Efficacy of Bidens pilosa and Euphorbia hirta Extracts in Control of Bacterial Leaf Spot Disease of Solanum scabrum
William Omuketi Emitaro, David Mutisya Musyimi- May 2022 Page No.: 01-06
Bacterial leaf spot disease incited by Xanthomonas campestris pv. vescatoria affects solanum plants worldwide and caused up to 40-70% yield loss of Solanum scabrum. Efficacy of Bidens pilosa and Euphorbia hirta leaf and root extracts and one synthetic chemical Ridomil® was evaluated for control of bacterial leaf spot in Solanum scabrum. The experiment was laid out in randomized complete block design with three replicates. Seedlings were inoculated with Xanthomonas campestris pv. vesicatoria isolated from diseased S. scabrum and then treated separately with test concentrations of 25%, 50%, 100% and 50 mg/ml 100 mg/ml and 200 mg/ml for water and ethanol extract respectively. The extracts reduced disease severity with the highest concentrations (100% and 200 mg/ml significantly lowering disease severity compared to other extracts and Ridomil®. Plants treated with high concentrations of extracts had high growth vigor when stem diameter, plant height and leaf weight were evaluated. Reduction in disease severity and promotion of plant growth could be due to presence of secondary metabolites with antimicrobial activity and growth promoting hormones in the extracts. From this study B. pilosa and E. hirta extracts can be used as an alternative to synthetic chemical to control bacterial leaf spot disease of solanum. Future studied should focus on isolating active compounds to be used in formulating pesticides.
Page(s): 01-06 Date of Publication: 03 June 2022
William Omuketi Emitaro
Department of Biological Sciences, School of Biological and Physical Sciences, Jaramogi Oginga Odinga University of Science and technology, P.O. Box 210-4060 Bondo, Kenya
David Mutisya Musyimi
Department of Botany, School of Physical and Biological Sciences, Maseno University, P.O. Box Private bag Maseno, Kenya
[1] Abdalla, M.M. (2013). The Potential of Moringa Oleifera Extract as a Biostimulant in Enhancing the Growth, Biochemical And Hormonal Contents In Rocket (Eruca vesicaria Subsp. sativa) Plants. International Journal of Plant Physiology and Biochemistry, (3), 42-49.
[2] Abo-Elyousr, K. A. M., Najeeb, M. A., Ahmed, W.M. A., Sergio R. R. and Khamis, Y. (2020). Plant Extract Treatments Induce Resistance to Bacterial Spot by Tomato Plants for a Sustainable System. Horticulturae, 6(36), 1-12.
[3] AL-Saleh, M. A. (2011). Pathogenic Variability among Five Bacterial Isolates of Xanthomonas campestris pv. vesicatoria, Causing Spot Disease on Tomato and their Response to Salicylic Acid. Journal of the Saudi Society of Agricultural Sciences, 10(1), 47-51.
[4] Arefin, M.N., Bhuiyan, M. K. A. and Rubaye, M.T. (2019). Integrated use of Fungicide, Plant Extract and Bio-Agent for Management of Alternaria Blight Disease of Radish (Raphanus Sativus L.) and Quality Seed Production,” Research in: Agricultural & Veterinary Sciences, 3(1), 10-21.
[5] Araújo, E.R., Costa, J.R., Ferreira, M.A.S.V. and Quezado-Duval, A.M. (2012). Simultaneous Detection and Identification of the Xanthomonas Species Complex Associated with Tomato Bacterial Spot Using Species-Specific Primers and Multiplex PCR. Journal of Applied Microbiology, 113(6), 79-90.
[6] Choudhury, D., Prerna, D., Seweta, S., Soumen, S. and Susamoy, K. (2018). Role of Botanical Plant Extracts to Control Plant Pathogens-A review. Indian Journal of Agricultural Research, 52(4), 341-346.
[7] Didwania, N., Deepti, S. and Trivedi, P. C. (2013). Antibacterial Activity of a Few Medicinal Plants against Xanthomonas Campestris Pv . Campestris. International Journal of Research in Pharmaceutical Sicences, 4, 177–182.
[8] Din, N., Ahmad, M., Siddique, M., Ali, A., Naz, I., Ullah, N. and Ahmad, F. (2016). Phytobiocidal Management of Bacterial Wilt of Tomato Caused by Ralstonia solanacearum (Smith). Yabuuchi, Spanish Journal of Agricultural Research, 14(3), 1-13. http://dx.doi.org/10.5424/sjar/2016143-9012.
[9] Emitaro, W.O., Musyimi, D.M., Opand, G.T. and Odhiambo, G. (2020). Phytochemical and Antimicrobial Properties of Leaf Extracts of Calliandra calothyrsus, Leucaena diversifolia and Sesbania sesban. Bacterial Empire, 3(3), 20-24. https://doi.org/10.36547/be.2020.3.3.20-24
[10] Emitaro, W.O., Musyimi, D.M., Otiato, D.A. and Onyango, B. (2017). Morphological, Biochemical and Molecular Characterization of Xanthomonas campestris pv. vesicatoria on African nightshade (Solanum scabrum). International Journal of Biosciences, 11(1), 190-197.
[11] Emitaro, W.O., Musyimi, D.M., Otiato, D.A. and Buyela, D.K. (2018). Antibacterial effect of Euphorbia hirta and Bidens pilosa extracts against Xanthomonas campestris Pv vesicatoria isolated from diseased African nightshade (Solanum scabrum). International Journal of Microbiology and Mycology, 7 (5), 1-6.
[12] Gayathri, A. and Ramesh, K.V. (2013). Antifungal Activity of Euphorbia Hirta L . Inflorescence Extract against Aspergillus Flavus — A Mode of Action Study. International Journal of Current Microbiology and Applied Science, 2(4), 31-37.
[13] Gracelin, D. H. S., John, A.D.E.B., Benjamin, P.J. and Rathna, K. (2012). Detection and Identification of Xanthomonas campestris pv.centellae on Leaves of Centella asiatica Collected in Tamilnadu. Asian Journal of Pharmaceutical and Clinical Research, 5(3), 11-13.
[14] Hossain, M.D.F., Hasan, S.M.Z., Zannati, F.Z., Habiba, F.M.H., Asadul, M.I. and Biswanath, S. (2018). Biological Control of Bacterial Leaf Spot Disease of Papaya (Carica papaya) Through Antagonistic Approaches using Medicinal Plants Extracts and Soil Bacteria,” International Journal of Pure and Applied Biosciences, 6(1), 1-11. https://dx.doi.org/10.18782/2320-7051.6137.
[15] Izah, S.C. (2018). Some Determinant Factors of Antimicrobial Susceptibility Pattern of Plant Extracts. Research and Review Insight, 2(3), 1-4.
[16] Kebede, M., Amare, A. and Mohammed (2013). Efficacy of Plant Extracts , Traditional Materials and Antibacterial Chemicals Against Xanthomonas campestris pv . vesicatoria on Tomato Seed. African Journal of Microbiology Research, 7(20), 2395-2400.
[17] Le K.D., Kim. J., Yu, N.H., Kim, B., Lee, C.W. and Kim, J.C. (2020). Biological Control of Tomato Bacterial Wilt, Kimchi Cabbage Soft Rot, and Red Pepper Bacterial Leaf Spot Using Paenibacillus elgii JCK-5075. Frontiers in Plant Science, 11(775),1-12. https://doi.org/10.3389/fpls.2020.00775.
[18] Mamun, M. S. A. and Ahmed, M. (2011). Prospect Of Indigenous Plant Extracts In Tea Pest Management Indigenous Plant Extracts In Tea,” International Journal of Agricultural Research Inovation and Technology, 1, 16–23.
[19] Mbega, E.R., Mortensen, C.N., Mabagala, R.B. and Wulff, E.G. (2012). The Effect of Plant Extracts as Seed Treatment to Control Bacterial Leaf Spot Of Tomato In Tanzania,” Journal of General Plant Pathology, 78, 277-286.
[20] Nirosha, M., Pavani, K., Priya, A.K., Haseena, U. (2019). Jyothsna, S. Antimicrobial Activity of Organic Leaf Extract of Sesbania sesban Against Gram Negative Pathogenic Bacteria. International Journal of Life science and Pharmacy Research, 9(2), 30-38. http://dx.doi.org/10.22376.
[21] Ondieki, M. and Aguyoh, J. (2011). Variations in Growth and Yield Characteristics of Three Black Nightshade Species Grown under High Altitude Conditions. Agriculture and Biology Journal of North Americ, 2(3), 1-6.
[22] Opara, E.U. and Obani, F.T. (2010). Performance of Some Plant Extracts In the Control of Bacterial Spot Disease of Solanum. Agricultural journal, 5(2), 45-49.
[23] Perez, S.M., Biondi, E., Laurita, R., Proto, M., Sarti, F., Gherardi, M., Bertaccini, A., Colombo, V. (2019). Plasma Activated Water as Resistance Inducer Against Bacterial Leaf spot of Tomato. PLoS ONE, 14(5), 1-19. https://doi.org/10.1371/journal.pone.0217788
[24] Potnis, N., Timilsina, S., Strayer, A., Shantharaj, D., Barak, J.D., Paret, M.L., Vallad, G.E. and Jones, J.B. (2015). Bacterial Spot of Tomato and Pepper: Diverse Xanthomonas Species with a Wide Variety of Virulence Factors Posing a Worldwide Challenge. Molecular Plant Pathology, 16(9), 907–920.
[25] Roach, R., Mann, R., Gambley, C.G., Shivas, R.G. and Rodoni, G. (2020). Pathogenicity and Copper Tolerance in Australian Xanthomonas species Associated with Bacterial Leaf spot. Crop Protection, 127, 1-11. https://doi.org/10.1016/j.cropro.2019.104923.
[26] Roach, R., Mann, R., Gambley, C.G., Shivas, R.G. and Rodoni, G. (2017). Identification of Xanthomonas Species Associated with Bacterial Leaf Spot of Tomato, Capsicum and Chilli Crops in Eastern Australia. European Journal of Plant Pathology, 150, 595-608. https://doi.org/10.1007/s10658-017-1303-9.
[27] Salhi, N., Sultan, A.M., Saghir, V.T., Iman, B.N.G. and Samia, B. (2017). Antifungal Activity of Aqueous Extracts of Some Dominant Algerian Medicinal Plants,” BioMed Research International, 1- 6. https://doi.org/10.1155/2017/7526291.
[28] Shandukani, P.D., Shonisani, C.T., Peter, M. and Kgabo, M.M. (2018). Antibacterial Activity and in Situ Efficacy of Bidens pilosa Linn and Dichrostachys cinerea Wight et Arn Extracts Against Common Diarrhoea-Causing Waterborne Bacteria. BioMed Central Complementary and Alternative Medicine, 18(171), 1-10. https://doi.org/10.1186/s12906-018-2230-9.
[29] Syed-Ab-Rahman, S.F., Carvalhais, L.C. and Omar, D. (2020). Development of Plant-based Emulsion Formulations to Control Bacterial Leaf Blight and Sheath Brown Rot of Rice. Heliyon, 6, 1-6.
