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	<title>TVB-N &#8211; Science</title>
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	<title>TVB-N &#8211; Science</title>
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		<title>Red Cabbage Aerogel Labels Turn Color to Reveal When Chicken Goes Bad</title>
		<link>https://scienmag.com/red-cabbage-aerogel-labels-turn-color-to-reveal-when-chicken-goes-bad/</link>
		
		<dc:creator><![CDATA[Bethany Barker]]></dc:creator>
		<pubDate>Tue, 13 Oct 2026 17:54:01 +0000</pubDate>
				<category><![CDATA[Chemistry]]></category>
		<category><![CDATA[aerogel]]></category>
		<category><![CDATA[aerogel-based freshness markers]]></category>
		<category><![CDATA[anthocyanins]]></category>
		<category><![CDATA[biodegradable food freshness sensors]]></category>
		<category><![CDATA[chicken meat freshness]]></category>
		<category><![CDATA[colorimetric indicator]]></category>
		<category><![CDATA[edible plant-based food packaging indicators]]></category>
		<category><![CDATA[food spoilage]]></category>
		<category><![CDATA[food spoilage detection]]></category>
		<category><![CDATA[freeze-drying]]></category>
		<category><![CDATA[halochromic sensor]]></category>
		<category><![CDATA[intelligent packaging]]></category>
		<category><![CDATA[lightweight porous aerogel materials]]></category>
		<category><![CDATA[microbial and chemical spoilage monitoring]]></category>
		<category><![CDATA[natural food dye replacement]]></category>
		<category><![CDATA[pectin]]></category>
		<category><![CDATA[pectin-based food freshness labels]]></category>
		<category><![CDATA[pH-sensitive pigments in food safety]]></category>
		<category><![CDATA[real-time meat freshness indicators]]></category>
		<category><![CDATA[red cabbage anthocyanin color-changing sensors]]></category>
		<category><![CDATA[red cabbage extract]]></category>
		<category><![CDATA[smart food packaging technologies]]></category>
		<category><![CDATA[total viable count]]></category>
		<category><![CDATA[TVB-N]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=268575</guid>

					<description><![CDATA[Researchers have created a pectin aerogel loaded with red cabbage anthocyanins that changes from purple to green as chicken spoils, with the most porous formulation tracking bacterial counts and volatile nitrogen more reliably than denser versions.]]></description>
										<content:encoded><![CDATA[<p>A small label made from red cabbage and apple pectin could soon tell shoppers and retailers whether the chicken in a sealed pack is still fresh, without opening the container, scanning a chip, or running a single laboratory test. Researchers at Bu-Ali Sina University in Hamedan, Iran, have developed a lightweight, highly porous aerogel indicator that changes color as meat spoils, and their results, published in Food Chemistry: X, show that the simplest formulation tracked microbial and chemical spoilage more faithfully than denser versions of the same material. The work sits at the intersection of two growing trends: the push to replace synthetic dyes in food packaging with edible, plant-derived pigments, and the search for solid support matrices that make those pigments respond faster and more dramatically to the gases that spoilage releases.</p>
<p>The logic behind the indicator rests on the peculiar chemistry of anthocyanins, the water-soluble pigments that give red cabbage its deep color. Anthocyanins are molecular chameleons: their structure, and therefore their color, shifts with the acidity of their surroundings. In acidic conditions the pigment exists mainly as a flavylium cation, producing a rose-red hue. As pH rises toward neutral, the molecule equilibrates among several forms, including the quinoidal base and carbinol pseudo base. Above pH 7, deprotonation generates quinoidal structures with extended conjugation that shift absorbed light toward longer wavelengths, and under strongly alkaline conditions the pyran ring cleaves and rearranges into yellow chalcones. The team confirmed this behavior spectroscopically, measuring the total anthocyanin content of their dried cabbage powder at 18.90 milligrams of cyanidin-3-glucoside equivalents per gram of dry matter, and observing the absorption maximum of their extract drift from roughly 500 nanometers under acidic conditions to 600 nanometers as pH climbed from 3 to 12.</p>
<p>Red cabbage is an attractive pigment source because it is cheap, edible, and richer in anthocyanins than many alternative plants, which matters when the indicator will sit inside a food package where dye migration is a safety concern. Synthetic pH dyes can volatilize or leach into food matrices, so natural colorants have become the preferred option for intelligent packaging. But a pigment alone is not enough; it needs a physical platform that exposes it to the air inside the package while holding it in place. The Iranian team chose pectin, the plant polysaccharide best known for setting jam, as that platform. Pectin is built from alpha-1,4-linked D-galacturonic acid units, and its degree of esterification governs how it gels and holds water, allowing it to form the layered macroporous structures needed for aerogel fabrication.</p>
