Impact of Salinity on the Radiation Use Efficiency of Quinoa (Chenopodium quinoa Willd.) in Semi-arid Area in Tunisia
Bibliographic record
Abstract
The impact of three level of salinity (T0 = 1.2 dS m-1, T1 = 9.2 dS m-1 and T2 = 18 dS m-1) on photosynthetically active radiation intercepted (PARabs), Radiation Use Efficiency at pre-anthesis and post-anthesis (RUEPR and RUEPS), Radiation Use Efficiency of total dry biomass (RUETDM) and Radiation Use Efficiency of Grain Yield (RUEGY) at quinoa harvest were investigated during the growing season (2015). The RUE pre-anthesis (from transplanting to anthesis) has registered a decrease of 10.8 and 15.8% respectively in T1 (RUEPR = 4.62 g MJ-1) and T2 (RUEPR = 4.36 g MJ-1) compared to the control T0 (RUEPR = 5.18 g MJ-1). Likewise, the RUE post-anthesis was reduced by 8.9 and 32.1% in T1 (RUEPS = 1.23 g MJ-1) and in T2 (RUEPS = 0.91 g MJ-1), dissimilarity to T0 (RUEPS = 1.35 g MJ-1). The maximum RUETDM (3.2 g MJ-1) was manifested in (T0). However, the minimum RUETDM (2.8 g MJ-1) was observed in T2 (S = 18 dS m-1). A decline of 16.1% was observed in RUETDM due to the reduction on TDM from T0 (S = 1.2 dS m-1) to T2 (S = 18 dS m-1). As well, the RUEGY declined when salinity increased. The highest RUEGY (1.24 g MJ-1) was registered in T0. However, the lowest RUEGY (0.62 g MJ-1) was obtained in T2. A decrease of 50% in RUEGY due to the height reduction on yield was observed in the T2.
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".