Screening of different nitrogen rates and intra-row spacing effects on yield and yield components of safflower (<i>Carthamus tinctorius</i> L.) under microclimate conditions, Iğdır Plain, Turkey
Bibliographic record
Abstract
Eryiğit, T., Akiş, R. and Kaya, A. R. 2015. Screening of different nitrogen rates and intra-row spacing effects on yield and yield components of safflower (Carthamus tinctorius L.) under microclimate conditions, Iğdır Plain, Turkey. Can. J. Plant Sci. 95: 141–147. The yield of safflower (Carthamus tinctorius L.) is affected by many factors, among which nitrogen fertilization and plant density are significant. This study was conducted as a split plot in a randomized complete block design arrangement with four replications, during the successive seasons 2011 and 2012, to determine the effects of nitrogen application rate and intra-row spacing on the growth, yield and yield components of safflower under the ecological conditions of the Iğdır Plain, Turkey. The main plots were three intra-row spacing (IRS1, IRS2 and IRS3) and subplots were four nitrogen rates (N1, N2, N3 and N4). Intra-row spacing had significant effects on all parameters except plant height and seed oil content. There were significant effects of fertilizer rate on all parameters except seed oil content. The interaction of nitrogen rate and years had significant effects on seed yield. Correlations showed significant negative results between 1000-seed weight and seed oil content (−0.217). However, there was a high seed yield in 2011 compared with 2012. Among intra-rows, IRS2 and IRS3 gave greater yield compared with IRS1, while N3 gave a higher yield than other N rates (0, 100, 150, 200 kg ha−1) in both years of the study, especially 2011.
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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) | 0.001 | 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".