首页    期刊浏览 2024年10月04日 星期五
登录注册

文章基本信息

  • 标题:Multivariate analysis in mathematical model selection to describe Croton urucurana Baill drying kinetics
  • 本地全文:下载
  • 作者:LOPES ALVES Jáliston Júlio ; RESENDE Osvaldo ; RIBEIRO NETO Francisco de Araújo
  • 期刊名称:Food Science and Technology (Campinas)
  • 印刷版ISSN:0101-2061
  • 电子版ISSN:1678-457X
  • 出版年度:2022
  • 卷号:42
  • DOI:10.1590/fst.12821
  • 语种:English
  • 出版社:Sociedade Brasileira de Ciência e Tecnologia de Alimentos
  • 摘要:The Croton urucurana Baill species is known in Brazil as “sangra d’água” and is popular due to its medicinal properties. For better processing of herbal medicines, it is essential that efficient drying and storage techniques are developed and that compounds are preserved. Therefore, this study aimed to select models through multivariate cluster analysis applying Akaike (AIC) and Bayesian information criteria (BIC) to describe Croton urucurana leaves drying kinetics at different temperatures (40-70 °C). The initial moisture content in Croton urucurana leaves was 1.791, 1.841, 2.196 and 2.144 kg water kg dry matter-1, and 8.25, 7.75, 4.25 and 2 hours were required to reach hygroscopic equilibrium, with a final moisture content of 0.134, 0.105, 0.065 and 0.0601 kg water kg dry matter-1, at 40, 50, 60 and 70 °C, respectively. The models with the greatest similarity to the experimental data were Diffusion Approximation; Cavalcanti Mata; Two-term; Two-term Exponential; Modified Henderson & Pabis; Logarithmic; Midilli; Page and Verma. The multivariate cluster technique associated with AIC and BIC criteria during model selection is a great applicability tool to help decision-making when evaluating the drying plant leaves. The Cavalcanti Mata mathematical model was selected to represent the drying kinetics.
  • 关键词:mathematical modeling;AIC and BIC;plant products;post;harvest
国家哲学社会科学文献中心版权所有