Quantifying Straw Removal through Baling and Measuring the Long‐Term Impact on Soil Quality and Wheat Production
Bibliographic record
Abstract
Crop residues are considered the feedstock of choice for the production of ethanol, but removing crop residues may negatively impact soil productivity. The objectives were to quantify the proportion of total aboveground crop residues removed through baling and to evaluate the effects of 50 yr of straw removal with baling on soil quality and wheat ( Triticum aestivum L.) production. The first study evaluated three harvesting systems and their impact on straw removal with baling. The second study measured straw removal after 50 yr on soil quality and wheat production using a fallow‐spring wheat‐spring wheat rotation (F‐W‐W) with three different treatments imposed. One treatment was not fertilized with straw retained, and the other two were fertilized with N and P but one treatment retained the straw while the other had the straw baled every year during the cropping years. The proportion of total aboveground residues other than grain removed with baling ranged from 22 to 35% or 26 to 40% depending on the method of calculation based on the first study. Measurements of soil organic carbon (SOC) and nitrogen (SON) showed no differences after 50 yr of straw removal, and spring wheat grain yields and grain protein concentration were also not affected based on the second study. The potential therefore exists to use crop residues for ethanol production or other industrial purposes without adversely affecting the long‐term productivity of medium‐ to heavy‐textured soils providing that <40% of the total aboveground residues other than grain are removed and the frequency of removal is no more than 2 yr out of three.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".