[30] Verma, A.K. and Agrawal K. (2017). In vitro Evaluation of Antibacterial Activity of Some Medicinal Plants against Xanthomonas pisi Causing Leaf Spot of Pea. International Journal of Pharmaceutical Sciences Review and Research, 45(2), 156-159
William Omuketi Emitaro, David Mutisya Musyimi “Efficacy of Bidens pilosa and Euphorbia hirta Extracts in Control of Bacterial Leaf Spot Disease of Solanum scabrum” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-5, pp.01-06 May 2022 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/volume-7-issue-5/01-06.pdf
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A multi-sphere project assessment framework for livelihood projects in Zimbabwe
Sifelani Ngwenya- May 2022 Page No.: 07-14
Incapacitation due to low commitment levels, limited stakeholder participation and the adhoc manner in which assessments are done defeat the purpose for which the practice and process was instituted, “to judge the direction, progress and performance of programs and projects.” This scenario undermines the noble benefits and value that the assessment practice brings to the design, planning and implementation of programs. Thus, the need for a multi-sphere assessment framework tended towards stakeholder commitment, inclusion and participation becomes apparent. This study assesses the need for a multi-sphere assessment framework for livelihood projects in Zimbabwe, by interrogating the participants’ experiences, and perceptions, on the assessment practice, and the ideal components of the new framework. Data for this study were collected through, desktop review, focus group discussion and questionnaires, limited to non-probability purposive, and conveniently selected 85 participants from Bulilima, Gwanda, Mangwe and Umzingwane districts of Zimbabwe. These participants comprised of district development coordinators (DDCs), Environmental Management Agency (EMA), Rural District Council (RDC) chief executive officers, councilors, traditional leaders (chiefs), NGO managers, and heads of schools. These participants were significant to the study, in that they brought depth to this study due the number of years of involvement in livelihood projects. The study found assessment to be a popular practice, that is variedly understood across domains and disciplines, but accorded little priority, done in an ad hoc manner, and districts lacking uniform assessments frameworks to guide all stakeholders. Hence, the existence of a parallel assessment regimes in the districts, and high incapacitation levels due to lack of political will and commitment. Therefore, the study recommends the strategic lobbying of all stakeholders to commit towards the embracement of the multi-sphere assessment framework, through the mobilization of political systems and institutions, to formulate pro assessment policies and allocation of resources. Taking this route may be critical in addressing commitment related incapacitation challenges and help stakeholders change their perception on assessment, resulting in a radical shift from an ad hoc approach to a proactive one that embraces inclusivity and participation. Furthermore, the proposed radical approach will foster confidence, participation, inclusivity, equity, accountability, transparency, networks, trust, and a mindset change, leading to new innovations in the assessment practice. The study further recommends, the making of capacity-building, training, and education the prime focus, to promote correct understanding, all stakeholder commitment to the assessment practice, and significantly contribute to the expansion of assessment knowledge. Therefore, study findings offer implications in terms of highlighting the salience of establishing the multi-sphere assessment framework that promotes inter-stakeholder collaboration.
Page(s): 07-14 Date of Publication: 04 June 2022
Sifelani Ngwenya
Centre for Evaluation Science, Faculty of Humanities and Social Science, Lupane State University, PO Box 170 Lupane. Zimbabwe
[1] Abildgaard, J.S., Saksvik, P.Ø. and Nielsen, K., 2016. How to measure the intervention process? An assessment of qualitative and quantitative approaches to data collection in the process evaluation of organizational interventions. Frontiers in Psychology, 7, p.1380.
[2] Archer, E. (2018). Qualitative data analysis: A primer on core approaches. Online Readings in Research Methods (ORIM), 1-23.
[3] Austrian Development Agency, 2008. Guidelines for project and programme evaluations. Vienna: Austrian Development Agency, Evaluation Unit.
[4] Bamberger, M. Rugh, J & Mabry, L,.2012. Real world evaluation. 2nd ed. Thousand Oaks: Sage Publications.
[5] Brown, A. 2012. CDC Coffee break: Using mixed methods program evaluation. https://www.cdc.gov/dhdsp/pubs/docs/cb_july_2012pdf Date of access:30 Jan.2019.
[6] Derbinski, N. & Reinhardt, T. 2017. The Evaluation process in 10 steps – a guideline. Berlin: Brot für die Welt –Evangelischer Entwicklungsdienst Evangelisches Werk für Diakonie und Entwicklung e. V.
[7] Farell, K., Kratzmann, M., McWilliams., Robinson., Saunders, S., Ticknor, J & White 2002. Evaluation made very easy, accessible, and logical. Nova Scotia: Atlantic Centre of Excellence for Women’s Health.
[8] Flemming, K., Booth, A., Hannes, K., Cargo, M. and Noyes, J., 2018. Cochrane Qualitative and Implementation Methods Group guidance series—Paper 6: Reporting guidelines for qualitative, implementation, and process evaluation evidence syntheses. Journal of Clinical Epidemiology, 97, pp.79-85.
[9] Ganti, A. (2021). Central Limit Theorem (CLT). [web log post] Retrieved from: https://www.investopedia.com/terms/c/central_limit_.
[10] https://wordbueno.com › word › multisphere
[11] Izumi, T., Shaw, R., Djalante, R., Ishiwatari, M. and Komino, T., 2019. Disaster risk reduction and innovations. Progress in Disaster Science, 2, p.100033.
[12] Kahan, B. & Consulting, K. 2008. Excerpts from review of evaluation frameworks. Regina: Saskatchewan Ministry of Education.
[13] LeClair, D. 2015. The evolution of assessment and its forces of change. https://www.aacsb.edu/blog/2015/september/revolution-of-assessment-and-its-forces-of-change. Date of access:12 Jan. 2022.
[14] Lenzen, S.A., Daniëls, R., van Bokhoven, M.A., van der Weijden, T. and Beurskens, A., 2018. What makes it so difficult for nurses to coach patients in shared decision making? A process evaluation. International journal of nursing studies, 80, pp.1-11.
[15] Li, S.T.T., Klein, M. D., Balmer, D.F and, Gusic, M.E. 2020. Scholarly evaluation of curricula and educational programs: using a systematic approach to produce publishable scholarship. AcademicPediatrics.
[16] Liu, S., 2020. Bioprocess engineering: kinetics, sustainability, and reactor design. Elsevier.
[17] Longman Dictionary of Contemporary English. 2020. Approach. https://www.collinsdictionary.com/dictionary/english/approach. Date of access:7Sep.2020.
[18] M. Melvin and T. H Gary, “Logic models and content analyses for the explication of evaluation theories: The case of emergent realist evaluation,” Evaluation and Program Planning, 38(2013):74-76, 2012.
[19] Mathimani, T., Baldinelli, A., Rajendran, K., Prabakar, D., Matheswaran, M., van Leeuwen, R.P. and Pugazhendhi, A., 2019. Review on cultivation and thermochemical conversion of microalgae to fuels and chemicals: process evaluation and knowledge gaps. Journal of cleaner production, 208, pp.1053-1064.
[20] MBA Skool Team. 2019. Outcome Evaluation Meaning, Importance, Process & Example. https://www.mbaskool.com/business-concepts/human-resources-hr-terms/17932-outcome- evaluation.html Date accessed: Jan, 4, 2022.
[21] Mingchu, L and Lion, D 2005. Mixed methods design for an objective – based evaluation of a magnet school assistance project, Evaluation and Program Planning, 28, pp.109 -118.
[22] Ngwenya, S. (2021). Assessment processes and principles related to Food Security that Zimbabwe can rely on for insight. International Journal of Scientific Research and Management, 9(12), 852–862. https://doi.org/10.18535/ijsrm/v9i12.sh01
[23] OECD (Organisation for Economic Cooperation and Development). 2007. Annual report Paris: OECD www.oecd.org. Date of access:26 Sep. 2021.
[24] Patel, M., & Patel, N. 2019. Exploring Research Methodology: Review Article. International Journal of Research and Review, 6(3), 48-55.
[25] PMI (Program Management Institute). 2017. The Standard for Program Management, Project Management Institute Inc., Pennsylvania
[26] Randall, R., Nielsen, K. and Houdmont, J., 2019. Process evaluation for stressor reduction interventions in sport. Journal of Applied Sport Psychology, 31(1), pp.47-64.
[27] Sayce, K. & Norrish, P. 2006. Perceptions and practice: an anthology of impact assessment experiences. AJ Wageningen: Technical Centre for Agricultural and Rural Cooperation CTA.
[28] Scriven, D. 1991. Evaluation Thesaurus, 4th edi. Newbury Park, CA: Sage.
[29] Terrell, S.R. 2012. Mixed-methods research methodologies. The qualitative report, 17(1), 254-280. https://nsuworks.nova.edu/tqr/vol17/iss1/14 Date of access: 21 Sep. 2019.
[30] UNAIDS (United Nations Programme on HIV/AIDS). 2010. An introduction to indicators. Geneva UNAIDS
[31] USAID (United States Agency for International Development). 2016. Maize production and marketing in Zimbabwe: policies for a high growth strategy. USAID strategic economic research and analysis. Zimbabwe (sera) program, Nathan Associates Inc.
[32] Wisner, B., Gaillard, J.C. and Kelman, I. eds., 2012. Handbook of hazards and disaster risk reduction and management. Routledge.
[33] White, H., 2009. Theory-based impact evaluation: principles and practice. Journal of development effectiveness, 1(3):271-284.
[34] Yarbrough, D.B., 2017. Developing the program evaluation utility standards: Scholarly foundations and collaborative processes. Canadian Journal of Program Evaluation, 31(3).
Sifelani Ngwenya “A multi-sphere project assessment framework for livelihood projects in Zimbabwe” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-5, pp.07-14 May 2022 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/volume-7-issue-5/07-14.pdf
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Analysis of School Population Growth and Educational Infrastructures/Facilities in Makurdi Town, Benue State
Joseph Enefu; Godwin Kwanga; James Ikyernum; Godwin Echer Amerwua; Augustine Tarlumun Ahile; John Iorhemen Ajo; Zauka Solomon Aondoaver; Disha Terseer and Anita Onyeche Makyur- May 2022 Page No.: 15-21
The study examined the growth in school population and educational infrastructures/facilities in Makurdi Local Government Area of Benue State. The specific objectives of the study were to identify the educational institutions and facilities in Makurdi town and to examine the growth in school population and its pressure on educational infrastructures/facilities in Makurdi Town. The study population include secondary schools and its facilities, teachers and students. The research studied 5 Secondary Schools selected via simple random sampling technique. The research data were collected through inventory/measurement of school infrastructures/facilities. Data were analysed and presented via frequency, percentage, ratios and tables. The result shows that most of the schools did not experienced increased in school population growth between the year 2009 and 2019. Most of the schools did not exceed the UBEC, 2010 recommended standard (1440) pupils per school in an urban area. No school exceeded the standard limit of student/teacher ratio (35-40) pupils set by NPE (2004) and UBEC (2010). Majority of the schools met the standard requirement of 40 pupils per class. Only few schools failed to meet the standard classroom size requirement (56.0M2) recommended by UBEC, 2010. The schools also meet the individual students/space requirement (1.4M2) set by UBEC, 2010 and NPE, 2004. Only three schools meet the standard library requirement (120.0M2) for 40 pupils. The schools did not meet the standard requirement for computer laboratory (140M2) set by UBEC, 2010. Most of the schools did not meet the standard space requirement (3.5M2) for each pupil set by UBEC, 2010. None of the schools meet the physics, chemistry and biology laboratory standard requirement (140.0M2) and individual space requirement (3.5M2) set by UBEC, 2010. All the schools have various sport facilities. The schools have access water but did not meet the UBEC (2010) requirement for urban schools while toilet facilities were grossly inadequate. Although some of the schools did not meet all the UBEC (2010) and NPE (2004) standard requirement for schools in urban areas but the current population in all the schools have no serious implication on the facilities for now. The study recommend that all school owners in Makurdi town should adhere strictly to the NPE (2004) and UBEC (2010) requirement for standard secondary school in urban areas.
