7 authors, including: Serena Niro Università degli Studi del Molise 25



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2013ricotta

Statistical analysis



Agro FOOD Industry Hi Tech - vol 24(6) - November/December 2013
The analysis of variance (ANOVA) was applied to the data. The least significant differences were obtained using an LSD test (P<0.05). Statistical analysis was performed using an SPSS version 13.0 for Windows (SPSS Inc., Chicago, IL, USA).


RESULTS AND DISCUSSION

Ricotta samples were characterised to assess the most common quality indexes. For all samples, no significant variation of composition during storage was evidenced (data not shown). As shown in Table 1, the composition of Ricotta cheese added with Lb. paracasei subsp. paracasei F19 (RLB) was similar to that of the control (RC).



  • RC: Ricotta cheese without the addition of functional ingredients and used as control;

  • RI: Ricotta cheese added with 3 g 100 g–1 of inulin;

  • RLB: Ricotta cheese added with 109 cfu 100 g–1 of Lb. paracasei subsp. paracasei F19;

  • RI+LB: Ricotta cheese added with 3 g 100 g–1 of inulin and 109 cfu 100 g–1 of Lb. paracasei subsp. paracasei F19;

  • RCF: Ricotta cheese added with 3 g 100 g–1 of chestnut flour;

  • RCF+LB: Ricotta cheese added with 3 g 100 g–1 of chestnut flour and 109 cfu 100 g–1 of Lb. paracasei subsp. paracasei F19.




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