Sugarcane tasseling under artificial photoperiod conditions as affected by nitrogen rate and temperature
Bibliographic record
Abstract
Optimizing flowering in the LSU AgCenter’s Sugarcane ( Sacchrum spp. hybrids) Breeding Program is an important step in the variety development program. The effect of nitrogen and ambient air temperature in pot cultured sugarcane were examined as a means of improving sugarcane flowering. The experiment was conducted on agronomic and reproductive traits of sugarcane at the Sugar Research Station, St. Gabriel, LA, on sugarcane genotypes subjected to artificial photoperiod regimes. The potting media consisted of equal parts of washed sand, Canadian peat moss, and a Commerce silt loam soil (fine-silty, mixed, nonacid, thermic aeric Fluvaquents). Early nitrogen (22.4-22.4-22.4 kg ha-1) in addition to a high nitrogen potting media (>200 mg kg-1) was necessary for adequate vegetative growth and stalk numbers for tasseling. Leaf macronutrient levels were examined at reproductive growth stages as affected by pre-photoperiod nitrogen fertilizers (22.4-22.4-22.4 kg ha-1 and 0-22.4-22.4 kg ha-1). Since tasseling in nitrogen and no-nitrogen treatments were 77% and 25%, respectively, the critical leaf nutrient level for nitrogen at the vegetative stage for sugarcane intended for tasseling should be 12.4 g kg-1. A chlorophyll meter was used to collect chlorophyll readings from the same leaves that were sampled for plant analysis. The initiation stage was the only stage that both leaf nitrogen (r = -0.34) and chlorophyll meter readings (r = 0.80) showed significant associations. A chlorophyll index level (34.53) was developed as a maximum threshold level for sugarcane breeding genotypes at the initiation stage. Average daily maximum temperature for specific time intervals can affect sugarcane tasseling. A reduced regression model (P=0.02) for the overall tasseling regime indicated that the percent tasseling is expected to increase 4.19 percent when the May 30 – June 14 temperatures increase by one degree above 31.9° C, decrease by 4.36 percent when the June 15- June 30 temperatures increase by one degree above 32.1° C, and decrease by 4.69 percent when the August 16 – September 10 temperatures increase by one degree above 33.1° C. These results help to explain the variation in tasseling percentages that have been encountered over the years when above average temperatures were experienced.
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".