Role of home gardens in enhancing food security in rural and urban areas : a case study of Nkonkobe Municipality, Eastern Cape South Africa
- Authors: Mcata, Bongiwe
- Date: 2013
- Subjects: Food security -- South Africa -- Eastern Cape Gardening -- South Africa -- Eastern Cape
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10353/13105 , vital:39465
- Description: In South Africa, home gardens are an important source of food and nutrition. In both urban and rural areas, home gardens have been a traditional way of providing food and offer a great potential for improving household food security and alleviating micronutrient deficiencies. In the Eastern Cape Province which is the second largest province in South Africa, and is characterized by poverty, home gardens can help enhance household food security through direct access to nutritionally-rich fresh vegetables. Home gardens are also becoming an important source of food and income, especially for poor households, in both urban and rural areas. the province. The findings illustrates that livelihood diversification may not be relevant for household welfare in the case of South Africa. However promoting livelihood diversification remain imperative for household welfare in the South Africa in the long-run. It further illustrate that gender of head, education, access to electricity, home agriculture are imperative for the improvement of household welfare. Hence the study recommends policy relating to conditional granting of cash grant support, intensification of rural development programmes, education affordable and accessible at all level and support home stead or subsistence agriculture This study was carried out to investigate the role of home gardens in addressing household food security in urban and rural areas of Nkonkobe Municipality. The study also identified the factors affecting the ownership of home gardens and food security. Data was collected from 160 households from both the urban and rural areas of the Nkonkobe Municipality. These households were selected through the use of stratified random sampling. Data was collected by a questionnaire was administered through face-to-face interviews. Frequencies and means were used to describe the general characteristics of the households as well as ownership patterns of home gardens. In order to determine the factors that influence home gardens and food security among the sampled households, a binary logistic regression model was adopted. The results show that the statistically significant variables, at the 5percent level, on food security are total income and home garden ownership. Food security was measured using the dietary diversity score. Location, access to land and education significantly affect the ownership of home gardens positively. In view of the research findings, several policy proposals are suggested. These include greater investment in programmes such as Massive food projects, Siyazondla and related home garden initiatives. Household income can be improved by promoting more non-agricultural activities in order to ensure household food security.
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- Authors: Mcata, Bongiwe
- Date: 2013
- Subjects: Food security -- South Africa -- Eastern Cape Gardening -- South Africa -- Eastern Cape
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10353/13105 , vital:39465
- Description: In South Africa, home gardens are an important source of food and nutrition. In both urban and rural areas, home gardens have been a traditional way of providing food and offer a great potential for improving household food security and alleviating micronutrient deficiencies. In the Eastern Cape Province which is the second largest province in South Africa, and is characterized by poverty, home gardens can help enhance household food security through direct access to nutritionally-rich fresh vegetables. Home gardens are also becoming an important source of food and income, especially for poor households, in both urban and rural areas. the province. The findings illustrates that livelihood diversification may not be relevant for household welfare in the case of South Africa. However promoting livelihood diversification remain imperative for household welfare in the South Africa in the long-run. It further illustrate that gender of head, education, access to electricity, home agriculture are imperative for the improvement of household welfare. Hence the study recommends policy relating to conditional granting of cash grant support, intensification of rural development programmes, education affordable and accessible at all level and support home stead or subsistence agriculture This study was carried out to investigate the role of home gardens in addressing household food security in urban and rural areas of Nkonkobe Municipality. The study also identified the factors affecting the ownership of home gardens and food security. Data was collected from 160 households from both the urban and rural areas of the Nkonkobe Municipality. These households were selected through the use of stratified random sampling. Data was collected by a questionnaire was administered through face-to-face interviews. Frequencies and means were used to describe the general characteristics of the households as well as ownership patterns of home gardens. In order to determine the factors that influence home gardens and food security among the sampled households, a binary logistic regression model was adopted. The results show that the statistically significant variables, at the 5percent level, on food security are total income and home garden ownership. Food security was measured using the dietary diversity score. Location, access to land and education significantly affect the ownership of home gardens positively. In view of the research findings, several policy proposals are suggested. These include greater investment in programmes such as Massive food projects, Siyazondla and related home garden initiatives. Household income can be improved by promoting more non-agricultural activities in order to ensure household food security.
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Studies on bioflocculants produced by three freshwater Actinomycetes (Streptomyces Sp.Gansen, Cellulomonas Sp,Bola and Brachybacterium Sp, UFH) isolated from Tyume river
- Authors: Oladele, Agunbiade M
- Date: 2011
- Subjects: Flocculation Streptomyces Gram-positive bacteria Actinobacteria
- Language: English
- Type: Thesis , Masters , Degree
- Identifier: http://hdl.handle.net/10353/6550 , vital:30552
- Description: Several bacteria were isolated from the bottom sediments of Tyume River and investigated for bioflocculant production potentials. Kaolin clay suspension (4 g/l) was used to measure the flocculating activity and three of the positive isolates were identified by 16S rRNA gene nucleotide sequence analyses and the sequences deposited in GenBank as Streptomyces sp Gansen (accession number HQ537129), Brachybacterium sp UFH (accession number HQ537131.), and Cellulomonas sp Bola (accession number HQ537132). Streptomyces sp Gansen exhibited its maximum flocculating activity using lactose (85% activity), peptone (76.3% activity), Ca2+ as sole sources of carbon, nitrogen and cations respectively, and at a neutral pH of 7.0, while, the bioflocculant produced by Brachybacterium sp UFH with glucose, urea and Ca2+ as carbon, nitrogen and cations sources yielded 82% and 97% flocculation activity respectively at a neutral pH. Also, glucose (73.2% activity), ammonium chloride (78.2% activity) and Ca2+ resulted in optimal production of bioflocculant by Cellulomonas sp Bola, also at a neutral pH. Chemical analysis confirmed that bioflocculant produced by Streptomyces Gansen is a polysaccharide while Brachybacterium sp UFH and Cellulomonas sp Bola produces a glycoprotein compound. This freshwater actinomycetes appears to have a tremendous potential as sou rces of new bioflocculants.
