Mapping and Comparison of Maize Products Value Chains in Nigeria and Rwanda



Abstract Views
598

Downloads
1061

Citations

Share

##plugins.themes.bootstrap3.article.sidebar##

Submitted Apr 26, 2022
Published Jun 13, 2022
10.24018/ejfood.2022.4.3.501

Abstract viewed = 598 times

Table of Contents

##plugins.themes.bootstrap3.article.main##

Maize products are very significant for domestic consumption as well as industrial uses both locally and globally. For there to truly appreciate the spread of maize production in Africa, the geospatial mapping and subsequent comparison of the value chain for Nigeria and Rwanda were necessitated hence the purpose of this study. Farm mapping geospatial techniques and remotely sensed data were used for both Nigeria and Rwanda in this study. GIMMS Global Agricultural Monitoring data from United States Department of Agriculture (USDA) were adopted for Nigeria and Rwanda. The crop calendars of both countries were examined which thereafter reviewed a marked distinction among them. The results of the agroecological zones for the two countries showed a significant variation in their distribution and types, which in turn affect both the planting and harvesting of maize; storage, marketing, processing, and policy framework for maize products value chain in Nigeria and Rwanda. Mapping of the two countries was carried out and the normalized differential vegetation index (NDVI) and the policy associated with maize value chains were checked and reported.

