College of Food Science and Engineering, Jilin University, Changchun, China.
J Texture Stud. 2018 Feb;49(1):102-112. doi: 10.1111/jtxs.12295. Epub 2017 Aug 30.
The cloud model is a typical model which transforms the qualitative concept into the quantitative description. The cloud model has been used less extensively in texture studies before. The purpose of this study was to apply the cloud model in food crispness comparison. The acoustic signals of carrots, white radishes, potatoes, Fuji apples, and crystal pears were recorded during compression. And three time-domain signal characteristics were extracted, including sound intensity, maximum short-time frame energy, and waveform index. The three signal characteristics and the cloud model were used to compare the crispness of the samples mentioned above. The crispness based on the Ex value of the cloud model, in a descending order, was carrot > potato > white radish > Fuji apple > crystal pear. To verify the results of the acoustic signals, mechanical measurement and sensory evaluation were conducted. The results of the two verification experiments confirmed the feasibility of the cloud model. The microstructures of the five samples were also analyzed. The microstructure parameters were negatively related with crispness (p < .01).
The cloud model method can be used for crispness comparison of different kinds of foods. The method is more accurate than the traditional methods such as mechanical measurement and sensory evaluation. The cloud model method can also be applied to other texture studies extensively.
云模型是一种将定性概念转化为定量描述的典型模型。在过去,云模型在纹理研究中的应用较少。本研究的目的是将云模型应用于食品脆性比较。在压缩过程中记录了胡萝卜、白萝卜、土豆、富士苹果和水晶梨的声音信号。并提取了三个时域信号特征,包括声强、最大短时帧能量和波形指数。使用这三个信号特征和云模型来比较上述样本的脆性。基于云模型的 Ex 值的脆性从大到小依次为胡萝卜>土豆>白萝卜>富士苹果>水晶梨。为了验证声信号的结果,进行了机械测量和感官评价。两个验证实验的结果证实了云模型的可行性。还分析了五个样本的微观结构。微观结构参数与脆性呈负相关(p<.01)。
云模型方法可用于不同类型食品的脆性比较。该方法比机械测量和感官评价等传统方法更准确。云模型方法还可以广泛应用于其他纹理研究。