<?xml version="1.0" encoding="utf-8"?><urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9" xmlns:news="http://www.google.com/schemas/sitemap-news/0.9" xmlns:image="http://www.google.com/schemas/sitemap-image/1.1" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.sitemaps.org/schemas/sitemap/0.9 http://www.sitemaps.org/schemas/sitemap/0.9/sitemap.xsd http://www.google.com/schemas/sitemap-news/0.9 http://www.google.com/schemas/sitemap-news/0.9/sitemap-news.xsd"><url><loc>https://www.perfumerflavorist.com/flavor/regulatory-research/news/22978410/machine-learning-accelerates-discovery-of-flavor-compounds-that-trigger-pungency-and-irritation</loc><news:news><news:publication><news:name>Perfumer & Flavorist</news:name><news:language>en</news:language></news:publication><news:publication_date>2026-11-13T14:32:49.000Z</news:publication_date><news:title>Machine Learning Accelerates Discovery of Flavor Compounds That Trigger Pungency and Irritation</news:title></news:news><image:image><image:loc>https://img.perfumerflavorist.com/mindful/allured/workspaces/default/uploads/2026/11/pexels-cottonbro-8955954.53AZUSGE9i.jpg?auto=format%252Ccompress&amp;q=70</image:loc><image:caption>For flavor developers, the integrated approach offers a potential pathway to screen chemesthetic ingredients more efficiently while better understanding the molecular mechanisms behind their sensory effects. Such insights could support more targeted exploration of pungency, irritation and other mouthfeel-related sensations, helping researchers connect molecular structure with sensory performance.</image:caption></image:image></url></urlset>