February WASDE

Dale Johnson, Farm Management Specialist
University of Maryland

Information from USDA WASDE report

Attached is a summary for the February WASDE published Tuesday. There was a 50 million bushel increase in the estimate of corn use for ethanol but this increase was offset by a 50 million decrease in the estimate of corn exports and so there was no change in supply, demand or ending stocks.

There was a significant 50 million bushel increase in the estimate for soybean exports. With all other supply and demand factors unchanged this decreased the stocks to use ratio from 11.9% to 10.5%. However, this was anticipated so there was no significant increase in Soybean futures on Tuesday.

There was a 25 million bushel increase in the estimates for wheat exports with all other supply and demand factors unchanged. However with the large ending stocks of wheat, this change was relatively insignificant.

2020 February WASDE


Call for Farmer participants in organic grain transitions project

Researchers at the University of Maryland are looking for farmers interested in partnering with them on a project to help develop strategies for transitioning to organic grain production. Please see the attached flier for details. Contact Dr. Ray Weil for additional information (rweil@umd.edu).

Organic Transitions1page announcement Jan2019

At-planting treatments for controlling early-season insect pests in corn

Maria Cramer, Edwin Afful, Galen Dively, and Kelly Hamby
Department of Entomology, University of Maryland

Slug feeding damage: characteristic long, thin holes made by a rasping mouthpart.

Background: Multiple insecticide options are available for early-season corn pest management, including neonicotinoid seed treatments (NSTs) and in-furrow pyrethroids such as Capture LFR®. In addition, many Bt corn hybrids provide protection against seedling foliar pests such as cutworm and armyworm. Given that almost all corn seed is treated with neonicotinoid seed treatments (NSTs), Capture LFR® may not provide any additional protection.

Methods: In this study we compared four treatments: fungicide seed treatments alone; Capture LFR® (active ingredient: bifenthrin) applied in the planting furrow with the fungicide seed treatment; Cruiser Maxx® 250, an NST (active ingredient: thiamethoxam), which includes a fungicide; and Capture LFR® + Cruiser Maxx® 250 together. We evaluated the amount of soil and foliar pest damage after emergence. Yield was measured at harvest.

Preliminary results: Our results suggest that when wireworm pressure is high, Capture LFR® and Cruiser Maxx® 250 protect against damage and significantly increase yields. Neither treatment is superior, so we recommend using only one, and only in fields where pest pressure is known to be high. As most corn seed already contains NSTs, use of Capture LFR® at planting is unlikely to be warranted.

Sampling for soil and foliar pests

Background: Capture LFR®, an in-furrow pyrethroid product, is marketed for control of early-season corn pests, including soil pests such as white grub and wireworm and above-ground pests such as cutworm and armyworm. However, the insect pest management systems already adopted in corn may provide sufficient protection. Most corn seeds are treated with NSTs, which provide seedlings with systemic protection from many soil and above-ground pests. Additionally, most Bt corn hybrids express proteins with efficacy against cutworm and armyworm in the seedling stage, although they do not affect soil pests. Unlike NSTs and Bt traits, pyrethroids are not systemic and do not provide protection beyond the soil area to which they are applied.

While in-furrow applications of bifenthrin (the active ingredient in Capture LFR®) can effectively reduce wireworm damage in potatoes1 and provides white grub control in field corn2,3, it does not consistently increase yield in corn3 or soybeans4. Yield benefits are likely to be seen only where there is known soil pest pressure. Meanwhile, preventative applications of pyrethroids have been linked to declines in natural enemies 5,6, including carabid beetles, which are important predators of slugs.

Objectives: Our objectives were to determine whether in-furrow applications of Capture LFR® (bifenthrin) provided 1) protection against soil pests, 2) protection against seedling pests, and 3) yield benefits compared with fungicide alone, Cruiser Maxx® 250, or combined with Cruiser Maxx® 250.

