Effects of Biogas byproducts “three-dimensional” Fertilization on Yield and Quality of Lettuce
Bibliographic record
Abstract
Effect of three-dimension fertilizing mode (3-DFM) using CO2 and liquid/solid fractions of the digesate from anaerobic digester was investigated in quality and yield of lettuce. CO2, solid fraction of digestate (SFD), and liquid fraction of digestate (LFD) were used as fertilizer for gaseous fertilizer, the base fertilizer, and foliar fertilizer, respectively. The result showed that the 3-DFM was appropriate for lettuce. Lettuce’s plant height, width and number of leaves growth amount were 29.25 cm, 22.38 cm, and 16.2 cm, which were 26.8%, 16.5%, and 18.4% higher than the control, respectively. The overall yield of lettuce was 30.78% more than that of the control. The soluble sugar content and the chlorophyll content in lettuce was the highest, which were 29.4% and 11.4% higher than the control. Under the CO2 and SFD condition, the content of vitamin C in lettuce, the content of free amino acid, crude protein and crude fiber contents of lettuce were the highest. The experimental study can provide an effective way to improve yield and quality of lettuce and utilize biogas plants wastes.
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".