NSERC Industrial Research Chair in Applied Forest Genetics and Biotechnology

在过去十年中，国际上对高产林业的兴趣和实施激增，利用以种植园为基础的集约管理的森林来最大限度地增加产量和价值。高产林业通过降低风险和轮伐时间，提供更高和更快实现的投资回报，为林业提供财政利益。 在较小的土地基础上生产更多的木材对于满足预计将急剧增加的纤维需求和减少林业的生态足迹至关重要。 卑诗省森林和牧场研究和树木改良部门、加拿大林务局以及包括种子和种苗生产商在内的大小林业成员正在积极开发、改进和保护新开发的几种具有重要商业价值的卑诗省树木的高增益和遗传多样性种质。本椅子研究计划的重点是建立种质开发商和业务用户之间的联系，以提高目前的树木改良系统的效率，通过纳入新的创新，包括适当的技术。 该提案有三个主要目标：（1）通过建立有效、无缝和综合的树木改良交付系统，最大限度地提高不列颠哥伦比亚省树木改良方案的效率，（2）开发有效的现场工具，用于调查木材质量属性，以便通过树木改良和造林将其纳入最终产品价值，人工神经网络在种子园管理和木材质量评价中的应用。 该计划将培养林业和相关生物科学所需的高素质人才。

During the past decade, there has been an international surge in interest and implementation of high-yield forestry, using plantation-based intensively-managed forests to maximize the volume and value. High-yield forestry provides fiscal benefits to the forest industry by lowering risks and rotation times, providing higher and more quickly realized investment returns. Producing more wood on a smaller landbase is critical to meet the dramatic increase projected for fibre demand and to reduce the ecological footprint of forestry. The BC Ministry of Forests and Ranges Research and Tree Improvement Branches, Canadian Forest Service, and large and small forest industry members including seed and seedling producers, are actively developing, improving, and protecting the newly developed high gain and genetically diverse germplasm for several commercially important BC trees. The focus of this Chairs research program is to create linkages between germplasm developers and operational users to enhance the efficiency of the current tree improvement system by incorporating new innovations including appropriate technologies. There are three primary aims of this proposal: (1) maximizing the efficiency of British Columbias tree improvement programs through the creation of effective, seamless and integrated tree improvement delivery system, (2) developing effective in situ tools for investigating wood quality attributes for their integration into end-product value via tree improvement and silviculture, and (3) application of Artificial Neural Networks (ANNs) to seed orchards management and wood quality assessment. This program will train highly qualified personnel needed in the forest industry and the related biological sciences.