Where does SARDA’s work go?

Plant counts are one of the data collection procedures we perform.

The simple answer is, to research. Of course, how that research is spread, interpreted, and implemented is a far more expansive question.

The process starts in the planning for SARDA’s research year. We have standard tests that a large number of research organizations across Alberta also take part in: RVTs, or regional variety trials. These trials are relatively simple, consisting of data collection on different crop varieties. Where the research goes is also a simple: the data is compiled and analyzed by the Alberta Seed Guide and ends up in some nifty charts. More local data is also published on our website, which only features our results for more localized information. You can find it at sarda.ca under ‘Publications’ and ‘Research Reports’.

We also do industry trials as a way to make enough money to keep SARDA running. The tests and results are only available to the company that orders the test, however. Our other trials come from a wide variety of sources. Researchers need data to test their hypotheses, so they come to us. We get clear instructions on the protocol needed when seeding, collecting data, and harvesting a trial. The foundation of good science is good data.

It is incredibly important to minimize the differences between what’s being tested so that the test is what causes the changes in data, not other factors. In agricultural science, this is incredibly difficult. A field isn’t nearly as sterile an environment than a lab. If we were testing fertilizer applications, for example, we need to make sure that other factors like weather, differences in soil composition, rain or snow, pesticide application, seeding density, etc. are as controlled as possible to make sure that differences between the plots are because of the fertilizer and not any other factor. Obviously we can’t control the weather (we wish!), so instead we have to rely on other techniques to minimize the effects of these other factors.

With repetition over a number of years and different locations across Alberta, it makes it more likely that any trends that appear in the data are due to what the trial is testing, as opposed to good weather one year or better growing conditions at a different site. If the trend can happen in northern Alberta and in southern Alberta, then it isn’t some unique aspect of the place that makes the difference.

Even within a trial site and year, the treatments (the plots will different testing conditions) are repeated 3 or 4 times and randomized, meaning that even micro-changes within a single field aren’t affecting the data. The more data points a study has, the easier it is to say that the test condition is what caused the trend.

When the trial is done, all our collected data is passed on to the scientist in charge of that study. They analyze and run tests of the data, building conclusions based on the results. Then, they share their methods and conclusions in a research paper. Before the paper is published, it is reviewed by other scientists in the field to ensure the science is sound – basically, looking over the methods, math, and results to ensure that the proper procedures were followed and that the conclusions drawn are sound. The paper is now “peer-reviewed.” Peer-review is a stamp of approval that helps guarantee the research done was completed with proper scientific measures and that the results are provable, as opposed to some random conclusion parading as science.

Every year our work is featured in peer-reviewed papers. Kabal S. Gill, our consultant (previously working as our researcher), has an extensive portfolio of research papers that he has written or participated in.

Here are summaries of the some of the research he has been featured in this year:

Crop rotations compared to continuous canola and wheat
– Kabal S. Gill

Two or three-year crop rotations of wheat, canola, peas, barley, and flax were compared to continuous canola and continuous wheat monocultures. The trial ran for 6 years, from 2010 to 2015. The study found that yield tended to improve for canola after a 1 to 2-year break by using crop rotations are opposed to continuous canola, with a 11.3 bu/ac benefit, or +19.4% of the continuous canola yield. Wheat showed a similar benefit from crop rotations, with wheat on pea stubble representing the greatest yield increase. Major reductions in the use of nitrogen were observed when a rotation included peas, and there was some reduction in sulfur needed when canola was not part of the rotation.

Advanced Agronomic Practices to Maximize Feed Barley Yield, Quality, and Standability in Alberta, Canada – L. A. Perrott, S. M. Strydhorst, L. M. Hall, R. C. Yang, D. Pauly, K. S. Gill, & R. Bowness

I. Responses to Plant Density, a Plant Growth Regulator, and Foliar Fungicides
A greater plant density (355 vs 240 plants/m2) reduced maturity by 1.3 days but didn’t have a significant effect on yield. Chlormequat chloride applications created a small height reduction but did not improve lodging, though it increased yield by 2.2%.
Fungicide application increased yield by an average of 3%, with no difference between application timings. The highest yield benefit of 7% required the combination of 355 plants/m2 density, chlormequat chloride application, and dual fungicide application. However, under low disease conditions, density and applications did not result in a significant yield increase for Amisk feed barley.

II. Responses to Supplemental Post-Emergence Nitrogen
Adding UAN at 30 lb N/ac or 60 lb N/ac at the stem elongation stage is best suited for irrigated or high rainfall environments of over 300mm in the growing season. In dry conditions (101-263mm rain) there was no grain yield increase. If the conditions were both dry and hot (27oC) at the time of application, grain yields actually decreased by up to 13%.
Potential of Spring Barley, Oat and Triticale Intercrops with Field Peas for Forage Production, Nutrition Quality and Beef Cattle Diet – Kabal S. Gill & Akim T. Omokanye
The trial tested nine treatments consisting of three cereal monocrops (barley, oat and triticale) and six pea-cereal intercrops in each site-year. The tested intercrops did not increase dry matter yield over the respective monocrops, but they indicated several nutritional quality benefit, such as increased crude protein yield; increased calcium, magnesium, phosphorus, and zinc content; and improved total digestive nutrients content for 12 of the 18 intercrops.

There are more extensive summaries of these trials in this year’s Back Forty Harvest Edition.


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