• 论文与研究报告 •

### 桉树叶片水分状态的近红外光谱检测

1. 国家林业局桉树研究开发中心 湛江 524022
• 收稿日期:2016-08-05 修回日期:2017-02-21 出版日期:2017-05-25 发布日期:2017-06-22
• 基金资助:
中央级公益性科研院所基本科研业务费专项资金项目（CAFYBB2017MA022）；广东省科技计划项目（2012B020302005）；“十三五”科技部国家重点研发计划（2016YFD0600503）。

### Assessing Leaf Water Status of Eucalyptus Using NIRS

Lu Wanhong, Yang Guili, Lin Yan, Wang Chubiao, Luo Jianzhong

1. Eucalypt Research Centre of State Forestry Administration Zhanjiang 524022
• Received:2016-08-05 Revised:2017-02-21 Online:2017-05-25 Published:2017-06-22

Abstract: [Objective] [Objective] The aim of this study was to monitor the leaf relative water content (RWC) and water potential (Ψw) in structured Eucalyptus camaldulensis and E. tereticornis populations by Near Infrared spectroscopy (NIRS). [Method]The samples were collected from the breeding population, which contained 21 families of 7 provenances for E. camaldulensis, and 26 families of 5 provenances for E. tereticornis. A total of 20 average-growth seedlings per family were chosen, divided into 5 groups randomly, and were watered every day by replenishing 100%, 70%, 50%, 30% and 0% of the average water loss of these seedlings from pots by evapotranspiration, respectively. In 60 days after water controls, three seedlings per water control and per family were chosen, of which the top second pair fully expanded leaves were used to be scanned with a portable near infrared spectrometer for getting the NIRS spectra. After the scanning, the leaf RWC and leaf Ψwwere measured. The measurements were conducted once a day for consecutive 18 days.[Result] The results showed that there was a close relationship between water status traits and the raw NIRS at 1 860-1 960 nm. However, after the transform of the 2nd derivate preprocess for raw NIR spectra, there were significant differences of leaf RWC and Ψw among all samples in the whole range of NIRs. The NIRs calibrated PLS(partial least squares) model for the prediction of leaf RWC and Ψw both showed a good fitting. The correlation coefficient between predicted and measured value (R2) were 0.92 and 0.84 for leaf Ψw and RWC, respectively. The average differences between predicted and measured values (RMSE) were 0.25 and 1.31 for leaf Ψw and RWC, respectively. [Conclusion] The coefficient of variation curve showed that the information of whole NIRS range should be used to calibrate the PLS model for the water status traits associated physiological characters in Eucalyptus. All the findings in this study highlight the advantages and perspectives of NIRS in monitoring leaf water status traits in structured Eucalyptus populations.