In this work, principal component analysis (PCA) was utilized to analyze laser-induced breakdown spectroscopy (LIBS) signals of the extracted chicken fat, lamb fat, beef fat, and lard froze using two different freezing methods. The frozen samples were ablated using a neodymium-doped yttrium aluminum garnet (Nd:YAG) laser with a wavelength of 1064 nm, 170 mJ pulse energy, and 6 ns pulse duration to produce plasma on target surfaces. The samples were ablated using 30–60 shots of the laser beam at different spots. Stronger LIBS signals from the extracted chicken fat and lamb fat were obtained with liquid nitrogen (LN2) method. However, LIBS signals obtained from the freezer freezing method were found to be stronger for extracted beef fat and lard. The PCA was then used to visualize the LIBS spectra of extracted animal fats into a score plot. Data points of each extracted animal fat were divided into three groups representing LIBS spectra collected at the early, middle, and end part of the ablation process. The score plot revealed that the data points of the three groups of frozen extracted animal fats using the LN2 method were more closely clustered than those frozen in the freezer. Good discrimination with 97% of the variance was achieved between the extracted chicken fat, lamb fat, beef fat, and lard using the LN2 method in the three-dimensional score plot. LIBS signals of the extracted animal fats produced from the LN2 method were found to be more stable than those from the freezer method.

中文翻译：

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EXPRESS：使用主成分分析方法对提取的动物脂肪进行激光诱导分解光谱的信号增强评估

在这项工作中，主成分分析 (PCA) 用于分析提取的鸡肉脂肪、羊肉脂肪、牛肉脂肪和使用两种不同冷冻方法冷冻的猪油的激光诱导击穿光谱 (LIBS) 信号。使用波长为 1064 nm、170 mJ 脉冲能量和 6 ns 脉冲持续时间的掺钕钇铝石榴石 (Nd:YAG) 激光器烧蚀冷冻样品，以在目标表面上产生等离子体。在不同的点使用 30-60 次激光束对样品进行烧蚀。使用液氮 (LN2) 方法从提取的鸡肉脂肪和羊肉脂肪中获得了更强的 LIBS 信号。然而，发现从冷冻冷冻方法获得的 LIBS 信号对于提取的牛肉脂肪和猪油更强。然后使用 PCA 将提取的动物脂肪的 LIBS 光谱可视化为评分图。每种提取的动物脂肪的数据点分为三组，代表在消融过程的早期、中期和后期收集的 LIBS 光谱。得分图显示，使用 LN2 方法的三组冷冻提取的动物脂肪的数据点比在冰箱中冷冻的数据点更紧密地聚集在一起。在三维评分图中使用 LN2 方法在提取的鸡肉脂肪、羊肉脂肪、牛肉脂肪和猪油之间实现了 97% 的良好区分。发现由 LN2 方法产生的提取动物脂肪的 LIBS 信号比来自冷冻方法的信号更稳定。得分图显示，使用 LN2 方法的三组冷冻提取的动物脂肪的数据点比在冰箱中冷冻的数据点更紧密地聚集在一起。在三维评分图中使用 LN2 方法在提取的鸡肉脂肪、羊肉脂肪、牛肉脂肪和猪油之间实现了 97% 的良好区分。发现由 LN2 方法产生的提取动物脂肪的 LIBS 信号比来自冷冻方法的信号更稳定。得分图显示，使用 LN2 方法的三组冷冻提取的动物脂肪的数据点比在冰箱中冷冻的数据点更紧密地聚集在一起。在三维评分图中使用 LN2 方法在提取的鸡肉脂肪、羊肉脂肪、牛肉脂肪和猪油之间实现了 97% 的良好区分。发现由 LN2 方法产生的提取动物脂肪的 LIBS 信号比来自冷冻方法的信号更稳定。