INVESTIGADORES
GONZALEZ Fernanda Gabriela
congresos y reuniones científicas
Título:
Physiological and genetic bases of wheat and soybean to biotic and abiotic stress: application to breeding and crop management in the southern cone of America
Autor/es:
GONZÁLEZ FG; MIRALLES DJ; OTEGUI, MARÍA ELENA; KAVANOVÁ, MONICA; CORREA MARCELINO-GUIMARAES; AGUERO, M; ALFARO, C; AGUIRREZABAL, LUIS; BREDEMEIER, C.; BORSANI, O
Reunión:
Simposio; . WUM Symposium Cum Research Summit on Impacts of grain legume research and development in developing countries.; 2017
Resumen:
The demand of wheat and soybean products is expected to increase steadily in next decades, which represents a great opportunity for the economy of meridional South America. The land under wheat crops has stabilized close to 8.5 mill ha (1970-2014, FAO 2016), while the area under soybean crops has expanded exponentially, reaching nowadays ca. 54 mill ha of mentioned region (FAO 2016). Increasing the agricultural land is not a sustainable solution to further production increments. Contrary, improving grain yield, as well as its stability and quality, seems the right option. Additionally, climatic variability and crop exposure to biotic and abiotic stress will be over-expressed due to expected climate change, reducing the yield and quality of grain crops. In these scenarios, breeding efforts should focus on releasing cultivars with improved adaptation to the new variable and stressful environments. The main objectives of the project are: (i) characterization of regional germplasm to biotic and abiotic stresses (flooding, drought and/or high temperature); (ii) identification of physiological and genetic bases associated with high yield and stability under such stresses; (iii) development of a high throughput phenotyping platform validated at regional level; and (iv) quantification of current and future abiotic stresses using agronomic simulation models. The expected outcome is to provide breeding programs with applicable tools to develop improved germplasm adapted to the new environmental constraints, as well as decision support systems based on current crop simulation models for helping farmers to achieve sustainable production.