摘要
由一名新闻记者-机器人与机器学习的工作人员新闻编辑-每日新闻-一项关于支持向量机的新研究现在可用。根据NewsRx e Ditors在爱达荷州莫斯科的新闻报道，研究表明：“确定组织培养的茎叶矿物状态可能是昂贵和耗时的，但高光谱特征可能有助于确定这些茎叶的矿物含量。"从组织培养的小叶Mockorange(Philad elphus microphillus)嫩梢中获得高光谱RAL信号,以确定利用该技术预测叶片氮钙含量的可行性."本研究的资助者包括美国农业部国家食品和农业研究所、Hatch/Evans项目、美国农业部国家食品和农业研究所、Hatch/Evans项目下的爱达荷州农业试验站、爱达荷州农业部苗圃咨询委员会。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on Support Vector Machines is now available. According to news reporting out of Moscow, Idaho, by NewsRx e ditors, research stated, "Determining foliar mineral status of tissue cultured s hoots can be costly and time consuming, yet hyperspectral signatures might be us eful for determining mineral contents of these shoots. In this study, hyperspect ral signatures were acquired from tissue cultured little-leaf mockorange (Philad elphus microphillus) shoots to determine the feasibility of using this technolog y to predict foliar nitrogen and calcium contents." Funders for this research include USDA National Institute of Food and Agricultur e, Hatch/Evans project, USDA National Institute of Food and Agriculture, under t he Hatch/Evans project, Idaho Agricultural Experiment Station, Nursery Advisory Committee of the Idaho State Department of Agriculture.
NETL
NSTL