1Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou, Zhejiang 311400, China
2AgResearch Ltd., Christchurch 8140, New Zealand
| Received 06 Jun 2021 |
Accepted 21 Dec 2021 |
Published 12 Jan 2022 |
The internal cycling of nitrogen (N) storage and consumption in trees is an important physiological mechanism associated with tree growth. Here, we examined the capability of near-infrared spectroscopy (NIR) to quantify the concentration across tissue types (needle, trunk, branch, and root) without time and cost-consuming. The NIR spectral data of different tissues from slash pine trees were collected, and the concentration in each tissue was determined using standard analytical method in laboratory. Partial least squares regression (PLSR) models were performed on a set of training data randomly selected. The full-length spectra and the significant multivariate correlation (sMC) variable selected spectra were used for model calibration. Branch, needle, and trunk PLSR models performed well for the concentration using both full length and sMC selected NIR spectra. The generic model preformatted a reliable accuracy with R2C and R2CV of 0.62 and 0.66 using the full-length spectra, and 0.61 and 0.65 using sMC-selected spectra, respectively. Individual tissue models did not perform well when being used in other tissues. Five significantly important regions, i.e., 1480, 1650, 1744, 2170, and 2390 nm, were found highly related to the content in plant tissues. This study evaluates a rapid and efficient method for the estimation of content in different tissues that can help to serve as a tool for tree storage and recompilation study.
