Big data management for sugarcane breeding program
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Abstract
The aim of this work was to design and establish a model of macro data management to facilitate decision-making in the Sugarcane Breeding Program in Cuba and increase its efficiency. For this, available sources of information from the selection process from the period 2000 to 2017 and those coming from the agroproductive response of cultivars in production areas were used. A model was designed and applied that includes components such as: infrastructure, collection, validation, storage, processing, analysis and visualization. A case study of the C86-12 x CP70-1133 cross was conducted to characterize its selection background. As a result, the big data approach made it possible to obtain a compilation of primary data and selection results, estimate the genetic value of parents and crosses, classify the crosses and facilitate decision-making in the sugarcane breeding program in Cuba to obtain new commercial cultivars. Its application in the case study guaranteed access to all available information on the subject and recommending its best management.
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