Resumen La demanda actual de energías limpias y renovables ha provocado cambios conside rables en el sistema productivo de las empresas agroindustriales. La generación de bioelec tricidad mediante la quema de bagazo de caña de azúcar ha aumentado considerablemente en los últimos años. Este trabajo tuvo como objetivo centrarse en la selección de genotipos de caña de azúcar para la productividad de la fibra. El experimento se esbozó en bloques aleatorios con cuatro repeticiones y se evaluaron dieciséis genotipos. Las caracteristicas evaluadas fueron: toneladas de caña por hectárea, toneladas de sacarosa por hectárea, tone ladas de fibra por hectárea, contenido de fibra y contenido aparente de sacarosa. Para la selección se utilizó la metodología de modelos lineales mixtos. Los coeficientes de hereda bilidad sugieren una ganancia genética significativa y las medias armónicas de desempeños relativos de los valores genotípicos predichos permitieron la identificación de genotipos estables relacionados con las características evaluadas en cuatro ciclos de cosecha. Consi derando la demanda actual de la agroindustria de la caña de azúcar por variedades con contenido de fibra entre 12% y 17% y contenido de sacarosa cercano al 13%, para gene ración de energía y producción de azúcar, los genotipos EECAC 06, EECAC 03, EECAC 04 y EECAC 07 se presentan como comerciales opciones de cultivo.

Abstract The current demand for clean and renewable energy has provoked considerable changes in the production system of agro-industrial companies. Bioelectricity generation through sugarcane bagasse burning has considerably risen in recent years. This work aimed to focus on sugarcane genetic selection for fiber productivity, using mixed linear modeling. The experiment was outlined in randomized blocks with four repetitions and sixteen genotypes. The evaluated traits were: cane tons per hectare, sucrose tons per hectare, fiber tons per hectare, fiber content and apparent sucrose content. Heritability coefficients suggested a significant genetic gain, while harmonic means of relative performance of predicted geno typic values allowed the identification of stable genotypes related to the traits evaluated, in four harvest cycles. The current agro-industrial demand for sugarcane varieties considers energy generation and sugar production with fiber content between 12% and 17%, and sucrose content near 13%. With this regard, genotypes EECAC 06, EECAC 03, EECAC 04 and EECAC 07 result interesting commercial cultivation options.

Increasing efforts to preserve environmental resources have included the development of more efficient technologies to produce energy from renewable sources such as plant biomass, notably through biofuels and cellulosic residues. The relevance of the soybean industry is due mostly to oil and protein production which, although interdependent, results from coordinated gene expression in primary metabolism. Concerning biomass and biodiesel, a comprehensive analysis of gene regulation associated with cell wall components (as polysaccharides and lignin) and fatty acid metabolism may be very useful for finding new strategies in soybean breeding for the expanding bioenergy industry. Searching the Genosoja transcriptional database for enzymes and proteins directly involved in cell wall, lignin and fatty acid metabolism provides gene expression datasets with frequency distribution and specific regulation that is shared among several cultivars and organs, and also in response to different biotic/abiotic stress treatments. These results may be useful as a starting point to depict the Genosoja database regarding gene expression directly associated with potential applications of soybean biomass and/or residues for bioenergy-producing technologies.