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- Authors: Oladele, Agunbiade M
- Date: 2011
- Subjects: Flocculation Streptomyces Gram-positive bacteria Actinobacteria
- Language: English
- Type: Thesis , Masters , Degree
- Identifier: http://hdl.handle.net/10353/6550 , vital:30552
- Description: Several bacteria were isolated from the bottom sediments of Tyume River and investigated for bioflocculant production potentials. Kaolin clay suspension (4 g/l) was used to measure the flocculating activity and three of the positive isolates were identified by 16S rRNA gene nucleotide sequence analyses and the sequences deposited in GenBank as Streptomyces sp Gansen (accession number HQ537129), Brachybacterium sp UFH (accession number HQ537131.), and Cellulomonas sp Bola (accession number HQ537132). Streptomyces sp Gansen exhibited its maximum flocculating activity using lactose (85% activity), peptone (76.3% activity), Ca2+ as sole sources of carbon, nitrogen and cations respectively, and at a neutral pH of 7.0, while, the bioflocculant produced by Brachybacterium sp UFH with glucose, urea and Ca2+ as carbon, nitrogen and cations sources yielded 82% and 97% flocculation activity respectively at a neutral pH. Also, glucose (73.2% activity), ammonium chloride (78.2% activity) and Ca2+ resulted in optimal production of bioflocculant by Cellulomonas sp Bola, also at a neutral pH. Chemical analysis confirmed that bioflocculant produced by Streptomyces Gansen is a polysaccharide while Brachybacterium sp UFH and Cellulomonas sp Bola produces a glycoprotein compound. This freshwater actinomycetes appears to have a tremendous potential as sou rces of new bioflocculants.
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Modelling false positive reduction in maritime object detection
- Authors: Nkele, Nosiphiwo
- Date: 20xx
- Subjects: Computer vision Neural networks (Computer science)
- Language: English
- Type: Thesis , Masters , MSc (Computer Science )
- Identifier: http://hdl.handle.net/10353/17168 , vital:40862
- Description: Target detection has become a very significant research area in computer vision with its applications in military, maritime surveillance, and defense and security. Maritime target detection during critical sea conditions produces a number of false positives when using the existing algorithms due to sea waves, dynamic nature of the ocean, camera motion, sea glint, sensor noise, sea spray, swell and the presence of birds. The main question that has been addressed in this research is how can object detection be improved in maritime environment by reducing false positives and promoting detection rate. Most of Previous work on object detection still fails to address the problem of false positives and false negatives due to background clutter. Most of the researchers tried to reduce false positives by applying filters but filtering degrades the quality of an image leading to more false alarms during detection. As much as radar technology has previously been the most utilized method, it still fails to detect very small objects and it may be applied in special circumstances. In trying to improve the implementation of target detection in maritime, empirical research method was proposed to answer questions about existing target detection algorithms and techniques used to reduce false positives in object detection. Visible images were retrained on a pre-trained Faster R-CNN with inception v2. The pre-trained model was retrained on five different sample data with increasing size, however for the last two samples the data was duplicated to increase size. For testing purposes 20 test images were utilized to evaluate all the models. The results of this study showed that the deep learning method used performed best in detecting maritime vessels and the increase of dataset improved detection performance and false positives were reduced. The duplication of images did not yield the best results; however, the results were promising for the first three models with increasing data.
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- Authors: Nkele, Nosiphiwo
- Date: 20xx
- Subjects: Computer vision Neural networks (Computer science)
- Language: English
- Type: Thesis , Masters , MSc (Computer Science )
- Identifier: http://hdl.handle.net/10353/17168 , vital:40862
- Description: Target detection has become a very significant research area in computer vision with its applications in military, maritime surveillance, and defense and security. Maritime target detection during critical sea conditions produces a number of false positives when using the existing algorithms due to sea waves, dynamic nature of the ocean, camera motion, sea glint, sensor noise, sea spray, swell and the presence of birds. The main question that has been addressed in this research is how can object detection be improved in maritime environment by reducing false positives and promoting detection rate. Most of Previous work on object detection still fails to address the problem of false positives and false negatives due to background clutter. Most of the researchers tried to reduce false positives by applying filters but filtering degrades the quality of an image leading to more false alarms during detection. As much as radar technology has previously been the most utilized method, it still fails to detect very small objects and it may be applied in special circumstances. In trying to improve the implementation of target detection in maritime, empirical research method was proposed to answer questions about existing target detection algorithms and techniques used to reduce false positives in object detection. Visible images were retrained on a pre-trained Faster R-CNN with inception v2. The pre-trained model was retrained on five different sample data with increasing size, however for the last two samples the data was duplicated to increase size. For testing purposes 20 test images were utilized to evaluate all the models. The results of this study showed that the deep learning method used performed best in detecting maritime vessels and the increase of dataset improved detection performance and false positives were reduced. The duplication of images did not yield the best results; however, the results were promising for the first three models with increasing data.
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