Riddet Institute, and Institute of Food, Nutrition and Human Health, Massey Univ, Palmerston North, New Zealand.
J Food Sci. 2012 Jun;77(6):S216-25. doi: 10.1111/j.1750-3841.2012.02744.x.
A predictive color matching model based on the colorimetric technique was developed and used to calculate the concentrations of primary food dyes needed in a model food substrate to match a set of standard tile colors. This research is the first stage in the development of novel three-dimensional (3D) foods in which color images or designs can be rapidly reproduced in 3D form. Absorption coefficients were derived for each dye, from a concentration series in the model substrate, a microwave-baked cake. When used in a linear, additive blending model these coefficients were able to predict cake color from selected dye blends to within 3 ΔE*(ab,10) color difference units, or within the limit of a visually acceptable match. Absorption coefficients were converted to pseudo X₁₀, Y₁₀, and Z₁₀ tri-stimulus values (X₁₀(P), Y₁₀(P), Z₁₀(P)) for colorimetric matching. The Allen algorithm was used to calculate dye concentrations to match the X₁₀(P), Y₁₀(P), and Z₁₀(P) values of each tile color. Several recipes for each color were computed with the tile specular component included or excluded, and tested in the cake. Some tile colors proved out-of-gamut, limited by legal dye concentrations; these were scaled to within legal range. Actual differences suggest reasonable visual matches could be achieved for within-gamut tile colors. The Allen algorithm, with appropriate adjustments of concentration outputs, could provide a sufficiently rapid and accurate calculation tool for 3D color food printing.
The predictive color matching approach shows potential for use in a novel embodiment of 3D food printing in which a color image or design could be rendered within a food matrix through the selective blending of primary dyes to reproduce each color element. The on-demand nature of this food application requires rapid color outputs which could be provided by the color matching technique, currently used in nonfood industries, rather than by empirical food industry methods.
开发了一种基于比色技术的预测配色模型，并将其用于计算模型食品基质中所需的主要食品染料浓度，以匹配一组标准瓷砖颜色。这项研究是开发新型三维（3D）食品的第一阶段，其中可以快速以 3D 形式再现颜色图像或设计。从模型基质（微波烤制的蛋糕）中的浓度系列中得出了每种染料的吸收系数。当在线性加性混合模型中使用时，这些系数能够在所选择的染料混合物内将蛋糕颜色预测到 3 ΔE*（ab，10）色差单位内，或在视觉可接受的匹配范围内。吸收系数被转换为伪 X₁₀、Y₁₀ 和 Z₁₀ 三刺激值（X₁₀（P）、Y₁₀（P）、Z₁₀（P））用于比色匹配。使用 Allen 算法计算染料浓度以匹配每个瓷砖颜色的 X₁₀（P）、Y₁₀（P）和 Z₁₀（P）值。对于每种颜色计算了几个配方，包括或不包括瓷砖镜面成分，并在蛋糕中进行了测试。一些瓷砖颜色超出了色域，受到法定染料浓度的限制；这些颜色被缩小到法定范围内。实际差异表明，对于色域内的瓷砖颜色，可以实现合理的视觉匹配。Allen 算法，通过适当调整浓度输出，可以为 3D 彩色食品打印提供足够快速和准确的计算工具。
预测配色方法显示出在新型 3D 食品打印中的应用潜力，其中颜色图像或设计可以通过选择性混合主要染料在食品基质中呈现，以再现每个颜色元素。这种食品应用的按需性质需要快速的颜色输出，这可以通过比色技术提供，该技术目前用于非食品行业，而不是通过经验丰富的食品行业方法。
