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.
Jim Eichhorst, State Executive Director in Maryland, USDA Farm Service Agency
The clock is ticking… March 16 is the last day to make what is likely one of the most important business decisions you will make for your farming operation this year.
If you have not already visited your local Farm Service Agency (FSA) county office to make your election for either the Agriculture Risk Coverage (ARC) or the Price Loss Coverage (PLC) program and to sign your annual enrollment contract, you should call and make your appointment now.
Many of you are gearing up to head to the field for spring planting, but I cannot stress enough the importance of not letting this deadline get lost in the hectic day-to-day obligations of farm life. If you fail to enroll for 2019 ARC or PLC, you will be ineligible to receive a payment for the 2019 crop year. ARC and PLC provide financial protections to farmers from substantial drops in crop prices or revenues and are vital economic safety nets for most American farms. These programs cover 20 commodities produced in the U.S. FSA anticipates more than 1.7 million producers will enroll in ARC or PLC – that’s a lot of producers to assist in a short period of time.
Want to maximize your time visiting with FSA? Inquire about deadlines and options for also enrolling in 2020 ARC or PLC and updating PLC payment yields. Our staff will help you make the most out of your visit or set you up with a future appointment to help check FSA programs off your lengthy “to do” list.
If you’re still unsure about the choice of ARC or PLC, we offer online decision tools to help you determine the best program election for your farming operation. To access these tools, visit www.fsa.usda.gov/arc-plc. Call FSA today for an appointment.
To locate your local FSA office, visit farmers.gov/service-center-locator. We know that time is money… so make the time to avoid losing the money.
The Delmarva Soil Summit will be held on February 26 & 27 at the Delaware Technical Community College in Georgetown.
Whether you farm 2 acres or 2,000 acres, this conference will deliver information that’s relevant to your farm’s scale and production type. We’re bringing in experts from around the country, and bringing you the latest updates from researchers right here on Delmarva. With learning tracks and farmer panels for both large-scale commodity farmers and small-scale diversified growers, there’s something here for everyone!
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).
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
(Cru)
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.
Sources
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).
Afful, E., Illahi, N. & Hamby, K. Agronomy News. 10, 2–4 (2019).
Reisig, D. & Goldsworthy, E. Efficacy of Insecticidal Seed Treatments and Bifenthrin In-Furrow for Annual White Grub, 2016. Arthropod Manag. Tests43, 1–2 (2017).
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).
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
Funayama, K. Influence of pest control pressure on occurrence of ground beetles (Coleoptera: Carabidae) in apple orchards. Appl. Entomol. Zool.46, 103–110 (2011).
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.
Locations
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
Kelly Nichols, Agriculture Agent Associate & Matt Morris, Agriculture Agent University of Maryland Extension, Frederick County
Soybean population plots were planted on two farms in Frederick County near Thurmont and Tuscarora on June 4 and 7, respectively. Planted populations were 80, 100, 120, 140, and 160 thousand plants per acre (ppa). The Thurmont plots were planted on 30-inch spacing with three replications. The Tuscarora plots were drilled on 7.5-inch spacing with four replications.
On July 1, initial population counts were taken at both farms. At the Thurmont farm, plots ranged from 79 to 88 percent germination. At the Tuscarora farm, plots ranged from 88 to 98 percent germination (Table 1). This is consistent with the germination percentage of the seed.
Plots were harvested on October 3 and October 24 at the Tuscarora and Thurmont farms, respectively. The average yield for each farm individually and combined were calculated (Table 2). Yield ranged from 61 to 70 bu/A. Overall, yield differences between the populations were within three bu/A. While a complete statistical analysis has not been conducted, the trend of the data indicates that planting at a lower population, such as 120,000 or 100,000, would allow for reduced seed costs while still maintaining optimum yield.
The variety used at the Thurmont farm was Pioneer P37A69, which retails for $71.00 per unit of 140,000 seeds. The variety used at the Tuscarora farm was Hubner 38-27R2X, which retails for $59.00 per unit of 140,000 seeds. (Note that these costs do not include any discounts or seed treatments.) At the time of harvest, soybeans were $9.51/bu on the Chicago Board. The net dollar amount was calculated by subtracting the seed cost from the gross amount per acre. At the Thurmont farm, the 100,000 planting population had the highest net per acre at $598.19, while the 140,000 and 160,000 populations had the lowest net, around $581/A (Table 2). At the Tuscarora farm, the 120,000 planting population had the highest net per acre at $560.13, while the 160,000 population had the lowest net at $515.76/A.
Planting at lower populations, around 100 to 120 thousand ppa, may not reduce yield or net per acre, indicating that this is a potential for cost savings on farms. We are planning to conduct this study again next year at more locations around the state. To stay up to date with this research project, visit https://go.umd.edu/FCagresearch.
Table 1. Initial Population Counts, July 1.
Thurmont Farm
Tuscarora Farm
Planted Population
(1000 plants per acre [ppa])
Initial Population (1000 ppa)
% Germination
Initial Population (1000 ppa)
% Germination
80
63
79
71
88
100
85
85
88
88
120
95
79
117
98
140
123
88
124
88
160
135
84
153
96
Table 2. Average Yield at 13.5% Moisture and Net Profit in $/A.
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.
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.
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.
