Number of emergent individuals was affected by seeding rates regardless of wheat varieties (P=0.0031). As such, number of emergent individuals was 28 and 32% greater at 35 (P=0.0065) and 40 (P=0.0019) plants per squared foot respectively compared to lower seeding rates. Moreover, combined emergence at seeding rates of 30, 35 and 40 plants per foot was 66% greater than at 25 plants per foot (P<0.0001).
Height was influenced by both variety and seeding rate (P=0.0002). Tallest stands were found in plots sown with AAC Brandon and AAC Redberry at 40 plants per squared foot, whereas shortest individuals were found in AAC Redberry at 25 and 30 plants per squared foot. Indeed, AAC Brandon and AAC Wheatland stands were taller compared to the other varieties by 43 (P<0.0001) and 13% (P=0.0029) respectively. Moreover, those plants sown at 35 and 40 plants per squared foot showed to be taller by 13 (P= 0.0006) and 50% (P<0.0001).
Even though emergence and height were impacted by wheat variety and seeding rate , there was no effect with either on test weight (P=0.8181), yield (P=0.3436) and protein content (P=0.2174). Yield especially was the same even when AAC Redberry was sown two weeks after the other varieties.
In conclusion, it is possible height and emergence are impacted by variety and seeding rate but eventually yield, test weight and protein content is the same despite the wheat varieties selected and under different seeding rates.
Greatest number of emergent stands were found in CDC Austenson, followed by CDC Copeland and CDC Metcalfe. Despite seeding rates emergence number were 8% higher in CDC Austenson compared to CDC Metcalfe and CDC Copeland varieties (P<0.0001) and CDC Metcalfe was 9% compared to CDC Austenson and CDC Copeland (P<0.0001). In terms of seeding rates, Number of individuals emerging above ground were greater at the highest seeding rates (34 plants per squared foot) of CDC Austenson and CDC Copeland varieties, but not in CDC Metcalfe at the same seeding rate (P<0.0001). As such, those plots sown at 34 plants per square foot showed 4% more of the number of emergent stands (P=0.0015) in comparison to those plots sown at 24 and 29 plants per square foot.
Height was evaluated twice during the growing season. Instead of pooling the data, height was treated as repeated measurements. Analysis showed an interaction between height and treatments, much more in relation to varieties rather than seeding rates (P<0.0001). It was found that average heights of CDC Metcalfe and CDC Copeland had a 4% difference (P= 0.0001) compared to CDC Austenson stand height. CDC Metcalfe was then 9% taller than average heights of CDC Austenson and CDC Copeland (P=0.0005) and CDC Copeland was 23% taller than average heights of CDC Austenson and CDC Metcalfe (P=0.0001).
Yield was the same in CDC Austenson and CDC Copeland and both were greater than CDC Metcalfe (P=0.0034). As such, CDC Austenson yielded 25% more than CDC Metcalfe and CDC Copeland (P=0.0032) and CDC Metcalfe yielded 40% less than CDC Austenson and CDC Copeland (P<0.0001).
In conclusion, CDC Austenson was the barley variety with most emergent number of individuals and yield whereas CDC Copeland was the tallest variety. Seeding rate impacted height but emergence and yield was mostly influenced by barley variety.
There was more biomass in the Ultimate mix compared to the other cover crop mixes. It is important to note that, despite producing 32% more than the other NPARA blends (P=0.0076), its mean biomass value was statistically the same than biomass found in Pinpoint in NPARA blends 5 and 6 (P=0.0151). In contrast, NPARA blends 1 and 4 which were the blends that produced the lightest mean biomass. It can be argued that blends 5 and 6 as they have corn in their cover crop mix, which is a heavy and bulky plant and ryegrass, which is an early emergence high yielding cover crop. Blends 1 and 4, have cereal rye as part of their mix, but biomass produced from these stands is not as copious as that found in annual ryegrass.
Protein values were the highest in ultimate and pinpoint blends (P<0.0001). As such, Ultimate and Pinpoint had 54 and 42% more protein respectively compared to NPARA protein values combined. Protein content in NPARA blend 3 was the same as that found in Pinpoint blend in comparison to the other blends from NPARA, likely due to white clover being part of such blend.