Page(s): 15-21 Date of Publication: 12 June 2022
Joseph Enefu
Department of Geography, Benue State University, Makurdi, Nigeria
Godwin Kwanga
Department of Geography, Benue State University, Makurdi, Nigeria
James Ikyernum
Department of Geography, Benue State University, Makurdi, Nigeria
Godwin Echer Amerwua
The Nigerian Police, Zone 4, Makurdi-Benue State.
Augustine Tarlumun Ahile
Department of Works and Housing (Survey Section) Vandeikya L.G.A
John Iorhemen Ajo
Department of Quality Assurance, Benue State Ministry of Education (Science and Technology)
Zauka Solomon Aondoaver
Benue State Community and Social development Agency, Makurdi
Disha Terseer
Department of Geography, Benue State University, Makurdi, Nigeria
Anita Onyeche Makyur
Department of Hospitality and Tourism Management, Federal University, Wukari-Taraba State
[1]. Abdulrahaman, S (2013). Population Growth and Food Security in Nigeria (2010-2012). Arabian Journal of Business and Management Review,1(3):41-53
[2]. Adedeji, S. O (1998). The Relationship between Resource Utilization and Academic Performance in Vocational Education in Osun State Secondary Schools. An unpublished Ph.D Thesis, Department of Vocational Education, University of Ibadan, Ibadan-Nigeria.
[3]. Benue State Ministry of Lands and Survey (2019). Makurdi Town Showing the Selected Schools. Ministry of Lands and Survey, Makurdi.
[4]. Chandan, J. S (1999). Management Theory and Practice. New Delhi: Vikas Publishing House PUT Ltd.
[5]. Ekanem, I (1972). A Critical Appraisal of 1963 Census. Benin City: Ethiope Publishing Corporation.
[6]. Federal Ministry of Education (2019). Nigeria Digest of Education Statistics. Abuja: Federal Ministry of Education.
[7]. Federal Ministry of Education (2016). Nigeria Digest of Education Statistics 2011-2016. Abuja: Federal Ministry of Education. Retrieved on 30/07/2019 from http://education.gov.ng/nigeria-digest-of-education-statistics/#efbe91d9f8098dcf7
[8]. Hallack, J (1990). Investing in the Future: Setting Educational Priorities in the Developing World. Paris 1 TEP and Pergonion Press.
[9]. Lyam, A. A (2005). “The Benue Environment in the Twentieth Century”. In Lyam, A. A., Ochefu, A. Y., Sambe, A. j., and Adejo, M. A (eds). Benue State in Perspective. Makurdi: Aboki Publishers.
[10]. NPC (1998).1991 Population and Housing Census: Benue State Final Results. Abuja, Nigeria: National Population Commission.
[11]. NPC (2009). 2006 Population and Housing Table. Benue State Priority Tables Volume 1. Abuja, Nigeria: National Population Commission.
[12]. NPE (2004). National Policy on Education 2004.4thedt. Abuja: Federal Republic of Nigeria.
[13]. Owoeye, J. S and Yara, P. O (2011). School Facilities and Academic Achievement of Secondary School Agricultural Science in Ekiti State, Nigeria. Asian Social Science, 7(7):64-74
[14]. PRB (2015). World Population Data 2015. Retrieved on 24/06/2019 from www.prb.org/2015-world-population-data-sheet
[15]. Shah, J. and Inamullah, M. (2012). The Impact of Overcrowded Classroom on the Academic Performance of the Students at Secondary School Level. International Journal of Research in Commerce, Economics and Management, 2(6):2231-4245
[16]. Tser, A (2013). The Dynamics of Benue State Population. Makurdi: Micro Teachers and Associates.
[17]. UBEC (2010) Minimum Standard for Basic Education in Nigeria. Abuja: Universal Basic Education Commission.
[18]. Wood, J. (2011). Malthus, Famine, Disease and World Population. Retrieved on 19/01/2013 from http://www.thenevadaview.com/2264/malthus-famine-disease-andworldpopulation/html.
[19]. Worldometer (2021). Current World Population. Retrieved
on 06/06/2021 from http://worldometers.info/world-population
Joseph Enefu; Godwin Kwanga; James Ikyernum; Godwin Echer Amerwua; Augustine Tarlumun Ahile; John Iorhemen Ajo; Zauka Solomon Aondoaver; Disha Terseer and Anita Onyeche Makyur “Analysis of School Population Growth and Educational Infrastructures/Facilities in Makurdi Town, Benue State” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-5, pp.15-21 May 2022 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/volume-7-issue-5/15-21.pdf
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HIC-DEEP: A Hierarchical Clustered Deep Learning Model for Face Mask Detection
Olugbenga S. Olukumoro, Folurera A. Ajayi, Adedeji A. Adebayo, Al-Amin B. Usman, Femi Johnson- May 2022 Page No.: 22-28
The use of face masks is apparently not strange in these present days as conceptualized in the past due to the emergence of the Pandemic Covid-19 Corona virus. As part of the non-clinical preventive measures for the spread of this virus is the prescription and proper usage of face mask by the World health organization (WHO). In lieu of this, heads of organizations, directors of industries and individuals have adopted the “No facemask, no entry” policy in varieties of designs placed at their door posts. The state of the arts technologies has also been developed to help detect face mask non-compliant users. Whereas, the use of non-supervised machine learning approach for classifying and detecting Covid-19 facemask compliant users is not widespread. In this paper, HIC-DEEP (an un-supervised machine learning) model is proposed using a pre-trained InceptionV3 network for Kaggle database Image features vector extraction for subsequent computations of Euclidian, Spearman, and Pearson distance matrixes. The Hierarchical clustering method is then activated to identify face mask wearing faces from defiant faces. The distance algorithms all returned a perfect precision rate of 100% for the identification of faces with no face masks while an accuracy of 60%, 78% and 85% are achieved by Spearman, Pearson and Euclidian respectively for the cluster with full face mask compliance. However, the Euclidian distance algorithm returned the best overall accuracy in terms of the distance matrix with data points grouped along close proximities with unique clusters
Page(s): 22-28 Date of Publication: 12 June 2022
Olugbenga S. Olukumoro
Computer Technology Department, Yaba College of Technology, Yaba, Lagos, Nigeria
Folurera A. Ajayi
Computer Technology Department, Yaba College of Technology, Yaba, Lagos, Nigeria
Adedeji A. Adebayo
Computer Technology Department, Yaba College of Technology, Yaba, Lagos, Nigeria
Al-Amin B. Usman
Computer Technology Department, Yaba College of Technology, Yaba, Lagos, Nigeria
Femi Johnson
Computer Science Department, Federal University of Agriculture, Abeokuta, Ogun, Nigeria
[1]. Bussan, D.D.; Snaychuk, L.; Bartzas, G.; Douvris, C., (2021). Quantification of trace elements in surgical and KN95 face masks widely used during the SARS- COVID-19 pandemic. Sci. Total Environ., 814, 151924.
[2]. Chen, T.; Kornblith, S.; Norouzi, M.; Hinton, G. A simple framework for contrastive learning of visual representations. In Proceedings of the 37th International Conference on Machine Learning, Vieena, Austria, 12–18 July 2020; pp. 1597–1607.
[3]. Chowdary, G. J., Punn, N. S., Sonbhadra, S. K., & Agarwal, S. (2020). Face Mask Detection Using Transfer Learning of InceptionV3. International Conference on Big Data Analytics (pp. 81-90). Springer.
[4]. De Sio, L.; Ding, B.; Focsan, M.; Kogermann, K.; Pascoal-Faria, P.; Petronella, F.; Mitchell, G.; Zussman, E.; Pierini, F. Personalized Reusable Face Masks with Smart Nano-Assisted Destruction of Pathogens for COVID-19: A Visionary Road. Chem. A Eur. J. 2020, 27, 6112–6130.
[5]. Fan, X., & Jiang, M. (2020). RetinaFaceMask: A Single Stage Face Mask Detector.arXiv:2005.03950v3, PP. 1-6.
[6]. Ieamsaard, J., Charoensook, S. N., & Yammen, S. (2021). Deep learning-based face mask detection using yoloV5. 2021, 9th International Electrical Engineering Congress (iEECON) , pp. 428-431). IEEE.
[7]. Jan, B.; Farman, H.; Khan, M.; Imran, M.; Islam, I.U.; Ahmad, A.; Ali, S.; Jeon, G. Deep learning in big data analytics: A comparative study. Comput. Electr. Eng. 2019, 75, 275–287
[8]. Jiang, M.; Fan, X.; Yan, H. Retinamask: A face mask detector. arXiv 2020, arXiv:2005.03950.
[9]. Latif, S.; Usman, M.; Manzoor, S.; Iqbal,W.; Qadir, J.; Tyson, G.; Castro, I.; Razi, A.; Boulos, M.N.K.;Weller, A. Leveraging data science to combat COVID-19: A comprehensive review. IEEE Trans. Artif. Intell. 2020, 1, 85–103.
[10]. Loey, M., Manogaran, G., N.Taha, M. H., & M.Khalifa, N. E. (2021). A hybrid deep transfer learning model with machine learning methods for face mask detection in the era of the COVID-19 pandemic. Elsevier Journal of Measurement, 1-11.
[11]. Nagrath, P., Jain, R., Madan, A., Arora, R., Kataria, P., & Hemanth, J. (2021). SSDMNV2: A real time DNN-based face mask detection system using single shot multibox detector and MobileNetV2. Sustainable Cities and Society.
[12]. Olaleye, T., Abayomi-Alli, A., Adesemowo, K., Arogundade, O. T., Misra, S., & Kose, U. (2022). SCLAVOEM: hyper parameter optimization approach to predictive modelling of COVID-19 infodemic tweets using smote and classifier vote ensemble. Springer Berlin Heidelberg, 1-20.
[13]. Peishu Wu, Han Li, Nianyin Zeng, Fengping Li,: FMD-Yolo (2022): An efficient face mask detection method for COVID-19 prevention and control in public, Image and Vision Computing, Volume 117, 104341,ISSN 0262-8856,https://doi.org/10.1016/j.imavis.2021.104341.
