Advances in Food and Nutrition Research最新文献

Ancient grains have remained relatively unchanged by modern breeding practices, which are notable for their nutrient density. They have a variety of essential vitamins, minerals, and bioactive compounds as well as a rich fiber content. Consumers are interested in incorporating ancient grain into their diet for the health benefits. However, the availability, high cost and low consumer acceptance limit their application. In this book chapter, we describe the history, types of ancient grains and ancient grain products as well as their sensory properties and sensory evaluation strategies. We also explore marketing and consumer expectations, current product limitations, and future research directions which can help readers better evaluate the market potential of ancient grains. This chapter provides evidence and resources supporting the use of ancient grain in the development of next-generation cereal-based foods.

Wine is an important global alcoholic beverage produced in many regions, in a wide array of styles, and from different grape varieties. Quality is an important concept for wine production, but that depends on the viewpoint (e.g., winemaker, novice consumer, expert), making it challenging to simply define the quality of wine and the grapes from which it originates. Based on extensive research, however, some consensus on the definition of quality is available, which helps underpin how to measure, evaluate, and control grape and wine quality using chemical and sensory methods. Recently, with the growing demand for simple, rapid, and cost-effective techniques to objectively evaluate the quality of grape, wine, and wine-derived spirits in the wine industry, novel spectroscopic technologies, used in conjunction with chemometrics, have been developed and implemented. Among these, fluorescence spectroscopy has shown advantages as an analytical tool in a number of aspects of grape and wine research and winemaking practice. This chapter provides an overview of the definition of grape and wine quality from different perspectives and summarizes commonly used methods for measurement, evaluation, and control of grape and wine quality after providing an understanding of the chemical components of importance. Finally, the chapter provides an update on the current progress of research and application of fluorescence spectroscopy combined with chemometrics and machine learning devoted to grape and wine analysis, including phenolic detection and prediction, grape maturity monitoring, wine classification, and authentication, among others.

The integration of machine learning (ML) with vibrational spectroscopy has revolutionized the food industry, advancing the ways food quality, authenticity, and safety are analyzed. ML methods, including traditional approaches such as support vector machines (SVMs) and partial least squares regression (PLSR), and advanced deep learning techniques like neural networks (NNs), enable the efficient and precise processing of complex multivariate datasets. Vibrational spectroscopy methods-near-infrared (NIR), mid-infrared (MIR), and Raman spectroscopy- are non-destructive, versatile, and provide detailed molecular insights. The synergy between ML and these spectroscopic techniques has significantly enhanced capabilities for identifying adulterants, quantifying quality indicators, and detecting contaminants in food products. CNNs analyze spectral data to classify products, identify spoilage, and verify food origins, while RNNs excel in capturing sequential spectral patterns for monitoring storage conditions. Portable spectrometers integrated with ML algorithms offer real-time, on-site food analysis, streamlining quality assessments and safety protocols. Despite challenges such as data variability, limited labeled datasets, and the interpretability of deep learning models, advancements in ML, including data augmentation and transfer learning, are addressing these limitations. The combination of ML and vibrational spectroscopy represents a transformative leap for the food industry, providing innovative solutions to global challenges in food security, quality control, and sustainability. As these technologies continue to evolve, they promise to drive significant improvements in food analysis, ensuring safer and higher-quality food products worldwide.

Foodborne diseases affect millions of people globally, resulting in a huge number of hospitalizations and deaths. In this context, laboratory-based research is crucial to identify the major pathogens as well as the relevance of each one for distinct food production chains. Pork meat is very popular, being the most consumed meat in many countries and its inspection at the slaughterhouse is the main component of surveillance to protect consumers. Healthy pigs may carry pathogenic and antibiotic resistant bacteria that can be subsequently transferred to humans through the consumption of contaminated meat. Further, the food processing environment can harbor pathogenic persistent bacteria, representing a risk of cross-contamination to pork meat, demanding strict slaughtering procedures. Among these foodborne bacteria, Salmonella, Yersinia enterocolitica, Escherichia coli, Campylobacter spp., Listeria monocytogenes and Staphylococcus aureus are the most relevant in the pork production chain. Molecular subtyping has been fundamental for pathogen detection and also to track transmission, and nowadays it is a key component of the efforts to prevent and control foodborne diseases. In this chapter, characteristics of these major foodborne bacteria associated to pork meat will be addressed, including their occurrence and importance along the pork production chain, worldwide distribution, typing, as well as control and prevention measures from farm to fork.

