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Prediction of coffee aroma from single roasted coffee beans by hyperspectral imaging (2021)
Journal Article
Caporaso, N., Whitworth, M. B., & Fisk, I. D. (2022). Prediction of coffee aroma from single roasted coffee beans by hyperspectral imaging. Food Chemistry, 371, Article 131159. https://doi.org/10.1016/j.foodchem.2021.131159

Coffee aroma is critical for consumer liking and enables price differentiation of coffee. This study applied hyperspectral imaging (1000–2500 nm) to predict volatile compounds in single roasted coffee beans, as measured by Solid Phase Micro Extractio... Read More about Prediction of coffee aroma from single roasted coffee beans by hyperspectral imaging.

Assessment of milk fat content in fat blends by 13 C NMR spectroscopy analysis of butyrate (2018)
Journal Article
Sacchi, R., Paduano, A., Caporaso, N., Picariello, G., Romano, R., & Addeo, F. (2018). Assessment of milk fat content in fat blends by 13 C NMR spectroscopy analysis of butyrate. Food Control, 91, https://doi.org/10.1016/j.foodcont.2018.04.011

Butyric acid (butyrate) is a candidate marker of milk fat in complex fat blends, since it is exclusive of milk triacylglycerols (TAGs) from different ruminant species. In this work, we determined the amount of milk fat used for the preparation of fat... Read More about Assessment of milk fat content in fat blends by 13 C NMR spectroscopy analysis of butyrate.

Variability of single bean coffee volatile compounds of Arabica and robusta roasted coffees analysed by SPME-GC-MS (2018)
Journal Article
Caporaso, N., Whitworth, M. B., Cui, C., & Fisk, I. D. (2018). Variability of single bean coffee volatile compounds of Arabica and robusta roasted coffees analysed by SPME-GC-MS. Food Research International, 108, 628-640. https://doi.org/10.1016/j.foodres.2018.03.077

We report on the analysis of volatile compounds by SPME-GC-MS for individual roasted coffee beans. The aim was to understand the relative abundance and variability of volatile compounds between individual roasted coffee beans at constant roasting con... Read More about Variability of single bean coffee volatile compounds of Arabica and robusta roasted coffees analysed by SPME-GC-MS.

Hyperspectral imaging for non-destructive prediction of fermentation index, polyphenol content and antioxidant activity in single cocoa beans (2018)
Journal Article
Caporaso, N., Whitworth, M. B., Fowler, M. S., & Fisk, I. D. (2018). Hyperspectral imaging for non-destructive prediction of fermentation index, polyphenol content and antioxidant activity in single cocoa beans. Food Chemistry, 258, https://doi.org/10.1016/j.foodchem.2018.03.039

The aim of the current work was to use hyperspectral imaging (HSI) in the spectral range 1000-2500 nm to quantitatively predict fermentation index (FI), total polyphenols (TP) and antioxidant activity (AA) of individual dry fermented cocoa beans scan... Read More about Hyperspectral imaging for non-destructive prediction of fermentation index, polyphenol content and antioxidant activity in single cocoa beans.

Rapid prediction of single green coffee bean moisture and lipid content by hyperspectral imaging (2018)
Journal Article
Caporaso, N., Whitworth, M. B., Grebby, S., & Fisk, I. D. (2018). Rapid prediction of single green coffee bean moisture and lipid content by hyperspectral imaging. Journal of Food Engineering, 227, 18-29. https://doi.org/10.1016/j.jfoodeng.2018.01.009

© 2018 The Authors Hyperspectral imaging (1000–2500 nm) was used for rapid prediction of moisture and total lipid content in intact green coffee beans on a single bean basis. Arabica and Robusta samples from several growing locations were scanned usi... Read More about Rapid prediction of single green coffee bean moisture and lipid content by hyperspectral imaging.

Near infrared spectroscopy and hyperspectral imaging for non-destructive quality assessment of cereal grains (2018)
Journal Article
Caporaso, N., Whitworth, M. B., & Fisk, I. D. (2018). Near infrared spectroscopy and hyperspectral imaging for non-destructive quality assessment of cereal grains. Applied Spectroscopy Reviews, 53(8), 667-687. https://doi.org/10.1080/05704928.2018.1425214

Hyperspectral imaging (HSI) combines spectroscopy and imaging, providing information about the chemical properties of a material and their spatial distribution. It represents an advance of traditional Near-Infrared (NIR) spectroscopy. The present wor... Read More about Near infrared spectroscopy and hyperspectral imaging for non-destructive quality assessment of cereal grains.

Non-destructive analysis of sucrose, caffeine and trigonelline on single green coffee beans by hyperspectral imaging (2017)
Journal Article
Caporaso, N., Whitworth, M. B., Grebby, S., & Fisk, I. D. (2018). Non-destructive analysis of sucrose, caffeine and trigonelline on single green coffee beans by hyperspectral imaging. Food Research International, 106, https://doi.org/10.1016/j.foodres.2017.12.031

Hyperspectral imaging (HSI) is a novel technology for the food sector that enables rapid non-contact analysis of food materials. HSI was applied for the first time to whole green coffee beans, at a single seed level, for quantitative prediction of su... Read More about Non-destructive analysis of sucrose, caffeine and trigonelline on single green coffee beans by hyperspectral imaging.

Application of calibrations to hyperspectral images of food grains: example for wheat falling number (2017)
Journal Article
Caporaso, N., Whitworth, M. B., & Fisk, I. D. (2017). Application of calibrations to hyperspectral images of food grains: example for wheat falling number. Journal of Spectral Imaging, 6(a4), https://doi.org/10.1255/jsi.2017.a4

The presence of a few kernels with sprouting problems in a batch of wheat can result in enzymatic activity sufficient to compromise flour functionality and bread quality. This is commonly assessed using the Hagberg Falling Number (HFN) method, which... Read More about Application of calibrations to hyperspectral images of food grains: example for wheat falling number.