[14]. Qin, B.; Li, D. Identifying facemask-wearing condition using image super-resolution with classification network to prevent COVID-19. Sensors 2020, 20, 5236
[15]. Shahzad, Y.; Javed, H.; Farman, H.; Ahmad, J.; Jan, B.; Nassani, A.A (2021). Optimized Predictive Framework for Healthcare through Deep Learning. Comput. Mater. Contin, 67, 2463–2480.
[16]. Suresh, K., Palangappa, M., & Bhuvan, S. (2021). Face Mask Detection by using Optimistic Convolutional Neural Network. 2021 6th International Conference on Inventive Computation Technologies (ICICT) (pp. 1084-1089). IEEE.
[17]. Yar, H.; Abbas, N.; Sadad, T.; Iqbal, S.( 2021). Lung Nodule Detection and Classification using 2D and 3D Convolution Neural Networks (CNNs). Artif. Intell. Internet Things 2021, 365–386.
[18]. Yadav, S. Deep learning based safe social distancing and face mask detection in public areas for COVID-19 safety guidelines adherence. Int. J. Res. Appl. Sci. Eng. Technol. 2020, 8, 1368–1375.
[19]. Zhu, N.; Zhang, D.; Wang,W.; Li, X.; Yang, B.; Song, J.; Zhao, X.; Huang, B.; Shi,W.; Lu, R. A novel coronavirus from patients with pneumonia in China, 2019. N. Engl. J. Med. 2020, 382, 727–733.
Olugbenga S. Olukumoro, Folurera A. Ajayi, Adedeji A. Adebayo, Al-Amin B. Usman, Femi Johnson “HIC-DEEP: A Hierarchical Clustered Deep Learning Model for Face Mask Detection” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-5, pp.22-28 May 2022 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/volume-7-issue-5/22-28.pdf
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Probability of Ticks Infestation in Goats Sold in Okitipupa Main Market, In Southern Part of Ondo State
Bagbe, A. S, Bagbe, A., Arosoye, A. S. and Owolabi, D. O.- May 2022 Page No.: 29-34
Ticks are the most important ectoparasites of livestock in tropical and sub-tropical areas. They are responsible for severe economic losses both through direct effects of blood sucking and indirectly as vectors of pathogens and toxins. Feeding by large numbers of ticks causes reduction in live weight gain and anaemia among domestic animals. An epidemiological study was carried out on ticks of goat in Okitipupa main market in Southern part of Ondo State from September, 2021 to November, 2021. Goats were sampled randomly. Collected ticks species were preserved in 70% ethanol to be counted and morphologically identified to the species level. A total of eighty (80) goats were examined, thirty-five (35) of the goats examined were infested out of which (20) female and (15) male were infested. One hundred and eleven (111) species which were largely Amblyomma variegatum, the most predominant hard tick species was identified. The main attachment/predilection sites of tick detected were head (33), neck (9), back (13), abdomen (39) and leg (17) which is significant to the tick infestation. The infestation rate of tick was insignificantly different between sex, female (46.5%) and male (40.5%). Therefore, to reduce high prevalence of tick, proper and planned control measure by creating awareness about the importance and control of ectoparasites for farmers is needed.
Page(s): 29-34 Date of Publication: 14 June 2022
Bagbe, A. S
Department of Biological Sciences, School of Science, Olusegun Agagu University of Science and Technology, Okitipupa. Ondo State, Nigeria
Bagbe, A.
Department of Mathematical Sciences, Statistics unit, Olusegun Agagu University of Science and Technology, Okitipupa, Ondo State, Nigeria
Owolabi, D. O.
Department of Mathematical Sciences, Statistics unit, Olusegun Agagu University of Science and Technology, Okitipupa, Ondo State, Nigeria
[1] Abebe R, Tatek M, Megersa B, Sheferaw D (2011). Prevalence of Small Ruminant Ectoparasites and Associated Risk Factors in Selected Districts of Tigray Region, Ethiopia. Global Veterinaria 7 (5), 433-437.
[2] Adediminiyi B, George J, Otobo S, Ogunleye J (1992). Louse and mite infestations in domestic animals in Northern Nigeria. Tropical Animal Health and Production 24(2): 121-4.
[3] Adu I F (2000). Sheep farming in Nigeria. Net. Anim. Prod. Res. Inst. Bull. 3:19-46.
[4] Allan, B. F., Keesing, F. and Ostfeld, R. S. (2003). Effect of forest fragmentation on Lyme disease risk. Conservation Biology, 17(1): 267 – 272.
[5] Amare, S., Asfaw, Y. and Tolossa, Y. H. (2014). Ectoparasites of Sheep and Goats in North-West Amhara Regional State, Ethiopia. Ethiopian Veterinary Journal, 17(1), 55-67.
[6] Amuta, E. U., Houmsou, R. S., and Ogubiela, M. (2010). Tick infestation of dogs in Makurdi Metropolis, Benue State Nigeria. The International Journal of Veterinary Medicine. 7 (2): 12 -17.
[7] Anaeto, M.B., Tayo, G.I, Chioma, G.O and Afolabi, A. A. (2009) Comparative study of Albendazole and C.papaya seed on the control of gastrointestinal nematodes in goats. Journal of life and physical sciences.3(1): 25-28.
[8] Ayoade, J. A. (2005). Problems and prospect of small ruminant production in Benue state proceeding of the Animal conference of Nigerian Society for Animal production.
[9] Barker, S. C. and Murrell, A. (2004). Systematics and evolution of ticks with a list of valid genus and species names. Journal of Parasitology, 129, 15-36.
[10] Bayu, K. (2005). Country paper Ethiopia. Proceedings of Regional Workshop on preslaughter defects of hides/skins and intervention options in East Africa: Harnessingthe Leather Industry to Benefit the Poor, April, 18-20 Addis Ababa, Ethiopia, pp. 71-84.
[11] Bowman, D. D. (1999). Georges’ Parasitology for Veterinarians, 7th edition, W. B. Saunders Company, 29-35, 38-39, 46-53, 61-62, 294.
[12] Bram, R.A. (1983). Tick-borne livestock diseases and their vectors. The global problem. Wld. Anim. Rev., (FAO). 36, 1-5.
[13] Canga, A. G., Sahagu´n Prieto, A. M., Lie´bana, M. J., Martı´nez, N. F., Vega, M. S. and Vieitez, J. J. G. (2009). The pharmacokinetics and metabolism of Ivermectin in domestic animal species. The Vet. Journal 179, 25-37.
[14] Chaminuka, P., Udo, H. M. J., Eilers, K. C. H. A. M. and Zijpp, A. (2014). Livelihood roles of cattle and prospects for alternative land uses at the Wildlife/livestock interface in South Africa. Land Use Policy. 38: 80 – 90.
[15] Clark, A. C. and R. B. Milne. (2003). Ectoparasite awareness in sheep, SAC Veterinary Science Division, Disease Surveillance Centre, Janetstown, Thurso, Caithness KW14 7XF, UK. Veterinary Record. 152(9), 271-272.
[16] Colebrook, E and Wall, R. (2004). Ectoparasites of livestock in Europe and the Mediterranean region. Vet. Parasitol. 120, 251-274.
[17] Cumming, G. S. (1998). Host preference in African ticks (Acari: Ixodidae): a quantitative data set. B. Entomol. Res. 88, 379-406
[18] Dipeolu, O.O. (1975). Survey of blood parasite in domestic animals in Northern Nigeria. Historical review (1923 – 1966). Trop. Anim. Hlth. Prod. 2: 49 – 52.
[19] Drummond, R.O. (1983). Tick-borne livestock diseases and their vectors. Chemical control of ticks. Wld. Anim. Rev., (FAO). 36, 28-33.
[20] El Hakim, A. E., Shahein, Y. E., Aboelella, A. M. K. and Selim, M. E. (2007). Purification and Characterization of two larval glycoproteins from Cattle Tick Boophilus annulatus. Journal of Veterinary Science, 8(2): 175-180.14, 121-136.
[21] El-Kammah, K. M., Oyoun, L. M., El-Kady, G. A., Shafy, S. A. (2001). Investigation on blood parasites in livestock infested with Argasid and Ixodid ticks. Egypt Journal of Parasitololgy, 31 (2):104-15.
[22] Elsaid, M., El-Arifi, O. and El-Buni, A. A. (2013). The Prevalence of Ectoparasites on Sheep and Goats at EL Khoms Region–Libya. Journal of American Science, 9(10), 359-363.
[23] Fabiyi, J.P. (2007). Containment of livestock parasites with emphasis on ticks. Nigeria Australia collaborative Agricultural research. Aciar proceeding series No.4 pp 67-69.
[24] Feder Jr, H. M., Johnson, B. J., O’Connell, S., Shapiro, E. D., Steere, A. C. and Wormser, G. P. (2007). A critical appraisal of “chronic Lyme disease”. New England Journal of Medicine, 357(14): 1422 – 1430.
[25] Fuehrer, H. P., Igel, P., Treiber, M., Baumann, T. A., Riedl, J., Swoboda. P. and Noedl, H. (2012). Ectoparasites of livestock, dogs, and wild rodents in the Chittagong Hill Tracts in Southeastern Bangladesh. Parasitology Research, 111(4): 1867 – 1870.
[26] Hall, C. M. (2006). A Survey on Ectoparasites on Domestic fowls and Guinea fowls in Gongonia, Navrongo. University for Develoment Studies, Navrongo, Ghana: p. 65.
[27] Hassan, M. M., Hoque, M. A., Islam, S. K. M. A., Khan, S. A., Roy, K. and Banu, Q. (2011). A prevalence of parasites in black bengal goats in Chittagong, Bangladesh. International Journal of Livestock Production, 2(4), 40-44.
[28] Ibe, D. C., Okonofua, C. and Akwari, A. A. (2012). Comparative prevalence and mean intensities of ectoparasites of goats from two Nigerian regions and their epidemiological implications. Transnational Journal of Science and Technology, 2 (10), 75-85.
[29] Iwuala, M. O. and Okpala, J. (1978). Studies on the ectoparasitic fauna of Nigerian livestock II: Seasonal infestation rates. Bulletin of Health and Production in Africa (4): 351-358.
[30] James-Rugu, N. N. and Iwuala, M. O. E. (2002). Ectoparasites of some domestic animals in Jos Plateau, Nigeria Science Forum 5 (1):149-156.
[31] Kirby, C. S. (2007). Tick Management Handbook. An integrated guide for homeowners, pest control operators, and public health officials for the prevention of tick associated disease. The Connecticut Agricultural Experiment Station, pp. 4-8.
[32] Klompen, J. S. H., Black, W. C., Keirans, J. E. and Oliver Jr, J. H. (1996). Evolution of ticks. Annual Review of Entomology, 41(1), 141-161.
[33] Knipling, E. F., and Steeman, C. D. (2000). Feasibility of controlling Ixodes capularis Ticks (Acaric: Ixididae), the vector Lyme disease by parasitoid Augmentation. Journal of Medical Entomology, (37):55.
