| Literature DB >> 31344934 |
Eduardo Enrique Valdez-Meza1, Anabela Raymundo2, Oscar Gerardo Figueroa-Salcido3, Giovanni Isaí Ramírez-Torres4, Patrícia Fradinho2, Sonia Oliveira2, Isabel de Sousa2, Miroslava Suárez-Jiménez1, Feliznando Isidro Cárdenas-Torres3, Alma Rosa Islas-Rubio5, Guillermo Rodríguez-Olibarría1, Noé Ontiveros6, Francisco Cabrera-Chávez7.
Abstract
BACKGROUND: Alcalase-treated amaranth proteins generate angiotensin-1-converting enzyme (ACE-1) inhibitory peptides, which could be useful for functional foods development. Our aim was to evaluate the technological, sensory, and antihypertensive properties of pasta enriched with an amaranth hydrolysate.Entities:
Keywords: amaranth protein; functional food; hypertension; pasta; sensory evaluation
Year: 2019 PMID: 31344934 PMCID: PMC6722561 DOI: 10.3390/foods8080282
Source DB: PubMed Journal: Foods ISSN: 2304-8158
Formulations for pasta making with changes in the content of protein *.
| Ingredients (g) | Pasta A | Pasta B | Pasta C |
|---|---|---|---|
| Semolina | 100.00 | 91.87 | 57.00 |
| Amaranth protein concentrate | - | 8.53 | 43.00 |
| Amaranth protein hydrolysate | - | 4.00 | 4.00 |
* Based on the method 66-10.01 of the American Association of Cereal Chemists (AACC), (2001) [15].
Figure 1IC50 (half-inhibitory concentration) estimation of the amaranth hydrolysate (optimized hydrolysate parameters: pH 7.01; temperature 52 °C; enzyme concentration 0.04 mU/mg of protein; reaction time 6.16 h). ACE-1: angiotensin-1-converting enzyme.
Proximate analysis of the three types of pasta (dry basis).
| Sample | Moisture | Protein | Fat | Ash | Carbohydrates |
|---|---|---|---|---|---|
| Pasta A | 7.64 ± 0.01 a | 11.10 ± 0.01 a | 0.92 ± 0.61 a | 0.63 ± 0.01 a | 87.33 ± 2.04 c |
| Pasta B | 7.84 ± 0.01 a | 15.06 ± 0.29 b | 1.44 ± 0.34 b | 0.90 ± 0.01 a | 82.59 ± 0.34 b |
| Pasta C | 8.12 ± 0.01 a | 20.00 ± 0.06 c | 2.27 ± 0.40 b | 0.92 ± 0.01 a | 76.89 ± 0.21 a |
Comparisons in each column were carried out using ANOVA and Tukey tests. Different superscripts letters in the same column mean significant difference (p < 0.05). Mean values ± standard deviations are shown. Carbohydrates were calculated by difference.
Cooking quality of the three types of pasta.
| Sample | Optimum Cooking Time (MIN) | Cooking Loss | Weight Gain |
|---|---|---|---|
| PASTA A | 10.5 ± 0.5 b | 11.5 ± 0.5 b | 207 ± 4.9 a |
| PASTA B | 7.5 ± 0.5 a | 8.9 ± 0.1 b | 205 ± 6.0 a |
| PASTA C | 5.5 ± 0.0 a | 7.3 ± 1.1 a | 193 ± 1.0 a |
Comparisons in each column were carried out using ANOVA and Tukey tests. Different superscript letters in the same column mean significant difference (p < 0.05). Mean values ± standard deviations are shown.
Color parameters in dry and cooked pasta.
| Sample | Presentation | L* | a* | b* |
|---|---|---|---|---|
| Pasta A | Dry | 78.5 ± 0.7 d | 2.02 ± 0.1 a | 17.4 ± 0.8 b |
| Cooked | 78.5 ± 1.6 d | 1.01 ± 0.6 a | 16.7 ± 0.9 a | |
| Pasta B | Dry | 72.1 ± 0.5 c | 4.3 ± 0.2 b | 21.6 ± 0.5 c |
| Cooked | 56.2 ± 1.2 a | 7.8 ± 0.2 c | 24.5 ± 0.5 de | |
| Pasta C | Dry | 60.0 ± 0.3 b | 7.6 ± 0.2 c | 24.1 ± 0.3 d |
| Cooked | 55.7 ± 0.6 a | 8.2 ± 0.2 d | 25.1 ± 0.4 e |
Comparisons in each column were carried out using ANOVA and Tukey tests. Different superscript letters in the same column mean significant difference (p < 0.05).
Texture characteristics of the three types of pasta after cooking.
| Sample | Firmness (N) | Adhesivness (−N·S) |
|---|---|---|
| Pasta A | 3.31 ± 0.26 a | 0.053 ± 0.011 a |
| Pasta B | 3.64 ± 0.77 b | 0.043 ± 0.010 b |
| Pasta C | 5.73 ± 0.75 c | 0.041 ± 0.007 c |
Comparisons in each column were carried out using ANOVA and Tukey tests. Different superscript letters in the same column mean significant difference (p < 0.05). Mean values ± standard deviations are shown.
Figure 2Sensory evaluation of cooked pasta. A hedonic scale was used, where 0 = totally dislike and 10 = like very much. Comparisons in each sensory attribute were carried out using ANOVA and Tukey tests. Different letters indicate statistical difference (p < 0.05). NS: nonsignificant difference.
Figure 3Triangle test to evaluate the capability of the panelists to discriminate among pasta samples. Sixty untrained panelists were recruited. Pastas (A, B, C) were assigned a code and presented simultaneously to all panelists. In each sample sequence, two equal pastas and one different pasta were given to panelists. Statistical differences were estimated according to ISO-4120:2004.
Figure 4Systolic blood pressure in spontaneously hypertensive rats after supplementation with three types of pasta and captopril. Comparisons at each time point were carried out using nonparametric ANOVA and Kruskal–Wallis test. Different letters at specific time points mean significant difference (p < 0.05). NS: nonsignificant difference.