Modelling the influence of time and temperature on the respiration rate of fresh oyster mushrooms

• Tipo: Artigo em Revista Científica Internacional
• Data: 2015

Autores

Azevedo, S (Autor) Outra; Cunha, LM (Autor) FCUP; Fonseca, SC (Autor) FCUP

Revista

Título: Food Science and Technology International

Vol. 21

Páginas: 593-603

ISSN: 1082-0132

Editora: SAGE

Indexação

ISI Web of Knowledge - 14 Citações

Scopus - 16 Citações

Outras Informações

ID Authenticus: P-00G-WF1

DOI: 10.1177/1082013214555925

Abstract (EN): The respiration rate of mushrooms is an important indicator of postharvest senescence. Storage temperature plays a major role in their rate of respiration and, therefore, in their postharvest life. In this context, reliable predictions of respiration rates are critical for the development of modified atmosphere packaging that ultimately will maximise the quality of the product to be presented to consumers. This work was undertaken to study the influence of storage time and temperature on the respiration rate of oyster mushrooms. For that purpose, oyster mushrooms were stored at constant temperatures of 2, 6, 10, 14 and 18 degrees C under ambient atmosphere. Respiration rate data were measured with 8-h intervals up to 240 h. A decrease of respiration rate was found after cutting of the carpophores. Therefore, time effect on respiration rate was modelled using a first-order decay model. The results also show the positive influence of temperature on mushroom respiration rate. The model explaining the effect of time on oyster mushroom's respiration rate included the temperature dependence according to the Arrhenius equation, and the inclusion of a parameter describing the decrease of the respiration rate, from the initial time until equilibrium. These yielded an overall model that fitted well to the experimental data. Moreover, results show that the overall model is useful to predict respiration rate of oyster mushrooms at different temperatures and times, using the initial respiration rate of mushrooms. Furthermore, predictive modelling can be relevant for the choice of an appropriate packaging system for fresh oyster mushrooms.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 11