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Modelling crop portfolios that minimize human macronutrient deficiency on subsistence farms in Burundi

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Abstract

In Burundi, many subsistence farmers employ mixed cropping systems in an attempt to provide food for their families in an environment with high risks, few safety nets and limited storage options. In this paper, we studied the crop portfolios that minimize energy and macronutrient deficiency. We accounted for yield variability, seasonality and storage availability. A mathematical programming approach was applied to four different farm types (based largely on farm size) to predict optimal mixes of crops for farmers to achieve the household year-round supply in calories, fats and proteins. The models predicted that farmers could best cover their household needs in terms of calories, fats and proteins by growing fewer crops in a more optimal combination. Bananas and cassava appear in the crop portfolios as sources of energy; growing beans add proteins to the diets and groundnuts and/or soybeans will supply the needed fats. Crop portfolios differ by farm type and change when yield variability and storage is accounted for. Some of the portfolios predicted by the models have a more diverse crop combination and include maize, rice and/or peas additional to the crops mentioned above. Results also highlighted the benefits of basic storage infrastructure in overcoming seasonal shortages. Nevertheless, even if they would choose to apply the proposed crop portfolios, farms with very small land size in Burundi will continue to struggle to supply sufficient food for the family. Further refinement for micronutrient supply, diet quality, food preferences and market purchases may change these findings.

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Notes

  1. In this paper we use the term ´mixed cropping systems´ to refer to farm practices that combine different crops on different pieces of land as sole crops, as intercrops or in rotations. We use it interchangeably with ´on-farm diversification´.

  2. The prices of the crop commodities were taken from the national bureau of statistics for the study area.

  3. This data of a large group of farmers is less detailed that the data used to calibrate our models.

References

  • Adesina, A. A. (2010). Conditioning trends shaping the agricultural and rural landscape in Africa. Agricultural Economics, 41, 73–82.

    Article  Google Scholar 

  • Anderson, E. W. (2002). The dynamics of risk-sensitive allocations. Journal of Economic Theory, 125, 93–150.

    Article  Google Scholar 

  • Baghdadli, I., Harborne, B., & Rajadel, T. (2008). Breaking the cycle: A strategy for conflict-sensitive rural growth in Burundi. The World Bank, Washington, DC, USA.

  • Baramburiye, J., Kyotalimye, M., Thomas, T. S., & Waithaka, M. (2013). Burundi. In Waithaka, M., Nelson, G. C., Thomas, T. S. and Kyotalimye, M. (eds) East African Agriculture and Climate Change: A Comprehensive Analysis. Washington, DC, International Food Policy Research Institute.

  • Barrett, C. B., Place, F., & Aboud, A. A. (Eds.). (2002). Natural resources management in African agriculture: Understanding and improving current practices. CABI.

  • Bergen, D. (1986). Perspectives de la spécialisation régionale comme stratégie de développement. Synthèse nationale des dossiers par région naturelle sur les flux des produits agricoles. ISABU.

    Google Scholar 

  • Berger, T., & Schreinemachers, P. (2006). Land-use and decisions in Developing Countries and their representative representation in multi-agent systems. Journal of Land Use Science, 1, 29–44.

    Article  Google Scholar 

  • Bolarinwa, O. D., Ogundari, K., & Aromolaran, A. B. (2020). Intertemporal evaluation of household food security and its determinants: Evidence from Rwanda. Food Security, 12(1), 179–189.

    Article  Google Scholar 

  • Bundervoet, T. (2010). Assets, activity choices, and civil war: Evidence from Burundi. World Development, 38, 955–965.

    Article  Google Scholar 

  • Buse, R. C., & Salathe, L. E. (1978). Adult Equivalent Scales: An alternative 22 approach. American Journal of Agricultural Economics, 60, 460–468.

    Article  Google Scholar 

  • Caddad, I., Al-Husni, M., & Chen, B.F. (2010). Risk analysis in agricultural enterprises. Revue Des economies nord Africaines N°6.

  • Cochet, H. (2004). Agrarian dynamics, population growth and resource management: The case of Burundi. GeoJournal, 60, 111–124.

