UAN (urea-ammonium-nitrate) solutions are routinely applied in the late spring and early summer to deliver nitrogen (N) to young crops. Because UAN is a nonpressurized solution, it can be used without the hazards associated with anhydrous ammonia and can be spread more uniformly than granular fertilizer. Certain pesticides may also be added, eliminating an extra pass through the field. UAN solutions are usually manufactured with a 32% N analysis, transported nearer the point of use, and then diluted (“cut”) to 28% or 30% N with water or a nutrient rich solution such as ammonium sulfate. The N analysis of UAN solutions is monitored throughout the supply chain to assure quality and consistency. A hydrometer is commonly used to check the N analysis of solutions, estimating the N content by solution density. A hydrometer reading will vary with the temperature of the solution. Nitrogen and density values will differ by source of 32% UAN solution.
The density of a cutting solution should also be considered when making dilutions. The density of ammonium sulfate (AMS) solution is usually higher than water, and can vary by source. For example, if a hydrometer reading is 1.28 g/cc for a UAN solution that was diluted with water to 28% N, diluting the same UAN solution to that density with AMS would result in a product with only 26% N. The UAN density corresponding to a given N content must be adjusted when diluting with a solution other than water. A hydrometer calibration (chart) can be developed using laboratory analyses of N, S and specific gravity on the various solutions (UAN, AMS, etc.) and mixtures that might be used. Once a calibration is developed, hydrometer readings, adjusted for temperature, can approximate the N content of the UAN solution. Periodic laboratory analyses should be performed to update the hydrometer calibration since the density of new UAN and cutting solutions can change.
The key component of any efficient nitrogen (N) program is minimizing the risk of loss. Nitrogen losses can greatly reduce a grower’s profitability and can have environmental consequences. With a better understanding of the mechanisms that cause N loss and the conditions that increase the risk of loss, we can better decide when and how much to apply.
Plants can only take up N in two forms, ammonium (NH4+) or nitrate (NO3-). Regardless of your source of N, whether it be synthetic fertilizer (anhydrous ammonia, ammonium sulfate, urea, etc.), manure, or compost, the product must first be converted or mineralized to the ammonium form of N. Ammonium can then be converted to nitrate by a microbial process called nitrification. While plants can take up either form, they are generally able to access more N in the nitrate form because it moves freely with the soil water that is taken up during evapotranspiration. On the other hand ammonium is relatively immobile in the soil because it is held by the soil’s cation exchange complex. The difference in the mobility of these two forms of N is the main reason we may lose N before a plant is able to utilize it. In this case, the mechanism for N loss is leaching. In a well-drained soil, a heavy rainfall can move water downward through the soil profile, nitrate can move with the water and may move too deep for our crops to access or may be completely lost from the field if the nitrate makes it to a drainage tile. Leaching losses can be best minimized by applying N as close as possible to the time when the crop can utilize the N. In corn, the greatest N uptake occurs from V8 until R1. Losses can be further reduced by splitting N applications throughout the vegetative growing season.
Another potential mechanism for N loss to occur is denitrification. Denitrification is a microbial process that occurs poorly drained, saturated soils. When soils are saturated, there is not enough oxygen for microbial activity to thrive. Under these conditions, certain microbes are able to scavenge the oxygen atoms from a nitrate molecule in order to survive. The remaining N is then lost to the atmosphere in a gaseous form. Extended periods of saturation, especially when soil temperatures are warm, can lead to a significant loss of N. It is estimated that 4-5% of plant available N can be lost for every day of saturation. Denitrification can be minimized by ensuring you have adequate drainage in poorly drained areas and avoiding applications prior to heavy rainfall.
Volatilization is another potential loss of N to the atmosphere. Volatilization is the conversion of ammonium to ammonia gas. This is most likely to occur when ammonium forming fertilizers such as urea, or manures are applied to the surface of a warm soil with a high pH. Volatilization can account for losses as high as 80% when topdressing wheat in excessively warm conditions. Volatile losses can best be avoided by maintaining soil pH between 6.5 and 7.0, using a urease inhibitor with urea-based materials, and applying when soil conditions are moist and cool.
