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At each assessment time, the percentage of viable conidia was estimated by observation under the microscope (at 40�� or 100�� magnification) of 100 conidia from each droplet of inoculum, thus yielding a total of nine counts per treatment at each time (Xu et?al. 2001). The spores were considered alive when the length of the germinate tube was equal to half of the diameter of the spore (Paul et?al. 1992). To evaluate the effects on radial growth, a 10-��l aliquot of 10?��l 105?spores ml?1 was inoculated at the centre of Petri dishes containing a test medium. Petri plates were sealed and then incubated at each temperature. http://www.selleck.cn/products/Imatinib(STI571).html The average radial growth of each growing mycelial colony was measured daily (in mm) in two perpendicular directions without opening the Petri dishes, until the plates were completely colonized (Marin et?al. 1996). Growth rates (mm?day?1) were calculated for each aw�Ctemperature combination by linear regression from the linear phase of the growth curve. This http://www.selleckchem.com/products/AZD6244.html experiment was conducted three times with three replicates. A fully factorial design run in triplicate was used to generate the percentage of viable conidia and growth rate of F.?sacchari (isolate Mln799), C.?malorum (isolate Mln715) and Alternaria sp. (isolate Mlb684) in modified media at three temperatures and three aw levels. Variance analysis was used to assess the effects of temperature and aw on the percentage of viable conidia and mycelial growth in vitro. Growth rates were subjected to the general linear model procedure http://www.selleckchem.com/products/SP600125.html of the Statistical Analysis System (sas software ver 9.1. Cary, NC, USA). All statistical significances were estimated at P?=?0��05. Where anova revealed significant differences, Duncan��s multiple range tests were applied to the means. Percentages of viable conidia were modelled using a nonlinear equation y?=?ax2?+?bx?+?c, where y, x, (a and b) and c represent, respectively, the percentage of viable conidia, incubation temperature, model parameters and the response value of y for all factors equal to zero. MINITAB �C 15 ENGLISH was used to apply RSM to a 32 factorial design. Temperature (15, 25 and 35��C) and aw (0��880, 0��920 and 0��960) were the studied factors, and the design included nine experiments with three replicates. The following quadratic polynomial model was fitted to the response: where Y is the response (growth rate in mm?day?1), B0 is a constant coefficient, Xi are coded variables that can have three values (?1, 0, or 1), Bi are linear coefficients, Bij are the second-order interaction coefficients, and Bii are the quadratic coefficients. All model coefficient values were calculated by multiple regression analysis. Interpretation of the data was based on the sign (positive or negative effect on the response) and statistical significance (P?