Abstract

SAUCEDA-ACOSTA, Carlos P. et al. A precise method to measure leaf rust (Puccinia triticina Eriksson) severity in wheat. Rev. fitotec. mex [online]. 2015, vol.38, n.4, pp.427-434. ISSN 0187-7380.

Visual estimation of disease severity in plant organs is subjective and not repeatable, thus accurate methods to measure damaged surfaces are needed. This study proposes a method for measuring severity of leaf rust (Puccinia triticina Eriksson) on wheat (Triticum aestivum L.) cultivars INIA F-66, Jupateco-73R, Morocco, Sonora F-64 and WL-711 by using digital image analysis (AID). The actual percentage of leaf area damaged by the disease (MED, %) was estimated using AID and then compared to a visual assessment method of disease severity (EST, %) performed by three volunteers, on two samples with 10 replicates. Leaf images were scanned, and then AID was performed via automation with software (ImageJ 1.48r). Leaf area (AS, mm²), damaged area (AD, mm²), number (NTL), size (TAM, mm²) and shape of lesions were measured. Number of lesions per cm² (LPC) and MED was calculated. The two methods correlated with each other (r_s = 0.86, P ≤ 0.0001); although EST lacks accuracy. Severity was different among volunteers and AID (K-W ≈ X2 = 21.73, P ≤ 0.05). MED and EST were different between cultivars (P ≤ 0.001). Volunteers overestimated EST when AD was less than 19 %, and they underestimated it when it exceeded this level. Morocco had the largest MED (49.4 %). Sonora F-64 and Jupateco-73R had the lowest NTL, TAM and LPC (P ≤ 0.001). Usage of AID has many advantages, among which it allows accurate identification of damaged and healthy leaf area; it requires less than 1 min to determine variables related with severity of leaf rust; and this method is repeatable, reduces experimental errors and subjectivity.

Keywords : Puccinia triticina; Triticum aestivum; visual estimation; digital images; severity of rust.

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