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Davide Cammarano

Researcher at Purdue University

Publications -  111
Citations -  7147

Davide Cammarano is an academic researcher from Purdue University. The author has contributed to research in topics: Climate change & Crop simulation model. The author has an hindex of 34, co-authored 91 publications receiving 5250 citations. Previous affiliations of Davide Cammarano include University of Melbourne & James Hutton Institute.

Papers
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Rising Temperatures Reduce Global Wheat Production

Senthold Asseng, +59 more
TL;DR: The authors systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 degrees C to 32 degrees C, including experiments with artificial heating.
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Uncertainty in Simulating Wheat Yields Under Climate Change

Senthold Asseng, +53 more
TL;DR: In this article, the authors present the largest standardized model intercomparison for climate change impacts so far, finding that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient.
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Multimodel ensembles of wheat growth: many models are better than one

Pierre Martre, +52 more
TL;DR: It is concluded that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics, and argued that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models.
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Similar estimates of temperature impacts on global wheat yield by three independent methods

Bing Liu, +72 more
TL;DR: This paper showed that grid-based and point-based simulations and statistical regressions, without deliberate adaptation or CO 2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales.
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Climate change impact and adaptation for wheat protein

Senthold Asseng, +75 more
TL;DR: A 32-multi-model ensemble is tested and applied to simulate global wheat yield and quality in a changing climate to potential benefits of elevated atmospheric CO2 concentration by 2050, likely to be negated by impacts from rising temperature and changes in rainfall, but with considerable disparities between regions.