Critical knowledge gaps about environmental fate and unintentional effects of currently used pesticides (CUPs) hamper the understanding and mitigation of their global impacts on ecological processes. We investigated the exposure of earthworms to 31 multiclass CUPs in an arable landscape in France. We highlighted the presence of at least one pesticide in all soils (n = 180) and 92 % of earthworms (n = 155) both in treated crops and nontreated habitats (hedgerows, grasslands, and cereals under organic farming).
Background: Today's meat and dairy industry has a vast environmental footprint. To reach the UN sustainable development goals (SDGs) of ending hunger globally (SDG #2) and achieving sustainable consumption and production (SDG #12), this food production system needs to change. Recent years have seen the rise in popularity of the vegan or plant-based diet among consumers, which can go some way to reducing the environmental burden.
Non-destructive testing techniques have gained importance in monitoring food quality over the years. Hyperspectral imaging is one of the important non-destructive quality testing techniques which provides both spatial and spectral information. Advancement in machine learning techniques for rapid analysis with higher classification accuracy have improved the potential of using this technique for food applications. This paper provides an overview of the application of different machine learning techniques in analysis of hyperspectral images for determination of food quality.
This study was conducted to assess the self-reported and observed food safety practices (FSP) of food handlers, who deliver food products that are prepared and cooked at home during the COVID-19 pandemic in the Philippines. 751 participated in the online survey who were selected using criterion sampling. A questionnaire developed by the researcher was used to gather data with Cronbach Alpha of 0.91. t-test, ANOVA, and Fleiss kappa were performed to treat data.
The consumption of meat contributes significantly to undesirable effects on the environment. In order to reduce the impact of animal husbandry, one approach is to decrease meat consumption by substituting plant-based meat alternatives. Because the consumption of such meat alternatives is currently rather low, the aim of this research was to identify the barriers that keep people from consuming meat alternatives and increase the probability of future consumption.
Background: Fake meat industry is expected to grow and to be worth $140 billion by 2030. Alternative protein can be produced by plant or microbe. Animal-free dairy protein can be produced by fermentation in microflora. Scope and approach: In order to improve the real production, many companies are focusing on fermentation for animal-free meat, eggs, and dairy respectively. Key findings and conclusions: However, their production capabilities, efficiencies, and costs are not available in public respectively. This paper reports briefly what is going on in sustainable protein alternatives.
Increasing the production of food from the ocean is seen as a pathway toward more sustainable and healthier human diets.
This is a special issue on food systems for children and adolescents with research on food marketing, nutrition and sustaining healthy diets and food supply chains. It brings together research advancing SDGs 2, zero hunger, SDG 3, good health and wellbeing and SDG 12, responsible production and consumption.
The dynamic impact of income and income distribution on food consumption among adults in rural China
Journal of Integrative Agriculture, Volume 20, January 2021
Using China Health and Nutrition Survey data, this study employs a consistent two-step quadratic almost ideal demand system model, with addressed problems of endogeneity of total expenditure and zero shares, to estimate the food demand elasticities among adults in rural areas with regard to the different income strata.
Targeted interventions have important under-explored potential for reducing meat consumption. We hypothesized that group-specific interventions targeting reduction for reducer, moderate-hindrance, and strong-hindrance meat eaters would be effective. All participants were randomly assigned to one of three treatment conditions designed for these three meat-eating groups, or to a control condition. Following the intervention, up to 28 days of food diaries were gathered to measure their consumption of animal products, which were weighted according to their greenhouse gas emissions.
