Rainfall is not the most limiting factor to maize (Zea mays L.) production in intermediate rainfall regions of Zambia. Lessons from Choma District

Authors

  • Dr. Kabwe Harnadih Mubanga The University of Zambia
  • Prof. Martin Joachim Steyn University of Pretoria

DOI:

https://doi.org/10.47941/jap.377
Abstract views: 283
PDF downloads: 70

Keywords:

Maize yield, maize stress index, evapotranspiration, smallholder farmers, Soil Water Balance (SWB) model

Abstract

Purpose: This study was based on the following objectives; (1) to investigate the sufficiency of rainfall received in Choma by assessing the differences in the precipitation received (PPT) against the potential evapotranspiration (PET) and actual evapotranspiration (ETa) for maize, and (2) to estimate potential for maize production in Choma under the current rainfall and temperature conditions.

Methodology: The Soil Water Balance (SWB) crop growth model was used to analyze the rainfall-temperature interactions and estimate the maize stress index (SI) for analyses of crop water stress and potential yields (Yp). The relationships involving precipitation, potential and actual evapotranspiration were performed using time series auto regression and Fisher’s least significant difference (LSD).

Findings: Choma was not in a state of water deficit as maize water requirements were lower than precipitation. Maize water stress was destructive when it occurred in the mid than late stages of maize development. Mean precipitation (799.29mm) was higher than mean actual evapotranspiration (719.23 mm), though the difference was insignificant (F = 1.281; p = 0.126). However, potential evapotranspiration for maize in the area was significantly higher than the actual evapotranspiration (mean = 719.23) (F = 5.621; p = 0.012). Less destructive moderately dry periods seldom occurred during the sensitive initial and mid periods of maize development.

Results: Farmers in Choma can potentially increase their rain-fed maize yields from the current 1.89 t/ha/year to 4.9 t/ha/year by managing limiting factors to maize production such as reduced access to fertilizer, declining of soil nutrients, late delivery of inputs, lack of markets, pests and lack of proper nutrient management. The study also showed that management rather than climatic conditions is responsible for the low yields in Choma area.

Unique contribution to theory, practice and policy: The study established a methodology for simulating potential yields of farmers given existing climatic and soil conditions. Policy should concentrate on improving crop management rather than the current concentration on mitigating impacts of climate change as these are not the factors responsible for observed reduced crop yields.

Downloads

Download data is not yet available.

Author Biographies

Dr. Kabwe Harnadih Mubanga, The University of Zambia

Lecturer, School of Natural Science Department of Geography and Environmental Studies, 

Prof. Martin Joachim Steyn, University of Pretoria

Lecturer, Department of Plant Production and Soil Science,

University of Pretoria

References

Alcamo, J., Florke, M. and Marker, M. (2007). Future long-term changes in global water resources driven by socio-economic and climatic changes. Hydrological Sciences Journal 52 (2):247-275.

http://dx.doi.org/10.1623/hysj.52.2.247

Annandale, J.G., Benadé, N., Jovanovic, N.Z., Steyn, J.M. and Du Sautoy, N. (1999). Facilitating Irrigation Scheduling by Means of the Soil Water Balance Model: Water Research Commission (WRC) Report No 753/1/99.

Annandale, J.G., Campbell, G.S., Olivier, F.C. and Jovanovic, N.Z. (2000). Predicting crop water uptake under full and deficit irrigation: An example of pea (Pisum sativum L. cv. Puget). Irrigation Science 19: 65-72

http://dx.doi.org/10.1007/s002710050002

Bejiga, G. (1991). Effect of Sowing Date on the Yield of Lentil (Lens culinaris Medik.). Journal of Agronomy and Crop Science 167 (2):135-140.

http://dx.doi.org/10.1111/j.1439-037X.1991.tb00944.x

CFU. (2007). Conservation Farming and Conservation Agriculture Handbook for HOE Farmer s in Agro-Ecological Regions I & IIa - Flat Culture 2007 Edition. Lusaka, Zambia: Zambia National Farmers Union and Conservation Farming Unit.

Chisanga, C.B. (2019). Chapter 7: Climate change impacts on future millet yields in Zambia, in: Assessing Climate Change Impacts on Future Crop Yields in Zambia. FAO MOSAICC. Lusaka, Zambia, pp. 80–92.

Du Plessis, J. (2003). Maize production. Pretoria: Department of Agriculture, South Africa.

FAO. (2010). Climate Smart Agriculture Policies, practices and financing for food security adaptation and mitigation. Rome: Food and Agricultural Organization of the United Nations.

Fischer RA, Byerlee D, Edmeades GO. (2014). Crop yields and global food security: will yield increase continue to feed the world? Canberra: Australian Centre for International Agricultural Research. Available online from: http://aciar.gov.au/publication/mn158.

Ghanem, M. E., Marrou, H., Biradar, C. and Sinclair, T.R. (2015). Production potential of Lentil (Lens culinaris Medik.) in East Africa. Agricultural Systems 137 (0):24-38.

http://dx.doi.org/10.1016/j.agsy.2015.03.005

GRZ. (2007). The National Adaptation Programme on Action. Lusaka: Ministry of Tourism, Environment and Natural Resources (MTENR).

GRZ. (2016). Second National Agricultural Policy. Ministry of Agriculture and Ministry of Fisheries and Livestock.

IPCC. (2007). Summary for Policymakers. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press.