The development and adoption of precision sampling and variable rate fertilizer application technology has been of great benefit to producers. This technology has allowed for more efficient utilization of nutrients, allowing nutrients to be placed where they are needed and not applied to areas where they are not. However, like many technological advancements, understanding how to implement these technologies is not always cut and dried. Currently in precision ag, we have the ability to collect more data at a greater resolution than ever before. However, how to effectively utilize that ability in a practical way can present challenges.
The concept might be easier understood with a real world scenario. The names have been changed to protect the guilty and any similarities to actual occurrences are completely intentional. An agronomist is looking to utilize yield map data, along with soil test data to create a VR fertilizer application prescription while taking both data layers into account. A dry box will then be used to spread the fertilizer. With today’s technology at our disposal, it is very simple to utilize these two sets of data to make a very detailed, high resolution application map. However, just because the technology to generate the prescription exists does not mean that it is the best approach for this scenario. Let’s look into the practical application of this prescription.
Let’s first examine the soil test data layer. Soil samples were collected on a 2.5 acre grid; therefore our hypothetical 40 acre field is represented by 16 samples. Using mathematical modeling and techniques such as kriging, we can generate a smooth, almost seamless map to represent our soil test data, and can theoretically have tens of thousands of sets of data points for this 40-acre field. However, remember that while the color map generated from this data is filled in based on mathematical models, there are only 16 actual data points.
Now consider the yield data in this example. Depending on the monitor and configuration of the equipment, data can be collected by the combine every second. This leads to about 18,000 to 21,000 yield data points in the same field. If the raw yield data and modeled soil test data are utilized for creating prescriptions, unless a lager grid/cell size is used, the resulting prescription map for will contain 18,000 to 21,000 unique fertilizer rates within this 40- acre field.
While many computers with robust GIS software can handle this data volume today, a larger question remains: is the controller and application equipment up to the task? Many GPS controllers in the cab of application equipment cannot handle more than a few hundred unique rates within a given prescription file without performance issues. Beyond the controller, the other question is whether or not the fertilizer application equipment can meet the demands generated by this level of detail.
If, in our scenario, the combine used to collect the data was only 20 to 35 ft wide and the dry box spreader used to apply the variable rate fertilizer is capable of spreading 60 to 110 ft wide, it could be covering a number of unique fertilizer rates across the spread width. In addition, the spreader is most likely traveling 4 to 10 times faster than the combine, meaning that the spreader could be prompted a new fertilizer application rate as often as 10 times a second. When this occurs, spatial accuracy in the as applied map is usually poor. The rate controller cannot change rates fast enough to keep up with the prescription map change, and the application equipment cannot physically change quickly enough to match these rates. This usually leads to spatial inaccuracies and often the total product applied to the field will have a greater than desired level of error.
While the addiction to high resolution data grows, it is important to be mindful of the intended outcome for that data. While contouring data can reduce the special resolution of the data layer, controller files must be contoured to the practical restrictions and abilities of the application equipment in order to improve the accuracy of the final application.
Selecting the right supplier is a key business decision, regardless of the industry. From major manufacturers to the agricultural producer, supplier selection is a key aspect of running a successful business, and with the current tight margins in agriculture, selecting a quality supplier is especially crucial. Lower revenues often make the lowest cost supplier look very enticing, but before making the purchasing decision, successful business managers must carefully weigh all options to decide what is the best option for his or her business.
The adage of “You get what you pay for” still holds true. We need to keep in mind the magnitude of the supplier decision and the impact to our business. There are a number of factors beyond the price of the product or service we need to consider, such as:
As a farmer every year I make a choice on not only what products I want to buy, but also who I want to buy those products from. I can look at a bag of seed as a basic input commodity and look for the cheapest price, or I can choose to realize that there are major differences in those products. Those differences, whether it be in genetics, versatility of the product line, research, and support after the sale from someone that is genuinely interested in my success, all will help me to reach my goals and to make me (and them) more profitable. Choosing a supplier that helps you generate greater revenues is usually more profitable than simply choosing the one offering the lowest cost.
