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Rapid Assessment of Bioenergy Feedstock Quality by Near Infrared Reflectance Spectroscopy
Author(s) -
Foster A. J.,
Kakani V. G.,
Ge J.,
Mosali J.
Publication year - 2013
Publication title -
agronomy journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.752
H-Index - 131
eISSN - 1435-0645
pISSN - 0002-1962
DOI - 10.2134/agronj2013.0100
Subject(s) - panicum virgatum , andropogon , neutral detergent fiber , panicum , zoology , bioenergy , spectroradiometer , forage , near infrared reflectance spectroscopy , agronomy , sorghum , poaceae , chemistry , environmental science , biofuel , reflectivity , near infrared spectroscopy , biology , ecology , physics , optics , neuroscience
The portability, quick turnaround time, and low long‐term maintenance costs of near infrared reflectance spectroscopy (NIRS) offers rapid determination of feedstock quality. The objective of this study was to estimate biomass composition (total N [TN], acid detergent fiber [ADF], neutral detergent fiber [NDF], and acid detergent lignin [ADL]) with NIRS. Linear regression of simple ratios (SRs), and partial least square (PLS) regression models with all wavebands (WBs) and selected waveband (SB) approaches were used. Laboratory analysis was conducted for TN, ADF, NDF, and ADL. Samples from 13 switchgrass ( Panicum virgatum L.) cultivars, ES5200 high‐biomass sorghum [ Sorghum bicolor (L.) Moench], and mixed grasses composed of Alamo switchgrass, Cheyenne Indian grass [ Sorghastrum nutans (L.) Nash] and Kaw big bluestem ( Andropogon gerardii Vitman) fertilized at different rates of N ranging from 0 to 252 kg N ha –1 yr –1 were collected from two locations in Oklahoma. Spectral reflectance between 1000 and 2500 nm was collected with an ASD Fieldspec spectroradiometer from all samples. Results showed that TN can be estimated using a SR of R 2080 /R 2190 ( r 2 = 0.84), while a SR of R 2190 /R 2230 ( r 2 = 0.65) was able to estimate ADF ( r 2 = 0.70), NDF ( r 2 = 0.65), and ADL ( r 2 = 0.67). In comparison with SRs, a SB PLS model gave better prediction accuracy with nine wavebands for TN ( r 2 = 0.93) and seven wavebands for ADF ( r 2 = 0.78), NDF ( r 2 = 0.78), and ADL ( r 2 = 0.65). In conclusion, the success of both SR and SB PLS for estimating bioenergy feedstock composition indicates opportunities for instrument development for practical purposes.