Epidemiological studies on aonla rust: A Novel Weather-Based Model for Predicting Ravenelia emblicae Styd. infection in aonla fruits
The present investigation on cultivar NA-7 proposed under natural conditions during first appearance of the disease at 35th standard meteorological week (date of 2nd September), the minimum per cent disease intensity was observed (0.33%) and maximum 43.33% during 52 standard meteorological weeks when the corresponding to weather parameters viz., temperature maximum 19.2 0C, minimum 7.1 0C, relative humidity morning 90.2% and evening 58.5%, rainfall 0.0 mm, evaporation 3.4 mm, and sunshine 3.8 hrs/day were convenient for the growth, initiation and escalation of Pathogen. further investigations on the correlation of each individual parameter with the development and progress of the disease. Revealed that minimum temperature was recorded negatively correlated highly significant (-0.96) with per cent disease intensity, followed by maximum temperature (-0.94), evening relative humidity (-0.78) and evaporation (-0.82), whereas morning relative humidity (-0.50) and rainfall (-0.48) were found significant negative correlation with PDI. Sunshine (0.14) was observed positive correlation non-significant with PDI. The highest infection rate in 36th standard meteorological week which is amount of 0.206 and lowest infection rate was found 41th standard meteorological week which was 0.006. The AUDPC values ranged from 1.16 to 295.96, indicating a rapid progression of the disease.
Authors
- Jitendra Kumar (ORCID: https://orcid.org/0000-0002-7208-3111)
- Vishwa Vijay Raghuvanshi
- Shubham Patel (ORCID: https://orcid.org/0000-0002-0046-9031)
- H. K. Singh
- Abhishek Singh (ORCID: https://orcid.org/0000-0002-1721-7391)
Publication Details
- Journal
- Environment and Ecology
- Published
- 2024-09-01
- DOI
- https://doi.org/10.60151/envec/ywfg7533
- Citations
- 1
- Primary Topic
- Banana Cultivation and Research
- Type
- article
- Field-Weighted Citation Impact
- 0.60
Funders
- Indian Council of Agricultural Research