Acid (P=0.0279) and neutral (P=0.0184) detergent fibre were also greater in the ultimate blend. Acid and neutral detergent fibre were 30 (P=0.0153) and 26% (P=0.0452) respectively compared to those found in NPARA blends. From the blends selected at NPARA, blends #2, 5 and 6 showed statistically similar ADF and NDF values to Ultimate and Pinpoint blends. Lowest ADF and NDF values on the other hand were attributed to blends 1 and 4, possibly due to presence of cereal rye in a greater proportion with respect to the other blends. Total digestible nutrients were greater in Ultimate and Pinpoint blends (P=0.0022). Values were 43 (P=0.0002) and 32% (P=0.0087) greater than those found in NPARA blends.
Soil organic matter (P=0.9045), Cation Exchange Capacity (P=0.0669), pH (P=0.7063), P (P=0.1634), K (P=0.1623), Mg (P=0.7874), S (P=0.2400), Zn (P=0.9525), Fe (P=0.2619), Cu (P=0.4967), B (P=0.3848), Al (P=0.9629) and Na (P=0.9629) as well as nitrate (P=0.2096) were the same for all treatments. Moreover, insects were monitored every two weeks and data suggests that number of insects did not differ across treatments (P=0.0950).
Overall, NPARA blends 1 and 4 more digestible for the animal to eat compared to the other NPARA blends. However, NPARA blend #3 might also be a good choice of energy as it provides as much protein as that found in the Pinpoint blend.
Soil infiltration measurements are preliminary and do not provide any effect made by the treatments themselves. It is expected that in following seasons, soil analysis and infiltration conducted can be used to compute and further analyse differences among treatments.
Cover crop mixes were crafted to observe how different cover crop roots affect infiltration and fertility across the soil column. Consider treatments as four sets of three treatments. The first set consists of a brassica group (daikon radish, forage radish and forage turnip) which is sown at 1X, 2X and 3X of the recommended seeding rate. With the exception of the fallow treatment, all other sets have a brassica group at either of these seeding rates and field pea and sunflower. Thus, The second set was sown with oat, Japanese millet, sweet clover, chicory, in addition with the brassica group and afore mentioned crops. Third set had a brassica group with only field pea and sunflower and the last set of three was seeded with a brassica group, brown midrib corn, annual ryegrass and hairy vetch. Treatments were harvested for biomass yield and sent for feed analysis. Due to funding constraints, biomass was not collected for fallow plots and no subsequent feed analysis in the plots of this treatment were made. Biomass yield was statistically the same across all treatments (P=0.0582). Likewise, protein (P=0.4873) and acid detergent fibre (P=0.0982) were the same among treatments. Neutral detergent fibre (P=0.0029) on the other hand, was greater in mixes containing oat, Japanese millet, sweet clover, chicory, field pea and sunflower, despite brassica seeding rates. Moreover, mixes with only brown midrib corn, annual ryegrass and hairy vetch and single rates of the brassica group showed NDF as great as those found in previous mentioned mixes. Values of NDF were low in mixes were only the brassica group was present or when it was accompanied with field pea and sunflower. In fact, NDF in treatment sets with sown with brassica group, field pea and sunflower plus oat, Japanese millet, sweet clover and chicory was 113% more than that found in sets sown with only the brassica group. This same set were Japanese millet, oat, chicory and sweet clover were sown had 97% more NDF than sets were a brassica group plus field pea and sunflower were seeded and 69% more NDF than mixes including brown midrib corn, annual ryegrass and hairy vetch.
Soil samples are sent to two different places, one is a standard lab which will provide you with a soil analysis and fertility recommendations and the other is WARD labs in Kearney Nebraska, which provides you with the same but, unlike the former, it shows you N content through a different method (thus concludes on fertility recommendations based on the N content measured from such method). This method is called Haney test, developed by Rick Haney of United States Department of Agriculture and Agricultural Research Service in Temple, Texas. Moreover, WARD labs gives you results for a phospholipid fatty acid test, which is used to profile different phylla of bacteria and fungi in the soil. Since both tests can recommend you how much N is required in the soil to seed the next crop for the upcoming season, it bears to ask the question, which one is better?
Over the last three years, canola, pea and wheat have been rotated in the same trial and treated under different fertilization rates. Fertilization treatments were set as follows. A) 0% (Control) – N recommendations from standard lab. 100% of the recommended N will be applied. B) N recommendations from the standard lab will be 30%. Then it will be topped up with that recommended by the WARD Haney analysis to equate the total recommended by Haney. C) N recommendations from WARD lab. 100% of the N recommended from the Haney soil test will be added.
