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Milk adulteration is one of the most dishonest food preparation which not only reduces the nutritional value but also causes various diseases to human. Some of the common adulterants are detergents, ammonium sulphate ((NH4)2SO4), sodium hydroxide (NaOH), sodium-bi-carbonate (NaHCO3) and common salt (NaCl). The aim of the paper is to identify the mi...
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... block diagrams of the measurement system and the signal conditioning circuit are shown in Fig. 4 and Fig. 5. An external temperature bath controller (NSW-125 Thermostatic Water Bath) is used to keep the temperature of the milk samples constant at 42 • C. It is required for two purposes. The first one is to keep the conductivity constant at fixed temperature [32] and second is to maintain the homogeneity of the fat globules' ...
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Citations
... Some of the commonly used chemical adulterants are high protein compounds, such as whey powder, bone meal, dried egg white, soy protein, and nitrogen-based chemicals, entailing urea, ammonium sulphate, melamine, and dicyandiamide [4]. Adulterants, like detergents, sodium-bi-carbonate, sodium hydroxide, and salts are mostly reported in the developing countries [5]. Preservatives added in the milk are potassium dichromate, hydrogen peroxide, salicylic acid, and benzoic acid. ...
... Changes of the phase angle (i.e. changes in impedance) are converted into voltage signal with the proposed electronic circuit [5]. The phase angle and, so, the voltage produced, change due to alterations in the urea adulteration in milk. ...
... In previous works, urea quantification in water was carried out by modeling the EIS sensor for its electrical circuit in the LEVMW software. Another research where similar sensors were deployed for detection of fat percentage [5] classified the milk with the help of the EIS analyzer software. The EIS sensor assembly with the signal conditioning circuit is a novel contribution on the hardware side. ...
Milk is a major food constituent. However, the existing discrepancy between milk demand and supply leads to adulteration, which can be dangerous since it causes detrimental effects on health implicating lethal diseases. Although classical methods for adulteration detection are very accurate, their implementation requires skilled technicians as well as expensive and sophisticated instruments. These reasons trigger the need for improved techniques in uncovering adulteration. Urea is a natural component in milk and accounts for a substantial share of adulteration in the non-protein content of milk. The current research proposes and employs a sensor system utilizing the Electrical Impedance Spectroscopy (EIS) method to determine the presence of urea. The classification system was developed using different machine learning algorithms. Three classifiers, Extreme Gradient Boosting (XGBoost), Extreme Learning Machines (ELM), and Deep Neural Networks (DNN) were considered for various levels of urea adulteration. Milk samples were assessed by deploying the developed EIS sensor assembly and the results derived were employed in the training of the machine learning algorithms. The estimated classifiers displayed promising outcomes, involving up to 98.33% classification accuracies, outshining frequently used existing learning approaches like logistic regression.
... Furthermore, this sensor design significantly minimizes sample wastage. Traditional methodologies have typically necessitated using 50 ml or larger milk samples for measurement purposes [10], [12], [13], whereas this novel design requires only 4 ml of the milk sample. ...
... Electronic tongues and noses have been considered in food spoilage detection in combination with chemometric tools [11]. In another example, impedance sensors have been used in the detection of milk adulterants in samples with different fat content [12]. However, these instruments require trained personnel and the cost associated with fabrication and materials represents a drawback for these devices. ...
Milk is considered a complete meal that requires supervision to determine its suitability for human consumption. The development of sustainable devices that evaluate food properties has gained importance due to the necessity of integrating these instruments into the production chain. However, the materials employed to develop it, such as polymers, semiconductors, and glass, lack sustainability and require specialized equipment to fabricate them. Different chemical techniques have been used to miniaturize these detection systems such as microfluidics, which have been used in milk component detection using colorimetry. In this work, a cantilever beam paper-based microfluidic system is proposed to evaluate differences in milk, according to nutritional information, using its electromechanical response. A 20-microliter milk drop is deposited in the system, which induces hygroexpansion and deflection due to liquid transport within the paper. Likewise, a conductive path is added on the beam top surface to supply a constant current that induces heat to evaporate the solution. According to the results obtained, it is possible to point out differences between trademarks with this microfluidic system. The novelty of this system relies on the paper electromechanical response that integrates the hygroexpansion-induced displacement, which can be used for further applications such as milk microtesters instead of colorimetric tests that use paper as a property-evaluation platform in combination with chemical reactions.
