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Tiger nut is a comestible tuber which offers many under products such as yoghurt. The parameters influencing the quality of yoghurt being numerous, response surface methodology was used to optimize the formulation in order to reach a low intake of milk powder. The volume of tiger nut milk, mass milk powder and sugar mass are the factors monitored while the titratable acidity (AT), pH, dry soluble extract (ESS), ash, viscosity and color are the expected responses in these tests. The data are processed with a degree of confidence p < 0.05 associated with statistical analysis by the software Statgraphic Centurion XVI version 16.2.04. The different tests show that the factors have overall significant effects (p < 0.05) on the acidity, the ashes and the Whiteness index. The linear and quadratic factors of tiger nuts milk as well as those linears of the milk powder have significant effects (p < 0.05) on the pH and the ashes. The linear factors of milk powder have significant effects on DSE, AT and pH. The optimal formulation yielded a volume of tiger nut milk equal to 3.7 L/kg, a mass of powder milk of 63.4 g and 75 g of sugar for one kilogram of yogurt. With a desirability of 75%, this model is apt to explain the results and the experimental values fit with the predicted ones and are within the norms. The proximate analysis of optimal yoghurt formulation shows that fat and proteins contents are respectively 5.67% and 2.2%. Calcium, magnesium and potassium contents are respectively 160, 40 and 180 mg in 100 g of yoghurt.

The inadequacy of the distribution of plant resources around the world and the lack of processing of available resources in some parts of the world mean that today a large part of the world’s population still suffers from the consequences of malnutrition. The latter remains a real scourge and one of the major public health problems in the world despite the considerable progress made. It is thought to be responsible for almost 55% of all deaths among children aged from 0 to 5 years, and this proportion is higher in poor countries; particularly in Africa. Nowadays, one of the axes of research in the field of food sciences is the development of functional foods that provide health benefits [

The tiger nut tubers (Cyperus esculentus) represent the basic raw material for this present study (

The tiger nut tubers and the powdered milk used in this work were bought from the local market. The tubers have been cleaned many times with tap water before being soaked in water for twelve hours. Tubers after soaking are represented in

The extracted tiger nut milk has been mixed with a mass of milk and sugar according to the different formulations described by the design of experiments in order to obtain a final mass of 1 kg of yogurt. The pasteurization is carried out at 75˚C during 5 minutes and then the mix is transferred into jars for fermentation at 45˚C during 4 hours in an incubator and they are removed to be cooled.

Box-Behnken design are used in this study for the conception of the design of experiments. The response surface methodology (RSM) has been applied to optimize the factors and study the influences of the volume of tiger nut milk (X_{1}) (concentration), of the mass of powdered milk (X_{2}) and the mass of sugar (X_{3}) on the responses. The tiger nut milk volume extracted from 1 kg of tiger nut tuber ranges from 2 liter to 5 liter, the masse of milk powder varies between 20 g and 120 g and sugar mass ranges from 50 g to 75 g. These values are taken in order to produce a firm yoghurt. The pH, titratable acidity, total soluble dry extract (SDE), viscosity, ashes content and color of the yogurt from the different formulations were evaluated as responses for the factors studied. The real levels of the variables are indicated in

Independent variables | Symbol | Unit | Minimum | Level | Maximum |
---|---|---|---|---|---|

−1 | 0 | 1 | |||

Volume (tiger nut milk) | X_{1} | l/kg | 2 | 3.5 | 5 |

Mass of sugar | X_{2} | G | 50 | 62.5 | 75 |

Mass of milk | X_{3} | G | 20 | 70 | 120 |

Note: X_{1} (A), X_{2} (B), X_{3} (C), X_{1}X_{2} (AB), X_{1}X_{3} (AC), X_{2}X_{3} (CB), X_{11} (AA), X_{22} (BB) and X_{33} (CC). X_{1}, X_{2} and X_{3} mean respectively the letter A, B and C in the response surface and PARÉTO graphic.

combination of factor levels; β_{0} is a constant; β_{i} is the regression coefficient calculated from the observed experimental values of Y_{i}. The terms X_{i}, X_{i}X_{j} and X i 2 represent the interaction and the quadratic terms, respectively.

1) pH and titratable acidity

The samples were analysed to get pH and titratable acidity as described by Olubamiwa et al. (2006). A pH-meter of the brand Hanna HI-98128 was utilized to evaluate the pH of the different formulations of yogurt. The acidity has been measured by titration of 10 ml of yogurt with NaOH 0.1 N; and was expressed in equivalent gram of lactic acid/100g.

