Use of spectral reflectance from a compact spectrometer to assess chlorophyll content in Zizania latifolia

Abstract

Hyperspectral remote sensing is frequently used to monitor chlorophyll content, an important characteristic for assessing photosynthetic ability, health and defence against a variety of degenerative diseases. To obtain hyperspectral data, field portable spectroradiometers, such as Ocean Optics Hyperspectral Vis-NIR spectroradiometers and Analytical Spectral Devices FieldSpec series, have been widely used. The development of an affordable hyperspectral remote sensing system would be advantageous. Highly sensitive, affordable and cost-effective finger-tip size spectrometers have recently been released. In this study we investigate the potential of hyperspectral data obtained from such a compact spectrometer (C12880MA-10, Hamamatsu Photonics) for estimating chlorophyll content in Zizania latifolia. We also tested the efficacy of five pre-processing techniques (first derivative reflectance, continuum-removal transformation, de-trending, multiplicative scatter correction and standard normal variate) in conjunction with five machine learning algorithms.