Impact assessment of natural variations in different weather factors on the incidence of whitefly, Bemisia tabaci Genn. and yellow vein mosaic disease in Abelmoschus esculentus (L.) Moench

Radheshyam Ramakrishna Dhole, Rajendra Nath Singh,Rajendran Dhanapal, Saurav Singla,Govindaraju Ramkumar, Ranganathan Muthuusamy,Saleh H. Salmen,Sulaiman Ali Alharbi,Mathiyazhagan Narayanan,Indira Karuppusamy

Environmental Research(2023)

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摘要
Bemisia tabaci Gennadius, also renowned as the silver leaf whitefly, is among the most damaging polyphagous insect pests in many commercially important crops and commodities. A set of field experiments were conducted for three consecutive years i.e., 2018–2020, to investigate the role of variations in rainfall, temperature, and relative humidity on the abundance of B. tabaci in okra (Abelmoschus esculentus L. Moench). In the first experiment, the variety Arka Anamika was cultivated twice a year to analyse the incidence of B. tabaci concerning the prevailing weather factors and the overall pooled incidence recorded during the dry and wet season was 1.34 ± 0.51 to 20.03 ± 1.42 and 2.26 ± 1.08 to 18.3 ± 1.96, respectively. Similarly, it was observed that the highest number of B. tabaci catch (19.51 ± 1.64 whiteflies/3 leaves) was recorded in morning hours between 08:31 to 09:30 a.m. The Yellow Vein Mosaic Disease (YVMD) is a devastating disease of okra caused by begomovirus, for which B. tabaci acts as a vector. In another experiment, screening was conducted to check the relative susceptibility of three different varieties viz., Arka Anamika, Pusa Sawani, and Parbhani Kranti against B. tabaci (incidence) and YVMD ((Percent Disease Incidence (PDI), Disease Severity Index (DSI), and Area Under the Disease Progress Curve (AUDPC)). The recorded data was normalized by standard transformation and subjected to ANOVA for population dynamics and PDI. Pearson's rank correlation matrix and Principal Component Analysis (PCA) have been used to relate the influences of various weather conditions on distribution and abundance. SPSS and R software were used to create the regression model for predicting the population of B. tabaci. Late sown Pusa Sawani evolved as a highly susceptible variety in terms of B. tabaci (24.83 ± 6.79 adults/3leaves; mean ± SE; N = 10) as well as YVMD i.e., PDI (38.00 ± 4.95 infected plants/50plants), DSI (71.6–96.4% at 30 DAS) and AUDPC (mean β-value = 0.76; R2 = 0.96) while early sown Parbhani Kranti least susceptible to both. However, the variety Arka Anamika was observed as moderately susceptible to B. tabaci and its resultant disease. Moreover, environmental factors were predominantly responsible for regulating the population of insect pests in the field and hence its productivity like rainfall and relative humidity were negative while the temperature was positively correlated with B. tabaci (incidence) and YVMD (AUDPC). The findings are helpful for the farmers to choose need-based IPM strategies than timing-based, which would fit perfectly with the present agro-ecosystems in all ways.
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