Production of an innovative biowaste-derived fertilizer: Rapid monitoring of physical-chemical parameters by hyperspectral imaging

•Biowaste fertilizer production at pilot plant scale.•Rapid monitoring of fertilizer production process by hyperspectral imaging.•Correlation between physical-chemical parameters and spectral signatures by PLS.•No sample preparation required, differently from classical analytical techniques.•The pro...

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Veröffentlicht in:Waste management (Elmsford) 2018-05, Vol.75, p.141-148
Hauptverfasser: Serranti, S., Trella, A., Bonifazi, G., Izquierdo, C. Garcia
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Sprache:eng
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Zusammenfassung:•Biowaste fertilizer production at pilot plant scale.•Rapid monitoring of fertilizer production process by hyperspectral imaging.•Correlation between physical-chemical parameters and spectral signatures by PLS.•No sample preparation required, differently from classical analytical techniques.•The proposed HSI approach can be applied both “in situ“ and/or at “laboratory scale”. In this work the possibility to apply hyperspectral imaging as a fast and non-destructive technique for the monitoring of the production process at pilot plant scale of an innovative biowaste-derived fertilizer was explored. Different mixtures of urban organic waste, farm organic residues, biochar and vegetable active principles were selected and utilized in two different European countries, Italy and Spain, for the production of the innovative fertilizer. The biowaste-derived fertilizer samples were collected from the pilot plant piles at different curing time and acquired by the hyperspectral imaging device. Spectra have been collected in the near infrared wavelength range (1000–1700 nm). Conventional analyses were carried out on the same samples in order to find correlations between the physical-chemical parameters detected at laboratory scale, and the acquired reflectance spectra. The investigated parameters were: pH, electrical conductivity, soluble total organic carbon and soluble total nitrogen. Hyperspectral data were processed adopting chemometric strategies through the application of principal component analysis, for exploratory purposes, and partial least squares analysis to establish correlations between spectral features and measured physical-chemical parameters. Good correlations, with R2 ranging between 0.85 and 0.96, were obtained for all the investigated parameters. Results showed as the proposed approach, based on hyperspectral imaging, is suitable to be adopted for a rapid and non-destructive monitoring of waste-derived fertilizer production.
ISSN:0956-053X
1879-2456
DOI:10.1016/j.wasman.2018.02.013