CERES‐Maize Predictions of Maize Phenology under Nitrogen‐Stressed Conditions in Nigeria

Abstract

Simulation models have the potential of greatly enhancing decision‐making by farmers and researchers in Nigeria. These models however, need to be adapted before use. This study was conducted to test the phenology module of CERES‐Maize model version 3.5 under varying N rates as a step toward adapting the model in the Southern Guinea Savanna of Nigeria. Data on seven late‐maturing cultivars of maize (Zea mays L.) grown under 0, 30, 60, 90, and 120 kg N ha−1 in the field for two seasons were used for running the model. There was a linear relationship between N rates and days to silking and maturity with R2 values of > 0.70 for most of the cultivars, indicating that N strongly influenced phenology. Predictions of days to silking at high N rates (90 and 120 kg N ha−1) were close, with most prediction errors of <2 d. The highest deviations in the calibration results were 4 and 2 d for 90 and 120 kg N ha−1, respectively, while in the validation results, they were 1 and 2 d. Similarly, days to maturity were closely predicted by the model at high N rates with <2‐d deviations for most predictions. At low N rates, however, there were greater deviations in model predictions. This shows that the CERES‐Maize model can be reliably used for predicting maize phenology only under nonlimiting N conditions. Thus, a N stress factor needs to be incorporated into the model for more accurate phenology prediction in low‐N tropical soils.

Options for calibrating CERES-maize genotype specific parameters under data-scarce environments

“…This is a common occurrence with simulations of grain yield and yield attributes under low nitrogen fertilizer applications. Gungula et al [39], reported that the CERES-Maize model poorly predicts performance of maize under low nitrogen conditions in the tropics. The agreements between observed and simulated grain and stover nitrogen for both GSPs under high fertilizer applications is an indication that CERES-model still performs best under high nitrogen applications especially on tropical soils.…”

“…The CERES-Maize model has been shown over the years to be an important tool in evaluating crop management [3], climate change impacts [40], fertilizer recommendations [5,39] and yield forecasting [41]. Calibrating the newly released maize varieties currently recommended for the Nigerian maize belts will provide an important input requirement for using crop models to evaluate major production constraints including optimum stand density (OSD), appropriate varietal selection (targeting/stability analysis), choice of major partner crop (in case of mixed cropping) and fertilizer (especially N and P) managements.…”

Negative effects of climate warming on maize yield are reversed by the changing of sowing date and cultivar selection in Northeast China

“…b). Therefore, the APSIM‐Maize model assumed that accumulation of thermal time for a given cultivar was constant (McCown et al ., ; Wang et al ., ), similar to other crop models such as CERES (Jones & Kiniry, ; Gungula et al ., ), ORYZA2000 (Bouman et al ., ; Bouman & van Laar, ). The phase between germination and emergence was determined by the thermal time affected by the depth of sowing; therefore, this thermal time is assumed to be a constant for a given location over the period (1981–2007) in this study.…”

Delayed reproduction in Arabidopsis thaliana improves fitness in soil with suboptimal phosphorus availability

“…1987; Chauhan, Johansen & Venkataratnam 1992; Marschner 1995; Rodriguez, Pomar & Goudriaan 1998; Ma, Longnecker & Atkins 2002). This is noteworthy because the generalized stress response in annual plants is earlier flowering and maturity as a form of stress avoidance (Amir & Cohen 1990, Pigliucci & Schlichting 1995; Thies, Singleton & Bohlool 1995; Dorn, Pyle & Schmitt 2000; Gungula, Kling & Togun 2003). Phenological delay may simply be caused by the inability of plants to flower until they have attained some threshold of tissue phosphorus or size, the attainment of which would be delayed by a slower growth rate (Rodriguez, Santa Maria & Pomar 1994; Marschner 1995).…”