Comparative Efficacy of Common Broad Leaf Herbicides against an Invasive Weed: <i>Parthenium</i> <i>hysterophorus</i> L.
Bibliographic record
Abstract
Parthenium hysterophorus L. (parthenium weed) is an annual weed that grows rapidly in disturbed land. It is considered as one of the most hazardous weeds in Pakistan as it poses serious health problems to livestock as well as severe allergenic reactions in humans. It has invaded the Punjab and Khyber Pakhtunkhwa provinces and also been spreading in other parts of the country where it poses a risk for the grazing lands, roadsides, forests, wet lands, waste lands and of all types of cropped and non-cropped areas in Pakistan. The present studies were carried out to determine the impact of four locally available broad leaf herbicides viz; Stomp 455 CS (pendimethalin), Buctril Super 60 EC (bromoxynil + MCPA), Vantage 48 SL (glyphosate) and Logran Extra 750 WG (triasulfuron + terbutryn) (@ recommended and ½ of recommended dose) against P. hysterophorus grown in pots at research field of CABI CWA, Rawalpindi. All herbicides were applied at three growth stages (rosette, bolted and flowering). The observations for the mortality of P. hysterophorus were made 2 and 4 weeks after spray. The glyphosate was the most effective and reported 100% mortality of P. hysterophorus plants at flowering stage followed by bromoxynil + MCPA (89%), pendimethalin (80%) and triasulfuron + terbutryn (61%) at recommended dose after 4 weeks of spray. All tested herbicides achieved a mortality between 38% - 86% at rosette while 54% - 96% mortality at bolted stage after 4 weeks. Initially, 2 weeks after spray at flowering stage glyphosate caused 53% wilting followed by 49% (bromoxynil + MCPA), 33% (pendimethalin) and 9% (triasulfuron + terbutryn) at their recommended doses. The results indicated that P. hysterophorus is the most susceptible to glyphosate and bromoxynil + MCPA, both these herbicides are very promising for the wilting and management of parthenium weed.
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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) | 0.000 | 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".