Functionality-driven food product formulation – An illustration on selecting sustainable ingredients building viscosity

Quantifying techno-functional properties of ingredients from multiple crops using machine learning

Food ingredients with a low degree of refining consist of multiple components. Therefore, it is essential to formulate food products based on techno-functional properties rather than composition. We assessed the potential of quantifying techno-functional properties of ingredient blends from multiple crops as opposed to single crops. The properties quantified were gelation, viscosity, emulsion stability, and foaming capacity of ingredients from yellow pea and lupine seeds. The relationships were quantified using spline regression, random forest, and neural networks. Suitable models were picked based on model accuracy and physical feasibility of model predictions. A single model to quantify the properties of both crops could be created for each techno-functional property, albeit with a trade-off of higher prediction errors as compared to models based on individual crops. A reflection on the number of observations in each dataset showed that they could be reduced for some properties.

Rheology of liquid foods under shear flow conditions: Recently used models

Proper modeling of flow or viscosity curves as a function of shear rate is a useful tool in any engineering activity. The rheology of foods depends on the composition, processing to which they have been subjected and the state of dispersion in which they are found. Liquid foods are complex biosystems, that show non-Newtonian behavior under flow conditions. This review presents models used in recent decades to describe the experimental rheological behavior of various liquid foods, ranging from Newtonian fluids to the most complex. Some non-Newtonian parameters such as those of the Ostwald-de Waele, Bingham, Herschel-Bulkley, Casson, Cross, and Carreau models are summarized. Examples of thixotropic behavior described by the Weltman and Abu-Jdayil models are also presented. In each model, explanations based on the composition and dispersion state of the food are made. This is useful in innovative processing technologies and for scientists new to the field of food rheology. An attempt is made to exemplify and group the expected behavior for most fluid foods, including some for a dysphagia diet, depending on their composition or the dispersed system formed, which will be useful for professionals who wish to compare reported rheological parameters with those obtained experimentally.

Mild Fractionation for More Sustainable Food Ingredients

With the rising problems of food shortages, energy costs, and raw materials, the food industry must reduce its environmental impact. We present an overview of more resource-efficient processes to produce food ingredients, describing their environmental impact and the functional properties obtained. Extensive wet processing yields high purities but also has the highest environmental impact, mainly due to heating for protein precipitation and dehydration. Milder wet alternatives exclude, for example, low pH-driven separation and are based on salt precipitation or water only. Drying steps are omitted during dry fractionation using air classification or electrostatic separation. Benefits of milder methods are enhanced functional properties. Therefore, fractionation and formulation should be focused on the desired functionality instead of purity. Environmental impact is also strongly reduced by milder refining. Antinutritional factors and off-flavors remain challenges in more mildly produced ingredients. The benefits of less refining motivate the increasing trend toward mildly refined ingredients.