[34] McKellar, Q.A. and Benchaoui, H.A. (1996). Avermectins and milbemycins. Journal of Veterinary Pharmaceutical Therapy, 19, 331-351.
[35] Mulugeta, Y., Hailu Y., and Ashenafi, H. (2010). Ectoparasites of small ruminants in three selected agro-ecological sites of Tigray Region, Ethiopia. Trop. Anim. Health Prod., 42, 1219-1224.
[36] Olabode, H.O.K., Ejiofor, C.E and Agbede, R.I.S. (2010). Survey of Ectoparasite and Ectoparasitic Conditions, Their Prediliction Sites on Goats in Bukuru Market, Plateau State. Nigerian Journal of Parasitology, 31(2): 90-92.
[37] Padjung, R. and Natsir, A. (2005). Preliminary survey on Beef/Bali cattle production in South Sulawesi. Report prepared for ACIAR, 15 pp.
[38] Parola, P. and Raoult, D. (2001). Ticks and tick-borne bacterial human diseases, an emerging infectious threat. Clin. Inf. Dis., 32: 897-928.
[39] Parola, P., Inukoma, H., Camicas, J. L., Bronqui, P., and Raoult, D. (2001). Detection and identification of spotted fever group Rickettiae and Ehrlichae in Africa ticks. Emerging Infectious Diseases. 7(6): 10114-7.
[40] Radostits, O.M., Gay, C.C., Blood, D.C. and Hinchcliff, K.W. (2003). Veterinary Medicine-A textbook of the diseases of cattle, sheep, pigs, goats and horses. 9th edition Book Power.
[41] Rechav, Y. and Nuttall, P. A. (2000). The effects of male ticks on the feeding performance of immature stages of Rhipcephlus sanquineus and Amblylomma americanum (Acari: Ixodidae). Experimental Applied Acarinalogy. 24: 569-578.
[42] Sansoucy, R. (1995). Livestock – A driving force for food security and sustainable development. World, 3074(5389): 1035.
[43] Sarkar, M., Rahman, S. A., Sarker, B. K., Anisuzzaman, A., Begum, N., and Mondal, M. M. H. (2010). Epidemiology and pathology of ectoparasitic infestations in Black Bengal goats in Gaibandha and Mymensingh districts of Bangladesh. Bangladesh Journal of Veterinary Medicine, 8(1), 41-50.
[44] Schiere, J. B., Ibrahim, M. N. M. and Van Keulen, H. (2002). The role of livestock for sustainability in mixed farming: Criteria and scenario studies under varying resource allocation. Agriculture, Ecosystems and Environment, 90(2): 139 – 153.
[45] Sertse, T. and Wossene, A. (2007b). Effect of ectoparasites on quality of pickled skins and their impact on the tanning industry in Amhara Regional State, Ethiopia. Small Rumin. Res., 69, 55-61.
[46] Smyth, J. D. (1994). Introduction to animal parasitology. Cambridge University Press.
[47] Solomon, T. and Mallew, M. (2001). Dengue and other emerging flaviviruses. Journal of Infectious Diseases. 42 (2): 104-105.
[48] Soneshine, D. E. (1991). Biology of ticks. Oxford University Press, New York, 1: 1-449.
[49] Soulsby, E.J.I. (1978) Helminthes, Arthropods, and Protozoa of Domesticated Animals 7th edition. Bailliere, Jindall and Casse Ltd London pp 450-531150-156
[50] Soulsby, E. J. L. (1986). Healminths, Arthropods Protozoan of domesticated Animals. 7th Edition London, U. K. Bailliere Tindal. pp 456-475
[51] Stachurski, F. and Lancelot, R. (2006). Footbath acaricide treatment to control cattle infestation by the tick Amblyomma variegatum. Medical Veterinary Entomology 20 (4):402 – 412
[52] Steel, J. W. (1993). Pharmacokinetics and metabolism of avermectins in livestock. Vet. Parasitol. 48, 45-47.
[53] Steelman, C. D. (1976). Effects of external and internal arthropod parasites on domestic livestock production. Annu. Rev. Entomol., 21, 155-178.
[54] Teasdale, J. D., Segal, Z. V., Williams, J. M. G., Ridgeway, V. A., Soulsby, J. M., and Lau, M. A. (2000). Prevention of relapse/recurrence in major depression by mindfulness-based cognitive therapy. Journal of consulting and clinical psychology, 68(4), 615.
[55] Tefera, S. and Wessene, A. (2007a). A study on ectoparasites of sheep and goats in eastern part of Amhara Region, northeast Ethiopia. Small Rumin. Res., 69, 62-67.
[56] Thornton, P. K. (2010). Livestock production: Recent trends, future prospects. Philos. Trans. R. Soc. B. Biol. Sci. 365: 2853 – 2867.
[57] Walker, A. R., Bouattour, A., Camicas, J. L., Estrada-Pena, A., Horak, I.G., Latif, A. A., Pegram, K.G. and Preston, P. M. (2007). Ticks of domestic animals in Africa: A guide to identification of species. Bioscience Reports. 221pp
[58] Wall, R. (2007). Ectoparasites: Future challenges in a changing World. Elsevier B. V., Veterinary Parasitology. 148: 62 – 74.
[59] Wall, R. and Shearer, D. (2001). Veterinary Ectoparasites: Biology, Pathology and Control. 2nd edition., Blackwell Science, 1-2, 27-31, 66, 76, 80-81, 149-150, 166-167, 172-177, 179-181.
[60] Wilson, M. L. (1990). Micro geographic distribution of immature ixodes Dammini ticks. Journal of medical and veterinary entomology. 4:15-151
[61] Yacob, H. T., Yalew, T. A. and Dinka, A. A. (2008). Part I: Ectoparasite prevalences in sheep and in goats in and around Wolaita Soddo, Southern Ethiopia. Revue de Médecine Vétérinaire, 159 (8-9).
[62] Zewdie, S. (2010). Control of External Parasites of Sheep and Goats. In Eds: Alemu Yami and R.C. Merkel Ethiopia Sheep and Goat Productivity Improvement Program, Technical Bulletin No. 41, 1-13.
Bagbe, A. S, Bagbe, A., Arosoye, A. S. and Owolabi, D. O. “Probability of Ticks Infestation in Goats Sold in Okitipupa Main Market, In Southern Part of Ondo State” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-5, pp.29-34 May 2022 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/volume-7-issue-5/29-34.pdf
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Cost-Effectiveness Analysis of Optimal Control Strategies for Malaria Transmission in Bubanza Province, Burundi
Venant Niyonkuru, Winifred Mutuku- May 2022 Page No.: 35-43
Malaria is a parasitic infection ranked among the leading causes of mortality and morbidity in Sub-Sahara African countries. If recommended interventions measures are well applied, malaria can be prevented and controlled. In many cases, the budget allocated to malaria prevention and treatment project is not enough, using malaria intervention measures properly will guarantee the reduction of infected population while the intervention costs is minimized. This saves the budget and produces the results in economical way. The aim of this article is to understand the cost so that decision makers are well informed when they determine budget allocated to malaria interventions. After ordering different possible strategies from the smallest to the highest, utilizing Incremental Cost-Effectiveness Ratio (ICER), we studied the Cost-effectiveness of each strategy. This study analyses the cost-effectiveness of all possible optimal control measures to identify which is the intervention strategy is going to save available resources and cost-effective. After analysis, this study shows that malaria can be minimized in Bubanza using preventive measures at the most cost effective way.
Page(s): 35-43 Date of Publication: 16 June 2022
Venant Niyonkuru
Department of Mathematics and Actuarial Science, Kenyatta University, P.O. Box 43844-00100 Nairobi, Kenya
Winifred Mutuku
Department of Mathematics and Actuarial Science, Kenyatta University, P.O. Box 43844-00100 Nairobi, Kenya
[1]. Abioye, A. I., Peter, O. J., Oguntolu, F. A., Adebisi, A. F., & Aminu, T. F. (2020). Global stability of seir-sei model of malaria transmission. Adv. Math., Sci. J, 9, 5305-5317.
[2]. Agusto, F. B., Marcus, N., & Okosun, K. O. (2012). Application of optimal control to the epidemiology of malaria.
[3]. Appiah, P. (2020). Optimal Strategy for Effective Control and Possible Eradication of Malaria (Doctoral dissertation, University of Cape Coast).
[4]. BAWA, M., YUSUF, I., & MAYAKI, Z.(2021). Controlling The Spread Of Malaria: A Mathematical Modelling Approach Sub-Sahara African Academic Research Publications.
[5]. Fleming, W. H., & Rishel, R. W. (2012). Deterministic and stochastic optimal control (Vol. 1). Springer Science & Business Media.
[6]. Guerra, C. A., Gikandi, P. W., Tatem, A. J., Noor, A. M., Smith, D. L., Hay, S. I., & Snow, R. W. (2008). The limits and intensity of Plasmodium falciparum transmission: implications for malaria control and elimination worldwide. PLoS medicine, 5(2), e38.
[7]. Hansen, K. S., Ndyomugyenyi, R., Magnussen, P., & Clarke, S. E. (2012). Cost-effectiveness analysis of three health interventions to prevent malaria in pregnancy in an area of low transmission in Uganda. International health, 4(1), 38-46.
[8]. La Salle, J. P. (1976). The stability of dynamical systems. Society for Industrial and Applied Mathematics.
[9]. Levin, H. M., & McEwan, P. J. (2000). Cost-effectiveness analysis: Methods and applications (Vol. 4). Sage.
[10]. Minisante.(2020). Annuare des statistiques. Retrieved 2021-07-09 from http//minisante.bi/donnees-sur-malaria-depuis-2000/
[11]. Mojeeb, A. L., Adu, I. K., & Yang, C. (2017). A simple seir mathematical model of malaria transmission. Asia Res J Math, 1-27.
[12]. Nkurunziza, H., Gebhardt, A., & Pilz, J. (2011). Geo-additive modelling of malaria in Burundi. Malaria Journal, 10(1), 1-7.
[13]. Ojo, M. M., & Akinpelu, F. O. (2017). Lyapunov functions and global properties of seir epidemic model. Int. J. Chem. Math. Phys, 1(1), 11-16.
[14]. Okosun, K. O., Rachid, O., & Marcus, N. (2013). Optimal control strategies and cost-effectiveness analysis of a malaria model. BioSystems, 111(2), 83-101.
[15]. Olaniyi, S., Okosun, K. O., Adesanya, S. O., & Areo, E. A. (2018). Global stability and optimal control analysis of malaria dynamics in the presence of human travelers. The Open Infectious Diseases Journal, 10(1).
[16]. Otieno, G., Koske, J. K., & Mutiso, J. M. (2016). Cost effectiveness analysis of optimal malaria control strategies in Kenya. Mathematics, 4(1), 14.
[17]. Pontryagin, L. S., Boltyanskii, V. G., Gamkrelidze, R. V., Mishchenko, E. F., Trirogoff, K. N., & Neustadt, L. W. (2018). LS Pontryagin Selected Works: The Mathematical Theory of Optimal Processes. Routledge.