Methods: This study was conducted in 2018 and 2019 at the University of Maryland research farm in Beltsville, MD. We planted 4 replicate plots of a standard Bt field corn hybrid, TA 758-22DP (VT Double Pro insect control) in 2018 and LC1488 VT2P (SmartStax RIB complete insect control) in 2019 at 29,999 seeds per acre. Plots were planted late in 2018 (June 18) but on time in 2019 (May 20). Standard agronomic growing practices for the region were used. We compared the following four treatments, applied at planting:

  No in-furrow application In-furrow Capture LFR®

Applied at 13.6 fl oz/ac

Fungicide seed treatment Fungicide (F) seed treatment alone

2018: Maxim Quattro®

2019: Vibrance Cinco®

Fungicide +

Capture LFR® (F + Cap)


Cruiser Maxx® 250 Cruiser Maxx® 250


Cruiser Maxx® 250 + Capture LFR® (Cru +Cap)

We sampled plants 24 days after planting in 2018, and 18 days after planting in 2019. In 2018, we recorded the number of stunted plants (indicating potential soil pest damage), and in 2019, we dug up stunted plants and recorded those for which soil pest damage could be confirmed. In both years, we assessed rates of above-ground feeding by pests such as cutworm and armyworm.

Wireworm (left) and characteristic above-ground symptoms of wireworm feeding (right). Note wilted center leaf.Results: Soil Pests. In 2018 there was no difference in the percent stunted plants between treatments (Figure 1), with less than 5% stunting in all treatments. This low level of pest damage may have been due to the late planting date, which could have avoided peak soil pest pressure. In 2019, all of the insecticide treatments had significantly lower soil pest damage than the fungicide control (Figure 1). Combining Capture LFR® with Cruiser Maxx® 250 was not more effective than Cruiser Maxx® 250 alone, but was more effective than Capture LFR® alone, suggesting that treatments involving Cruiser Maxx® 250 are somewhat more effective against the soil pests at this farm. In both years, plots were located in a field with a history of wireworms; however, damage was only observed in 2019. In a field without pest pressure, such as we saw in 2018, these treatments did not improve plant stand.

Foliar pests. In both 2018 and 2019, rates of foliar damage were extremely low (below 5% of plants) in all treatments and there were no differences between treatments.

Yield. In 2018, there were no yield differences between the treatments (Figure 2). Overall, we had low yields in 2018, likely a result of the late planting date. In 2019, all of the insecticide treatments had significantly higher yields than the fungicide control, with no differences between any of the insecticide treatments (Figure 2). Combining Capture LFR® with Cruiser Maxx® 250 did not increase yield.

Figure 1. 2018 and 2019 soil pest pressure, Beltsville, MD. Mean percent plants damaged for four treatments: F=Fungicide, F+Cap= Fungicide + Capture LFR®, Cru=Cruiser Maxx® 250, Cru+Cap= Cruiser Maxx® 250 + Capture LFR®. In 2018, treatments did not impact stunted plants (N.S.) In 2019, all insecticide treatments significantly reduced soil pest damage (columns with different letters have significantly different mean damage).
Figure 2. 2018 and 2019 yields, Beltsville, MD. Mean yield for four treatments: F=Fungicide, F+Cap= Fungicide + Capture LFR®, Cru=Cruiser Maxx® 250, Cru+Cap= Cruiser Maxx® 250 + Capture LFR®. Yields were not significantly different in 2018 (N.S). In 2019, all insecticide treatments had significantly higher yield than the fungicide only treatment (columns with different letters have significantly different mean yield).

Conclusions: In 2018 and 2019 we did not see sufficient foliar pest pressure to justify an insecticide application. This may be due to effective control by Bt proteins in the corn hybrids and/or low foliar pest pressure.

In a field with established wireworm pressure, all three insecticide treatments reduced soil pest damage and improved yield relative to a fungicide only control in the 2019 field season. While there were differences in pest damage levels between the different insecticide treatments, no one treatment provided superior yield benefits. Because nearly all corn seed is treated with NSTs like Cruiser Maxx® 250, additional applications of Capture LFR® may not be necessary. Preventative applications increase costs and present risks to beneficial insects without providing yield benefits. Additionally, soil pest pressure tends to be low throughout Maryland. We sampled untreated corn at five locations across Maryland in 2019 and found on average less than 3% soil pest damage. Unless a field has a known history of wireworms or white grubs, we do not recommend using at-planting insecticides.

Acknowledgements and Funding. This project was funded in both years by the Maryland Grain Producers Utilization Board. We appreciate the help provided by Rachel Sanford, Madison Tewey, Eric Crandell, Gabriel Aborisade, and Kevin Conover.


