Being educated in the realm of Soil Fertility at Oklahoma State University by the likes of Dr Gordon Johnson and Dr. Bill Raun, Brays Nutrient Mobility Concept and Mitscherlich’s Percent Sufficiency Concept are ingrained in my psyche. In class the concept of Build and Maintain for phosphorus fertilizer management was just briefly visited and not discussed as a viable option. For anyone in the corn belt, and some Okies, reading this that may seem unusual. But when I was in school on average in Oklahoma there was about 100-200 K acres of 100 120 bpa (bushel per acre) corn, 300-400 K acres of 40-50 bpa sorghum, and over 5 million acres of 20-30 bpa wheat. In a state with those average yields, replacing P removed by the crop was not a major concern.
But times are changing. There is more corn and soybean planted and the achievable yields of all crop are increasing. While the average winter wheat producer should not be worried about replacement rates of P there is a growing group of producers that should. This blog will discuss the scenarios in which sufficiency rates are best and those in which replacement should be considered. The OSU factsheet PSS-2266 goes in-depth on each of these methods.
Applying P based on sufficiency will increase soil test P levels in a low yielding environment. For example on a 20 bpa wheat field that starts out with a soil test P level of 0. Using the sufficiency recommendation each year the soil test value will reach 20 ppm (40 STP) in 20 years. A 30 bpa field would take 30 years. Yes that is a long time but the soil test value is increasing a little each year. The point of 20 ppm is important because at that level the crop is 95% sufficient, meaning if no P is added the crop will only reach 95% of the fields yield potential.
Using a mass balance approach we can determine at what point does the crop remove more than we can supply with in or near furrow starter fertilizer. Table 1 shows the values I am using for the discussion. The first column is just the average amount of P removed per bushel of grain, most of our grains fall in the .4 to .5 lbs P per bushel range. The second column is the soil test value at which P level is said to be at 90% sufficient. The reason this column is included is that the P2O5 reccomendation for this P level fits into the starter rate for all crops. The low high starter rates are the typical range of P2O5 that is delivered within the safe range (N based) and what I see as the common rates. These values may be above or below what you use.
Table 2 is pretty simple but it is the center point of this article. The one caveat I need to add is this assumes strip till or 2*2 / 3*2 is not being used. Table 2 is using the starter range and removal value to determine the yield level the starter can support. The first take on this table may provide some hint on why in a state with 5 million acres of wheat averaging 36 BPA the state soil fertility specialist didn’t focus on replacement rates. In fact for most for most the the wheat ground P application is higher than removal and P levels are slowly increasing. The big take home from this table should be is my yield level outside this window? If so do not immediately go out in crease your P rates but do take a close look at your system as a whole. Take a close look at your cropping system, not just one seasons but look at a three or four year cycle. Add up P applied and P removed, are you positive or negative net balance? If you are negative take a long hard look at your soil test over time. Some soils can supply a large amount of P even if you are removing more than you apply. Other soils will be rapidly drawn down. Regualr soil testing allows for producers to keep an eye on these values.
In the end even if the production warrants the use of replacement rates, the current market may not. For more on that read https://osunpk.com/2016/08/27/now-may-not-be-the-time-for-replacement/.
Speaking of market currently both soybeans and cotton are getting a lot of attention due to how the economics is penciling out. Soybean is a “heavy” P crop pulls .8 lbs per bpa while cotton removes 13 lbs per bales. Both of these crops are salt sensitive and the rate of inforrow is typically quite low providing only about 6 lbs when on 30″ rows. If you are growing beans or cotton make sure you account for their removal when you talley up your system.
Below is a table that I wanted to add, well because I like it. This table illustrates that buildup, and drawdown, rate is heavily impacted by existing soil test value. In short it takes a lot more fertilizer P to raise soil test p levels in a very low P testing field than it does when soil test P is closer to optimum, 19 lbs per 1 lb at STP of 10 and 5 lbs per lb when STP is 65. The exact rate changes by soil type and the same holds true to drawn down via crop removal.
