Structure analysis of multi-component pastes – The effect of water distribution on the rheological properties

Möller, Anna Cäcilie; Lie-Piang, Anouk; Bian, Ting; Padt, A. van der; Goot, A.J. van der

doi:10.1016/j.foodres.2022.112069

Cited by 1 publication

(2 citation statements)

References 12 publications

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“…Notably, in the previous study, it was concluded that high fibre samples were not predicted well using the log linear model, which was later suggested to be caused by phase separation taking place at these fibre concentrations. 174 Based on the predicted viscosity values, it seems that the spline regression is able to describe this change in behaviour. This can be attributed to the non-parametric character of the spline regression, which makes it more flexible to fit data as opposed to the predefined linear regression.…”

Section: Revisiting the Quantification Of The Final Viscositymentioning

confidence: 98%

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Functionality-driven food formulation : reducing the environmental impact using machine learning

Lie-Piang¹

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In the coming decades, meat-based protein foods will increasingly be replaced by plant-based protein foods. These are typically prepared from highly refined protein isolates or concentrates, which require a lot of energy and auxiliary chemicals to be produced. Milder techniques such as dry fractionation or mild aqueous fractionation deliver alternative ingredients that have a multicomponent character but do not need the same amount of chemicals and energy. This study aims to assess the effect of reducing the degree of refining on the environmental impact using a life cycle assessment. The functional unit was 1000 kg of the processed crop. As protein is considered key in these ingredients, the functional unit of 1 kg of protein in the produced fractions was also assessed. The contribution of processing to the overall impact was found to be significant and, in some cases, larger than the contribution by the crop cultivation. Therefore, any analysis of the environmental impact should include both. Reducing the degree of refining substantially reduces global warming potential, human carcinogenic toxicity, fossil resource scarcity, and water consumption. However, for all impact categories, drying remains the largest contributor. The global warming potential of less refined ingredients was still lower compared to the conventionally refined ingredients when expressed per kg of protein, despite the significantly lower amount of protein. The fractions obtained through mild aqueous fractionation have a higher protein yield and a lower global warming potential compared to conventional full refining. Both dry fractionation and the combination of dry and mild aqueous fractionation substantially lower the environmental impact, but the protein yield and purity are also considerably lower.Overall, linking environmental impact to protein purity and yield allows for a comprehensive selection of sustainable food ingredients.

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Section: Revisiting the Quantification Of The Final Viscositymentioning

confidence: 98%

“…For example, the water competition between different phases that relates to the pasting properties of yellow peas could be quantified using a polymer blending law. 174 This model provides information that can be implemented and combined with the current models to create so-called hybrid models.…”

Section: How To Improve and Extend Current Models?mentioning

confidence: 99%

Functionality-driven food formulation : reducing the environmental impact using machine learning

Lie-Piang¹

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Structure analysis of multi-component pastes – The effect of water distribution on the rheological properties

Cited by 1 publication

References 12 publications

Functionality-driven food formulation : reducing the environmental impact using machine learning

Functionality-driven food formulation : reducing the environmental impact using machine learning

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