  1. Langdon, K. W., Colee, J. & Abney, M. R. Observing the effect of soil-applied insecticides on wireworm (coleoptera: Elateridae) behavior and mortality using radiographic imaging. J. Econ. Entomol. 111, 1724–1731 (2018).
  2. Afful, E., Illahi, N. & Hamby, K. Agronomy News. 10, 2–4 (2019).
  3. Reisig, D. & Goldsworthy, E. Efficacy of Insecticidal Seed Treatments and Bifenthrin In-Furrow for Annual White Grub, 2016. Arthropod Manag. Tests 43, 1–2 (2017).
  4. Koch, R. L., Rich, W. A., Potter, B. D. & Hammond, R. B. Effects on soybean of prophylactic in-furrow application of insecticide and fertilizer in Minnesota and Ohio. Plant Heal. Prog. 17, 59–63 (2016).
  5. Douglas, M. R. & Tooker, J. F. Meta-analysis reveals that seed-applied neonicotinoids and pyrethroids have similar negative effects on abundance of arthropod natural enemies. PeerJ 1–26 (2016). doi:10.7717/peerj.2776
  6. Funayama, K. Influence of pest control pressure on occurrence of ground beetles (Coleoptera: Carabidae) in apple orchards. Appl. Entomol. Zool. 46, 103–110 (2011).


2020 Grain Marketing Workshop

Friday January 10, 2020 from 8:00am – 11:30am

This breakfast meeting will include speakers on various topics in grain marketing.  Come have breakfast and discuss this year’s strategies for marketing your grain. Speakers include marketing specialists, traders and more.  Topics include local and national grain outlook for 2020, tax considerations, crop insurance and the farm bill.


In person:

  • Chesapeake College, Wye Mills, MD Higher Education Center HES-110. Contact Shannon Dill, sdill@umd.edu or call 410-822-1244.

Broadcast to:

  • Charles County Extension, 9501 Crain Hwy, Bel Alton, MD 20611. Contact Alan Leslie, aleslie@umd.edu or call (301) 934-5403
  • Harford County Extension, 3525 Conowingo Rd., Suite 600, Street, MD 21154. Contact Andy Kness, akness@umd.edu or call (410) 638-3255
  • Somerset County Extension Office, 30730 Park Dr, Princess Anne, MD 21853. Contact: Sarah Hirsh, shirsh@umd.edu or call (410) 651-1350

Mn, Zn, and B Starter for Corn Production

Jarrod Miller, Extension Agronomist & Amy Shober, Professor & Nutrient Management Extension Specialist
University of Delaware


Micronutrient deficiencies are commonly exhibited in agronomic crops grown on Delaware’s sandy, low organic matter soils. In 2018, University of Delaware researchers conducted a study at the Carvel Research and Education Center (Georgetown, DE) to examine corn response to manganese (Mn), zinc (Zn), and boron (B) in starter fertilizer. Two rates of Mn (0.25 and 0.5 lb/ac), Zn (0.5 and 1.0 lb/ac), and B (0.15 and 0.30 lb/ac) were applied as a liquid starter with the planter.

The goal of this project was to increase yields with additional starter applications of Mn, Zn, or B, which did not occur. However, based on the soil test UD recommendations, no additional micronutrients were called for (Shober et al., 2019). Fields deficient in Mn, Zn, or B (based on UD recommendations) would still benefit from their addition as a starter band or foliar application.

Although starter applications of B did not produce a yield effect, tissue concentrations of B increased with yield. Predicting B availability is difficult, as it is more prone to leaching than other micronutrients. With lower tissue B concentrations related to stand counts, there is potential evidence that B leached below the root zone in saturated soils. It is possible that B would benefit from split applications, similar to N management.

The application of B increased Mn content in ear leaf tissue, but not yields. Across all treatments there was a positive relationship between B and Mn uptake. The relationship between these two nutrients in should be investigated further.

Read the full report here.


