(322) The Effect of Plant Growth Regulators and Time of Plantings on Stem Cuttings of Peach cv. Shan-i-Punjab
Bibliographic record
Abstract
Peach [ Prunus persica Batsch. (L.)] is a major fruit of northern India, which is commercially propagated through stem cuttings. There is a scarcity of information available on the effect of plant growth regulators (PGRs) and time of plantings on rooting of peach stem cuttings. Studies were conducted to learn the effects of various PGRs and planting times on stem cuttings of peach cv. Shan-i-Punjab at the fruit nursery of the Horticulture Department, Khalsa College, Amritsar, India, in 2001 and 2002. The study on stem cuttings, taken from the middle portion of the shoot, compared three PGRs: indolebutyric acid (IBA), indoleacetic acid (IAA), and naphthaleneacetic acid (NAA), each at concentrations of 50, 100, and 200 mg·L -1 and two planting dates (20 Dec. and 20 Jan.). Cuttings were treated for 24 hours before keeping under moist sand for 1 month for callusing. Callused cuttings were planted in the field. Measurements on sprouting percentage, survival percentage, plant height, shoot diameter, number of leaves per plant, leaf size, average root length, and root weight per cutting were recorded. The study showed that, overall, auxins had significant effect on the success and rooting character of peach plants over the control. The greatest sprouting and survival percentage, plant height, leaf area, and shoot diameter was exhibited by IBA followed by IAA and NAA. IBA at 100 ppm proved to be the most suitable PGR for improving success along with other rooting and vegetative characters of the plant. The cuttings planted on 20 Dec. gave a higher percentage of success (55.32%) over those planted on 20 Jan. (33.04 %), during both years of study. The other plant characteristics, such as average root length, plant height, leaf area, and plant height, of cuttings planted on 20 Dec. also showed greater success during both years.
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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".