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WHOSE GAP COUNTS? THE ROLE OF YIELD GAP ANALYSIS WITHIN A DEVELOPMENT-ORIENTED AGRONOMY

Published online by Cambridge University Press:  05 July 2018

JOÃO VASCO SILVA*
Affiliation:
Plant Production Systems, Wageningen University, Wageningen, the Netherlands
JOSHUA J. RAMISCH
Affiliation:
School of International Development and Global Studies, University of Ottawa, Ottawa, Canada

Summary

Yield gaps have become a useful tool for guiding development-related agronomy, especially in the global South. While critics have challenged some aspects of the yield gap methodology, and the relevance of food security advocacy based on yield gaps, very few studies question the actual relevance, application and scalability of yield gaps for smallholder farmers (and researchers) in the tropics. We assess these limitations using two contrasting case studies: maize-based farming systems in Western Kenya and rice-based farming systems in Central Luzon, the Philippines. From these two cases, we propose improvements in the use of yield gaps that would acknowledge both the riskiness of crop improvement options and the role that yield increases might play within local livelihoods. Participatory research conducted in Western Kenya calls into question the actual use and up-scaling of yield measurements from on-station agronomic trials to derive estimates of actual and water-limited yields in the region. Looking at maize yield gaps as cumulative probabilities demonstrates the challenges of assessing the real magnitude of yield gaps in farmers’ fields and of deciding whose yield gaps count for agricultural development in Kenya. In the case of rice-based farming systems, we use a historical dataset (1966–2012) to assess changes in rice yields, labour productivity, gross margin and rice self-sufficiency in Central Luzon, the Philippines. While large rice yield gaps persist here, there appear to be few incentives to close that gap once we consider the position of crop production within local livelihoods. In this context, economic returns to labour for farm work were marginal: labour productivity increased over time in both wet and dry seasons, but gross margins decreased in the wet season while no trend was observed for the dry season. Since most households were rice self-sufficient and further increases in crop production would offer minimal returns while relying increasingly on hired labour, we question who should close which yield gap. Our case studies show the importance of contextualising yield gaps within the broader livelihood context in which farmers operate. We propose that this should be done at farm and/or farming systems level while considering the risks associated with narrowing yield gaps and looking into multiple performance indicators.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2018 

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References

REFERENCES

Allan, A. Y. (1971). The Influence of Agronomic Factors on Maize Yields in Western Kenya with Special Reference to Time of Planting. Ph.D. thesis, Nairobi: University of East Africa.Google Scholar
Angulo, C., Becker, M. and Wassmann, R. (2012). Yield gap analysis and assessment of climate-induced yield trends of irrigated rice in selected provinces of the Philippines. Journal of Agriculture and Rural Development in the Tropics and Subtropics 113:6168.Google Scholar
Barker, R. and Levine, G. (2012). Water Productivity in Context: The experiences of Taiwan and The Philippines over the past half-century, 33p,. Colombo, Sri Lanka: International Water Management Institute. IWMI Research Report 145. doi:10.5337/2012.206.Google Scholar