IPCC. (2014). Climate Change 2014: impacts, adaptation, and vulnerability. Summary for policy makers. In IPCC WGII AR5 Summary for Policymakers. University Press: Cambridge, UK

Jovanovic, N. Z. and Annandale, J. G. (2000). Crop growth model parameters of 19 summer vegetable cultivars for use in mechanistic irrigation scheduling models. Water SA. 26(2): 181-189.

Jovanovic, N. Z. Annandale, J. G., and Hammes, P. S. (2000). Teaching crop physiology with the soil water balance model. Journal of Natural Resources and Life Sciences Education 29:23-30.

Kiniry, J.R., Bean, B., Xie, Y. and Chen, P. (2004). Maize yield potential: critical processes and simulation modeling in a high-yielding environment. Agricultural Systems 82 (1):45-56.

http://dx.doi.org/10.1016/j.agsy.2003.11.006

Mazvimavi, K. (2011). Socio-Economic Analysis of Conservation Agriculture in Southern Africa. In Network Paper No. 2. Rome, Italy: Food and Agriculture Organization of the United Nations, Regional Emergency Office for Southern Africa.

Mubanga, K.H., and Umar, B.B. (2014). Smallholder Farmers’ Responses to Rainfall Variability and Soil Fertility Problems by the Use of Indigenous Knowledge in Chipepo,

Southern Zambia. Journal of Agricultural Science, 6 (6): 75-85.

Mubanga, K. H., and Ferguson, W. (2017). Threats to food sufficiency among smallholder farmers in Choma, Zambia. Food Security, 9,745–758.

Shrestha, R., Turner, N.C., Siddique, K.H.M. and Turner, D.W. (2006). Physiological and seed yield responses to water deficits among lentil genotypes from diverse origins. Australian Journal of Agricultural Research 57 (8):903-915.

http://dx.doi.org/10.1071/AR05204

Siddique, K.H.M, Loss, S.P, and Thomson, B.D. (2003). Cool season grain legumes in dryland Mediterranean environments of Western Australia: significance of early flowering in: Saxena N.P. (Eds.) Management of Agricultural Drought – Agronomic and Genetic Options. Oxford University Press New Delhi.

Sinclair, T.R., Purcell, L.C. and Sneller, C.H. (2004). Crop transformation and the challenge to increase yield potential. Trends in Plant Science 9 (2):70-75.

http://dx.doi.org/10.1016/j.tplants.2003.12.008

Sinclair, T.R., Marrou, H., Soltani, A., Vadez, V. and Chandolu, K.C. (2014). Soybean production potential in Africa. Global Food Security 3 (1):31-40.

http://dx.doi.org/10.1016/j.gfs.2013.12.001

Singels, A., Annandale, J.G., De Jager, J.M., Schulze, R.E., Inman-Bamber, N.G., Durand, W., Van Rensburg, L.D., Van Heerden, P.S., Crosby, C.T., Green, G.C. and Steyn, J.M. (2010). Modelling crop growth and crop water relations in South Africa: Past achievements and lessons for the future. South African Journal of Plant and Soil 27(1): 49-65

http://dx.doi.org/10.1080/02571862.2010.10639970

Soltani, A. and Sinclair, T.R. (2012). Modeling Physiology of Crop Development, Growth and Yield. Wallingford, Oxfordshire, UK: CABI

http://dx.doi.org/10.1079/9781845939700.0000

Syampaku, E.M., Daka, A., Simfukwe, P., Phiri, E., Chisanga, C., Chota, M., (2019). Assessing climate change impacts on future crop yields in Zambia. FAO MOSAICC. Lusaka, Zambia.

Tembo S, and Sitko N. (2013). Technical compendium: descriptive agricultural statistics and analysis for Zambia. Working Paper 76. Lusaka Indaba Agricultural Policy Research Institute (IAPRI).

Thornton, P. and Cramer, L. (2012). Impacts of Climate Change on the Agricultural and Aquatic Systems and Natural Resources within the CGIAR's Mandate. CCAFS Working Paper No. 23. Copenhagen, Denmark: CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS).

Trajkovic, S., Stojnic, V. and Gocic, M. (2011). Minimum weather data requirements for estimating reference evapotranspiration. In Advances in Irrigation, edited by D Hillel. New York, USA.

http://dx.doi.org/10.2298/FUACE1102335T

Umar, B. B., Aune, J. B., Johnsen, F. H. and Lungu, I. O. (2012). Are Smallholder Zambian Farmers Economists? A Dual-Analysis of Farmers' Expenditure in Conservation and Conventional Agriculture Systems. Journal of Sustainable Agriculture 36: 908-929.

http://dx.doi.org/10.1080/10440046.2012.661700

Usman, M. T. and Reason, C. J. C. (2004). Dry spell frequencies and their variability over southern Africa. Climate Research 26:199-211.

http://dx.doi.org/10.3354/cr026199

Vogel, C. (2000). Usable science: an assessment of long-term seasonal forecasts amongst farmers in rural areas of South Africa. South African Geographical Journal 82:107–116.

WMO. (2012). Standardized Precipitation Index User Guide. Geneva, Switzerland: World Meteorological Organization.

World Bank (2019). Zambia Climate-Smart Agriculture Investment Plan. Analyses to support the climate-smart development of Zambia’s agriculture sector. International Bank for Reconstruction and Development / The World Bank. Washington DC.

Downloads

Published

2020-03-11

How to Cite

Mubanga, D. K. H., & Steyn, P. M. J. (2020). Rainfall is not the most limiting factor to maize (Zea mays L.) production in intermediate rainfall regions of Zambia. Lessons from Choma District. Journal of Agricultural Policy, 3(1), 18–40. https://doi.org/10.47941/jap.377

Issue

Section

Articles