Study of Spinyhead Croaker (Collichthys lucidus) Fat Content Forecasting Model Based on Electronic Nose and Non-linear Data Resolution Model

Zheng, Hao; Wang, Siyang; Ping, Xinyi; Shao, Chenning; Zhou, Huimin; Xiang, Bin; Li, Jian; Lou, Xiongwei; Yi, Xiaomei; Hui, Guohua

doi:10.1007/s12161-019-01510-x

Cited by 23 publications

(5 citation statements)

References 29 publications

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“…These results indicate that volatile compounds can be largely reduced in heat-treated fish. These analyses indicate that tilapia treated by four different thermal processing methods possesses different aroma characteristics, which is essential to understanding the effects of thermal processing on the nutrients in food [ 20 ]. From the results, aldehyde, ketone, and alcohol are identified as the main flavoring substances in fish, although the proportion of hydrocarbon is larger only in the boiled fish samples.…”

Section: Nanoelectronic Smelling: Analysis Of Animal-based Foodsmentioning

confidence: 99%

Progress of Research on the Application of Nanoelectronic Smelling in the Field of Food

Sha

2022

Micromachines

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In the past 20 years, the development of an artificial olfactory system has made great progress and improvements. In recent years, as a new type of sensor, nanoelectronic smelling has been widely used in the food and drug industry because of its advantages of accurate sensitivity and good selectivity. This paper reviews the latest applications and progress of nanoelectronic smelling in animal-, plant-, and microbial-based foods. This includes an analysis of the status of nanoelectronic smelling in animal-based foods, an analysis of its harmful composition in plant-based foods, and an analysis of the microorganism quantity in microbial-based foods. We also conduct a flavor component analysis and an assessment of the advantages of nanoelectronic smelling. On this basis, the principles and structures of nanoelectronic smelling are also analyzed. Finally, the limitations and challenges of nanoelectronic smelling are summarized, and the future development of nanoelectronic smelling is proposed.

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Section: Nanoelectronic Smelling: Analysis Of Animal-based Foodsmentioning

confidence: 99%

Progress of Research on the Application of Nanoelectronic Smelling in the Field of Food

Sha

2022

Micromachines

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“…For example, the electronic nose technology, which uses odor to evaluate the freshness of food, has the advantages of low cost, fast detection speed and good repeatability (Peng et al, 2018). At present, scholars have used this technology to realize the quality evaluation of fish, shrimp and other aquatic products (Shao et al, 2018; Zheng, Wang, Ping, et al, 2019; Zheng, Wang, Shao, et al, 2019), as well as the application of beef purity identification (Wakhid et al, 2022). In addition, most of the other studies also focus on the freshness detection of aquatic products, while there are few studies on the detection of residual foreign matters.…”

Section: Introductionmentioning

confidence: 99%

De‐noising method of aquatic product image with foreign matters based on improved wavelet transform and bilateral filter

Cui

2023

J Food Process Engineering

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Aiming at the strong spot noise caused by the reflection of meat slices in fish image with foreign matters that collected by ordinary camera or Single Lens Reflex (SLR) camera, we proposed an improved wavelet transform and bilateral filtering algorithm to reduce the noise of image. In this paper, our algorithm absorbed the advantages of wavelet threshold de‐noising algorithm and bilateral filtering algorithm, the wavelet threshold de‐noising algorithm being used for high frequency components and bilateral filtering being used for low frequency components, which not only achieved the effect of eliminating noise and weakening light spot, but also protected the details of the image. In the experiment, in order to verify the effectiveness of the proposed algorithm, we used the traditional bilateral filtering, Gaussian filtering and median filtering algorithms to process 500 salmon fish images which had residual fishbone, respectively. Since the original image itself was a noisy image, it was impossible to evaluate the noise reduction effect by using an algorithm that requires a noiseless image as a reference image, so we used five methods to evaluate the quality of the image processed by each algorithm, which were Blind/Referenceless Image Spatial QUality Evaluator (BRISQE), Cumulative Probability of Blur Detection (CPBD), variance, image entropy, and operation speed. Among them, BRISQE and CPBD could quantitatively reflect the overall quality of the image, the lower the BRISQE score or the higher the CPBD score, the better the quality of the image. Compared with other algorithms, the BRISQE score and CPBD score of the image processed by our algorithm were the best, with the average scores reaching 20.65 and .8421, respectively. Experimental results showed that the improved algorithm in this paper can effectively eliminate this kind of strong spot noise. The processed image has achieved better visual effect in both subjective and objective level.

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“…Compared with the traditional detection method mentioned above, the gas sensing technology has provided a new option for nondestructive, inexpensive, and less time‐consuming quality assessment (Li, Feng, Liu, Gao, & Hui, 2016). Therefore, it has been successfully applied in food quality detection, including fish (Han, Jinghao, Feixiang, & Guohua, 2015; Zhang et al, 2018; Zheng et al, 2019; Zheng et al, 2019), shrimps (Jiang, Li, Zheng, Lin, & Hui, 2016; Shao et al, 2018; Zheng, Wang, et al, 2019), meat (Musatov, Sysoev, Sommer, & Kiselev, 2010), tea (Kovács et al, 2010), wine (Arroyo et al, 2009), coffee (Rodrigues, Fragoso, & Lemos, 2021), oil (Karami, Rasekh, & Mirzaee‐Ghaleh, 2020; Rusinek et al, 2021; Tata et al, 2022), bread (Rusinek et al, 2021), fruit (Lihuan, Liu, Xiaohong, Guohua, & Zhidong, 2017; Ying, Liu, & Hui, 2015), grain (Xu et al, 2018; Ying, Liu, Hui, & Fu, 2015), milk (Eriksson et al, 2005), and vegetables (Zhiyi et al, 2017). The quality assessment of meat is regarded as one of the most important applications of gas sensing technology.…”

Section: Introductionmentioning

confidence: 99%

Gas sensing technology for meat quality assessment: A review

Wang

Chen

2022

J Food Process Engineering

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Meat is rich in many nutritional elements and is one of the most basic foods for human beings. The demand for meat is increasing year by year, but at the same time, meat is highly susceptible to spoilage during storage and transportation, and consumption of such meat can be hazardous to human health. Gas sensing technology provides a nondestructive, less time‐consuming, and convenient detection method compared with traditional meat quality testing techniques. In this review, we briefly describe the working principle, the common sensors, signal processing, and pattern recognition for gas sensing technology. Then, we discuss the most relevant contributions of gas sensing technology to meat freshness evaluations and authenticity assessments using different data processing methods in recent years. Finally, the problems, prospects, and likely future development of gas sensing technology are highlighted. Practical applications This article analyzes each key technology of gas sensing, points out some existing defects and future trends, reviews the practical applications of gas sensing technology in meat quality inspection in recent years, and puts forward feasible technology enhancement suggestions.

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Study of Spinyhead Croaker (Collichthys lucidus) Fat Content Forecasting Model Based on Electronic Nose and Non-linear Data Resolution Model

Cited by 23 publications

References 29 publications

Progress of Research on the Application of Nanoelectronic Smelling in the Field of Food

Progress of Research on the Application of Nanoelectronic Smelling in the Field of Food

De‐noising method of aquatic product image with foreign matters based on improved wavelet transform and bilateral filter

Gas sensing technology for meat quality assessment: A review

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