Instrumental methods as strategic supporting tools for systematic biochemical analysis of serra da estrela sheep milk.

• Autor(a) principal: Oliveira, Jorge
• Data de Publicação: 2022
• Outros Autores: Lemos, Carlota, Brito, Manuel, Pinto, António, Coutinho, Rui Coutinho, Barracosa, Paulo, Coelho, Catarina, Dinis, Rui
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.19/7549
• topic: Instrumental analysis; somatic cell count; fat content; protein content; Serra da Estrela sheep milk; Portugal.

Serra da Estrela sheep crude milk is mandatory for the PDO Serra da Estrela (SE) cheese production. The production system implies the need for systematic knowledge of the values of useful matter (fat and protein) to produce cheese. The knowledge of somatic cell count (SCC) allows to predict the mammary health status of ewes as well as make decisions on the use of crude milk for human consumption, through its transformation into cheese. The need for simple, fast and reliable methodologies for the determination of this parameters is fundamental for the sustainability of this productive sector through milk recording procedure for animal genetic evaluation, as well for the previous analysis of the bulk milk, before the process of elaboration of the PDO SE cheese. Two sets of milk samples were collected: 50 individual samples of Serra da Estrela ewes’ milk from 2 farms for analysis of SCC and 53 samples of Serra da Estrela ewes’ milk (16 individual samples and 37 samples of bulk milk) for analysis of fat and protein contents (Fat% and Prot%). Duplicates of samples were simultaneously analyzed by reference and instrumental methodologies (DCC De Laval optical reader and FT-NIR MasterTM from Büchi) as reliable alternatives for parameters evaluation for the SE sheep milk. The results showed a significant agreement between the pairs of values (type of methodologies) for all parameters, with correlations between 0.925 (Prot%) and 0.960 (SCC) (p<0.001). The linear regressions for the pairs of data of the three parameters studied presented a strong adjustment (with the coefficients of determination between 0.856 and 0.921). The findings showed that both instrumental methodologies applied can be used as alternative to count somatic cells and evaluate fat and protein contents of SE sheep milk and will be useful as strategic measuring devices for milk farmers and cheesemakers.