An Environmental Model Predicting Bacterial Ring Rot Symptom Expression

Abstract

Bacterial ring rot (BRR) is a regulated disease of potato caused by the gram-positive bacterium Clavibacter michiganensis subsp. sepedonicus. Many countries have seed certification programs that involve pre- and post-harvest inspections for disease symptoms supplemented by laboratory immunological and nucleic acid diagnostics. Several studies have shown that environmental factors and other parameters may affect the severity of BRR symptoms. Collection and analysis of field data from 154 cultivated potato genotypes over 15 years indicates that moisture, temperature, and cultivar are major factors influencing BRR symptom expression. Sensitivity analysis showed that late season temperatures were more important than mid-season moisture. Contrary to expectations, cultivar susceptibility was of less importance in our models than weather parameters in determining BRR symptoms. A neural network model was successfully deployed that predicts severity of BRR symptom expression based on late season temperature, precipitation, and cultivar susceptibility.