浙江农林大学学报2017，Vol.34Issue(2)：361-368,8.DOI:10.11833/j.issn.2095-0756.2017.02.022
杉木木材结晶度的近红外预测模型建立及变异分析
A near infrared prediction model and variation analysis of wood crystallinity in Cunninghamia lanceolata
摘要
Abstract
Understanding variation of wood crystallinity, an important indicator of timber quality measurement, of Cunninghamia lanceolata, one of the most widely planted timber trees in southern China, is important for C. lanceolata clonal selection and wood processing technology improvements. For an inexpensive and less time-consuming method of rapid crystallinity determination, near infrared spectrum technology was tested. Using 164 C. lanceolata clones from 11 different geographic origins such as Guangxi, Hunan, and Guizhou Provinces, a near infrared spectroscopy prediction model of wood crystallinity was established by the partial least squares (PLS) method in combination with X-ray diffraction techniques, and then evaluated. Next, unknown samples were predicted through the model, and the variation of crystallinity was analyzed. Results showed that when us-ing a spectral region of 6000-4000 cm-1, the second derivative spectrum, and PLS method, the calibration model had the best prediction effect. The calibration model correlation coefficient was r=0.9875, and the root mean square error of calibration (RMSEC) was 0.318. Verifying the model revealed r = 0.9213 and root mean square error of prediction (RMSEP) was 0.742. Using unknown samples not involved in modeling to evaluate the model, predicted and measured r = 0.9050 with an average standard deviation of 0.301. So, the model could predict the crystallinity of C. lanceolata. Then, wood crystallinity determination results of 164 C. lanceolata clones showed that the average value was 44.52%, the range was 40.49%-49.75%, and the value between 42.06% and 47.28% took up 72.86%. According to the distribution of geographical provenances, the average wood crystallinity of C. lanceolata had a minimum of 43.45% from Jing County, Hunan, and a maximum of 45.23% from Liping County, Guizhou. The variance analysis showed no significant difference among the prove-nances, but there were significant differences for clones (P = 0.0003). The results indicate that near infrared spectroscopy could be used for the establishment of reliable prediction model, and the selection of improved varieties should be carried out among clones.关键词
木材科学与技术/杉木/近红外/预测模型/木材结晶度/变异分析Key words
wood science and technology/Cunninghamia lanceolata/near infrared spectroscopy/prediction model/wood crystallinity/variation analysis分类
农业科技引用本文复制引用
胡梦霄,杭芸,黄华宏,张胜龙,童再康,楼雄珍..杉木木材结晶度的近红外预测模型建立及变异分析[J].浙江农林大学学报,2017,34(2):361-368,8.基金项目
国家自然科学基金资助项目(31300565) （31300565）
浙江省农业新品种选育重大科技专项(2016C02056-5) （2016C02056-5）
浙江省农业科技重点项目(2011C12014) （2011C12014）
浙江农林大学亚热带森林资源培育研究中心预研项目(CCSFR2013002) （CCSFR2013002）
浙江省林学重中之重一级学科研究生创新项目(201527) （201527）
