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	<title>adulteration detection &#8211; BIOENGINEER.ORG</title>
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		<title>Thermal Fingerprints: How DSC and TGA Are Exposing Food Fraud</title>
		<link>https://bioengineer.org/thermal-fingerprints-how-dsc-and-tga-are-exposing-food-fraud/</link>
		
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		<pubDate>Thu, 08 Oct 2026 02:30:33 +0000</pubDate>
				<category><![CDATA[Chemistry]]></category>
		<category><![CDATA[adulteration detection]]></category>
		<category><![CDATA[chemometrics]]></category>
		<category><![CDATA[differential scanning calorimetry]]></category>
		<category><![CDATA[food authentication]]></category>
		<category><![CDATA[food fraud]]></category>
		<category><![CDATA[glass transition]]></category>
		<category><![CDATA[honey]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[olive oil]]></category>
		<category><![CDATA[oxidative stability]]></category>
		<category><![CDATA[thermal analysis]]></category>
		<category><![CDATA[thermogravimetric analysis]]></category>
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					<description><![CDATA[A new review in Food Chemistry: X shows that differential scanning calorimetry and thermogravimetric analysis, boosted by chemometrics and artificial intelligence, are becoming fast, green, and powerful tools for detecting food adulteration in oils, honey, dairy, meat, and coffee.]]></description>
		
		
		
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