2 resultados para Multi-dimensional cluster analysis
em Bioline International
Resumo:
Poverty is a multi-dimensional socio-economic problem in most sub-Saharan African countries. The purpose of this study is to analyse the relationship between household size and poverty in low-income communities. The Northern Free State region in South Africa was selected as the study region. A sample of approximately 2 900 households was randomly selected within 12 poor communities in the region. A poverty line was calculated and 74% of all households were found to live below the poverty line. The Pearson’s chi-square test indicated a positive relationship between household size and poverty in eleven of the twelve low-income communities. Households below the poverty line presented larger households than those households above the poverty line. This finding is in contradiction with some findings in other African countries due to the fact that South Africa has higher levels of modernisation with less access to land for subsistence farming. Effective provision of basic needs, community facilities and access to assets such as land could assist poor households with better quality of life. Poor households also need to be granted access to economic opportunities, while also receiving adult education regarding financial management and reproductive health.
Resumo:
Phenotypic variation in plants can be evaluated by morphological characterization using visual attributes. Fruits have been the major descriptors for identification of different varieties of fruit crops. However, even in their absence, farmers, breeders and interested stakeholders require to distinguish between different mango varieties. This study aimed at determining diversity in mango germplasm from the Upper Athi River (UAR) and providing useful alternative descriptors for the identification of different mango varieties in the absence of fruits. A total of 20 International Plant Genetic Resources Institute (IPGRI) descriptors for mango were selected for use in the visual assessment of 98 mango accessions from 15 sites of the UAR region of eastern Kenya. Purposive sampling was used to identify farmers growing diverse varieties of mangoes. Evaluation of the descriptors was performed on-site and the data collected were then subjected to multivariate analysis including Principal Component Analysis (PCA) and Cluster analysis, one- way analysis of variance (ANOVA) and Chi square tests. Results classified the accessions into two major groups corresponding to indigenous and exotic varieties. The PCA showed the first six principal components accounting for 75.12% of the total variance. A strong and highly significant correlation was observed between the color of fully grown leaves, leaf blade width, leaf blade length and petiole length and also between the leaf attitude, color of young leaf, stem circumference, tree height, leaf margin, growth habit and fragrance. Useful descriptors for morphological evaluation were 14 out of the selected 20; however, ANOVA and Chi square test revealed that diversity in the accessions was majorly as a result of variations in color of young leaves, leaf attitude, leaf texture, growth habit, leaf blade length, leaf blade width and petiole length traits. These results reveal that mango germplasm in the UAR has significant diversity and that other morphological traits apart from fruits can be useful in morphological characterization of mango.