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214 IV.Resultados y discusión. Capítulo II Glucose x inulin 0.17 2 0.252 Inulin x inoculum -0.625 50 0.006 Inoculum x inoculum 0.10 2.20 0.234 Lack-of-fit - 5.47 0.094 R 2 0.56 - - R 2 -adj 0.32 - - Standard error of est. 0.25 - - Mean absolute error 0.35 - - Durbin-Watson statistic 2.73 - 0.925 As can be seen in the coefficients and F-ratios (Table 2), glucose affected the duration of the fermentation process positively, which was expected since it is a basic nutrient for all bacteria, especially in GG (Corcoran et al., 2005). Inulin had a quite significant negative impact on the duration of this process (coefficient sign is positive and F-ratio is high). Despite being a prebiotic, inulin is also industrially used as a thickener (Franck, 2002), so it might reduce the mobility and availability of nutrients for the fermentation process. De Souza-Oliveira et al. (2009) also observed an increase in the duration on the fermentation of milk when it contained inulin. Inoculum addition also had a negative impact, which could be explained by considering the limiting effect of the availability of nutrients within the matrix, commented on above. Moreover, the interaction between inulin and the added starters had a synergic effect on the fermentation time, probably due to the known prebiotic property of inulin that positively affects the growth of Lactobacillus genus (Kolida, Tuohy and Gibson, 2002). As
IV. Resultados y discusión. Capítulo II 215 shown in Table 2, the fitting coefficients of the model were very low. The determination coefficient (R 2 ) was 0.56 and only 32% of the variation in the experimental data (R 2 adj) was explained by the predictive model. A model is considered adequate to describe the influence of the dependent variable(s) when R 2 is at least 80% (Yaakob et al., 2012) or values of R 2 adj over 70% (Cruz et al., 2010). In this case, it is difficult to obtain greater values because the variation of the experimental responses is very low (most fermentation times were around 3.5 h) (Table 1), and consequently, the model obtained can only provide rough predictions. The health benefits of probiotic products are believed to be dependent on the bacterial viability within the matrix, recommending a minimum survival of over 10 7 cfu/mL (Gomes and Malcata, 1999; Stanton et al., 2003; Van Niel et al., 2002). Furthermore, fermentation is a critical process within the product development and has to be done as quickly as possible to prevent non-desirable bacteria. Hence, despite the lack of fit in probiotic responses, experimental GG survivals (Y 2 data) together with the quantified fermentation times (Y 1 data), were used to optimise a hazelnut formulation. The fermentation time was minimised and GG counts for 28 days were maintained at 8 log cfu/mL. This optimum corresponded to the addition of 3 g/100 mL of glucose, 2.75 g/100 mL of inulin and 6 mL/100 mL of mixed culture inoculum to the hazelnut milk. With this formulation, the vegetable milk fermented in 3.6 h and, after being stored for 28 days at 4 ºC, GG survival in the fermented product was 8 log cfu/mL. Figure 1 shows the overlay of the RSM contour plots for the two variable responses and the location of the optimised formulation.
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UNIVERSITAT POLITÈCNICA DE VALÈNC
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Agraïments A Chelo González per t
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RESUMEN La tesis doctoral tiene com
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Dentro del amplio abanico de propie
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colonies forming units per mL is re
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En el disseny i optimització del p
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ÍNDICE PÁGINA Justificación e in
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Justificación e interés del traba
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pretende que el producto fermentado
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I. Introducción 9 En la introducci
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Vegetable milks and fermented deriv
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14 I. Introducción 1. INTRODUCTION
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16 I. Introducción able to adapt t
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18 I. Introducción large quantitie
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20 I. Introducción observe signifi
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22 I. Introducción Table 1. Raw ma
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24 I. Introducción Table 2. Main f
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26 I. Introducción KAMUT (cereal)
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28 I. Introducción Spelt (cereal)
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30 I. Introducción Husked cereals
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32 I. Introducción or sucralose) a
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(1) Nutriops S.L. (Spain) (2) Soria
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36 I. Introducción animal milks an
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38 I. Introducción with great sens
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40 I. Introducción and Streptococc
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42 I. Introducción prebiotics such
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44 I. Introducción new generation
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46 I. Introducción In the developm
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48 I. Introducción Biel W, Bobko K
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50 I. Introducción Chisholm A, Man
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52 I. Introducción Dykes L and Roo
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54 I. Introducción Jing P and Hu X
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56 I. Introducción Mattes RD, Kris
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58 I. Introducción Philips KM, Rug
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60 I. Introducción Sharma A and Ka
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62 I. Introducción Wu WH, Kang YP,
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II. Contribución científica del t
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III. OBJETIVOS
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70 III.Objetivos 70 III. Objetivos
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IV. Resultados y discusión 73 Se s
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IV. Resultados y discusión 75 micr
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Capítulo I Elección de las “lec
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IV. Resultados y discusión. Capít
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% Volume particles number (%) % Vol
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Capítulo II Diseño y optimizació
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IV.Resultados y discusión. Capítu
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Development of a non-dairy probioti
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158 IV.Resultados y discusión. Cap
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IL-8 concentration (ng/mL) IV. Resu
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Conclusiones ‣ Las altas presione
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de los yogures convencionales, espe
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leche de vaca, vegetarianos…). De
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