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Raedan Sharry, Precision Nutrient Management Ph.D. student
Brian Arnall, Precision Nutrient Management Extension Specialist
Cotton production in Oklahoma has expanded the past decade into areas which other production systems such as continuous wheat may have traditionally dominated. Fields that have been managed for continuous wheat production may have become acidic in response to management practices, such as the use of ammoniacal nitrogen fertilizers. In response to the acidification of these soils it may be important to recognize and understand the potential impacts of soil acidification on cotton production.
To better document the impact of soil pH on cotton lint yield and quality a study was conducted over the 2019 and 2020 growing seasons at two locations: Stillwater, OK (EFAW farm) and Perkins, OK. Soil pH in these experiments were adjusted to a depth of approximately 6 inches using aluminum sulfate (acidifying) and hydrated lime (alkalinizing). All three locations were planted to two varieties; NexGen 3930 and Deltapine 1612 at a rate of approximately 35,000 seeds per acre, into plots with soils ranging in pH from 4.0 to 8.0.
In season measurements taken included stand count, plant height, node count and NDVI (normalized difference vegetative index. All four in season measurements demonstrated a significant critical threshold in which soil pH negatively impacted crop performance. Stand was significantly decreased at a soil pH of 5.3 or lower. This trend is displayed in Figure 1. Plant height and node count depicted in figures 2 and 3 respectively were both significantly decreased when soil pH dropped below 5.3 and 4.9, while NDVI began to deteriorate around a pH of 5.1 (Figure 4). Response to soil pH level was also visually observable as shown by Figure 5 from the Perkins 2019 location.
Yield levels across this experiment ranged from 0 to 1284 lbs. of lint per acre. In this work yield is reported as relative yield. To calculate relative yield the yield of each plot is normalized to the average of the three highest yields for that site. This method of reporting yield response allows this work to be applied across a range of yield environments.
When all sites and cultivars were combined relative yield reached a plateau at approximately 73% of yield with a critical threshold observed at a pH of 5.4. Below this critical threshold yield decreased at a rate of 37% per point of pH decline. This equates to 15% yield loss at a pH of 5.0, 33% yield loss at a pH of 4.5, and 52% yield loss at a pH of 4.5. This relationship is depicted in Figure 6. It is important to note that yield was 0 when pH was 4.3 in two plots. This represents the possibility for total crop failure when planting into very acidic conditions.
Differences in relative yield between cultivars were insignificant. However, further investigation may produce a significant difference. Critical threshold for the DP 1612 and NG 3930 cultivars were 6.1 and 5.2 respectively. This suggests that there may be value in further examining the influence of genetics on cotton response to soil acidity.
The influence of soil pH level on cotton productivity is confirmed by this study. All three sites evaluated provided a strong correlation between soil pH and lint yield, as well as the in-season growth parameters measured. While this study is likely to be expanded to another location to provide a more robust evaluation of the potential impact of soil acidity on cotton, the current dataset provides ample evidence to conclude that soil acidity is likely to be detrimental to cotton production in the southern plains. Soil pH levels below 5.5 appear to provide the greatest opportunity for yield loss as depicted above. Lint quality measurements taken in the study (micronaire, length, uniformity, and strength) showed no consistent trends in the relationship between quality parameters and soil pH suggesting that soil acidity had a limited influence on lint quality characteristics. Cotton response to soil pH is likely to be influenced by the environment of a specific location and growing season. This underlines the importance of understanding the soil properties that negatively impact productivity, such as the presence of toxic forms of aluminum or manganese. It is also important to highlight the possibility of acidic conditions significantly affecting the ability of the crop to access important nutrients such as phosphorus. Under acidic conditions cotton productivity is likely to be significantly decreased unless soils are neutralized using a soil amendment such as lime.
Project Supported by the
Oklahoma Cotton Council
Oklahoma Fertilizer Checkoff Program
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.
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.