Welcome to SUAIRE

Sokoine University of Agriculture  Institutional Repository (SUA IR). This repository was built and is maintained by the university library  (Sokoine National Agricultural Library-SNAL) , in order to collect, preserve and disseminate scholarly output generated by University research community (staff and students) members.

This repository hosts a variety of openly accessible materials including: scholarly articles and books, theses and dissertations, conference proceedings and technical reports. For assistance about depositing your research output in the repository click here. SUA IR Policy  click here or any queries contact us at snal@sua.ac.tz.

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Now showing 1 - 5 of 15

Recent Submissions

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The role of Artificial Intelligence in livestock farming for improved animal health and productivity: opportunities, challenges, and future research directions
(East African Journal of Agriculture and Biotechnology, 2026-05-11) Barakabitze, Alcardo Alex; Sanga, Camilius
Livestock farming is a growing sector globally, and it makes a big contribution to GDP and food security. In Sub-Saharan countries such as Tanzania, livestock farming is used as a means of poverty eradication in some communities, but it requires a lot of manpower, time, and material resources to monitor animal health and welfare. As the number of animal farming enterprises increases, the continued use of traditional livestock monitoring methods may reduce economic outputs and the welfare of animals; thus, farmers are opting for ICT solutions to mitigate this.Machine learning and artificial intelligence (AI) are used to revolutionise how livestock is managed and monitored. Machine learning algorithms are an integral part of precision livestock farming. Farmers can use it to streamline the monitoring of animal behaviour and welfare, predict disease outbreaks, and optimise feeding schedules. This paper aims to assess the role of artificial intelligence technology in animal husbandry to improve animal one health and production. We conducted a systematic literature review from relevant databases. Finding studies showed that AI has a great role in animal husbandry. The studies revealed that AI technology has various uses like health monitoring, reproduction monitoring (oestrus and parturition and pedigree), real-time data collection, automated milking, location tracking, and identification of animals, hence theft prevention, detection of animal parameters, Hatchery condition detection, reducing workload, pasture evaluation, and grazing management. To conclude, we propose an artificial intelligence– based framework for monitoring livestock and increasing animal productivity and sustainability in Tanzania.
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Multi-metric flood hazard characterization using daily rainfall runoff dynamics: a comparative analysis of Rufiji and Mirongo Catchments, Tanzania
(MDPI, 2026-06-15) Sumari Neema Simon; Maginga Theofrida J.
Flood hazards are intensifying across Africa due to rapid urban expansion and hydro- climatic variability. This study develops a multi-metric geospatial framework combining extreme value analysis, hydrograph-based metrics, and dependence modelling to quan- tify flood magnitude, frequency, timing, and joint risk dynamics. Daily precipitation and streamflow reanalysis data (1985–2025) were analyzed for two contrasting Tanzanian catchments: the large Rufiji basin (RU) and the smaller Mirongo catchment (MW). An- nual maxima were modelled using the Generalized Extreme Value (GEV) distribution, complemented by flow duration curves, peak-over-threshold detection, and regression- copula dependence analysis. Results reveal strong hydrological contrasts. RU exhibits amplified rare-event growth (design floods from ~2850 to 11,770 m3/s), extended recession persistence (>100 days), low flashiness, and long rainfall-runoff lags (~15 days), indicating storage-dominated behavior. MW shows smaller design floods (~80 to 370 m3/s), higher flashiness, and short lags (~4 days), reflecting rapid, rainfall-driven response. Gaussian copula parameters indicate moderate dependence in both basins (0.32 and 0.34), suggesting that joint dependence alone does not distinguish flood mechanisms without complementary metrics. The proposed framework improves basin-specific flood risk profiling and supports geospatial early-warning system design in data-scarce Sub-Saharan environments.
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ICT4Agroecology: a participatory research methodology for agroecological field research in Tanzania
(Taylor & Francis, 2024) Hilbeck, Angelika; Tisselli, Eugenio; Crameri, Simon; Sibuga, Kallunde P.; Constantine, John; Shitindi, Mawazo J.; Kilasara, Method; Churi, Ayubu; Sanga, Camillius; Kihoma, Luambano; Brush, Gladness; Stambuli, Fadhili; Mjunguli, Rainard; Burnier, Blaise; Maro, Janet; Mbele, Angelina; Hamza, Suleyman; Kissimbo, Mary; Ndee, Ayoub
