Claim · model-written summary
Forecasting emergence of the three weed species from CGDD and rainfall patterns will help growers make better weed management decisions.
Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirectionValueQualifier
Verbatim
e0“forecasting the emergence of three weed species on the basis of CGDD and rainfall patterns will help growers to make better weed management decisions”
Title
Gulshan Mahajan; Bhagirath Singh Chauhan Journal of Crop Health 2024. doi:10.1007/s10343-024-01003-w
Other claims from this paper (10)
- Method / resource Model verification of the CGDD-based emergence model gave coefficients of determination above 85% for the three weeds.
- Observation Cumulative growing degree days required for 50% emergence of Argemone mexicana ranged from 3380 to 5302 depending on seasonal temperature and rainfall.
- Observation The majority of emergence appeared from March to June (species not restated in the sentence).
- Observation Argemone mexicana seeds exhibited dormancy: most germinated in the second season.
- Observation Cumulative growing degree days required for 50% emergence of Brassica tournefortii ranged from 824 to 2311.
- Observation Most Brassica tournefortii cohorts emerged in the first season from February to June, indicating little seed dormancy.
- Observation Cumulative growing degree days required for 50% emergence of Rapistrum rugosum ranged from 2242 to 2699.
- Observation The main Rapistrum rugosum cohorts emerged from February to June.
- Observation About 60% of Rapistrum rugosum seeds germinated in the first season.
- Observation About 40% of Rapistrum rugosum seeds germinated in the second season, indicating seed dormancy.