Evaluation of chemical composition of roots of three sugar beets varieties growing under different water deficit and harvesting dates in Upper Egypt
Bibliographic record
Abstract
Field experiments were carried out at Shandaweel Agricultural Research Station, Sohag, Egypt to study the effects of deficit irrigation and harvesting date chemical composition of three sugar beet varieties. A split block design with three replications was used. Main blokes were assigned to three irrigation water regimes (100%, 85%, and 70% of water requirement). The sub blot was occupied by three harvesting dates (180, 195 and 210 days). Sub- sub plots comprised three sugar beet varieties namely (RAVEL, SV1841and SA1686). Results indicated that reducing water supply reduced alpha - amino N present in the second season, Na present in the second season, and K present and sugar lost to molasses, but increased sucrose present, extractable present, QZ present, purity present, extractability present. Increasing harvesting date increased K present, sucrose present, extractable present, QZ present, purity present, extractability present but reduced alpha - amino N present, Na present and sugar lost to molasses in the second season. Sucrose present, extractable present, QZ present purity present and extractability present of RAVEL and SA1686 varieties were almost comparable but higher than those of SV1841 variety.
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".