Agroecology has become increasingly popular but locally optimized agroecological production methods and informa­tion and communication technology (ICT) support tools are limited. This study was conducted at three different geo­graphic locations across Tanzania; we co-developed an integrated participatory field research methodology con­sisting of two components, each supported by a specifically developed, complementary ICT tool, withmaize and cassava as the two focal crops, to examine soil fertility and conservation (compost and mulching), increased biodiversity through intercropping (legumes), and organic pest control measures. Two specifically devel­ oped ICT tools, the AgroEco Research application (AER) and AgroEco Analysis application (AEA) were used for data gathering & storage and visualization & statistical analysis,respectively. Further, farmer-managed satellite experiments were performed to further test the research premises and validate their outcomes in the “real world” of smallholder farmers, which was supported by a smartphone application called “Ugunduzi” – enabling farmers to collect, store, and evaluate data generated at different stages of their research. Farmers were free to choose any type, number, and combination of the agroecological practices tested in the field research. This study serves as a methodology reference for a number of companion publications reporting
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Natural history observations on a warty frog: callulina dawida (amphibia: brevicipitidae) in the Taita Hills, Kenya
(International Scholarly Research Network, 2012) Malonza, Patrick K.
Amphibian populations are declining throughout the world, but most of the susceptible species possess particular biological attributes. Understanding these traits plus the environmental factors responsible for declines greatly aids conservation prioritization and planning. This paper examines the natural history observations and ecological characteristics of Callulina dawida, a frog endemic to the montane forests of the Taita Hills, Kenya. Sampling was accomplished by use of standardized pitfall trapping, transects, and time-limited searches. Mean monthly temperature and elevation significantly influenced the species distribution and abundance but mean monthly rainfall did not. The species was rare or absent during the cold season and its abundance increased with elevation. Breeding occurred during the long dry season (June to October) with juveniles being abundant between January and March. Available evidence shows that this species deposits a cluster of large yolk-rich eggs on the forest floor with maternal care and direct development. Its occurrence only within highly fragmented indigenous forests makes the species worth listing as critically endangered. To conserve this species, all remaining indigenous forest fragments including those communally or privately owned should be preserved and connected through planting of indigenous trees along stream valleys. In addition, the exotic tree plantations should be replaced with indigenous trees to restore the species habitat.
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The predictive validity of form two secondary education examination (FTSEE) on students’ performance in the certificate of secondary education examination (CSEE) in biology subject: a Tanzanian perspective
(IISTE, 2013) Komba, Sotco Claudius; Kafanabo, Eugenia Joseph; Tryphone, Dorice; Kira, Ernest Simon
This article is based on the study which sought to examine the predictive validity of Form Two Secondary Education Examination (FTSEE) on students’ performance in the Certificate of Secondary Education Examination (CSEE) in Biology subject. A sample of 120 students from some selected secondary schools in Morogoro Municipality, Tanzania, was involved. The collected data were analyzed using computer software, Statistical Package for Software System (SPSS), Version 18. In the data analysis, the Pearson’s Product-Moment Correlation (r) technique was used in order to determine the strength, direction and significance o of the relationships of all the variables included in the study. The findings indicated that there was a strong relationship between the students’ performance in the FTSEE and CSEE (i.e. from r=0.442, p<0.01 to r=0.726, p<0.01) regardless of sex and type of school. Nevertheless, the relationship was found to be higher for females (r=0.726) than males (r= 0.613). In addition, for the case of the studied Day school, male students in the Day school had a higher correlation coefficient between the two examinations (r=0.65) than female students (r=0.442). This implies that female students performed slightly better than males in Boarding schools while in the Day school, male students performed better than females. Therefore, on the basis of these findings, it is recommended that the FTSEE should be sustained in order to improve the students’ performance in the CSEE in Tanzania