Sweet corn (Zea mays convar. saccharata var. rugose) is a naturally occurring genetic mutation of field corn that causes the kernels to store more sugar than field corn. To further increase sweetness, the ears are harvested before physiological maturity. In the USA, about 75% of production is consumed fresh, the balance going to processed (canned and frozen) products. 

Previous maize simulation models had limited potential to assist sweet corn production as a result of the distinctive nature of the marketed end product, i.e., fresh market ears versus dry mature kernels. The CSM-CERES-Maize module (version 4.0) was modified to improve the simulation of ear growth, to predict ear fresh market yield, and to predict fresh market ear quality according to U.S. standards (Lizaso et al., 2007). Ear fresh weight is estimated by assuming that the ear dry mass concentration (fraction of fresh ear weight) increases linearly with thermal time, and then calculates fresh weight from the simulated ear dry weight. Marketable fresh mass is assumed to increase linearly with total fresh mass. The marketable mass is then used to estimate number of ears in the US fancy classes. From there, US No 1 and No 2 ear numbers and masses is estimated. Similar to other crop modules of CSM (Jones et al., 2003), the model uses a minimum of readily available weather, soil, and variety-specific genetic inputs.

A field experiment conducted in 2003 was used for model development. A sh2-based commercial hybrid with a Bt gene was sown at five nitrogen fertilization levels (0, 67, 133, 200, and 267 kg·ha⁻¹ N). Three experiments in 2002, 2004, and 2005 allowed for independent evaluation of model performance. In 2002, the treatments and hybrid were the same as mentioned, but the population density was 5.5 plants/m². A yellow sh2-based hybrid with a Bt gene was planted at 6.1 plants/m² in 2004. In 2005, a bicolor sh2-based hybrid with a Bt gene was planted at 8.1 plants/m². The 2004 and 2005, the experiments had 100% and 150% of the Florida N recommendations applied to the crop. 

The CSM-CERES-Sweetcorn model adequately simulated crop and ear growth of sweet corn. The ear dry weight simulation was improved as indicated by a 30% reduction of root mean square of the error (RMSE) when the new model was compared with the original CSM-CERES-Maize. Total ear fresh weight yield and marketable yield were also simulated reasonably well with RMSE values of 3367 and 3502 kg ha^-1, respectively. Ear quality was overpredicted at intermediate levels of N fertilization. Considering the impact of ear quality on farmers income, the simulation of ear quality should be further refined including the effect of limited N on the quality of marketable ears. The possibility of incorporating other quality scales in addition to the one used in US should be also explored.

As a process-based model, the CERES-Sweetcorn should be applicable to a wide range of research problems, including response to nitrogen fertilization, irrigation, optimum population density for specific locations, and other environmental conditions, and yield-gap analyses. Until now the model has not been evaluated for other regions of the USA, Latin America, and South Asia where sweet corn is popular.

References

• 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 (2003): 235–65.
• Lizaso, J.I., Boote, K.J., Cherr, C.M., Scholberg, J.M.S., Casanova, J.J., Judge, J., Jones, J.W., Hoogenboom, G., 2007. Developing a sweet corn simulation model to predict fresh market yield and quality of ears. Journal of the American Society for Horticultural Science 132, 415–422. https://doi.org/10.21273/JASHS.132.3.415