Any questions or comments? Feel free to contact me at email@example.com
I recently wrote a article for the Crops and Soils magazine on the components of a Variable Rate Nitrogen Recommendation. The people at the American Society of Agronomy headquarters were kind enough to make it open access. What follows in this blog is just a highlight reel. For the full article visit https://dl.sciencesocieties.org/publications/cns/articles/49/6/24
Components of a variable rate nitrogen recommendation
Variable-rate nitrogen management (VRN) is a fairly hot topic right now. The outcome of VRN promises improved efficiencies, economics, yields, and environmental sustainability. As the scientific community learns more about the crop’s response to fertilizer nitrogen and the soil’s ability to provide nitrogen, the complexity of providing VRN recommendations, which both maximize profitability and minimize environmental risk, becomes more evident.
The components of nitrogen fertilizer recommendations are the same whether it is for a field flat rate or a variable-rate map. The basis for all N recommendations can be traced back to the Stanford equation (Stanford, 1973). At first glance, the Stanford equation is very basic and fairly elegant with only three variables in the equation.
Historically, this was accomplished on a field level through yield goal estimates and soil test nitrate values. The generalized conversions such as 1.2 lb N/bu of corn and 2.0 lb N/bu of winter wheat took account for Ncrop and efert to simplify the process.
The basis for Ncrop is grain yield × grain N concentration. As grain N is fairly consistent, the goal of VRN methods is to identify grain yield. This is achieved through yield monitor data, remote sensing and crop models.
The N provided by, or in some cases removed by, the soil is dynamic and often weather dependent. Kindred et al. (2014) documented the amount of N supplied by the soil varied spatially by 107, 67, and 54 lb/ac across three studies. Much of the soil N concentration is controlled by OM. For every 1% OM in the top 6 inches of the soil profile, there is approximately 1,000 lb N/ac.
Historically, the efficiency at which N fertilizer is utilized was integrated into N recommendations and not provided as an input option, e.g., the general conversion factor for corn of 1.2 lb N/bu. Nitrogen concentration in corn grain ranges from 1.23–1.46% with an average of 1.31% (Heckman et al., 2003) or 0.73 lb N/bu. Therefore, the 1.2-lb value is assuming a 60% fertilizer use efficiency. More recently, recommendations have been to incorporate application method or timing factors in attempt to account for efficiencies.
While a VRN strategy that works across all regions, landscapes, and cropping systems has yet to be developed, the process of nitrogen management has greatly improved and is evolving almost daily. Those methods that are capable of determining the three inputs of the Stanford equation while incorporating regional specificity will capture the greatest level of accuracy and precision. Ferguson et al. (2002) suggested that improved recommendation algorithms may often need to be combined with methods (such as remote sensing) to detect crop N status at early, critical growth stages followed by carefully timed, spatially adjusted supplemental fertilization to achieve optimum N use efficiency. As information and data are gathered and incorporated and data-processing systems improve in both capacity and speed, the likelihood of significantly increasing nitrogen use efficiency for the benefit of the society and industry improves. The goal of all practitioners is to improve upon the efficiencies and economics of the system, and this should be kept in mind as new techniques and methods are evaluated. This improvement can be as small as a few percentages
This article is published in the Crops and Soils Magazine doi:10.2134/cs2016-49-0609. The full article includes more details on the components plus concepts of integration.
Published in Progressive Forage http://www.progressiveforage.com/ 9.1.2016
First, let’s agree the term “precision” is relative. Forage is a diverse system with an even more diverse set of management strategies. Regardless, every manager should be constantly striving to improve the precision in which nutrients are managed. The ultimate goal of any precision nutrient management tool should be this: producing the highest quality output (in this case forage) with the least amount of input – ultimately, optimizing efficiencies and maximizing profits. Within this readership there are those who are soil sampling at a 1-acre resolution and others who have likely not pulled a soil sample in the past decade. For both spectrums we can make improvements – let’s start basic and move forward.
