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Implementation of marker-assisted selection (MAS) in modern beekeeping would improve sustainability, especially in breeding programs aiming for resilience against the parasitic mite Varroa destructor. Selecting honey bee colonies for natural resistance traits, such as brood-intrinsic suppression of varroa mite reproduction, reduces the use of chemical acaricides while respecting local adaptation. In 2019, eight genomic variants associated with varroa non-reproduction in drone brood were discovered in a single colony from the Amsterdam Water Dune population in the Netherlands.Recently, a new study tested the applicability of these eight genetic variants for the same phenotype on a population-wide scale in Flanders, Belgium. As the properties of some variants varied between the two studies, one hypothesized that the difference in genetic ancestry of the sampled colonies may underly these contribution shifts. In order to frame this, we determined the allele frequencies of the eight genetic variants in more than 360 Apis mellifera colonies across the European continent and found that variant type allele frequencies of these variants are primarily related to the A. mellifera subspecies or phylogenetic honey bee lineage. Our results confirm that population-specific genetic markers should always be evaluated in a new population prior to using them in MAS programs.

Honey bee colonies have great societal and economic importance. The main challenge that beekeepers face is keeping bee colonies healthy under ever-changing environmental conditions. In the past two decades, beekeepers that manage colonies of Western honey bees (Apis mellifera) have become increasingly concerned by the presence of parasites and pathogens affecting the bees, the reduction in pollen and nectar availability, and the colonies’ exposure to pesticides, among others. Hence, beekeepers need to know the health condition of their colonies and how to keep them alive and thriving, which creates a need for a new holistic data collection method to harmonize the flow of information from various sources that can be linked at the colony level for different health determinants, such as bee colony, environmental, socioeconomic, and genetic statuses. For this purpose, we have developed and implemented the B-GOOD (Giving Beekeeping Guidance by computational-assisted Decision Making) project as a case study to categorize the colony’s health condition and find a Health Status Index (HSI). Using a 3-tier setup guided by work plans and standardized protocols, we have collected data from inside the colonies (amount of brood, disease load, honey harvest, etc.) and from their environment (floral resource availability). Most of the project’s data was automatically collected by the BEEP Base Sensor System. This continuous stream of data served as the basis to determine and validate an algorithm to calculate the HSI using machine learning. In this article, we share our insights on this holistic methodology and also highlight the importance of using a standardized data language to increase the compatibility between different current and future studies. We argue that the combined management of big data will be an essential building block in the development of targeted guidance for beekeepers and for the future of sustainable beekeeping.

The use of microalgae proteins as an alternative protein source in the European food market is becoming increasingly important. Despite their potential, these foods are still relatively unknown to European consumers. Therefore, it is crucial for their successful market introduction to explore consumer awareness, perception and willingness to try them. The objectives of this study were to identify factors shaping willingness to try and consumer segments likely to adopt foods with microalgae proteins. Data were collected via a quantitative online survey (N = 3027) in five European countries: the Netherlands, Germany, Hungary, Spain, and Italy. First, binary logistic regression showed that a flexitarian diet, general health interest, food neophobia, and environmental concern significantly shaped willingness to try foods with microalgae proteins. Second, factor analysis identified two dimensions of consumers’ perceptions about foods with microalgae proteins: credence attributes related and experience attributes related. Third, these perception constructs were used alongside willingness to try in a two-stage segmentation analysis to identify consumer segments willing to adopt foods with microalgae proteins. The analysis yielded four segments, “Enthusiast”, “Cautiously curious”, “Undecided”, and “Uninterested”. Finally, the segments were profiled in terms of sociodemographic characteristics, attitudes and perceptions by means of a multinomial logistic regression (n = 2957). Consumers with a higher general health interest, stronger environmental concern, and greater interest in information about foods with microalgae proteins were more likely to be part of segments with a higher willingness to try and more favorable perceptions. Consumers with higher levels of food (technology) neophobia, were more likely to be part of segments with a lower willingness to try and less favorable perceptions. This study has shown that segmentation proves useful to identify and profile consum

Discrete choice experiments (DCEs) have become an often-used research method in food research due to their ability to uncover trade-offs made when choosing among multiple alternatives, especially when dealing with credence attributes. Insights into the main elements of the consumers’ decision-making process are key to informing both public and private policies related to food production and consumption. However, DCEs are not confined to this field of study. This narrative methodological review sets out to provide a critical appraisal of the state of the art of DCEs in food research. We logically structure our review by comparing the field-independent state-of-the-art to its application in the specific food choice research domain. The comparison is presented for each of the steps required in implementing DCEs and allows for the identification of areas of improvement in best practice. We find that food research has adopted many of the methodological advances over the years, but further improvements are encouraged and outlined. Recommendations for future research are discussed.