2) Viscosity and color

Yoghurt samples were gently stirred with a plastic spoon prior to viscosity measurements. The viscosity was measured at 7˚C using a Brookfield digital viscometer and is expressed in Cp. The color was measured with a colorimeter (CM-3600d, MINOLTA Co.; Japan) of the model D25A-9. The coordinates CIE Lab was obtained with the illuminating observer D65/10˚. The color parameters such as L, a*, b*, c* and h* were given by the colorimeter directely and are used to calculate the whiteness index (WI) and total color (TC) according to [

WI = 100 − ( 100 − L ) 2 + a ∗ 2 + b ∗ 2 (1)

TC = L 2 + a ∗ 2 + b ∗ 2 (2)

3) Physicochemical properties analysis

The ash content was determined according the [

4) Resultats and discussion

The analysis results are set out in

Sample | Volume (l) | Mass of Sugar (g) | Mass of Milk (g) | Titratable acidity (g lactic acid/100g) (Y_{1}) | SDE (brix) (Y_{2}) | Ph (Y_{3}) | Ash (%) (Y_{4}) | Viscosity (cp) (Y_{5}) | Color | ||
---|---|---|---|---|---|---|---|---|---|---|---|

TC (Y_{6}) | H (Y_{7}) | WI (Y_{8}) | |||||||||

1 | 5.0 | 50.0 | 70.0 | 0.74 ± 0.02 | 16.6 ± 0.50 | 4.69 ± 0.005 | 0.22 ± 0.00 | 38.76 ± 0.66 | 85.43 ± 0.05 | 120.31 ± 0.25 | 81.27 ± 0.00 |

2 | 5.0 | 75.0 | 70.0 | 0.75 ± 0.00 | 16.65 ± 0.65 | 4.67 ± 0.005 | 0.54 ± 0.00 | 39.69 ± 0.54 | 85.20 ± 0.10 | 120.13 ± 0.26 | 81.01 ± 0.02 |

3 | 5.0 | 62.5 | 120.0 | 1.13 ± 0.02 | 22.45 ± 0.05 | 4.88 ± 0.01 | 0.94 ± 0.00 | 200.17 ± 0.46 | 91.82 ± 0.02 | 101.83 ± 0.04 | 81.97 ± 0.01 |

4 | 5.0 | 62.5 | 20.0 | 0.45 ± 0.00 | 11.90 ± 0.10 | 4.47 ± 0.005 | 0.06 ± 0.00 | 288.68 ± 0.57 | 81.92 ± 0.01 | 109.89 ± 0.00 | 79.87 ± 0.01 |

5 | 3.5 | 62.5 | 70.0 | 0.63 ± 0.02 | 17.45 ± 0.35 | 4.57 ± 0.005 | 0.99 ± 0.08 | 30.21 ± 0.09 | 85.46 ± 0.00 | 116.83 ± 0.06 | 80.47 ± 0.00 |

6 | 3.5 | 75.0 | 20.0 | 0.49 ± 0.01 | 17.95 ± 0.15 | 4.39 ± 0.005 | 0.77 ± 0.14 | 30.53 ± 0.24 | 79.50 ± 0.33 | 122.67 ± 0.8 | 77.17 ± 0.18 |

7 | 3.5 | 75.0 | 120.0 | 1.17 ± 0.00 | 23.55 ± 0.25 | 4.69 ± 0.005 | 1.23 ± 0.14 | 109.67 ± 0.33 | 81.27 ± 0.00 | 103.43 ± 0.02 | 81.74 ± 0.00 |

8 | 3.5 | 62.5 | 70.0 | 0.81 ± 0.01 | 17.45 ± 0.50 | 4.61 ± 0.005 | 1.01 ± 0.05 | 176.23 ± 0.87 | 89.84 ± 0.00 | 109.86 ± 0.03 | 80.43 ± 0.01 |

9 | 3.5 | 50.0 | 20.0 | 0.50 ± 0.00 | 12.70 ± 0.00 | 4.45 ± 0.005 | 0.75 ± 0.00 | 219.87 ± 0.84 | 88.27 ± 0.01 | 109.44 ± 0.03 | 78.64 ± 0.00 |