<p>Aerogels are among the lightest solid materials known, produced by replacing the liquid in a gel with gas while preserving the three-dimensional polymer network. To make theirs, the researchers dissolved apple pectin at concentrations of 10, 15, and 20 percent weight per volume, mixed in a diluted red cabbage extract, cast the solutions into molds, froze them in liquid nitrogen, and freeze-dried them at minus 80 degrees Celsius for 48 hours. The resulting indicators were extraordinarily porous: bulk densities ranged from 0.074 to 0.139 grams per cubic centimeter, with porosity between 90 and 95 percent. That internal free volume is the point. A highly porous network adsorbs and retains volatile spoilage gases efficiently, accumulating them near the embedded anthocyanins and amplifying the color response.</p>
<p>The formulation details turned out to matter enormously. Increasing the pectin concentration produced a denser, more cross-linked network: porosity fell, moisture absorption dropped from 16.1 percent to 7.9 percent, and the aerogels became harder, more cohesive, and less springy in texture analysis. Adding the red cabbage extract reinforced this trend, because hydrogen bonding between anthocyanin molecules and pectin chains packed the polymer network more tightly. Fourier-transform infrared spectroscopy revealed the signature of these interactions: the hydroxyl stretching band broadened and shifted to lower wavenumbers in loaded aerogels, while a band near 1623 per centimeter, assigned to the aromatic carbon-carbon skeletons of anthocyanin rings, grew in intensity, confirming that the pigment was genuinely integrated into the matrix rather than merely sitting on its surface. X-ray diffraction showed increased crystallinity in the loaded samples, consistent with closer molecular packing.</p>
<p>When the team exposed the loaded aerogels to ammonia vapor, a stand-in for the volatile bases that escaping from spoiling meat, the materials shifted from red to purple in a time-dependent manner. After 30 minutes of exposure, the 10 percent pectin formulation registered the largest total color difference, a delta E of 27.79, compared with 24.20 for the 15 percent version and 19.95 for the 20 percent version. The explanation is straightforward physics: the denser networks at higher pectin concentrations restricted ammonia diffusion and slowed the anthocyanins&#8217; structural transformation. The 10 percent aerogel, with its lower polymer density, higher porosity, and greater anthocyanin accessibility relative to its pectin content, let the gas reach the pigment fastest and most completely.</p>
<p>The real test came with actual chicken. The researchers sealed 40-gram skinless chicken samples in oriented polypropylene containers, attached the aerogel labels to the inner upper surface without direct meat contact, and stored everything at 4 degrees Celsius for 12 days, measuring pH, total volatile basic nitrogen, lipid oxidation, bacterial counts, and sensory qualities along the way. The meat started fresh, with 3.76 log colony-forming units per gram of total viable count, a pH of 5.25, and TVB-N of 9.6 milligrams of nitrogen per 100 grams. By day 8, those values had reached 7.01 log CFU per gram, 6.577, and 25.61 milligrams per 100 grams respectively, crossing the accepted spoilage thresholds for raw chicken fillets, while odor scores from trained panelists collapsed to the minimum of the hedonic scale.</p>
<p>The labels told the same story in color. The 10 percent pectin indicator transitioned from purple on day 0 to purplish-blue by day 6, marking semi-fresh meat, and turned green during days 8 through 12, signaling advanced spoilage. The 15 and 20 percent formulations lagged, turning purplish-blue on day 8 and green only during days 10 through 12. Critically, the team went beyond visual impressions and ran statistical analyses to determine whether the measured color change could serve as an objective spoilage metric. After controlling for storage time, only the 10 percent pectin aerogel showed significant partial correlations between its delta E values and the key spoilage indicators, total viable count and TVB-N, as well as sensory attributes including color, texture, and overall acceptability. Receiver operating characteristic analysis then established delta E cut-off values of 25.8, 16.9, and 11.1 for the 10, 15, and 20 percent formulations against the microbiological and chemical spoilage thresholds.</p>
