Theses and Dissertations Collection

Permanent URI for this collectionhttp://10.10.97.169:4000/handle/123456789/5605

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    Accessibility and use of nutrition information in addressing under five child malnutrition in Morogoro urban, Tanzania
    (Sokoine University of Agriculture, 2002) Chilimo,Wanyenda Leonard
    This study was undertaken to examine the access to and use of nutrition information in addressing the problem of malnutrition in Morogoro urban district Tanzania. The study investigated the Maternal and Child Health clinics (MCH) nutrition information delivery systems; variables that determine accessibility and use of information; extent of the use of nutrition information in addressing malnutrition and the relationship between the information that mothers have and the nutritional status of their children. Survey research method was used for data collection whereby questionnaires and face-to-face interviews were used for collecting data. The study found that although the MCH health and nutrition education sessions arc an important aspect in disseminating nutrition information to mothers, these sessions are seldom conducted and the attendance of mothers to these sessions is poor; awareness of mothers concerning different nutritional aspects is still low due to lack of information; and education is the most important variable that determines use and access to nutrition information.
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    Data Preservation, Sharing and Reuse Practises among Agricultural Researchers in Tanzania
    (Sokoine University of Agriculture, 2023) Mwinami N.V
    Agricultural research data preservation, sharing, and use practices are crucial in enhancing research activities in Tanzania. However, little is known about the preservation, sharing, and use/reuse practises among agricultural researchers in the country. The main purpose of this study was to investigate data preservation, sharing, and use/reuse practises among agricultural researchers in Tanzania. Specifically, the study, focused on data sources for accessibility and reuse practises among agricultural researchers in Tanzania; analysed the communication channels and their potential applicability in enhancing agricultural research data sharing among agricultural researchers in Tanzania; examined the data preservation practises for enhancing agricultural research data usage among researchers in Tanzania, and examined the factors influencing agricultural researchers’ data sharing practises for enhanced accessibility of agriculture research data in Tanzania. The current study employed cross-sectional survey methods to investigate data preservation, data-sharing, and use/reuse practises among agricultural researchers in Tanzania. The study was conducted in Agricultural Research Institutions (TARI) centres and Sokoine University of Agriculture (SUA) as an academic and agricultural research institution. The study used both quantitative and qualitative approaches in data collection and analysis. The study involved 227 agricultural researchers who were randomly selected from the study area. Purposively, eleven (11) key informants were selected, namely eleven Directors/Managers from selected TARI centres and one (1) Director of Postgraduate Studies, Research, Technology Transfer & Consultancy for SUA. Also, two Focus Group Discussions which included six participants from Mikocheni TARI centre and IIonga TARI centre) were conducted in these two centres. The data collection involved the use of multiple data-gathering techniques (questionnaires and interviews and focus group discussions). Quantitative data were analysed with the help of the Statistical Product Service Solution (SPSS) Version 22 while thematic analysis was used to analyse qualitative data. Descriptive statistics techniques were calculated to establish the demographic characteristics of respondents, data sources and use/reuse practises, existing communication channels and their applicability in data sharing, data preservation practices in enhancing data usage, and factors influencing agricultural researchers’ data sharing practises for enhanced accessibility of agriculture research data in Tanzania. The findings indicate that agricultural researchers use/reuse data that are accessed from different other sources. Findings reveal that the majority of researchers 95.1% use/reuse data in writing scientific papers. Research data are also used in writing technical reports and project proposals. Similarly, results from Binary Logistic Regression Analysis revealed that factors influencing researchers in the use/reuse of research data were not statistical significance meaning that all factors (independent variables) contributed equally to influence researchers in actual data use/reuse. Furthermore, findings reveal that both mediated and non-mediated channels exist and were used as data-sharing channels. The majority of researchers more than 80% preferred to use non-mediated channels. Moreover, findings show that some mediated data-sharing channels were least used, including social media platforms, institutional repositories and funding agency databases. Through cross-tabulation, findings indicate that the extent of data sharing channel usage at SUA was higher than at the other research institutions investigated. Some channel usage also has statistical significance including meetings and conferences p=0.005, website p=0.001, workshop p=0.049, telephone as interpersonal mediated p=0.045, and technical report p=0.045. This meant that these channels were preferred for use across all agricultural research institutions. Findings also indicate that more than fifty percent of the respondents agreed that timely delivery, the cost for the use of a channel and convenience to a channel were among the factors influencing researchers in their channel selection. Likewise, findings reveal that the majority of researchers preferred to preserve their data using different storage devices such as field notebooks, desktop/personal computers, and institutional libraries. Moreover, the findings indicate that agricultural researchers preferred to preserve their data for more than six years after the end of the project. The findings also indicate the factors that influence researchers in the choice of data preservation methods were: easy to reach, cost-effective storage devices, support to use the devices, adequate infrastructure for data preservation, and reliable power supply. Furthermore, the findings indicate that some factors that influence researchers in data sharing indicating statistical significance included perceived community benefit, perceived ability to share, data sharing norms, and funding agency policies. The findings also indicate that the lack of data sharing policy and the absence of data preservation/management infrastructures, for example, data repositories were the challenges facing agricultural researchers in data sharing. Based on these findings it can be concluded that agricultural researchers share their data with fellow close research fellows. Agricultural researchers use both mediated and non- mediated data-sharing channels. The main factors motivating researchers to share their data include perceived community benefits, perceived ability to share, data-sharing norms and funding agency policy. Also, it can be concluded that there is yet a great role of research data preservation in enhancing data usage among researchers in Tanzania.
