Improvement in genetic gains of crops could be achieved by phenomics' characterization of agronomic, physiological and stress-related traits. Molecular and strategic breeding programmes require broad range of foreground and background phenotypic information for crop improvement. The current experiment was performed on 123 advanced soybean (Glycine max L.) genotypes including seven local lines belongs to four different maturity groups (000-lV) to estimate the endogenous potential of various yield-related traits. The experimental trial was repeated for two cropping seasons. Four traits out of six, yield per plant (YPP), number of seeds per plant, number of pods per plant and plant height (PH), showed maximum variation (CV%) that directly correlate with variability in the subjected population. PH, number of pods, 100-seed weight and YPP showed strong positive correlation in both years. Among the principal components, factors 1 and 2 showed maximum contribution in phenotypic variability ranges from 19 to 48.5% and 26 to 47.7% in the first and second years, respectively. Number of pods showed significant positive correlation with genotypes in both years. Dendrogram showed two distinct groups of soybean genotypes. Genetic variation and association among the accessions is indispensable for effective conservation and utilization of germplasm. Principal component analysis helps to identify the diverse genotypes that will be used as a parent for various breeding programmes. These phenotypic data will be used for detection of heat stress-related quantitative trait loci with genotypic data in genome-wide association studies experiments.

The aim of this study was to test whether a positive and a negative component could be found in broadly defined schizophrenic patients. Therefore, 70 patients either in an exacerbated or in a stabilized phase were selected according to the criteria of at least 1 of the 4 following diagnostic systems: DSM III-R, Schneider, Carpenter, Langfeldt; principal component analyses (PCA) were carried out with the 9 global ratings of the Scales for Assessment of Negative and Positive Symptoms (SANS and SAPS) and with the Positive and Negative Syndrome Scale (PANSS). The PCA of the SANS-SAPS global ratings yielded a 3-factor solution explaining 72.14% of the total variance, depicting a negative, a positive and a disorganization component. The PCA of the PANSS provided a 5-factor solution with a total explained variance of 55.98%. The first 3 factors were similar to those of the SANS-SAPS global rating analysis. The results showed that the positive and negative components described in a homogeneous schizophrenic population could be replicated in a larger and more heterogeneous group of schizophrenic patients. The question regarding the sufficiency of the positive-negative dichotomy was strengthened by the presence of a third disorganization component which explained as much of the variance as the positive component.