Effect of Temperature and Photoperiod on Time to Flowering in Chickpea
Bibliographic record
Abstract
ABSTRACT Flowering time is a key factor in determining the adaptation of crops to diverse environments. Temperature and photoperiod are the two major environmental variables that affect the length of the period between sowing and flowering and the rate of plant development. The objectives of this research were to examine the days to flowering of selected chickpea ( Cicer arietinum L.) accessions grown in a range of thermal regimes combined with either long or short days and to examine the interaction between photoperiod and day and night temperatures on flowering response. Eight chickpea accessions representative of different photoperiod sensitivity responses were included, that is, day‐neutral (ICCV 96029 and FLIP‐98‐142C), intermediate (ICC 8621, ICC 8855, ICC 15294, and ILC 1687), and highly sensitive (‘CDC Frontier’ and ‘CDC Corinne’). Significant effects of accession, temperature, photoperiod, and their interaction were observed for days to flower. Under long photoperiod combined with the higher temperature regime, earliest flowering was observed in day‐neutral accessions followed by intermediate accessions, then photoperiod‐sensitive accessions, which flowered, on average, in 20, 23, and 41 d, respectively. For the two day‐neutral accessions, the difference in the number of days to flower under 16 h photoperiod combined with the temperature regimes of 24 and 16°C and 20 and 12°C (day vs. night) was not significant. Regression analysis revealed that days to flower of the day‐neutral, intermediate, and photoperiod‐sensitive accessions was a linear function of temperature ( R 2 = 0.88–0.99) within the photoperiod.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".