflectance makes a big difference.
Measuring reflectance requires a light source, this is where the two forms of NDVI separate. Passive sensors measure reflectance using the sun (natural light) as a light source while active sensors measure the reflectance from a known light source (artificial light). The GreenSeeker is a good example of a active sensor, it emits its own light using LEDs in the sensor while satellite imagery is the classic passive sensor.
The challenge with passive remote sensing lies within the source of the light. Solar radiation and the amount of reflectance is impacted by atmospheric condition and sun angle to name a few things. That means without constant calibration, typically achieved through white plate measurements, the values are not consistent over time and space. This is the case whether the sensor is on a satellite or held held. In my research plots where I am collecting passive sensor data, so that I can measure all wavelength, I have found it necessary to collected a white plate calibration reading every 10 to 15 minutes of sensing. This is the only way I can remove the impacts of sun angle and cloud cover. When using the active sensors as long as the crop does not change the value is calibrated and repeatable.
What does this mean for those wanting to use NDVI collected from a passive sensor (satellite, plane, or UAV)? Not much if the user wants to distinguish or identify high biomass and low biomass areas. Passive NDVI is a great relative measurement for good and bad. However many who look at the measurements over time notice the values can change significantly from one day to the next. The best example I have for passive NDVI is a yield map with no legend. Even the magnitude of change between high and low is difficult to determine.
Passive NDVI in the hands of an agronomist or crop scout can be a great tool to identify zones of productivity. It becomes more complicated when decisions are made solely upon these values. One issue is this is a measure of plant biomass. It does nothing to tell us why the biomass production is different from one area to the next. That is why even with an active sensor OSU utilizes N-Rich Strips (N-Rich Strip Blog). The N-Rich Strip tells us if the difference is due to nitrogen or some other variable. We are also looking into utilizing P, K, and lime strips throughout fields. Again a good agronomist can utilize the passive NDVI data by directing sampling of the high and low biomass areas to identify the underling issues creating the differences.
OkState has been approached by many UAV companies to incorporate our nitrogen rate recommendation into their systems. This is an even greater challenge. Our sensor based nitrogen rate calculator (SBNRC blog) utilizes NDVI to predict yield based upon a model built over that last 20 years. That means to correctly work the NDVI must be calibrated and accurate to a minimum of 0.05 level (NDVI runs from 0.0 to 1.0). To date none have been able to provide a mechanism in which the NDVI could be calibrated well enough.
NDVI values collected with a passive sensor, regardless of the platform the sensor is on, has agronomic value. However its value is limited if the user is trying to make recommendations. As with any technology, to use NDVI you should have a goal in mind. It may be to identify zones or to make recommendations. Know the limitations of the technology, they all have limitations, and use the information accordingly.
From trials to phone calls (and text messages, and tweets, and ect. ect) I have gathered a fairly good picture of this years winter wheat nitrogen story. And as normal, nothing was normal. Overall I seen/heard three distinct trends 1) Did not take much to make a lot 2) took a ton to make a lot 3) saw a response (N-rich strip or cow-pow) but fertilizer never kicked in. Covers most of the options, doesn’t it.
The N-rich strips really came out over all very good this year. N-Rich Strip Blog. On average many of those using the N-Rich Strip and SBNRC (SBNRC Blog) producers have been getting in the neighborhood of 1.0-1.3 lbs of N applied per bushel produced. This year the numbers ran from 0.66 to 2.3 lbs of N per bushel. In both extremes I believe it can be explained via the field history and the N-Cycle.
In at least two fields, documented with calibrated yield monitors, the N-Rich Strip and SBNRC lead to massive yields on limited N. One quarter of IBA bumped 86 bpa average on 47 lbs of N while a second quarter, also IBA, managed 94 bpa average on about 52 units of N. We are currently running grain samples from these fields to look protein levels.
The other side of the boat were those with N-Rich strip calling for +2.0 lbs N per bushel. I had received notes from producers without N-rich strips saying that they could predict yield based on the amount of N applied and it was a 2 to 1 ratio. Not always but many of these high N demand fields where wheat following a summer or double crop or corn or sorghum. While many of the low N demand fields were wheat after wheat or wheat after canola. In a rotational study that had been first implemented in the 2014-15 crop year I saw big differences due to previous crop. The picture below was taken in early March. The straw residue in wheat after wheat had just sucked up the nitrogen. While it was evident the residue from the canola broke down at a much more rapid pace releasing any and all residual nutrients early.
