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Thermal inactivation of African swine fever virus in feed ingredients.
Songkasupa, Tapanut; Boonpornprasert, Prakit; Suwankitwat, Nutthakarn; Lohlamoh, Walaiporn; Nuengjamnong, Chackrit; Nuanualsuwan, Suphachai.
Afiliação
  • Songkasupa T; Virology Laboratory, National Institute of Animal Health, Chatuchak, Bangkok, Thailand.
  • Boonpornprasert P; Virology Laboratory, National Institute of Animal Health, Chatuchak, Bangkok, Thailand.
  • Suwankitwat N; Virology Laboratory, National Institute of Animal Health, Chatuchak, Bangkok, Thailand.
  • Lohlamoh W; Virology Laboratory, National Institute of Animal Health, Chatuchak, Bangkok, Thailand.
  • Nuengjamnong C; Department of Animal Husbandry, Faculty of Veterinary Science, Chulalongkorn University, Bangkok, Thailand.
  • Nuanualsuwan S; Center of Excellence for Food and Water Risk Analysis (FAWRA), Department of Veterinary Public Health, Faculty of Veterinary Science, Chulalongkorn University, Bangkok, Thailand.
Sci Rep ; 12(1): 15998, 2022 09 26.
Article em En | MEDLINE | ID: mdl-36163486
ABSTRACT
African swine fever virus (ASFV) causes a fatal infectious disease affecting domestic pigs and wild boars. ASFV is highly stable and easily transmitted by consumption of contaminated swine feed and pork products. Heat treatment of feed ingredients is a means to minimize the risk of contamination through swine feed consumption. The objectives of this study were to determine the thermal inactivation of ASFV in non-animal and animal origin feed ingredients. The rate of thermal inactivation is represented by decimal reduction time (DT) or time required to reduce ASFV per 1 log at temperature T. The mean D60, D70, D80 and D85 of meat and bone meal (MBM), soybean meal (SBM), and maize grain (MZ) are in the ranges 5.11-6.78, 2.19-3.01, 0.99-2.02, and 0.16-0.99 min, respectively. DT is used to compare the heat resistance of ASFV in the feed ingredient matrices. The mean DT of ASFV in MBM, SBM and MZ was not statistically significant, and the heat resistance of ASFV in MBM, SBM, and MZ was not different at 60, 70, 80, or 85 °C. The multiple DT was used to develop a DT model to predict DT at various inactivation temperatures. The DT models for MBM, SBM, and MZ are log DT = - [Formula see text] + 2.69, log DT = - [Formula see text] + 2.55, and log DT = - [Formula see text] + 4.01. To expand and ease the field applications, a spreadsheet predicting the DT and the inactivation time (with 95% confidence interval) from these DT models is available to download.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Febre Suína Africana / Vírus da Febre Suína Africana / Carne de Porco / Fabaceae Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Revista: Sci Rep Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Tailândia

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Febre Suína Africana / Vírus da Febre Suína Africana / Carne de Porco / Fabaceae Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Revista: Sci Rep Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Tailândia