Against the backdrop of meat production and consumption being increasingly contested, this paper presents a narrative descriptive review of (reductions in) meat consumption in the Netherlands and Belgium with a focus on trends during the period 2010–2020. Based on household panel purchasing data and supply balance sheet data as proxies, our analysis shows that meat consumption in the Netherlands is relatively stable, based on supply balance sheet data, despite an estimated annual decrease of around 250 g per capita per year based on household panel purchasing data. Meanwhile, household purchasing panel data for Belgium show a more steady and stronger decline with an annual decrease of slightly >1 kg per capita per year over the past decade, as well as more fluctuations based on supply balance sheet data. The ‘Covid-year’ 2020 displays a distinct pattern in both countries which deserves further exploration. Both countries face growing shares of (self-declared) flexitarians (ranging from around or above 30% in Belgium to 40% or more in the Netherlands depending on the data source and its definition of flexitarians) and consumers who claim to intend reducing their meat consumption in the future. The analysis reveals important differences in research methodologies, sample compositions, and analytical techniques. Such differences raise caveats for direct comparison between countries and impose challenges for the (European) monitoring of the so-called ‘protein transition’. Although some change is occurring, the data suggest that meat reduction calls resonate still more in terms of people's attitudes, awareness, and intentions than in overt dietary behavioral change. Overall, our findings provide reason to conclude that the established meat-centered food system and its dominant meat-eating culture are still prevailing in the Low Countries.

Discrete choice experiments (DCEs) have become an often-used research method in food research due to their ability to uncover trade-offs made when choosing among multiple alternatives, especially when dealing with credence attributes. Insights into the main elements of the consumers’ decision-making process are key to informing both public and private policies related to food production and consumption. However, DCEs are not confined to this field of study. This narrative methodological review sets out to provide a critical appraisal of the state of the art of DCEs in food research. We logically structure our review by comparing the field-independent state-of-the-art to its application in the specific food choice research domain. The comparison is presented for each of the steps required in implementing DCEs and allows for the identification of areas of improvement in best practice. We find that food research has adopted many of the methodological advances over the years, but further improvements are encouraged and outlined. Recommendations for future research are discussed.

The Welfare Quality® consortium has developed and proposed standard protocols for monitoring farm animal welfare. The uptake of the dairy cattle protocol has been below expectation, however, and it has been criticized for the variable quality of the welfare measures and for a limited number of measures having a disproportionally large effect on the integrated welfare categorization. Aiming for a wide uptake by the milk industry, we revised and simplified the Welfare Quality® protocol into a user-friendly tool for cost- and time-efficient on-farm monitoring of dairy cattle welfare with a minimal number of key animal-based measures that are aggregated into a continuous (and thus discriminative) welfare index (WI). The inevitable subjective decisions were based upon expert opinion, as considerable expertise about cattle welfare issues and about the interpretation, importance, and validity of the welfare measures was deemed essential. The WI is calculated as the sum of the severity score (i.e., how severely a welfare problem affects cow welfare) multiplied with the herd prevalence for each measure. The selection of measures (lameness, leanness, mortality, hairless patches, lesions/swellings, somatic cell count) and their severity scores were based on expert surveys (14-17 trained users of the Welfare Quality® cattle protocol). The prevalence of these welfare measures was assessed in 491 European herds. Experts allocated a welfare score (from 0 to 100) to 12 focus herds for which the prevalence of each welfare measure was benchmarked against all 491 herds. Quadratic models indicated a high correspondence between these subjective scores and the WI (R 2 = 0.91). The WI allows both numerical (0-100) as a qualitative ("not classified" to "excellent") evaluation of welfare. Although it is sensitive to those welfare issues that most adversely affect cattle welfare (as identified by EFSA), the WI should be accompanied with a disclaimer that lists adverse or favorable effects