Beddow, J. M., Hurley, T. M., Pardey, P. G. and Alston, J. (2015). Rethinking Yield Gaps. Staff Papers 201093, University of Minnesota, Department of Applied Economics.Google Scholar
Bhatia, V., Singh, P., Wani, S., Chauhan, G., Rao, A. K., Mishra, A. and Srinivas, K. (2008). Analysis of potential yields and yield gaps of rainfed soybean in India using CROPGRO-Soybean model. Agricultural and Forest Meteorology 148:12521265.Google Scholar
Boling, A., Tuong, T., van Keulen, H., Bouman, B., Suganda, H. and Spiertz, J. (2010). Yield gap of rainfed rice in farmers’ fields in Central Java, Indonesia. Agricultural Systems 103:307315.Google Scholar
Brooks, S., Thompson, J., Odame, H., Kibaara, B., Nderitu, S., Karin, F. and Millstone, E. (2009). Environmental Change and Maize Innovation in Kenya: Exploring Pathways In and Out of Maize. Technical report, STEPS working paper, 36, STEPS Centre, Brighton.Google Scholar
Bunei, E., Rono, J. and Chessa, S. (2013). Factors influencing farm crimes in Kenya: Opinions and experiences from farmers. International Journal of Rural Criminology 2:75100.Google Scholar
Cabling, J. M. and Dawe, D. C. (2006). Why does the Philippines import rice? Meeting the challenge of trade liberalization. In Filipino Farmers Receive High Palay Prices, 911. Los Baños, Philippines: International Rice Research Institute (IRRI).Google Scholar
Cassman, K. G. and Pingali, P. L. (1995). Intensification of irrigated rice systems: Learning from the past to meet future challenges. GeoJournal 35:299305.Google Scholar
Dawe, D. C. (2006). The Philippines imports rice because it is an island nation. Why Does the Philippines Import Rice? Meeting the Challenge of Trade Liberalization, 38. International Rice Research Institute.Google Scholar
Dawe, D. C., Moya, P. F. and Casiwan, C. B. (2006). Why Does the Philippines Import rice? Meeting the Challenge of Trade Liberalization. Los Baños, Philippines: International Rice Research Institute.Google Scholar
de Koeijer, T., Wossink, G., van Ittersum, M., Struik, P. and Renkema, J. (1999). A conceptual model for analysing input–output coefficients in arable farming systems: from diagnosis towards design. Agricultural Systems 61: 3344.Google Scholar
Dobermann, A., Witt, C., Dawe, D., Abdulrachman, S., Gines, H., Nagarajan, R., Satawathananont, S., Son, T., Tan, P., Wang, G., Chien, N., Thoa, V., Phung, C., Stalin, P., Muthukrishnan, P., Ravi, V., Babu, M., Chatuporn, S., Sookthongsa, J., Sun, Q., Fu, R., Simbahan, G. and Adviento, M. (2002). Site-specific nutrient management for intensive rice cropping systems in Asia. Field Crops Research 74:3766.Google Scholar
Dzanku, F. M., Jirstrom, M. and Marstorp, H. (2015). Yield gap-based poverty gaps in rural Sub-Saharan Africa. World Development 67:336362.Google Scholar
Ellis, F. (1993). Peasant Economics: Farm Households and Agrarian Development, 309. Cambridge: Cambridge University Press.Google Scholar
Estudillo, J. P. and Otsuka, K. (1999). Green revolution, human capital, and off-farm employment: Changing sources of income among farm households in Central Luzon, 1966–1994. Economic Development and Cultural Change 47:497523.Google Scholar
FAO/FPMA (2017). Food Price Monitoring and Analysis (FPMA): http://www.fao.org/giews/pricetool/.Google Scholar
FAOSTAT (2017). Food and Agriculture Data: http://www.fao.org/faostat/en/.Google Scholar
Frelat, R., Lopez-Ridaura, S., Giller, K. E., Herrero, M., Douxchamps, S., Djurfeldt, A. A., Erenstein, O., Henderson, B., Kassie, M., Paul, B. K., Rigolot, C., Ritzema, R. S., Rodriguez, D., van Asten, P. J. A. and van Wijk, M. T. (2016). Drivers of household food availability in sub-Saharan Africa based on big data from small farms. Proceedings of the National Academy of Sciences of the United States of America 113:458463.Google Scholar
