A trait-based model ensemble approach to design rice plant types for future climate.

Crop models are powerful tools to support breeding because of their capability to explore genotype × environment×management interactions that can help design promising plant types under climate change. However, relationships between plant traits and model parameters are often model specific and not necessarily direct, depending on how models formulate plant morphological and physiological features. This hinders model application in plant breeding.

Improving adoption of technologies and interventions for increasing supply of quality livestock feed in low- and middle-income countries.

The global increase in the demand for and production of animal-source foods (four-to five-fold increase between 1960 and 2015), which has been mostly concentrated in low- and middle-income countries (LMIC), provides smallholder livestock producers with an opportunity for improving their livelihoods and food and nutrition security. However, across livestock production systems in many LMIC, limited supplies and high cost of good quality feed severely constrains exploitation of this opportunity. In many of such countries, feeds and feeding-related issues are often ranked as the primary constraint to livestock production and increased consumption of animal-source foods.

Narrowing uncertainties in the effects of elevated CO on crops.

Plant responses to rising atmospheric carbon dioxide (CO) concentrations, together with projected variations in temperature and precipitation will determine future agricultural production. Estimates of the impacts of climate change on agriculture provide essential information to design effective adaptation strategies, and develop sustainable food systems. Here, we review the current experimental evidence and crop models on the effects of elevated CO concentrations.

Modelling climate change impacts on maize yields under low nitrogen input conditions in sub-Saharan Africa.

Smallholder farmers in sub-Saharan Africa (SSA) currently grow rainfed maize with limited inputs including fertilizer. Climate change may exacerbate current production constraints. Crop models can help quantify the potential impact of climate change on maize yields, but a comprehensive multimodel assessment of simulation accuracy and uncertainty in these low-input systems is currently lacking.

Simulated Optimum Sowing Date for Forage Pearl Millet Cultivars in Multilocation Trials in Brazilian Semi-Arid Region.

Forage production is primarily limited by weather conditions under dryland production systems in Brazilian semi-arid regions, therefore sowing at the appropriate time is critical. The objectives of this study were to evaluate the CSM-CERES-Pearl Millet model from the DSSAT software suite for its ability to simulate growth, development, and forage accumulation of pearl millet [ (L.) R.