Identifying the component structure of job satisfaction by principal components analysis among extension officers in North West Province, South Africa

The component structure of a 34-item scale measuring different aspects of job satisfaction was investigated among extension officers in North West Province, South Africa. A simple random sampling technique was used to select 40 extension officers from which data were collected. A structured questionnaire consisting of 34 job satisfaction and 10 personal characteristic items was administered to the extension officers. Items on job satisfaction were measured at interval level and analyzedwith Principal ComponentAnalysis. Most of the respondents (82.5%) weremales, between 40 to 45 years, 85% were married and 87.5% had a diploma as their educational qualification. Furthermore, 54% of the households size between 4 to 6 persons, whereas 75% were Christians. The majority of the extension officers lived in their job area (82.5), while 80% covered at least 3 communities and 3 farmer groups. In terms of number of farmers covered, only 40% of the extension officers covered more than 500 farmers and 45% travelled more than 40 km to reach their farmers. From the job satisfaction items 9 components were extracted to show areas for job satisfaction among extension officers. These were in-service training, research policies, communicating recommended practices, financial support for self and family, quality of technical help, opportunity to advance education, management and control of operations, rewarding system and sanctions. The results have several implications for motivating extension officers for high job performance especially with large number of clients and small number of extension agents.

Cereal/legume rotation effects on rhizosphere bacterial community structure in West African soils

The increased use of cereal/legume crop rotation has been advocated as a strategy to increase cereal yields of subsistence farmers in West Africa, and is believed to promote changes in the rhizosphere that enhance early plant growth. In this study we investigated the microbial diversity of the rhizoplane from seedlings grown in two soils previously planted to cereal or legume from experimental plots in Gaya, Niger, and Kaboli, Togo. Soils from these legume rotation and continuous cereal plots were placed into containers and sown in a growth chamber with maize (Zea mays L.), millet (Pennisetum glaucum L.), sorghum (Sorghum bicolor L. Moench.), cowpea (Vigna unguiculata L.) or groundnut (Arachis hypogaea L.). At 7 and 14 days after sowing, 16S rDNA profiles of the eubacterial and ammoniaoxidizing communities from the rhizoplane and bulk soil were generated using denaturing gradient gel electrophoresis (DGGE). Community profiles were subjected to peak fitting analyses to quantify the DNA band position and intensities, after which these data were compared using correspondence and principal components analysis. The data showed that cropping system had a highly significant effect on community structure (p <0.005), irrespective of plant species or sampling time. Continuous cereal-soil grown plants had highly similar rhizoplane communities across crop species and sites, whereas communities from the rotation soil showed greater variability and clustered with respect to plant species. Analyses of the ammonia-oxidizing communities provided no evidence of any effects of plant species or management history on ammonia oxidizers in soil from Kaboli, but there were large shifts with respect to this group of bacteria in soils from Gaya. The results of these analyses show that crop rotation can cause significant shifts in rhizosphere bacterial communities.

Symptoms and causes of poverty in a rural Vietnamese commune: Does ethnicity matter?

This study uses data from a sample survey of 200 households drawn from a mountainous commune in Vietnam’s North Central Coast region to measure and explain relative poverty. Principal components analysis is used to construct a multidimensional index of poverty outcomes from variables measuring household income and the value of domestic assets. This index of poverty is then regressed on likely causes of poverty including different forms of resource endowment and social exclusion defined by gender and ethnicity. The ordinary least squares estimates indicate that poverty is indeed influenced by ethnicity, partly through its interaction with social capital. However, poverty is most strongly affected by differences in human and social capital. Differences in the amount of livestock and high quality farmland owned also matter. Thai households are poorer than their Kinh counterparts even when endowed with the same levels of human, social, physical and natural capital considered in the study. This empirical result provides a rationale for further research on the causal relationship between ethnicity and poverty outcomes.