Diagrammatic scale for improved late leaf rust severity assessments in raspberry leaves

Abstract Late leaf rust (Thekopsora americana) is a disease that affects raspberry (Rubus idaeus L.), leading to a decrease in raspberry production. The adoption of precise criteria for disease quantification helps decision-making for its management. A diagrammatic scale (DS) is a useful tool for quantifying disease severity in the field. A DS was developed and validated in this study to estimate late leaf rust severity in raspberry leaves. The DS was defined with eight levels of severity (0.2, 0.4, 0.9, 2.2, 5.1, 11.5, 23.9 and 43.2%). The validation was performed by 15 untrained raters in two steps, with and without using the DS. Two approaches were used for statistical analysis: linear regression and Lin’s method. Both analyses demonstrated that the use of the DS improved the precision and accuracy of the disease estimates. The inter-rater reliability was estimated by the coefficient of determination (R2) and the intra-class correlation coefficient (ICC). Again, the use of the DS improved the reproducibility of the estimates. For the first time, a diagrammatic scale was developed and validated to evaluate late leaf rust severity in raspberry leaves.