This study introduces an innovative contour detection algorithm,PeakCET,designed for rapid and efficient analysis of natural product image fingerprints using comprehensive two-dimensional gas chromatogram(GC×GC)....This study introduces an innovative contour detection algorithm,PeakCET,designed for rapid and efficient analysis of natural product image fingerprints using comprehensive two-dimensional gas chromatogram(GC×GC).This method innovatively combines contour edge tracking with affinity propagation(AP)clustering for peak detection in GC×GC fingerprints,the first in this field.Contour edge tracking signif-icantly reduces false positives caused by“burr”signals,while AP clustering enhances detection accuracy in the face of false negatives.The efficacy of this approach is demonstrated using three medicinal products derived from Curcuma wenyujin.PeakCET not only performs contour detection but also employs inter-group peak matching and peak-volume percentage calculations to assess the compositional similarities and differences among various samples.Furthermore,this algorithm compares the GC×GC fingerprints of Radix/Rhizoma Curcumae Wenyujin with those of products from different botanical origins.The findings reveal that genetic and geographical factors influence the accumulation of secondary metabolites in various plant tissues.Each sample exhibits unique characteristic components alongside common ones,and vari-ations in content may influence their therapeutic effectiveness.This research establishes a foundational data-set for the quality assessment of Curcuma products and paves the way for the application of computer vision techniques in two-dimensional(2D)fingerprint analysis of GC×GC data.展开更多
The determination of the ethanol content in food products is of fundamental importance for HALAL certification. In this work, an analytical method for the determination of ethanol in water by headspace gas chromatogra...The determination of the ethanol content in food products is of fundamental importance for HALAL certification. In this work, an analytical method for the determination of ethanol in water by headspace gas chromatography with flame ionization detector (HS-GC-FID) has been developed and validated for the use in characterization of ethanol reference materials. The validation study was carried out in the linear calibration range 100 - 1500 mg/kg using the NIST SRM 2900, nominal 95.6%. The studied performance characteristics of the method were the limit of detection, LOD, the limit of quantification LOQ, selectivity, linearity, precision, recovery and bias. The validation results showed that the method is selective, precise, accurate and free from any significant bias. The LOD and LOQ were 1.27 and 3.86 mg/kg respectively and the estimated expanded uncertainty was 2% indicating that the method is fit for the purpose of certification of ethanol in water reference materials.展开更多
基金supported by Hunan 2011 Collaborative Innovation Center of Chemical Engineering&Technology with Environmental Benignity and Effective Resource Utilization,Hunan Province Natural Science Fund,China(Grant Nos.:2020JJ4569,2023JJ60378)Hunan Province College Students'Innovation and Entrepreneurship Training Program,China(Grant Nos.:S202110530044,S202210530048).
文摘This study introduces an innovative contour detection algorithm,PeakCET,designed for rapid and efficient analysis of natural product image fingerprints using comprehensive two-dimensional gas chromatogram(GC×GC).This method innovatively combines contour edge tracking with affinity propagation(AP)clustering for peak detection in GC×GC fingerprints,the first in this field.Contour edge tracking signif-icantly reduces false positives caused by“burr”signals,while AP clustering enhances detection accuracy in the face of false negatives.The efficacy of this approach is demonstrated using three medicinal products derived from Curcuma wenyujin.PeakCET not only performs contour detection but also employs inter-group peak matching and peak-volume percentage calculations to assess the compositional similarities and differences among various samples.Furthermore,this algorithm compares the GC×GC fingerprints of Radix/Rhizoma Curcumae Wenyujin with those of products from different botanical origins.The findings reveal that genetic and geographical factors influence the accumulation of secondary metabolites in various plant tissues.Each sample exhibits unique characteristic components alongside common ones,and vari-ations in content may influence their therapeutic effectiveness.This research establishes a foundational data-set for the quality assessment of Curcuma products and paves the way for the application of computer vision techniques in two-dimensional(2D)fingerprint analysis of GC×GC data.
文摘The determination of the ethanol content in food products is of fundamental importance for HALAL certification. In this work, an analytical method for the determination of ethanol in water by headspace gas chromatography with flame ionization detector (HS-GC-FID) has been developed and validated for the use in characterization of ethanol reference materials. The validation study was carried out in the linear calibration range 100 - 1500 mg/kg using the NIST SRM 2900, nominal 95.6%. The studied performance characteristics of the method were the limit of detection, LOD, the limit of quantification LOQ, selectivity, linearity, precision, recovery and bias. The validation results showed that the method is selective, precise, accurate and free from any significant bias. The LOD and LOQ were 1.27 and 3.86 mg/kg respectively and the estimated expanded uncertainty was 2% indicating that the method is fit for the purpose of certification of ethanol in water reference materials.
