Impact of Heat Damaged Corn Gluten Meal as Fertilizer on Forage Production During Winter and Summer Seasons and Soil Characteristics
Bibliographic record
Abstract
Corn gluten meal (CGM) has been used as a supplement for livestock feeding due to its high concentration of digestible nitrogen (N) compounds. Heat damaged CGM (HDCGM), which is not suitable for livestock feeding, may still have value as an organic fertilizer. Objective of the study was to evaluate the impacts of non-feed grade HDCGM on forage production from annual cool and warm season grasses and soil characteristics. Pre-plant incorporated HDCGM at 3 Mg/ha was compared with 4.2 Mg/ha poultry litter (POTL), and 160 kg/ha commercial N fertilizer (COMF), and zero fertilizer (ZERO) for production of the cool-season ‘Prine’ annual ryegrass (Lolium multiflorum), and the warm-season ‘Greentreat’ sorghum × sudangrass (SS) hybrid (Sorghum bicolor). The treatments were repeated at the same site on December 3, 2010 (planted annual ryegrass), May 26, 2011 (planted SS hybrid), October 24, 2011 (planted annual ryegrass) and May 18, 2012 (planted SS hybrid). The HDCGM had 68% more N concentration than POTL, while its P, K, Mg, and Ca were less than half in POTL. The residual N concentration in buried HDCGM and POTL increased in a similar pattern with time in soil. The HDCGM produced less dry matter (DM) of annual ryegrass and SS hybrid than POTL; however, the differences between the two treatments were not statistically significant. All treatments produced more DM in the second than first year. After two years of field test, soil receiving HDCGM contained higher soil organic matter (OM) and N than receiving POTL. Although not as beneficial as POTL for DM production, HDCGM showed potential value as a slow release fertilizer to improve DM production and soil characteristics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.001 | 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 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".