Yield, Nitrogen, Phosphorus, Copper and Zinc Uptake by Barley Forage Amended with Anaerobically Digested Cattle Feedlot Manure (ADM)
Bibliographic record
Abstract
With increasing production of bio-gas and availability of anaerobically digested cattle feedlot manure (ADM), we need a better understanding of the impact of its application on crop production and the environment. The objective of this study was to investigate nutrient and heavy metal uptake by barley forage from soil amended with ADM. A four-year field study was conducted in southern Alberta to compare annual application of ADM liquid (ADML), and the solid fraction separated from the ADM (ADMS) to raw undigested cattle feedlot manure (CFMR). An unamended control (CK) was also included for comparison. Treatments were replicated four times using a split plot experimental design. All amendments were applied in spring each year prior to seeding and barley was grown and harvested at the soft dough stage for making cattle silage feed. All amendments were applied at rates supplying 100 or 200 kg N ha-1 yr-1, assuming 100% mineral N and 50% organic N was available to crops in the year of application. Averaged over four years, the highest yields were found from ADML (9.55 and 9.6 Mg ha-1 yr-1), and lowest from CK (6.93 Mg ha-1 yr-1), with ADMS and CFMR (7.80 to 8.66 Mg ha-1) in between. Contents and total uptake of nutrients and heavy metals (N, P, Cu and Zn) by barley forage from ADML were higher than ADMS and CFMR. and higher at 200 kg N ha-1 yr-1 than 100 kg N ha-1yr-1. Our data suggest that anaerobic digestion increases nutrients and heavy metal availability in cattle feedlot manure, but most increases occurred in the liquid fraction. Our data also suggest that the impact of organic amendment application on forage barley production is not only affected by the types of amendment used, but also by agronomic practices (e.g., seeding date) as well as growing conditions.
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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) | 0.004 | 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".