Biotechnologizing Jatropha for local sustainable developments

This article explores whether and how the biotechnologization process that the fuel-plant Jatropha curcas is undergoing might strengthen local sustainable development. It focuses on the ongoing efforts of the multi-stakeholder network Gota Verde to harness Jatropha within local small-scale production systems in Yoro, Honduras. It also looks at the genomics research on Jatropha conducted by the Dutch research institute Plant Research International, specifically addressing the ways in which that research can assists local development in Honduras. A territorial approach is applied for analysis employing a three domain concept (local sustainable biotechnological development) of territory, technology and re-territorialization. The article suggests that, although the biotechnologization process (through genomics) of Jatropha within the socio-technical framework of the institute and multi-stakeholder networks is an ongoing process¿¿and different trajectories are, therefore, still open - the process can, nevertheless, strengthen local sustainable developmen

How do various maize crop models vary in their responses to climate change factors?

Comments This article is a U.S. government work, and is not subject to copyright in the United States. Abstract Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly 0.5 Mg ha 1 per °C. Doubling [CO2] from 360 to 720 lmol mol 1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information