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作 者:徐惠荣[1] 宋保国 万旺军 周莹[1] 应义斌[1]
机构地区:[1]浙江大学生物系统工程与食品科学学院,浙江杭州310058 [2]浙江出入境检验检疫局,国家级羽毛绒检测重点实验室,浙江杭州311208
出 处:《光谱学与光谱分析》2012年第4期974-977,共4页Spectroscopy and Spectral Analysis
基 金:国家自然科学基金项目(61005022);浙江省科技计划项目(2009C31137)资助
摘 要:鹅绒和鸭绒的外观相似但在品质上鹅绒优于鸭绒,各国羽绒毛标准对鹅绒毛中的鸭绒毛含量都有最高限定。传统检测方法为高倍显微镜目测法,该方法劳动强度大,且不适宜大批量样本的分析及现场快速检测。利用可见/近红外光谱结合连续投影算法(SPA)特征波长选择的建模方法对鹅绒中混有鸭绒含量进行了定量检测。在450~930nm范围内,通过SPA选择的8个特征波长建立多元线性回归模型,取得了较好的预测结果,相关系数为0.983,校正均方根误差(RMSEC)为5.44%,预测均方根误差(RMSEP)为5.75%,有望用于羽绒毛品质的快速检测。Goose down and duck down have very similar appearance but the quality of goose down is better than that of duck down in general. There is a highest allowable limit as spec!fied by the various national standards of feather and down for the percentage of duck feather or down mixed in goose feather-or down. Traditional detection method, manual inspection with a high- scale microscope, is labor intensive and not suitable for l'arge-volUme samples analysis and on-site rapid testing In the present paper, visible/near-infrared (NIR) spectroscopy combined with successive projection algorithm (SPA) for characteristic wavelengths selection was used to determinate the content of duck down mixed in goose down. In the range of 450-930 nm, the mutiple linear regression (MLR) model established with.the 8 characteristic wavelengths selected by SPA achieved good prediction, the correlation coefficient of 0. 983, root mean square error of calibration (RMSEC) of 5.44 %, and root mean square error of prediction (RMSEP) of 5.75%. Therefore, it is expected to be used for rapid detection of feather and down quality in future.
关 键 词:羽绒品质 定量分析 可见/近红外光谱 连续投影算法 波长选择
分 类 号:S123[农业科学—农业基础科学]
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