    Article  Google Scholar 

  • Cochet, H. (2001). Crises et Révolutions Agricoles au Burundi. Karthala.

    Google Scholar 

  • de Janvry, A., & Sadoulet, E. (2006). Progress in the modeling of rural households' behavior under market failures. In: de Janvry, A., Kanbur, R. (Eds.), Poverty, Inequality and Development. USA: Springer online.

  • Dercon, S. (2002). Income risk, coping strategies and safety nets. The World Bank Research Observer, 17(2), 141–166.

    Article  Google Scholar 

  • Devereux, S., Roelen, K., Sabates-Wheeler, R., Stoelinga, D., & Dyevre, A. (2019). Graduating from food insecurity: Evidence from graduation projects in Burundi and Rwanda. Food Security, 11(1), 219–232.

    Article  Google Scholar 

  • ENAB. (2013). Enquête, nationale agricole du Burundi : Résultats de la campagne agricole 2011–2012. Bujumbura, République du Burundi.

    Google Scholar 

  • FAO. (1997). Agriculture food and nutrition for Africa - A resource book for teachers of agriculture. FAO.

    Google Scholar 

  • FAO. (2015). Country fact sheet on food and agriculture policy trends. Bujumbura, République du Burundi.

    Google Scholar 

  • FAO. (2020). The state of food and agriculture: Transforming Food Systems for Affordable Healthy Diets. FAO.

    Google Scholar 

  • FAO, Ifad & WFP. (2014). The State of Food Insecurity in the World : Strengthening the enabling environment for food security and nutrition. FAO.

    Google Scholar 

  • FAO & WHO. (2013). Designing Nutrition-Sensitive Agriculture Activities, Second International Conference on Nutrition: Better nutrition better lives. Rome: FAO.

  • Flichman, G. & Allen, T. (2014). Bio-economic modeling: State-of-the-art and key priorities. Washington, D.C.: International Food Policy Research Institute (IFPRI).

  • Gil, J. (2020). Multiple Cropping Systems. Nature Food, 1(10), 593–593.

    Article  Google Scholar 

  • Glen, J. J., & Tipper, R. (2001). A mathematical programming model for improvement planning in a semi-subsistence farm. Agricultural Systems, 70, 295–317.

    Article  Google Scholar 

  • Hawkes, C. & Ruel, M. T. (2008). From Agriculture to Nutrition: Pathways, Synergies and Outcomes. Agricultural and Rural Development Notes; No. 40. Washington, DC: World Bank.

  • Hazell, P. B. R., & Norton, R. D. (1986). Mathematical programming for economic analysis in agriculture. Macmillan Publishing Company.

    Google Scholar 

  • Hosu, S., & Mushunje, A. (2013). Optimizing resource use and economics of crop- livestock integration among small farmers in semiarid regions of South Africa. Agroecology and Sustainable Food Systems, 37, 985–1000.

    Article  Google Scholar 

  • Jones, S., Lacey, P., & Walshe, T. (2009). A dynamic hydrological Monte Carlo simulation model to inform decision-making at Lake Toolibin, Western Australia. Journal of Environmental Management, 90, 1761–1769.

    Article  PubMed  Google Scholar 

  • Khan, D. (2008). Managing risks in farming in farming. FAO.

    Google Scholar 

  • Kimura, S., & LeThi, C. (2011). Farm Level Analysis of Risk and Risk Management Strategies and Policies: Technical Note. OECD Food, Agriculture and Fisheries Papers, 48.

  • Köbrich, C., & Khan, T. R. M. (2003). Typification of farming systems for constructing representative farm models: Two illustrations of the application of multi-variate analysis in Chile and Pakistan. Agricultural Systems, 76, 141–157.

    Article  Google Scholar 

  • Lauwers, L., Decock, L., Dewit, J., & Wauters, E. (2010). A Monte Carlo model for simulating insufficiently remunerating risk premium: Case of market failure in organic farming. Agriculture and Agricultural Science Procedia, 1, 76–89.

