Journal of Food Quality
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Acceptance rate34%
Submission to final decision86 days
Acceptance to publication18 days
CiteScore3.600
Journal Citation Indicator0.480
Impact Factor2.450

Aflatoxin M1 Contamination of Ghanaian Traditional Soft Cottage Cheese (Wagashie) and Health Risks Associated with Its Consumption

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 Journal profile

Journal of Food Quality publishes original research on issues of food quality, including the handling of food from a quality and sensory perspective and covers both medical and functional foods.

 Editor spotlight

Chief Editor, Anet Režek Jambrak, is a professor at the University of Zagreb. Her fields of research include food physics, food processing, food chemistry, sustainability, nonthermal processing, and advanced thermal processing.

 Special Issues

We currently have a number of Special Issues open for submission. Special Issues highlight emerging areas of research within a field, or provide a venue for a deeper investigation into an existing research area.

Latest Articles

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Research Article

Functional Potential and Chemical Profile Analysis of Propolis Oil Extracted from Propolis of Balochistan

Propolis oil (PO) was examined for chemical composition, phenolic and flavonoid content, and antioxidant and antimicrobial potential. Phenolic and flavonoid contents were 2.388 ± 1.116 mg GAE/g and 0.579 ± 0.140 mg QE/g. Oil showed 64.59 ± 14.59% inhibition of DPPH radical and significant antibacterial activities against target bacteria. Salmonella typhi was found to be highly sensitive (27.23 ± 4.35 mm) to PO, compared to Escherichia coli (23.40 ± 3.21), Staphylococcus aureus (21.43 ± 2.80), and Klebsiella pneumoniae (21.26 ± 3.25). The MIC and MBS values of PO were 0.35 and 0.7 mg/mL for S. typhi and E. coli, whereas they were 0.7 and 1.4 mg/mL for S. aureus. Moreover, the PO was found to be bacteriostatic for K. pneumoniae. Aspergillus flavus was found to be highly sensitive to PO, with an effective growth inhibition percentage of 73%, followed by Aspergillus niger (70%), whereas Aspergillus parasiticus was less sensitive with 25% growth inhibition. Functional groups in PO were determined with an FTIR spectrophotometer, and alcohol, alkane, aldehydes, alkenes, and ketones groups were found to be present, whereas GC-MS analysis revealed the presence of 27 different medicinal compounds, among which α-copanene (29.85%), benzyl benzoate (26.8%), 2,4-bis[1-(4-hydroxyphenyl)isopropyl]phenol, acetophenone (14.92%), undecylenic aldehyde (7.46%), p-linalool (5.9%), and ethyl 3-phenylpropionate (4.47%) were found in abundance.

Research Article

Research on Food Security Risk Assessment and Early Warning in China Based on BP Neural Network Model

China has always attached great importance to food security issues; especially in today’s changeable world, it is particularly important to build a feasible and accurate food security early warning system. According to the influencing factors in food security, this paper uses the PCA method and the AHP method to construct a food security early warning index system that includes 4 secondary indicators and 13 tertiary indicators of total security, trade security, ecological security, and food security. There are four security levels of no warning, light warning, moderate warning, and heavy warning, and finally the comprehensive evaluation of food security from 2000 to 2019 and the specific early warning levels of various indicators are obtained. This paper constructs a food security evaluation system from the perspective of data, breaks through the limitations of existing research, and improves the completeness of food security early warning indicators. Because the BP neural network is a multilayer feedforward neural network with strong adaptability, it is one of the most widely used and successful neural network models at present. Finally, BP neural network is used to simulate China’s food security early warning system and design standardized risk prevention and control processes and classified response strategies—routine monitoring, risk control, and emergency response—to provide signal guidance and reference for China’s food security to respond to risks early.

Research Article

Smart Farming System Based on Intelligent Internet of Things and Predictive Analytics

The Internet of Things (IoT) makes it conceivable to communicate among distinctive things. The use of IoT in the farming industry is critical for increasing utility. Smart agricultural practices may boost crop yield while also creating more output with the same amount of input. The majority of farmers, however, are still unaware of the most recent technologies and procedures. In this study, a revolutionary wireless mobile robot based on the Internet of Things (IoT) is created and installed to perform a variety of outdoor tasks. The benefits of this work include more accurate and efficient data, as well as a reduction in manpower. This research has applications in agriculture, arrival, and water division. Keen agrarian frameworks have been built up in different parts of the world utilising the Internet of Things (IoT) and remote sensor systems. One of the branches that springs to intellect in this respect is exactness cultivating. Numerous analysts have made checking and robotization frameworks for different cultivating capacities. Information collection and transmission between IoT gadgets set in ranches will be basic utilising WSN. The Kalman Filter (KF) is used with expectation investigation within the proposed method to get high-quality information free of commotion and exchange it with cluster-based WSNs. The quality of information utilised for examination is progressed as a result of this strategy, and information transport overhead within the wireless sensor network application is decreased. A decision tree is used for forecast analytics decision making for trim surrender expectation, trim classification, soil classification, climate expectation, and trim malady expectation. IoT components integrated with IoT cloud are coordinates in proposed framework to supply keen arrangement for edit development observing to clients.

