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This study was conducted to assess genetic diversity among the 32 tall fescue half-sib families using a randomized complete block design (RCBD) experiment in the four replicates. Based on analysis of variance, significant differences were observed among studied genotypes at the probability of 1% for plant height, canopy diameter, days to heading, days to pollination, crown diameter, fresh forage yield, dry forage yield, number of stem and seed yield in first harvest and in canopy diameter, crown diameter, fresh forage yield and dry forage yield in second harvest. Based on the results of mean comparisons, highest dry forage yield in the first harvest was obtained in genotype 32 by 758.5 grams. Principal component analysis by considering eigenvalues greater than one, caused to introduction of three components which determined 80.5% of the variation among the samples. In cluster analysis, the greatest of distinction between the groups was achieved with three clusters, and by cutting the dendrogram genotypes in three groups. According to the results, the third cluster was superior to other two clusters in terms of most traits. The genotypes of third cluster, according to the value of this cluster in terms of forage yield and seed yield will be of particular importance in breeding programs. In the breeding of cross-pollinated forage crops, success in selection depends on creating diversity by genetic recombination and achievement of heterosis. Due to the distance between groups 1 and 3, probably the most successful crosses will be achieved among genotypes of these two groups.

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Any industry needs an efficient predictive plan in order to optimize the management of resources and improve the economy of the plant by reducing unnecessary costs and increasing the level of safety. Rotating machinery is the most common machinery in industry and the root of the faults in rotatingmachinery is often faulty rolling element bearings. Because of a transitory characteristic vibration of bearing faults, combining Continuous wavelet transforms with envelope analysis is applied for signal proseccing. This paper studies the application of independent component analysis and support vector machines to for automated diagnosis of localized faults in rolling element bearings. The independent component analysis is used for feature extraction and data reduction from original features. The principal components analysis is also applied in feature extraction process for comparison with independent component analysis does. In this paper, support vector machines-based multi-class classification is applied to do faults classification process and utilized a cross-validation technique in order to choose the optimal values of kernel parameters.

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Multi-environment trials have a significant role in selecting the best cultivars to be used at different locations. The objectives of the present study were to evaluate GE interactions for grain yield in barley doubled haploid lines, to determine their stability and general adaptability and to compare different parametric and nonparametric stability and adaptability measures. For these purposes, 40 doubled haploid lines as well as two parental cultivars (Morex and Steptoe) were evaluated across eight variable environments (combinations of location-years-water regime) during the 2012-2013 and 2013-2014 growing seasons in Iran. The Additive Main effect and Multiplicative Interaction (AMMI) analysis revealed that environments, genotypes, and GE interaction as well as the first four Interaction Principal Component Axes (IPCA1 to 4) were significant, indicating differential responses of the lines to the environments and the need for stability and general adaptability analysis. The stability parameters S_i⁽³⁾, S_i⁽⁶⁾, NP2, NP3, NP4 as well as Fox-rank (Top) were positively and significantly correlated with mean yield, suggesting these statistics can be used interchangeably as suitable parameters for selecting stable lines. The results of Principal Components Analysis (PCA) showed that the first two PCAs explained 92% of total variation for ranks of mean grain yield and parameters, and also clustered stability parameters on the basis of static and dynamic concepts of stability. In general, the parametric and non-parametric stability measures revealed that among tested doubled haploid lines at different environments, the line DH-30 followed by DH-29 and DH-3 were identified as lines with high grain yields as well as the most stable for variable environments of semi-arid regions of Iran.