The DSSAT cropping system model

Jones, J. W.; Hoogenboom, Gerrit; Porter, Cheryl; Boote, Kenneth J.; Batchelor, William D.; Hunt, L. A.; Wilkens, Paul W.; Singh, Upendra; Gijsman, Arjan J.; Ritchie, J. T.

doi:10.1016/s1161-0301(02)00107-7

Cited by 3,436 publications

(2,172 citation statements)

References 147 publications

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“…The GCMs include HadGEM2-ES, 41 IPSL-CM5A-LR, 42 and MIROC-ESM-CHEM; 43 and the crop models include DSSAT and LPJmL. 44,45 The pair-wise combination of GCMs with crop models resulted in six climate change scenarios for each socio-economic and emissions pathway. We calculated the mean and standard deviation of the scenario endpoints (changes in food availability and consumption, and changes in mortality) that are associated with the different climate change scenarios, and we report those in the main text to simplify exposition.…”

Section: Panels Panel 1: Future Pathways Of Emissions and Socio-economentioning

confidence: 99%

Global and regional health effects of future food production under climate change: a modelling study

et al. 2016

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Section: Panels Panel 1: Future Pathways Of Emissions and Socio-economentioning

confidence: 99%

Global and regional health effects of future food production under climate change: a modelling study

et al. 2016

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“…The CSM-CROPGRO-Soybean model is included in the Decision Support System for Agrotechnology Transfer (DSSAT) (Jones et al 2003) v4.6 (Hoogenboom et al 2015. This model was originally developed as CROPGRO for simulating soybean growth and development with a daily time step (Boote et al 1998).…”

Section: Introductionmentioning

confidence: 99%

Modelling soybean yield responses to seeding date under projected climate change scenarios

et al. 2017

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“…It has been included in the decision support system for agrotechnology transfer (DSSAT). The CSM-CERES-Rice model is physiologically based and simulates daily canopy photosynthesis, respiration, growth, biomass partitioning and crop development as a function of input information, including daily weather conditions, soil properties, management practices and cultivar characteristics (Jones et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

CSM-CERES-Rice model to determine management strategies for lowland rice production

Vilayvong

Banterng

Patanothai

et al. 2015

Sci. agric. (Piracicaba, Braz.)

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The cropping system model, namely, the crop environment resource synthesis-rice (CSM-CERES-Rice) model, is a decision supporting tool for the design of crop management. This study aimed to determine management practices for increasing rice (Oryza sativa L.) production in Laos by using the CSM-CERES-Rice model. The model was evaluated with data sets from the TDK8 and TDK11 cultivars in farmers' fields in the Vientiane plain in 2012. Anthesis and harvesting dates, growth and yield for various management scenario combinations (eight transplanting dates × two levels of plant densities × three rates of nitrogen (N) fertilizer application) for both cultivars were simulated by the model from 1980 to 2012. The model evaluation results showed strong agreement between simulated and observed data for days to harvest with a difference within four days. The model provided acceptable accuracy for grain yields with normalized root mean square error values ranging between 1 and 16 %. The results from the model application indicated that TDK8 and TDK11 produced similar yields. Transplanting TDK8 with two plant densities produced similar yields. The highest yield for both cultivars was achieved on the transplanting date of 15 Jan. N-fertilizer application at 60 and 120 kg N ha −1 was able to increase yield for TDK8 by 50 and 87 %, respectively, and for TDK11 by 54 and 70 %, respectively. Rice transplanted on 15 Jan with 5 seedlings hill −1 and N-fertilizer at 120 kg N ha −1 had the highest average yield for both cultivars with 6,460 and 6,351 kg ha −1 for TDK8 and TDK11, respectively. The CSM-CERES-Rice model is an alternative tool in determining crop management practices for rice production.

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The DSSAT cropping system model

Cited by 3,436 publications

References 147 publications

Global and regional health effects of future food production under climate change: a modelling study

Global and regional health effects of future food production under climate change: a modelling study

Modelling soybean yield responses to seeding date under projected climate change scenarios

CSM-CERES-Rice model to determine management strategies for lowland rice production

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