What do the numbers really mean? Interpreting variety trial results

Andrew Kness, Agriculture Extension Agent | University of Maryland Extension, Harford County
Dr. Nicole Fiorellino, Extension Agronomist | University of Maryland, College Park

Each year, the University of Maryland, and other land-grant universities across the US, conduct agricultural variety trials that provide farmers and other professionals in the industry with valuable data on crop performance. These data provide critical information regarding varietal differences, such as yield, plant characteristics, disease resistance, and geographic performance, which aid producers in making the best decisions on variety selection for their farms.

Reports from University variety trials are generated yearly, and can be quite lengthy and may contain values, metrics, and other information that require explanation. If you are going to utilize variety trial data to make on-farm decisions, it is important to understand how to read and interpret the data so that you are able to draw the correct conclusions. For example, it is easy to simply search the tables for the top-yielding variety and dismiss the rest of the information. This article will explain how and why variety trials are set-up the way they are, walk you through what the data mean, and how to interpret the statistics and make sound conclusions based on those statistics.

The primary objective of a variety trial field study is to test the performance of crop hybrids relative to each other and relative to check varieties embedded in the study. To do this, the trials are designed in such a way as to eliminate as much variability as possible to strengthen our ability to detect a difference in hybrid performance. As with anything in agriculture, there is a lot of variability associated with conducting research in the field. Variations in weather, soil types, and pest pressure are just a few of the factors that introduce variability in our research. In order to help control for this variability, variety trials are designed as small plots (often 10 feet wide x 30 feet long) and placed in a field with consistent soil types – again, to minimize variability. All the plots are treated exactly the same in respect to planting date, planting depth, harvest date, data collection, pest management, and fertility; the only variable we allow to be different is variety. In addition, each variety is replicated multiple times within one field, usually 3-5 times at random locations within one field. This randomized replicated plot design helps to minimize the effects of the spatial variability that we do not have control over (such as weather, soil type, and pest pressure). Figure 1 depicts a randomized plot design that contains four varieties replicated four times.

Figure 1. Example field plot design with four varieties replicated four times in a randomized block plot design.
Figure 1. Example field plot design with four varieties replicated four times in a randomized block plot design.

The data that are collected from these plots are then used to compare each variety to the others in the trial using statistical methods, which is typically an analysis of variance (ANOVA). An ANOVA test compares each treatment (or variety in this example) with each other, taking into account the variation in the data. Figure 2 on the next page is a table from the 2019 University of Maryland Corn Variety Trials for mid-season maturity corn hybrids at Keedysville, MD. There is one number listed for yield for each variety, but this number is actually an average of the yield for the three plots, or replicates, of each variety that were planted and harvested. For example, yield for LG62C02VTRIB, reported as 223 bushels per acre, is the average of 226, 231, and 212 bushels per acre, collected for each of the three plots planted at this location. Since the yields were not identical for each of the plots, there is variation about the average yield. The ANOVA test compares the variation in average yield for each variety to determine if the numerical difference in average yield is due to differences in variety performance or due to random chance. The ANOVA test takes into account a confidence interval, which we define prior to the study. In the scientific field of agricultural research, it is generally acceptable to define your confidence interval between 90-95%. This means that we are 90-95% confident that the differences observed between varieties is due to the variety performance and not some other factor (such as weather, soil type, etc.). This confidence means it is likely this difference in variety performance would likely be observed if the comparison was repeated under similar conditions.

With the basic concept in mind, return back to Figure 2. One might think that hybrid DKC61-41RIB out-yielded NK 1205-3120 by 6.4 bushels per acre. It is true that it did; however, we plan to utilize this data to make predictions going forward; in other words, will DKC61-41RIB consistently out-yield NK 1205-3120, or is the 6.4 bushel difference we observed in yield due to random effects? This is where we need to use statistics to answer these questions.

The bottom four rows of the table in Figure 2 are where you will find the statistics to make inferences about the trial dataset. Trial mean is simply the average of all varieties in the trial, which is an indicator of how the trial performed as a whole and is used to calculate the relative yield. The next two rows, Probability > F and LSD0.1, are generated from an ANOVA test and are critical to interpreting the data correctly.

Probability > F (indicated as P > F in other reports) indicates the likelihood that what we observe in variation between varieties is due to random effects and not some other variable (in this case, variety). This value can be between 0 and 1. If this value is large, then it means that the differences we observe are due to random effect and not hybrid performance; therefore there are no yield differences between varieties. However, if the value is small, then there are differences between varieties that are not explained by random variation.

