Home > XXX International Horticultural Congress IHC2018: International Symposium on Fruit and Vegetables for Processing, International Symposium on Quality and Safety of Horticultural Products and VII International Symposium on Human Health Effects of Fruits and Vegetables > Artificial neural network as alternative method for prediction of sugar and acidity using near-infrared spectroscopy in table grapes

Articles

Artificial neural network as alternative method for prediction of sugar and acidity using near-infrared spectroscopy in table grapes

Article number

1292_42

Pages

321 – 328

Language

English

Abstract

Publication

XXX International Horticultural Congress IHC2018: International Symposium on Fruit and Vegetables for Processing, International Symposium on Quality and Safety of Horticultural Products and VII International Symposium on Human Health Effects of Fruits and Vegetables

Authors

C. Poblete-Echeverría, A.J. Daniels, H.H. Nieuwoudt, U.L. Opara

Keywords

whole table grape bunches, total soluble solid, titratable acidity, sugar-acid ratio, near-infrared spectroscopy, non-destructive measurements, machine learning, artificial neural networks

Full text

https://doi.org/10.17660/ActaHortic.2020.1292.42

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