<p>Those numbers carry practical weight. A delta E above 5 is generally considered the threshold at which a color change becomes visible to the naked eye, so a cut-off of 25.8 for the best formulation means the label&#8217;s color shift is not subtle; it is unmistakable. Because the indicator works passively, responding to the ammonia and other alkaline nitrogenous compounds that protein-degrading bacteria release into the package headspace, it requires no electronics, no reader device, and no cold-chain data infrastructure. A consumer, an inspector, or a warehouse camera could in principle read it. The researchers note that the anthocyanin-to-pectin ratio directly controls both the magnitude of the color response and the delta E threshold at which spoilage is flagged, which suggests the technology can be tuned for different foods and spoilage chemistries.</p>
<p>The study also contributes a useful design principle for the broader field of halochromic food sensors: the support matrix is not a passive carrier but an active determinant of sensitivity. Three-dimensional porous networks enhance sensing performance, but only up to the point where the matrix remains open enough for gases to diffuse. Too much polymer, and the indicator goes blind; too little, and the structure may lack the mechanical integrity to survive handling. The pectin aerogels&#8217; combination of low density, high porosity, and anthocyanin-stabilized mechanical strength appears to hit a workable balance, and the fact that every component, from the cabbage pigment to the fruit-derived polysaccharide, is food-safe removes the migration concerns that have limited synthetic dye indicators. Whether such labels can be manufactured at scale, and whether their response holds up under the temperature fluctuations of real supply chains, remain questions for future work, but the demonstration that a simple, edible aerogel can quantitatively track chicken spoilage in real time marks a concrete step toward packaging that speaks for the food it protects.</p>
<p><strong>Subject of Research:</strong> Pectin aerogel colorimetric indicators with red cabbage anthocyanins for real-time monitoring of chicken meat freshness</p>
<p><strong>Article Title:</strong> Evaluation of intelligent aerogel indicators composed of red cabbage extract and pectin for monitoring chicken meat freshness</p>
<p><strong>Article References:</strong> Shirkhani, H., Emamifar, A., &amp; Davati, N. (2026). Evaluation of intelligent aerogel indicators composed of red cabbage extract and pectin for monitoring chicken meat freshness. <em>Food Chemistry: X</em>, Article 104615. <a href="https://doi.org/10.1016/j.fochx.2026.104615" rel="noopener noreferrer">https://doi.org/10.1016/j.fochx.2026.104615</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1016/j.fochx.2026.104615" rel="noopener noreferrer">10.1016/j.fochx.2026.104615</a></p>
<p><strong>Keywords:</strong> intelligent packaging, aerogel, anthocyanins, red cabbage extract, pectin, chicken meat freshness, colorimetric indicator, food spoilage, TVB-N, total viable count, freeze-drying, halochromic sensor</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">268575</post-id>	</item>
		<item>
		<title>Color-Changing Tag Paired With AI Spots Spoiled Seafood in Hours</title>
		<link>https://scienmag.com/color-changing-tag-paired-with-ai-spots-spoiled-seafood-in-hours/</link>
		
		<dc:creator><![CDATA[Alan Morgan]]></dc:creator>
		<pubDate>Sat, 12 Sep 2026 16:08:33 +0000</pubDate>
				<category><![CDATA[Agriculture]]></category>
		<category><![CDATA[aggregation-induced emission]]></category>
		<category><![CDATA[AI and sensor technology for food safety]]></category>
		<category><![CDATA[AI-powered seafood spoilage testing]]></category>
		<category><![CDATA[ammonia detection]]></category>
		<category><![CDATA[color-changing freshness indicator for seafood]]></category>
		<category><![CDATA[convolutional neural network]]></category>
		<category><![CDATA[convolutional neural networks in food quality assessment]]></category>
		<category><![CDATA[fluorescein isothiocyanate]]></category>
		<category><![CDATA[innovative seafood preservation monitoring tools]]></category>
		<category><![CDATA[non-destructive seafood freshness monitoring]]></category>
		<category><![CDATA[rapid low-cost seafood spoilage detection]]></category>
		<category><![CDATA[ratiometric fluorescent tag]]></category>
		<category><![CDATA[ratiometric fluorescent tags for food safety]]></category>
		<category><![CDATA[real-time seafood freshness assessment]]></category>
		<category><![CDATA[refrigerated storage]]></category>
		<category><![CDATA[ResNet-34]]></category>
		<category><![CDATA[seafood freshness]]></category>
		<category><![CDATA[seafood freshness detection]]></category>
		<category><![CDATA[seafood spoilage detection using AI and fluorescence]]></category>
		<category><![CDATA[silver-copper nanoclusters]]></category>
		<category><![CDATA[smartphone sensing]]></category>
		<category><![CDATA[TVB-N]]></category>
		<category><![CDATA[volatile amines]]></category>
		<category><![CDATA[volatile amines sensing in seafood]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=196139</guid>