In this example for yield, Probability of > F is 0.0805, or 8.05%. As mentioned previously, for field research, confidence intervals are often set at 90-95%; which equates to a probability level of between 0.1 and 0.05 (defined as an “alpha level” in statistics). In this trial, the alpha level was defined as 0.1, as indicated by the subscript 0.1 after LSD. If the Probability > F is less than 0.1, we can conclude with at least 90% confidence that there is a difference in yield due to variety. If the value of P > F is greater than 0.1, then we conclude there were no yield differences between varieties. In this example, there are significant differences in yield, moisture, and test weight due to variety. We cannot conclude there is a difference in lodging or plant population as a result of variety. This means that statistically there is no difference in DKC59-82RIB with a lodging score of 1.4%, and P1197 AM, with a lodging score of 0%.

The next row in the table, LSD0.1, tells us the “least significant difference,” or the threshold that must be overcome to conclude that the performance of two varieties are significantly different. If the ANOVA test returns a P value that is greater than the defined alpha level (0.1 for our example), then there will be no significant differences between treatments, and LSD is denoted NS (not significant). If the test returns a P value less than the alpha level, then the LSD value will tell us what is considered a significant difference between treatments. For yield in the example above, there needs to be a difference of 12.4 bushels before we can say with 90% confidence that the difference in yield between any two hybrids is due to the variety and not random chance. The top yielding variety in this trial was DKC59-82RIB (highlighted). This variety yielded significantly more than all other varieties, except for SCS 1105AM. You will notice that the difference in yield between these two hybrids (8.4 bushels) does not exceed the cutoff defined by the LSD; therefore, they are not significantly different than each other. If there is a difference of at least 12.4 bushels between any two varieties in the trial, then we can conclude that there is a difference in yield that was caused by variety. In the example, the lowest yielding variety (LCX10-98 VIP3110) did not yield significantly less than any other variety except for the top two (DKC59-82RIB and SCS 1105AM).

The final statistic is the coefficient of variation (CV%). This is a measure of the variation in the data; the smaller the number, the less variability. Values for CV under 10% for yield tell us there was not too much variability in yield and that we are able to distinguish variety differences. The more variation in the dataset will require a larger LSD to separate differences between treatments.

Variety trials presented with statistical analyses provides a way for us to compare varieties as best we can in a real-world setting through replicated plots. When using variety trial data, it is best to choose varieties with yield stability and desirable characteristics across multiple locations and across multiple years, whenever possible. You will also find very similar statistical methods in not only variety trial reports, but for any type of replicated field research. These statistical analyses provide you with assurance that the conclusions drawn are due to treatments research and you could expect similar results if the comparison was repeated under similar conditions. If you encounter data or reports that do not have any type of statistical analysis presented, it is important to realize that you should not draw any conclusions from that dataset.


Evaluation of the performance of a soy protein seed lubricant

Dr. Nicole Fiorellino, Extension Agronomist
University of Maryland, College Park

With the arrival of a new seed lubricant product (DUST, Low Mu Tech, Calamus, IA), we evaluated its performance against two common seed lubricants, Graphite and Fluency (Bayer Crop Science, USA), and untreated check (UTC) plots in both corn and soybeans in 2019 at Wye Research and Education Center in Queenstown, MD. DUST is a soy protein lubricant and is reported to contribute to early plant vigor as well as be a cleaner alternative to commonly available seed lubricants such as graphite, which can create a mess for users of the product. As such, we utilized a completely randomized design with five replicates and evaluated emergence and early season vigor at 7, 14, and 21 days after planting (DAP). Stand counts were reported as number of 1,000 plants per acre, with plants counted in a 30 ft length of one corn row and plants counted in an area the size of 1/1000 of an acre in soybean plots. Early season vigor was assessed through collection of normalized difference vegetation index (NDVI) readings using a handheld Greenseeker sensor held approximately 1 m from the surface of the ground as the operator walked down the length of one corn or soybean row per plot. Corn was harvested when moisture approached 15% and yields are reported in bushels per acre corrected to 15% moisture.

