Biobased residues sustain crop productivity and soil health in a maize–soybean rotation
Bibliographic record
Abstract
Abstract Biobased residues are local and cost‐effective sources of soil amendments that can efficiently provide nutrients to crops, enhance soil health and serve as alternatives to mineral fertilizers. The objective of our study was to comprehensively evaluate the soil health and crop productivity of temperate agroecosystems amended with different types of organic residues (biobased residues), including composted food waste (compost), biosolid slurry (biosolids) and liquid anaerobic digestate (digestate), compared with nitrogen fertilizer. The experiment was conducted on a silt loam soil under maize–soybean rotation in Canada, where a wide range of physical, chemical and biological indicators were measured and integrated into a soil health score. Biobased residues resulted in about 50%–60% increase in soil‐exchangeable potassium and 10% soil‐exchangeable sodium over levels found in nitrogen fertilizer. Soil microbial biomass and the capacity of soil microbes to utilize carbon substrates differed among growing seasons but not among amendment types ( p > .05). Crop productivity was similar among amendment types ( p > .05). We found that the soil health score of biosolids was positively correlated with shoot and root biomass and negatively correlated with shoot nitrogen ( p < .05), while that of nitrogen fertilizer was positively correlated with shoot carbon ( p < .05). This was likely because of a variation in the availability of labile carbon and nitrogen among amendment types. Our research also suggests that temperate silt loam soil amended with biobased residues, especially biosolids, supplied sufficient nitrogen without the need for additional nitrogen fertilizer.
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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 | 0.000 | 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 | 0.000 | 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".