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For phosphorus (P) and potassium (K) fertilizer management there are three primary schools of thought when it comes to rate recommendations. The three approaches are Build-up, Maintenance/Replacement, and Sufficiency. There is a time and place for each one of the methods however the current markets are making the decision for the 2016-16 winter wheat crop a very easy one. The OSU factsheet PSS-2266 goes in-depth on each of these methods. For the rest of the blog I will use P in the conversation but in many scenarios K should/could be treated the same.
Build-up is when soil test is below a significant amount of fertilizer, about 7.5 lbs P2O5 per 1 ppm increase, is added so that soil test values increase. This method is only suggested when grain price is high and fertilizer is relatively cheap. Given the market, this is a no go. The two most commonly used methods of recommendation are Replacement and Sufficiency. In the replacement approach if the soil is at or below optimum P2O5 rate it based upon replacing what the crop will remove. The sufficiency approach uses response curves to determine the rate of P that will maximize yield. These two values are typically quite different. A good way you boil the two down is that replacement feeds the soil and sufficiency feeds the plant.
Oklahoma State Universities Soil, Water, and Forage Analytical Lab (SWFAL) provides recommendations utilizing sufficiency only while many private labs and consultants use replacement or a blended approach. Some of this is due to region. Throughout the corn belt many lease agreement contain clauses that the soil test values should not decrease otherwise the renter pays for replacement after the lease is over. For the corn belt both corn and soybean can be expected to remove 80 to 100 pounds of P per year. Conversely the Oklahoma state average wheat crop removes 17 lbs P a year. In areas where wheat yields are below 40 bushel per acre (bpa) using the sufficiency approach for P recs can increase soil test P over time.
Back to subject of this blog, consultants, agronomist, and producers need to take a good look at the way P recs are being made this year. Profitability and staying in the black is the number 1, 2, and 3 topic being discussed right now. The simple fact is there is no economic benefit to apply rate above crop need, regardless of yield level. The figures above demonstrate both the yield response to fertilizer based upon soil test. At the point of Critical level crop response / increase in yield is zero. What should also be understood is that in the replacement approach P fertilizer is still added even when soil test is in Optimum level. This also referred to as maintenance, or maintaining the current level of fertility by replacing removal. If your program is a replacement program this is not a recommendation to drop it completely. Over a period of time of high removal soil test P levels can and will be drawn down. But one year or even two years of fertilizing 100 bpa wheat based on sufficiency will not drop soil test levels. On average soils contain between 400 and 6000 pounds of total phosphorus which in the soil in three over arching forms plant available, labile, and fixed. Plant available is well plant available and fixed is non plant available. The labile form is intermediate form of P. When P is labile it can be easily converted to plant available or fixed. When a plant takes up P the system will convert labile P into available P. When we apply P fertilizer the greatest majority of was is applied makes it to the labile and fixed forms in a relatively short period of time. For more in-depth information on P in the soil you can visit the SOIL 4234 Soil Fertility course and watch recorded lectures Fall 2015 10 26-30 Link .
How to tell if your P recs have a replacement factor, not including calling your agronomist. First replacement recs are based on yield goal, so if you change your yield goal your rate will change. The other and easier way is to compare your rates to the table below. Most of the regional Land Grant Universities have very similar sufficiency recs for wheat. Another aspect of the sufficiency approach is the percent sufficiency value itself. The sufficiency can provide one more layer in the decision making process for those who are near the critical or 100% level. Response and likelihood of response to P is not equal. At the lowest levels the likelihood of response is very high and the yield increase per unit of fertilizer is the greatest. As soil test values near critical (32.5 ppm or 65 STP) the likelihood of response and amount of yield increase due to fertilizer P decreases significantly. At a STP of 10 the crop will only produce 70% of its environmental potential if P is not added while at a STP of 40 the crop will make 90% of its potential. The combination of % sufficiency and yield goal can be used to determine economic value of added P.
This year with margins tight soil testing is more important than ever before. Knowing the likelihood of response and appropriate amount of fertilizer to apply will be critical maximizing the return on fertilizer invest while maximizing the quality and amount of grain we can produce. Visit with your consultant or agronomist to discuss what the best approach is for your operation. Lets ride this market out, get the most out of every input and come out of this down cycle strong.
Feel free to contact me with any questions you may have.
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 access 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.