Standard area diagram set for olive leaf spot assessment/Escala diagramatica para avaliacao de repilo em oliveira.
Combining the need to increase production and consumption, while reducing imports, researchers have conducted a number of important olive studies in Brazil, on subjects such as cutting propagation (PENSO et al., 2016), indication of more favorable areas for cultivation (WREGE et al., 2015 a; WREGE et al., 2015b), identification of pests (RICALDE et al., 2015) and olive and oil quality (OLIVEIRA et al., 2012). However, studies regarding olive plant pathology under Brazilian climate conditions have not yet received sufficient attention. This is an important study area as increased olive cultivation in Brazil could result in increased spending and reduced production due to diseases occurrence.
Olive leaf spot (OLS, also called repilo or peacock's eye) is the most important disease of olives and is due to Spilocaea oleaginea (synonym: Cycloconium oleagineum), reclassified as Fusicladium oleagineum (SCHUBERT et al., 2003). Signs of the disease include circular brown spots on leaves that can be present with or without a yellowish halo, these occur from autumn to early spring (May to September), a period of mild temperatures and high humidity in southern Brazil, the ideal conditions for OLS development. The primary inoculum is provided by latent infections on leaves, which produce and disseminate conidia via rain in autumn (OBANOR et al., 2011). Inefficient control of OLS leads to leaf fall, which can reduce fruit quality and production by over 20% (ROUBAL et al., 2013).
The SDA Normative Instruction No. 19 (Brazilian Official Gazette, August 16, 2012) aims to prevent the introduction of new pathogen sources via imported olive plants. However, OLS is already present in the main cultivation areas of Brazil. Currently there are no licensed fungicides for olive crops in Brazil (MAPA-AGROFIT) and only sparse information about OLS resistant cultivars is available. These two problems are the principle bottlenecks for olive crop expansion in Brazil.
To advance OLS control there is a need for accurate disease assessment. The main disease assessment methodology was presented by MacDONALD et al. (2000), who demonstrated how to make the latent lesions visible using NaOH and estimate spot area and number. Spot area is highly correlated to spot number, which is the variable most easily measured. This methodology; however, presents some inconveniences: there is no standard area diagram set (SAD) to assist with visual estimates; it is infeasible to perform disease analysis on the same leaves over the long-term; distinct spot size and the merging of lesions hinder the estimation of spot number and indirectly OLS severity. Therefore, this study aimed to develop a SAD for the assessment of OLS severity in humid subtropical climate conditions.
Leaves from 96 olive trees of the 'Arbequina' and 'Koroneiki' cultivars were collected during the winter of 2015, from the Experimental Area of the Federal University of Technology--Parana, Campus Pato Branco (26[degrees]10' S; 52[degrees]41' W, 764m), the climate is Cfa (humid subtropical with warm summers) according to Koppen's classification (ALVARES et al., 2013). No fungicide was applied to the olive orchard during the evaluation cycle. Leaves exhibiting signs of OLS were scanned and the OLS severity estimated using the software AFSoft (EMBRAPA--Instrumentacao Agropecuaria).
For the validation of the SAD, eight people, without disease assessment experience, made estimates for 50 random images with and without the proposed SAD. OLS images (228 pictures), of known severity, were inserted into the Disease Plan spreadsheet, which performs the randomization of images, estimate recording and agreement statistics (SACHET et al., 2016). The precision, accuracy, deviations from the ideal projection, Lin's concordant correlation coefficient as shown by NICOLI et al. (2015) and the smallest difference detectable value based on the random effect of the one-way ANOVA corresponding to the least significant difference (DMS-t com P=0.05) were evaluated. The SAD was developed with six levels: 1, 3, 6, 9, 12 and 15% (Figure 1), the last level was higher than the real maximum severity observed (13.8%), with diagrams being generated from standard leaf (edge) and lesion shapes (circles). For diagram generation, area measurement was based on the image binarization process and counting of pixels using the software ImageJ.
