D.V. SAI RAM KUMARNARAVA RAMANA2023-12-012023-12-012023-12-01D6403https://krishikosh.egranth.ac.in/handle/1/5810202016The present study entitled “Molecular Characterization of Beet Armyworm, Spodoptera exigua and Development of Forecast Model for Pod Borers in Chickpea” was carried out during 2019-20 and 2020- 21. The objectives are; to assess the varietal and temporal factors on the incidence of pod borer, H. armigera and beet armyworm, Spodoptera exigua, development of weather based forecast model for pod borer, phylogeographic characterization of S. exigua with reference to mt COX 1 gene, In vivo characterization of Ryanodine receptors and evaluation of chlorantranilliprole induced mitochondrial dysfunction and metabolic changes in S. exigua. The experiments were conducted under field and laboratory conditions at International Crops Research Institute for Semi-Arid Tropics (ICRISAT), Patancheru, Hyderabad. Telangana, India. Ten Chickpea genotypes were sown at monthly interval during first week of September, October and November. Among the different sowing regimes tested, November sown crop was found to be optimal and right time for sowing of the chickpea genotype to evade the pod borer and beet armyworm incidence. The borer population fluctuated with the change in dates of sowing. Pod borer population was higher in the early sown crop (September) and with delayed dates of sowing in October and November, population decreased, further H. armigera peak larval population coincided with the flowering and pod formation stages, whereas S. exigua incidence was restricted to early vegetative stages of the crop growth. There were significant differences in percent pod damage across genotypes ranging from 10.50 to 40.66 per cent. Minimum pod damage was observed in ICCV 10 and maximum pod damage was observed in ICC 3137. To provide a more efficient and accurate information on timely application of insecticides, this research was aimed to develop a forecast model to predict population dynamics of pod borer using Autoregressive Integrated Moving Average (ARIMA), xxiv Artificial Neural Networks (ANN), ARIMAX and NNARX models. Several ARIMA (p, d, q) (P, D, Q) and ANN models were developed using the historical trap catch data. ARIMA model (1,0,1), (1,0,2) with minimal BIC, RMSE, MAPE, MAE and MASE values and higher R2 value (0.53) was selected as the best ARIMA fit model, and neural networks (7-30-1) was found to be the best fit to predict the catches of male moths of pod borer from September 2021 to August 2023. Similarly, ARIMAX and NNARX models were developed by including weather variables. ARIMAX model (2,0,0) with maximum temperature and rainfall as external variables was selected as the best ARIMAX fit. The neural network (10-32-1) was found to be the best fit to predict the catches of male moths of pod borer from September, 2021 to August, 2023. A comparative analysis performed between the ARIMA and ANN, shows that the ANN based models were best suited for effective pest prediction. The Phylogeographic studies based COX-1 and EF-1 gene sequences revealed that genes of the studied populations were separated into 2 major clades with a total of 31 COX-1 and 27 EF-1 alpha haplotypes. The FST values indicated low genetic difference between the population groups and within the groups, 14-18% genetic variation was observed. There are no gene flow and conversion tracts between the populations of four southern India. Our molecular studies on In vivo characterization of S. exigua Ryanodine receptors revealed the presence of target site mutations I4743M, Insertion of QLRHRLLATQS, YLKWISHNTPG, stop codon formation and several other mutations (replacements of P-X, T-A, Q-L, K-D, S-N, E-A, A-V, E-K, K-T, Y-H I-M, L-X, Deletion of APSALSQVDLSQ, Q and IEI (Numbered according to SeRyR, AFC36359.1) and are important for formation of the calcium channel pore formation and may alter the putative diamide insecticide binding sites in insect RyRs, thus these mutations conferring resistance in the field populations of S. exigua. Studies on chlorantranilliprole induced effects on mitochondrial function and metabolic changes revealed that chlorantranilliprole impeded the mitochondrial respiratory functions (Mitochondrial complex I- V) and induced lipid peroxidation, H2O2 content and LDH leak in a time and dose-dependent manner, further altered the level of antioxidant enzymes, gut proteases, trypsin, chymotrypsin and aminopeptidase leading to oxidative stress in cells, resulting in deleterious effects on the growth of S. exigua larvae, along with the neurotoxic effects.EnglishThesis