Small Grains 2013 Introduction
Measured Crop Performance
Small Grains 2013
North Carolina State University
College of Agriculture and Life Sciences
North Carolina Agricultural Research Service
Raleigh, NC 27695
David Monks, Interim Director of Research
Crop Science Research Report No. 240
Across the state of North Carolina during the fall of 2012 growers planted 21,000 acres of barley, 35,000 acres of oats and 960,000 acres of wheat.
With the large number of commercially available and prospective varieties of oats and wheat, it becomes difficult for growers to select a superior variety suited for their particular area of the state. To make this decision, the grower needs up-to-date, unbiased, reliable information. The Official Variety Testing Program, through this report, seeks to provide that type of information.
Information on variety performance is presented from four test locations in the state. Also included are multiple-year performance data on a selected number of varieties.
The tests were located in the Piedmont, Coastal Plain, and Tidewater on research stations and private farms.
Entries: Commercial varieties and experimental lines developed by public and private agencies are included in these tests. Any individual or firm may make application for having entries included by writing the Official Variety Testing Program, Department of Crop Science, North Carolina State University, Raleigh, N.C. 27695-8604. A fee is charged on an entry basis for all private entries. A total of 7, 10 and 90 commercial varieties and experimental lines of barley, oats and wheat, respectively, were evaluated in the 2012 – 2013 season.
Field Plot Design: A randomized, complete block design with four to seven replicates was used at each location. Each plot consisted of eight rows, 7.5 inches apart, 22 feet long with 2.5 feet between each plot.
Crop Management: Cultural practices, such as seed bed preparation, date of planting, fertilization and topdressing were in accord with good farming practices and were uniform for all entries at a given location (Table 4); only those locations where data were collected are shown in this table. Prior to planting each test, soil samples were obtained from the test field and fertilizer and lime applications were made accordingly (Table 5). Seeding rate was 23 seed per row-foot.
Performance of a variety cannot be determined with absolute precision. Even though the tests are conducted in a uniform manner, uncontrollable variability exists among experimental plots due to differences in soil, fertility, moisture, insects, diseases, and other sources of variation. Because this variability exists, statistics are used as a tool to determine differences among varieties. The size of difference among varieties which may have been due to chance variation is listed in each table as the B.L.S.D. (least significant difference). Those varieties which do not differ by more than the B.L.S.D. are not statistically different. The B.L.S.D. K-50 is equivalent to the Fisher’s L.S.D. at the 10% level.
The coefficient of variability (C.V.) is listed as a general indicator of population variability; it does not, however, always indicate level of precision. The coefficient of determination (R2) is a better measure of the level of precision because it indicates the amount of variation accounted for in the trial. The higher the R2 value the more precise the trial. Thus, relative precision among various trials can be compared. The standard error of the mean (s.e.) is also listed as a general indicator of precision since it reveals how well the true mean was estimated. The formula for the s.e. is the square root of the error variance divided by the square root of the number of replicates. The error degrees of freedom (Error d.f.) used to test varieties is listed along with the mean of the test.
Variety performance may appear inconsistent among locations within an area or among years at a particular location, thus it is important for the reader to examine results from more than one location and more than one year to obtain a more accurate picture of relative variety performance.
Because new varieties are being introduced each year and these varieties are potentially higher-yielding than the current varieties, growers should closely examine two-year means provided in this bulletin. Research has shown that two-year means across locations provide the best predictors of performance the following year while at the same time including some of the newer varieties. Enough year to year variation in weather occurs to make single-year data less predictable than two-year data.
Other agronomic characteristics may be as equally important as yield. All available data regarding pathologic and agronomic characteristics of the varieties are found in Tables 1, 2 and 3 for barley, oats and wheat, respectively.
It is suggested that the grower plant a small number of acres in a new variety when first determining if it is adapted to his farm.
Research conducted at North Carolina State University and several other universities has consistently shown a significant yield advantage where professionally grown/certified seed is used rather than “farmer saved” or “brown bagged” seed. These tests were planted with professionally grown/certified seed provided by the sponsoring agencies. Farmers who use inferior seed sources can expect accompanying decreases in performances.
Yield, test weight, plant height and lodging are reported statewide. Yield and test weight are reported by location also. The lodging data are for lodging prior to harvest.
All plots were adjusted to 13% moisture. Additionally, all yield values reported here were further reduced by 23.6% to account for small plot border effects that have historically been determined in our field trials. Heading date, plant height, and lodging data are reported in Tables 1, 2 and 3 for barley, oats and wheat. Table 3 also lists disease ratings.
In calculating averages statewide, equal weight was given to each location; therefore, two and three-year averages may not appear to equal the average between years when the number of locations varies from year to year. Data in tables are ranked from high to low yield by the two-year average. Those wheat entries that were tested as experimentals appear at the bottom of the tables.
The 2012-2013 small grain growing season began with planting on time for the OVT program (Table 4). The fall was characterized with average to above-average temperatures once planting was begun and average to below-average temperatures in the winter months (see figures). Average temperatures and adequate rainfall was characteristic of the spring. The crop was maturing on schedule and luckily no spring freezes occurred.
Unfortunately the OVT program was unable to harvest at the ideal time due to Tropical Storm Andrea. The Union County and Robeson County small grain tests were discarded due to variability in stand. The Washington County small grain test was discarded due to severe wet conditions after planting. Test weights were good to low as a result of delayed harvest due to continuous rainfalls. Diseases were evident at most locations and ratings were recorded (a href=”https://officialvarietytesting.ces.ncsu.edu/wp-content/uploads/2017/02/SmallGrains2013_tab3.pdf”>Table 3). Spring infestation of Hessian fly was also evident.
A barley test was conducted at Rowan county. Data are presented in Table 6.
Data are presented in Table 7. Yields were good at both locations. Harvest was delayed due to continuous rainfall. Test weights were average.
One, two and three-year statewide averages are shown in Table 8 and Table 9. Yields were good at all locations (Tables 10-13). Test weights were average to below-average. Harvest was delayed at Lenoir and Rowan county locations due to continuous rainfall.
No systemic fungicide or insecticide seed treatments were used on entries this year except for AgriMAXX. AgriMAXX entered their varieties both non-treated and treated with an insecticidal seed treatment. A list of all seed treatments used on the entries is found in Table 14.
Two-year and three-year data across locations provide the best predictors of performance and is found in Table 8.
Milling quality data from last year are presented in Table 15. Thanks to Lonnie Andrews at Mennel Milling Company in Fostoria, Ohio.