Keywords: Maize, NDVI, Nigeria, Rwanda, Value chain

References

  1. Murdia L. K., Wadhwani R., Wadhawan N., Bajpai P., & Shekhawat S. Maize utilization in India: an overview. American Journal of Food and Nutrition, 2016;4(6):169–176.
     Google Scholar
  2. Gwirtz J. A., & Garcia‐Casal, M. N. Processing maize flour and corn meal food products. Annals of the New York Academy of Sciences, 2014;1312(1):66–75.
     Google Scholar
  3. Pettit T. J., Croxton, K. L., & Fiksel J. The evolution of resilience in supply chain management: a retrospective on ensuring supply chain resilience. Journal of Business Logistics, 2019;40(1):56–65.
     Google Scholar
  4. Godde C. M., Mason-D’Croz D., Mayberry D. E., Thornton P. K., & Herrero M. Impacts of climate change on the livestock food supply chain: a review of the evidence. Global food security, 2021;28:100488.
     Google Scholar
  5. Oyetunde-Usman Z., & Shee A. Farmer preferences for adopting drought-tolerant maize varieties: evidence from a choice experiment in Nigeria. 2021
     Google Scholar
  6. Ibrahim H. Y., Ale-Ojo H. A., & Wahab M. J. Impact of the growth enhancement support scheme (GESS) on maize farmers in Dutsinma local government area of Katsina State, Nigeria. FUDMA Journal of Science, (FJS), 2018;2(1):143–148.
     Google Scholar
  7. Silvestri S., Macharia M., & Uzayisenga B. Analysing the potential of plant clinics to boost crop protection in Rwanda through adoption of IPM: the case of maize and maize stem borers. Food Security, 2019;11(2):301–315.
     Google Scholar
  8. Adam R. I., Misiko M., Dusengemungu L., Rushemuka P., & Mukakalisa Z. Gender and equitable benefit-sharing mechanisms through Agricultural Innovation Platforms in Rwanda. Community Development, 2018;49(4):380–397.
     Google Scholar
  9. Liverpool‐Tasie L. S. O., Reardon T., & Belton B. Essential non‐essentials”: COVID‐19 policy missteps in Nigeria rooted in persistent myths about African food supply chains. Applied Economic Perspectives and Policy, 2021;43(1):205–224.
     Google Scholar
  10. Shahidi F. Journal of Food Bioactives, 2020;9:1–3.
     Google Scholar
  11. Khan S. A. R., Razzaq A., Yu Z., Shah A., Sharif A., & Janjua L. Disruption in food supply chain and undernourishment challenges: An empirical study in the context of Asian countries. Socio-Economic Planning Sciences, 2021;101033.
     Google Scholar
  12. Torre A., Polge E., & Wallet. F., Proximities and the role of relational networks in innovation: The case of the dairy industry in two villages of the “green municipality” of Paragominas in the Eastern Amazon. Regional Science Policy & Practice, 2018. https://doi.org/10.1111/rsp3.12151.
     Google Scholar
  13. Faostat F. Agriculture organization of the United Nations statistics division. Economic and Social Development Department, Rome, Italy, 2016. Available online: http://faostat3. fao. org/home/E.
     Google Scholar
  14. FAO (Food and Agriculture Organization of the United Nations). State of food security 2015. Food and Agriculture Organization of the United Nations, Rome, 2015.
     Google Scholar
  15. FMWR (Federal Ministry of Water Resources of Nigeria). Draft national irrigation and drainage policy and strategy. Federal Ministry of Water Resources, 2014.
     Google Scholar
  16. World Bank. Project appraisal document on a proposed credit for transforming irrigation management in Nigeria project. World Bank, Washington, 2014.
     Google Scholar
  17. NISR (National Institute of Statistics of Rwanda). 2020.
     Google Scholar
  18. Bashir M., Adam A., Abubakar J., Faruk A., Garuba H., & Francis N. The role of national farmers helps line in agricultural information dissemination among crop farmers in Nigeria: a case study of farmers help line centre, NAERLS ABU Zaria. Journal of Agricultural Extension, 2021;25(1):93-103. https://doi.org/10.4314/jae.v25i1.8s.
     Google Scholar
  19. Olaniyan A. B. Maize: Panacea for hunger in Nigeria. African Journal of Plant Science, 2015;9(3):155–174.
     Google Scholar
  20. Ayinde O. E., Olaoye I. J., Bolaji M. O., & Oloyede A. O. Politics in fertilizer subsidy implementation and governance structure towards agricultural and economic Development in Nigeria: a review, 2019.
     Google Scholar
  21. Ogbodo J. A., Anarah S. E., & Abubakar S. M. GIS-based assessment of smallholder farmers' perception of climate change impacts and their adaptation strategies for maize production in Anambra State, Nigeria. Amanullah, & S. Fahad (Eds.), Corn production and human health in changing climate, 2018;115–138.
     Google Scholar
  22. Ater P. I., Aye G. C., & Daniel A. Analysis of maize value addition among entrepreneurs in Taraba State, Nigeria. International Journal of Environment, Agriculture and Biotechnology, 2018;3(6).
     Google Scholar
  23. Rakshit S., Chikkappa K. G., Jat S. L., Dhillon B. S., & Singh N. N. Scaling-up of proven technology for maize improvement through participatory approach in India. Best Practices of Maize Production Technologies in South Asia. Published by the SAARC Agriculture Centre (SAC), South Asian Association for Regional Cooperation, BARC Complex, Farmgate, New Airport Road, Dhaka-1215, Bangladesh, 2017:36–60.
     Google Scholar
  24. Banful A. B. Old problems in the new solutions? Politically motivated allocation of program benefits and the “new” fertilizer subsidies. World Development, 2011;39(7):1166–1176.
     Google Scholar
  25. Shiferaw B., Prasanna B. M., Hellin J., & Bänziger M. Crops that feed the world 6. Past successes and future challenges to the role played by maize in global food security. Food security, 2011;3(3):307–327.
     Google Scholar
  26. Mundia C. W., Secchi S., Akamani K., & Wang G. A regional comparison of factors affecting global sorghum production: The case of North America, Asia and Africa’s Sahel. Sustainability, 2019;11(7):21–35.
     Google Scholar
  27. Sadiq M. A., Kuwornu J. K., Al-Hassan R. M., & Alhassan S. I. Assessing maize farmers’ adaptation strategies to climate change and variability in Ghana. Agriculture, 2019;9(5):90.
     Google Scholar