French, R. J. and Schultz, J. E. (1984). Water use efficiency of wheat in a Mediterranean-type environment. I. The relation between yield, water use and climate. Australian Journal of Agricultural Research 35:743764.Google Scholar
FURP (1986). The Fertilizer Use and Recommendations Project (FURP): Preliminary Project Proposal Draft. Nairobi, Kenya: Ministry of Agriculture. Available at http://www.kalro.org:8080/repository/handle/0/6914.Google Scholar
FURP (1987). The Fertilizer Use and Recommendations Project (FURP) Final Report: Annex III - Volume 5. Busia district. Nairobi, Kenya: Ministry of Agriculture. Available at http://www.kalro.org:8080/repository/handle/0/6234.Google Scholar
FURP (1993). The Fertilizer Use and Recommendations Project (FURP): Extended Phase II - Vol. 9. Busia district. Nairobi, Kenya: Ministry of Agriculture. Available at http://www.kalro.org:8080/repository/handle/0/6479.Google Scholar
Gerhart, J. (1975). The Diffusion of Hybrid Maize in Western Kenya. Technical report, CIMMYT Studies in the Adoption of New Technologies. Mexico: CIMMYT. Available at https://repository.cimmyt.org/xmlui/handle/10883/708.Google Scholar
Giller, K., Tittonell, P., Rufino, M., van Wijk, M., Zingore, S., Mapfumo, P., Adjei-Nsiah, S., Herrero, M., Chikowo, R., Corbeels, M., Rowe, E., Baijukya, F., Mwijage, A., Smith, J., Yeboah, E., van der Burg, W., Sanogo, O., Misiko, M., de Ridder, N., Karanja, S., Kaizzi, C., K’ungu, J., Mwale, M., Nwaga, D., Pacini, C. and Vanlauwe, B. (2011). Communicating complexity: Integrated assessment of trade-offs concerning soil fertility management within African farming systems to support innovation and development. Agricultural Systems 104: 191203.Google Scholar
GoK (2015). Economic Review of Agriculture - 2015. Nairobi, Kenya: Ministry of Agriculture, Livestock and Fisheries.Google Scholar
Grace, K., Husak, G. and Bogle, S. (2014). Estimating agricultural production in marginal and food insecure areas in Kenya using very high resolution remotely sensed imagery. Applied Geography 55:257265.Google Scholar
Grassini, P., van Bussel, L. G., Wart, J. V., Wolf, J., Claessens, L., Yang, H., Boogaard, H., de Groot, H., van Ittersum, M. K. and Cassman, K. G. (2015). How good is good enough? Data requirements for reliable crop yield simulations and yield gap analysis. Field Crops Research 177:4963.Google Scholar
Hassan, R., Murithi, F. and Kamau, G. (1998a). Determinants of fertilizer use and the gap between farmers yields and potential yields in Kenya. In Maize Technology Development and Transfer: A GIS Application for Research Planning in Kenya, 137162. Nairobi, Kenya: CAB International.Google Scholar
Hassan, R., Onyango, R. and Rutto, J. (1998b). Relevance of maize research in Kenya to maize production problems perceived by farmers. In Maize Technology Development and Transfer: A GIS Application for Research Planning in Kenya, 7188. Nairobi, Kenya: CAB International.Google Scholar
Herdt, R. W. (1979). An overview of the constraints project results. In Farm-Level Constraints to High Rice yields in Asia: 1974–1977, 411. Los Baños, Philippines: International Rice Research Institute.Google Scholar
Herdt, R. W. and Mandac, A. M. (1981). Modern Technology and Economic Efficiency of Philippine Rice Farmers. Chicago: University of Chicago.Google Scholar
Hochman, Z., Gobbett, D., Holzworth, D., McClelland, T., van Rees, H., Marinoni, O., Garcia, J. N. and Horan, H. (2012). Quantifying yield gaps in rainfed cropping systems: A case study of wheat in Australia. Field Crops Research 136:8596.Google Scholar
