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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, doi:10.1016/j.foodcont.2018.04.011. ISSN 0956-7135

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

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). doi:10.1016/j.foodres.2018.03.077. ISSN 0963-9969

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

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, 228, doi:10.1016/j.jfoodeng.2018.01.009. ISSN 0260-8774

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 using a “push-broom” s... Read More

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. doi: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

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, doi:10.1016/j.foodres.2017.12.031. ISSN 0963-9969

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

Protein content prediction in single wheat kernels using hyperspectral imaging (2017)
Journal Article
Caporaso, N., Whitworth, M. B., & Fisk, I. D. (2018). Protein content prediction in single wheat kernels using hyperspectral imaging. Agroforestry Systems, 240, doi:10.1016/j.foodchem.2017.07.048. ISSN 0167-4366

Hyperspectral imaging (HSI) combines Near-infrared (NIR) spectroscopy and digital imaging to give information about the chemical properties of objects and their spatial distribution. Protein content is one of the most important quality factors in whe... Read More

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), doi:10.1255/jsi.2017.a4. ISSN 2040-4565

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