Spring tissue sampling of winter wheat can be a very useful management tool. The timing of wheat sampling does not correspond to a specific growth stage though. The important factor when determining the appropriate time to sample wheat is that the wheat has broken dormancy and is actively growing again. Generally, wheat will be at a growth stage of Feekes 3 or 4 when this occurs. The appropriate method for collecting wheat samples at this stage is to collect 25 or more whole plants from ½ inch above the soil surface. One of the benefits of early season wheat sampling is to fine tune a “green-up” nitrogen application based on the nitrogen content of the plant at Feekes 5 (please visit the Purdue Extension News Release for more information).
Image: Feekes 5 wheat. Source: Kansas State University
Once the plants reach Feekes 6 and beyond, indicated by stem elongation and jointing, only the most recent fully developed leaf should be sampled. The most recent fully developed leaf is the highest leaf on the plant with a fully developed collar. Once the plant begins heading (Feekes 10 and beyond), the flag leaf should be sampled. Generally, 40 to 50 leaves should be sampled at these growth stages.
Accurate plant tissue testing begins with proper sample collection and handling. Make sure to collect the proper plant part for the current growth stage of the crop, and collect the proper number to make the sample. This information can be found on the plant analysis page at algreatlakes.com. Always avoid soil contamination in your plant samples. Package samples in paper bags. If shipping is delayed, store samples in a cool location, but do not freeze. Never include roots with a plant sample. If you have any questions on proper plant tissue sampling, please contact the lab for assistance.
Tradeshows offer a great opportunity to get out and talk to many of our customers, as well as to see what is new and exciting in the industry. We attend or exhibit at a number of tradeshows throughout the late fall and winter. Some of our upcoming shows include:
Date | Location | Tradeshow or Event |
Dec. 4-6, 2018 | Grand Rapids, MI | The Great Lakes Fruit, Vegetable and Farm Market EXPO |
Jan. 14-16, 2019 | Lansing, MI | Michigan Agribusiness Association (MABA) Winter Conference and Trade Show |
Jan. 15-17, 2019 | Madison, WI | Wisconsin Agribusiness Classic - Wisconsin Agri-Business Association (WABA) |
Jan. 15-17, 2019 | Ft. Wayne, IN | Fort Wayne Farm Show |
Jan. 23-25, 2019 | Indianapolis, IN | Agribusiness Council of Indiana (ACI) Conference & EXPO |
Jan. 28-30, 2019 | Peoria, IL | Illinois Fertilizer and Chemical Association (IFCA) Annual Convention and Trade Show |
Jan. 28-31, 2019 | Phoenix, AZ |
Compost 2019 - U.S. Composting Council Conference and Trade Show |
Jan 31-Feb. 1, 2019 | Columbus, OH |
Ohio AgriBusiness Association (OABA) Industry Conference |
Please stop by and say hi!
Thank you to everyone that shared pictures for the 2019 A&L Great Lakes Customer Calendar, and to those who voted for their favorite on our Facebook site. Last year we were amazed by the quality of the photos we received, and this year that bar was raised even higher! This year we let the people have more of a say in the calendar design and left the winning photo selection to our followers on social media. The task was a difficult one as all of the pictures were incredible in their own way.
We are pleased to announce that Lydia Holste of Altamont, IL was our winner with a photo of a family dinner at harvest time. Lydia will receive $250 for her winning photo.
Second place went to Cary Crop Farms of Mount Pleasant, MI, with a picture of fall harvest. They will receive $150.
Third place was Paige Sullivan from Montgomery, IN, with a picture of a spider web at harvest time. Paige will receive $50.
These pictures and others will be published in the A&L Great Lakes 2019 calendar later this fall.
A good understanding of the amount of plant nutrients removed from the soil in the harvested portion of a crop is an important aspect of nutrient management. While a number of sources provide estimates of the amount of plant nutrients removed with a harvested crop, more precise nutrient removal values can be obtained by analyzing the concentration of nutrients in the crop. This can be done by submitting grain samples for a Crop Nutrient Removal Analysis.
