Influence of leaf position that correspond to whole plant severity and diagrammatic scale for white spot of corn

The main objective of this research is to determine the influence of leaf position on corn plants with white spot caused by Pantoea ananatis, which better represents the infection on the whole plant. A diagrammatic scale to quantify the severity of the disease was elaborated and validated. For scale elaboration, the minimal and maximal limits of the disease severity observed in the field were considered, and intermediate levels followed logarithmic increments according to the Weber–Fechner stimulation law. The scale has nine classes: 0.1, 1, 2, 4, 8, 16, 24, 32 and 64%. For scale evaluation, a severity evaluation for white spot was performed by 10 raters with no experience in disease evaluation. Initially, severity estimation was performed without a scale for 41 leaves with different levels of severity. Afterward, the same raters used the proposed diagrammatic scale. Through linear regression to compare the actual and estimate severity values, the raters’ accuracy and precision were analyzed. Satisfactory accuracy and precision were achieved when estimation was performed with a diagrammatic scale. To determine the best leaf disease severity evaluation, correlation and regression analyses were performed with 25 plants of five genotypes, for a total of 284 leaves analyzed. Results analysis leads us to conclude that the severity of white spot on corn plants significantly correlates with the disease mean severity of leaves 0 and -1, i.e., a leaf of the corn ear and the one immediately below it. This scale provided good levels of accuracy and precision (a mean R² of 94%), with errors concentrating around 10%. Raters presented increased reproducibility (R² > 90% in 82% of cases) of severity estimates. The proposed diagrammatic scale is considered adequate to estimate the severity of white spot in corn for germplasm evaluations, for epidemiological studies and for evaluation of control strategies for this disease.