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© 2023 MJH Life Sciences and Spectroscopy Online. All rights reserved.
© 2023 MJH Life Sciences™ and Spectroscopy Online. All rights reserved.
August 01, 2022
Spectroscopy offers a range of available techniques that can be differentiated by the use or omission of reference spectra.
June 01, 2022
In this second part of this four-part series on spectroscopy instrument components, we take a closer look at optical components or subassemblies used for vibrational spectroscopy instruments.
We propose a theoretical basis using vis-NIR spectroscopy for the development of an online nondestructive testing system for the quality of Nanguo pear fruit.
May 01, 2022
Our annual review of new products for atomic and molecular spectroscopy, including details by category and highlights of overarching trends.
March 01, 2022
High-performance instrumentation requires many critical components. We focus here on energy sources, lasers, and detectors.
January 01, 2022
In this study, we propose a low-altitude unmanned aerial vehicle (UAV) hyperspectral visible near-infrared (vis-NIR) remote sensing hardware platform, which combines efficiency and accuracy for high-precision remote sensing-based ecological surveys and statistical data collection on grassland desertification.
December 02, 2021
This issue is a compilation of five peer-reviewed articles on the combined application of UV-vis-NIR spectral data with advanced chemometrics.
Classification and identification of different wood species are demonstrated
using a portable near-infrared spectrometer, combined with four spectral pretreatment methods and three pattern recognition methods. Additional chemometric tools were used for comprehensive evaluation of classification model accuracy and complexity.
Given that grape seed oil has shown beneficial effects for consumers, there is a interest in measuring oil quality and potential adulteration. This study demonstrates an effective near-infrared (NIR) spectroscopy method, using a series of machine learning approaches for wavelength variable selection, to rapidly discriminate grape seed oil adulteration.
Spectral reflectance is a non-destructive method that is applicable to remote sensing and may be used to measure the chlorophyll content in a crop, which indicates the photosynthetic capacity, growth cycles, and degrees of stress (such as disease, insect infestation, and heavy metal stress) on plant ecosystems. This vis-NIR spectral reflectance method measures leaf chlorophyll using a wavelet analysis algorithm approach.