[18]. Robinson, R. (1993). Cost-effectiveness analysis. British Medical Journal, 307(6907), 793-795.
[19]. Rodrigues, P., Silva, C. J., & Torres, D. F. (2014). Cost-effectiveness analysis of optimal control measures for tuberculosis. Bulletin of Mathematical Biology, 76(10), 2627-2645.
[20]. Shuai, Z., & van den Driessche, P. (2013). Global stability of infectious disease models using Lyapunov functions. SIAM Journal on Applied Mathematics, 73(4), 1513-1532.
[21]. Stuckey, E. M., Stevenson, J., Galactionova, K., Baidjoe, A. Y., Bousema, T., Odongo, W., & Chitnis, N. (2014). Modeling the cost effectiveness of malaria control interventions in the highlands of western Kenya. PloS one, 9(10), e107700.
[22]. Stuckey, E. M., Stevenson, J., Galactionova, K., Baidjoe, A. Y., Bousema, T., Odongo, W., & Chitnis, N. (2014). Modeling the cost effectiveness of malaria control interventions in the highlands of western Kenya. PloS one, 9(10), e107700.
[23]. UNDP (2020), Human Development Report 2020. Retrieved 2022-19- 02 from shorturl.at/iwEIL.
Venant Niyonkuru, Winifred Mutuku “Cost-Effectiveness Analysis of Optimal Control Strategies for Malaria Transmission in Bubanza Province, Burundi” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-5, pp.35-43 May 2022 DOI: https://dx.doi.org/10.51584/IJRIAS.2022.7501
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The Effect of Record-Keeping on Financial Performance of Small and Medium Scale Enterprises in Uganda in Lira City
Okello Apollo- May 2022 Page No.: 44-53
The study sought to examine the effect that Record-keeping could have on financial performance of SMEs in Lira city. The researcher used both descriptive and correlational design. The study adopted a quantitative approach. The researcher used simple random sampling in selecting 118 SMEs operators in the service sector that formed the sample size of the study. A structured questionnaire was used as the main instrument of quantitative data collection from the selected SMEs Operators. Completed questionnaires were edited, coded, and entered into and categorized into themes and analyzed using SPSS 20 for Windows. Bivariate analysis in form of Pearson’s product moment correlation was used to show the direction and strength of the relationship between each dimension of Record-keeping and financial performance. Regression analysis was also used to test the effect each construct of Record-keeping on financial performance. The study therefore concludes that Record-keeping has effect on financial performance of SMEs and recommends proper record filling, retention and retrieval in order to improve financial performance of SMEs
Page(s): 44-53 Date of Publication: 27 June 2022
Okello Apollo
Department of Accounting and Finance, Uganda Martyrs University P.O. Box 5498 Kampala (U)
[1]. Abioye, A. [1] Ademola, G. O., James, S., & Olore, I. (2012). The roles of record keeping in the survival and growth of small scale enterprises in Ijumu Local Government Area of Kogi State. Global Journal of Management and Business Research.
[2] Amin, M. (2005). Social Research Conception “Methodology and Analysis. Kampala: Makerere Printery.
[3] Amin, M. (2005). Social Science Research Conception: Methodology and Analysis . Kampala: Makerere University Printery.
[4] Crane, M. (1997). Record Keeping. Essential to Risk Management NCIS.
[5] Cronbach, L. (1946). Response sets and tests validating. Journal for Educational & Psychological Measurement, 475 – 494.
[6] Eton, M., Barige, G., Nyangomal, M., Mwosi, F., & Ogwal, B. (2018). Financial Literacy, Cash management and Business Growth in Kampala City Council Authority, Uganda. Economics,Commerce and Trade Management. An International Journal (ECTIJ).
[7] Eton, M., Uwonda, G., Mwosi, F., Ogwal, B., & Obote, D. (2019). Cash management and financial performance of Business Firms in Northern Uganda a case of Lira District. International Journal of Business Management and Technology.
[8] Fanen, A.-k., & Avanenge, F. (2020). Micro-Finance and Performance of Micro, Small and Medium Enterprises in Makurdi Metropolis. International Journal of Accounting and Finance.
[9] Kihamaiso, M., Kansiime, C., Asiimwe, B., & Paddy, M. (2018). The Effect of Financial Record Keeping on Financial Performance of Development Groups in Rural Areas of Western Uganda. International Journal of Economics and Finance, 136-145.
[10] Kizito. (2017). Working capital management, Service quality and financial performance of Hotels in Kampala. Kamapala.
[11] Kothari, C. R. (2009). Research Methodology. New Delhi: New Age International Publishing Ltd.
[12] McLeod, S. (2018). Questionaires. Retrieved from http://www.simplypsychology.org/maslow.html
[13] Muchira, B. W. (2012). Record Keeping and Growth of Micro and Small Enterprises. A Case Study Municipally in Kenya. Nairobi: Masters of Business Administration (thesis) of Kenyatta University.
[14] Mukhaye, D. (2020). Uganda Business Impact Survey. Impact of COVID-19 on formal sector small and medium enterprises. Kampala: The observatory of economic complexity. Unlocking Public and Private Finance for the poor.
[15] Mulajje, M. (2019). Working Capital Management and Financial Performance of Small and Medium Enterprises in Kampala Capital City Authority: A Case Study of Kawempe Division Urban Council. Kampala.
[16] Mutesigensi, D., Eton, M., Ebong, C., & Mwosi, F. (2017). Cash flow and survival of SMES in Arua District, West Nile Region Uganda. International Journal of Small Business and Entrepreneurship Research, 9-18.
[17] Nangih, E., Ofor, T., & Onuorah, V. (2020). Cash Flow Management and Financial Performance of Quoted Oil and Gas Firms in Nigeria. Journal of Accounting and Financial Management.
[18] Niwemutoni, S., Mulyungi, P., & Jaya, S. (2018). Effect of Cash Management Practices on Financial Performance of Small Medium Enterprises in Rwanda: case study of SMEs in Kicukiro District. International Journal of Management and Commerce Innovations .
[19] Nshemereirwe, S. (2018). Economic factors affecting the performance of Small and medium enterprises in Katwe, Kampala, Uganda. Kamapala: Uganda Management Institute.
[20] Onaolapo, A., & Adegbite, I. (2014). The Analysis of the Impact of Accounting Records Keeping on the Performance of Small Scale Enterprises. International Journal of Academic Research in Business and Social Sciences, .
[21] Onaolapo, A., & Adegbite, T. (2014). The Analysis of the impact of Accounting Records Keeping on the Performance of the Small Scale Enterprises. International Journal of Academic Research in Business and Social Sciences, 1-17.
[22] Ozatambgo, O. (2015). Financial Record Keeping In Religious Organizations: A Case Study of Catholic Church in Enugu Diocese.
[23] Pandy, D. (2019). Impact of Cash Management on Profitability in Small Manufacturing Organization. Silver Jubliee Issue PRAVAHA.
[24] Reed, R. (2010). Good Small Business Guide; How to Start and Grow Your Own Business. London: A & C Black publishers Ltd.
[25] Salamatu, A., & Muhammad, K. (2021). Exploring the Effect of Financial Record Keeping on Financial Performance of Tertiary Institutions in Yobe state. International Journal of Advances in Engineering and Management, 1607-1612.
[26] Sibongiseni, S. (2018). Cash-Flow Management Strategies in Small and Medium-Sized Occupational Health Enterprises. Walden Dissertation and Doctoral Studies.
[27] Ssekajugo, D., Tuyishime, E., & Kasenene, E. S. (2013). Performance of Public Institutions in Ngororero District, North Western Rwanda.
[28] Ssempala, R. (2019). Determinants of Growth of Micro, Small and Medium Enterprises (Msmes) in Developing Countries. Evidence from Rubaga Division, Kampala District Uganda. Kampala.
[29] UBoS. (2020). National Account Statistics and database. Kampala: Uganda Bureau of Statistics (UBoS) .
[30] UIA. (2020). Annual Report 2019-2020. Kampala: Uganda Investment Authority.
[31] Uwonda, G., & Okello, N. (2015). Cash Flow Management and Sustainability of Small Medium Enterprises (SMEs) in Northern Uganda. International Journal of Social Science and Economics Invention (IJSSEI).
[32] Wenzhen, M., & Nik-Intan, N. (2021). Short-Selling and Financial Performance of SMEs in China: The Mediating Role of CSR Performance. International Journal of Financial Studies, 2-16.
[33] Williams, P. (2008). Rethinking Decision Usefulness. Austria: Interdisciplinary Perspectives on Accounting Conference held in Innsbruck.
Okello Apollo “A multi-sphere project assessment framework for livelihood projects in Zimbabwe” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-5, pp.44-53 May 2022 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/volume-7-issue-5/44-53.pdf
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Micropropagation of Mokara Orchid by Temporary Immersion System Technique
Tran Van Minh- May 2022 Page No.: 54-58
Based young leaves of Mokara Leuen Berger Gold were used as cultured materials. Callus was initiated and increase biomass on medium of semisolid and liquid cultures: MS medium supplemented with CW (30%), sucrose (30 g/l), 2.4D (1 mg/l). Callus was used as materials for initiation and biomass propagation on medium: (1) MS medium supplemented with NAA (1 mg/l), B1 (5 mg/l), Adenin sulfate (10 mg/l), peptone (1 g/l), CW (10%), sucrose (30 g/l) (2) MS medium supplemented with 2.4D (1 mg/l), CW (30%), Adenin sulfate (10 mg/l), peptone (1 g/l), CW (10%), sucrose (30 g/l). Semisolid medium for callus cell regeneration and to induce multiple shoots were: MS medium supplemented with BA (0.5 mg/l), B1 (5 mg/l), Adenin sulfate (10 mg/l), peptone (1 g/l), CW (10%), sucrose (20 g/l). Multiple-shoots were propagated on MS medium supplemented with BA (0.5 mg/l), B1 (5 mg/l), CW (10%), sucrose (20 g/l). Propagation of multiple-shoots in TIS on MS medium supplemented with BA (0.5 mg/l), B1 (5 mg/l), CW (10%), sucrose (20 g/l). Interval culture time was optimum for 2 hours floating and 1 minute rising. Plantlets were induced roots on MS medium supplemented with NAA (1 mg/l), B1 (5 mg/l), CW (10%), sucrose (20 g/l). Experiments on callus formation and callus growth of mokara orchids both on semi-solid medium (agar) and liquid medium to create callus suspension, the best medium selected was: MS supplemented with 2.4D (1 mg/l), CW (30%), sucrose (30 g/l)
Page(s): 54-58 Date of Publication: 30 June 2022
Tran Van Minh
International University, Vietnam National University Ho Chi Minh City, Vietnam
[1]. Abioye, A. [1] Ducus J. P., Bollon H., Pettard V. (1993) Production of carrot somatic embryos in Bioreactor – Francereco. SA. 101 Avenue Gustave Eiffel, 38390 Notre dame D’Oe. France. Appl. Microbial Biotechol 39 :465-470.