10 | 3.5 | 62.5 | 70.0 | 0.80 ± 0.00 | 21.40 ± 0.15 | 4.66 ± 0.005 | 0.99 ± 0.02 | 267.89 ± 0.56 | 80.36 ± 0.01 | 103.10 ± 0.05 | 81.77 ± 0.00 |

11 | 3.5 | 50.0 | 120.0 | 1.21 ± 0.00 | 21.40 ± 0.35 | 4.77 ± 0.01 | 1.06 ± 0.04 | 298.90 ± 0.17 | 88.61 ± 0.01 | 113.39 ± 0.04 | 81.03 ± 0.00 |

12 | 2.0 | 62.5 | 120.0 | 0.72 ± 0.00 | 21.75 ± 0.15 | 4.68 ± 0.00 | 1.37 ± 0.01 | 74.36 ± 0.08 | 88.19 ± 0.20 | 98.82 ± 0.43 | 79.83 ± 0.06 |

13 | 2.0 | 75.0 | 70.0 | 0.86 ± 0.00 | 21.10 ± 0.10 | 4.97 ± 0.005 | 1.01 ± 0.02 | 74.52 ± 0.16 | 86.04 ± 0.01 | 109.37 ± 0.01 | 78.42 ± 0.00 |

14 | 2.0 | 50.0 | 70.0 | 0.68 ± 0.01 | 19.15 ± 0.45 | 4.80 ± 0.005 | 0.97 ± 0.01 | 266.16 ± 1.07 | 83.21 ± 0.00 | 104.87 ± 0.02 | 79.58 ± 0.01 |

15 | 2.0 | 62.5 | 20.0 | 0.51 ± 0.01 | 15.65 ± 0.05 | 4.88 ± 0.01 | 0.86 ± 0.02 | 296.04 ± 0.23 | 81.07 ± 0.01 | 113.78 ± 0.01 | 77.10 ± 0.00 |

Note: Y_{1} (Soluble dry extracts), Y_{2} (titratable acidity), Y_{3} (pH), Y_{4} (ashes), Y_{5} (viscosity), Y_{6} (total color), Y_{7} (angle h), Y_{8} (whiteness index). DSE (dry soluble extract), gram (g).

of the parameters studied. The results obtained from the ANOVA are shown in ^{2} Values range from 42.63% to 98.18% and was established in _{1}, Y_{2}, Y_{3}, Y_{4}, Y_{5}, Y_{6}, Y_{7} and Y_{8} which are regression equation predicting the relationship between the factors (

5) Titratable acidity

Titratable acidity is a very important factor in the characterization and acceptability of fermented dairy products. The variance analysis of the regression models gives a R^{2} value of 90.67%. The titratable acidity varies from 0.45% to 1.21%. Response surface plot of the relationship is shown as

Model | Titratable Acidity | Soluble Dry Extracts | pH | ASH | Viscosity | TC | H | WI |
---|---|---|---|---|---|---|---|---|

Transformation | None | None | None | None | None | None | None | None |

D.D.L. Model | 9 | 9 | 9 | 9 | 9 | 9 | 9 | 9 |

Probability | 0.0390* | 0.0869 | 0.0511 | 0.0028* | 0.7665 | 0.8823 | 0.3170 | 0.0008* |

D.D.L. error | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 |

Standard error | 0.125632 | 2.06723 | 0.0901018 | 0.101923 | 125.447 | 4.63919 | 6.22152 | 0.334627 |

Mean absolute error | 0.062222 | 1.03444 | 0.0432222 | 0.0487778 | 60.9667 | 2.983 | 2.32433 | 0.156333 |

R-squared | 90.67 | 86.57 | 89.47 | 96.95 | 51.63 | 42.63 | 74.11 | 98.18 |

Adjusted R-squared | 73.88 | 62.38 | 70.51 | 91.47 | 0.00 | 0.00 | 27.50 | 94.90 |

*Significant at 0.05.