Differences among seed lubricant treatments for plant population, early season vigor, and crop yield were analyzed using a mixed model analysis of variance using replication as a random variable using SAS 9.4 software. Coefficient of variation (CV%) are reported as a measure of variability at a test site and values less than 10% indicate enough precision existed to determine a significant difference.







Based on the measurements observed in 2019, the DUST soy protein seed lubricant is comparable to other seed lubricants commonly used in Maryland for corn and soybean planting. There were no differences in emergence or yield among the treatments for either corn, indicating all seed lubricants perform as well as each other and a control plot with no seed lubricant used. Additionally, there was no effect of seed lubricant on early season vigor, as indicated by the company. Additional extension reports will include soybean yield data and economic analysis of the products, as there is a difference in price and amount of product recommended for use and if product performance is similar, as indicated by these results, then product cost will be a deciding factor for use.

2019 Corn Variety Trials Results

Dr. Nicole Fiorellino, Extension Agronomist
University of Maryland, College Park

The University of Maryland offers a fee-based, corn hybrid performance testing program to local and national seed companies. The results from these replicated trials provide agronomic performance information about corn hybrids tested at five locations in Maryland considered representative of the state’s geography and weather conditions. During 2019, 56 hybrids were tested using three maturity groups: early season (17 hybrids), mid-season (14 hybrids), and full season (25 hybrids). Check hybrids were included in each of the five tests.

This year’s weather was welcomed compared to last year’s extreme precipitation. As reported in the results document, there was much less rainfall in 2019, with precipitation at all locations very similar to the long term average for each location. We experienced some drought at the end of summer (August through September in some locations), but yields did not seem to be impacted by this. Averaged over the five locations, yield for early (17), mid (14), and full (25) season hybrids was 196 bu/ac, 199 bu/ac, and 206 bu/ac, respectively. Compared to 2018, these yields were +11%, -1%, and +5%, respectively, to those observed for early, mid, and full season hybrids this season. Average yield for all hybrids tested at all five locations was 201 bu/ac or 10 bushels shy of the record yield of 211 bu/ac in 2011. Two locations had average yield greater than 210 bu/ac (Keedysville – 220 bu/ac and Clarksville – 236 bu/ac) with Clarksville average yield surpassing the record best location yield of 232 bu/ac at attained at Wye in 2016.

A list of hybrids and their performance across the state and at each individual location is presented in the results document, which can be downloaded from the MD Crops website at psla.umd.edu/extension/md-crops. You may also request a printed copy from your local Extension office.

Download the full report here: 2019 Corn Hybrid Trials Results.


November WASDE

Dale Johnson, Farm Management Specialist
University of Maryland

Information from USDA November WASDE report

Attached is the summary for the November WASDE published on November 8. After months of volatile WASDE estimates caused by weather and political events, the changes in estimates for the November WASDE are fairly small. Corn yield/acre estimate was down 1.4 bushels/acre to 167 bushels/acre. But the estimates for all areas of demand were also down slightly. The net effect is ending stocks down 19 million bushel to 1,910 million bushel and a stocks to use ratio of 13.7%.

Production and supply estimates for Soybeans were unchanged. Crushings  were down slightly which increase the ending stocks 15 million bushel and a modest increase in the stocks to use ratio to 11.9%.

There were only slight changes in Wheat estimates.

October WASDE

Dale Johnson, Farm Management Specialist
University of Maryland

Information from USDA October WASDE report

Attached is the summary for the September World Agricultural Supply and Demand Estimates (WASDE) that was published on October 10. Corn harvested acres and yields were slightly adjusted. The estimate for beginning stocks were down 331 million bushels. Estimate for total use was down 90 million bushel. Other minor changes result in an estimate of endings stock 261 million bushel lower and a decrease in the estimate of Ending Stocks to Use Ratio from 15.5% in September to 13.8% in October.

Soybean harvested acres estimate decreased from 75.9 to 75.6 million acres. Yield estimate was adjusted up 1 bushel per acre. Beginning stock estimate was adjusted down and ending stocks estimate was down 180 million bushel, which significantly decreased the stocks-to-use ratio from 15.9% to 11.4%. In June, the estimated Stocks to Use Ratio was 24.9% and has been decreasing every month. But market prices have not responded significantly because of the uncertainty in the soybean market caused by the trade war.

There were only slight changes in Wheat estimates.