Saccharomyces cerevisiae filtrate showed inhibitory effect against Fusarium spp. when grow in a liquid medium (Sabouraud) with different concentrations (1, 3, 5) %. The higher inhibitory effect against fungus growth was (24.5) mm at (5%) in PDA medium compared with control (36.5) mm during the seventh day propagation. The filtrate of Lactobacillus plantarum isolate was mixed with the PDA medium ,which showed inhibitory effect against Fusarium spp. The concentrated filtrate( one fold) appcarcd a higher effect against the same fungus compared with un concentrated filtrate one. Saceharomyces cerevisiae and Lactobacillus plantarum were grown in (GYE) liquid medium for(24,48,72)hr. and resulted growth filtrate were tested against Fusarium growth for (7) days, the results showed that the fungus stopped its growth stopped after (48- 72) hr. of incubation.
Effect of Saccharomyces Cerevisiae and Lactobacillus Plantarum in Growth of Fusarium sp.
: Saceharomyces cerevisiae
Lactobacillus plantarum
effect on
Fusarium.
Publication Date
Sun Jun 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Different Methods for Estimating Location Parameter & Scale Parameter for Extreme Value Distribution
Extreme Value Distribution
Maximum likelihood estimator
Method of moment Estimators
Estimators based on Percentiles
Least Squares estimators
Weighted Least Squares estimators
Ridge regression estimators
Adjusted Ridge regression estimators.
In this study, different methods were used for estimating location parameter and scale parameter for extreme value distribution, such as maximum likelihood estimation (MLE) , method of moment estimation (ME),and approximation estimators based on percentiles which is called white method in estimation, as the extreme value distribution is one of exponential distributions. Least squares estimation (OLS) was used, weighted least squares estimation (WLS), ridge regression estimation (Rig), and adjusted ridge regression estimation (ARig) were used. Two parameters for expected value to the percentile as estimation for distribution f
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