The EU and its Member States have articulated a sustainability vision ‘to live well within the limits of our planet’ by 2050. In this context, consumers play a key role, being able to drive seafood production sustainability and responsibility according to their behaviour, also in relation to their attitudes towards health, nutrition and wellbeing. On the basis of these premises, this research explores Italian consumers' attitudes towards health and sustainability in relation to seafood, in order to segment different target of consumers. The framework used in this study is mainly focused on a quantitative exploratory data collection based on an online survey. Three groups of consumerswere identified based on general health interest, perceived benefits of eating seafoods and attitude towards seafoods: Health seekerswho eat seafood for duty; Health seekers and seafood lovers; Lowcommitment to health and indifferent to seafood. Differences among groups related to socio-demographic characteristics, sustainability attitudes, intentions and interest in information about seafood productswere also investigated. In particular, the first two groups are more familiar with sustainable seafood products and more interested in information on these products than the third, both in terms of product origin and seasonality. Consumers belonging to second group show a higher probability to buy seafood products considering this characteristic than the other two groups. Based on the results obtained, a strategic plan could be developed to achieve relevant goals in education, communication and sustainability labelling related with seafood products. Following a preliminary scouting carried out with all the seafood stakeholders, a specific territory to test this approach has been already identified in Torre del Cerrano (Italy). These results have a strong implication for policy makers and educational institutions as they identify differences in attitudes and perceptions among consumers that a

The Welfare Quality® consortium has developed and proposed standard protocols for monitoring farm animal welfare. The uptake of the dairy cattle protocol has been below expectation, however, and it has been criticized for the variable quality of the welfare measures and for a limited number of measures having a disproportionally large effect on the integrated welfare categorization. Aiming for a wide uptake by the milk industry, we revised and simplified the Welfare Quality® protocol into a user-friendly tool for cost- and time-efficient on-farm monitoring of dairy cattle welfare with a minimal number of key animal-based measures that are aggregated into a continuous (and thus discriminative) welfare index (WI). The inevitable subjective decisions were based upon expert opinion, as considerable expertise about cattle welfare issues and about the interpretation, importance, and validity of the welfare measures was deemed essential. The WI is calculated as the sum of the severity score (i.e., how severely a welfare problem affects cow welfare) multiplied with the herd prevalence for each measure. The selection of measures (lameness, leanness, mortality, hairless patches, lesions/swellings, somatic cell count) and their severity scores were based on expert surveys (14–17 trained users of the Welfare Quality® cattle protocol). The prevalence of these welfare measures was assessed in 491 European herds. Experts allocated a welfare score (from 0 to 100) to 12 focus herds for which the prevalence of each welfare measure was benchmarked against all 491 herds. Quadratic models indicated a high correspondence between these subjective scores and the WI (R2 = 0.91). The WI allows both numerical (0–100) as a qualitative (“not classified” to “excellent”) evaluation of welfare. Although it is sensitive to those welfare issues that most adversely affect cattle welfare (as identified by EFSA), the WI should be accompanied with a disclaimer that lists adverse or favorab

Many retailers have expanded and diversified their private label food product assortment by offering premium-quality private label food products such as organic products. With price being identified as the major barrier for organic food purchases, private label organic food products could be a suitable and more affordable alternative for many consumers. While numerous studies have examined consumer preferences for organic food, very few organic food studies have incorporated the concept of private labels. This study addresses this research gap by studying consumer preferences and willingness to pay for national brand and private label organic food using a latent class model. Specifically, this study analyzes consumer preferences for organic eggs and orange juice and the effect of national branding versus private label. Findings show heterogeneity in consumer preferences for production method and brand, with three consumer segments being identified based on their preferences for both juice and eggs. For eggs, about half of the consumers prefer private label and organic production, whereas one-quarter clearly prefers organic, and another quarter is indifferent about the brand and the organic production. For orange juice, the majority (75%) prefer the national brand. In addition, one-quarter of the consumers prefers organic juice, and about one-third values both organic and the national brand.

This research utilizes eye-tracking measures to quantify the visual attention paid to claims for nutrition and sustainability on food concepts. It analyzes whether and to what extent the attention to voluntary nutrition and sustainability claims affects choices. A choice experiment was designed using granola bar concepts where each alternative was described by four attributes for claims related to sustainability, genetic modification, sweetener content, antioxidant content, and price. During the choice experiment, the visit duration was measured using an eye-tracking device as proxy for visual attention. Findings show that sweetener content and genetic modification claims were attended to the most, followed by sustainability claims, antioxidant content claims and price. Results indicate that visual attention to nutrition and sustainability claims affects product choice. More visual attention is associated with a higher choice likelihood. Insights from this study can inform future research on attention and choice in particular with regards to healthy and sustainable food choices. Managerial findings related to the claims tested can be used by practitioners to efficiently and effectively promote the choice of healthy and sustainable food products.