Sunday, 21 June 2020
Pomegranate Peel as Suitable Source of High-Added Value Bioactives: Tailored Functionalized Meat Products
Thursday, 18 June 2020
Rapid liquid chromatographic method for the control of doxycycline and tiamulin residues and their metabolites in vivo assays with pigs: Treatment and depletion
Journal of Pharmaceutical and Biomedical Analysis, 2020, 190, 113428
DOI:10.1016/j.jpba.2020.113428

Thursday, 11 June 2020
AA1 & EcoChestnut
- Develop specific knowledge on production and promotion of Organic Chestnuts & Chestnut Products through a tailor made training course for farmers & producers.
- Support chestnut farmers & chestnut products producers to enter the market of Organic Chestnuts & Chestnut Products in order to enhance their development opportunities and their growth potential.
- Raise awareness in chestnuts & chestnut groves as part of cultural, historical and landscape heritage of the countries that produce them.
- Promote sustainable agricultural farming & encourage the application of organic farming among new and existing chestnut farmers and producers.
- The EcoChestnut Learning Model
- A Training Course on Organic Chestnuts & Chestnut Products
- A Manual for Trainers
- A Guidebook on Certification of Organic Chestnuts
- A Handbook on “Utilize the potential of the chestnut groves”
Monday, 8 June 2020
Scientific basis for the industrialization of traditionally used plants of the Rosaceae family
Food Chemistry, 2020, 330, 127197
https://doi.org/10.1016/j.foodchem.2020.127197

Friday, 5 June 2020
The effect of two antifungal commercial formulations on the metabolism of a commercial Saccharomyces cerevisiae strain and their repercussion on fermentation evolution and phenylalanine catabolism
Food Microbiology, 2020, 92, 103554

Thursday, 4 June 2020
Plant-Food Guarantee and Improvement
Date: June 5th, 2020
Program:
11:30- Greetings and presentation
11:35- Pre and post-harvest factors determining fruit nutritional quality.
Presenter: Bruno Mezzetti, Prof.- Full Professor Department of Agricultural, Food and Environmental Sciences – Università Politecnica delle Marche. Higlhy Cited Researcher 2019. (Visiting professor)
12:10- Circular Bio-Economy and the Case of Phenolic Compounds from Food By-Products.
Presenter: Jesús Simal Gándara, Prof.- Full Professor Department of Food and Analytical Chemistry– Vigo University. Higlhy Cited Researcher 2018.
12:30- Models for Quantification of Individual, Synergistic, and Antagonistic Anti- and Pro-Oxidant Responses.
Presenter: Miguel Angel Prieto Lage, PhD- Postdoctoral Researcher (Ramón y Cajal), Department of Food and Analytical Chemistry – Vigo University.
12:50- Discussion
Date: June 12th, 2020
Program:
11:30- Greetings and presentation
11:35- Breeding and biotechnology for improving nutritional quality.
Presenter: Bruno Mezzetti, Prof.- Full Professor Department of Agricultural, Food and Environmental Sciences – Università Politecnica delle Marche. Higlhy Cited Researcher 2019. (Visiting professor)
12:10- Technological Application of Tannin-Based Extracts.
Presenter: María Fraga Corral, PhD- Postdoctoral Researcher (Xunta de Galicia), Department of Food and Analytical Chemistry – Vigo University.
12:30- Phenolic Compounds as Nutraceutical Tools for the Prevention of Metabolic diseases.
Presenter: Tamara Forbes Hernández, PhD- Postdoctoral Researcher (Juan de la Cierva), Department of Food and Analytical Chemistry – Vigo University.
12:50- Discussion
Date: June 19th, 2020
Program:
11:30- Greetings and presentation
11:35- RNAi technology for food security and safety.
Presenter: Bruno Mezzetti, Prof.- Full Professor Department of Agricultural, Food and Environmental Sciences – Università Politecnica delle Marche. Higlhy Cited Researcher 2019. (Visiting professor)
12:10- Phenolic Compounds as Nutraceutical Tools for the Prevention of Cancer.
Presenter: Francesca Giampieri, PhD.- Distinguished Researcher, Department of Food and Analytical Chemistry – Vigo University. Higlhy Cited Researcher 2019.
12:30- Bioactive compounds recovery from winery industry by-products: vine shoots as study case.
Presenter: Particia Gullón Estévez, PhD- Researcher Laboratory of Microbiology and Technology of Marine Products, Instituto de Investigaciones Marinas (IIM-CSIC).
12:50- Discussion
Tuesday, 26 May 2020
Advantages of techniques to fortify food products with the benefits of fish oil
Food Research International, 2020, 137, 109353
DOI: 10.1016/j.foodres.2020.109353

Saturday, 23 May 2020
Dietary polyphenols for managing cancers: What have we ignored?
Trends in Food Science & Technology, 2020, 101, 150-164
DOI: 10.1016/j.tifs.2020.05.017

Monday, 27 April 2020
Recent advances in extracting phenolic compounds from food and their use in disease prevention and as cosmetics
Critical Reviews in Food Science and Nutrition
Friday, 24 April 2020
Mitigation of emerging implications of climate change on food production systems
Thursday, 23 April 2020
Food production link to underground waters quality in A Limia river basin
Agriculture, Ecosystems & Environment, 2020, 297, 106969
DOI:10.1016/j.agee.2020.106969

Wednesday, 22 April 2020
Toward a sustainable metric and indicators for the goal of sustainability in agricultural and food production
Critical Reviews in Food Science and Nutrition

Saturday, 4 April 2020
Thursday, 2 April 2020
Latest developments in the application of cyclodextrin host-guest complexes in beverage technology processes
Saturday, 1 February 2020
Random Forest, Artificial Neural Network, and Support Vector Machine Models for Honey Classification
Different separated protein fractions by the electrophoretic method in polyacrylamide gel were used to classify two different types of honeys, Galician honeys and commercial honeys produced and packaged outside of Galicia. Random forest, artificial neural network, and support vector machine models were tested to differentiate Galician honeys and other commercial honeys produced and packaged outside of Galicia. The results obtained for the best random forest model allowed us to determine the origin of honeys with an accuracy of 95.2%. The random forest model, and the other developed models, could be improved with the inclusion of new data from different commercial honeys.