    Article  Google Scholar 

  • Lourme-Ruiz, A., Dury, S., & Martin-Prével, Y. (2021). Linkages between dietary diversity and indicators of agricultural biodiversity in Burkina Faso. Food Security, 13(2), 329–349.

    Article  Google Scholar 

  • MINAGRIE (2020). Document d'orientation de la politique environnementale, agricole et d'élevage. Gitega, Burundi: MINAGRIE.

  • MPDRN. (2006). Programme d’Appui à la Gouvernance; Monographie de la province de Ngozi. République du Burundi.

    Google Scholar 

  • Muthini, D., Nzuma, J., & Nyikal, R. (2020). Farm production diversity and its association with dietary diversity in Kenya. Food Security, 12(5), 1107–1120.

    Article  Google Scholar 

  • Ndimira, P. F. (1991). Dynamique et problématique d'amélioration des systèmes d'exploitation agricoles au Burundi. Cas de Remera. PhD thesis, Université Catholique de Louvain, Louvain-La-Neuve, Belgium.

  • NEPAD & FAO. (2006). Appui à la mise en oeuvre du NEPAD-PDAA: Promotion des technologies agricoles et agroalimentaires. Repulique du Burundi, Bujumbura: NEPAD, FAO.

  • Niragira, S. (2016). Understanding smallholder farming systems for food security in Burundi. PhD thesis, Ghent University, Ghent, Belgium.

  • Niragira, S., D’Haese, M., Buysse, J., Van Orshoven, J., & Ndimubandi, J. (2021). Historical changes in the traditional agrarian systems of Burundi: Endogenous drive to survive from food insecurity. GeoJournal, 86, 865–884.

    Article  Google Scholar 

  • Niragira, S., D’Haese, M., D’Haese, L., Ndimubandi, J., Desiere, S., & Buysse, J. (2015). Food for survival: Diagnosing crop patterns to secure lower threshold food security levels in farm households of Burundi. Food and Nutrition Bulletin, 36, 196–210.

    Article  PubMed  Google Scholar 

  • Niragira, S. (2011). Optimizing land use among small scale farms through agricultural specialization in the north of Burundi. Master dissertation. Ghent University, Ghent, Belgium.

  • Nkala, P., Mango, N., Corbeels, M., Velduisch, G. J., & Huising, J. (2011). The conundrum of conservation agriculture and livelihoods in Southern Africa. African Journal of Agricultural Research, 6, 5520–5528.

    Google Scholar 

  • Nkurunziza, J. D., Ngaruko, F. (2002). Explaining growth in Burundi: 1960–2000. CSAE WPS/ 2002–03, University of Oxford, UK.

  • Ntakyo, P. R., & van den Berg, M. (2019). Effect of market production on rural household food consumption: Evidence from Uganda. Food Security, 11(5), 1051–1070.

    Article  Google Scholar 

  • Osaki, M., & Batalha, M. O. (2014). Optimization model of agricultural production system in grain farms under risk, in Sorriso, Brazil. Agricultural Systems, 127, 178–188.

    Article  Google Scholar 

  • Plumptre, A. J., Davenport, T. R. B., Behangana, M., Kityo, R., Eilu, G., Ssegawa, P., Ewango, C., Meirte, D., Kahindo, C., Herremans, M., Peterhans, J. K., Pilgrim, J. D., Wilson, M., Languy, M., & Moyer, D. (2007). The biodiversity of the Albertine Rift. Biological Conservation, 134(2), 178–194.

    Article  Google Scholar 

  • PRSP. (2006). Poverty Reduction Strategic Paper. Republic of Burundi.

    Google Scholar 

  • PND. (2018). Plan National de Developement du Burundi (2018–2027). Bujumbura, République du Burundi.

    Google Scholar 

  • Reardon, T. (1997). Using evidence of household income diversification to inform study of the rural nonfarm labor market in Africa. World Development, 25, 735–747.

    Article  Google Scholar 

  • Rishirumuhirwa, T., & Roose, E. (1998). The contribution of banana farming systems to sustainable land use in Burundi. Advance in Geoecology, 31, 1197–1204.