... This study has elaborated the use of EIS in the detection of adulteration in honey samples, provided the detection limit (10%) be reduced. Similarly, in the case of adulterated milk, it has been observed that the impedance spectra of pure milk changes with the addition of adulterants [121]. The presence of water and hydrogen peroxide in milk was identified using EIS coupled with artificial neural network with a classification accuracy of 94.6% [116]. ...
Food safety and authenticity have become a serious concern among consumers worldwide. Economically motivated practices of food fraud can have widespread implications for public health and reduce the overall food quality. As such, there is a rapidly increasing requirement for more sensitive and accurate methods to detect deliberate adulteration of food commodities. An attempt to summarize the present status of adulterated foods, the most common adulterants used, and the non-destructive methods to detect food fraud, has been made in this review article. The techniques and modern methods of food adulteration detection including NIR, FTIR, Raman spectroscopy, NMR, e-nose/e-tongue, and LIBS have been discussed. The methods of qualitative and quantitative data analysis have a significant role in the determination of process efficiency and as such a comprehensive knowledge of the process and recent applications discussed in the review would be of high interest to solve food adulteration problems.
... We would like to pay attention again to the fact that a lossy capacitor is nothing but a frequency-dependent fractional capacitor that provides different values of orders and fractances at different frequencies. Moreover, the order and fractance of the lossy capacitive type sensor also change when the physical value of the measurand changes [3], [21], [22]. The change in these values will force the frequency of the oscillator to change. ...
... First, we study the performance of the signal conditioning circuit by integrating an emulated lossy capacitive sensor with the oscillator. And the second one is by connecting a capacitive type sensor which has been earlier used for sensing different types of physical parameters [21], [22], [26]. ...
... In this section, we show the interfacing of the oscillator with a polymer-coated lossy capacitive-type sensor which has already been used for different sensing applications [21], [22], [26]. It is made using epoxy glass sandwiched between two copper plates as shown in Fig. 9(a). ...
In this work a new type of fractional oscillator circuit is proposed employing two fractional capacitors. Based on the Barkhausen criteria, a generalized close form equation for the oscillating frequency has been derived with simple design equations. The closed form of design equation enables the circuit to be use as a signal conditioning circuit for any type of lossy capacitive sensors. Experimental results of the fractional oscillator as a signal generator as well as a signal conditioning circuit are presented. Performance as a signal conditioning circuit is studied by using an emulated lossy capacitor and with a stick type lossy capacitive type sensor.
... Sodium hydroxide, sodium carbonate, and sodium bicarbonates act as neutralizers, and their role is to balance the milk pH unethically, which should be 6.5 to 6.8 for natural milk. Many researchers like Bansal and Bansal (1997); Kaura (2005); Ahirwar et al. (2015); Das et al. (2016); and Chakraborty and Biswas (2018) have validated the above statements regarding different adulterants and their use. ...
... Analytical tools like polymerase chain reaction (PCR) and polyacrylamide gel electrophoresis (PAGE) are generally deployed to differentiate milk of various species (Azad and Ahmed 2016;Das et al. 2016;Chakraborty and Biswas 2018). A lot of adulterants are in practice for fulfilling various purposes; the next section will focus on their use, side effects, and possible detection techniques. ...
... Production of synthetic milk is even a bigger challenge than adulteration as it is very harmful to consumers. Because of non-stringent rule regulation, poor implementation of existing law, corrupt Das et al. 2011a;Chakraborty and Biswas 2018) practices, lack of awareness among producers and consumers, and most importantly greed for higher profit are responsible for the current scenario of milk adulteration. The biggest sufferer of these malpractices is the consumer who not only loses his money but also has a threat to his health. ...
