Use of Disease Assessment Methods in Predicting Yield Loss Due to Northern Leaf Blight of Maize

Abstract

Different severities of northern leaf blight were induced by inoculating maize plants once at GS 4 and 5, three time at GS 4,5 and 6, allowing natural disease development, and by applying fungicides to deter disease development on cultivars with different levels of resistance to Exserohilum turcicum. Percentage leaf area affected by northern leaf blight on the whole plant, ear, first, and second leaf above the ear leaf were assessed weekly for a total of six times at GS 8,9.0,9.1,9.2,9.3, and 9.4. Data obtained from the ear leaf, first leaf above the ear leaf, and second leaf above the ear leaf were used to develop a one-three-two weighted scale to account for leaf position and time of infection for the three leaves assessed and were related to yield by regression analysis. The average disease severity estimated on the ear leaf was significantly (P ≤ 0.001) correlated with severities estimated using other disease assessment methods and loss in grain yield. Overall, AUDPC yield-loss models using percentage leaf area affected on the ear leaf gave the best relationship (Y= 5835-135 AUDPC, R² = 0.42, P ≤ 0.001). Further analysis using leaves of various positions on the plant did not improve the yield-loss models. Critical point models, using percentage leaf area affected at GS 9.1 on A619xA632 also gave good fit (R² = 0.53). Keywords: Exserohilum turcicum, maize, northern leaf blight, yield loss