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Value-Ag: An integrated model for rapid ex-ante impact evaluation of agricultural innovations in smallholder systems

Published online by Cambridge University Press:  21 July 2020

Marta Monjardino*
Affiliation:
CSIRO, Waite Road, Urrbrae, SA 5064, Australia
Geoff Kuehne
Affiliation:
Meaningful Social Research, PO Box 278, Balhannah, SA 5242, Australia Centre for Global Food and Resources, University of Adelaide, Adelaide, Australia
Jay Cummins
Affiliation:
Centre for Global Food and Resources, University of Adelaide, Adelaide, Australia
*
*Corresponding author. Email: marta.monjardino@csiro.au

Abstract

Evaluation of agricultural Research, Development, Extension and Management requires knowledge of farming systems economics and risk as well as broader adoption drivers. But until now, these factors have not been effectively combined when determining the success of agricultural research projects. To fill this gap, we developed Value-Ag, an integrated modelling platform using whole-farm economic analysis and prediction of the scaling potential in the context of production risk and household dynamics to provide an ex-ante estimate of the benefits of adopting an innovation. In this paper, we use a hypothetical case study to illustrate Value-Ag’s potential to evaluate agricultural innovations in a rigorous, systematic and participatory manner across a range of scenarios, thereby stimulating thinking and learning opportunities with the relevant stakeholders, and increasing the scrutiny of projects so that they deliver greater value for money while fostering a more results-focused culture in developing countries.

Type
Research Article
Copyright
© The Author(s), 2020. Published by Cambridge University Press

