Three-dimensional (3D) printing is an additive manufacturing technology whereby objects are built layer by layer, from a 3D image file held in a computer, using base materials as diverse as metal powders (Wikipedia, 2011), molten plastics (Wikipedia, 2014a), concrete (Day, 2011) and paper (Mcor Technologies Ltd., 2013). 3D printing offers an economical and convenient alternative to traditional forms of manufacturing: it does not require the use of a mould, and it is designed to produce objects on-demand. 3D printing is also a developing technology for food manufacture, providing an ideal means for personalising food production to meet customer specifications for selected product characteristics. Currently, 3D food printers exist as concepts (Seth, 2009; Coelho, 2010) or as prototypes (Moskvitch, 2011), or are available in the form of open-source hardware and software (fab@home Project, 2011) or retail units. Open-source and retail units are designed to print conventional food items - such as chocolate (Hao et al., 2010), cookie dough (Lipton et al., 2010) and cakes (Natural Machines, 2014) - or ingredients (e.g. sugar) into new shapes and forms (Inspix, 2014; The CandyFab Project, 2014), while concept printers allow for new ingredient combinations to be created, leading to more fully customised outputs. The technology being developed in the wider 3D food printing research project, of which this thesis forms one part, is a realisation of the latter type. The provision of outputs which meet individual customer specifications for such product characteristics as shape, texture, flavour, appearance and nutritional value, will be underpinned by a thorough understanding of how these characteristics develop as a function of formulation. Therefore it should be possible each time for the printer to not only select the appropriate ingredients, but to combine the ingredients and deposit the mixtures accurately in raw form, before the food is cooked rapidly to develop and set the structure.
A less explored aspect of personalised foods is the concept of being able to customise the visual appearance of any prepared food. The focus of this thesis is on customising the visual
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appearance and visual appeal of 3D printed foods in a novel way: by the rendering of any chosen complex colour image or design in 3D within the food matrix. During the printing process, dye blends will be delivered in small volumes to predetermined positions within the colour-neutral raw food, so that a multitude of colour voxels (volume elements) are produced in the finished food to match the original design. Each blend, corresponding to a single voxel, will be produced from the same three or four primary dyes, but blends will differ in the relative proportions of these dyes.
The formation, coloration and cooking of 3D colour printed foods is being designed as a rapid, bench-scale, one-stop, on-demand process, for home or industrial use. The specifications for printing present a number of challenges to developing suitable colour matching capability. The printed foods have the potential to be hugely diverse in their physical and chemical attributes (varying according to the formulation selected), all of which will affect final colour rendition. This, together with the need for colour matching capability to be fast, and built-in, rules out methods currently used by the food industry, such as custom blending by expert formulators, which are applied on a case-by-case basis and are based usually on visual assessment. While conventional colour printing does use primaries (CMYK inks), it relies also on the size and positioning of fine ink dots on a two-dimensional, white printing surface to produce colours whereas the printed foods will require coloration in 3D, and not necessarily against a white background. Potentially more suitable is the Pantone Matching System (PMS) which is used for a range of materials including dyed textiles and pigmented plastics, as well as for colour printing. Pantone systems however, are based on a larger number of primaries (10 to 14) and take the form of extensive colour palettes with a proprietary ink recipe for each colour, which are used to communicate colour between designers and printers. In contrast, the 3D colour food printer will need to compute (unknown) dye quantities on demand from a smaller number of available primaries. And while non-food 3D colour printers are available which are capable of producing up to 390,000 colours with high resolution, using up to five print heads, printing again uses a white substrate (or alternatively, a clear substrate), in the form of a powder (3D
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Systems, 2014). In addition, the processes of structure formation and coloration in these printers differ to those being proposed for the 3D colour food printer.
Predictive computer colour matching techniques used in the paint, textiles, plastics and ceramics industries might be more suitable for use by the 3D colour food printer. These techniques are based on linear, additive models in which the relative contributions of colorants and substrates to measured colour are expressed in terms of their light absorption-scatter spectra (McDonald, 1987; Berns, 2000). Drawing on a spectral database, either spectral or colorimetric matching algorithms are used to select quickly and accurately the colorants, and the quantities of each, that are needed to match target colours. Colorimetric matching, which is the conditional matching of tristimulus values under specified illuminant and observer conditions in spite of spectral differences, is more commonly used because in most situations the coloration systems of the target and match are not identical (McDonald, 1987). Although measurements of absorption and scatter have been used in the analysis of various aspects of food appearance, such as the relationship between visual translucency and storage time of tomatoes (Lana et al., 2006), the determination of pigment composition (Hutchings, 1999) and the prediction of food emulsion colour (McClements et al., 1998), predictive computer colour matching has not found wider application in the food industry. Compared to the other industries, the food industry does not normally need the same level of precision for matching colours; the much broader range of substrates presented by foods has made it difficult to justify development of a spectral database for food colorants and substrates (Francis, 1999).
The aim of the research which is the subject of this chapter was to develop a predictive color matching model based on colorimetric matching, which can compute the quantities of primary- coloured food dyes that need to be added to a model food, in order for the food to match a range of target colours. This work forms the first step in the development of colour matching capability for the 3D colour food printer. Because it serves as an in-principle demonstration of the application of computer colour matching to food, the research used only a single food as the model substrate: a microwave-baked cake. Microwave cooking suits the rapidity of 3D
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printing, while baked goods are an ideal model on which to base 3D printed foods, providing potentially a range of desired characteristics in both raw and cooked states, which can be made to vary with changes in formulation.
The specific objectives of this research were:
x To derive the light absorption spectrum for the model substrate and the unit absorption spectra for each of three primary-coloured dyes when these are added separately to the substrate;
x To validate the unit absorption spectra by investigating the colour outputs when the dyes are blended within the substrate;
x To match a set of standard colours using the dye-substrate system and a modified colorimetric matching technique; and
x To evaluate the degree of matching using colour difference formulae.