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Copyright of Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao is the property of Chinese Journal of Applied Ecology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Clinical Nursing in Practice is the property of Journal of Clinical Nursing in Practice (Editorial Board, Shanghai Jiao Tong University Press) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao is the property of Chinese Journal of Applied Ecology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

为快速、无损检测白檀果实的含油率及其油脂各脂肪酸含量，采用DA 7200型近红外分析仪采集115份白檀果实的光谱数据。采用标准正态变量转换法（SNV）、乘积分散校正法（MSC）、卷积平滑法（SG）、一阶导数（FDE）、二阶导数（SDE）以及多种方式相结合对原始光谱进行预处理，对比不同预处理方法的效果，选择最佳预处理方法，在此基础上，结合偏最小二乘法（PLS）和主成分回归分析（PCR）建立含油率及各脂肪酸含量的预测模型，比较不同模型的交互验证决定系数（RCV）和交互验证标准偏差（RMSECV），确定最佳模型，同时结合化学法的测定结果进行模型外部验证。结果表明：白檀果实含油率、棕榈酸含量、油酸含量的最佳建模方法为PLS与SG+FDE预处理，硬脂酸含量为PLS与 SNV+SDE预处理，亚油酸含量为PLS与 MSC+SDE预处理，亚麻酸含量为PLS与FDE预处理；模型校验结果表明，近红外光谱法可以用于白檀果实含油率和各脂肪酸含量的测定，其含油率和亚麻酸、亚油酸、硬脂酸、棕榈酸、油酸含量的定标外部验证系数分别为0.960 2、0.727 8、0.909 1、0.709 8、0.903 7和0.912 0。综上，建立的模型预测性能好，能够满足白檀果实品质性状快速、无损检测，可为大批量白檀种质资源的选择和评价提供技术支撑。In order to establish a rapid and nondestructive determination for oil content and fatty acid content in Symplocos paniculate fruit, the near-infrared spectrum data of 115 Symplocos paniculate fruits were collected by DA 7200 near infrared spectrometer．Standard normal variable transformation (SNV), multiplicative dispersion correction (MSC), convolutional smoothing (SG), first order derivative (FDE) and second order derivative (SDE) and a combination of these methods were used to pretreat the raw spectra, the effects of different pretreatment methods were compared to select the best pretreatment method, and the prediction models of oil content and fatty acid content were established by using partial least squares （PLS）and principal component regression analysis(PCR), and the RCV and RMSECV of different models were compared to determine the best model.The external validation of the model was performed by combining the results of the chemical method. The results showed that the best modeling methods for oil content, palmitic acid and oleic acid content in Symplocos paniculate fruit were PLS with SG+FDE pretreatment, stearic acid contents with PLS and SNV+SDE pretreatment, linoleic acid content with PLS and MSC+ SDE pretreatment, and linolenic acid content with PLS and FDE pretreatment. The model validation results showed that near infrared reflectance spectroscopy(NIRS) could be used for the determination of oil content and each fatty acid content of Symplocos paniculate fruits,and the determination coefficients of NIRS model for oil content, linolenic acid, linoleic acid, stearic acid, palmitic acid and oleic acid contents were 0.960 2,0.727 8,0.909 1,0.709 8,0.903 7 and 0.912 0, respectively. In summary, the established NIRS model used for the rapid and nondestructive determination of qualitative characteristics in Symplocos paniculate fruit has excellent predictive capability, and can be used for large-scale screening and evaluation of Symplocos paniculate germplasm resources.