Y_{1} | Y 1 = 1.58198 + 0.257926 X 1 − 0.05016 X 2 − 0.000177 X 3 − 0.028704 X 1 2 + 0.000483 X 2 2 + 0.000008 X 3 2 − 0.002267 X 1 X 2 + 0.00156667 X 1 X 3 − 0.000012 X 2 X 3 (3) |
---|---|

Y_{2} | Y 2 = 16.6632 + 2.67398 X 1 − 0.318867 X 2 + 0.085675 X 3 − 0.500926 X 1 2 − 0.0253333 X 1 X 2 + 0.0268333 X 1 X 3 + 0.00470667 X 2 2 − 0.00124 X 2 X 3 − 0.000240833 X 3 2 (4) |

Y_{3} | Y 3 = 5.54418 − 0.536037 X 1 + 0.00286 X 2 − 0.00192833 X 3 + 0.0714815 X 1 2 + 0.000053 X 2 2 − 0.000019 X 3 2 − 0.002533 X 1 X 2 + 0.00203 X 1 X 3 − 0.000008 X 2 X 3 (5)^{ } |

Y_{4} | Y 4 = − 0.878881 + 0.186537 X 1 + 0.0549 X 2 − 0.00486 X 3 − 0.101481 X 1 2 + 0.00373333 X 1 X 2 + 0.001233 X 1 X 3 − 0.000533 X 2 2 + 0.00006 X 2 X 3 + 0.000016 X 3 2 (6) |

Y_{5} | Y 5 = 66.0527 − 198.462 X 1 + 26.6765 X 2 − 5.203 X 3 − 0.723889 X 1 2 + 2.5676 X 1 X 2 + 0.4439 X 1 X 3 − 0.330872 X 2 2 + 0.000044 X 2 X 3 + 0.0233325 X 3 2 (7) |

Y_{6} | Y 6 = 60.0084 + 1.218 X 1 + 0.815993 X 2 − 0.00922833 X 3 + 0.115 X 1 2 − 0.0354667 X 1 X 2 + 0.00926667 X 1 X 3 − 0.006904 X 2 2 + 0.000572 X 2 X 3 − 0.0000795 X 3 2 (8) |

Y_{7} | Y 7 = 167.815 + 8.15278 X 1 − 3.01338 X 2 + 0.551525 X 3 − 0.536111 X 1 2 + 0.031656 X 2 2 – 0.0010575 X 3 2 − 0.0624 X 1 X 2 + 0.023 X 1 X 3 − 0.009276 X 2 X 3 (9) |

Y_{8} | Y 8 = 74.6532 + 0.2445 X 1 + 0.11616 X 2 − 0.005905 X 3 − 0.011667 X 1 2 − 0.002072 X 2 2 − 0.000281 X 3 2 + 0.012 X 1 X 2 − 0.0021 X 1 X 3 + 0.001272 X 2 X 3 (10) |

*Co-efficient are significant (p < 0.05).

fermentation and therefore in the production of lactic acid and acidic compounds. As such, it plays a key role in the acidity of yogurts. The lactose contained milk is an ideal substrate for yogurt cultures. These microorganisms use milk lactose to release more lactic acid, which leads to the influence of milk on acidity. Similar results were found by [

influence the shelf life. However, given the fiber content of the tiger nut milk, it has been reported that the hydrolysis of these compound during the fermentation could increase glucose and maltose levels, which are converted into organic acids or alcohols by microbial activity and which directly influences the acidity of the environment [

6) Soluble dry extract

ANOVA indicates an R^{2} equal to 86.58% on the variability of soluble solids content. Its adjusted R^{2} is 62.38%. The various yogurt samples have dry soluble extract contents ranging between 11.90% to 23.55%. However, the milk powder mass remains the only factor with a significant (p < 0.05) positive influence on the dry soluble extract content. Nevertheless, the linear factor of the sugar mass and the interaction between the volume and the mass of powdered milk and the concentration of the tiger nut milk have less significant (p > 005) but positive effects. A visual illustration of the relationship is shown in

7) pH

Using a multiple regression analysis of the experimental results, the pH is obtained by the second-order polynomial Equation (5) (^{2} indicates that the model accounts for 89.47% of the pH variability. The adjusted R-squared is 70.51%. A visual illustration of pH relationship with idependent wariables is shown in

pure yellow tiger nut with a pH equal to 6.10, yoghurt mixed yam and soybean for a pH 6.32 and yoghurt mixed soya and coconut of pH 6.58. These reported pH values are dependent on tiger nut milk which has a pH of plus or minus 6.6 [

8) Ash

Analysis of variance (ANOVA) of the R^{2} indicates that the model accounts for 96.95% (

9) Viscosity

The R^{2} statistic analysis indicates that the model explains 51.6314% of the variability of the viscosity. Values reported for viscosity range from 296.04 to 30.21 Cp. A visual illustration of the relationship between the viscosity and independent variables is shown in

particular its viscosity.

