scholarly journals Microbial growth models for shelf life prediction in an Icelandic cod supply chain

2011 ◽  
Author(s):  
R. Gospavic ◽  
H. L. Lauzon ◽  
V. Popov ◽  
E. Martinsdottir ◽  
M. N. Haque ◽  
...  
Keyword(s):  
Supply Chain ◽  
Shelf Life ◽  
Life Prediction ◽  
Microbial Growth ◽  
Growth Models ◽  
Shelf Life Prediction

scholarly journals Freshness Assessment and Shelf-Life Prediction for Seriola dumerili from Aquaculture Based on the Quality Index Method

Molecules ◽  
2019 ◽  
Vol 24 (19) ◽  
pp. 3530 ◽  
Author(s):  
Jorge Freitas ◽  
Paulo Vaz-Pires ◽  
José S. Câmara
Keyword(s):  
Shelf Life ◽  
Quality Index ◽  
Life Prediction ◽  
Microbial Growth ◽  
Point System ◽  
Psychrophilic Bacteria ◽  
Index Method ◽  
Seriola Dumerili ◽  
Life Evaluation ◽  
Shelf Life Prediction

Fish and fish-based products are easily perishable foods due to different factors, including fragile organization, abundant endo-enzymes, psychrophilic bacteria, and impact of pre-harvest operations, that contribute to reducing its value. Therefore, a timely effective method for fish freshness and shelf-life evaluation is important. In this context, this study aimed to develop a sensory scheme based on the Quality Index Method (QIM) (sensory table and point system) for freshness monitorization and shelf-life prediction for Seriola dumerili from aquaculture in Madeira Island. Evaluation of appearance, texture, eyes, and gills was performed during 20 days of storage on ice (0 ± 1 °C). The shelf-life prediction was supported by the analysis of microorganisms (total viable colonies, TVC, counts), texture (Torrymeter), and production of trimethylamine (TMA), evaluated by HS-SPME–GC–MS and validated according to Association of Official Analytical Chemists AOAC guidelines. The result is a QIM scheme with 25 demerit points, where zero indicates total freshness. From the integration of sensory analysis, microbial growth at the time of rejection (TVC, 108 cfu/cm2 and H2S producers, 107 cfu/cm2), texture (Torrymeter value < 8), and TMA analyses (>12.5 mg/100 g), shelf-life was estimated as 12 days (±0.5 days). The obtained results show the high-throughput potential of the developed method for fish freshness assessment and shelf-life prediction. This QIM scheme is a secure way to measure quality and provide users with a reliable standardized fish freshness measure.

Prediction for Shelf Life and Safety of Minimally Processed CAP/MAP Chilled Foods: A Review

1992 ◽  
Vol 55 (9) ◽  
pp. 741-750 ◽  
Author(s):  
THEODORE P. LABUZA ◽  
BIN FU ◽  
PETROS S. TAOUKIS
Keyword(s):  
Shelf Life ◽  
Microbial Growth ◽  
Growth Models ◽  
Minimally Processed ◽  
Safety Assurance ◽  
Use Of Time ◽  
Modified Atmospheric Packaging ◽  
Shelf Life Prediction ◽  
Root Model ◽  
Nonisothermal Conditions

The reliance of minimally processed chilled foods on low temperature for distribution with optimized controlled/modified atmospheric packaging to maintain safety and quality poses new challenges to food microbiologists. Effects of controlled/modified atmospheric packaging conditions on microbial growth are briefly discussed. Microbial growth models are systematically examined with emphasis on the temperature dependence models—the Arrhenius model and the square root model. Their applicability for making predictions of both shelf life and safety under nonisothermal conditions is assessed. The use of time-temperature integrators for shelf-life prediction and safety assurance is also addressed.

scholarly journals System Architectures for Sensor-Based Dynamic Remaining Shelf-life Prediction

2019 ◽  
Vol 10 (4) ◽  
pp. 21-38
Author(s):  
Åse Jevinger ◽  
Paul Davidsson
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Shelf Life ◽  
Life Prediction ◽  
Temperature Sensors ◽  
Proof Of Concept ◽  
System Architectures ◽  
Novel Approach ◽  
Shelf Life Prediction ◽  
Suitable System

Different storage and handling conditions in cold supply chains often cause variations in the remaining shelf life of perishable foods. In particular, the actual shelf life may differ from the expiration date printed on the primary package. Based on temperature sensors placed on or close to the food products, a remaining shelf-life prediction (RSLP) service can be developed, which estimates the remaining shelf life of individual products, in real-time. This type of service may lead to decreased food waste and is used for discovering supply chain inefficiencies and ensuring food quality. Depending on the system architecture, different service qualities can be obtained in terms of usability, accuracy, security, etc. This article presents a novel approach for how to identify and select the most suitable system architectures for RSLP services. The approach is illustrated by ranking different architectures for a RSLP service directed towards the supply chain managers. As a proof of concept, some of the most highly ranked architectures have been implemented and tested in food cold supply chains.

scholarly journals Shelf life prediction of carica seeds powder using accelerated method

2021 ◽  
Vol 653 (1) ◽  
pp. 012055
Author(s):  
S D Astuti ◽  
S Lestari ◽  
Erminawati ◽  
S Widarni ◽  
G Wijanarko ◽  
...  
Keyword(s):  
Shelf Life ◽  
Life Prediction ◽  
Shelf Life Prediction

Optimized Rules-Based Non-Destructive Monitoring System for Chilled Chicken Quality Evaluation and Shelf Life Prediction

2021 ◽  
Author(s):  
Jinchao Xu ◽  
Xue Liu ◽  
Stevan Stankovski ◽  
Ruiqin Ma ◽  
Xiaoshuan Zhang ◽  
...  
Keyword(s):  
Shelf Life ◽  
Monitoring System ◽  
Life Prediction ◽  
Quality Evaluation ◽  
Shelf Life Prediction ◽  
Non Destructive

E-nose for Shelf-Life Prediction of Climacteric Fruits

2021 ◽  
Author(s):  
Sunil Karamchandani ◽  
Bhavya Sekhani ◽  
Kartik Nair ◽  
Krina Shah
Keyword(s):  
Shelf Life ◽  
Life Prediction ◽  
Shelf Life Prediction
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