A soil sample should the basis for all nutrient management decisions. Is soil testing a perfected science? No, far from it. However, there must be a starting point. A soil sample is that first bit of information we can start with and the basic data collection for precision ag to make improved management decisions. When fertilizer is applied without a recent soil sample, it is done based upon pure guesswork. How many other management decisions are made on a farm or ranch by a guess?
The composite soil sample is a great start, but it is just that – a start. While there are some soils that are very uniform most are extremely variable. In a survey of 178 fields in the southern Great Plains on average the soil pH was 6.12; phosphorus (Mehlich 3 phosphorus [M3P] and Bray 1 phosphorus [B1P]) was 28 ppm while soil test potassium averaged 196 ppm. So on the average the primary components of soil fertility were okay. However, on average the 178 fields had a range in soil pH of 1.8 units, M3P and B1P both had range of a 52 ppm and STK had a range of 180 ppm.
Table 1 shows the minimum and maximum soil test values for the 178 fields.
This data helps support the concept that we should find ways to increase the resolution or decrease the number of acres represented by a single soil sample. Increasing soil sample resolution is typically done using one or two methods – zone or by grid.
The basis of a zone sample is creating a smaller field. The biggest question with zones is how to draw the lines. There are dozens, if not hundreds, of possible methods, each having their own reasons and benefits. My basic recommendation is that before lines are drawn goals have to be established. For example, if phosphorus or soil pH management is important, the basis for the lines should be soil based. This could be based on soils map, soil texture, slope and on and on. If the target is improved nitrogen management, then the reason for drawing lines should be yield based. This could be based on yield maps, aerial images, historic knowledge or many soil parameters.
Why does it matter? Two reasons: First, across the broad spectrum of soils and environments two nutrients are hardly spatially correlated, which means the zone that is best at describing phosphorus variability does an extremely poor job describing potassium variability. Second, more theoretically the demand for nutrients are driven by different factors. Phosphorus (a soil immobile nutrient) fertilizer need is driven by the soil P concentration (look up Brays Sufficiency Concept). Many use yield as a parameter for phosphorus application, but this is not a plant need or even a yield maximizing practice. Fertilizing based on removal is done to prevent nutrient mining. However, nitrogen (a nutrient mobile in the soil) fertilizer need is based on yield and crop removal. Hence, the common Land Grant University N and sulfur recommendations are yield goal based.
To be honest even the experts disagree on the hows, whys and ifs of grid sampling. I like data, therefore I naturally lean towards grid sampling if the field warrants it. For me, the biggest benefit of grid over zone sampling is that soils data from zone samples are biased to whatever parameter was set for the zone and therefore any resulting map for all nutrients must reflect the original zones. In a grid, each data point is independent therefore the maps of each nutrient can be independent, and (the science tells us) in most cases nutrients are independent of each other.
Ideally two pieces of information are available for determining whether a field is grid sampled or not. The first piece of information is a yield map from any previous crop. If yield is fairly uniform, I question the need for variable rate management, much less the expense of grid sampling. Regardless of the sampling method zone or grid, the discussion is moot if spatial variability does not exist across the field. However, many forage producers may not have access to this kind of data.
One of the most useful decision aid tools for grid sampling is the composite soil sample. The reason is simple statistics: A composite sample should be a representative average of the field. If the data is normally distributed, that means half of the field is above and half the field is below the sample average. So the optimum fields to grid are those in which an input falls at the point in which the benefit of applying is in question, because it suggests that approximately half the field needs the inputs while the other half likely does not. It is in this scenario that the return on investment can be greatest. As with pH, for example, fields with a very low value should have a flat broadcast application and should be sampled again at a later date. Fields with a composite pH well above 6.0 will unlikely have enough acres needing lime to warrant sending out an applicator.