[2] Ducus J. P., Lambot C., Pétiard V. (2000) Bioreactors for coffee mass propagation by somatic embryogenesis. International Journal of Plant Developmental Biology, Global Science Books; 2007.
[3] Matsumoto K., Kaizer A., Brandao C. (2009) Comparison of temporary and permanent immersion systems for the in vitro culture of banana. InfoMus. 11(2):36 – 37.
[4] Nguyễn Quốc Thiện (2009) Bước đầu ứng dụng thành công hệ thống nuôi cấy ngập chìm tạm thời trong nhân giống Lan Hồ Điệp lai – Phalaenopsis hydrid. Hội nghị CNSH phía nam 2009. Vietnam.
[5] Paek K. Y., Chakrabarty D., Hahn E. J. (2005) Application of bioreactor systems for large scale production of horticultural and medicinal plants. Plant Cell, Tissue, and Organ Culture 81: 287-300.
[6] Park S. Y., Murthy H. N., Peak K. Y. (2000) Mass multiplication of PLB’s using bioreactor system and subsequent plant regeneration in phalaenopsis – Research centerfor Development of Advanced Horticultural Technology, Chungbuk National University Cheongju 361-361 Korea. Plant cell, Tissue, and Organ culture 63:67-72.
Tran Van Minh “Micropropagation of Mokara Orchid by Temporary Immersion System Technique” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-5, pp.54-58 May 2022 DOI: https://dx.doi.org/10.51584/IJRIAS.2022.7502
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The Effect of The Combination of Precursor and Elicitors Enhance the Taxol Accumulation in Red Pine Cell Cultivation
Tran Van Minh- May 2022 Page No.: 59-64
The material introduced into the callus culture was the in vitro cloned red pine stem and leaves. Callus obtained through culture from leaves and stems were included in the study on proliferation on agar and liquid media. The suspension obtained after 45 days of culture was determined for biomass, used in proliferation culture, and studied taxol accumulation.
Media for taxus cell cloning was MS supplemented with 3 mg/l 2.4D, 3 mg/l NAA, 0.5 mg/l kinetin, 0.1 mg/l BA, 10% CW. Selections were carried out through 8 steps in the year of 2010 with interval cultivation time of 45 days/each step. It’s could improve the taxol accumulation via cell suspension cultures sourced from leaves 170.1 mg/gDW and stems 27.3 mg/gDW. Picloram was not effect on taxol accumulation.
On the basic media MS supplemented with 3 mg/l 2.4D, 3 mg/l NAA, 0.5 mg/l kinetin, 0.1 mg/l BA, 10% CW supplemented with precursor of 15mg/l phenyl alanine (PA) effects on the percentage of FW/DW (fresh weight/dried weight) was 9.815 and the taxol accumulation was 0.778%. The effects of elicitors supplemented to media with 10 mg/l methyl jasmonate (MJ) having 7.183 FW/DW and 0.273% taxol, 100 mg/l salysilic acid (SA) having 10.12 FW/DW and 0.094% taxol, 50mg/l chitosan having 10.09 FW/DW and 0.119% taxol, 5mg/l oligo-chitosan having 9.090 FW/DW and 0.778% taxol.
The effects of the combination of precursor and elicitors (15 mg/l phenyl alanine, 10 mg/l methyl jasmonate, 5 mg/l O-chitosan, 100 mg/l salysilic acid) enhance the taxol accumulation to 1.003% in comparison of separately as PA having 0.114% taxol, PA+Ochi having 0.542% taxol, PA+MJ+Ochi having 0.564%. Cell cloning from leaves (1.701%) had the taxol accumulation more than from stem (0.273%).
Page(s): 59-64 Date of Publication: 30 June 2022
Tran Van Minh
International University, Vietnam National University Ho Chi Minh City, Vietnam
[1]. Fett-Neto A. G., Melanson S. J., Nicholson S. A., Pennington J. J., Dicosmo F. (1994) Improved taxol yield by aromatic carboxylic acid and amino acid feeding to cell cultures of Taxus cuspidata. Biotechnology and Bioengineering 44:967–971.
[2]. Jaziri M., Zhiri A., Guo Y. D., Dupont J. P., Shimomura K., Hamada H., Vanhhaelen M., Homes J. (1996) Taxus, sp cell, tissue and organ cultures as alternative sources for taxoids production : a literature survey. Plant Cell, Tissue and Organ Culture 46:59-75.
[3]. Linden J. C., Phisalaphong M. (2000) Oligosaccharides potentiate methyl jasmonate-induced production of paclitaxel in Taxus Canadensis. Plant Science 158:41–51.
[4]. Ma R., Guo Y. D., Pulli S. (2003) Somatic embryogenesis and ferile green plant regeneration from suspension cell derived protoplasts of rye. Plant Cell Rep. 22: 320327
[5]. Srinivasan V., Ciddi V., Bringi V., Shuler M. L. (1996) Metabolic inhibitors, elicitors and precursors as tools for probing yield limitation in taxane production by Taxus chinensis cell cultures. Biotechnology Progress 12:457–465.
[6]. Wu J. Y., Wang C. G., Mei X. G. (2001) Stimulation of taxol production and excretion in Taxus spp. cell cultures by rare earth chemical lanthanum. Journal of Biotechnology 85:67–73.
[7]. Yanpaisan W., King N., Doran P. (1999) Flow cytometry of plant cells with applications in large scale bioprocessing. Biotechnol. Adv. 17: 3-27.
[8]. Yu L. J., Gao W., Hahn E. J., Paek K. Y. (2002) Jasmonic acid improves ginsenoids accumulation in adventitious roots culture of Pinax ginseng. Biochem. Eng. J 11: 211-215.
[9]. Yukimune Y., Tabata H., Higashi Y., Hara H. (1996) Methyl-jasmonate induced overproduction of paclitaxel and baccatin III in Taxus cell suspension cultures. Nature Biotechnology 14:1129–1132.
[10]. Zhang C. H., Mei X. G., Liu L., Yu L. G. (2000) Enhanced paclitaxel production induced by the combination of elicitors in cell suspension cultures of Taxus chinensis. Biotechnology Letters 22:1561–1564.
[11]. Zhong J. J., Wang S. J., Wang H. Q. (1997) A new centrifugal impeller reactor and its application to plant cell cultures. In: Horizon of Biochemical Engineering. The Society of Chemical Engineers, Japan, Tokyo 175–179.
Tran Van Minh “The Effect of The Combination of Precursor and Elicitors Enhance the Taxol Accumulation in Red Pine Cell Cultivation” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-5, pp.59-64 May 2022 DOI: https://dx.doi.org/10.51584/IJRIAS.2022.7503
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Nutritional and Anti-Nutritional Constituents of Cassava (Manihot Esculentus) Tubers and Leaves in Jos North Lga of Plateau State, Nigeria
Adeyanju, O, Adeyemi, A. E, Nimmyel. N. V., Dirikebamoh , S.T, Chukwu, C. S and Okafor, D.C- May 2022 Page No.: 65-67
This study was conducted to determine the nutritional and anti-nutritional content of cassava tubers and leaves in Jos North Local Government Area of Plateau state, Nigeria. Proximate analysis was determined by standard method for the percentage moisture content, ash content, crude protein, crude fibre and carbohydrate. Elemental analysis was determined using AAS and UV-Spectrophotometer. The anti-nutritional constituents determined includes; cyanogenic glycosides, trypsin inhibitor, phytic acid, tannins and oxalate. The tubesr have moisture content (10.57±0.2%), ash content (2.4±0.001%), crude protein (4.8±0.30%), crude fat (2.4±0.02%), crude fibre (3.9±0.08%), carbohydrate (80.54±2.40%), calcium (29.31±0.14%), potassium (8.94±0.04%), sodium (38.7±0.20%), magnesium (23.5±0.10%), phosphorus (0.150±0.004%), cyanogenic glycosides (2.06±0.008mg/L), trypsin inhibitor (4.28±0.03TUI/mg), phytate (31.02±0.34mg/100g), tannins (3.64±0.009mg/100g), oxalate (1.29±0.029g/100g) and the leaves showed moisture content (5.86±0.01%), ash content (1.6±0.01%), crude protein (5.6±0.08%), crude fat(1.8±0.04%), crudefibre (4.6±0.01%), carbohydrate (75.9±0.60%), calcium (38.65±1.35%), Potassium (13.10±0.12%), sodium (58.8±0.58%), magnesium (24.80±0.20%), phosphorus (0.280±0.001%), cyanogenic glycosides (7.31±0.098mg/L), trypsin inhibitor (10.74±0.012TUI/mg), phytate (58.47±0.403mg/100g), tannins (78.67±0.471mg/100g), oxalate (1.61±0.084g/100g).
Page(s): 65-67 Date of Publication: 30 June 2022
Adeyanju, O
Department of Chemistry, Faculty of Natural Sciences, University of Jos, Nigeria
Adeyemi, A. E
Department of Basic Sciences, Federal School of Medical Laboratory, Jos University Teaching Hospital (JUTH). Jos, Nigeria
Nimmyel. N. V.
Department of Chemical Sciences, the Federal Polytechnic, Bida, Nigeria
Dirikebamoh , S.T
Department of Chemistry, Faculty of Natural Sciences, University of Jos, Nigeria
Chukwu, C. S
Department of Chemistry, Faculty of Natural Sciences, University of Jos, Nigeria
Okafor,D.C
Department of Biochemistry, Faculty of Medical Sciences, University of Jos, Nigeria
[1] Adewusi, S.R.A, Bradbury, J.H. (1993). Carotenoids in cassava: Comparison of open-column and HPLC methods of analysis. J. Sci Food Agric 62: 375-383.
[2] Adeyanju. O and Emesi. I.C . (2019). Acetylation of Manihot esculentus crantz starch and its potential application in the pharmaceuticals. IOSR. Journal of Applied Chemistry.12(2) : 23 – 28.
[3] O. Adeyanju, E.S Egga, J. Plavec, E. A. Ewaoche, (2017). Nutritional evaluation, characterization and potential utilization of under-utilized indigenous livinstone potato(Plecthrantus esculentus) Journal of sustainable Technology 8(2); 1 -11
[4] Adeyanju O, Lajide L. and Abayomi Toluwalop G. (2013). Nutritional assessment of Antiaris africana exudate gum: A new emulsifier in food processing.. Photon Journal of Phytochemistry 114: 196-200.
[5] Adeyanju Olusola, Olajide Olutayo, Afolayan Michael, Adewusi Adepoju John, (2012). Antimicrobial activity and Elemental analysis of Cassia siberieana leaves using Atomic Absorption spectrometer. Journal of Natural Product and Plant Resource 2(1): 9 –18
[6] Adeyanju O and Joshua E.C(2020). Nutritional and Structural Evaluation of Sweitenia mycrophylla Exudate gum. A potential excipient and food additive. Advanced Journal of Chemistry. Section A 3; (1);9-14
[7] Emesi I. C, Zang .C. U and Adeyanju.O (2019). Nutritional analysis of Manihot esculentus tubers. a potential biomaterial in food processing. International Journal of current Research in Chemistry and Pharmaceatical Sciences. 6 (6);19-22
[8] AOAC. (2005). Official Method of Analysis of the Association of Official Analytical Chemist. Washington DC, USA.