Research Article

Machine Learning Model-Based Applications for Food Management in Alzheimer’s Using Regression Analysis Approach

Alzheimer’s disease (AD) has become a public health concern due to its misinterpretation with vascular dementia (VD) and mixed dementia Alzheimer’s disease (MXD). Therefore, an accurate differentiation of these diseases is essential for improving the treatment procedure. It has been seen that nutrition along with several other factors plays a role in the disease progression. Scientists are trying to find a solution using some machine learning (ML) techniques. The ML algorithms used for this purpose are neural networks, support vector machines, regression and many more. The current research is focused on understanding the extent of the application of machine learning tools in enhancing food management for patients with Alzheimer’s since there is no cure known for the same. A total of 100 patient data have been collected where the patients had AD, VD, and MXD. Their demographic data, dietary intake, Fazekas scores, and Hachinski scores were collected (independent variables) and analysed in IBM SPSS by considering the risk of development of AD, VD, and MXD as dependent variables. The findings showed that age is highly related () to the development of these three diseases and other demographics are not prioritized. Discussion of other available journal articles showed that nutritional intake, Fazekas scores, Hachinski scores, and gender are also indicators for predicting these diseases (). Thus, this study concluded that age, gender, diet consumption, and Fazekas and Hachinski scores are important indicators for differentiating AD from other diseases, and ML can be used to create a custom nutrition plan based on the patient’s diet and stage of disease progression. Lastly, future scopes of ML have been explained in this paper.

Research Article

Household Level Determinants of Food Insecurity in Rural Ethiopia

Introduction. Currently, Ethiopia, in particular, the rural areas of Ethiopia, faces high levels of food insecurity. In spite of the fact that there have been many studies on food security, most of them have been conducted in specific national settings. Hence, the determinants of food insecurity should be assessed at the national level. Therefore, this study was primarily aimed to identify the determinant factors of household food insecurity in rural Ethiopia. Method. A cross-sectional Ethiopian socioeconomic survey (ESS) data collected from September 2018 to August 2019 was utilized. A sample of 3115 households was selected from 316 clusters across rural Ethiopia using a two-stage probability sampling technique. To identify the determinants of food insecurity, logistic regression was applied. Results. Among 3,115 households, 50.05% of them were food insecure. Factors such as the household head being aged from 30 to 64 (AOR = 0.786, 95% CI: [0.635, 0.973]), widowed, divorced, or separated (AOR = 1.588, 95%CI: [1.001, 2.518]), literate (AOR = 0.702, 95%CI: [0.590, 0.834]), household aid (AOR = 1.339, 95%CI: [1.089, 1.648]), drought-affected (AOR = 0.640, 95%CI: [0.507, 0.808]), nonagricultural business (AOR = 0.655, 95%CI: [0.472, 0.908]), dependency ratio from 50 to 75% (AOR = 0.680, 95%CI: [0.534, 0.867]), having 6 to 10 livestock (AOR = 0.644, 95%CI: [0.496, 0.836]), and more than 10 livestock (AOR = 0.362, 95% CI: [0.284, 0.461]) were found to be significantly associated with the household’s food insecurity at 5% level of significance. Conclusion. The household head’s age from 30 to 64, being literate, drought-affected, having nonagricultural business, dependency ratio from 50 to 75%, and owning more than 10 livestock have been negatively affecting food insecurity. While supporting households, a “widowed, divorced, or separated” household head has had a positive effect on food insecurity in rural Ethiopia positively influencing food insecurity in rural Ethiopia. Policymakers need to pay special attention to very young and old-aged household heads, adult education, household self-help, livestock improvement, and entrepreneurship while implementing poverty reduction programs.

Research Article

Preservative Effect of Ginger Root (Zingiber officinale R.) Extract in Refined Palm Olein Subjected to Accelerated Thermal Oxidation

Oils and fats are susceptible to the oxidation of their unsaturated fatty acids during processing, storage, or handling. Oxidation reactions lead to serious damages to oil quality that makes it to be rejected by consumers for health issues and industries that might undergo financial challenges. To limit these damages, chemically synthesized antioxidants have been added to oils and fats as preservatives. However, these were reported not to be healthy and natural substitutes extracted from plant have been the main focus of many researchers and industries these recent years. This study aimed at evaluating the preservative effect of ginger root extracts in inhibiting palm olein alteration during accelerated air-dried oven storage at 180°C. The natural antioxidants were added to palm olein at the concentrations of 200, 600, 1000, 1400, and 1800 ppm and kept in the air-dried oven for six days at 180°C (daily heating was 4 h). Butylated hydroxytoluene (BHT) was used as positive control and oil with no additive functioned as the negative one. Oil samples were collected from the oven after every 2 days for analysis. The quality parameters including the peroxide value (PV), the p-anisidine value (p-AV), the total oxidation value (TOTOX), the acid value (AV), the thiobarbituric acid value (TBA), and the iodine value (IV) were determined. The changes in the fatty acid composition of palm olein were characterized by gas chromatography coupled to a flame ionization detector (GC/FID). The ginger extract was found to be effective in delaying palm olein alteration during processing. Extract efficiency was concentration-dependent and was better than that of the control and the sample supplemented with butylated hydroxytoluene (BHT). Therefore, ginger root extract can be an ideal alternative to synthetic antioxidants used in palm olein.

Journal of Food Quality
Publishing Collaboration
More info
Wiley Hindawi logo
 Journal metrics
See full report
Acceptance rate34%
Submission to final decision86 days
Acceptance to publication18 days
CiteScore3.600
Journal Citation Indicator0.480
Impact Factor2.450
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Article of the Year Award: Outstanding research contributions of 2020, as selected by our Chief Editors. Read the winning articles.