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NIR Spectroscopy for Discriminating and Predicting the Sensory Profile of Dry-Cured Beef "Cecina"., , , , , и . Sensors, 20 (23): 6892 (2020)Incorporating authentic learning experiences in the Degree in Agro-Food Engineering., , и . TEEM, стр. 378-383. ACM, (2021)Flavonoid and Antioxidant Capacity of Propolis Prediction Using Near Infrared Spectroscopy., , , и . Sensors, 17 (7): 1647 (2017)A digitalization strategy for quality control in food industry based on Artificial Intelligence techniques., , , , , и . INDIN, стр. 221-226. IEEE, (2018)The application of new teaching methodologies: experience in actual situations., и . TEEM, стр. 86-92. ACM, (2018)Prediction of Sensory Parameters of Cured Ham: A Study of the Viability of the Use of NIR Spectroscopy and Artificial Neural Networks., , , , , и . Sensors, 20 (19): 5624 (2020)Determination of the Mineral Composition and Toxic Element Contents of Propolis by Near Infrared Spectroscopy., , , , , , и . Sensors, 15 (11): 27854-27868 (2015)Accurate Prediction of Sensory Attributes of Cheese Using Near-Infrared Spectroscopy Based on Artificial Neural Network., , , , , , и . Sensors, 20 (12): 3566 (2020)Prediction of Mineral Composition in Wheat Flours Fortified with Lentil Flour Using NIR Technology., , , и . Sensors, 23 (3): 1491 (февраля 2023)Application of New Assessment Tools in Engineering Studies: The Rubric., , , , , , и . Rev. Iberoam. de Tecnol. del Aprendiz., 9 (4): 139-143 (2014)