Using the CSM–CERES–Maize model to assess the gap between actual and potential yields of grain maize

Abstract

SUMMARYMaize in Canada is grown mainly in the south-eastern part of the country. No comprehensive studies on Canadian maize yield levels have been done so far to analyse the barriers of obtaining optimal yields associated with cultivar, environmental stress and agronomic management practices. The objective of the current study was to use a modelling approach to analyse the gaps between actual and potential (determined by cultivar, solar radiation and temperature without any other stresses) maize yields in Eastern Canada. The CSM–CERES–Maize model in DSSAT v4·6 was calibrated and evaluated with measured data of seven cultivars under different nitrogen (N) rates across four sites. The model was then used to simulate grain yield levels defined as: yield potential (YP), water-limited (YW, rainfed), and water- and N-limited yields with N rates 80 kg/ha (YW, N-80N) and 160 kg/ha (YW, N-160N). The options were assessed to further increase grain yield by analysing the yield gaps related to water and N deficiencies. The CSM–CERES–Maize model simulated the grain yields in the experiments well with normalized root-mean-squared errors <0·20. The model was able to capture yield variations associated with varying N rates, cultivar, soil type and inter-annual climate variability. The seven calibrated cultivars used in the experiments were divided into three grades according to their simulated YP: low, medium and high. The simulation results for the 30-year period from 1981 to 2010 showed that the average YP was 15 000 kg/ha for cultivars with high yield potential. The YP is generally about 6000 kg/ha greater than the actual yield (YA) at each experimental site in Eastern Canada. Two-thirds of this gap between YP and YA is probably associated with water stress, as a gap of approximately 4000 kg/ha between the YW and the YP was simulated. This gap may be reduced through crop management, such as introducing irrigation to improve the distribution of available water during the growing season. The simulated yields indicated a gap of about 3000 and 1000 kg/ha between YW and YW,N-80N for cultivars with high YP and low YP, respectively. The gap between YW and YW,N-160N decreased to <2000 kg/ha for high Yp cultivars with little difference for the low Yp cultivars. The different yield gaps among cultivars suggest that cultivars with high YP require high N rates but cultivars with low YP may need only low N rates.

Climate change impacts on Canadian yields of spring wheat, canola and maize for global warming levels of 1.5 °C, 2.0 °C, 2.5 °C and 3.0 °C

“…DSSAT includes several crop growth models in the crop system model (CSM) including the CSM-CERES-Maize model, the CSM-CERES-Wheat model and the CSM-CROPGRO-Canola model. These crop growth models were calibrated and evaluated with Canadian cultivars and current growing conditions (Jing et al 2016a(Jing et al , 2016b(Jing et al , 2017. DNDC is a well-known process-based model used to simulate carbon and nitrogen biochemistry for agricultural systems over a wide range of agricultural management, soil and climatic conditions.…”

“…DNDC is a well-known process-based model used to simulate carbon and nitrogen biochemistry for agricultural systems over a wide range of agricultural management, soil and climatic conditions. It is able to estimate the growth of a wide variety of crops (Zhang and Niu 2016) Jing et al (2016aJing et al ( , 2016bJing et al ( , 2017 were used to simulate continuous wheat, maize and canola in the CRAM regions where the crop is currently cultivated, as shown in figure 1. Crop cultivars in DNDC and DayCent are more generically described, but when it was feasible, each model used crop parameters consistent with the cultivars used in DSSAT.…”

Evaluating APSIM-and-DSSAT-CERES-Maize Models under Rainfed Conditions Using Zambian Rainfed Maize Cultivars

“…In contrast, the grain and biomass yield evaluations (DSSAT-CERES-Maize model) for all three cultivars had a d-stat ≥ 0.70. The d-stat ≥ 0.70 has been reported as being acceptable in crop model evaluations [41,60]. The RMSE for a pooled biomass yield in the APSIM-Maize and DSSAT-CERES-Maize models were 3.19 t ha −1 and 2.87 t ha −1 , respectively.…”

“…The simulation is considered excellent with RMSEn <10%, good if 10-20%, acceptable or fair if 20-30% and poor >30% [59]. The d ≥ 0.70 is considered acceptable in crop modeling and evaluations [60].…”

Multi-scale assessment of winter wheat yield gaps with an integrated evaluation framework in the Huang-Huai-Hai farming region in China

“…The main restrictive factors for crop production by farmers can be evaluated with the participatory evaluation approach (Studnicki et al ., 2019), but there is a certain degree of subjectivity and randomness in such surveys (Cheesman et al ., 2017). Crop models can serve as an important tool for evaluating yield potential, with the advantages of simple implementation, multifactor analysis and predictable capacity, but there are inconsistencies among crop models (Jing et al ., 2017). The definitions and evaluation frameworks of yield gaps exhibit large differences.…”