The University of Maryland offers a fee-based, soybean variety performance testing program to local and national seed companies. The results from these replicated trials provide agronomic performance information about soybean varieties tested at four locations in Maryland considered representative of the state’s geography and weather conditions. Table 1 summarizes the agronomic and production information for each test site.
Varieties tested in 2021 were entered by participating seed companies, listed in Table 2, that were solicited for submission of varieties. These varieties represented those currently available for purchase to experimental lines still under evaluation. Select Pioneer and Syngenta varieties were identified for use as checks in the test. The inclusion of the performance data for check varieties that are proven performers in the Mid-Atlantic region allows comparisons of newer varieties to proven varieties.
During 2021, 85 varieties were tested using four maturity groups: MG 3 (22 varieties, Table 6), early MG 4 (4.0-4.3, 21 varieties, Table 7), late MG 4 (>4.4, 36 varieties, Table 8) and MG 5 (6 varieties, Table 9). Check varieties were included in each of the tests. All genetic traits and seed treatments are listed in Tables 6-9.
Each variety was replicated three times per location. For 2021, we modified a John Deere Maxemerge 2 four-row, 30” spacing, no-till planter, with coulters and trash wheels. The modifications included the addition of a single cone planting unit that delivered seed to a spinner powered by a 12v motor to evenly distribute seed to the four planter units (Figure 1). Planting, harvest, and in-season management information is presented in Tables 1 and 2. We aimed for a seeding rate of 6-7 seeds/foot and plot harvest length was approximately 20 feet, but harvested plot length varied slightly across locations. Center two rows (~5 ft. swath) were harvested with an Almaco R1 research combine (Almaco Co., Nevada, IA). Grain yield, harvest moisture, and test weight were measured for each plot. These data were collected with a Seed Spector LRX system (Almaco Co., Nevada, IA) and recorded on Microsoft xTablet T1600. Due to the fabrication of the new planter, planting dates were slightly delayed – especially in the double crop tests. We believe this negatively impacted yields in these tests. Additionally, there was ample stover present on the surface at Central Maryland Research and Education Center when planting, and we believe poor seed-to-soil contact at planting negatively impacted yield at this location. Despite late planting, we were able to harvest plots in a timely manner, due to favorable fall weather conditions.
Test Results
The overall performance across the locations for the full season varieties in each maturity group is reported in Tables 10-13 and double crop varieties in Tables 28-31. Variety performance at individual locations can be found in Tables 14-27. The agronomic characteristics reported are yield, in bushels/acre at 13% moisture content, test weight (lb/bu) at 13% moisture, height in inches (at Wye location, one replication) and date to maturity (at Wye location, one replication).
A least significant difference (LSD) value is reported for each test where statistically significant differences (P ≤ 0.1) for yield was observed among varieties. The mean separation value has been calculated at the 10% probability level (LSD0.1). The LSD can be used to compare two varieties within the same test. For example, when the yield difference between two varieties is greater than the LSD value, there is a 90% certainty that the difference in yield is due to variety performance rather than due to random variability.
Relative Yield
The selection of a variety based solely on performance at one location is not recommended. It is better to select variety based upon performance over a number of locations and years, if possible. To compare the performance of each variety across the five locations, relative yield tables (Tables 32-35) are included. Relative yield is the ratio of the yield of a variety at a location to the mean yield of all the varieties at that location expressed in percentage. A variety that has a relative yield consistently greater than 100 across all testing locations is considered to have excellent stability.
Acknowledgments
The University of Maryland Agronomy Trials Center work would not be possible without the assistance and oversight of equipment maintenance, seed packaging, planting, data collection, and plot harvest by faculty research assistant, Louis Thorne. This work could not be accomplished without the assistance of research technician Joseph Crank during the season. Also, we acknowledge the undergraduate students for their assistance with seed packaging. Thank you to the crew at Wye Research and Education Center for sharing your experience, tools, and space in your shop with Louis Thorne as he continues to keep our equipment running. Table 1 outlines the crews at each test location who assisted with land preparation, flagging, plot management, and harvest. I personally would like to acknowledge each farm manager, David Armentrout, John Draper, Ryan McDonald, and Douglas Price for their continued support of the Agronomy Trials Center and their continued patience with me.
Additional Information
The inclusion of varieties in these tests is not an endorsement by the University of Maryland. Advertising statements about a company’s varieties can be made as long as they are accurate statements about the data as published. Statements similar to “See the Maryland Soybean Tests Agronomy Facts No. 32” or “Endorsement or recommendation by the University of Maryland is not implied” must accompany any reproduced information.
Nicole Fiorellino, Extension Agronomist University of Maryland, College Park
The results of the 2020 Maryland Soybean Variety Trials are now available. Click on the link below to download the full report, or contact your local ag extension agent for a hard copy. You may also view the report, along with past variety trial reports, at: https://psla.umd.edu/extension/md-crops
Nicole Fiorellino, Extension Agronomist University of Maryland , College Park
Results of the 2020 University of Maryland corn hybrid trials are available to view by clicking the link below, or you may visit: https://psla.umd.edu/extension/md-crops. Questions may be directed to Nicole Fiorellino (nfiorell@umd.edu)
Amanda Grev, Pasture and Forage Specialist University of Maryland Extension
As new forage varieties continue to be developed and released, the efficacy and performance of these varieties needs to be evaluated. Similarly, as forage and livestock producers are making decisions on which forage species and variety to establish, it is helpful to compare performance data from a number of available varieties. To this end, the University of Maryland Extension Forage Team is in the process of establishing a series of forage variety trials.
In September 2019, an orchardgrass variety trial was established at the Western Maryland Research and Education Center (WMREC) in Keedysville, MD in order to evaluate select orchardgrass varieties based on forage production and quality. Plots were arranged in a randomized complete block design with each individual entry replicated four times. All varieties were planted at a rate of 25 pounds per acre; seed was broadcast and then cultipacked to establish good seed-to-soil contact. The varieties planted included: Alpine, Bounty II, Extend, HLR Blend, Inavale, Olathe, Pennlate, and Rushmore II.
Data collection began when the majority of forage varieties reached the boot stage of development (prior to seed head emergence). The first cutting occurred on May 18, 2020; this was followed by a second cutting on August 3, 2020 and a third and final cutting on September 28, 2020. At each cutting, forage biomass was collected along a 3 ft. by 20 ft. strip from the center of each plot using a forage harvester set to a cutting height of 4 inches. Collected biomass was weighed, dried in a forced air oven, and weighed again for dry matter and forage yield determination. Sub-samples were also taken from each plot and sent to a commercial laboratory for forage quality analysis.
Seasonal cumulative yield for all orchardgrass varieties ranged from 3.6 to 3.8 tons per acre (Figure 1). Statistical analysis indicates no significant difference in forage yield among any of the varieties for the 2020 growing season. Forage quality analysis is underway; forage quality results will be shared once the analysis is complete.
A big thank you to Jeff Semler and the entire WMREC crew for their assistance in getting this trial started and their help with harvest and data collection. Seed for this study was donated by DLF Pickseed, Seedway, and Kings Agriseeds. These plots will continue to be evaluated for yield, quality, and additional performance parameters in the coming years. We hope to expand the trial to include multiple locations, as well as additional forage species and varieties.
Figure 1. Orchardgrass forage variety trial yield results for 2020, presented as total seasonal yield in tons per acre. Varieties marked by a common letter indicate similar yield production (i.e. no significant difference).
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.
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.
The 2019 UMD small grain variety trial data concerning Fusarium head blight (head scab) and DON vomitoxin information is now available. Click the link below to view the report:
