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Effects of weather variables on grain mould of sorghum in South Africa
Author(s) -
Tarekegn G.,
McLaren N. W.,
Swart W. J.
Publication year - 2006
Publication title -
plant pathology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.928
H-Index - 85
eISSN - 1365-3059
pISSN - 0032-0862
DOI - 10.1111/j.1365-3059.2006.01333.x
Subject(s) - sorghum , biology , alternaria alternata , hybrid , incidence (geometry) , fusarium , agronomy , maximum temperature , veterinary medicine , precipitation , relative humidity , horticulture , mathematics , atmospheric sciences , meteorology , medicine , physics , geometry , geology
Effects of weather variables of mould development on sorghum grain were studied over three consecutive seasons in South Africa. Five sorghum hybrids planted at different dates ensured developing seeds were exposed to different weather conditions. Incidence of grain mould fungi was determined at harvest by incubating seeds on 2% malt extract agar. Averages of different weather variables (maximum and minimum temperatures, maximum relative humidity, total precipitation and frequency of precipitation) were determined for all permutations of weekly time intervals for a 2‐month postflowering period to identify when these variables and pathogen incidence were significantly correlated. Significant correlations were used to develop models to quantify relationships between variables. Significant positive correlations were observed between the incidence of mould fungi and weather 4–6 weeks after flowering in the shorter season hybrid cv. Buster, and 5–8 weeks after flowering in the remaining hybrids. In most hybrids, correlations between the incidence of grain mould pathogens, including Alternaria alternata , Curvularia spp. ( C. lunata and C. clavata ), Fusarium spp. ( F. proliferatum and F. graminearum ), and Drechslera sorghicola , and average minimum temperature, total rainfall and frequency of rainfall were significant ( P = 0·05). In four hybrids, models showing a linear relationship between the logarithm of pathogen incidence and minimum temperature, and in one hybrid, between pathogen incidence and rainfall frequency, were developed. Depending on the hybrid, models that used minimum temperature as predictor described 60–82% of variation in the incidence of pathogens. Frequency of rainfall explained 93% of the variation in pathogen incidence in one sorghum hybrid genotype. Evaluation of the models using an independent data set yielded average prediction errors near zero, indicating that the models were acceptable.