Onipe Oluwatoyin O, Beswa Daniso, Jideani Afam I O
Department of Food Science and Technology, School of Agriculture, University of Venda, Thohoyandou 0950, South Africa.
Department of Biotechnology & Food Technology, Faculty of Science, University of Johannesburg, Doornfontein 2028, South Africa.
Foods. 2020 May 9;9(5):605. doi: 10.3390/foods9050605.
A double staining protocol for image acquisition using confocal microscopy (CLSM) coupled with image analysis was employed to elucidate the crust and cross-sectional properties of fried dough. Penetrated oil by image analysis (POia), porosity and pore features were quantified from the cross-section micrographs. Crust surface roughness was measured using fractal metrics and fat content was determined by solvent extraction using the American Association of Cereal Chemists method. Crumb porosity ranged between 54.94%-81.84% and reduced ( < 0.05) with bran addition. Crumb pore sizes ranged from 0-475 µm with <1 circularity, indicating elliptical shape. POia values were notably higher ( < 0.05) than PO by Soxhlet extraction (POsox), except for wheat bran (WB) fried dough where the values of POia and POsox were closely ranked. The linear effect of initial moisture content and bran concentration showed a significant impact on the image properties. The mean fractal dimension (FD) decreased as initial moisture increased. The addition of WB caused a significant reduction in the FD of fried dough, while the opposite effect was noted for its oat bran counterpart. Due to non-collinearity of image properties (FD, POia and porosity), data were fitted to cubic polynomial regression with R values > 0.70. CLSM and image analysis were effective in measuring oil absorption and interpreting crumb properties of fried dough. The protocol used in this study can be applied to other thick deep-fried foods for qualitative observation and quantitative measurement of a specific physical or chemical property.
采用一种结合共聚焦显微镜(CLSM)图像采集和图像分析的双重染色方案,以阐明油条的外皮和横截面特性。通过图像分析测定渗透油(POia),并从横截面显微照片中量化孔隙率和孔隙特征。使用分形度量法测量外皮表面粗糙度,并采用美国谷物化学家协会的方法通过溶剂萃取法测定脂肪含量。面包心孔隙率在54.94%-81.84%之间,添加麸皮后孔隙率降低(<0.05)。面包心孔径范围为0-475 µm,圆形度<1,表明为椭圆形。除了麦麸(WB)油条外,POia值显著高于索氏提取法测得的渗透油(POsox)值,而在麦麸油条中,POia和POsox的值相近。初始水分含量和麸皮浓度的线性效应显示出对图像特性有显著影响。平均分形维数(FD)随着初始水分的增加而降低。添加WB会导致油条的FD显著降低,而燕麦麸油条则呈现相反的效果。由于图像特性(FD、POia和孔隙率)的非共线性,数据拟合为三次多项式回归,R值>0.70。CLSM和图像分析在测量油炸面团的吸油率和解释面包心特性方面是有效的。本研究中使用的方案可应用于其他厚的油炸食品,用于特定物理或化学性质的定性观察和定量测量。