Adulteration in most food products is a rising challenge and a matter of concern in front of the authorities of countries, especially the developing ones. Even though the problem with milk contamination exists in developed countries too, yet the underdeveloped nations suffer more because they do not have adequate screening and regulating infrastructure to detect point-to-point adulteration. Besides this, another big issue that boosts malpractice is the lack of awareness regarding the maintenance of food standards. Among all the food products, milk is most vulnerable to adulteration and can cause serious health issues in consumers. Adulterated milk in circulation and consumption poses a bigger threat to regulators, consumers, and the milk industry equally in the implementation of food safety standards. There are numerous detection methods and techniques available globally which are in practice to analyze and differentiate adulterated milk. However, most of them are complex, expensive, and lab-based techniques that limit their application. In this review paper, various adulterants, their health consequences, and available detection techniques have been discussed. This paper will focus on types of milk adulterants and their purposes of mixing, consequences of mixing, and different available detection techniques including methods based on electrical technologies.
... Milk is contaminated with urea 2-4 , melamine 5,6 , detergents 7 , boric acid 8 , formalin 9 , ammonium sulphate, soaps, salt, neutralisers 10 , maltodextrin 11 , starch, sugars 12 , clenbuterol 13 , tetracycline 14 , hydrogen peroxide 15 , caramel, water 16,17 , and many other harmful substances 18 . These chemicals are inexpensive and widely available. ...
Milk adulteration is a common problem in developing countries, and it can lead to fatal diseases in humans. Despite several studies to identify different adulterants in milk samples, the effects of multiple adulterants remain unexplored. In this work, a three-dimensional (3D) paper-based microfluidic device is designed and fabricated to simultaneously detect multiple chemical adulterants in milk. This device comprises a top cover, a bottom cover, and a middle layer composed of transportation and a detection zone. By making cuts on the middle layer’s support, the device’s flow path is characterised by optimum and uniform velocity. For the first time, seven adulterants (urea, detergents, soap, starch, hydrogen peroxide, sodium-hydrogen-carbonate, and salt) are detected in the milk sample simultaneously with specificity evaluation and detailed color interference analysis. Only 1–2 mL of sample volume is required to detect 7 adulterants at one time. We have used only 10 μL of the reagent’s volume for the colorimetric reaction and found the results within a few seconds. Observation reveals that the limit of detection (LOD) of the adulterants lies in the range between 0.05% (vol./vol.) to 0.2% (vol./vol.) using the colorimetric detection technique. The unknown quantity of the added adulterants is measured using the calibration curves obtained from the experiments results. The repeatability and reproducibility of the process, sensitivity, and the linear range of detection of the calibration curves and the statistical study of the color intensity data are thoroughly analysed herein. In any resource-limited setting, this simple, portable, and user-friendly 3D microfluidic device is expected to be used for testing liquid foods before consumption.
... [24] Gluti nous rice fl our To Improve the fl avour [25] Milk is reckoned as one of the foods most frequently subjected to fraud. It downgrades the overall nutriti onal quality of the milk and can cause numerous human diseases [9][10]. Vegetable protein, whey, milk from other species and water are reckoned as some of the common adulterants found in milk that do not pose serious health issues [9]. ...
... Vegetable protein, whey, milk from other species and water are reckoned as some of the common adulterants found in milk that do not pose serious health issues [9]. Meanwhile, adulterants like sodium bicarbonate, sodium hydroxide, detergents, ammonium sulfate, formalin, urea, melamine, boric acid, salicylic acid, hydrogen peroxide, and benzoic acid are reported to have a drasti c negati ve impact on human health [9][10][11]. ...
