Rapid Quality Control of Woodchip Parameters Using a Hand-Held Near Infrared Spectrophotometer

Leoni, Elena; Mancini, Manuela; Duca, Daniele; Toscano, Giuseppe

doi:10.3390/pr8111413

Cited by 16 publications

(11 citation statements)

References 41 publications

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“…Currently, several well‐investigated methods are available for the rapid determination of M in solid biofuels, such as capacitive measurement 60, 61, 230, TDR 60, 61, 126–128, electrical resistance 60, 61, 234, 236 infrared drying (gravimetric) 60, 256, NIRS 60, 86–96, 241, 242, microwave‐, or radio wave methods 60, 80, 120–125. Usually, most of these methods do not require any special sample preparation such as milling or grinding of the material and can be applied directly when fuels are delivered to the plant.…”

Section: Discussionmentioning

confidence: 99%

“…In particular, capacitive measurement, infrared drying and NIR spectroscopy have been investigated in detail in various studies in recent years 60, 61, 86–96, 241, 242. They usually show medium to good results in terms of instrument precision compared to the reference method (ISO 18134‐1 to ‐3) 13–15.…”

Section: Discussionmentioning

confidence: 99%

“…Due to the wide penetration depth into the sample and the particularly high sensitivity of the moisture measurement, NIRS is especially useful in rapidly analysing M in solid biofuels 60, 86–96, 241. However, instruments require a good calibration to the respective biofuel for precise M determination using NIRS methods (likewise capacitive methods).…”

Section: Discussionmentioning

confidence: 99%

“…Various approaches for the rapid determination of A and Q in solid biofuels were investigated in recent studies using, e.g., NIRS 1, 86–88, 91–97, 102, Laser applications 207, 208, 210, or X‐ray method 184. Most of the tested devices are already available on the market but mainly for other sectors and not especially for solid biofuels.…”

Section: Discussionmentioning

confidence: 99%

“…show potential for future studies 102. Various studies investigate the usability of IR methods to measure different parameters of solid biofuels like the carbon content or plastic contaminations 62–64, 72, 92–98. Kip et al evaluated the development of spectrometers and showed that they are increasingly robust and less susceptible to vibrations.…”

Section: Analysis Of Solid Biofuelsmentioning

confidence: 99%

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Analytical Methods for the Rapid Determination of Solid Biofuel Quality

Endriss

Kuptz

Hartmann

et al. 2023

Chemie Ingenieur Technik

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Fuel properties of solid biofuels are essential aspects for the energy‐efficient and low‐emission operation of biomass heat and power plants. Hence, fuel quality parameters are often defined and used for pricing in supply contracts. To simplify and accelerate analytical approaches, rapid analysis devices are required to determine fuel properties such as water‐ and ash content, calorific value, and chemical composition on‐site. This article gives an overview about available technologies and, if applicable, their current state of use as rapid analysis devices for solid biofuels.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Analysis Of Solid Biofuelsmentioning

confidence: 99%

See 3 more Smart Citations

Analytical Methods for the Rapid Determination of Solid Biofuel Quality

Endriss

Kuptz

Hartmann

et al. 2023

Chemie Ingenieur Technik

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Chemometrics using near-infrared spectra for the quantification of robusta coffee and chicory added as adulterants in roasted arabica coffee

Munyendo,

Babor,

Zhang

et al. 2023

Food Measure

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Roasted ground coffees are targets of concern regarding intentional adulteration with cheaper foreign materials because, in this form, it may be difficult to detect due to the small particle size and the dark color. Therefore, a significant interest is developing fast, sensitive, and accurate methodologies to quantify adulterants in roasted coffees. This study investigated the potential of using near-infrared spectroscopy (NIR) to quantity robusta coffee and chicory in roasted arabica coffee. The adulterated arabica coffee samples were composed of robusta coffee or chicory ranging from 2.5 to 30% in increments of 2.5%. Four regression approaches were applied: gradient boosting regression (GBR), multiple linear regression (MLR), k-nearest neighbor regression (KNNR), and partial least squares regression (PLSR). The first three regression models were performed on the features extracted from linear discriminant analysis (LDA) or principal component analysis (PCA). Additionally, two classification methods were applied (LDA and KNN). The regression models derived based on LDA-extracted features presented better performances than PCA ones. The best regression models for the quantification of robusta coffee were GBR (pRMSEP of 13.70% and R2 of 0.839) derived based on PCA-extracted features and MLR (pRMSEP of 1.11% and R2 of 0.998) derived based on LDA-extracted features. For the chicory quantification, the same models derived under the same settings as mentioned above also presented the best performances (GBR, pRMSEP = 9.37%, R2 = 0.924; MLR, pRMSEP = 1.54%, R2 = 0.997). The PLSR prediction errors for the quantification of arabica coffee and chicory were 9.90% and 8.09%, respectively. For the classification methods, the LDA model performed well compared to KNN. Generally, some models proved to be effective in quantifying robusta and chicory in roasted arabica coffee. The results of this study indicate that NIR spectroscopy could be a promising method in the coffee industry and other legal sectors for routine applications involving quality control of coffee.

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