Esta publicación presenta la anatomía macroscópica y microscópica de 50 especies maderables comerciales de la Selva Central del Perú, y puede ser utilizada como material de consulta en el proceso de identificación de especies maderables en los puestos de control de Selva Central del Serfor. Además, proporciona información de otras especies con valor comercial que podrían ser utilizadas en la industria maderera en reemplazo de las especies comúnmente utilizadas.

Introduction: The great diversity of tropical timber species demands the development of new technologies capable of identifying them based on their patterns or anatomical characteristics. The application of convolutional neural networks (CNN) for the recognition of tropical timber species has increased in recent years due to the promising results of CNNs. Objective: To evaluate the quality of macroscopic images with three cutting tools to improve the visualization and distinction of anatomical features in the CNN model training. Methods: Samples were collected from 2020 to 2021 in areas of logging and sawmills in the Central Jungle, Peru. They were later sized and, after botanical and anatomical identification, cut in cross sections. A database of macroscopic images of the cross-section of wood was generated through cutting with three different tools and observing its performance in the ...