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ZENODO
Dataset . 2019
License: CC BY SA
Data sources: ZENODO
ZENODO
Dataset . 2019
License: CC BY SA
Data sources: Datacite
ZENODO
Dataset . 2019
License: CC BY SA
Data sources: Datacite
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Non-destructive determination of taste-related compounds in tomato using NIR spectra

Authors: Ibañez, Ginés; Cebolla-Cornejo, Jaime; Martí, Raul; Roselló, Salvador; Valcárcel, Mercedes;

Non-destructive determination of taste-related compounds in tomato using NIR spectra

Abstract

Near infrared (NIR) diffuse reflectance was used to predict the contents of taste-related compounds of tomato. Models were obtained for several varietal types including processing tomato, cherry and cocktail tomato, mid-sized tomato and tomato landraces, with a wide range of varieties. Good performance was obtained for the prediction of soluble solids, sugars and acids, considering a non-destructive methodology applied to fruits with different internal structure. Specific models averaged RMSEP (%mean) values lower than 6.1% for SSC, 13.3% for fructose, 14.1% for glucose, 12.7% for citric acid, 13.8% for malic acid and 21.9% for glutamic acid. The performance was dependent on varietal type. General models with a higher number of samples and variation did not improve the performance of specific models. The models obtained, either specific or general, couldn't be extrapolated to external assays and an internal calibration would be required for each assay in order to provide a reliable performance. Ibáñez, G., Cebolla-Cornejo, J., Martí, R., Roselló, S. and Valcárcel, M., 2019. Non-destructive determination of taste-related compounds in tomato using NIR spectra. Journal of Food Engineering, 263, pp.237-242 For more detailed data contact the authors AckowledgementsThis research was performed despite the lack of direct public funding for its development and thanks to the enthusiasm of the authors.The authors thank Dr. Lahoz and Dr. Campillo for providing processing tomato samples and Dr. Moreno for providing samples from tomato landraces. G. Ibañez thanks Universitat Jaume I for funding his pre-doctoral grant (PREDOC/2015/45). Link to publication: https://doi.org/10.1016/j.jfoodeng.2019.07.004 Link to repository: http://hdl.handle.net/10234/183798

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average