Vivian Chinekwu Onwujiogu, Samuel Ibezim Orjiocha, Eze Faith Chinonso, Mansour A.S. Salem, Aadil Shafi Bhat, Rabiya Mehandi, Abugu Hillary Onyeka
Hyphenated techniques for natural product analysis significantly enhance the separation and identification of complex mixtures. Among these, Gas Chromatography-Mass Spectrometry (GC-MS) excels at analyzing volatile and semi-volatile compounds. Food safety, forensics, medicines, environmental analysis, and other fields depend on it heavily, and new technical developments are always improving its abilities and extending its uses. Sensitivity and selectivity of GC-MS have greatly increased in recent years. Automated sample preparation methods improve efficiency, decrease human error, and streamline operations. Machine learning techniques also improve data analysis by allowing automated peak detection, quantification, and compound property prediction. High-throughput analysis is facilitated by ultra-high-performance liquid chromatography (UHPLC) and high-performance liquid chromatography-mass spectrometry (HPLC-MS). When it comes to locating and measuring the bioactive substances in medicinal plants, HPLC-MS is quite useful. Liquid Chromatography-Fourier Transform Infrared Spectroscopy (LC-FTIR) provides complementary benefits by combining liquid chromatography’s separation capabilities with FTIR’s structural elucidation. LC-FTIR improves molecular composition comprehension and quantitative capabilities, as chemometrics advances. Combining LC-FTIR with additional methods, such as LC-MS, offers a full perspective of sample composition. Along with these technological advancements, green chromatography methods such as eco-friendly solvents, supercritical fluid chromatography (SFC), energy-efficient apparatus, and low-waste sample preparation are gaining popularity for decreasing the ecological impact. This study aims at understanding the principles, advantages, limits, scientific evaluation, applications and differences in modern hyphenated chromatographic technique which have found relevance in natural products analysis.