[9] Bultman, T. L. (1998). Attempting a collaborative approach to community ecology. Journal of ecology, Ecology society of America, 79 (2) pp. 746-747
[10] Cock, J.H. (1985). Cassava: New Potential for a Neglected Crop, West view Press Boulder Co. pp 191.
[11] Ene-Obong, H.N. (2001). Determinants of health and nutritional status of rural Nigerian women. Journal of health, population and nutrition, 19(4), pp. 329-330.
[12] Fasuyi, A.O. (2005). Nutrient composition and processing effects on cassava leaf (Manihot esculenta, Crantz) Anti-nutrients. Pakistan journal of nutrition, Vol. 4, Iss. 1. pp. 37-42
[13] Kakade, M. L., N.R. Simon and T.E. Liener, (1971). Biochemical and Nutritional assessment of different varieties of soyabean. J. Agr. Food Chem., 20(87).
[14] Markkar, H. P. S., M. Blummer, N. K. Browy and K. Becker. (1993). Gravimetric of Tannins and their correlation with chemical and protein precipitation methods. J. Sci. Food Agr., 61: 161-165.
[15] Oke, O. L. (1969). Chemical studies on some Nigerian foodstuffs. Latum W. Afr. J. Biol. Appl. Chem., 8: 53-56
[16] Siddig, N. E. (1996). Nitrogen and specific rotation as qualifying indices for gum Arabic derived from Acacia Senegal (L) wild. M.Sc. Thesis, Faculty of Agriculture, University of Khartoum.
[17] Wobeto, C, Angelita, D.C, Celeste, M.P, Custodio, D.S and Henrique, V. P. (2007). Anti-nutrients in the cassava (Manihot esculenta Crantz) leaf powder at three ages of the plant. Journal of food science and technology, Aliment. Vol. 27(1).
Adeyanju, O, Adeyemi, A. E, Nimmyel. N. V., Dirikebamoh , S.T, Chukwu, C. S and Okafor, D.C “Nutritional and Anti-Nutritional Constituents of Cassava (Manihot Esculentus) Tubers and Leaves in Jos North Lga of Plateau State, Nigeria” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-5, pp.65-67 May 2022 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/volume-7-issue-5/65-67.pdf
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ACO-KNN Predictive Model for Diagnosis of Chronic Kidney Disease
Olukiran Oyenike Adunni, Omidiora Elijah Olusayo, Olabiyisi Stephen Olatunde, Shoyemi Olufemi Segun, Segun Aina- May 2022 Page No.: 68-73
Chronic Kidney Disease (CKD) remains a worldwide health challenge that is increasing steadily. It is a chronic situation accompanied by an increase in morbidity, mortality, and also a risk of other several diseases like cardiovascular diseases and high healthcare costs. More than two million individuals over the globe receive dialysis or transplanting kidney treatment to stay alive, yet this figure shows only 10% represent people who need treatment to live. Early detection and management of CKD are necessary. It is important to predict the progression of CKD with reasonable accuracy due to its dynamic and covert nature in the early stages and patient heterogeneity. This paper presents a CKD predictive model by the introduction of a nature-inspired computation algorithm known as Ant Colony Optimization for the selection of discriminant attributes from the CKD indigenous dataset and employing some selected machine learning algorithms for classification. The CKD predicted model was evaluated using an indigenous dataset collected from Ladoke Akintola University of Technology (LAUTECH) teaching hospital, Ogbomoso and Osogbo, University College Hospital (UCH), Ibadan, Oyo State and Obafemi Awolowo University Teaching Hospital (OAUTH), Ile-Ife, Osun State, Nigeria. Experimental results showed that binary classification for CKD predictive model produced the best accuracy of 99.13%, the best specificity of 0.9839, the best sensitivity of 0.9929 in ACO-KNN and also for the multistage CKD predictive model, the best outputs for accuracy, specificity, sensitivity are given respectively with 99.65%, 0.9956 and 1.000 in CKD patients with stage 2 disease Severity using ACO-KNN.
Page(s): 68-73 Date of Publication: 30 June 2022
Olukiran Oyenike Adunni
Department of Mathematical and Computing Sciences, Faculty of Applied Sciences,
Kola Daisi University, Ibadan, Oyo State, Nigeria
Omidiora Elijah Olusayo
Department of Computer Science and Engineering, Faculty of Technology and Engineering,
Ladoke Akintola University of Technology, Ogbomoso, Nigeria
Olabiyisi Stephen Olatunde
Department of Computer Science and Engineering, Faculty of Technology and Engineering,
Ladoke Akintola University of Technology, Ogbomoso, Nigeria
Shoyemi Olufemi Segun
University of Plymouth, School of Nursing and Midwifery, Plymouth, United Kingdom
Segun Aina
Department of Computer Science and Engineering Obafemi Awolowo University, Nigeria
[1]. Abioye, A. [1] J. Tabassum, S., Mamatha B.& Majumdar, “Analysis and Prediction of Chronic Kidney Disease using Data Mining Techniques,” Int. J. Eng. Res. Comput. Sci. Eng., vol. 4, no. 9, pp. 25–32, 2017.
[2] R. Arasu, S.D., & Thirumalaiselvi, “Review of Chronic Kidney Disease based on Data Mining Techniques,” Int. J. Appl. Eng. Res., vol. 12, no. 23, pp. 13498–13505, 2017.
[3] M. Gopika, S. & Vanitha, “Survey on Prediction of Kidney Disease by using Data Mining Techniques,” Int. J. Adv. Res. Comput. Commun. Eng., vol. 6, no. 1, pp. 198–201, 2019.
[4] R. . Pasadana, I. A., Hartama, D. zarlis, Sianipar, A.S, Munandar, S.B, & Alam, “Chronic Kidney Disease Prediction by Using Different Decision Tree Techniques,” Int. Conf. Comput. Sci. Appl. Math., vol. 1255, pp. 1–6, 2019.
[5] P. M. Patil, “Review on Prediction of Chronic Kidney Disease Using Data Mining Techniques,” Int. J. Comput. Sci. Mob. Comput., vol. 5, no. 5, pp. 135–141, 2016.
[6] M. K. Ameta, M. A., & Jain, “Data Mining Techniques for the Prediction of Kidney Diseases and Treatment : A Review,” Int. J. Eng. Comput. Sci., vol. 6, no. 2, pp. 20376–20378, 2017.
[7] S. Vijayarani and S. M. Sylviaa, “Comparative Analysis of Dimensionality Reduction Techniques,” Int. J. Innov. Res. Comput. Commun. Eng., vol. 4, no. 1, pp. 23–29, 2016.
[8] L. Duan, C. Aggarwal, M. Shuai, M. Tiejun, and J. Huai, “An Ensemble Approach to Link Prediction,” IEEE Trans. Knowl. Data Eng., vol. 10, no. 10, pp. 1–14, 2017.
[9] X. Teng and Y. Gong, “Research on Application of Machine Learning in Data Mining,” in IOP Conference Series: Materials Science and Engineering, 2018, vol. 392, no. 6.
[10] S. Kumar, V. & Minz, “Feature Selection: A literature Review,” Smart Comput. Rev., vol. 4, no. 3, pp. 211–229, 2014.
[11] M. Shardlow, “An Analysis of Feature Selection Techniques,” Univ. Manchester, vol. 14, no. 1, pp. 1–7, 2016.
[12] N. Krishnaveni and V. Radha, “Feature Selection Algorithms for Data Mining Classification: A Survey,” Indian J. Sci. Technol., vol. 12, no. 6, pp. 1–11, 2019.
[13] M. Doshi, S. K. Chaturvedi, and D. Ph, “CORRELATION BASED FEATURE SELECTION ( CFS ) TECHNIQUE TO PREDICT STUDENT PERFROMANCE,” Int. J. Comput. Netw. Commun., vol. 6, no. 3, pp. 197–206, 2014.
[14] M. B. Imani, T. Pourhabibi, M. R. Keyvanpour, and R. Azmi, “A New Feature Selection Method Based on Ant Colony and Genetic Algorithm on Persian Font Recognition,” Int. J. Mach. Learn. Comput., vol. 2, no. 3, pp. 278–282, 2012.
[15] K. Sheena, Krishan, K., & Gulshan, “Analysis of Feature Selection Techniques : A Data Mining Approach,” in International Conference on Engineering & Technology, 2016, pp. 17–21.
[16] H. Polat, H. Danaei Mehr, and A. Cetin, “Diagnosis of Chronic Kidney Disease Based on Support Vector Machine by Feature Selection Methods,” J. Med. Syst., vol. 41, no. 4, p. 55, Apr. 2017.
[17] R. S. Wahono, N. Suryana, and S. Ahmad, “Metaheuristic Optimization based Feature Selection for Software Defect Prediction,” J. Softw., vol. 9, no. 5, pp. 1325–1333, 2014.
[18] S. Beniwal and J. Arora, “Classification and Feature Selection Techniques in Data Mining,” Int. J. Eng. Res. Technol., vol. 1, no. 6, pp. 1–6, 2012.
[19] A. Tripathi, A. Nadaf, and A. K. Yadav, “Identification of the Stages of Chronic Kidney Disease Using Data Mining Approach,” Int. Res. J. Mod. Eng. Technol. Sci., vol. 2, no. 8, pp. 463–467, 2020.
[20] N. Oladeji, F A, Idowu, P A, Egejuru, “Model for Predicting the Risk of Kidney Stone using Data Mining Techniques,” Int. J. Comput. Appl., vol. 182, no. 38, pp. 36–56, 2019.
[21] M. K. Subhashini, R. & Jeyakumar, “E-Anfis to Diagnose the Progression of Chronic Kidney Disease,” Clin. Pract., vol. 16, no. 5, pp. 1235–1244, 2019.
[22] M. D. Basar and A. Akan, “Detection of Chronic Kidney Disease by Using Ensemble Classifiers,” in 10th International Conference on Electrical and Electronics Engineering, ELECO 2017, 2018, pp. 544–547.
[23] M. Alshammari and M. Mezher, “A comparative analysis of data mining techniques on breast cancer diagnosis data using WEKA toolbox,” Int. J. Adv. Comput. Sci. Appl., vol. 11, no. 8, pp. 224–229, 2020.
[24] S. Gopika and M. Vanitha, “Efficiency of Data Mining Techniques for Predicting Kidney Disease,” Int. J. Eng. Technol., vol. 9, no. 5, pp. 3586–3591, 2017.
Olukiran Oyenike Adunni, Omidiora Elijah Olusayo, Olabiyisi Stephen Olatunde, Shoyemi Olufemi Segun, Segun Aina “ACO-KNN Predictive Model for Diagnosis of Chronic Kidney Disease” International Journal of Research and Innovation in Applied Science (IJRIAS) volume-7-issue-5, pp.68-73 May 2022 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/volume-7-issue-5/68-73.pdf
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