Maize Cultivar Specific Parameters for Decision Support System for Agrotechnology Transfer (DSSAT) Application in Tanzania

Abstract

In order to develop basis for tactical or strategic decision making towards agricultural productivity improvement in Tanzania, a new approach in which crop models could be used is required. Crop specific parameters for maize cultivars in Tanzania have not been determined before and consequently; crop modeling approaches to address biophysical resource management challenges has not been effective. The objective of this study was to evaluate DSSAT (v4.5) Cropping System Model (CSM) using four adapted maize cultivars namely Stuka, Staha, TMV1 and Pioneer HB3253 for quantifying model parameters. The results indicate that maize cultivars did not differ significantly in terms of the number of days to anthesis, maturity, or grain weight except final aboveground biomass. Also, there was no difference between variables with respect to growing seasons. The cultivar specific parameters obtained were within the acceptable range of those for a hypothetical maize medium season cultivar (990002) included in the DSSAT 45 CSM. Model evaluation results indicate that using the estimated cultivar coefficients, the model simulated well the effects of varying nitrogen management as indicated by the agreement index (d-statistic) closer to unity. Therefore, it is concluded that model calibration and evaluation was satisfactory within the limits of test conditions, and that the model fitted with cultivar specific parameters can be used in simulation studies for research, farm management or decision making.

Share and Cite:

