Given the great innovation in pasta formulations, elucidating factors that will impact pasta behaviour during cooking is essential when alternative ingredients are incorporated. Whole wheat (W), vegetable (V) and gluten free (GF) pastas (from raw to overcooked) were analysed using a multiscale approach and compared with a standard (STD) formulation. Macroscopic (moisture content and hardness), mesoscopic (viscoelastic properties and degree of gelatinization) and molecular (1H NMR relaxometry) properties were evaluated and coupled with discrimination analysis (by means of principal components analysis and partial least square). Results from 2-ways ANOVA indicated that the cooking time (CT) was the main factor influencing the studied properties overlapping the effect of pasta formulation (PF). The application of partial least square analysis was effective in indicating viscoelastic properties and several molecular mobility indicators as typifying features able to describe pasta behaviour during cooking and discriminating GF from their gluten-containing counterparts.

Use of discrimination analysis to identify differences during cooking of novel pasta formulations

Vittadini, E
2022-01-01

Abstract

Given the great innovation in pasta formulations, elucidating factors that will impact pasta behaviour during cooking is essential when alternative ingredients are incorporated. Whole wheat (W), vegetable (V) and gluten free (GF) pastas (from raw to overcooked) were analysed using a multiscale approach and compared with a standard (STD) formulation. Macroscopic (moisture content and hardness), mesoscopic (viscoelastic properties and degree of gelatinization) and molecular (1H NMR relaxometry) properties were evaluated and coupled with discrimination analysis (by means of principal components analysis and partial least square). Results from 2-ways ANOVA indicated that the cooking time (CT) was the main factor influencing the studied properties overlapping the effect of pasta formulation (PF). The application of partial least square analysis was effective in indicating viscoelastic properties and several molecular mobility indicators as typifying features able to describe pasta behaviour during cooking and discriminating GF from their gluten-containing counterparts.
2022
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11581/464971
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