The yield differences were striking. The canola rotation benefited the un-fertilized plots by 22 bpa and even with 90 lbs of N applied having canola in the rotation increased yields by 12 bpa. We are looking and grain quality and residual soil sample now. I am sure there will be a more indepth blog to follow.
Another BIG story from the 2015-16 wheat crop was the lack of benefit from any N applied pre-plant. It really took top-dress N this year to make a crop. Due to our wet early fall and prolong cold winter N applied pre was either lost or tied up late. Work by Dr. Ruans Soil Fertility Program really documented the lack luster pre-plant N effect. The figure below shows 4 location of a rate by timing student. The number at the bottom of each graph is a rate by time (30/0 means 30 lbs Pre-0 lbs Top, 60/30 means 60 lbs Pre-30 lbs Top). At every single location 0/60 beat 60/0. Top-dress N was better than Pre-plant N.
The last observation was lack of response from applied N even though the crop was deficient. Seen this in both the NE and NW corners. I would hazard with most of the circumstance it was due to a tie up of applied N by the previous crops residue. The length at which the winter stretched into spring residue break down was also delayed.
Here it is folks APPLY NITROGEN RICH STRIPS. Just do it, 18 years of research preformed in Oklahoma on winter wheat says it works. Hold off on heavy pre-plant N even if anhydrous is cheap. It does matter how cheap it is if it doesn’t make it to the crop. Will we see another year like 2015-16, do not know and not willing to place money on either side. What we do know is in Oklahoma split applying nitrogen allows you to take weather into account and the N-Rich strip pays dividends.
There are several fact sheets available on top-dressing N and the application of N-Rich strips. Contact your local Oklahoma Cooperative Extension Service county educator to get a copy and see if they have a GreenSeeker sensor on hand.
Historically the two primary sources of phosphorus have had different homes in Oklahoma. In general terms MAP (11-52-0) sales was focused in Panhandle and south west, while DAP (18-46-0) dominated the central plains. Now I see the availability of MAP is increasing in central Oklahoma. For many this is great, with MAP more P can be applied with less material. which can over all reduce the cost per acre. There is a significant amount of good research that documents that source of phosphorus seldom matters. However this said, there is a fairly large subset of the area that needs to watch what they buy and where they apply it.
If you are operating under optimum soil conditions the research shows time and time again source does not matter especially for a starter. In a recent study just completed by OSU multiple sources (dry, liquid, ortho, poly ect ect) of P were evaluated. Regardless of source there was no significant difference in yield. With the exception of the low pH site. The reason DAP was so predominate in central Ok, soil acidity. See an older blog on Banding P in acidic soils.
Figure 1. The cover of an extension brochure distributed in Oklahoma during the 1980s.
When DAP is applied, the soil solution pH surrounding the granule will be alkaline with a pH of 7.8-8.2. This is a two fold win on soil acidity aka aluminum (Al) toxicity. The increase in pH around the prill reduces Al content and extends the life of P, and as the pH comes back down the P ties up Al and allows the plant to keep going. However, the initial pH around the MAP granule ranges from an acid pH of 3.5-4.2. There is short term pH change in the opposite direction of DAP, however the the Al right around the prill becomes more available and in theory ties up P even faster.
Below is a table showing the yield, relative to untreated check, of in-furrow DAP and MAP treatments in winter wheat. The N401 location had a ph 6.1 while Perk (green) has a pH of 4.8. At Perkins in the low pH, both forms of P significantly increased yeild, almost 20 bushel on the average. DAP however was 5 bushel per acre better than MAP. At the N40 site the yield difference between the two sources was 1 bushel.
In general it can be said that in acid soils DAP will out preform MAP while in calcareous high pH soils MAP can out preform DAP. So regarding the earlier statement about the traditional sales area of MAP or DAP if you look at the soil pH of samples went into the Oklahoma State University Soil, Water, and Forage Analytical lab the distribution makes since.
Average soil pH of samples sent into OSU soil water forage analytical lab by county.
In the end game price point and accessibility drives the system. In soils with adequate soil pH levels, from about 5.7 to around 7.0, get the source which is cheapest per lbs of nutrient delivered and easiest to work with. But if you are banding phosphorus in row with your wheat crop because you have soil acidity, DAP should be your primary source.