期刊
REMOTE SENSING
卷 5, 期 1, 页码 254-273出版社
MDPI
DOI: 10.3390/rs5010254
关键词
agriculture; bioenergy; biomethane potential; hyperspectral remote sensing
类别
资金
- FNR (Fonds National de la Recherche, Luxembourg, project HYPERSPEC) [C09/SR/21]
- FNR (Fonds National de la Recherche, Luxembourg, project BIONIR) [CO8/SR/13]
- FNR (Fonds National de la Recherche, Luxembourg, project SOC3D) [INTER/STEREOII/10/01]
- BMWi (Bundesministerium fur Wirtschaft, Germany) (project EnMAP-BMP) [50 EE 1021]
Biogas production from energy crops by anaerobic digestion is becoming increasingly important. The amount of biogas that can be produced per unit of biomass is referred to as the biomethane potential (BMP). For energy crops, the BMP varies among varieties and with crop state during the vegetation period. Traditional ways of analytical BMP determination are based on fermentation trials and require a minimum of 30 days. Here, we present a faster method for BMP retrievals using near infrared spectroscopy and partial least square regression (PLSR). PLSR prediction models were developed based on two different sets of spectral reflectance data: (i) laboratory spectra of silage samples and (ii) airborne imaging spectra (HyMap) of maize canopies under field (in situ) conditions. Biomass was sampled from 35 plots covering different maize varieties and the BMP was determined as BMP per mass (BMPFM, Nm(3) biogas/t fresh matter (Nm(3)/t FM)) and BMP per area (BMParea, Nm(3) biogas/ha (Nm(3)/ha)). We found that BMPFM significantly differs among maize varieties; it could be well retrieved from silage samples in the laboratory approach (R-cv(2) = 0.82, n = 35), especially at levels >190 Nm(3)/t. In the in situ approach PLSR prediction quality declined (R-cv(2) = 0.50, n = 20). BMParea, on the other hand, was found to be strongly correlated with total biomass, but could not be satisfactorily predicted using airborne HyMap imaging data and PLSR.
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