Influence of Varying Degrees of Straw Production and Removal on Soil Properties and Crop Yield: Two-year Results
Bibliographic record
Abstract
Straw residue retention has many benefits: mitigating soil organic matter loss; recycling macro and micronutrients; reducing runoff and evaporation, increasing water infiltration; along with promoting microbial abundance and activity. However, increasing straw demand for livestock feed and bedding, in addition to pulp, cellulosic ethanol, and fibreboard production, necessitates investigating where straw harvesting works best agronomically, environmentally, and economically. Limited information exists on straw removal effects in modern crop rotations with high-yielding varieties. Moreover, its impact has never been assessed on a landscape-scale, where soil organic matter and crop productivity differ greatly among landscape positions. The objective of this study was to examine the effects of different straw production and removal rates on soil properties and crop yield over a three-year cereal (spring wheat), pulse (field pea), and oilseed (canola) rotation in both high (depression) and low (knoll) straw producing landscape positions. A three-year study was established in 2023 at two landscape positions (≈85 m apart) in a typical south-central Saskatchewan hummocky agricultural field near Central Butte. At each landscape location, four treatment plots consisted of varying degrees of crop straw residue removal: i) no straw removal─both wheat straw (2023) and pea straw (2024) retained; ii) half straw removal─alternating wheat straw (2023) and pea straw (2024) retention and removal from plots; and iii) complete straw removal (straw harvested annually). Consistent with wheat production in 2023, the field pea yield in the depression was greater than the knoll for straw (1.5×) grain (3.9×), and total (1.9×) biomass; primarily, reflecting the more favourable soil moisture conditions in the lower landscape position. The lack of significant effect of post-harvest wheat straw residue treatment on pea yield the following year may reflect field pea’s lower water requirement. Greater grain (4.1×), straw (1.6×), and total (1.9×) biomass WUE of field pea growing in the depression, compared with the knoll, agrees with the 2023 wheat yields and may reflect the greater water-holding capacity and fertility of the depressional soil. The reduced WUE of grain (26%) and total (19%) yields in the depression following 100% straw removal, is indicative of decreased moisture availability concomitant with greater soil surface water evaporation loss following straw removal. The wetter spring soils supported the greatest microbial biomass in 2024, which was reduced 25% by straw removal in the depression, due to the removal of substrate for growth. Straw retention and greater microbial biomass was associated with a 44% reduction in soil NO3 supply rates in the first two months, which may be explained by microbial immobilization. The infiltration rate Kfs increased with 50% straw removal, compared with no straw removal and was attributed to drier surface soil and greater cracking. There were larger runoff losses of NO3 in post-harvest simulated snowmelt from the more fertile depressional soils in both 2023 and 2024. Diminished losses of NO3 (67%) and PO4 (43%) on the knolls with complete straw retention reflects reduced meltwater velocity. The impact of straw removal on crop yield and soil properties thus far have been relatively small, with more effects observed in the wetter depressional areas where there is greater straw production. Future work will examine the impact of straw removal on canola yield and other soil properties in the third year of removal treatment (2025), in addition to the economic implications of straw harvesting.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".