Mourice, S. , Rweyemamu, C. , Tumbo, S. and Amuri, N. (2014) Maize Cultivar Specific Parameters for Decision Support System for Agrotechnology Transfer (DSSAT) Application in Tanzania. American Journal of Plant Sciences, 5, 821-833. doi: 10.4236/ajps.2014.56096.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] van Ittersum, M.K., Cassman, K.G., Grassini, P., Wolfa, J., Tittonell, P. and Hochmand, Z. (2013) Yield Gap Analysis with Local to Global Relevance—A Review. Field Crops Research, 143, 4-17.
http://dx.doi.org/10.1016/j.fcr.2012.09.009
[2] Rosenzweig, C. and Liverman, D. (1992) Predicted Effects of Climate Change on Agriculture: A Comparison of Temperate and Tropical Regions. In: Majumdar, S. K., Ed., Global Climate Change: Implications, Challenges, and Mitigation Measures, The Pennsylvania Academy of Sciences, PA, 342-361.
[3] White, J.W., Hoogenboom, G., Kimball, B.A. and Wall, G.W. (2011) Methodologies for Simulating Impacts of Climate Change on Crop Production. Field Crops Research, 124, 357-368. http://dx.doi.org/10.1016/j.fcr.2011.07.001
[4] Mupangwa, W., Dimes, J., Walker, S. and Twomlow, S. (2011) Measuring and Simulating Maize (Zea mays L.) Yield Responses to Reduced Tillage and Mulching under Semi-Arid Conditions. Agricultural Sciences, 2, 167-174.
http://dx.doi.org/10.4236/as.2011.23023
[5] MAFSC (2013) Agricultural Basic Data 2005/2006-2009/2010.
http://www.kilimo.go.tz/agricultural/statistics/Basic/Chapter4.pdf
[6] FAOSTAT, (2012) Food and Agricultural Commodities Production. http://faostat.fao.org/site/339/default.aspx
[7] Hunt, L.A. and Boote, K.J. (1998) Data for Model Operation, Calibration and Evaluation. In: Tsuji, G.Y., Hoogenboom, G. and Thornton, P.K., Eds., Understanding Options for Agricultural Production, Kluwer Academic Publishers/ICASA, Dordrecht, 9-40.
[8] Hoogenboom, G., Jones, J.W., Wilkens, P.W., Porter, C.H., Boote, K.J. and Hunt, L.A. (2010) Decision Support System for Agrotechnology Transfer (DSSAT) Version 4.5, Honolulu, University of Hawai, CD ROM.
[9] Mwandosya, M.J., Nyenzi, B.S. and Luhanga, M.L. (1998) The Assessment of Vulnerability and Adaptation to Climate Change Impacts in Tanzania. Centre for Energy, Environmental Science and Technology, Dar-es-Salaam, Tanzania.
[10] Harvest Choice (2010) Yield Gap: Rain-fed Maize. IFPRI, Washington, http://harvestchoice.org/node/1622
[11] Arndt, C., Farmer, W., Strzepek, K. and Thurlow, J. (2011) Climate Change, Agriculture and Food Security in Tanzania. Working Paper No. 6188. United Nations University-World Institute for Economic Development Research (UNU-WIDER), 26.
[12] Anothai, J., Patanothai, A., Jogloy, S., Pannangpetch, K., Boote, K.J. and Hoogenboom, G. (2008) A Sequential Approach for Determining the Cultivar Coefficients of Peanut Lines Using End-Of-Season Data of Crop Performance Trials. Field Crops Research, 108, 169-178. http://dx.doi.org/10.1016/j.fcr.2008.04.012
[13] Bannayan, M. and Hoogenboom, G. (2009) Using Pattern Recognition for Estimating Cultivar Coefficients Of a Crop Simulation Model. Field Crops Research, 111, 290-302. http://dx.doi.org/10.1016/j.fcr.2009.01.007
[14] He, J., Jones, J.W., Graham, W.D. and Dukes, M.D. (2010) Influence of Likelihood Function Choice for Estimating Crop Model Parameters Using the Generalized Likelihood Uncertainty Estimation Method. Agricultural Systems, 103, 256-264. http://dx.doi.org/10.1016/j.agsy.2010.01.006
[15] MacCarthy, D.S., Vlek, P.L.G. and Fosu-Mensah, B.Y. (2012) The Response of Maize to N Fertilization in a Sub-Humid Region of Ghana: Understanding the Process Using a Crop Simulation Model. In: Kihara, J., Fatondji, D., Jones, J. W., Hoogenboom, G., Tabo, R. and Bationo, A., Eds., Improving Soil Fertility Recommendations in Africa using the Decision Support System for Agrotechnology Transfer (DSSAT), Springer Science + Business Media, Dordrecht, 61-75.
[16] Jones, P.G. and Thornton, P.K. (2003) The Potential Impacts of Climate Change on Maize Production in Africa and Latin America in 2055. Global Environmental Change, 13, 51-59. http://dx.doi.org/10.1016/S0959-3780(02)00090-0
[17] Craufurd, P.Q., Vadez, V., Jagadish, S.V.K., Vara-Prasad, P.V. and Zaman-Allah, M. (2013) Crop Science Experiments Designed to Inform Crop Modeling. Agricultural and Forest Meteorology, 170, 8-18.
http://dx.doi.org/10.1016/j.agrformet.2011.09.003
[18] Jones, C.A. and Kiniry, J.R. (1986) CERES-Maize. Texas A&M University Press, College Station.
[19] Jones, J.W., Hoogenboom, G., Porter, C.H., Boote, K.J., Batchelor, W.D., Hunt, L.A., Wilkens, P.W., Singh, U., Gijsman, A.J. and Ritchie, J.T. (2003) The DSSAT Cropping System Model. European Journal of Agronomy, 18, 235-265.
http://dx.doi.org/10.1016/S1161-0301(02)00107-7
[20] Hoogenboom, G., Jones, J.W., Traore, P.C.S. and Boote, K.J. (2012) Experiments and Data for Model Evaluation and Application. In: Kihara, J., Fatondji, D. Jones, J.W., Hoogenboom, G., Tabo, R. and Bationo, A., Eds., Improving Soil Fertility Recommendations in Africa Using the Decision Support System for Agrotechnology Transfer (DSSAT), Springer Science + Business Media, Dordrecht, 9-18.
[21] Mokhtarpour, H., Teh, C.B.S., Saleh, G., Selamat, A.B., Asadi, M.E. and Kamkar, B. (2010) Non-Destructive Estimation of Maize Leaf Area, Fresh Weight, and Dry Weight Using Leaf Length and Leaf Width. Communications in Biometry and Crop Science, 5, 19-26.
[22] Ogoshi, R.M., Cagauan, B.G. and Tsuji, G.Y. (1999) Field and Laboratory Methods for Collection of Minimum Data sets. In: Hoogenboom, G., Wilkens P.W. and Tsuji G.Y., Eds., DSSAT, Version 3, Vol. 4. IBSNAT-ICASA, University of Hawaii, Honolulu, 217-286.
[23] United Republic of Tanzania (1993) Review of Fertilizer Recommendation in Tanzania. Soil Fertility Report F6, National Soil Service, Tanga, Tanzania.
[24] Wallach, D. (2006) Evaluating Crop Models. In: Wallach, D., Makowski, D. and Jones, J.W., Eds., Working with Dynamic Crop Models Evaluation, Analysis, Parameterization, and Applications, Elsevier, Amsterdam, 11-54.
[25] Wilmott, C.J. (1981) On the Validation of Models. Physical Geography, 2, 184-194.
[26] Tumbo, S.D., Kahimba, F.C., Mbilinyi, B.P., Rwehumbiza, F.B., Mahoo, H.F., Mbungu, W.B. and Enfors, E. (2012) Impact of Projected Climate Change on Agricultural Production in Semi-Arid Areas of Tanzania: A Case of Same District. African Crop Science Journal, 20, 453-463.
[27] MAFSC (2012) Tanzania Variety Catalogue. http://www.kilimo.go.tz/publications/publications.htm
[28] Cenacchi, N. and Koo, J. (2011) Effects of Drought Tolerance on Maize Yield in Sub-Saharan Africa.
http://addis2011.ifpri.info/files/2011/10/Paper_4C_Nichola-Cenacci.pdf
[29] Tollenaar, M. and Lee, E.A. (2002) Yield Potential Yield, Yield Stability and Stress Tolerance in Maize. Field Crops Research, 75, 161-170. http://dx.doi.org/10.1016/S0378-4290(02)00024-2
[30] Birch, C.J., Vos, J., Kiniry, J., Bos, H.J. and Elings, A. (1998) Phyllochron Responds to Acclimation to Temperature and Irradiance in Maize. Field Crops Research, 59, 187-200. http://dx.doi.org/10.1016/S0378-4290(98)00120-8
[31] Hokmalipour, S. (2011) The Study of Phyllochron and Leaf Appearance Rate in Three Cultivar of Maize (Zea mays L.) at Four Nitrogen Fertilizer Levels. World Applied Sciences Journal, 12, 850-856.

Copyright © 2023 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.