10) Color parameters

In food science, color is one of the main assets of a product that can lead to the purchase by the consumer [

11) Total color

The analysis results give total color values ranging from 79.5 to 91, 82. These observed variations can be attributed to different opacity levels, related to the level of aggregation of particles. The high value is found in formulation (3.5 l; 50 g; 120 g) and the lowest value in formulation (3.5 l; 75 g; 20 g). The co-efficient of determination predicting the mean score for total color explained up to 42.63% (

values, the higher the opacity, the lower the chromium, which also corresponds to a higher brightness index. No factors had a significant influence on the total yoghurt color (p > 0.05) (

12) Hue tint angle

Statistical analysis of the coefficient of determination R^{2} indicates that the model accounts for 74.11% of the variability of Hue. The adjusted R^{2} is 27.50%. The regression Equation (9) predicted the relationship between Hue value and independent variables is established in

13) Whiteness index (WI)

The whiteness index (WI), which measures the overall whiteness of the food product or its deviation from the white color, ranges from 77.10 to 81.97 (

62.5 g and 120 g) and the low respectively for tiger nut volume, sugar mass and milk mass. The linear factors of milk mass (p < 0.001), and of tiger nut milk volume (concentration) (p < 0.0001) are the most factors witch have the most significant effect, the interactive factor of sugar and milk masses (p < 0.05) and the quadratic factor of the milk mass have significant influences on the whiteness index of yogurts (

to brightness L. A high value of L in the case of yogurt is a good quality factor however a drop in L can be attributed to color degradation [

14) Optimization

Multi-response optimization of RSM was applied to determine the optimal combination in yoghurt preparation. The optimum formulation predicted by the regression model is the follows: for tiger nut milk volume (3.77 l), for milk mass (63.84 g) and 75 g for sugar mass. These conditions were tested and compared to the predicted optimal response. Yoghurt optimal sample were prepared using the derived optimum formulation conditions to check the validity of surface

Factors | Optimal value | Responses | Desirability | Prevision | Experimental measures | Inferior limit at 95.0% | Superior limit at 95.0% |
---|---|---|---|---|---|---|---|

Titrable acidity | 1 | 0.80 | 0.66 ± 0.06 | 0.596 | 1.004 | ||

Volume (liter) | 3.77 | Soluble dry extract | 0.739 | 20.03 | 18 ± 0.1 | 16.66 | 23.39 |

pH | 0.625 | 4.59 | 4.5 ± 0.004 | 4.44 | 4.74 | ||

Ash | 0.662 | 0.89 | 1.25 | 0.726 | 1.06 | ||

Mass of powdered milk (g) | 63.84 | WI | 0.623 | 79.93 | 75.24 ± 0.003 | 79.38 | 80.47 |

H | 0.766 | 117.37 | 115. 27 ± 0.145 | 107.26 | 127.49 | ||

Mass of sugar | 75.0 | CT | 0.746 | 82.63 | 80.41 ± 0.19 | 75.08 | 90.17 |

(g) | Viscosity | 0.886 | 43.17 | 36.4 | −160.87 | 247.23 |

Parameter (/100g) | Content |
---|---|

Proteins % | 2.2 |

Fat % | 5.67 |

Calcium (mg) | 160 |

Magnesium (mg) | 20 |

Potassium (mg) | 180 |

response model. The experimental data were compared with predicted values in order to verify adequacy of final reduced flour (

The response surface methodology has successfully optimized the tiger nut yoghurt formulation process. The experimental data after optimization and the predicted data are significantly the same overall. The development of yoghurt based on tiger nuts by adding milk powder can constitute on the one hand a real nutritional advantage in view of these many biological properties of nutsedge and other departure its valuation. Optimization has made it possible to minimize milk powder intake. The physicochemical and biochemical analysis confirms the nutritional value of the product compared to those already existing on the market. Further studies on microbial quality and stability would predict the conditions of optimized product use. Finally, the production, utilization, and consumption of tigernut-based yoghurt should be encouraged because such product will be helpful in providing nutritious, safe and wholesome food for the poor and malnourished populations in developing country.

The authors declare no conflicts of interest regarding the publication of this paper.

Ndiaye, B., Sakho, M., Ayessou, N.C., Cisse, O.I.K., Cisse, M. and Diop, C.M. (2019) Optimization of a Tiger Nut-Based Yoghurt Formulation by Response Surface Methodology. Food and Nutrition Sciences, 10, 1400-1418. https://doi.org/10.4236/fns.2019.1012100