Impact of Different Drying Approaches on VOCs and Chemical Composition of Mentha spicata L. Essential Oil: A Combined Analysis of GC/MS and E-nose with Chemometrics methods

Given the significance spearmint (Mentha spicata L.), there is an increased demand for dry medicines and high-quality aromatic mint. In this study, a non-destructive technique based on electronic nose was used in combination with a GC/MS method and chemometrics to determine the quality of spearmint essential oil under eight drying methods. It was found that hot air drying (HAD) method yielded the highest amount of essential oil and its compounds. So that its highest amount was obtained in HAD1a method and equal to 1.380%. However, the amount decreased with increasing drying temperature and air velocity. In addition, sun drying performed worst its value was equal to 0.663%. The highest percentage of the obtained essential oil compounds was related to the three main components of carvone (64.30-7.45%), limonene (24.21-6.59%), and carveol (18.34-1.92%). Furthermore, the Nu-SVM classification algorithm with the sigmoid function provided an accuracy of 0.975 for classifying eight essential oil groups. In light of the limited knowledge about the effects of drying on the qualitative and quantitative characteristics of medicinal plants, a new method for essential oil evaluation was proposed in this study. The results could provide a theoretical reference to choose the best drying method and quickly determine the quality of mint essential oils. •This study introduces a novel approach using electronic nose and chemometrics to assess essential oil quality, offering a fresh perspective on drying methods' impact.•The HAD1A drying technique displayed the highest essential oil yield, while sun drying showed the lowest, aiding in selecting the most effective drying process. The research also demonstrates a decrease in essential oil amount with rising drying temperatures and air velocity.•Three classification algorithms were used to evaluate the aromatic properties of mint essential oil. The Nu-SVM method achieved the highest classification rate using the sigmoid function with 0.975.•This study highlights the need for continued research on enhancing drying technology and implementing monitoring systems for sensory quality control. The results pave the way for further advancements in in situ drying processes for medicinal plants.