Estimation of the shelf life of pezik pickles using Weibull hazard analysis

Keklik, Nene Meltem; Işıklı, Nursel Develi; Sur, Esen Bilge

doi:10.1590/1678-457x.33216

Cited by 9 publications

(6 citation statements)

References 18 publications

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“…Among these, electronic sensing for rapid diagnosis of food quality [7] and a multiple linear regression model was reported to predict the shelf-life of roasted coffee, sterilized milk drinks [8] or yogurt [6,9]. In recent years, we have witnessed the development and application of more reliable, effective and fast mathematical modelling, such as the Weibull hazard model used for estimating the shelf-life of pezik pickles, for example [10]. Fast mathematical modeling, such as the Q10 model [11], has been widely used forshelf-life evaluation of food products such as frozen shrimp [12], for kinetics analysis of quality changes in Pangasius fillets at stable and dynamic temperatures, for simulating downstream cold chain conditions [13], and also for analysis of chilled pork [14], ketchup [15] or juice drinks [16].…”

Section: Introductionmentioning

confidence: 99%

Multiple regression models and Artificial Neural Network (ANN) as prediction tools of changes in overall quality during the storage of spreadable processed Gouda cheese

Stangierski

Weiss

Kaczmarek

2019

Eur Food Res Technol

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The aim of the study was to compare the ability of multiple linear regression (MLR) and Artificial Neural Network (ANN) to predict the overall quality of spreadable Gouda cheese during storage at 8 °C, 20 °C and 30 °C. The ANN used five factors selected by Principal Component Analysis, which was used as input data for the ANN calculation. The datasets were divided into three subsets: a training set, a validation set, and a test set. The multiple regression models were highly significant with high determination coefficients: R 2 = 0.99, 0.87 and 0.87 for 8, 20 and 30 °C, respectively, which made them a useful tool to predict quality deterioration. Simultaneously, the artificial neural networks models with determination coefficient of R 2 = 0.99, 0.96 and 0.96 for 8, 20 and 30 °C, respectively were built. The models based on ANNs with higher values of determination coefficients and lower RMSE values proved to be more accurate. The best fit of the model to the experimental data was found for processed cheese stored at 8 °C.

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Section: Introductionmentioning

confidence: 99%

Multiple regression models and Artificial Neural Network (ANN) as prediction tools of changes in overall quality during the storage of spreadable processed Gouda cheese

Stangierski

Weiss

Kaczmarek

2019

Eur Food Res Technol

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“…dairy foods, including some yoghurt (Zhi et al, 2018 ). Many models were developed as a result of research on plant products: modelling of the effect of storage temperature on the respiration rate and texture of fresh cut pineapple (Benítez et al, 2012 ), Weibull hazard analysis for estimation of the shelf-life of pezik pickles (Keklik et al, 2017 ), kinetics of changes in shelf-life parameters during storage of pearl millet (Bunkar et al, 2014 ), non-isothermal kinetic modelling for anthocyanins in bread and crust (Sui et al, 2015 ), prediction of the quality and storage period of soybean at different temperatures (Dong et al, 2015 ). The fast mathematical modelling methods such as the Weibull hazard model and Q10 model have been used with meat products to predict the shelf-life of chilled pork (Tang et al, 2013 ), for the modelling of frozen shrimp shelf-life at variable temperatures (Tsironi et al, 2009 ), the kinetics of changes in the quality of Pangasius fillets at stable and dynamic temperatures, and to simulate downstream cold chain conditions (Mai and Huynh, 2017 ).…”

Section: Introductionmentioning

confidence: 99%

Kinetic models of quality parameters of spreadable processed Gouda cheese during storage

Weiss

Stangierski

Baranowska

et al. 2018

Food Sci Biotechnol

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The aim of the study was to prepare mathematical models based on the Arrhenius equation as predictive tools for the assessment of changes in quality parameters during the storage of spreadable Gouda cheese at temperatures of 8, 20 and 30 °C. The activation energy value and the chemical reaction rate constant enabled the construction of kinetic models, which helped to estimate the direction and rate of changes. Moreover, the activation energy (Ea) of the quality parameters was used to determine the sequence of their vulnerability during storage. The value of activation energy corresponding to temperature changes resulted in the following order of susceptibility of the quality parameters: ΔC > ΔE ≈ water activity > texture parameters > pH > colour > sensory parameters > rheological parameters. The research showed limited applicability of the mathematical models for estimation of quality parameters referring to spreadable processed Gouda cheese.

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“…To calculate hazard parameters, log (time) vs log (cumulative hazard values) was plotted. The equation obtained from the graph was replaced in Equation 2 (Keklik et al, 2017).…”

Section: 𝐻(𝑡)=∫ℎ(𝑥)𝑑𝑥=(𝑡/𝛼) 𝛽mentioning

confidence: 99%

Aromalı soğuk kahve içeceğinin raf ömrü ve tüketici beğenisi üzerine bir araştırma

POLAT

İbanoğlu

2021

Harran Tarım Ve Gıda Bilimleri Dergisi

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In this article, it was aimed to develop a method to determine the shelf life of pistachio nut flavored cold coffee. The shelf life of flavored cold coffee was determined by the Weibull hazard analysis method. While a fixed time (i.e., 10 min) was applied for the sterilization process, different sterilization temperatures (i.e., 110, 120 and 125°C) were used. In the first stage of the study, while carrageenan gum was added as a thickener to all cold coffees, sodium bicarbonate, which is an acidic regulator, was not added. The shelf lives of products sterilized in this way were determined as 14, 28 and 18 days at 110°C, 120°C and 125°C, respectively. In the second step, both sodium bicarbonate and carrageenan gum were added to the samples and the shelf life of the product, which was sterilized at 120°C for 10 min., was calculated as 16 months and 9 days. As a result of the hedonic tests, 71% of the panelists stated that they liked pistachio flavored cold coffee. The optimum formulation of cold coffee was 1.5% (w/w) coffee, 0.2% (w/w) sodium bicarbonate, 7.5% (w/w) sugar, 5.0% (w/w) milk powder, 0.1% (w/w), chewing gum and 0.1% (w/w) pistachio flavor.

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Estimation of the shelf life of pezik pickles using Weibull hazard analysis

Cited by 9 publications

References 18 publications

Multiple regression models and Artificial Neural Network (ANN) as prediction tools of changes in overall quality during the storage of spreadable processed Gouda cheese

Multiple regression models and Artificial Neural Network (ANN) as prediction tools of changes in overall quality during the storage of spreadable processed Gouda cheese

Kinetic models of quality parameters of spreadable processed Gouda cheese during storage

Aromalı soğuk kahve içeceğinin raf ömrü ve tüketici beğenisi üzerine bir araştırma

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