Lewis, Olin M (2014-11). The Temperature Dependent Development of Bactericera cockerelli (Sulc) from south Texas (Hemiptera: Triozidae). Master's Thesis. Thesis uri icon

abstract

  • Bactericera cockerelli (Sulc) (Hemiptera: Triozidae) is a pest of potato (Solanum tuberosum L.) that vectors the bacterium that putatively causes zebra chip disease in potatoes, 'Candidatus Liberibacter solanacearum.' The economic risk of zebra chip disease is mitigated by controlling populations of B. cockerelli in commercial potato fields. Lacking an integrated pest management (IPM) strategy, growers have resorted to an intensive chemical control program that may be leading to insecticide-resistant B. cockerelli populations in south Texas and Mexico. To initiate the development of an integrated approach of controlling B. cockerelli, we used constant temperature studies and non-linear and linear modeling to determine degree day parameters for development of B. cockerelli infesting potato. We field validated the parameters by making degree day model predictions for three different B. cockerelli life stages tested against population data collected from 49 pesticide-free fields. The models estimated the lower and upper threshold for overall (egg plus nymph) development of B. cockerelli as 6.5 and 29.3?C, respectively, with a thermal constant, K, of 354.6 degree days. In the field validation, the model accurately predicted within the normal sampling frequency of 7 days 73% of the egg-to-egg peaks, 80% of the nymph-to-nymph peaks, and 58% of the peaks for the highly mobile adults. It is impractical to predict first occurrence of B. cockerelli in potato plantings as adults are present as soon cotyledons break through the soil. Therefore, we suggest integrating the degree day model into current B. cockerelli management practices using a two-phase method. Phase one occurs from potato planting through the first peak of a B. cockerelli field population and are managed using current practices. Once the B. cockerelli population peaks, phase two begins and the degree day model is initiated to predict the subsequent population peaks, thus providing growers a tool to proactively manage B. cockerelli.

publication date

  • November 2014