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Damage to guava nursery plants due to multiple infections by Austropuccinia psidii

Grant number: 22/05816-8
Support Opportunities:Scholarships in Brazil - Master
Effective date (Start): November 01, 2022
Effective date (End): June 01, 2024
Field of knowledge:Agronomical Sciences - Agronomy - Plant Health
Principal Investigator:Lilian Amorim
Grantee:Ana Laura Toledo Simões
Host Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
Associated research grant:19/13191-5 - Epidemiological components, damage characterization and control of tropical and temperate rusts at a global climate change scenario, AP.TEM
Associated scholarship(s):23/06630-8 - Carbon assimilation and redistribution in Paluma guava potted plants infected by Austropuccinia psidii, BE.EP.MS


Myrtle rust, caused by Austropuccinia psidii, is the most severe fungal disease in guava plants, especially cv. Paluma. Rust in perennial plants usually cause polyetic damage, it is possible to estimate the polyetic damage in a greenhouse, by means of multiple inoculations in potted plants. The objective of this work will be to estimate the impact of successive inoculations of A. psidii on vegetative development, leaf gas exchange, biomass accumulation and carbohydrate accumulation in guava plants, kept in a controlled environment. Guava nursery plants cv. Paluma will be inoculated with A. psidii suspension. The plants will be inoculated every 14 days, with four replications. The maximum length and width of all leaves, the length of the main stem, the length of internodes and the total number of leaves will be measured during the experiment. The dry mass of the shots and roots of the plants will be quantified at the end of the experiment, and these samples will be used for the quantification of carbohydrates. Leaf gas exchange will be evaluated at 21 and 28 days after inoculations in each marked leaf. The variables measured will be: intercellular concentration of CO2 (Ci), net assimilation of CO2 (A), stomatalconductance (gs) and transpiration (E). These variables will be estimated by infrared gas analyser in a 2 cm2 leaf area. The marked areas will be photographed to quantify the severity of the disease with Quant software. Disease severity will also be estimated on the marked pair of leaves, with the aid of a diagrammatic scale, and on the stems, by counting the number of lesions and measuring their size. The disease variables will be correlated to the photosynthetic and biomass variables of the plants. The damage estimates obtained in the experiments should be incorporated into simulation models.

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