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Effect of some Environmental Factors on In Vitro Germination of Urediniospores and Infection of Lentils by Rust
Author(s) -
Negussie T.,
Pretorius Z. A.,
Bender C. M.
Publication year - 2005
Publication title -
journal of phytopathology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.53
H-Index - 60
eISSN - 1439-0434
pISSN - 0931-1785
DOI - 10.1111/j.1439-0434.2004.00926.x
Subject(s) - urediniospore , biology , dew , germination , rust (programming language) , spore , germ tube , spore germination , horticulture , agronomy , incubation period , botany , veterinary medicine , incubation , zoology , medicine , biochemistry , physics , computer science , condensation , programming language , thermodynamics
For accurate lentil ( Lens culinaris ) rust phenotyping in controlled environments, conditions for infection should be optimized. Therefore, the effects of temperature on germination and germ tube growth of Uromyces viciae‐fabae , as well as the effect of different dew periods, were quantified. In all experiments urediniospores of a single‐pustule isolate were applied using a previously calibrated settling tower. After 3 h of incubation, a high percentage (≥80%) of spore germination was observed on 1.5% water agar at 10, 15, 20 and 25°C, with an optimum (99%) at 20°C. At this sampling time the length of germ tubes ranged from 66 μ m (10°C) to 196 μ m (20°C). Growth of germ tubes increased progressively from 10 to 20°C and then declined at 25°C. For minimum infection of lentil cultivar EL‐142 at 20°C, a dew period of at least 3 h was required, whereas maximum infection occurred with a dew period of 24 h. Infection efficiency increased linearly as the duration of dew period increased from 0 to 24 h. Regression models that best described the quantitative relationship between the environmental variables and growth of the pathogen and development of rust were derived empirically. Such models are of significance in optimizing studies of the particular pathosystem as well as eventual lentil rust prediction models.