Senturk Parreidt Tugce, Schmid Markus, Hauser Carolin
Fraunhofer Institute for Process Engineering and Packaging IVV, Giggenhauser Straße 35, Freising 85354, Germany.
Chair for Food Packaging Technology, Technische Universität München, Weihenstephaner Steig 22, Freising 85354, Germany.
Foods. 2017 Apr 20;6(4):31. doi: 10.3390/foods6040031.
Characterizing the physical properties of a surface is largely dependent on determining the contact angle exhibited by a liquid. Contact angles on the surfaces of rough and irregularly-shaped food samples are difficult to measure using a contact angle meter (goniometer). As a consequence, values for the surface energy and its components can be mismeasured. The aim of this work was to use a novel contact angle measurement method, namely the snake-based ImageJ program, to accurately measure the contact angles of rough and irregular shapes, such as food samples, and so enable more accurate calculation of the surface energy of food materials. In order to validate the novel technique, the contact angles of three different test liquids on four different smooth polymer films were measured using both the ImageJ software with the DropSnake plugin and the widely used contact angle meter. The distributions of the values obtained by the two methods were different. Therefore, the contact angles, surface energies, and polar and dispersive components of plastic films obtained using the ImageJ program and the Drop Shape Analyzer (DSA) were interpreted with the help of simple linear regression analysis. As case studies, the superficial characteristics of strawberry and endive salad epicarp were measured with the ImageJ program and the results were interpreted with the Drop Shape Analyzer equivalent according to our regression models. The data indicated that the ImageJ program can be successfully used for contact angle determination of rough and strongly hydrophobic surfaces, such as strawberry epicarp. However, for the special geometry of droplets on slightly hydrophobic surfaces, such as salad leaves, the program code interpolation part can be altered.
表征表面的物理性质很大程度上取决于确定液体所呈现的接触角。使用接触角测量仪（测角仪）很难测量粗糙且形状不规则的食品样品表面的接触角。因此，表面能及其组分的值可能会被误测。这项工作的目的是使用一种新颖的接触角测量方法，即基于蛇形的ImageJ程序，来精确测量粗糙和不规则形状（如食品样品）的接触角，从而能够更准确地计算食品材料的表面能。为了验证这项新技术，使用带有DropSnake插件的ImageJ软件和广泛使用的接触角测量仪，测量了三种不同测试液体在四种不同光滑聚合物薄膜上的接触角。两种方法获得的值的分布不同。因此，借助简单线性回归分析对使用ImageJ程序和液滴形状分析仪（DSA）获得的塑料薄膜的接触角、表面能以及极性和色散组分进行了解释。作为案例研究，使用ImageJ程序测量了草莓和菊苣沙拉外皮的表面特征，并根据我们的回归模型用等效的液滴形状分析仪对结果进行了解释。数据表明，ImageJ程序可成功用于测量粗糙和强疏水表面（如草莓外皮）的接触角。然而，对于稍疏水表面（如沙拉叶）上液滴的特殊几何形状，程序代码插值部分可以更改。
