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<ArticleSet>
<Article>
<Journal>
				<PublisherName>Iranian Research Organization for Science and Technology (IROST)</PublisherName>
				<JournalTitle>Innovative Food Technologies</JournalTitle>
				<Issn>2783-350X</Issn>
				<Volume>12</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2025</Year>
					<Month>07</Month>
					<Day>23</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Design and Fabrication of a Novel Electronic Sensor for Detecting Spoilage in Milk</ArticleTitle>
<VernacularTitle>Design and Fabrication of a Novel Electronic Sensor for Detecting Spoilage in Milk</VernacularTitle>
			<FirstPage>353</FirstPage>
			<LastPage>372</LastPage>
			<ELocationID EIdType="pii">1563</ELocationID>
			
<ELocationID EIdType="doi">10.22104/ift.2025.7689.2220</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Ali</FirstName>
					<LastName>Khoshchehre</LastName>
<Affiliation>Department of Electrical Engineering, Kermanshah University of Technology, Kermanshah</Affiliation>

</Author>
<Author>
					<FirstName>MohammadAmir</FirstName>
					<LastName>Sattari</LastName>
<Affiliation>Department of Electrical Engineering, Kermanshah University of Technology,</Affiliation>

</Author>
<Author>
					<FirstName>Omar Hamed</FirstName>
					<LastName>Shah</LastName>
<Affiliation>Department of Mechanical Engineering and Artificial Intelligence Research Center, Ajman University, Ajman, United Arab Emirates</Affiliation>

</Author>
<Author>
					<FirstName>Gholamhossein</FirstName>
					<LastName>Roshani</LastName>
<Affiliation>Department of Electrical Engineering, Kermanshah University of Technology,</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2025</Year>
					<Month>06</Month>
					<Day>11</Day>
				</PubDate>
			</History>
		<Abstract>Evaluating the quality and safety of milk, a vital component of human nutrition, is of paramount importance. Traditional methods for assessing milk quality, primarily based on chemical tests, are reliable but suffer from high costs, time-consuming processes, and the need for sample destruction. In contrast, microwave sensing technology, particularly using microstrip sensors, offers a novel, cost-effective, non-destructive, and real-time approach. These sensors detect quality changes, including spoilage, by analyzing frequency response variations driven by the material&#039;s dielectric properties. This study aimed to design, fabricate, and evaluate a novel microstrip sensor for detecting milk spoilage trends using microwave signals. A microstrip sensor with two passband regions was designed in ADS software and fabricated. Ten commercial milk samples, prepared under identical conditions, were collected over ten consecutive days and stored at a controlled temperature (21°C). The scattering parameter (S21) for each 180 ml sample was measured using a vector network analyzer (VNA). Results showed significant S21 changes in the first passband (1807–2466 MHz) as samples aged. The highest sensitivity was observed at 2166 MHz, with a 7.02 dB amplitude difference between the freshest and most spoiled samples, approximately 105 times the standard deviation (0.067 dB), indicating high resolution and statistical significance. Other frequencies, such as 1807 MHz, showed similar reliable trends. The proposed microstrip sensor is an efficient, accurate, and rapid tool for non-destructive, real-time milk spoilage monitoring, serving as a viable alternative to costly and time-consuming laboratory methods in the food industry.</Abstract>
			<OtherAbstract Language="FA">Evaluating the quality and safety of milk, a vital component of human nutrition, is of paramount importance. Traditional methods for assessing milk quality, primarily based on chemical tests, are reliable but suffer from high costs, time-consuming processes, and the need for sample destruction. In contrast, microwave sensing technology, particularly using microstrip sensors, offers a novel, cost-effective, non-destructive, and real-time approach. These sensors detect quality changes, including spoilage, by analyzing frequency response variations driven by the material&#039;s dielectric properties. This study aimed to design, fabricate, and evaluate a novel microstrip sensor for detecting milk spoilage trends using microwave signals. A microstrip sensor with two passband regions was designed in ADS software and fabricated. Ten commercial milk samples, prepared under identical conditions, were collected over ten consecutive days and stored at a controlled temperature (21°C). The scattering parameter (S21) for each 180 ml sample was measured using a vector network analyzer (VNA). Results showed significant S21 changes in the first passband (1807–2466 MHz) as samples aged. The highest sensitivity was observed at 2166 MHz, with a 7.02 dB amplitude difference between the freshest and most spoiled samples, approximately 105 times the standard deviation (0.067 dB), indicating high resolution and statistical significance. Other frequencies, such as 1807 MHz, showed similar reliable trends. The proposed microstrip sensor is an efficient, accurate, and rapid tool for non-destructive, real-time milk spoilage monitoring, serving as a viable alternative to costly and time-consuming laboratory methods in the food industry.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Microstrip sensor</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">milk spoilage</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">microwave sensing</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">milk quality</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">S21 parameter</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">electromagnetic waves</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jift.irost.ir/article_1563_994d9ac9d2ff0c268b810bf49753757b.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
