Volume 8, Issue 4, July 2020, Page: 74-80
Comparative Nutritional Analysis of Tylosema esculentum (Marama Bean) Germplasm Collection in Namibia
Paidamoyo Natasha Mataranyika, Department of Natural and Applied Sciences, Namibia University of Science and Technology, Windhoek, Namibia
Percy Maruwa Chimwamurombe, Department of Natural and Applied Sciences, Namibia University of Science and Technology, Windhoek, Namibia
Buhlebenkosi Fuyane, Department of Health Sciences, Namibia University of Science and Technology, Windhoek, Namibia
Kayini Chigayo, Department of Mining and Process Engineering, Namibia University of Science and Technology, Windhoek, Namibia
Julien Lusilao, Department of Natural and Applied Sciences, Namibia University of Science and Technology, Windhoek, Namibia
Received: May 27, 2019;       Accepted: Jul. 1, 2019;       Published: Jun. 28, 2020
DOI: 10.11648/j.jfns.20200804.11      View  8      Downloads  8
Malnutrition is a medical condition caused by an unbalanced diet, typically characterised by stunting and wasting in children. Malnutrition causes approximately a third of all deaths in children between 0-59 months mostly in developing countries. In Namibia, 24% of children under the age of 5 years are stunted while 6.2% are wasted. Tylosema esculentum, commonly known as marama bean is an underutilised legume of high nutritious value. Indigenous to Namibia, marama bean seeds have comparably high protein and lipid content. Marama bean is an appealing crop to Namibia in particular due to its low cultivation demands as it grows in sandy soils with minimal water requirements and no need for fertilisers. Ten accessions of marama bean seeds were analysed for their nutritional composition. The results indicate that ash content was found ranging between 2.13% and 3.46%. Minerals analysed were calcium, iron, magnesium, phosphorus and zinc. Their range of concentrations were 750.1-2306.2 mgkg-1, 53.9-322.4 mgkg-1, 1764.1-7415.0 mgkg-1, 4300.8-5267.9 mgkg-1 and 32.2-48.8 mgkg-1 respectively with no significant difference in concentration among the ten accessions. Correlation analysis of the minerals within the accessions showed that the correlations between zinc-magnesium and zinc-phosphorus concentrations were significantly different as compared to the rest of the pairs for all accessions. When analysed, the maximum and minimum amounts of crude fat and carbohydrates were 29.9%-44.1% and 19.4%-39.0% respectively which were found to not have a significant difference. However, the protein analysis determined that there was a significant difference with PMBC2 (mean content 34.6%) being the most significant accession. Therefore, PMBC2 was found to be the most suitable accession for crop development and domestication. This study’s main contribution with respect to the domestication of marama bean was the identification of the most superior accession based on nutritional composition.
Malnutrition, Marama Bean, Nutritional Composition, Biofortifier, Crop Domestication
To cite this article
Paidamoyo Natasha Mataranyika, Percy Maruwa Chimwamurombe, Buhlebenkosi Fuyane, Kayini Chigayo, Julien Lusilao, Comparative Nutritional Analysis of Tylosema esculentum (Marama Bean) Germplasm Collection in Namibia, Journal of Food and Nutrition Sciences. Vol. 8, No. 4, 2020, pp. 74-80. doi: 10.11648/j.jfns.20200804.11
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Ziba M, Kalimbira AA, Kalumikiza Z. Estimated burden of aggregate anthropometric failure among Malawian children. South African J Clin Nutr [Internet]. 2018; 31 (2): 20–3. Available from: https://doi.org/10.1080/16070658.2017.1387433
Ghosh-Jerath S, Singh A, Jerath N, Gupta S, Racine EF. Undernutrition and severe acute malnutrition in children. BMJ. 2017; 359: j4877.
Kalu RE, Etim KD. Factors associated with malnutrition among underfive children in developing countries: A review. Glob J Pure Appl Sci. 2018; 24 (1): 69.
Akombi BJ, Agho KE, Hall JJ, Wali N, Renzaho AMN, Merom D. Stunting, wasting and underweight in Sub-Saharan Africa: A systematic review. Int J Environ Res Public Health. 2017; 14 (8): 1–19.
Motbainor A, Worku A, Kumie A. Stunting is associated with food diversity while wasting with food insecurity among underfive children in East and West Gojjam Zones of Amhara Region, Ethiopia. PLoS One [Internet]. 2015; 10 (8): 1–15. Available from: http://dx.doi.org/10.1371/journal.pone.0133542
Bain LE, Awah PK, Geraldine N, Kindong NP, Sigal Y, Bernard N, et al. Malnutrition in Sub - Saharan Africa: Burden, causes and prospects. Vol. 15, Pan African Medical Journal. 2013. p. 1–9.
Domello M, Braegger C, Campoy C, Colomb V, Decsi T. Committee on Nutrition : 2014; 58 (1): 119–29.
Million M, Diallo A, Raoult D. Gut microbiota and malnutrition. Microb Pathog [Internet]. 2017; 106 (February): 127–38. Available from: http://dx.doi.org/10.1016/j.micpath.2016.02.003
Alou MT, Million M, Traore SI, Mouelhi D, Brah S, Alhousseini D, et al. Gut Bacteria Missing in Severe Acute Malnutrition, Can We Identify Potential Probiotics by Culturomics ? 2017; 8 (May): 1–17.
Mehta NM, Corkins MR, Lyman B, Malone A, Goday PS, Carney L, et al. Defining pediatric malnutrition: A paradigm shift toward etiology-related definitions. J Parenter Enter Nutr. 2013; 37 (4): 460–81.
