Differential physio-biochemical and yield responses of Camelina sativa L. under varying irrigation water regimes in semi-arid climatic conditions
Bibliographic record
Abstract
Camelina sativa L. is an oilseed crop with wide nutritional and industrial applications. Because of favorable agronomic characteristics of C. sativa in a water-limiting environment interest in its production has increased worldwide. In this study the effect of different irrigation regimes (I0 = three irrigations, I1 = two irrigations, I2 = one irrigation and I3 = one irrigation) on physio-biochemical responses and seed yield attributes of two C. sativa genotypes was explored under semi-arid conditions. Results indicated that maximum physio-biochemical activity, seed yield and oil contents appeared in genotype 7126 with three irrigations (I0). In contrast water deficit stress created by withholding irrigation (I1, I2 and I3) at different growth stages significantly reduced the physio-biochemical activity as well as yield responses in both C. sativa genotypes. Nonetheless the highest reduction in physio-biochemical and yield attributes were observed in genotype 8046 when irrigation was skipped at vegetative and flowering stages of crop (I3). In genotypic comparison, C. sativa genotype 7126 performed better than 8046 under all I1, I2 and I3 irrigation treatments. Because 7126 exhibited better maintenance of tissue water content, leaf gas exchange traits and chlorophyll pigment production, resulting in better seed yield and oil production. Findings of this study suggest that to achieve maximum yield potential in camelina three irrigations are needed under semi-arid conditions, however application of two irrigations one at flowering and second at silique development stage can ensure an economic seed yield and oil contents. Furthermore, genotype 7126 should be adopted for cultivation under water limited arid and semi-arid regions due to its better adaptability.
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".