de DEMIRSOY et al. (2004). Palavras-chave: Prunus persica, modelo, validação, análiseregressão stepwise. Kampai' peach trees. Further to this, a DEMIRSOY et al. (2004) DEMIRSOY et al. (2004). ABSTRACT The prediction of leaf area (LA) without causing damage to the plant is a subject of great interest in agricultural research. In this study, it was developed and tested three models based on the length (L), width (W) or both of these leaf dimensions of 'BRS

Several computer applications have been proposed for the visual assessment of plant disease severity; however, they have some restrictions such as not permitting the user to make modifications. Therefore, the VBA-Excel application was developed as a means to train people to estimate disease severity and to validate standard area diagrams through images and disease severity values (percentage, rating or score) inserted into a database. The main performance statistics are screen displayed and spreadsheet recorded. Finally, the authors hope to receive evaluations and feedback regarding this application.

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Leaf area (cm2 per leaf) and leaf pigment content are important traits that can be used to better understand a plants physiology. In this study, empirical non-destructive models for leaf area and leaf pigment based on the leaf dimensions, length (L) and width (W) in centimeters, and chlorophyll meter readings were developed for feijoa (Acca sellowiana). The experiment was carried out during January 2016 using five-year-old trees of 60 genotypes, grown under field conditions in the state of Paraná, Brazil. The proposed leaf area (LA) model was L A = 0 . 0022 L 3 + 0 . 1482 W 2 + 0 . 6159 L W + 0 . 1076 (R2 = 0.99). Three current leaf area models found in the literature were also assessed. All of the already created models were less accurate than the model proposed in this article. The proposed leaf pigment models were based on the Falker Chlorophyll Index for Chlorophyll a (A) and b (B), these were C h l a = 2 . 564 A + 13 . 098 B - 42 . 605 (R2 = 0.94), C h l b = 1 . 538 A + 3 . 287 B + 8 . 847 (R2 = 0.86) and C a r o t e n o i d s = 0 . 947 B + 8 . 943 (R2 = 0.88) expressed as µmol m-2 of leaf blade. In conclusion, the proposed models in this study were shown to be a reliable non-destructivel way of estimating A. sellowiana leaf area and leaf pigment.

The establishment of olive (Olea europaea) orchards in Brazil is increasing due to their economic potential and benefits to human health. However, a number of limiting factors need to be overcome, such as Olive Leaf Spot (OLS) occurrence, for olives to reach their full potential. OLS, which is caused by Fusicladium oleaginum, results in defoliation and a reduction in fruit production. This study aimed to develop a standard area diagram set (SAD) for the assessment of OLS severity under humid subtropical climate conditions. The SAD was developed with six levels of severity (1, 3, 6, 9, 12 and 15%) and OLS severity was validated by eight inexperienced raters. Using the SAD provided an increase in accuracy, precision and concordance, while also reducing the smallest difference detectable. The proposed SAD was adequate at estimating the OLS and could be a useful tool for use in epidemiological and phytopathometry studies, evaluation of control strategies and selection of resistant genotypes.

No abstract

A diagrammatic scale of anthracnose in feijoa fruit was elaborated and validated in order to standardize disease severity assessments. The proposed scale showed six disease severity levels: 2, 10, 20, 40, 70 and 100% of the injured fruit surface. The scale took into account the minimum and maximum limits of disease severity observed in the field and the intermediate values followed logarithmic increments according to the Weber-Fechner stimulus-response law. Eight inexperienced raters validated the scale by quantifying the disease severity (using/not using the scale) of 50 feijoas with anthracnose symptoms. In conclusion, the scale improved the assessment of anthracnose in feijoa. Eight genotypes from different crosses were tolerant to anthracnose.