  28. Fadara T., Adeleke K. M., Ogunlade C. A., Jekayinfa S. O., & Makinde O. O. Energy Analysis in Production and Processing of Selected Crops in Nigeria. Adeleke University Journal of Engineering and Technology, 2019;2(2):203–208.
     Google Scholar
  29. Daly J., Hamrick D., Gereffi G., & Guinn A. Maize value chains in East Africa. Duke Centre on Globalization, Governance, and Competitiveness. 2016.
     Google Scholar
  30. Abodi M. A., Obare G. A., & Kariuki I. M. Supply and demand responsiveness to maize price changes in Kenya: An application of error correction autoregressive distributed lag approach. Cogent Food & Agriculture, 2021;7(1):1957318.
     Google Scholar
  31. Seville D., Buxton A., & Vorley W. Under what conditions are value chains effective tools for pro-poor development? 2011.
     Google Scholar
  32. Ranum P., Peña‐Rosas J. P., & Garcia‐Casal M. N. Global maize production, utilization, and consumption. Annals of the New York academy of sciences, 2014;1312(1):105–112.
     Google Scholar
  33. Tanumihardjo S. A., McCulley L., Roh R., Lopez-Ridaura S., Palacios-Rojas N., & Gunaratna N. S. Maize agro-food systems to ensure food and nutrition security in reference to the Sustainable Development Goals. Global Food Security, 2020;25:100327.
     Google Scholar
  34. Afolabi K. O. Maize Innovation System in North Central, Nigeria. 2018.
     Google Scholar
  35. Abdulai S., Nkegbe P. K., & Donkoh S. A. Assessing the technical efficiency of maize production in northern Ghana: The data envelopment analysis approach. Cogent Food & Agriculture, 2018;4(1):1512390.
     Google Scholar
  36. Dandago M. A., Kitinoja L., & Abdullahi N. Commodity system assessment on postharvest handling, storage and marketing of maize (Zea mays) in Nigeria, Rwanda and Punjab, India. Journal of Horticulture and Postharvest Research, 2021;4:51-62.
     Google Scholar
  37. Hussain S., Ijaz M., Hussain M., Ul-Allah S., Abbas T., Nawaz A. Ahmad S. Advanced production technologies of maize. In Agronomic crops, Springer, Singapore, 2019:237–260.
     Google Scholar
  38. Santpoort R. The drivers of maize area expansion in Sub-Saharan Africa. How policies to boost maize production overlook the interests of smallholder farmers. Land, 2020; 9(3):68.
     Google Scholar
  39. Thornton P. K., van de Steeg J., Notenbaert A., & Herrero M. The impacts of climate change on livestock and livestock systems in developing countries: A review of what we know and what we need to know. Agricultural systems, 2009;101(3):113–127.
     Google Scholar
  40. Leitner S., Pelster D. E., Werner C., Merbold L., Baggs E. M., Mapanda F., & Butterbach-Bahl K. Closing maize yield gaps in sub-Saharan Africa will boost soil N2O emissions. Current Opinion in Environmental Sustainability, 2020;47:95–105.
     Google Scholar
  41. Ngango J., & Kim S. G. Assessment of technical efficiency and its potential determinants among small-scale coffee farmers in Rwanda. Agriculture, 2019;9(7): 161.
     Google Scholar
  42. Clay N. Seeking justice in Green Revolutions: Synergies and trade-offs between large-scale and smallholder agricultural intensification in Rwanda. Geoforum, 2018;97:352–362.
     Google Scholar
  43. Byishimo P. Assessment of Climate Change Impacts on Crop Yields and Farmers’ adaptation Measures: a case of Rwanda, 2017.
     Google Scholar
  44. Nzeyimana I. Assessment of Farmer-Led Irrigation Development in Rwanda, 2021.
     Google Scholar
  45. Niyomugabo J. D. D. Effects of Farm Household Heterogeneity on Agricultural inputs Adoption in Rwanda (Doctoral dissertation, UR-CAVM), 2019.
     Google Scholar
  46. Listman G. M., Guzmán C., Palacios-Rojas N., Pfeiffer W. H., San Vicente F., & Govindan V. Improving nutrition through biofortification: Preharvest and postharvest technologies. Cereal Foods World, 2019;64(3):1–7.
     Google Scholar
  47. Placide R., Ndacyayisenga T., Ntizo S., Kirimi S., & Nshimiyima J. C. Yield and yield components of CIP advanced potato clones under Rwandan agro-ecologies. Journal of Applied Biosciences, 2019;136: 13909–13920.
     Google Scholar
  48. NISR (National Institute of Statistics of Rwanda). 2015.
     Google Scholar
  49. Nishimwe K., Wanjuki I., Karangwa C., Darnell R., & Harvey J. An initial characterization of aflatoxin B1 contamination of maize sold in the principal retail markets of Kigali, Rwanda. Food Control, 2017; 73:574–580.
     Google Scholar
  50. Nabahungu N. L., & Visser S. M. Farmers' knowledge and perception of agricultural wetland management in Rwanda. Land Degradation & Development, 2013;24(4):363–374.
     Google Scholar
  51. Niassy S., Agbodzavu M. K., Kimathi E., Mutune B., Abdel-Rahman E. F. M., Salifu D. & Subramanian S. Bioecology of fall armyworm Spodoptera frugiperda (JE Smith), its management and potential patterns of seasonal spread in Africa. PloS one, 2021;16(6), e0249042.
     Google Scholar
  52. Batirbaev P., Kim T., Maini R., Shim R., Singer J., Snyder M., & Yawson F. Maize in Rwanda: a value chain analysis. Columbia University (SIPA) for the East West Management Institute & UNIDO. 50th Anniversary of the UNIDO. 2013:1– 5.
     Google Scholar
  53. Bamber P., Abdulsamad A., & Gereffi G. Burundi in the Agribusiness Global Value Chain. Skills for Private Sector Development. 2014.
     Google Scholar
  54. Akinyemi F. O. Land change in the central Albertine rift: Insights from analysis and mapping of land use-land cover change in north-western Rwanda. Applied Geography, 2017;87:127–138.
     Google Scholar
  55. https://glam1.gsfc.nasa.gov/.
     Google Scholar
  56. https://ipad.fas.usda.gov/.
     Google Scholar
  57. Rembold F., Meroni M., Urbano F., Csak G., Kerdiles H., Perez-Hoyos A. & Negre T. ASAP: A new global early warning system to detect anomaly hot spots of agricultural production for food security analysis. Agricultural systems, 2019;168:247–257.
     Google Scholar
  58. Gandhi G. M., Parthiban B., Thummalu N., & Christy A. NDVI: Vegetation change detection using remote sensing and GIS–A case study of Vellore District. Procedia computer science, 2015;57:1199–1210.
     Google Scholar


Most read articles by the same author(s)