Application of NIR Spectroscopy to Wood and Wood-Derived Products

Schimleck, Laurie; Tsuchikawa, Satoru

doi:10.1201/b22513-42

Cited by 11 publications

(5 citation statements)

References 1 publication

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“…1000–2500 nm) provides key information for the detection of fraud in nuts. For example, the 1000–1100 nm band, at the beginning of the second overtone region, can be useful to discriminate hazelnuts of different geographical origins since that band can be associated with the presence of polyphenols in aromatic compounds [ 38 ] while the 1200 nm wavelength can be related to absorbances of the second overtone of C–H bonds of lipids [ 68 ]. Furthermore, the 1408–1650 nm region can be related to the N-H stretching (first overtone) of proteins, which can be useful for determining the origins of almonds [ 52 ].…”

Section: Nir-based Instrumentation and Analysis Mode For The Detectio...mentioning

confidence: 99%

NIR Sensing Technologies for the Detection of Fraud in Nuts and Nut Products: A Review

Vega-Castellote,

Sánchez,

Torres-Rodríguez

et al. 2024

Foods

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Food fraud is a major threat to the integrity of the nut supply chain. Strategies using a wide range of analytical techniques have been developed over the past few years to detect fraud and to assure the quality, safety, and authenticity of nut products. However, most of these techniques present the limitations of being slow and destructive and entailing a high cost per analysis. Nevertheless, near-infrared (NIR) spectroscopy and NIR imaging techniques represent a suitable non-destructive alternative to prevent fraud in the nut industry with the advantages of a high throughput and low cost per analysis. This review collects and includes all major findings of all of the published studies focused on the application of NIR spectroscopy and NIR imaging technologies to detect fraud in the nut supply chain from 2018 onwards. The results suggest that NIR spectroscopy and NIR imaging are suitable technologies to detect the main types of fraud in nuts.

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Section: Nir-based Instrumentation and Analysis Mode For The Detectio...mentioning

confidence: 99%

NIR Sensing Technologies for the Detection of Fraud in Nuts and Nut Products: A Review

Vega-Castellote,

Sánchez,

Torres-Rodríguez

et al. 2024

Foods

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Section: Near Infrared Spectroscopymentioning

confidence: 99%

“…Applications for NIR spectroscopy include rapid determination of oil, protein, starch, and moisture in a range of grains and their products [51], including forages and food products [76]. Other applications include identification of wheat varieties and seed health [50], fungal contamination [43], and prediction of protein and moisture concentration [51,76]. NIR has been widely adopted to measure protein and moisture concentration which is then used to determine the value (grade of the grain) and processing quality of the grain, i.e., baking quality in wheat and malting quality in barley.…”

Section: Near Infrared Spectroscopymentioning

confidence: 99%

Technologies and Data Analytics to Manage Grain Quality On-Farm: A Review

Walker¹,

Assadzadeh²,

Wallace³

et al. 2023

Preprint

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“…5 The foundational relationship between NIR spectroscopy and biochemistry is that near infrared energy incident on an object is either absorbed or reflected based on the objects molecular composition. 6…”

Section: Introductionmentioning

confidence: 99%

Analysis of alkaloids and reducing sugars in processed and unprocessed tobacco leaves using a handheld near infrared spectrometer

Castillo

Acosta

Hodge

et al. 2023

Journal of Near Infrared Spectroscopy

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Near infrared (NIR) spectroscopy calibration models were developed to predict chemical properties of flue-cured tobacco ( Nicotiana tabacum L.) leaf samples using a microPHAZIRTM handheld NIR spectrometer. The sample data set consisted of 348 leaf-bundled samples of upper-stalk flue-cured tobacco leaves collected from an array of cultivars evaluated in multiple locations. Unprocessed leaf samples were intact whole unground leaves collected from curing barns. Processed leaf samples were further dried and ground before scanning. The NIR prediction models for percent reducing sugars, percent total alkaloids, and percent nicotine were very good for processed leaves [r2 (SEp in %) values = 0.98 (0.82), 0.92 (0.17), and 0.92 (0.14), respectively]. The models for the same three variables for unprocessed leaves were also very good, with only slightly lower fit statistics [r2 (SEp) = 0.93 (1.58), 0.87 (0.22), and 0.88 (0.18), respectively). Fit statistics for anabasine NIR models were intermediate with r2 (SEp in %) values ranging from 0.73 (0.003) to 0.76 (0.003), while the lowest fit statistics were observed for anatabine and norticotine with r2 (SEp in %) ranging from 0.49 (0.005) to 0.55 (0.017), respectively, for both unprocessed and processed leaves. Hence, use of a handheld NIR spectrometer would be of more limited value for these variables. The chemical composition of flue-cured tobacco leaf samples for some chemical traits can be directly assessed at the point when the leaves exit the curing barns, thus minimizing the need to dry and grind samples for colorimetric and chromatographic analyses.

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Application of NIR Spectroscopy to Wood and Wood-Derived Products

Cited by 11 publications

References 1 publication

NIR Sensing Technologies for the Detection of Fraud in Nuts and Nut Products: A Review

NIR Sensing Technologies for the Detection of Fraud in Nuts and Nut Products: A Review

Technologies and Data Analytics to Manage Grain Quality On-Farm: A Review

Analysis of alkaloids and reducing sugars in processed and unprocessed tobacco leaves using a handheld near infrared spectrometer

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