The use of SAD increased significantly (P [less than or equal to] 0.05) the precision (0.72 to 0.87), accuracy (0.91 to 0.98) and concordant correlation coefficient (0.66 to 0.86), in relation to OLS severity assessment without SAD. The estimated u values (difference between the line of regression and the concordant line) approached zero (ideal value) with the use of SAD (0.002), while for assessments without SAD it was 0.17. Raters began to demonstrate greater ability to estimate the real severity level with the aid of SAD, since the SDD was lower with SAD than without (1.91% and 3.91% respectively), reducing the lower value from which it can be stated that there was a difference between observations (Table 1).
The SAD set presented here, with the disease severities illustrated representing stages of OLS, was shown to be easy to use, applicable under a wide variety of conditions and provided reliable results, such as those presented by Berger (1980). Representative symptoms of the disease were identified, and the maximum and minimum disease severity in the field was ascertained. Thus, the adoption of the SAD proposed in this paper to evaluate olive leaf spot severity, can reduce the subjectivity of the estimates and provided better information for epidemiological studies on the Fusicladium oleagineum Olea europaea pathosystem under humid subtropical climate conditions.
Returned by the author 04.07.17
Plant materials evaluated in this research were obtained through the cooperative 'Xisto Project', conducted by Embrapa--Clima Temperado, Petrobras and Universidade Tecnologica Federal do Parana (UTFPR). This research was partly funded by Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES) and Fundacao de Amparo a Pesquisa do Estado de Goias (FAPEG). The authors acknowledge Barbara Bonissoni Cella for her collaboration with data set collection.
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Marcos Robson Sachet (1) * Moeses Andrigo Danner (1) Idemir Citadin (1) Rafael Henrique Pertille (2) Marieli Teresinha Guerrezi (2)
(1) Programa de Pos-graduacao em Agronomia, Departamento de Agronomia, Universidade Tecnologica Federal do Parana (UTFPR), Via do Conhecimento, km 1, 85503-390, Pato Branco, PR, Brasil. E-mail: firstname.lastname@example.org. 'Corresponding author.
(2) Graduacao em Agronomia, Departamento de Agronomia, Universidade Tecnologica Federal do Parana (UTFPR), Pato Branco, PR, Brasil.
Caption: Figure 1--Real (above) and proposed standard area diagram (SAD) (below) images for the evaluation of olive leaf spot (Fusicladium oleaginum) in olive (Olea europaea), indicating six levels of severity: 1, 3, 6, 9, 12, and 13.8 or 15%. UTFPR Campus Pato Branco-PR, 2016.
Table 1--Proposed standard area diagram set (SAD) on the visual estimate performance of olive leaf spot (Fusicladium oleagineum) severity on 50 olive (Olea europaea) leaves by eight raters. UTFPR Campus Pato Branco-PR, 2016. Variables (z) Means (y) MD (x) With scale Without scale r 0.87 (0.05) 0.72 (0.03) 0.15 (0.04) [C.sub.b] 0.98 (0.01) 0.91 (0.03) 0.07 (0.02) u 0.002 (0.07) 0.17 (0.14) -0.168 (0.07) V 1.01 (0.02) 1.15 (0.09) -0.14 (0.09) [[rho].sub.c] 0.86 (0.06) 0.66 (0.05) 0.20 (0.04) SDD 1.91 (0.48) 3.91 (0.41) -2.00 (0.28) Variables (z) CI (95%) (w) r 0.07 to 0.23 * [C.sub.b] 0.02 to 0.12 * u -0.31 to-0.02 * V -0.31 to 0.03 (ns) [[rho].sub.c] 0.12 to 0.28 * SDD 0.12 to 0.28 * (z) r: Precision, the correlation coefficient between estimated and real severity; Cb: a correction factor that measures how far away the adjusted line is in relation to concordant line (Accuracy); u: difference between the line of regression and concordant line; u: difference in the inclination between regression and concordant lines; [[rho].sub.c]: Lin's concordant correlation coefficient. SDD: smallest detectable difference. (y) Standard error of mean in parenthesis (n=8). (x) Mean Difference (MD) between each evaluation with mean standard error in parenthesis. (w) Confidence interval (CI) at 95% probability. Interval including zero, the difference is not significant (P>0.05); (ns) : not significant, * : significant.
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|Title Annotation:||CROP PROTECTION|
|Author:||Sachet, Marcos Robson; Danner, Moeses Andrigo; Citadin, Idemir; Pertille, Rafael Henrique; Guerrezi,|
|Date:||Jun 1, 2017|
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