There are several factors that can cause the actual concentration of nutrients in a given crop to vary from the average, including weather conditions, plant genetics, management practices, and soil properties
Nutrient removal analysis is similar to other plant tissue analyses in which the material is dried, ground and digested so that the concentration of various nutrients such as nitrogen, phosphorus, potassium, sulfur, calcium, magnesium, and various micronutrients can be determined for the sample. For grain samples, the results are then calculated and expressed as pounds per bushel based on a standard test weight and moisture content for a given crop. As with any other analysis, proper sample collection is crucial. For grain crops, collect a sample of grain that best represents the entire area, and submit 1 to 2 cups to the lab for analysis. Results will be presented on a pound per bushel and pounds per acre basis. The crop removal data can be reported based on the actual crop yield for the sampled area if the yield is provided for the submitted sample.
The utility of this type of analysis is not limited to grain samples. This data can be very useful for determining nutrient removal for other commodities such as fruits, vegetables, hay, straw, and silage. Since harvesting these crops often removes greater amounts of vegetative material and the concentration of nutrients in vegetative parts of a plant can be quite variable, nutrient removal values can differ considerably. To analyze for nutrient removal in these crops, submit 1 to 2 pounds of material for analysis.
Although considerable differences may exist between the results of a specific analysis and the reference values, this data is not intended to assess the fertility status of a crop or diagnose nutrient deficiencies. While nutrient removal data can be a valuable tool for managing soil fertility, it is only one piece of the puzzle. A good routine soil sampling plan remains the basis for a sound soil fertility program.
Laboratory data is an important and valuable asset. As an independent laboratory, it is important for us to assure our clients that their data remains their property, and that safeguards are in place to prevent information from being released to individuals not entitled to it.
We are occasionally requested by a client to send copies of reports or data files to someone else. We are very happy to do this, but are aware of the importance of this data. Our primary responsibility regarding the confidentiality of our reports is to our client that is invoiced for the services provided. That report may represent samples that were taken for a customer of our client, but the data is still the property of our client, not their customer.
In order to release data to another party, we require approval from an authorized representative of our client. The preferred method is by email or letter, but can be given via phone call if that is the most convenient. We recognize that this might be extra work for you, but we want to ensure that your information is protected.
If data is to be routinely copied to another party, information regarding this can be set up in our client database. If changes in client personnel or addresses occur, we need to be notified so that data is not sent to an incorrect address. Please contact the lab regarding your account if you need to verify or change who is authorized to receive your data.
The majority of our soils in the Great Lakes region require regular liming in order to maintain pH levels that are within the appropriate range to maximize crop growth and productivity. The quality and effectiveness of a liming material can vary tremendously depending on the source, composition, and physical properties of the material, so having a reliable lime analysis is critical to ensure that the proper type and quantity of liming material is used to get the desired effect.
Agricultural lime quality is usually measured by three characteristics:
A number of materials can be used to increase the pH of the soil, but historically the most common material is ground limestone, commonly referred to as ag lime. Ag lime is finely ground rock containing high levels of calcium carbonate (CaCO3) and magnesium carbonate (MgCO3). It is actually the carbonate (CO3-) in lime that reacts with acidity (hydrogen) to increase soil pH.
Calcium and magnesium in lime, in addition to being essential plant nutrients, exchange with hydrogen (H+) held on cation exchange sites, moving H+ into soil solution where it can be neutralized by carbonate.
Particle size determines how quickly lime will dissolve and react in the soil. Generally, 40-50% of the particles in a good quality liming material will pass through a 60-mesh sieve. States in this region have different lime quality systems, with state-specific terminology and measurements.
A&L Great Lakes offers a Fact Sheet, entitled Adjusting Lime Rates, which provides details on how to make adjustments. A & L Great Lakes has also developed a spreadsheet which outlines various states’ systems and helps adjust rates for a particular liming material. These useful tools are available from our website at www.algreatlakes.com.