Application of electronic nose with chemometrics methods to the detection of juices fraud

Abstract

Prevention of food adulteration has been a controversial topic in the last decade, and various intervention systems have been developed to prevent counterfeit products from entering the supply chain.Therefore, reliable analytical tools are needed to validate food products (Spink et al., 2017).Consumers and the beverage industries have considered monitoring the quality and freshness of fruit juices. Receiving significant attention from the consumers due to the nutritional and sensory properties. Quality has become an important issue as consumers gain more awareness of all aspects related to food quality. The customers' decision to select fruit juices depends on their personal preferences (Haddi et al., 2014). Fruit juice that has lost its fiber and nutrients is actually a concentrated source of sugar that lacks most of the supplementary nutrients required to facilitate digestion and metabolism. Fruit juice increases blood sugar faster than the whole fruit, and the level of sugar obtained from fruit juice is significantly higher. It is important to note that most fruit juices sold in supermarkets contain only a small percentage of natural fruit juice and usually include added sweeteners. As a result, these juices lead to the intake of large amounts of calories without providing nutrients for the body.Preparing natural homemade juice can almost completely preserve the pulp and skin, so it is useful for human health (Jaffe & Mani, 2018).Extensive research has recently focused on the development of non-destructive methods to assess fruit quality properties. In fact,

Identification of olfactory characteristics of edible oil during storage period using metal oxide semiconductor sensor signals and ANN methods

“…The results of the AOCS methods confirm the initial classification obtained in the score plot. Rasekh and Karami (2021a) reported similar results for predicting fruit fraud.…”

A Machine Learning Method for Classification and Identification of Potato Cultivars Based on the Reaction of MOS Type Sensor-Array

“…Rasekh and Karami [ 26 , 27 ] reported similar results for predicting fruit juice fraud. In addition, the results obtained in this study were far higher than the values reported by Ayari et al [ 38 ] for the detection of oxidation in animal and herbal oils.…”

“…Additionally, 9 Metal Oxide Semiconductor (MOS) sensors with low power consumption are used in this apparatus. The sensor specifications are listed in Table 2 [ 22 , 26 , 27 ].…”

“…Additionally, 9 Metal Oxide Semiconductor (MOS) sensors with low power consumption are used in this apparatus. The sensor specifications are listed in Table 2 [22,26,27]. The first 2-4 potatoes from each cultivar were placed in the sample container (Figure 1b) for 1 day to saturate the container with the odor.…”

E-nose coupled with an artificial neural network to detection of fraud in pure and industrial fruit juices

“…As shown in Table 1, the designed electronic nose system used a combination of 9 metal oxide semiconductor sensors with MQ and TGS trademarks . [14] Table 1. The used sensors in electronic nose The computer stored the output signal data of the sensors during the measurement period, as one data per second.…”