色调
鸡胸脯
轻巧
RGB颜色模型
色差
数学
主成分分析
食品科学
化学
人工智能
颜色分析
计算机科学
统计
GSM演进的增强数据速率
作者
Pramilih Wahyu Nastiti,Nursigit Bintoro,Joko Nugroho Wahyu Karyadi,Sri Rahayoe
出处
期刊:Key Engineering Materials
日期:2022-08-16
卷期号:928: 103-110
被引量:2
摘要
Chicken meat has a high nutritional content that makes its freshness rapidly deteriorates. A color change characterized the degradation. Color changes could influence the consumer perception toward food quality. Human perception and evaluation of color are often subjective. Sensors can provide better detection accuracy toward this phenomenon than the human senses. This study aims to determine the change of color attribute of chicken breast meat kinetically and classify meat quality based on color changes during meat storage using Principal Component Analysis (PCA). The experiment was performed with equipment consisting of a Raspberry Pi, Arduino, and a TCS 3200 color sensor. The meat sample was stored in a dark-colored container along with the sensor for 24 hours storage at room temperature. The measurement was done every hour in three replications. Color data from sensor readings in the frequency form was then converted into RGB (Red, Green, Blue) values and finally to L*, a*, b* values during the experiment. The data obtained was sent to the database for kinetic analysis and quality classification using PCA. It was found that the change of color attribute of Chroma (C), Hue Angle (Ho), Color Difference with True Red (DE), and Color Difference (AE) followed zero-order or first-order kinetics reactions. While from the PCA resulted, two chicken meat quality classes, PC 1, explained 85.4%, and PC 2 explained 12.5%.
科研通智能强力驱动
Strongly Powered by AbleSci AI