Jaetzold, R. and Schmidt, H. (1982). Farm Management Handbook of Kenya Vol. II - Natural Conditions and Farm Management Information. Part A West Kenya (Nyanza and Western Provinces). Nairobi, Kenya: Ministry of Agriculture. Available at http://library.wur.nl/isric/fulltext/isricu_i00023897_001.pdf.Google Scholar
Jaetzold, R., Schmidt, H., Hornetz, B. and Shisanya, C. (2009). Farm management handbook of Kenya Vol. II - Part A west Kenya subpart A2 Nyanza province. Nairobi, Kenya: Ministry of Agriculture. Available at http://www.fao.org/fileadmin/user_upload/drought/docs/FMHB%20Nyanza%20Province.pdf.Google Scholar
Janssen, B., Guiking, F., van der Eijk, D., Smaling, E., Wolf, J. and van Reuler, H. (1990). A system for quantitative evaluation of the fertility of tropical soils (QUEFTS). Geoderma 46:299318.Google Scholar
Kang’ethe, E. (2011). Situation Analysis: Improving Food Safety in the Maize Value Chain in Kenya. Working paper. Rome: FAO. Available at http://www.fao.org/fileadmin/user_upload/agns/pdf/WORKING_PAPER_AFLATOXIN_REPORTDJ10thOctober.pdf.Google Scholar
Kassie, B., Ittersum, M.V., Hengsdijk, H., Asseng, S., Wolf, J. and Roetter, R. (2014). Climate-induced yield variability and yield gaps of maize (Zea mays l.) in the Central Rift Valley of Ethiopia. Field Crops Research 160:4153.Google Scholar
Kerkvliet, B. (1990). Everyday Politics in the Philippines: Class and Status Relations in a Central Luzon Village. Berkeley: University of California Press.Google Scholar
Kibaara, B., Ariga, J., Olwande, J. and Jayne, T. (2008). Trends in Agricultural Productivity: 1997–2007. Tegemeo Institute working paper, WPS 31/2008. Nairobi, Kenya: Egerton University.Google Scholar
Kimani, V. and Gruere, G. (2010). Implications of import regulations and information requirements under the Cartagena protocol on biosafety for GM commodities in Kenya. AgBioForum 13:222241.Google Scholar
Laborte, A. G., de Bie, K. C., Smaling, E. M., Moya, P. F., Boling, A. A. and van Ittersum, M. K. (2012). Rice yields and yield gaps in Southeast Asia: Past trends and future outlook. European Journal of Agronomy 36: 920.Google Scholar
Lampayan, R., Bouman, B., de Dios, J., Espiritu, A., Soriano, J., Lactaoen, A., Faronilo, J. and Thant, K. (2010). Yield of aerobic rice in rainfed lowlands of the Philippines as affected by nitrogen management and row spacing. Field Crops Research 116:165174.Google Scholar
Lansigan, F., de los Santos, W. and Coladilla, J. (2000). Agronomic impacts of climate variability on rice production in the Philippines. Agriculture, Ecosystems & Environment 82:129137.Google Scholar
Licker, R., Johnston, M., Foley, J. A., Barford, C., Kucharik, C. J., Monfreda, C. and Ramankutty, N. (2010). Mind the gap: How do climate and agricultural management explain the ‘yield gap’ of croplands around the world? Global Ecology and Biogeography 19:769782.Google Scholar
Lobell, D. B., Cassman, K. G. and Field, C. B. (2009). Crop yield gaps: Their importance, magnitudes, and causes. Annual Review of Environment and Resources 34:179204.Google Scholar
Loevinsohn, M. E., Bandong, J. B. and Alviola, A. A. (1993). Asynchrony in cultivation among Philippine rice farmers: Causes and prospects for change. Agricultural Systems 41:419439.Google Scholar
Meng, Q., Hou, P., Wu, L., Chen, X., Cui, Z. and Zhang, F. (2012). Understanding production potentials and yield gaps in intensive maize production in China. Field Crops Research 143:9197.Google Scholar
Moya, P. F., Dawe, D., Pabale, D., Tiongco, M., Chien, N. V., Devarajan, S., Djatiharti, A., Lai, N. X., Niyomvit, L., Ping, H. X., Redondo, G. and Wardana, P. (2004). The economics of intensively irrigated rice in Asia. In: Increasing Productivity of Intensive Rice Systems through Site-Specific Nutrient Management (Eds Dobermann, A. and Witt, C.). Enfield, N. H. (USA) and Los Baños (Philippines): Science Publishers, Inc., and International Rice Research Institute.Google Scholar
