From this survey of the literature it can be concluded that the concept of a 3D colour food printer which produces rapidly fully customisable food outputs, including the 3D rendering of complex colour images within the food matrix, is as yet unexplored. Advancing the concept however, can draw on the features it shares with a number of existing methods and technologies that have been covered in this review:
x customised foods i.e. POSIFoods™, or the tailoring of recipes (such as baking recipes) to achieve specific nutritional or sensory properties;
x 3D printing technologies to produce customised outputs using a variety of food, non- food and biological build materials;
x rapid cooking (baking) technologies;
x conventional (2D) colour printing on a variety of surfaces, including food;
x conventional food coloration, tailoring dye recipes to the substrate, also the manual creation of 3D colour patterns (in home baking);
x computer colour matching algorithms that draw on a database of colorant and substrate spectra, used in non-food industries;
x mechanisms to deliver colorants in-line during food extrusion;
x 3D printing or prototyping in full colour, including the use of simple food substrates i.e. sugar.
In bringing together these features in the form of a 3D colour food printer, the major challenge that will be faced will be in trying to achieve simultaneous rapid customisation of complex food formulations and of complex 3D colour outputs. This thesis is concerned largely with the latter. On the one hand customised, rapid, automated, accurate, and complex coloration in both 2D and
129
3D is possible using available printing and computer colour matching techniques, but involve a limited range of substrates. On the other, customisation of complex food outputs has not yet reached the same level of rapidity and neither has coloration of such outputs. Although dye recipes can be tailored to food substrates, this requires the intervention of an expert due to the much broader range of substrates that foods present.
3.7.1.
Required experimental approach
Predictive colour matching capability for the 3D colour food printer should be based ideally on techniques such as computer colour matching and colour printing, for the speed and complexity of their outputs, but have the means of adapting to more complex and diverse food outputs. 3.7.1.1.Application of Kubelka-Munk (K-M) Theory
K-M Theory could form the basis for developing a predictive colour matching algorithm for the 3D colour food printer, as supported by the following:
x The blending of dyes to produce colours can be modelled using functions based on K-M Theory, and in turn the quantities of an unknown blend can be computed to match a given colour, as done routinely in a number of non-food industries; the food industry already makes use of the same relationships between colorant concentration and colour output, but more for the purposes of pigment identification and quantification, and for the modelling of food appearance, rather than for computing dye recipes;
x For both food and non-food applications, the contributions of the physical properties of the substrate, especially in terms of the degree of light scattering produced, to the measured or perceived colour of the substrate has been modelled using K-M or spectral principles; an understanding of these effects is needed in order to optimise the product by either adjusting the quantities of added colorant or the conditions bringing about the changes in physical properties.
130
Therefore, a K-M based model for the 3D colour food printer has the potential to not only compute dye quantities to match colours, but to take into account the physical properties of the substrate being coloured when computing these quantities. This is compatible with the provision of food outputs customised for both formulation and colour appearance.
3.7.1.2.Colour gamut mapping
The range of colours (including their strength) that can be achieved from the addition of colorants to foods depends on many factors. Broadly speaking these include the absorption characteristics of the colorants and their physical format (whether soluble or insoluble), the physical and chemical properties and processing conditions of the substrate (including temperature and heating time, and ingredients that bind dyes), and legal restrictions on the final concentrations of colorants in the foods. Therefore the range of colours that can be produced will be specific to a given combination of colorants and substrate, and also to the viewing conditions under which the coloured product is viewed.
Therefore, as well as to determine the impact of colorants and substrate on food coloration per se, the limit of the achievable colour range for a coloured food needs to be formally computed so that image colours can be transcribed by the 3D colour food printer to fit within the colour range of the food, using colour gamut mapping. This is because the range of colours in an image will far exceed that which can be produced by the combination of the 3D food printing device, the food substrate and colorants. Further, the printer will need to have the capability to compute rapidly colour gamuts for different blank food substrates containing dye blends in line with its capability to customise food outputs (i.e. their formulations). Again, this is where models based on K-M Theory should prove useful; such models can be used for the characterisation (profiling) of the 3D colour food printer, linking dye quantities with CIELAB values, as well as providing the basis for computing gamuts quickly.
131
3.7.1.3.Experimental samples and evaluation of coloration algorithms
Baked goods, especially cakes, are a class of food that satisfies many of the requirements for the 3D colour food printer substrate: these types of formulations are often targeted for modifications designed to achieve specific nutritional and/or sensory outcomes. They can also be rendered extrudable and are able to be cooked rapidly. Properties of the finished substrate affecting final colour rendition such as background colour, surface texture and volume can therefore be expected to vary according to changes in substrate formulation. To have the printer compute on-demand dye recipes for changing formulations, something that would normally be done manually, represents a formidable challenge, and demands a novel approach. This approach might involve investigating either the effects of each property on colour rendition in isolation from the rest, or the effects of several properties combined using representative ‘whole’ formulations. The job of the predictive coloration algorithm within the 3D colour food printer software would then be to combine this information according to the substrate and image specifications ‘keyed-in’ by the user. This algorithm would work in tandem with predictors of the substrate properties themselves; relevant predictive models developed by others for various applications should prove informative here.
Although the 3D colour printed foods are being designed to contain voxels of many colours, it will be far more practical in this thesis research to apply a single colour per experimental sample. In the wider printer research project, the mechanisms to deliver colorants for multiple voxels are yet to be settled. As an automated process, the 3D coloration of food by the printer will need to rely on computed colour differences rather than the visually assessed differences between the original image colours and the food-rendered equivalents. While models have not yet been established to evaluate the quality of colour (print) reproductions, the matching of single colours can be evaluated using colour difference formulae and associated tolerance indices, with consideration given to using formulae appropriate for the physical characteristics of the samples being compared.
132
i. remain relatively stable to the formulation and processing conditions of the substrate; ii. are added to levels which ensure their final concentrations in the finished substrate do
not exceed legal limits (and adhering to this limit for each voxel must ensure that the entire food remains compliant);
iii. are permitted for use in the country in which the food will actually be printed; it is entirely possible that digital colour printing files could be sent from one country in which certain colorants are permitted, to a country in which they are not.
3.7.2.
Consumer aspects
While the proposed 3D colour food printer can be seen as filling a technological gap, it needs also to be justifiable from a consumer point of view. The coloration of food by the printer is less about the role of colour as an indicator of food quality and more about dissociating this colour-quality link in order to customise food appearance in an unusual, creative and appealing way. The printing of colour images in 2D as cake toppers and the colouring of cake batters have paved the way for the acceptance of a technology that is able to print complex colour images in 3D within foods. Another appealing aspect of the technology is that it could allow food production to become a social activity through the sharing of digital files containing design ideas or ready-to-print designs for printing off-site, which taps into the surge in the use of social media in recent years.