Impact of icing with potato, sweet potato, sugar beet, and red beet peel extract on the sensory, chemical, and microbiological changes of rainbow trout (Oncorhynchus mykiss) fillets stored at (3 ± 1 °C)

Yavuzer, Emre; Özoğul, Fatih; Özoğul, Yeşim

doi:10.1007/s10499-019-00454-7

Cited by 16 publications

(9 citation statements)

References 24 publications

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“…The increase in the colors identified by Arduino indicated that those values fin the meat and head of the fish found by the color sensor decreased during storage. Our previous studies (Özo gul et al, 2013;Yavuzer et al, 2020) reported that the color score in the trout decreased during storage in sensorial terms. Similar to the fish meat, the color levels in the head of the fish also increased systematically during storage.…”

Section: Resultsmentioning

confidence: 93%

“…The microbial load of the fish meat during storage is a significant parameter of fish quality required in industrial processing; and, the increase in the microbial load causes the sensorial and chemical characteristics (Özo gul et al, 2013;Yavuzer et al, 2020) to take an undesired form. Moreover, microbial change affects the quality of the processing and rigor mortis time (Roco et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

“…While the undesired changes occurring in the odor and color due to oxidative spoilage could reduce the shelf life (Singh, Marimuthu, Murali, & Bawa, 2005), lipid peroxidation and microbial contamination are indicated as the two significant reasons of food spoilage (Cao et al, 2008; Mahmoudi, Gajarbeygi, Norian, & Farhoodi, 2014). The color, odor, taste, and mucus levels of the fish meat are measured by the experienced panelists in test environments (Yavuzer, Özogul, & Özogul, 2020); however, human senses could be mistaken while switching between the test groups. Therefore, significant results have been obtained from studies where electronic nose is used as the sensorial sensor in recent years (Silvello & Alcarde, 2020; Zhan et al, 2020; Zhu et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

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Determination of rainbow trout quality parameters with Arduino microcontroller

Yavuzer

2020

Journal of Food Safety

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In this study, the rainbow trout was stored under refrigeration conditions (3 ± 1 C) for 18 days. Changes in the resistance levels in head, meat and eyes, changes of color in the head and meat, changes of liquid levels in the skin and meat, and odor values in the head and the meat were measured with Arduino microcontroller card and recorded during the storing period. In order to perform a significant comparison with the data obtained via Ardunio, the total viable count, psychrotrophic count and Enterobacteriaceae count in the fish meat were identified on a daily basis during storage. The results of the study indicated that the resistance value on the meat decreased significantly as the storage period increased; and that the Arduino-based color, odor and liquid level measurement sensors could be used effectively in identifying the food quality.

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Section: Resultsmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Determination of rainbow trout quality parameters with Arduino microcontroller

Yavuzer

2020

Journal of Food Safety

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“…(2015) found the initial TVC value of sea bass as 3 log cfu per g, which increased during storage. In another study conducted on sea bream (Parlapani et al., 2014), the initial TVC value was found as 3.9 log cfu per g, and the bacterial load at the time the fish lost its freshness was reported as 7.5–8.5 log cfu per g. In addition, it was determined that trout started to spoil when the bacterial load exceeded the limit of 7 log cfu per g (Yavuzer, 2020; Yavuzer et al., 2020; Yavuzer, 2021).…”

Section: Resultsmentioning

confidence: 99%

Prediction of fish quality level with machine learning

Yavuzer

Köse

2022

Int J of Food Sci Tech

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In this study, sea bream, sea bass, anchovy and trout were captured and recorded using a digital camera during refrigerated storage for 7 days. In addition, their total viable counts (TVC) were determined on a daily basis. Based on the TVC, each fish was classified as 'fresh' when it was <5 log cfu per g, and as 'not fresh' when it was >7 log cfu per g. They were uploaded on a web-based machine learning software called Teachable Machine (TM), which was trained about the pupils and heads of the fish. In addition, images of each species from different angles were uploaded to the software in order to ensure the recognition of fish species by TM. The data of the study indicated that the TM was able to distinguish fish species with high accuracy rates and achieved over 86% success in estimating the freshness of the fish species tested.

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“…Results indicated that the mixture was efficient in the prevention of microbial and chemical spoilage of fish samples. Yavuzer et al [ 155 ] also investigated the effect of icing with peel extracts of potato, sweet potato, sugar beet, and red beet on the sensory, chemical, and microbiological attributes of rainbow trout fillets. One of the main conclusions was that these waste products could be used as antimicrobial agents.…”

Section: Traditional Methods Used To Evaluate Quality Changesmentioning

confidence: 99%

Use of Spectroscopic Techniques to Monitor Changes in Food Quality during Application of Natural Preservatives: A Review

et al. 2020

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Consumer demand for food of high quality has driven research for alternative methods of food preservation on the one hand, and the development of new and rapid quality assessment techniques on the other hand. Recently, there has been a growing need and interest in healthier food products, which has led to an increased interest in natural preservatives, such as essential oils, plant extracts, and edible films and coatings. Several studies have shown the potential of using biopreservation, natural antimicrobials, and antioxidant agents in place of other processing and preservation techniques (e.g., thermal and non-thermal treatments, freezing, or synthetic chemicals). Changes in food quality induced by the application of natural preservatives have been commonly evaluated using a range of traditional methods, including microbiology, sensory, and physicochemical measurements. Several spectroscopic techniques have been proposed as promising alternatives to the traditional time-consuming and destructive methods. This review will provide an overview of recent studies and highlight the potential of spectroscopic techniques to evaluate quality changes in food products following the application of natural preservatives.

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Impact of icing with potato, sweet potato, sugar beet, and red beet peel extract on the sensory, chemical, and microbiological changes of rainbow trout (Oncorhynchus mykiss) fillets stored at (3 ± 1 °C)

Cited by 16 publications

References 24 publications

Determination of rainbow trout quality parameters with Arduino microcontroller

Determination of rainbow trout quality parameters with Arduino microcontroller

Prediction of fish quality level with machine learning

Use of Spectroscopic Techniques to Monitor Changes in Food Quality during Application of Natural Preservatives: A Review

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