					<description><![CDATA[Researchers have created a color-changing fluorescent tag combined with a convolutional neural network that classifies seafood freshness with over 98 percent accuracy at refrigerated temperatures.]]></description>
										<content:encoded><![CDATA[<p>A small piece of paper that changes color as fish and shrimp decay, read by an artificial intelligence that is right more than 98 percent of the time, could soon change how consumers and retailers know when seafood is safe to eat. Researchers in China have developed a ratiometric fluorescent tag that responds to the volatile amines released by spoiling seafood, and they have paired it with a convolutional neural network that removes the guesswork from interpreting what the naked eye sees. The work, published in Current Research in Food Science, demonstrates a rapid, low-cost, and non-destructive approach to freshness monitoring that works at ordinary refrigeration temperatures, where most seafood is actually stored and sold.</p>
<p>The problem the researchers set out to solve is a familiar one. Seafood is densely packed with nutrients, and even when it is chilled or frozen, endogenous enzymes and microorganisms gradually break down proteins and other compounds, releasing volatile amines such as ammonia and biogenic amines. These gases are the key contributors to total volatile basic nitrogen, or TVB-N, the gold-standard chemical indicator of seafood freshness. Conventional laboratory methods for measuring TVB-N, including chemical-microbiological assays, chromatography, mass spectrometry, and spectroscopy, are accurate but slow, destructive to the sample, and dependent on expensive instrumentation and skilled technicians. They cannot tell a shopper whether the shrimp in the display case is fresh, and they cannot track freshness continuously inside a sealed package.</p>
<p>Fluorescent sensing tags have emerged as a promising alternative because they can be placed inside packaging and photographed with a smartphone. Early versions, however, relied on a single fluorescence signal that switched on or off, which made them vulnerable to environmental interference and difficult to judge by eye. The field responded with ratiometric probes, which carry two well-resolved emission bands so that one signal serves as an internal reference for the other. But many dual-emission probes built from dyes or quantum dots suffer from aggregation-caused quenching, in which the fluorescent signal collapses when the molecules cluster together on a solid surface. Aggregation-induced emission, or AIE, flips that behavior, glowing brighter when aggregated, and it has become a favored design principle for solid-state sensors.</p>
<p>The team, led by Wenyang Zhang with co-authors You Tian, Yanwu Chen, and Min Wei, built their tag around a relatively unexplored class of AIE materials: bimetallic nanoclusters. Using a microwave-assisted synthesis run at 90 degrees Celsius for just 150 seconds, they prepared silver-copper nanoclusters capped with D-penicillamine, abbreviated DPA-AgCuNCs. Transmission electron microscopy showed dense aggregates of particles averaging about 3 nanometers in diameter, and energy-dispersive X-ray mapping confirmed a homogeneous distribution of silver, copper, sulfur, carbon, and nitrogen. Spectroscopic characterization revealed a strong orange emission at 585 nanometers when excited at 360 nanometers, a large Stokes shift of 225 nanometers, and a long photoluminescence lifetime of about 4 microseconds, all hallmarks of a ligand-to-metal charge transfer from the sulfur atom of the capping ligand to the metal core.</p>
<p>Exposure to ammonia vapor quenched the nanocluster fluorescence in a linear fashion across concentrations from 10 to 120 parts per million, with a detection limit of 2.95 parts per million. Mechanistic experiments showed that the quenching is a synergistic combination of static and dynamic pathways. Ultraviolet-visible spectroscopy revealed two new absorption bands after ammonia exposure, evidence of a non-fluorescent ground-state complex, while fluorescence lifetime measurements showed the average lifetime plummeting from 4.023 microseconds to 3.27 nanoseconds, a signature of dynamic quenching. X-ray photoelectron spectroscopy showed the nitrogen content of the material rising after exposure and shifts in the copper oxidation-state features, and electron microscopy captured the physical disaggregation of the nanocluster aggregates. The researchers attribute the dominant pathway to static quenching through formation of an ammonia-coordinated copper-silver complex.</p>
