Application of spectroscopic and multispectral imaging technologies on the assessment of ready-to-eat pineapple quality: A performance evaluation study of machine learning models generated from two commercial data analytics tools-Reference-Cited by-同舟云学术

Application of spectroscopic and multispectral imaging technologies on the assessment of ready-to-eat pineapple quality: A performance evaluation study of machine learning models generated from two commercial data analytics tools

Published:2020-08 Issue: Volume:175 Page:105529
ISSN:0168-1699
Container-title:Computers and Electronics in Agriculture
language:en
Short-container-title:Computers and Electronics in Agriculture

Author:

Manthou Evanthia,Lago Sergio-Llaneza,Dagres Evaggelos,Lianou Alexandra,Tsakanikas Panagiotis,Panagou Efstathios Z.,Anastasiadi Maria,Mohareb Fady,Nychas George–John E.

Funder

European Union’s Horizon 2020

Publisher

Elsevier BV

Subject

Horticulture,Computer Science Applications,Agronomy and Crop Science,Forestry

Reference62 articles.

1. Mid-infrared spectroscopy and chemometrics for the authentication of meat products;Al-Jowder;J. Agric. Food Chem.,1999

2. Rapid monitoring of the spoilage of minced beef stored under conventionally and active packaging conditions using Fourier transform infrared spectroscopy in tandem with chemometrics;Ammor;Meat Sci.,2009

3. Prediction of chicken quality attributes by near infrared spectroscopy;Barbin;Food Chem.,2015

4. Partial least squares for discrimination;Barker;J. Chemom.,2003

5. Training algorithm for optimal margin classifiers;Boser;Proc. Fifth Annu. ACM Work. Comput. Learn. Theory,1992

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