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References

Akroush, S. and Dhehibi, B. (2015). Predicted willingness of farmers to adopt water harvesting technologies: a case study from the Jordanian Badia (Jordan). American-Eurasian Journal of Agricultural and Environmental Sciences 15(8), 15021513.Google Scholar
Antle, J. (2011). Parsimonious multi-dimensional impact assessment. American Journal of Agricultural Economics 93(5), 12921311.CrossRefGoogle Scholar
Antle, J.M., Basso, B.O., Conant, R.T., Godfray, C., Jones, J.W., Herrero, M., Howitt, R.E., Keating, B.A., Munoz-Carpena, R., Rosenzweig, C., Tittonell, P. and Wheeler, T.R. (2017). Towards a new generation of agricultural system data, models and knowledge products: Design and improvement. Agricultural Systems 155, 255268.CrossRefGoogle ScholarPubMed
Berger, T. (2001). Agent-based spatial models applied to agriculture: a simulation tool for technology diffusion, resource use changes and policy analysis. Agricultural Economics 25, 245260.CrossRefGoogle Scholar
Brown, B., Nuberg, I. and Llewellyn, R. (2017a). Negative evaluation of conservation agriculture: perspectives from African smallholder farmers. International Journal of Agricultural Sustainability 15(4), 467481.CrossRefGoogle Scholar
Brown, B., Nuberg, I. and Llewellyn, R. (2017b). Stepwise frameworks for understanding the utilisation of conservation agriculture in Africa. Agricultural Systems 153, 1122.CrossRefGoogle Scholar
Brown, P.R., Nidumolu, U.B., Kuehne, G., Llewellyn, R., Mungai, O., Brown, B. and Ouzman, J. (2016). Development of the public release version of Smallholder ADOPT for developing countries. ACIAR Impact Assessment Series Report No. 91. Canberra: Australian Centre for International Agricultural Research. 56 pp.Google Scholar
Byerlee, D. and Hesse De Polanco, E. (1986). Farmers’ stepwise adoption of technological packages: evidence from the Mexican Altiplano. American Journal of Agricultural Economics 68(3), 519527.CrossRefGoogle Scholar
Clark, M. and Tilman, D. (2017). Comparative analysis of environmental impacts of agricultural production systems, agricultural input efficiency, and food choice. Environmental Research Letters 12, 064016.CrossRefGoogle Scholar
Connor, D.J., van Rees, H. and Carberry, P.S. (2015). Impact of systems modelling on agronomic research and adoption of new practices in smallholder agriculture. Journal of Integrative Agriculture 14(8), 14781489.CrossRefGoogle Scholar
Crawford Fund. (2018). Building awareness and skills for smarter agriculture. Annual Report 2016-2017. Australia: The Crawford Fund. https://www.crawfordfund.org/news/news-building-awareness-skills-smarter-agriculture-annual-report-2016-17-march-2018// (accessed 2 March 2018).Google Scholar
Davila, F., Sloan, T. and van Kerkhoff, L. (2016). Knowledge Systems and RAPID Framework for Impact Assessments. ACIAR Impact Assessment Series Report No. 92. Canberra: Australian Centre for International Agricultural Research. 110 pp.Google Scholar
Dhehibi, B., Nejatian, A., Al-Wahaibi, H., Atroosh, K., Al Yafei, M.S., Al Otaibi, A., Al Hendi, M. and Belgacem, A.O. (2017). Adoption and factors affecting farmer’s adoption of technologies in farming system: a case study of improved technologies in ICARDA’s Arabian Peninsula Regional Program. Journal of Sustainable Development 10(6), 113.CrossRefGoogle Scholar
Dixon, J., Gulliver, A., Gibbon, D. and Hall, M. (2010). Farming Systems and Poverty: Improving Farmers’ Livelihoods in a Changing World (English). Washington, DC: World Bank. http://documents.worldbank.org/curated/en/126251468331211716/Farming-systems-and-poverty-improving-farmers-livelihoods-in-a-changing-world (accessed 7 April 2019).Google Scholar
Douthwaite, B. and Hoffecker, E. (2017). Towards a complexity-aware theory of change for participatory research programs working within agricultural innovation systems. Agricultural Systems 155, 88102.CrossRefGoogle Scholar
Farquharson, R.J., Martin, R.J., McCorkell, B., Scott, J.F., Sotheary, E.L., Phaloeun, C., Sophors, H., Sinath, S., Monida, C., Sinarong, S. and Sokun, B. (2013). Characteristics of an agricultural innovation and incentives for adoption: Rhizobium in Cambodia. International Journal of Environmental and Rural Development 4(2), 4449.Google Scholar
Feder, G. and Zilberman, D. (1985). Adoption of Agricultural Innovations in Developing Countries: A Survey. Washington, DC: World Bank.CrossRefGoogle Scholar
Fineman, M., Fenton, N. and Radlinski, L. (2009). Modelling Project Trade-Off Using Bayesian Networks. New York, NY: IEEE. e-ISBN: 978-1-4244-4507-3 (accessed 10 April 2018).CrossRefGoogle Scholar
Food and Agriculture Organization of the United Nations (2012). The State of Food and Agriculture: Investing in Agriculture for a Better Future. Rome: Food and Agriculture Organization of the United Nations.Google Scholar
Gabb, S., Bell, L., Basuno, E., Prestwidge, D., Prior, J. and Guppy, C. (2017). Whole farm impacts of forage legumes in smallholder crop-livestock systems. Proceedings of the 18th Australian Society of Agronomy Conference, 24–28 September 2017, Ballarat, Australia. http://www.agronomyaustraliaproceedings.org/ (accessed 2 March 2018).Google Scholar