Safety and nutritional security of food and agricultural products have become a major concern and challenge in Sri Lanka. The increasing demand, coupled with shortages in food supply, leads to food safety issues and nutritional insecurity. As food quality issues like adulteration and other forms of fraudulent practices are rampant in today’s world, sound scientific approaches are required to tackle them. Deliberate or in-deliberate addition of foreign materials and removal of value-added food substitutes frequently takes place in the food supply chain. Hence, international and local regulatory control measures are required to be implemented to safeguard the quality and safety of food commodities. In this backdrop, food authentication can play a crucial role to ensure the quality and safely of food produces in compliance with the standard guidelines. Food authentication throughout the food production and supply lines would aid not only to ensure food safety among the general public but also increase the competitiveness of our local products in the international market. Further, establishing comprehensive data bases on nutritional compositions of locally available agro-food products would help to address nutritional insecurity prevailing in the Sri Lankan Society.
... On the other hand, intentional adulteration also known as food fraud or economically motivated adulteration (EMA), includes the purposeful incorporation of adulterants into food [16,17]. Some of the common EMAs added to cow milk, and their effects on health are shown in Fig. 2 [7,18]. On the same note, the dairy industry exercise different chemicals mainly; the common chemicals used as a form of adulteration are chlorine, starch, sodium carbonate, hydrated lime, ammonium sulfate, and formalin. ...
Internet of Things (IoT) and Artificial Intelligence (AI) are two of the emerging techniques used in creating more significant opportunities in smart dairy farming (SDF). Currently, the demand for milk is continuously increasing due to the world's growing population. Thus, some suppliers are inclined towards adopting fraudulent practices such as introducing adulterants into milk to eliminate the demand and supply gap. Conventional detection techniques require specific chemicals and equipment to determine the presence of adulterants in milk. Though effective, this technique has the downsides of producing qualitative results that are laborious, time-consuming and the same milk sample cannot be further analyzed for other adulterants. Hence, this paper presents an IoT-based solution to detect adulterants in milk by measuring its pH and electrical conductivity (EC) parameters. To achieve this, a fuzzy logic system was designed in MATLAB® using the Fuzzy Logic Toolbox™ and implemented on an Arduino Mega microcontroller to analyze the impurities present in milk samples through hardware implemented. This research revealed that milk's pH and EC values with no adulteration range from 6.45 to 6.67 and 4.65 mS/cm to 5.26 mS/cm, respectively. Finally, the collected data is stored in the cloud using the ThingSpeak™ web platform, interconnected with an IoT (ESP8266 Wi-Fi module).
... As such, there are very few studies reported in literature on the adulteration of dairy products. In the past decade, most of the researchers were focused on the metamaterial-based sensor for the adulteration detection of dry milk and other products [39][40][41]. A microfluidic-based sensor is another important task for liquid detection by using the microwave approach [42,43]. ...
... In [39], an electronic circuit was developed for adulterant detection in milk, which is a different method and not based on microwave techniques as in this study. Harmonic motion of a uniform density metallic rod was employed for adulterant detection in butterfat in [40]. ...
In this work, a novel, to the best of our knowledge, metamaterial-based microwave sensor is designed, numerically simulated, and experimentally tested for milk and dairy products in the frequency range of 8 to 9 GHz. The proposed structure is composed of copper split-ring resonators printed on Arlon Diclad 527 dielectric substrate. Reflection coefficient $S_{11}$ S 11 was determined by using numerical simulation, and the structure was experimentally tested to validate the sensor at the X band frequency. The material under the test was placed in the sensor layer just behind the proposed structure, and the design was optimized to sense the change in the dielectric constant via resonance frequency shifts. The proposed study was not only used for fat contents and freshness checking of milk, it was also applied to other dairy products such as cheese, ayran, and yogurt. The maximum resonance frequency shift was observed in yogurt to be 140 MHz, and the minimum frequency shift was observed in fresh and spoiled ayran to be around 40 MHz. This work provides a new approach to the current metamaterial sensor studies existing in literature by having novel material applications with new microwave metamaterial sensors.
