Polyak Peter, Chaber Paweł, Musioł Marta, Adamus Grażyna, Kowalczuk Marek, Puskas Judit E, El Fray Miroslawa
Department of Food, Agricultural and Biological Engineering, College of Food, Agricultural, and Environmental Sciences, The Ohio State University, 1680 Madison Avenue, Wooster, 44691, USA.
Centre of Polymer and Carbon Materials, Polish Academy of Sciences, 34, M. Curie-Skłodowska St, 41-819, Zabrze, Poland.
Anal Sci. 2025 May 8. doi: 10.1007/s44211-025-00780-2.
In this paper, we present a method for calculating the average molecular weight of microbial polyesters using Fourier transform infrared spectroscopy (FTIR) data as input. FTIR spectra provide the necessary quantitative information, as the impact of chain ends on the spectra is influenced by the average molecular weight of the polymer. Since FTIR data can be collected rapidly and is available in abundance, it serves as an ideal input for machine learning algorithms, such as artificial neural networks. The robustness and reliability of the model are improved by designing the neural network to use absorbance ratios instead of absolute absorbances as input. We also propose a new feature selection method that facilitates the identification of absorbance ratio regions best suited to serve as input for the neural network. Our approach ensures that variations in sample preparation do not compromise the accuracy of the model. The proposed computational method is demonstrated using a microbial polyester [poly(3-hydroxybutyrate), PHB], which is a biopolymer natively synthesized by multiple bacterial strains. Although the computational method has been tested with PHB, the underlying concept can be extended to other polymers. To facilitate broader application, a step-by-step guide for developing similar models is also provided.
在本文中，我们提出了一种以傅里叶变换红外光谱（FTIR）数据作为输入来计算微生物聚酯平均分子量的方法。FTIR光谱提供了必要的定量信息，因为聚合物链端对光谱的影响受聚合物平均分子量的影响。由于FTIR数据可以快速收集且数量丰富，它是机器学习算法（如人工神经网络）的理想输入。通过设计神经网络使用吸光度比而非绝对吸光度作为输入，提高了模型的稳健性和可靠性。我们还提出了一种新的特征选择方法，有助于识别最适合作为神经网络输入的吸光度比区域。我们的方法确保了样品制备过程中的变化不会影响模型的准确性。使用微生物聚酯[聚（3-羟基丁酸酯），PHB]演示了所提出的计算方法，PHB是一种由多种细菌菌株天然合成的生物聚合物。尽管该计算方法已用PHB进行了测试，但其基本概念可扩展到其他聚合物。为便于更广泛的应用，还提供了开发类似模型的分步指南。