Giller, K.E., Witter, E., Corbeels, M. and Tittonell, P. (2009). Conservation agriculture and smallholder farming in Africa: the heretics’ view. Field Crops Research 114, 2334.CrossRefGoogle Scholar
Hardaker, J.B., Lien, G., Anderson, J.R. and Huirne, R.B.M. (2015). Coping with Risk in agriculture: Applied Decision Analysis, 3rd Edn. Wallingford, Oxfordshire: CABI Pub.CrossRefGoogle Scholar
HarvestChoice. (1995). DREAM (Dynamic Research Evaluation for Management 3.1). Washington, DC: International Food Policy Research Institute. http://harvestchoice.org/node/678 (accessed 8 April 2018).Google Scholar
Herrero, M., Gonzales-Estrada, E., Thornton, P.K., Quiros, C., Waithaka, M.M., Ruiz, R. and Hoogenboom, G. (2007). IMPACT: generic house-hold level databases and diagnostic tools for integrated crop-livestock systems analysis. Agricultural Systems 92, 240265.CrossRefGoogle Scholar
Holzworth, D.P., Huth, N. I., deVoil, P.G., Zurcher, E.J., Herrmann, N. I., McLean, G., Chenu, K., van Oosterom, E.J., Snow, V., Murphy, C., Moore, A.D., Brown, H., Whish, J.P.M., Verrall, S., Fainges, J., Bell, L.W., Peake, A.S., Poulton, P.L., Hochman, Z., Thorburn, P.J., Gaydon, D.S., Dalgliesh, N.P., Rodriguez, D., Cox, H., Chapman, S., Doherty, A., Teixeira, E., Sharp, J., Cichota, R., Vogeler, I., Li, F.Y., Wang, E., Hammer, G.L., Robertson, M.J., Dimes, J.P., Whitbread, A.M., Hunt, J., van Rees, H., McClelland, T., Carberry, P.S., Hargreaves, J.N.G., MacLeod, N., McDonald, C., Harsdorf, J., Wedgwood, S. and Keating, B.A. (2014). APSIM - Evolution towards a new generation of agricultural systems simulation. Environmental Modelling and Software 62, 327350.CrossRefGoogle Scholar
Kahan, D. (2008). Managing risk in farming. FAO Internal Report 3 - Farm management extension guide. Rome: Food and Agriculture Organization of the United Nations. http://www.fao.org/uploads/media/3-ManagingRiskInternLores.pdf (accessed 2 March 2018).Google Scholar
Khodakarami, V., Fenton, N. and Neil, M. (2007). Project Scheduling: Improved approach to incorporate uncertainty using Bayesian Networks. Project Management Journal 38(2), 3949.CrossRefGoogle Scholar
Komarek, A.M., Bell, L.W., Whish, J.P., Robertson, M.J. and Bellotti, W.D. (2015). Whole-farm economic, risk and resource-use trade-offs associated with integrating forages into crop–livestock systems in western China. Agricultural Systems 133, 6372.CrossRefGoogle Scholar
Kuehne, G., Llewellyn, R., Pannell, D.J., Wilkinson, R., Dolling, P., Ouzman, J. and Ewing, M. (2017). Predicting farmer uptake of new agricultural practices: a tool for research, extension and policy. Agricultural Systems 156, 115125.CrossRefGoogle Scholar
Kumar, S., Sravya, M., Pramanik, S., Dakshina, M.K., Balaji, N.B., Samuel, J., Prestwidge, D. and Whitbread, A. (2017). Potential for enhancing farmer income in semi-arid Telangana: A multi-model systems approach. Agricultural Economic Research Review 30, 300. ISSN 0971-3441.Google Scholar
Lindner, R. (1987). Adoption and diffusion of technology: an overview. Technological Change in Postharvest Handling and Transportation of Grains in the Humid Tropics. Bangkok, Thailand: ACIAR. http://aciar.gov.au/files/node/2300/technological_change_in_postharvest_handling_and_t_17625.pdf (accessed 2 March 2019).Google Scholar
Lisson, S., MacLeod, N., McDonald, C., Corfield, J., Pengelly, B., Wirajaswadi, L., Rahman, R., Bahar, S., Padjung, R. and Razak, N. (2010). A participatory, farming systems approach to improving Bali cattle production in the smallholder crop–livestock systems of Eastern Indonesia. Agricultural Systems 103, 486497.CrossRefGoogle Scholar
Mayberry, D., Ash, A.J., Prestwidge, D., Godde, C.M., Henderson, B., Duncan, A., Blummel, M., Ramana Reddy, Y. and Herrero, M. (2017). Yield gap analyses to estimate attainable bovine milk yields and evaluate options to increase production in Ethiopia and India. Agricultural Systems 155, 4351.CrossRefGoogle ScholarPubMed
Mayberry, D., Ash, A.J., Prestwidge, D. and Herrero, M. (2018). Closing yield gaps in smallholder goat production systems in Ethiopia and India. Livestock Science 214, 238244.CrossRefGoogle ScholarPubMed
McDonald, C.K., MacLeod, N., Lisson, S. and Corfield, J. (2019). The Integrated Analysis Tool (IAT) — A model for the evaluation of crop-livestock and socio-economic interventions in smallholder farming systems. Agricultural Systems 176, 176189.CrossRefGoogle Scholar
Monjardino, M., Hochman, Z. and Horan, H. (2019). Yield potential determines Australian wheat growers’ capacity to close yield gaps while mitigating economic risk. Agronomy for Sustainable Development. doi: 10.1007/s13593-019-0595-xCrossRefGoogle Scholar
Monjardino, M., Philp, J., Kuehne, G., Denton, M., Phimphachanhvongsod, V. and Sihathep, V. (2020). Quantifying the value of adopting a post-rice legume crop to intensify mixed smallholder farms in Southeast Asia. Agricultural Systems 177. doi: 10.1016/j.agsy.2019.102690CrossRefGoogle Scholar
