Utilize este identificador para referenciar este registo: http://hdl.handle.net/10362/183452
Título: Relationship between Physicochemical and Cooking Quality Parameters with Estimated Glycaemic Index of Rice Varieties
Autor: Pereira, Cristiana L.
Sousa, Inês
Lourenço, Vanda M.
Sampaio, Pedro
Gárzon, Raquel
Rosell, Cristina M.
Brites, Carla
Palavras-chave: cooking parameters
glycaemic index
physicochemical parameters
rice commercial types
Food Science
Microbiology
Health(social science)
Health Professions (miscellaneous)
Plant Science
Data: Jan-2024
Resumo: Rice is a significant staple food in the basic diet of the global population that is considered to have a high glycaemic index. The study of the physical and chemical parameters in rice that are related to the starch digestion process, which allows us to quickly predict the glycaemic index of varieties, is a major challenge, particularly in the classification and selection process. In this context, and with the goal of establishing a relationship between physicochemical properties and starch digestibility rates, thus shedding light on the connections between quality indicators and their glycaemic impact, we evaluated various commercial rice types based on their basic chemical composition, physicochemical properties, cooking parameters, and the correlations with digestibility rates. The resistant starch, the gelatinization temperature and the retrogradation (setback) emerge as potent predictors of rice starch digestibility and estimated glycaemic index, exhibiting robust correlations of r = −0.90, r = −0.90, and r = −0.70 (p ≤ 0.05), respectively. Among the rice types, Long B and Basmati stand out with the lowest estimated glycaemic index values (68.44 and 68.10), elevated levels of resistant starch, gelatinization temperature, and setback values. Furthermore, the Long B showcases the highest amylose, while the Basmati with intermediate, revealing intriguingly strong grain integrity during cooking, setting it apart from other rice varieties.
Descrição: Funding Information: Project TRACE-RICE—Tracing rice and valorising side streams along Mediterranean blockchain, grant No. 1934, of the PRIMA Programme, supported under Horizon 2020, the European Union’s Framework Programme for Research and Innovation. Research Unit, GREEN-IT Bioresources for Sustainability Base Funding https://doi.org/10.54499/UIDB/04551/2020 and Programmatic Funding https://doi.org/10.54499/UIDP/04551/2020, FCT- Foundation for Science and Technology (Portugal), through PhD grant number 2020.09555BD to Cristiana Pereira and PhD grant number 2023.02433.BDANA to Inês Sousa. Program PORTUGAL 2020 Partnership Agreement, under the scope of Biodata.pt–Infraestrutura Portuguesa de Dados Biológicos (22231/01/SAICT/2016), through the European Regional Development Fund (ERDF) for data management. Publisher Copyright: © 2023 by the authors.
Peer review: yes
URI: http://hdl.handle.net/10362/183452
DOI: https://doi.org/10.3390/foods13010135
ISSN: 2304-8158
Aparece nas colecções:Home collection (ITQB)

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