Impact of Climatic Variables on Carbon Content in Sugar Beet Root
Luis F. Sánchez-Sastre,
Pablo Martín-Ramos,
Luis M. Navas-Gracia,
Salvador Hernández-Navarro,
Jesús Martín-Gil
Affiliations
Luis F. Sánchez-Sastre
Department of Agriculture and Forestry Engineering, Escuela Técnica Superior de Ingenierías Agrarias de Palencia, Universidad de Valladolid, Avenida de Madrid 44, 34004 Palencia, Spain
Pablo Martín-Ramos
Department of Agricultural and Environmental Sciences, Escuela Politécnica Superior, Instituto de Investigación en Ciencias Ambientales (IUCA), University of Zaragoza, Carretera de Cuarte, s/n, 22071 Huesca, Spain
Luis M. Navas-Gracia
Department of Agriculture and Forestry Engineering, Escuela Técnica Superior de Ingenierías Agrarias de Palencia, Universidad de Valladolid, Avenida de Madrid 44, 34004 Palencia, Spain
Salvador Hernández-Navarro
Department of Agriculture and Forestry Engineering, Escuela Técnica Superior de Ingenierías Agrarias de Palencia, Universidad de Valladolid, Avenida de Madrid 44, 34004 Palencia, Spain
Jesús Martín-Gil
Department of Agriculture and Forestry Engineering, Escuela Técnica Superior de Ingenierías Agrarias de Palencia, Universidad de Valladolid, Avenida de Madrid 44, 34004 Palencia, Spain
The impacts of climatic variables on the growth and carbon content of spring sown sugar beet (Beta vulgaris L.) in the Castilla y Leon region (Northwestern Spain) were assessed by analyzing 35 beet crop variables at four sites over two cultivation years. ANOVA analysis allowed to discern that the location was the factor that had the highest effect on those variables. Fertilization treatments only had a significant impact on the variables derived from the quantity of fresh material (leaves), while the beet variety choice influenced the amount of nitrogen in leaves and the carbon to nitrogen ratio. It could be inferred that the percentage of root carbon content depended mostly on the location and that a higher percentage of root carbon content led to a higher content of dry matter, with a positive relationship with the sucrose content for the two types of varieties that were tested. Principal Component Analysis distinguished the climatic factors that most influenced each cultivation area in each cultivation year and provided a clear separation of the data in clusters, evidencing the uniqueness of each site.