Among the various dairy products, cheese is extensively utilized for domestic and commercial purposes. To ensure the quality of manufactured cheese, every aspect of the final product, such as the texture, aroma, and taste, is analyzed. Alongside this, manufacturing occurs under strictly monitored conditions. Incorporating sensors ensures that the final product is manufactured following food regulations and is completely safe for human consumption.
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Evaluation of Cheese Aroma Using Sensors
The distinctive aroma of cheese contains over 600 different volatile compounds, which greatly influence taste preference. One effective method for assessing this aroma involves using an electronic nose (e-nose).
Typically, an e-nose consists of a sensor or an array of sensors, which are made of materials like metal oxide semiconductors and polymers. These sensors respond to volatile compounds. Additionally, in certain instances, an e-nose may incorporate a means of component analysis through gas chromatography (GC).
A sensory evaluation of six different types of cheese was performed by the researchers in a recent study published in Sensors. The values and scores for cheese aroma were compared to understand the connection between the e-nose sensor readings and the aroma strength. Five processed cheese samples (A, B, C, E, F), along with one natural cheese type (D), were chosen by the research group.
The evaluation was judged on five key factors: the aroma intensity before consumption while chewing and after swallowing, the taste intensity while chewing, and the enduring flavor.
Natural cheese (D) typically scored lower than other cheeses in all aspects, while blue cheese types (E) and (F) tended to score higher. However, for blue cheese type (F), the aroma intensity before consumption was the same as the other three processed cheese types (A–C).
Regarding the e-nose values, the mean values were determined by assessing three samples of each cheese. Blue cheese type (E) exhibited the highest value, followed by the regular type (B), blue cheese type (F), regular type (A), aged cheese type (C), and natural cheese (D).
Notably, there was a linear correlation between the mean e-nose values and the median scores for aroma intensity during chewing in sensory evaluations. This suggests that e-nose values could be valuable in predicting cheese aroma intensity during the mastication process.
Using Immuno-Sensors for Ensuring Cheese Quality
It is critical to ensure the authenticity of cheese to protect consumers, especially those who refrain from consuming cow's milk for reasons such as allergies or religious/cultural beliefs. Conventional approaches for assessing cheese quality and contents are time-consuming and labor-intensive and often require costly equipment.
Immuno-sensors are an effective choice for detecting cheese adulteration, as per the article published in Analyst. Label-free immuno-sensors are well-suited for real-time and on-site analysis, as they offer direct signal transmission and enable high-throughput screening.
The research group introduced a label-free optical immuno-sensor for the swift and precise detection of adulteration in two cheeses: Mozzarella di Bufala Campana and Greek feta with bovine milk.
The photonic immuno-sensor utilized in the study employed a Mach–Zehnder interferometer that was monolithically integrated on a silicon chip, along with their respective light sources.
The results of the experimentation revealed that the immuno-sensor is capable of detecting the bovine cheese in both of the cheese samples. The limits for quantifying the cheese in mozzarella or feta were 0.5% and 0.25% (w/w), respectively. Additionally, the sensor also offered a viable linear dynamic range, up to 50% (w/w) for mozzarella and 25% (w/w) for feta.
These quantification parameters are well within the necessary detection limits and allowable content of bovine milk as specified by The European Union manufacturing regulations. The results ensured that the immuno-sensor is capable of commercial applications and can efficiently detect adulteration within the cheese manufacturing industry.
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Near Infrared Sensor: An Important Tool for Cheese Quality
Near-infrared spectroscopy, abbreviated as NIR spectroscopy, is a valuable tool for quality control and process monitoring in producing various cheese types. NIR sensors in cheese manufacturing pass light through a cheese product to measure the extent of light absorption at different wavelengths. It allows for detecting diverse food properties, including fat, water, protein, and others.
Recently, Tine Meieriet Jæren, a leader in Norway’s cheese industry, incorporated NIR sensors into the cheese production line. Instead of the conventional spot checks of a few samples, the NIR sensor analyzes each sample and collects a vast amount of data relating to cheese quality.
The main goal here is to utilize measurements for observing and comprehending the impact of various manufacturing factors and raw materials on their quality to ensure a better quality product.
Subsequently, the results obtained through NIR measurements are integrated into the control system to facilitate automatic adjustments in the production process based on milk quality.
Benefits of Microwave Sensors in Assessing Cheese Quality
In cheese manufacturing, the accurate measurement of moisture and temperature is essential to maintain quality standards. The amount of water in cheese significantly impacts its quality, processing, and shelf life.
For precise moisture measurements in mozzarella, cheese makers can utilize microwave resonator-based sensors. These RF sensors help control bacterial growth, ensuring top-notch product quality.
Advanced microwave-based sensors are famous because of some essential qualities that make them suitable for measuring cheese moisture. Notably, these sensors offer accurate measurements in small areas, detecting moisture levels in products within a range as short as 2-3 cm. Furthermore, these sensors are easily integrated into the production line to ensure rapid processing.
The use of sensors ensures that cheese manufacturers can continuously measure various essential parameters during all the stages of production. In recent times, Machine learning (ML) based algorithms are being integrated into modern sensors to ensure rapid data analysis to provide insights into detecting shortcomings in the manufacturing assembly. These innovations ensure that the quality of cheese remains unhindered.
References and Further Reading
Haegermark, W., (2023). This sensor is going to make sure that the cheese you buy always tastes the same. [Online]. Available at: https://partner.sciencenorway.no/biochemistry-biotechnology-food-quality/this-sensor-is-going-to-make-sure-that-the-cheese-you-buy-always-tastes-the-same/2159761
Roemhild, H., (2021). Using Microwave Sensors to Measure Residual Moisture in Mozzarella. [Online]. Available at: https://work-microwave.com/using-microwave-sensors-measure-moisture-levels-mozzarella-cheese/
Fujioka, K. (2021). Comparison of Cheese Aroma Intensity Measured Using an Electronic Nose (E-Nose) Non-Destructively with the Aroma Intensity Scores of a Sensory Evaluation: A Pilot Study. Sensors, 21(24), p. 8368. doi.org/10.3390/s21248368
Angelopoulou, M. et. al. (2021). Rapid detection of mozzarella and feta cheese adulteration with cow milk through a silicon photonic immunosensor. Analyst, 146(2), pp. 529-537. doi.org/10.1039/D0AN01706
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