Moya, P. F., Kajisa, K., Barker, R., Mohanty, S., Gascon, F. and Valentin, M. S. (2015). Changes in Rice Farming the Philippines: Insights From Five Decades of a Jousehold Level Survey. Los Baños, Philippines: International Rice Research Institute.Google Scholar
Njoroge, K., Mugo, S. N. and Laboso, A. K. (1995). Maize Variety National Performance Trials. Nairobi, Kenya: Kenya Agricultural Research Institute.Google Scholar
Nyoro, J. K., Kirimi, L. and Jayne, T. S. (2004). Competitiveness of Kenyan and Ugandan Maize Production: Challenges for the Future, Food Security Collaborative Working Papers 55158, Michigan State University, Department of Agricultural, Food, and Resource Economics.Google Scholar
van Oort, P. A. J., Saito, K., Dieng, I., Grassini, P., Cassman, K. G. and van Ittersum, M. K. (2016). Can yield gap analysis be used to inform R&D prioritisation? Global Food Security. 12:109118.Google Scholar
PDA (2012). Food Staples Sufficiency Program 2011–2016. Technical report, Department of Agriculture, The Philippines. Available at http://www.pinoyrice.com/wp-content/uploads/Food-Staples-Sufficiency-Program.pdf.Google Scholar
PSA (2017). CountrySTAT Philippines. Available at: http://psa.gov.ph/ (accessed 15.01.2017).Google Scholar
Ramisch, J. J. (2011). Experiments as ‘performances’: Interpreting farmers’ soil fertility management practices in western Kenya. In Knowing Nature: Conversations at the Intersection of Political Ecology and Science Studies, 280295. Chicago: University of Chicago Press.Google Scholar
Ramisch, J. J. (2014). ‘They don’t know what they are talking about’: Learning from the dissonances in dialogue about soil fertility knowledge and experimental practice in western Kenya. Geoforum 55:120132.Google Scholar
Ramisch, J. J. (2016). ‘Never at ease’: Cellphones, multilocational households, and the metabolic rift in western Kenya. Agriculture and Human Values 33:979995.Google Scholar
Ramisch, J. J., Misiko, M. T., Ekise, I. E. and Mukalama, J. B. (2006). Strengthening ‘folk ecology’: community-based learning for integrated soil fertility management, western Kenya. International Journal of Agricultural Sustainability 4:154168.Google Scholar
Roetter, R. and van Keulen, H. (1997). Variations in yield response to fertilizer application in the tropics: II. Risks and opportunities for smallholders cultivating maize on Kenya’s arable land. Agricultural Systems 53:6995.Google Scholar
Rojas, O. (2007). Operational maize yield model development and validation based on remote sensing and agro-meteorological data in Kenya. International Journal of Remote Sensing 28:37753793.Google Scholar
Silva, J. V., Reidsma, P., Laborte, A.G. and van Ittersum, M. K. (2017). Explaining rice yields and yield gaps in Central Luzon, Philippines: An application of stochastic frontier analysis and crop modelling. European Journal of Agronomy 82:Part B, 223241.Google Scholar
Silva, J. V., Reidsma, P., Velasco, M. L., Laborte, A. G. and van Ittersum, M. K. (2018). Intensification of rice-based farming systems in Central Luzon, Philippines: Constraints at field, farm and regional levels. Agricultural Systems 165:5570.Google Scholar
Smale, M. and Jayne, T. S. (2003). Maize in Eastern and Southern Africa: ‘Seeds’ of Success in Retrospect. Technical report, IFPRI, EPTD Discussion Paper #97.Google Scholar
Smaling, E. M. A. and Janssen, B. H. (1993). Calibration of QUEFTS, a model predicting nutrient uptake and yields from chemical soil fertility indices. Geoderma 59:2144.Google Scholar
