ArticleRSC advances2024
A simple and reliable QSPR model for prediction of chromatography retention indices of volatile organic compounds in peppers.
Article in RSC advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 17 citations in OpenAlex.
- SMILES-based QSAR analysis of carbamate derivatives targeting butyrylcholinesterase.Scientific reports · 2026Article
- Using the Coefficient of Conformism of a Correlative Prediction in Simulation of Cardiotoxicity.Toxics · 2025Article
- [Construction of a machine learning ensemble prediction model for gas chromatographic retention index on stationary phases with different polarities].Se pu = Chinese journal of chromatography · 2025Article
- Construction of reliable QSPR models for predicting the impact sensitivity of nitroenergetic compounds using correlation weights of the fragments of molecular structures.Scientific reports · 2025Article
- Article
- Simulation of the Long-Term Toxicity Towards Bobwhite Quail (Journal of xenobiotics · 2024Article
- QSAR models for the ozonation of diverse volatile organic compounds at different temperatures.RSC advances · 2024Article
Corrections and comments
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Authors and funding
4 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Worldwide, various types of pepper are used in food as an additive due to their unique pungency, aroma, taste, and color. This spice is valued for its pungency contributed by the alkaloid piperine and aroma attributed to volatile essential oils. The essential oils are composed of volatile organic compounds (VOCs) in different concentrations and ratios. In chromatography, the identification of compounds is done by comparing obtained peaks with a reference standard. However, there are cases where reference standards are either unavailable or the chemical information of VOCs is not documented in reference libraries. To overcome these limitations, theoretical methodologies are applied to estimate the retention indices (RIs) of new VOCs. The aim of the present work is to develop a reliable QSPR model for the RIs of 273 identified VOCs of different types of pepper. Experimental retention indices were measured using comprehensive two-dimensional gas chromatography coupled to quadrupole mass spectrometry (GC × GC/qMS) using a coupled BPX5 and BP20 column system. The inbuilt Monte Carlo algorithm of CORAL software is used to generate QSPR models using the hybrid optimal descriptor extracted from a combination of SMILES and HFG (hydrogen-filled graph). The whole dataset of 273 VOCs is used to make ten splits, each of which is further divided into four sets: active training, passive training, calibration, and validation. The balance of correlation method with four target functions
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.