Robust functional near infrared spectroscopy denoising using multiple wavelet shrinkage based on a hemodynamic response model

Gihyoun Lee, Seung Hyun Lee, Sang Hyeon Jin, and Jinung An

J. Near Infrared Spectrosc. 26(2), 79-86 (2018)  View: PDF

Selection of a calibration sample subset by a semi-supervised method

Zhonghai He, Zhenhe Ma, Mengchao Li, and Yang Zhou

J. Near Infrared Spectrosc. 26(2), 87-94 (2018)  View: PDF

Prediction of saponin content in soapnut (Sapindus mukorossi Gaertn.) fruits by near infrared spectroscopy

Yanjie Li, Wenhao Shao, Ruxiang Dong, Jingmin Jiang, and Songfeng Diao

J. Near Infrared Spectrosc. 26(2), 95-100 (2018)  View: PDF

Automatic classification of tobacco leaves based on near infrared spectroscopy and nonnegative least squares

Zhang Jianqiang, Liu Weijuan, Zhang Huaihui, Hou Ying, Yang Panpan, Li Changyu, Yang Yanmei, and Li Ming

J. Near Infrared Spectrosc. 26(2), 101-105 (2018)  View: PDF

Influence of spectral acquisition technique and wood anisotropy on the statistics of predictive near infrared–based models for wood density

Emylle Veloso Santos Costa, Maria Fernanda Vieira Rocha, Paulo Ricardo Gherardi Hein, Evelize Aparecida Amaral, and Luana Maria dos Santos

J. Near Infrared Spectrosc. 26(2), 106-116 (2018)  View: PDF

Global near infrared spectroscopy models to predict wood chemical properties of Eucalyptus

Gary R Hodge, Juan Jose Acosta, Faride Unda, William C Woodbridge, and Shawn D Mansfield

J. Near Infrared Spectrosc. 26(2), 117-132 (2018)  View: PDF

A comparison of point and imaging visible-near infrared spectroscopy for determining soil organic carbon

Mohammad Sadegh Askari, Sharon M O'Rourke, and Nicholas M Holden

J. Near Infrared Spectrosc. 26(2), 133-146 (2018)  View: PDF