Stuart, A. M., Pame, A. R. P., Silva, J. V., Dikitanan, R. C., Rutsaert, P., Malabayabas, A. J. B., Lampayan, R. M., Radanielson, A. M. and Singleton, G. R. (2016). Yield gaps in rice-based farming systems: Insights from local studies and prospects for future analysis. Field Crops Research 194:4356.Google Scholar
Studwell, J. (2013). How Asia Works: Success and Failure in the World’s Most Dynamic Region. New York: Grove Press.Google Scholar
Sumberg, J. (2012). Mind the (yield) gap(s). Food Security 4:509518.Google Scholar
Takahashi, K. and Otsuka, K. (2009). The increasing importance of nonfarm income and the changing use of labor and capital in rice farming: the case of Central Luzon, 1979–2003. Agricultural Economics 40:231242.Google Scholar
Tittonell, P. and Giller, K. E. (2013). When yield gaps are poverty traps: The paradigm of ecological intensification in African smallholder agriculture. Field Crops Research 143:7690.Google Scholar
Tittonell, P., Vanlauwe, B., Corbeels, M. and Giller, K. (2008). Yield gaps, nutrient use efficiencies and response to fertilisers by maize across heterogeneous smallholder farms of western kenya. Plant and Soil 313:1937.Google Scholar
van Dijk, M., Morley, T., Jongeneel, R., van Ittersum, M. K., Reidsma, P. and Ruben, R. (2017). Disentangling agronomic and economic yield gaps: An integrated framework and application. Agricultural Systems 154: 9099.Google Scholar
van Ittersum, M. K., van Bussel, L. G. J., Wolf, J., Grassini, P., van Wart, J., Guilpart, N., Claessens, L., de Groot, H., Wiebe, K., Mason-DCroz, D., Yang, H., Boogaard, H., van Oort, P. A. J., van Loon, M. P., Saito, K., Adimo, O., Adjei-Nsiah, S., Agali, A., Bala, A., Chikowo, R., Kaizzi, K., Kouressy, M., Makoi, J. H. J. R., Ouattara, K., Tesfaye, K. and Cassman, K. G. (2016). Can sub-Saharan Africa feed itself? Proceedings of the National Academy of Sciences of the United States of America 113:1496414969.Google Scholar
van Ittersum, M. K., Cassman, K. G., Grassini, P., Wolf, J., Tittonell, P. and Hochman, Z. (2013). Yield gap analysis with local to global relevance – A review. Field Crops Research 143:417.Google Scholar
van Ittersum, M. K. and Rabbinge, R. (1997). Concepts in production ecology for analysis and quantification of agricultural input–output combinations. Field Crops Research 52:197208.Google Scholar
Vanlauwe, B., Coe, R. and Giller, K. E. (2016). Beyond averages: New approaches to understand heterogeneity and risk of technology success or failure in smallholder farming. Experimental Agriculture 123. doi:https://doi.org/10.1017/S0014479716000193.Google Scholar
Vanlauwe, B., Descheemaeker, K., Giller, K. E., Huising, J., Merckx, R., Nziguheba, G., Wendt, J. and Zingore, S. (2015). Integrated soil fertlity management in sub-Saharan Africa: Unravelling local adaptation. SOIL 1:491508.Google Scholar
Vanlauwe, B., Tittonell, P. and Mukalama, J. (2007). Within-farm soil fertility gradients affect response of maize to fertiliser application in western Kenya. In Advances in Integrated Soil Fertility Management in sub-Saharan Africa: Challenges and Opportunities, 121132. Dordrecht, the Netherlands: Springer.Google Scholar
van Wart, J., van Bussel, L. G., Wolf, J., Licker, R., Grassini, P., Nelson, A., Boogaard, H., Gerber, J., Mueller, N. D., Claessens, L., van Ittersum, M.K. and Cassman, K. G. (2013). Use of agro-climatic zones to upscale simulated crop yield potential. Field Crops Research 143:4455.Google Scholar
Wairegi, L. W., van Asten, P. J., Tenywa, M. M. and Bekunda, M. A. (2010). Abiotic constraints override biotic constraints in East African highland banana systems. Field Crops Research 117:146153.Google Scholar
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