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    Examining ugunduzi app in enhancing smallholder farmers on farmer-led research of agro-ecological practices in Tanzania
    (Sokoine University of Agriculture, 2023) Kihoma. L
    Background: Smallholder farmers play a key role in feeding world population. In recent decades a challenge of shrinking crop productivity was observed to face many smallholder farmers, particularly in African countries. Food deficit was among significant consequences reported to affect this group. Climate change, caused by environmental pollution, is a major contributor to low food productivity performance. Transforming food production system to protect environment for climate change resilience is regarded as a better way for increasing crop productivity to meet food demand. Agro-ecological practices could suit this platform as they use natural resources in production system. Farmer-led research of agro-ecological practices (FLRAG) is considered as a key supporter to farmers on identifying best-fit among many agro-ecological practices available in their areas. In the same vein of supporting farmers, smallholder farmers in particular, SWISSAID Tanzania developed a smartphone based app named Ugunduzi aiming to uphold farmers in their research activities. The app was intended to enhance farmers on field data collection, record keeping, share information and calculate costs used and benefits obtained on a per plot basis. It was developed in 2018 with participation of farmers and ICT experts. The app started being used by a small group of 60 smallholder farmers since 2019. However, its potential in supporting farmers in FLRAG has not been documented. This study aimed to examine the ugunduzi app for validating its potential to smallholder farmers on FLRAG in Tanzania. Research methodology: The study was conducted in Bagamoyo, Masasi and Mvomero Districts, Tanzania. Before selecting participants in FLRAG and use of the ugunduzi, a baseline survey was conducted to identify factors influencing smallholder farmers to participate in the research. The aim was to set the criteria for selecting responsible participants in FLRAG by considering identified factors. Ninety smallholder farmers were interviewed using a structured questionnaire to collect quantitative data during baseline survey. Binary logit model in SPSS programme version 26 was used to analyse the data to identify factors influencing farmers to participate in FLRAG. Qualitative data were also collected and analysed using content analysis to explain what was observed with quantitative data. Thereafter, the criteria for selecting participants were formulated by considering identified factors. Smallholder farmers who met the criteria were identified from the study areas, and then 60 farmers were selected to participate in FLRAG and use the Ugunduzi app. Time series research method was used in the study. The research was conducted in three seasons of 2019, 2020 and 2021. In examining the Ugunduzi app, the study specifically intended to examine continuance intention of using the Ugunduzi app among Tanzanian smallholder farmers. This was done by examining farmers’ perception of usefulness and easiness of use which could lead to user satisfaction of the app and predict continuance intention of use. Identification of challenges on using the app and its limitation were also an aim of this study. Because farmers participated in FLRAG, investigation on the effects of agro-ecological practices in crop yield from the research was also an objective of the study. Field data were drawn from the Ugunduzi app in which participants used to collect and keep data. The data were also collected during field visits by using a structured questionnaire. Observation technique and focus group discussions were also conducted to collect qualitative data. Descriptive statistics were computed as part of quantitative data analysis to measure means and percentages. Partial least square structural equation modelling (PLS-SEM) using smartpls 3 was used to examine continuance intentions of using the Ugunduzi app. Excel software was used to measure average yields from agro-ecological treatments and control plots. R-software was used to determine the effects of the agro-ecological practices on crop yield from FLRAG. Findings and conclusions: From the research, it was identified that experience in farming, easiness in accessing agro-ecological inputs, interest in doing experiments and farm size were the factors that substantially influenced smallholder farmers to participate in FLRAG. On examining the Ugunduzi app, the results indicated that the app satisfied smallholder farmers and showed possibility of continuous usage by them. This was due to its usefulness on supporting them to identify best-fit agro-ecological