Impact Of Acetylsalicylic Acid Foliar Application And Sowing Dates On Cucumber Growth
Bibliographic record
Abstract
This study examines the effects of acetylsalicylic acid (ASA) foliar application and various dates of sowing on the growth and yield of cucumber plants.The research was conducted to ascertain the impact of varying ASA concentrations and planting times on critical growth parameters, including the number of fruits per plant, vine length, fruit length, fruit diameter, fruit weight, and overall fruit yield.Additionally, the male-to-female flower ratio and the days to flowering were studied.Early sowing dates (SD1) exhibited a 40-day delay in flowering, whereas later sowing dates (SD3) resulted in a 34-day early flowering period.Application of ASA also had a substantial impact on flowering time; plants treated with the highest ASA concentration (ASA3, 270 mg L-1) flowered the earliest (34 days), while untreated plants took the longest (41 days) to flower.The duration between the first harvest and the SD1 and SD3 plots differed as well; the former took the longest (62 days) and the other one the shortest (53 days).Plants treated with ASA3 were harvested 54 days earlier than untreated plants, which took 61 days.Early-planted seeds (SD1) had a lower male-to-female floral ratio than late-planted seeds (SD3).This ratio was decreased by ASA application; ASA3 displayed the lowest ratio, 2.93.Early sowing (SD1) yielded higher fruits per plant (11.1), longer vines (167 cm), and larger fruits (4.27 cm), whereas late sowing (SD3) gave the lowest values for these characteristics.The maximum number of fruits per plant (10.9), longest vines (167 cm), and highest fruit output (40.2 tonnes ha-1) were all consistently achieved with the highest ASA concentration (ASA3).The results show that increasing the concentration of ASA and planting the cucumbers earlier can both improve their development and yield.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".