Abstract

Near infrared laboratory data of whole fresh leaves were evaluated with respect to leaf chemical composition. Near infrared spectra were measured for 211 foliage samples including both broad- and needle-leaved species. A multiple linear regression analysis was used to determine if reflectance data from fresh leaf samples contains information on nitrogen, lignin and cellulose concentrations. Calibration equations were developed for all three leaf constituents, indicating that information on leaf biochemistry is present in the spectra of fresh as well as dried, ground leaf samples.

© 1994 NIR Publications

Nondestructive detection of anthocyanin content in fresh leaves of purple maize using hyperspectral data

Xin Yang, Shichen Gao, Xiaohe Gu, Chao Zhang, Qian Sun, Zhonghui Wei, Xueqian Hu, and Xuzhou Qu
Appl. Opt. 61(21) 6213-6222 (2022)

Fluorescence sensing techniques for vegetation assessment

Lawrence A. Corp, Elizabeth M. Middleton, James E. McMurtrey, Petya K. Entcheva Campbell, and L. Maryn Butcher
Appl. Opt. 45(5) 1023-1033 (2006)

Nondestructive nitrogen content estimation in tomato plant leaves by Vis-NIR hyperspectral imaging and regression data models

Razieh Pourdarbani, Sajad Sabzi, Mohammad H. Rohban, Ginés García-Mateos, and Juan I. Arribas
Appl. Opt. 60(30) 9560-9569 (2021)

Rapid detection of cellulose and hemicellulose contents of corn stover based on near-infrared spectroscopy combined with chemometrics

Na Wang, Longwei Li, Jinming Liu, Jianfei Shi, Yang Lu, Bo Zhang, Yong Sun, and Wenzhe Li
Appl. Opt. 60(15) 4282-4290 (2021)

Estimation of coniferous forest aboveground biomass with aggregated airborne small-footprint LiDAR full-waveforms

Haiming Qin, Cheng Wang, Xiaohuan Xi, Jianlin Tian, and Guoqing Zhou
Opt. Express 25(16) A851-A869 (2017)