|Publication type:||Research data|
|Title:||Dataset of fluorescence spectra and chemical parameters of olive oils|
Deriu, Marco Agostino
|Publisher / Ed. Institution:||Mendeley Data|
|Subjects:||Food engineering; Food chemistry; Fluorescence spectroscopy; Optical spectrum; Olive oil|
|Subject (DDC):||664: Food technology|
|Abstract:||This dataset encompasses fluorescence spectra and chemical parameters of 24 olive oil samples from the 2019–2020 harvest provided by the producer Conde de Benalúa, Granada, Spain. The oils are characterized by different qualities: 10 extra virgin olive oil (EVOO), 8 virgin olive oil (VOO), and 6 lampante olive oil (LOO) samples. For each sample, the dataset includes fluorescence spectra obtained with two excitation wavelengths and five chemical parameters necessary for the quality assessment of olive oil. The fluorescence spectra were obtained by exciting the samples at 395 nm and 365 nm and collecting the signal with a miniature spectrometer with a 1024-element CCD array with a resolution of 16 nm. Each olive oil sample was measured 20 times under identical conditions for excitation at 365 nm and 395 nm. Therefore, the dataset includes a total of 960 spectra (24 oil samples × 2 excitation wavelengths x 20 measurements). Each of the 960 spectra is an array of 1024 values whose elements are the intensity at the different pixel positions. For each olive oil sample, the dataset includes the values of the following chemical parameters: acidity, peroxide value, K_270, K_232, ethyl esters, and the quality of the samples (EVOO, VOO, or LOO). The chemical analysis of all the samples was performed by accredited laboratories according to the current European regulation. The dataset offers a unique possibility for researchers in food technology to develop machine learning models due to the availability of both spectroscopical and chemical data. The dataset can be used, for example, to predict one or multiple chemical parameters or to classify samples based on their quality from fluorescence spectra.|
|Further description:||The dataset was used for the study: Venturini, F., Sperti, M., Michelucci, U., Gucciardi, A., Martos, V.M. and Deriu, M.A., 2023. Extraction of physicochemical properties from the fluorescence spectrum with 1D convolutional neural networks: Application to olive oil. Journal of Food Engineering, 336, p.111198. https://doi.org/10.1016/j.jfoodeng.2022.111198 The description of the dataset acquisition is here: Venturini, F., Sperti, M., Michelucci, U., Gucciardi, A., Martos, V.M. and Deriu, M.A., 2023. Dataset of Fluorescence Spectra and Chemical Parameters of Olive Oils. arXiv preprint arXiv:2301.04471. https://doi.org/10.48550/arXiv.2301.04471|
|License (according to publishing contract):||CC BY 4.0: Attribution 4.0 International|
|Departement:||School of Engineering|
|Organisational Unit:||Institute of Applied Mathematics and Physics (IAMP)|
|Appears in collections:||ZHAW Forschungsdaten School of Engineering|
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Venturini, F., Sperti, M., Michelucci, U., Gucciardi, A., Martos, V., & Deriu, M. A. (2022). Dataset of fluorescence spectra and chemical parameters of olive oils [Data set]. Mendeley Data. https://doi.org/10.17632/thkcz3h6n6.6
Venturini, F. et al. (2022) ‘Dataset of fluorescence spectra and chemical parameters of olive oils’. Mendeley Data. Available at: https://doi.org/10.17632/thkcz3h6n6.6.
F. Venturini, M. Sperti, U. Michelucci, A. Gucciardi, V. Martos, and M. A. Deriu, “Dataset of fluorescence spectra and chemical parameters of olive oils.” Mendeley Data, Dec. 19, 2022. doi: 10.17632/thkcz3h6n6.6.
Venturini, Francesca, et al. Dataset of Fluorescence Spectra and Chemical Parameters of Olive Oils. Mendeley Data, 19 Dec. 2022, https://doi.org/10.17632/thkcz3h6n6.6.
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