<p>To convert this single-signal quenching into a visually readable ratiometric response, the team combined the orange-emitting nanoclusters with fluorescein isothiocyanate, or FITC, a dye that behaves in the opposite way. In the presence of the alkaline environment created by ammonia, the lactone ring of FITC opens to its carboxylate form and its green fluorescence at 510 nanometers brightens. Drop-casting the two probes together onto circular cellulose fiber paper produced a tag that glows orange-yellow under 365 nanometer ultraviolet light but shifts progressively toward green as amine concentrations rise. Scanning electron microscopy confirmed that both components, sheet-like FITC aggregates and petal-shaped nanocluster particles, coexisted on the paper fibers. After optimizing the volume ratio of nanoclusters to FITC at 4 to 0.5, the tag displayed a clean, graduated orange-to-yellow-to-green progression.</p>
<p>The practical test came with fresh sand shrimp stored at 4 degrees Celsius, with a tag affixed inside the lid of a sealed Petri dish where it never touched the sample. Independent measurements of TVB-N and total viable counts classified the shrimp as fresh at days zero to one, less fresh at days two to three, and spoiled at day four. The tag&#8217;s color changes tracked these grades precisely: bright orange when fresh, pale yellow when declining, and distinctly green when spoiled. Based on this behavior, the team built a fluorescence color card allowing anyone to grade freshness at a glance. The tag also proved rugged, retaining 94.47 percent of its initial fluorescence after 30 days at 4 degrees Celsius, more than 91 percent after a month across relative humidities from roughly 33 to 90 percent, and 95.47 percent after five days of continuous ultraviolet exposure.</p>
<p>Visual color cards, however, remain hostage to human subjectivity, since individual differences in color perception can produce inconsistent judgments. To eliminate that variability, the researchers trained five convolutional neural network architectures on a dataset of 1,842 labeled fluorescence images spanning the three freshness categories, augmented with flipping, rotation, scaling, cropping, translation, and Gaussian noise. ResNet-34 decisively outperformed the alternatives, achieving 98.39 percent accuracy, 98.48 percent precision, 98.41 percent recall, a 98.41 percent F1-score, and an area under the receiver operating characteristic curve of 99.02 percent on held-out data. VGGNet-16 and DenseNet managed only about 75 to 76 percent accuracy, GoogLeNet 53 percent, and AlexNet a dismal 36 percent. Stratified five-fold cross-validation confirmed ResNet-34&#8217;s robustness, with accuracy of 96.81 plus or minus 0.92 percent across folds, and on an independent test set of 122 unseen images the model achieved perfect precision for fresh and spoiled samples and 95.24 percent for the intermediate category.</p>
<p>The optimized network was then packaged into a proof-of-concept smartphone application called FreshSense, in which a user photographs the illuminated tag and the app displays an automatic freshness prediction, with inference currently handled on a remote server. The system generalized well beyond shrimp: applied to salmon, cod, and grass carp stored at 4 degrees Celsius, it achieved classification accuracies of 93.52, 90.74, and 92.59 percent, respectively, showing that the sensing chemistry is not tied to a single species. The authors note that future work will target model compression and on-device deployment so the tool can function fully offline, along with systematic evaluation of computational costs. Selectivity testing against thirteen volatile substances produced during spoilage, including methanol, hydrogen sulfide, formaldehyde, and acetic acid, showed strong responses only to ammonia, trimethylamine, putrescine, and a mixed-gas cocktail, precisely the compounds that matter for spoilage, suggesting the platform could become a practical, intelligent fixture in cold chains, retail displays, and eventually home refrigerators.</p>
<p><strong>Subject of Research:</strong> A CNN-integrated ratiometric fluorescent nanocluster tag for rapid seafood freshness monitoring at refrigerated temperatures</p>
<p><strong>Article Title:</strong> CNN-integrated ratiometric fluorescent tag for rapid monitoring of seafood freshness at refrigerated temperatures</p>
<p><strong>Article References:</strong> Zhang, W., Tian, Y., Chen, Y., &amp; Wei, M. (2026). CNN-integrated ratiometric fluorescent tag for rapid monitoring of seafood freshness at refrigerated temperatures. <em>Current Research in Food Science, 13</em>, Article 101560. <a href="https://doi.org/10.1016/j.crfs.2026.101560" rel="noopener noreferrer">https://doi.org/10.1016/j.crfs.2026.101560</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1016/j.crfs.2026.101560" rel="noopener noreferrer">10.1016/j.crfs.2026.101560</a></p>
<p><strong>Keywords:</strong> seafood freshness, ratiometric fluorescent tag, aggregation-induced emission, silver-copper nanoclusters, volatile amines, ammonia detection, convolutional neural network, ResNet-34, fluorescein isothiocyanate, TVB-N, smartphone sensing, refrigerated storage</p>
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