Potential Application of the Electronic Nose for Quality Assessment of Salmon Fillets Under Various Storage Conditions

2002 ◽  
Vol 67 (1) ◽  
pp. 307-313 ◽  
Author(s):  
W-X. Du ◽  
C-M. Lin ◽  
T. Huang ◽  
J. Kim ◽  
M. Marshall ◽  
...  
Author(s):  
Kranthi Kumar Pulluri ◽  
Vaegae Naveen Kumar

2019 ◽  
Vol 41 (1) ◽  
pp. 97-107 ◽  
Author(s):  
Damrongvudhi Onwimol ◽  
Thunyapuk Rongsangchaicharean ◽  
Pitipong Thobunluepop ◽  
Tanapon Chaisan ◽  
Wanchai Chanprasert

Abstract: The evaluation of seed deterioration is very important to control the quality of the seeds stored. This study aimed to investigate the potential of fast ethanol assay for seed quality assessment of maize stored under different conditions. The first experiment was to determine the incubating temperature, incubating time, and amount of seed used in the assay. The results showed that the best protocol for the detection of headspace ethanol was incubation of 3 g of maize seed with 20% moisture content (wet basis) in a 20 mL gas chromatography vial at 70 °C for 1.5 h. The assay induced approximately 200-700 µg.L-1 of headspace ethanol, which was sufficient to identify seeds with different vigour levels. In the second experiment, the optimal conditions were used for quality assessment in aged maize seed stored for 12 months under different storage conditions. The increase in the ethanol production of stored maize seed under the controlled conditions (15 °C and 20% RH in the hermetic seal) was lower than under ambient conditions. The ethanol production levels of maize seed samples at the start of storage was significantly lesser than at six months storage (p < 0.05). The test limitations in deteriorated seed with different cultivars and ages will be discussed.


2001 ◽  
Vol 64 (12) ◽  
pp. 2027-2036 ◽  
Author(s):  
WEN-XIAN DU ◽  
JEONGMOK KIM ◽  
JOHN A. CORNELL ◽  
TUNG-SHI HUANG ◽  
MAURICE R. MARSHALL ◽  
...  

Microbiological assessment, sensory evaluation, and electronic nose (AromaScan) analysis were performed on yellowfin tuna stored at 0, 4, 10, and 22°C for 0, 1, 3, 5, and 9 days. Fish color, texture, appearance, and odor were evaluated by a trained sensory panel, while aroma-odor properties were evaluated using an AromaScan. Bacterial enumeration was performed using plate count agar containing 1.5% NaCl. Tuna fillets stored at 22°C for 3 days or longer had a bacterial load of over 107 CFU/g and were rated not acceptable for consumption (grade C) by the sensory panel. Tuna fillets stored at 4°C for 9 days or 10°C for over 5 days were rated as grade C products and also had a bacterial load of over 107 CFU/g. The change in fish quality as determined by AromaScan followed increases in microbiological counts in tuna fillets, indicating that bacterial load can serve as a useful and objective indicator of gross spoilage. Electronic nose devices can be used in conjunction with microbial counts and sensory panels to evaluate the degree of decomposition in tuna during storage.


Author(s):  
Selda Güney ◽  
Ayten Atasoy

The aim of this study is to test the freshness of horse mackerels by using a low cost electronic nose system composed of eight different metal oxide sensors. The process of freshness evaluation covers a scala of seven different classes corresponding to 1, 3, 5, 7, 9, 11, and 13 storage days. These seven classes are categorized according to six different classifiers in the proposed binary decision tree structure. Classifiers at each particular node of the tree are individually trained with the training dataset. To increase success in determining the level of fish freshness, one of the k-Nearest Neighbors (k-NN), Support Vector Machines (SVM), Linear Discriminant Analysis (LDA) and Bayes methods is selected for every classifier and the feature spaces change in every node. The significance of this study among the others in the literature is that this proposed decision tree structure has never been applied to determine fish freshness before. Because the freshness of fish is observed under actual market storage conditions, the classification is more difficult. The results show that the electronic nose designed with the proposed decision tree structure is able to determine the freshness of horse mackerels with 85.71% accuracy for the test data obtained one year after the training process. Also, the performances of the proposed methods are compared against conventional methods such as Bayes, k-NN, and LDA.


2019 ◽  
Vol 42 (5) ◽  
Author(s):  
Ayat Mohammad‐Razdari ◽  
Mahdi Ghasemi‐Varnamkhasti ◽  
Seyedeh Hoda Yoosefian ◽  
Zahra Izadi ◽  
Maryam Siadat

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