Consumer Attitudes and Preference Exploration towards Fresh-Cut Salads Using Best-Worst Scaling and Latent Class Analysis

Methodological pipeline for monitoring post-harvest quality of leafy vegetables

Plants are primary source of nutrients for humans. However, the nutritional value of vegetables tends to decrease once organ and tissue sinks are detached from the plant. Minimal processing of leafy vegetables involves cutting and washing before packaging and storage. These processing procedures result in stressful conditions and post-harvest disorders senescence-related can also occur. The aim of this work is to define a methodological pipeline to evaluate the "quality" changes of fresh cut leafy vegetables over their shelf-life. At this purpose, intra-species variability has been investigated considering two varieties of Lactuca sativa (var. longifolia and capitata), showing different susceptibility to browning. Since browning mainly depends on phenol oxidation, redox parameters as well as the activity of the enzymes involved in phenol biosynthesis and oxidation have been monitored over storage time. At the same time, the metabolic changes of the lettuce leaves have been estimated as response patterns to chemical sensors. The obtained sensor outputs were predictive of browning-related biological features in a cultivar-dependent manner. The integration of the results obtained by this multivariate methodological approach allowed the identification of the most appropriate quality markers in lettuce leaves from different varieties. This methodological pipeline is proposed for the identification and subsequent monitoring of post-harvest quality of leafy vegetables.

An exploration of what freshness in fruit means to consumers

Perceived freshness is a key determinant of consumers' food choices but remains an imprecisely defined concept. A comprehensive and consumer-centric definition of freshness appears to be lacking, and the present research was situated in this knowledge gap, seeking, in particular, to explore the complexity of freshness in consumers' minds. People from the USA (n = 2092) took part in an online survey and completed a text highlighting task. Herein, participants read a text that described different aspects of freshness and the technologies used to prolong freshness during storage. While reading, they used highlighting functions within the software to indicate text content that they liked/disliked or agreed/disagreed with. The combined results from text highlighting and responses to the open-ended question "Considering the fruit you eat, why is freshness important to you?" confirmed that freshness is a complex construct with multiple dimensions and suggested that the complexity of freshness extends from food in general to specific product categories (in the case of fruit and apples). Further, the findings showed that freshness is desired by consumers because fruit are perceived as healthier and better tasting. The findings revealed negative attitudes towards stored fruit among participants, but also indicated some acceptance of the fact that some storage was unavoidable. Results provide useful insights to the development for communication strategies to increase consumer acceptance of stored apples and fruits in general.

Analysis of public opinion on food safety in Greater China with big data and machine learning

The Internet contains a wealth of public opinion on food safety, including views on food adulteration, food-borne diseases, agricultural pollution, irregular food distribution, and food production issues. To systematically collect and analyze public opinion on food safety in Greater China, we developed IFoodCloud, which automatically collects data from more than 3,100 public sources. Meanwhile, we constructed sentiment classification models using multiple lexicon-based and machine learning-based algorithms integrated with IFoodCloud that provide an unprecedented rapid means of understanding the public sentiment toward specific food safety incidents. Our best model's F1 score achieved 0.9737, demonstrating its great predictive ability and robustness. Using IFoodCloud, we analyzed public sentiment on food safety in Greater China and the changing trend of public opinion at the early stage of the 2019 Coronavirus Disease pandemic, demonstrating the potential of big data and machine learning for promoting risk communication and decision-making.

Which Factors Drive Consumer Decisions during Milk Purchase? New Individuals' Profiles Considering Fresh Pasteurized and UHT Treated Milk

The cow’s milk market is going through a critical period characterised by a continuous contraction in consumption as a consequence of the lack of competitiveness on the market of the conventional product (commodity) versus numerous specialties. This paper aimed to define the profiles of milk consumers in terms of individual preferences (assessed using the best-worst scaling methodology) and socio-demographic features. A survey was conducted in several stores of large-scale retail, convenience stores, and open-air markets distributed in north-west Italy to collect data from 1216 respondents. For milk shopper purchasing habits, two consumer groups were defined and compared in terms of preferences: the fresh pasteurized milk consumer (FPc) (56% of the total sample) and the ultra-high temperature treated milk consumer (UHT_c) (35%). A series of two-ways multivariate analysis of variance (MANOVA) were conducted to assess the effect of individuals’ socio-demographic characteristics and the type of milk chosen on the consumer preferences, simultaneously. Significant differences in milk purchasing habits and preferences emerged when comparing the two consumer groups (UHT_c and FP_c). Empirical evidence of the study supported the starting hypothesis, suggesting the significance or relevance of the consumer socio-demographic characteristic, as well as their interaction effect with the type of milk on the level of importance given to the considered milk quality attributes. On the contrary, the gender results were not significant for the milk preferences definition. The assessment of consumer preferences, associated with the individuals’ socio-demographic characteristics could have important implications for outlining more effective marketing strategies based on a more targeted communication (i.e., related to the sustainability dimension of the local product, nutritional value and brand), leading the consumer back to the commodity rediscovery concerning individuals’ features and habits.

Social media and unhealthy food nexus: Evidence from Saudi Arabia

This study assesses consumers' preference for food from social media on a sample of 510 respondents from the Eastern region of Saudi Arabia using the Best-Worst Scaling method. The findings of the study conclude that unhealthy and nutrient-poor food items are more preferred than healthy and nutrient-rich food items. The study recommends that the food and drug authority should intervene to increase consumers' awareness about the effect of unhealthy food items by creating social media accounts to warn consumers about the health outcomes of consuming certain unhealthy foods marketed through social media platforms.

Physiological and Nutraceutical Quality of Green and Red Pigmented Lettuce in Response to NaCl Concentration in Two Successive Harvests

Nutritional eustress such as salinity or nutrient stress applied in soilless systems, is a convenient pre-harvest factor efficient in modulating the phytochemical components of horticultural crops, by triggering defensive mechanisms and accumulating plant secondary metabolites in plants tissues. Nevertheless, genetic material (cultivars with different pigmentation) dictates lettuce metabolites and physiological response to extrinsic eustress, with red leaf cultivars being highly nutrient packed notwithstanding the stress. Product quality can be meliorated equally by applying several cuts, a practice proven to increase bioactive compounds accumulation. In this study, we analyzed the effects of four salinity levels (1, 10, 20 and 30 mM NaCl) on green and red pigmented Salad Bowl lettuce (Lactuca sativa L. var. acephala) in two successive harvests cultivated in a floating raft system. The morphological parameters, mineral composition, leaf gas exchanges, bioactive compounds, and antioxidant activity of both cultivars were assessed. The green cultivar exhibited superior crop productivity but was more prone to salinity effect than the red cultivar. Irrespective of cultivar and cut order, the net photosynthesis decreased with increasing salinity in the nutrient solution. The second cut incurred higher dry biomass, greater accumulation of most minerals and higher photosynthetic activity. In red lettuce, 20 mM NaCl proved adequate eustress to increase phytonutrients and beneficial minerals (K, Ca, and Mg) with minimal loss of yield. Mild salinity and sequential harvest have proven effective pre-harvest tools in positively modulating the quality of lettuce. Eustress interaction with genotype was demonstrated as a promising field for future breeding programs targeting select genotypes for agronomic application of eustress to improve the nutraceutical value of vegetable crops.