CSM-CROPGRO-Cowpea

Cowpea (Vigna unguiculata) is a fast-growing, short-cycle, N-fixing legume that originated from West Africa.  Common names include southern pea, blackeye pea, crowder pea, lubia, niebe, coupe or frijole.  It is grown for its seed for human consumption, based on dry seed used much like dry bean, but its immature pods are edible and eaten by some. Cowpea fodder (remaining vines) is highly valued as ruminant animal feed and dual-purpose cowpea is popular in Africa.  In addition to Africa, it is also widely grown in Latin America, southeast Asia and in the southern United States. Cowpea is often grown in maize-cowpea rotations and prized for its N contribution to the following maize crop. It is drought tolerant and its short cycle fits well in regions with short rainy season such as the Sahel.

The CSM-CROPGRO-Cowpea model was adapted about 1999 by K. J. Boote and is based on the CROPGRO-Soybean model (Boote et. al., 1998), with calibration to a single experiment on California Blackeye # 5 cultivar conducted in Florida (Maliro, 1987). This was the basis of the initial species, ecotype, and cultivar genetics files. The model was further evaluated for production of cowpea as a dual purpose crop in Nigeria in collaboration between the International Livestock Research Institute (ILRI), the International Institute of Tropical Agriculture (IITA), and the University of Georgia (Hoogenboom et al., 1999). A field experiment at the University of Georgia and a growth chamber experiment in the Georgia Envirotron to determine the response to different maximum and minimum temperature combinations were also conducted for evaluation of the initial version of the CROPGRO-Cowpea model (Hoogenboom, personal communication). 

The model shares the same source code as the other CROPGRO legume models (Boote et. al., 1998; Jones et al., 2003) which includes hedge-row light interception model (Boote and Pickering, 1994) combined with a leaf-scale photosynthesis model based on the Farquhar approach for simulating response to CO2. Differences from soybean include:  1) more rapid early leaf area expansion, 2) shorter crop cycle, 3) short individual pod-filling duration that can limit yield, and 4) short rapid flushes of pod addition such that pods may mature even while new flushes of pods are being added. 

So far only a few other studies have been conducted with the CROPGRO-Cowpea model. This includes planting data evaluation in Bahia, Brazil (Filho et al., 2013a, b), irrigation management in Piauí State, Brazil (Bastos et al.., 2002), and nitrogen management in Sudan (Lomeling et al, 2014; Lomeling and Huria, 2019, 2020). The CROPGRO-Cowpea model is relatively inexperienced, and, therefore, would benefit from further evaluation in other regions and environments.

References

  • Boote, K. J., J. W. Jones, G. Hoogenboom, and N. B. Pickering.  1998.  The CROPGRO Model for Grain Legumes.  pp. 99-128.  In G.Y. Tsuji, G. Hoogenboom, and P. K. Thornton (eds.). Understanding Options for Agricultural Production.  Kluwer Academic Publishers, Dordrecht.
  • Bastos, E.A., M.V. Folegatti, R.T. de Faria, A.S. de Andrade Jr., and M.J. Cardoso. 2002. Simulation of growth and development of irrigated cowpea in Piauí State by CROPGRO model. Pesquisa Agropecuária Brasileira 37(10):1381-1387. https://dx.doi.org/10.1590/S0100-204X2002001000005
  • Boote, K.J., and N.B. Pickering. 1994. Modeling photosynthesis of row crop canopies. HortScience 29:1423–34.
  • Filho, A.F.L., M.A. Coelho Filho, and A.B. Heinemann. 2013a. Calibration and evaluation of CROPGRO model for cowpea in Reconcavo of Bahia–Brazil. Revista Brasileira de Engenharia Agricola e Ambiental, 17(12), 1286+.
  • Filho, A.F.L., M.A. Coelho Filho, and A.B. Heinemann. 2013b. Determining the optimum sowing dates for cowpea based on CROPGRO model in Reconcavo of Bahia–Brazil. Revista Brasileira de Engenharia Agricola e Ambiental 17(12), 1294+.
  • Hoogenboom, G., G.R. Rodriguez, P.K. Thornton, and S. Tarawali. 1999. Development of a forage model for livestock production systems in Africa. The Third International Symposium on Systems Approaches for Agricultural Development (SAAD-III). Participants Manual: II-P-4.
  • Jones, J.W., G. Hoogenboom, C.H. Porter, K.J. Boote, W.D. Batchelor, L.A. Hunt, P.W. Wilkens, U. Singh, A.J. Gijsman, and J.T. Ritchie. 2003. The DSSAT Cropping System Model. European Journal of Agronomy 18:235–65.
  • Maliro, C.E. 1987. Physiological aspects of yield among four legume crops under two water regimes. University of Florida, Gainesville, FL, Master’s thesis.
  • Lomeling, D., M.M. Kenyi, A.A. Abass, S.M. Otwari, and Y.M. Khater. 2014. Using the CROPGRO Model to predict phenology of cowpea under rainfed conditions. International Journal of Plant & Soil Science 3(7):824-844.
  • Lomeling, D. and Huria, S.J. 2019. Simulating the effects of human urine on phenology and some cultivar coefficients of cowpea (Vigna  unguicalata L. Walp) using the DSSAT-CROPGRO model. Archives of Agriculture and Environmental Science 4(4):369-378. https://dx.doi.org/10.26832/24566632.2019.040402
  • Lomeling, D. and Huria, S.J.  2020. Using the DSSAT-CROPGRO model to simulate gross margin and N-leaching of cowpea fertigated with human urine. Archives of Agriculture and Environmental Science 5(1):1-10. https://dx.doi.org/10.26832/24566632.2020.050101