practices and to have better future season plan through records kept in the app. The app also showed greater potential on increasing agro-ecological knowledge through sharing information to the ugunduzi web-site via the Ugunduzi app. However, difficulties on using the app among smallholder farmers were observed, especially at the early stage of using it due to some processes involved. The issues of low practical experience of using smartphones, poor network connectivity, inadequate electrical power supply and limited purchasing power of smartphones were observed as the main challenges which many smallholder farmers faced in study areas. On the limitations side, it was identified that Ugunduzi app is a one- way communication app which runs on Android based smartphones supported by a Google Chrome web browser. The app was developed to support farmers who apply agro- ecological cropping practices only and is not suitable for illiterate farmers. On the effects of agro-ecological practices on crop yield from FLRAG, the results indicate that there were positive significant effects of the practices, particularly cow dung and poultry manure, on crop yield. From the findings, it is concluded that the Ugunduzi app positively supports smallholder farmers and is a valid tool to be promoted for using by many farmers in their agro-ecological areas and farming activities. Recommendations: From the study findings, it is recommended that key stakeholders including service providers of network and electricity power suppliers should work on reducing challenges of low network and power cut-outs in the study areas and other parts in Tanzania which face the same challenges. The government of Tanzania is advised to reduce costs of purchasing smartphone devices and promote their uses due to their usefulness, including using the Ugunduzi app. It is recommended that, the Ministry of Agriculture and NGOs dealing with agro-ecology to promote the use of the Ugunduzi app in FLRAG for quality research results of identifying best practices which could increase crop productivity. ICT experts should take Ugunduzi app limitations as a way forward on developing improved apps which are more suitable to smallholder farmers in Tanzania and Africa in general. Suggestion is also provided to the government of Tanzania, through its Ministry of Agriculture to (i) promote the uses of agro-ecological practices by many farmers, cow dung and poultry manure in particular as among of strategic approaches for increasing crop yield, (ii) Encourage more FLRAG for identifying more beneficial practices by smallholder farmers, and (iii) Encourage investment in agro-ecological practices particularly cow dung and poultry manure to mitigate the problem of inadequate availability of inputs. Furthermore, on selecting participants, identified factors have to be taken into consideration on setting criteria for selecting participants in FLRAG.
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    Prediction of factors influencing rats tuberculosis detection performance using data mining techniques
    (Uppsala Univers1tet, 2019) Jonathan, Joan
    This thesis aimed to predict the factors that influence rats TB detection performance using data mining techniques. A rats TB detection performance dataset was given from APOPO TB training and research center in Morogoro. Tanzania. After data preprocessing, the size of the dataset was 471,133 rats TB detection performance observations and a sample size of 4 female rats. However, in the analysis, only 200,000 data observations were used. Based on the CRISP- DM methodology, this thesis used R language as a data mining tool to analyze the given data. To build the predictive model the classification technique was used to predict the influencing factors and classify rats using a decision tree, random forest, and naive Bayes algorithms. The built predictive models were validated with the same test data to check their classification prediction accuracy and to find the best. The results pinpoint that the random forest is the best predictive model with an accuracy of 78.82%. However, the accuracy differences are negligible. When considering the predictive model accuracy (78.78%) and speed (3 seconds) of the decision tree, it is the best predictive model since it has less building time compared to the random forest (154 seconds). Moreover, the results manifest that age is the most significant influencing factor, and rats of ages between 3.1 to 6 years portrayed potentiality in detection performance. The other predicted factors are Session_Completion_Time, Session_Start_Timc, and Av_Weight_Pcr_Ycar. These results are useful as a reference to rats TB trainers and researchers in rats TB and Information Systems. Further research using other data mining techniques and tools is valuable.