Is grid sampling a lifelong activity? No. The initial activity of grid sampling will provide both an indicator of the variability level and overall needs of the field. From that point, decisions can be made and actions taken. Identify the greatest limiting factor in the field based on the samples, and focus on impacting change upon it. Zone sampling in subsequent years can be utilized to document change. When that issue is resolved, move to the next factor. It may require grid sampling again or using the original grid to develop new management zones. For instance, if the greatest issue first identified on the field is soil acidity then after the soil pH is neutralized the field should be grid sampled again. The reason is for this is that changing soil pH will influence many nutrients and the amount of change is not consistent but dependent upon many other factors.
In precision ag we tend to look at layers, yield, soil, etc. However, none of these tell the whole story independently. An area in a field may have moderate soil fertility and be under producing. Using the data collected the decision may be made to increase inputs; yet, the issue is a shallow restrictive layer limiting production. Therefore, the extra inputs will be of no benefit and could even further reduce production. It is at this point I like to bring out the importance of “getting dirty.” There is no technology that can take the place of “boots on the ground” agronomy.
For producers who have historically preformed intensive soil sampling there is still room for improvement. Soil testing and nutrient management is not an exact science; in fact, it was originally built for broad sweeping, statewide recommendations. As technology advances and inputs can be applied at sub-acre resolutions, all of the environment (weather, soil) by genotype inactions becomes more evident.
The next step in precision ag is to develop recommendations by upon site specific crop responses. This is where nutrient response strips can further improve nutrient use efficiencies and crop production. In Oklahoma, nitrogen-rich strips are applied across fields (grain and forage) to determine in-season nitrogen needs. Having a strip in the field with 50 to 100 extra units of N acts as a management tool which takes into account soil, environment and plant need. If the strip is visible the field or zone needs more N, if it is not visible then the crop is not deficient and at that point in the season does not need more N. Producers have taken this approach for N and adopted it for P and K with strips across the field with a zero and high rate of either nutrient. After a few seasons, responsive and non-responsive zones are developed and P and K applications are managed accordingly.
One misconception of precision ag is that the end result should be a field with uniform yield from one corner to the other. This is often not the case; in fact, in many cases the variability in production across the field can be increased. Theoretically, precision ag is applying inputs at the right rate in the right place. This means areas of the field which are yield limited due to underlying factors which cannot be managed have a reduction in inputs with no effect on yield. Other areas of the field have not been managed for maximum production therefore an increase inputs result in increasing yield widening the gap between the low and high yield levels.
Regardless of where a producer currently sets on the technology curve, there are potential ways to increase productivity and efficiency. There is nothing wrong with taking baby steps; it is often the simple things that lead to the greatest return.
Every year in August and early September I get the question “How soon after applying NH3 can I sow wheat?”. Typically my answer has been a conservative one which takes into account rate, depth, spacing and soil moisture to end up with a range of 3 days to a week. The concern with anhydrous application is that when NH3 is placed in the soil it immediately turns into NH4 by striping H from H2O. This action releases OH into the soil in increases pH, depending on rate pH can reach 10.0 this hike in soil pH is a short term as the system disperrses and NH4 immediately begins the conversion to NO3 release H and driving down pH. The high pH in itself is not the problem but if the pH is still high and soil dries the OH will strip H from NH4 and NH3 is formed. The ammonia gas (NH3) is what can easily damage the sensitive seedling.
After fielding several calls in one day I wanted to dig a bit deeper and see what the science and specialist say. I was hoping for a nice consensus, haven’t found that yet. Here are some snip-its.
From Kansas State University
Dr. Dave Mengel
As a general rule, wait about 7 to 10 days between the anhydrous ammonia application and wheat planting. The higher the nitrogen rates and the wider the spacing (creating a higher concentration of ammonia in the band), the longer period of time you should wait. Also, in dry soils you may need to wait longer.
Canada Grains Council’s Complete Guide to Wheat Management Link
In the past, it was recommended that seeding be delayed for two days after banding anhydrous ammonia (NH3). However, in many soils as long as the NH3 is placed 5- 7.5 cm ( 2-3 inches) away from the seed, NH3 can be applied at the time of seeding. Seed damage from NH3 is most likely to occur under dry conditions on sandy soils when there is insufficient separation from the seed. Placement of fertilizer nitrogen should be deeper in sandy soils than in loams or heavy textured soils. Narrow band spacing 25 to 30 cm (10-12 in) is better than wider band spacing particularly under low moisture conditions.