In recent years, increasing interest has been in exploring cold plasma applications in agri-food systems beyond bio-decontamination. In the early period, the application of cold plasma in the agri-food sector was focused primarily on microbial inactivation. However, the research perspective has widened due to the multifunctional mechanisms of action attributable to cold plasma, which now encompass applications such as pesticide degradation, seed germination, food functionality, food packaging modifications, and plasma-functionalised liquids. Cold plasma processes can be designed to be cost-effective, sustainable, non-thermal, and offer system and process design versatility. Foods present complex systems consisting of major compounds (water, carbohydrates, proteins, and lipids) and minor compounds (vitamins, minerals, and color). These compounds work individually as well as synergistically, giving sensory, texture, and quality characteristics of food. Understanding the effect of cold plasma on these food matrices and ingredient attributes is significant for its adoption as an alternative food processing technique. A complete understanding of the mechanism of action, interactions with food matrix functionality, and control over the food quality is required to commercialise cold plasma technology.

Beer is the most produced alcoholic beverage globally. It is a paradox of historical views in using the same four ingredients, water, malt, hops and yeast, but continues to be innovative in new beer styles, and technologies. However, near infrared technology has yet to be routinely adopted in brewing. It has been used for decades in testing grain and malt quality, and in more recent times testing hop quality. There are numerous studies showing rapid analysis of worts produced in the first stage of brewing, as well as in finished beer. Typical traits measured in worts are sugars, gravity and amino acids, while in finished beer, alcohol, bitterness and color have been reported. Some of the limitations in measuring beer quality during production is the range of temperatures and differing levels of wort clarity throughout the brewing process and the most appropriate testing is typically at-line on cooled samples which require centrifugation to remove malt, hop or yeast. However recent technologies are showing improved at-line measuring capacity and predicting more traits. The next stage of innovation in brewing will be near infrared applications to assist in real time assessment as well as providing data for long-term quality management.

The consumption of Plant-based Milk Alternatives (PBMAs) is experiencing rapid growth due to evolving food preferences, the rise of veganism, environmental concerns, and issues associated with animal-based milk such as lactose intolerance, milk protein allergy, and galactosemia. PBMAs are beverages derived from the extraction of cereals, nuts, seeds, and legumes, with examples including soy milk, almond milk, oat milk, and various others. Despite the numerous benefits of PBMAs, their nutritional profile differs slightly from animal-based milk, particularly in terms of calcium and protein content. Consequently, fortification of these alternatives using appropriate methods is necessary. The promotion of PBMAs is warranted due to their diverse advantages, including addressing problems related to animal-based milk, reducing economic burden, offering health benefits for conditions like diabetes and cardiovascular diseases, minimizing environmental impact, and reaching populations where livestock management is challenging. This review examines various aspects of PBMAs, including their nutritional profile, associated health benefits, bioavailability concerns, safety profile, and environmental considerations.

Non-thermal treatments are current trends in food safety, the application of these technologies may lessen the influence of heat on food quality. The non-thermal food preservation techniques enable the food industry to meet regulations for product safety and shelf life. Common non-thermal techniques include cold plasma, ionizing radiation, ultraviolet light, pulsed electric fields, and high-pressure processing. This chapter provides a quick summary of the most current uses of these technologies for food preservation. In addition, a succinct description of the process used to inactivate foodborne microorganisms in food has been provided.

This chapter explores the application of omics technologies in food mycology, emphasizing the significant impact of filamentous fungi on agriculture, medicine, biotechnology and the food industry. The chapter delves into the importance of understanding fungal secondary metabolism due to its implications for human health and industrial use. Several omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, are reviewed for their role in studying the genetic potential and metabolic capabilities of food-related fungi. The potential of CRISPR/Cas9 in fungal research is highlighted, showing its ability to unlock the full genetic potential of these organisms. The chapter also addresses the challenges posed by Big Data research in Omics and the need for advanced data processing methods. Through these discussions, the chapter highlights the future benefits and challenges of omics-based research in food mycology and its potential to revolutionize our understanding and utilization of fungi in various domains.