Mupangwa, W., Mutenje, M., Thierfelder, C. and Nyagumbo, I. (2016). Are conservation agriculture (CA) systems productive and profitable options for smallholder farmers in different agro-ecoregions of Zimbabwe? Renewable Agriculture and Food Systems 32, 117.Google Scholar
Muthoni, F.K., Guob, Z., Bekundaa, M., Sseguyac, H., Kizitod, F., Baijukyae, F. and Hoeschle-Zeledonf, I. (2017). Sustainable recommendation domains for scaling agricultural technologies in Tanzania. Land Use Policy 66, 3448.CrossRefGoogle Scholar
Mwinuka, L., Mutabazi, K.D., Graef, F., Sieber, S., Makindara, J., Kimaro, A. and Uckert, G. (2017). Simulated willingness of farmers to adopt fertilizer micro-dosing and rainwater harvesting technologies in semi-arid and sub-humid farming systems in Tanzania. Food Security 9, 12371253.CrossRefGoogle Scholar
Ndah, H.T., Schuler, J., Uthes, S., Zander, P., Traore, K., Gama, M.S., Nyagumbo, I., Triomphe, B., Sieber, S., Corbeels, M. (2014). Adoption potential of conservation agriculture practices in sub-Saharan Africa: results from five case studies. Environmental Management 53, 620635.CrossRefGoogle ScholarPubMed
Parsons, D., McDonald, C., Ba, N.X., Tuan, D.T., Lisson, S., Corfield, J., Phung, L.D., Quan, N.H., Van, N.H., Ngoan, L.D. and Lane, P. (2012). Improving cattle profitability in mixed crop-livestock systems in south central coastal Vietnam using an integrated modelling approach. Report to the Australian Centre of International Agricultural Research (ACIAR). http://aciar.gov.au/files/node/13992/improving_cattle_profitability_in_mixed_crop_lives_65276.pdf (accessed 2 March 2019).Google Scholar
Reynolds, M., Kropff, M., Crossa, J., Koo, J., Kruseman, G., Molero Milan, A., Rutkoski, J., Schulthess, U., Balwinder-Singh, , Sonder, K., Tonnang, H. and Vadez, V. (2018). Role of Modelling in International Crop Research: Overview and Some Case Studies. Agronomy 8, 291336.CrossRefGoogle Scholar
Rich, K.M., Ross, R.B., Baker, A.D. and Negassa, A. (2011). Quantifying value chain analysis in the context of livestock systems in developing countries. Food Policy 36, 214222.CrossRefGoogle Scholar
Rigolot, C., Watson, I., Herrero, M., Delma, B.J., Vall, E., Andrieu, N., Yakouba, B., Ouedrago, S., Ziebe, R., Dowe, V., Kolyang, T., Prestwidge, D., McDonald, C.K., Stirzaker, R., Bruce, C. and Carberry, P. (February 2015). Modelling households and value chains: Complementary methods for learning and evaluation in innovations platforms. Conférence Internationale sur les systèmes d’innovation en Afrique de l’Ouest et du Centre, Saly-Portudal, Senegal.Google Scholar
Rogers, E. (2003). Diffusion of Innovations. New York: Free Press.Google Scholar
Rosenzweig, C., Jones, J.W., Hatfield, J.L., Ruane, A.C., Boote, K.J., Thorburn, P., Antle, J.M., Nelson, G.C., Porter, C., Janssen, S., Asseng, S., Basso, B., Ewert, F., Wallach, D., Baigorria, G. and Winter, J.M. (2013). The Agricultural Model Intercomparison and Improvement Project (AgMIP): protocols and pilot studies. Agricultural and Forest Meteorology 170, 166182.CrossRefGoogle Scholar
Schmid, J., Brummer, M. and Taylor, M.Z. (2017). Innovation and alliances. Review of Policy Research 34(5), 588616.CrossRefGoogle Scholar
Schreinemachers, P., Squeros, T. and Lukumay, P.J. (2017). International research on vegetable improvement in East and Southern Africa: adoption, impact and returns. Agricultural Economics 48, 707717.CrossRefGoogle Scholar
Shafiullah, G.M. (2012). MSc Thesis. Wagga Wagga, Australia: Charles Sturt University.Google Scholar
Sheahan, M. and Barrett, C.B. (2017). Ten striking facts about agricultural input use in Sub-Saharan Africa. Food Policy 67, 1225.CrossRefGoogle ScholarPubMed
Smits, R.E.H.M. (2002). Innovation studies in the 21st century. Technology Forecasting and Social Change 69, 861883.CrossRefGoogle Scholar
Valdivia, R.O., Antle, J.M. and Stoorvogel, J.J. (2017). Designing and evaluating sustainable development pathways for semi-subsistence crop-livestock systems: lessons from Kenya. Agricultural Economics 48(S1), 1126.CrossRefGoogle Scholar
Van Wijk, M.T., Tittonell, P., Ruffino, M.C., Herrero, M., Pacini, C., de Ridder, N. and Giller, K.E. (2009). Identifying key entry points for strategic management of smallholder farming systems in sub-Saharan Africa using the dynamic farmscale simulation model NUANCES-FARMSIM. Agricultural Systems 102, 89101.CrossRefGoogle Scholar
Ward, P.S., Bell, A.R., Droppelmann, K. and Benton, T.G. (2018). Early adoption of conservation agriculture practices: understanding partial compliance in programs with multiple adoption decisions. Land Use Policy 70, 2737.CrossRefGoogle Scholar
World Bank. (2018). World Development Report 2018: Agriculture for Development. Washington, DC. https://siteresources.worldbank.org/INTWDR2018/Resources/WDR_00_book.pdf (accessed 2 May 2019).Google Scholar
Yet, B., Constantinou, A., Fenton, N., Neil, M., Luedeling, E. and Shepherd, K. (2016). A Bayesian network framework for project cost, benefit and risk analysis with an agricultural development case study. Expert Systems with Applications 60, 141155.CrossRefGoogle Scholar
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