From University on Minnesota
Peer reviewed publication
VARVEL: EFFECTS OF ANHYDROUS AMMONIA ON WHEAT AND BARLEY AGRONOMY JOURNAL, VOL. 74. NOVEMBER-DECEMBER 1982
Field experiments were conducted 1979-1981 on a Wheatville loam soil. The treatments consisted of three rates of N as anhydrous ammonia (45, 90, and 135 kg/ha) in 1979 and four rates of N (0, 45, 90, and 135 kg/ ha) in 1980-1981 at three depths (8,16, and 24 cm) in all combinations. Spring wheat and barley were then seeded at three different times. Seedling stand counts, grain yield, and protein were used to determine the effect of the treatments. Seedling stands were reduced in some cases, but no reduction in grain yield or protein was obtained due to the reduction in stand. The most important factor in spring anhydrous application was the depth of application, which caused greater moisture loss and seedbed disruption at the 24-cm application depth.
Spring wheat and barley response to N rates was similar at all depths of application (no significant interaction between N rate and application depth). The results indicate that anhydrous ammonia can be applied safely at planting time on spring wheat and barley, if applied at the 8 to 16 cm depth and at N rates currently used in the northern Great Plains.
From University on Minnesota (referring to corn) link
The only risk of planting soon after AA application is if seeds fall within the ammonia retention zone. To avoid seedling injury separation in time or space can be important. Under ideal soil moisture conditions and proper application depth of a typical agronomic rate normally there is little risk of seedling injury even if planted on top of the application zone right after AA application. That said, this can be risky and I would not recommend planting on top of the AA row. If you have RTK guidance it is very easy to apply AA between the future corn rows. If RTK guidance is not an option, I would recommend applying AA on an angle to the direction of planting to minimize the potential for planting on top of the AA band. If application conditions are less than ideal and you have no RTK guidance to ensure a safe distance from the AA band, then waiting 3 to 5 days before planting is typically enough time to reduce the risk of seedling injury.
From University on Wisconsin (referring to corn) Link
The depth of NH3 placement was the greatest factor in determined potential seedling damage. The time after application had little impact.
Iowa State University (referring to corn)
by Regis Voss, extension agronomist, Department of Agronomy
The wet fall and spring will cause anhydrous ammonia application and corn planting date to be close. This will lead to the oft asked question, “How long do I have to wait to plant corn after ammonia application?” If there is a soil separation between the ammonia zone and the seed, planting can be done the same day the ammonia is applied. If the seed is to be placed in the ammonia zone, the longer the waiting period the less potential for root injury. There is no magic number of days to wait.
My take home from several hours of reading research articles and factsheets was my favorite answer IT DEPENDS. I believe Regis Voss with ISU had it right, there is no magic number. The important aspects for determining time will be 1) Soil Moisture 2) N rate 3) Depth and 4) shank spacing. From the reading I think there may be some general rules of thumb.
On the conservative side with good soil moisture, NH3 placed at 6″ deep, rate below 80 lbs and spacing of about 15″ the next day should be ok. As any one of these factors change (drier soil, higher rates, shallower application, wider rows) the more time should be added to reduce risk. One thing to consider is field variability. While the field on average may have great moisture there could be dry spots, while on average you are 6″ deep with the NH3 there are areas the rig is bound to rise up and go shallow. So there is always a chance for hot spots. All of that said I could not find any research on this topic for winter wheat in the southern Great Plains much less Oklahoma. I will always tend to the safe side and suggest if possible to delay sowing a few days after applying anhydrous. However if time is critical proceed with caution.
Looks like I can add one more project to my list and I need to find some open ground and do some “Experimenting”.
Happy Sowing All!
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.