Preiner Sára, Tarcsay Bálint Levente, Pethő Dóra, Miskolczi Norbert
Research Centre for Biochemical, Environmental and Chemical Engineering, University of Pannonia, Egyetem st.10, Veszprém, 8200, Hungary.
MethodsX. 2025 Apr 5;14:103304. doi: 10.1016/j.mex.2025.103304. eCollection 2025 Jun.
The aim of our work was to estimate the composition of hydrosol produced as a byproduct of lavender steam distillation using UV-Vis spectrophotometry in the 200-600 nm wavelength range through a machine learning algorithm. The dissolved components of lavender essential oil (EO) from lavender hydrosol samples were extracted via liquid-liquid extraction, using three different solvents (pentane, heptane and diethyl ether). The UV-Vis absorbance spectra of the extracts were recorded and the composition analyzed using GC-MS. The composition data obtained allowed for the calculation of changes within the quantities of different EO components in the samples. The partial least squares regression technique (PLS) was utilized to establish a connection between changes in the composition of the hydrosol and the changes in the UV-Vis spectra. After optimization the established PLS model showed an score above 0.95 for the prediction of hydrosol composition changes during cross-validation. The model can thus be utilized as a soft sensor to infer extracted mass of EO components and characterize the composition of hydrosol during the process directly from UV-Vis spectra.•Investigation of lavender water and extract using UV-Vis spectrophotometry•GC-MS analysis of extracts•PLS model development for composition estimation based on spectra.
我们工作的目的是通过机器学习算法，利用紫外可见分光光度法在200 - 600纳米波长范围内估算薰衣草水蒸气蒸馏副产物水溶胶的成分。采用液液萃取法，使用三种不同溶剂（戊烷、庚烷和乙醚）从薰衣草水溶胶样品中提取薰衣草精油（EO）的溶解成分。记录提取物的紫外可见吸收光谱，并使用气相色谱 - 质谱联用仪（GC - MS）分析其成分。所获得的成分数据可用于计算样品中不同EO成分含量的变化。利用偏最小二乘回归技术（PLS）建立水溶胶成分变化与紫外可见光谱变化之间的联系。经过优化，所建立的PLS模型在交叉验证期间对水溶胶成分变化的预测得分高于0.95。因此，该模型可作为一种软传感器，直接从紫外可见光谱推断EO成分的提取量，并表征过程中水溶胶的成分。•利用紫外可见分光光度法研究薰衣草水和提取物•提取物的GC - MS分析•基于光谱的成分估计的PLS模型开发
