This investigation evaluated food values, food purchasing, and other food and eating-related outcomes during the COVID-19 pandemic in Quebec, Canada. The role of stress in eating outcomes was also examined. An online household survey was conducted among Quebec adults aged ≥18 years (n = 658). Changes in outcomes during, as compared to before, the pandemic were evaluated using descriptive statistics and thematic analysis of free text responses. Eating outcomes by daily stress level (low, some, high) were assessed using Cochran-Armitage test for trend. Most respondents reported increased importance and purchasing of local food products (77% and 68%, respectively) and 60% reported increased grocery spending (mean ± standard deviation: 28% ± 23%). Respondents with a higher daily stress level had a higher frequency of reporting eating more than usual compared to before the pandemic (low stress 21%, some stress 34%, high stress 39%, -trend <0.0001). Free text responses described more time spent at home as a reason for eating more than usual. To support healthy eating during and post-pandemic, dietitians should consider patients' mental/emotional well-being and time spent at home. Moreover, support of local food products may provide opportunities to promote healthy eating, sustainability, and post-pandemic resiliency of food systems.
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http://dx.doi.org/10.3148/cjdpr-2022-030 | DOI Listing |
J Food Sci
January 2025
Digital Agriculture, Food and Wine Research Group, School of Agriculture, Food and Ecosystem Science, Faculty of Science, The University of Melbourne, Melbourne, Victoria, Australia.
Fraud in alcoholic beverages through counterfeiting and adulteration is rising, significantly impacting companies economically. This study aimed to develop a method using near-infrared (NIR) spectroscopy (1596-2396 nm) through the bottle, along with machine learning (ML) modeling for beer authentication, quality traits, and control assessment. For this study, 25 commercial beers from different brands, styles, and three types of fermentation were used.
View Article and Find Full Text PDFJ Food Sci
January 2025
School of Life Sciences and Chemistry, Minnan Science and Technology College, Quanzhou, Fujian, China.
Polyphenols are known to interact with starch to form the V-type inclusion complex or the noninclusive complex. It is hypothesized that the addition of polyphenols could improve the properties of Chinese yam (Dioscorea opposita Thunb.) starch, and the properties of the complexes could be regulated by controlling the additive amount of polyphenols.
View Article and Find Full Text PDFJ Food Sci
January 2025
College of Electronics and Engineering, Heilongjiang University, Harbin, China.
Bruises can affect the appearance and nutritional value of apples and cause economic losses. Therefore, the accurate detection of bruise levels and bruise time of apples is crucial. In this paper, we proposed a method that combines a self-designed multispectral imaging system with deep learning to accurately detect the level and time of bruising on apples.
View Article and Find Full Text PDFThis study aimed to investigate the impact of dietary soybean oil and probiotics on goat meat quality, total conjugated linoleic acids (TCLA) concentration, and nutritional quality indicators of goats. Thirty-six male crossbred goats (Anglo-Nubian♂× Thai native♀), weighing 18.3 ± 2.
View Article and Find Full Text PDFJ Food Sci
January 2025
School of Computer and Artificial Intelligence, Beijing Technology and Business University, Beijing, China.
Whole-grain foods (WGFs) constitute a large part of humans' daily diet, making risk identification of WGFs important for health and safety. However, existing research on WGFs has paid more attention to revealing the effects of a single hazardous substance or various hazardous substances on food safety, neglecting the mutual influence between individual hazardous substances and between hazardous substances and basic information. Therefore, this paper proposes a causal inference of WGFs' risk based on a generative adversarial network (GAN) and Bayesian network (BN) to explore the mutual influence between hazardous substances and basic information.
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