Goudet S, Griffiths P, Bogin B, Madise N. Interventions to tackle malnutrition and its risk factors in children living in slums: a scoping review. Vol. 44, Annals of Human Biology. 2017. p. 1–10.
Ramos C V, Dumith SC, César JA. Prevalence and factors associated with stunting and excess weight in children aged 0-5 years from the Brazilian semi-arid region. J Pediatr (Rio J) [Internet]. 2015; 91 (2): 175–82. Available from: http://dx.doi.org/10.1016/j.jped.2014.07.005
Mas-Harithulfadhli-Agus AR, Hamid NA, Rohana AJ. Rural child malnutrition and unsuccessful outcome of food basket programme: does ethnicity matter? Ethn Heal [Internet]. 2018; 0 (0): 1–16. Available from: https://doi.org/10.1080/13557858.2018.1494820
Temba MC, Njobeh PB, Adebo OA, Olugbile AO, Kayitesi E. The Role of Compositing Cereals with Legumes to Alleviate Protein Energy Malnutrition in Africa. Int J Food Sci Technol. 2016; 51 (3): 543–554.
Cullis C, Kunert K, Vorster J, Chimwamurombe P, Barker N. Orphan Legumes Growing in Dry Environments: Marama Bean as a Case Study. Front Plant Sci. 2018; 9 (1199).
Jackson JC, Duodu KG, Holse M, Lima de Faria MD, Jordaan D, Chingwaru W, et al. The Morama Bean (Tylosema esculentum): A Potential Crop for Southern Africa. Adv Food Nutr Res. 2010; 61: 187–246.
Bøhn T, Cuhra M, Traavik T, Sanden M, Fagan J, Primicerio R. Compositional differences in soybeans on the market: Glyphosate accumulates in Roundup Ready GM soybeans. Food Chem [Internet]. 2014; 153: 207–15. Available from: http://dx.doi.org/10.1016/j.foodchem.2013.12.054
Qayyum MMN, Butt MS, Anjum FM, Nawaz H. Composition analysis of some selected legumes for protein isolates recovery. J Anim Plant Sci. 2012; 22 (4): 1156–62.
Kayitesi E, De Kock HL, Minnaar A, Duodu KG. Nutritional quality and antioxidant activity of marama-sorghum composite flours and porridges. Food Chem. 2012; 131 (3): 837–42.
Enders A, Lehmann J. Comparison of Wet-Digestion and Dry-Ashing Methods for Total Elemental Analysis of Biochar. Commun Soil Sci Plant Anal. 2012; 43 (7): 1042–52.
Mihaljev Ž, Jakšić S, B Prica N, N Ćupić Ž, Baloš M. Comparison of the Kjeldahl method, Dumas method and NIR method for total nitrogen determination in meat and meat products. J Agroaliment Process Technol. 2015; 21 (April 2017): 365–70.
Agri Laboratory Association of Southern Africa. Handbook on Feeds and Plant Analysis. 2nd ed. Palic P, Claassens AS, Collier J, Loock A, Hattingh D, editors. Agri Laboratory Association of Southern Africa; 2007.
Holse M, Husted S, Hansen Å. Chemical Composition of Marama Bean (Tylosema esculentum) - A Wild African Bean with Unexploited Potential. J Food Compos Anal. 2010; 23: 648–57.
Jhaumeer Laulloo S, Bhowon MG, Soyfoo S, Chua LS. Nutritional and Biological Evaluation of Leaves of Mangifera indica from Mauritius. J Chem. 2018; 1–9.
Zhou H, Yang WT, Zhou X, Liu L, Gu JF, Wang WL, et al. Accumulation of heavy metals in vegetable species planted in contaminated soils and the health risk assessment. Int J Environ Res Public Health. 2016; 13 (3).
Museler DL, Schonfeldt H. The Nutrient content of the marama bean. Agricola. 2006; 2–8.
Amonsou EO, Taylor JRN, Beukes M, Minnaar A. Composition of marama bean protein. Food Chem [Internet]. 2012; 130 (3): 638–43. Available from: http://dx.doi.org/10.1016/j.foodchem.2011.07.097
Etiosa O, Chika N, Benedicta A. Mineral and Proximate Composition of Soya Bean. Asian J Phys Chem Sci. 2018; 4 (3): 1–6.
Gerrano AS, Jansen van Rensburg WS, Venter SL, Shargie NG, Amelework BA, Shimelis HA, et al. Selection of cowpea genotypes based on grain mineral and total protein content. Acta Agric Scand Sect B Soil Plant Sci. 2019; 69 (2): 155–66.
Marles RJ. Mineral nutrient composition of vegetables, fruits and grains: The context of reports of apparent historical declines. J Food Compos Anal [Internet]. 2017; 56: 93–103. Available from: http://dx.doi.org/10.1016/j.jfca.2016.11.012
Kalidass C, Mohan VR. Biochemical composition and nutritional assessment of selected under-utilized food legume of the genus rhynchosia. Int Food Res J. 2012; 19 (3): 977–84.
Sanchez A, Mejia A, Sanchez J, Runte E, Brown-Fraser S, Bivens RL. Diets with customary levels of fat from plant origin may reverse coronary artery disease. Med Hypotheses [Internet]. 2019; 122 (October 2018): 103–5. Available from: https://doi.org/10.1016/j.mehy.2018.10.027
Browse journals by subject