    Google Scholar 

  • Roba, K. T., O’Connor, T. P., O’Brien, N. M., Aweke, C. S., Kahsay, Z. A., Chisholm, N., & Lahiff, E. (2019). Seasonal variations in household food insecurity and dietary diversity and their association with maternal and child nutritional status in rural Ethiopia. Food Security, 11(3), 651–664.

    Article  Google Scholar 

  • Ruben, R., & Pender, J. (2004). Rural diversity and heterogeneity in less favourable areas: The quest for policy targeting. Food Policy, 29, 303–320.

    Article  Google Scholar 

  • Ruben, R., & van Ruijven, A. (2001). Technical coefficients for bio-economic farm household models: A meta-modelling approach with applications for Southern Mali. Ecological Economics, 36(3), 427–441.

    Article  Google Scholar 

  • Sibhatu, K. T., & Qaim, M. (2018a). Farm production diversity and dietary quality: Linkages and measurement issues. Food Security, 10(1), 47–59.

    Article  Google Scholar 

  • Sibhatu, K. T., & Qaim, M. (2018b). Review: Meta-analysis of the association between production diversity, diets, and nutrition in small-holder farm households. Food Policy, 77, 1–18.

    Article  Google Scholar 

  • Simbizi, J. (1996). Analyse de l'incertitude dans les systèmes d'exploitation agricoles du Burundi. PhD thesis, Université Catholique de Louvain, Louvain-la-Neuve, Belgium.

  • Singh, S., Jones, A., De Fries, R. S., & Jain, M. (2020). The association between crop and income diversity and farmer intra-household dietary diversity in India. Food Security, 12(2), 369–390.

    Article  Google Scholar 

  • Singh, I., Squire, L., & John Strauss, J. (Eds.). (1986). Agricultural Household Models. Baltimore. The Johns Hopkins University Press.

    Google Scholar 

  • Snapp, S. S., & Fisher, M. (2015). “Filling the maize basket” supports crop diversity and quality of household diet in Malawi. Food Security, 7(1), 83–96.

    Article  Google Scholar 

  • Timmer, P. C. (1997). Farmers and markets: The political economy of new paradigms. American Journal of Agricultural Economics, 79, 621–627.

    Article  Google Scholar 

  • Tripathi, L., & Tripathi, J. N. (2009). Relative susceptibility of banana cultivars to Xanthomonas campestris pv. Musacearum. African Journal of Biotechnology, 8, 5343–5350.

    Google Scholar 

  • Verhaegen, E., Degand, J., & D’Haese, L. (1991). Amélioration des systèmes d’exploitation agricole traditionnels au Burundi. Université du Burundi.

    Google Scholar 

  • Verschelde, M., D’Haese, M., Rayp, G., & Vandamme, E. (2012). Challenging small scale farming: A non parametric analysis of the (inverse) relationship between farm productivity and farm size in Burundi. Journal of Agricultural Economics, 11, 261–287.

    Google Scholar 

  • WFP (2021). http://www.wfp.org/countries/burundi (last accessed on 10 May 2021).

  • Waldman, K. B., Giroux, S., Blekking, J. P., Baylis, K., & Evans, T. P. (2020). Smallholder food storage dynamics and resilience. Food Security, 12(1), 7–20.

    Article  Google Scholar 

  • Weisell, R. & Dop, M. C. (2012). The Adult Male Equivalent concept and 23. its application to Household Consumption and Expenditures Surveys (HCES). Food and Nutrition Bulletin, 33, 157–162.

  • West, C. E., Pepping, F. & Temalilwa, C. R., (Eds.) (1988). The composition of foods commonly eaten in East Africa. Wageningen, the Netherlands, Wageningen Agricultural University.

  • World Bank (2008). Agriculture for Development. World Development Report. Washington DC: The World Bank.

  • World Bank (2021). World Bank Open Data. https://data.worldbank.org (last accessed May 2021).

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Correspondence to Sanctus Niragira.

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Niragira, S., Ndimubandi, J., Van Orshoven, J. et al. Modelling crop portfolios that minimize human macronutrient deficiency on subsistence farms in Burundi. Food Sec. 14, 23–37 (2022). https://doi.org/10.1007/s12571-021-01216-1

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