Properties and Applications of Morinda citrifolia (Noni): A Review

Morinda citrifolia commonly known as noni is a perennial plant originating in Southeast Asia, consumed over 2000 years. Due to its versatility of adaptation and use of the structures of the plant for different therapeutic purposes, noni attracted the attention of researchers from the pharmaceutical and food industry. Chemical and nutritional analyzes already performed in M. citrifolia reveal the existence of more than 200 phytochemical substances with bioactive properties such as acids, alcohols, phenols, saccharides, anthraquinones, carotenoids, esters, triterpenoids, flavonoids, glycosides, lactones, iridoids, ketones, lactones, lignans, nucleosides, triterpenides, sterols, and aromatic compounds. The high nutritional value of M. citrifolia may induce therapeutic effects, including antimicrobial and antioxidant properties. The main industrial products from this plant are beverages (juice drinks), powders (from dried fruits), oil (from seeds), and leaf powders. Biological and phytotherapeutic applications of M. citrifolia are promising, but more extensive studies are still required. Thus, this review aims to gather updated and comprehensive information on Morinda citrifolia, discussing its traditional use, biochemical, phytotherapics, and toxicological properties, as well as the recent advances in the processing and standardization of products derived from noni fruit.     

Natural Antifungal Peptides/Proteins as Model for Novel Food Preservatives

A large range of ingredients for food and food products are subject to fungal contamination, which is a major cause of destruction of crops, exposure of animals and humans to invasive mycotoxins, and food spoilage. The resistance of fungal species to common preservation methods highlights the necessity of new ways to increase the shelf life of raw material for food and food products. Antimicrobial peptides and proteins (AMPs) are essential members of the immune system of most living organisms. Due to their broad range of activity and their stability to commonly used food processes, they represent promising alternatives to traditional preservatives. However, despite the growing number of reports of potential food applications of these AMPs, the number of approved peptides is low. Poor solubility, toxicity, and a time‐consuming extraction are hurdles that limit their application in food products. Thanks to a deep understanding of the key determinants of their activity, the development of optimized synthetic peptides has reduced these drawbacks. This review presents natural and synthetic antifungal peptides/proteins (AFPs), effective against food‐related fungi, with particular emphasis on AFPs from plant sources. The design of novel antifungal peptides via key elements of antifungal activity is also reviewed. The potential applications of natural and synthetic AFPs as novel antifungal food preservatives are finally discussed.     

Brazilian Artisanal Cheeses: An Overview of their Characteristics,Main Types and Regulatory Aspects

A large variety of cheeses exist in Brazil, reflecting historical and cultural aspects. Brazilian artisanal cheeses present differences in the processing, ripening time (when applied), type of milk used, texture, size, shape, color, moisture content, flavor, the use or not of starter cultures, among others. This review describes the main artisanal cheeses produced in Brazil, focusing on general and particular characteristics associated with their making process and geographical identity. Overall, the high variability of the physicochemical data and deficiency of information on sensorial properties of Brazilian artisanal cheeses were noticed. On the other hand, culture‐dependent methods were mostly used to expand the knowledge into the microbiology of these cheeses, whereas their microbial diversity has been recently discovered through the use of 16S rRNA gene sequencing‐based methods. The certification of a geographical indication for Brazilian artisanal cheeses may encompass an essential milestone for adding value to these products. Regardless of their significance in the diet, culture, and economy of producing regions, taken together, the reviewed literature discloses the need of insightful studies to generate scientific data to support the expansion of the market, while ensuring the protection of historic aspects related to the production of Brazilian artisanal cheeses.     

Meta‐Analysis for Correlating Structure of Bioactive Peptides in Foods of Animal Origin with Regard to Effect and Stability

Amino acid (AA) sequences of 807 bioactive peptides from foods of animal origin were examined in order to correlate peptide structure with activity (antihypertensive, antioxidative, immunomodulatory, antimicrobial, hypolipidemic, antithrombotic, and opioid) and stability in vivo. Food sources, such as milk, meat, eggs, and marine products, show different frequencies of bioactive peptides exhibiting specific effects. There is a correlation of peptide structure and effect, depending on type and position of AA. Opioid peptides contain a high percentage of aromatic AA residues, while antimicrobial peptides show an excess of positively charged AAs. AA residue position is significant, with those in the first and penultimate positions having the biggest effects on peptide activity. Peptides that have activity in vivo contain a high percentage (67%) of proline residues, but the positions of proline in the sequence depend on the length of the peptide. We also discuss the influence of processing on activity of these peptides, as well as methods for predicting release from the source protein and activity of peptides.     

Application of Deep Learning in Food: A Review

Deep learning has been proved to be an advanced technology for big data analysis with a large number of successful cases in image processing, speech recognition, object detection, and so on. Recently, it has also been introduced in food science and engineering. To our knowledge, this review is the first in the food domain. In this paper, we provided a brief introduction of deep learning and detailedly described the structure of some popular architectures of deep neural networks and the approaches for training a model. We surveyed dozens of articles that used deep learning as the data analysis tool to solve the problems and challenges in food domain, including food recognition, calories estimation, quality detection of fruits, vegetables, meat and aquatic products, food supply chain, and food contamination. The specific problems, the datasets, the preprocessing methods, the networks and frameworks used, the performance achieved, and the comparison with other popular solutions of each research were investigated. We also analyzed the potential of deep learning to be used as an advanced data mining tool in food sensory and consume researches. The result of our survey indicates that deep learning outperforms other methods such as manual feature extractors, conventional machine learning algorithms, and deep learning as a promising tool in food quality and safety inspection. The encouraging results in classification and regression problems achieved by deep learning will attract more research efforts to apply deep learning into the field of food in the future.     

口服液类保健食品中18种重金属元素检测

本文旨在建立一种基于微波消解-电感耦合等离子质谱(Inductively coupled plasma mass spectrometry,ICP-MS)测定源于中草药的口服液类保健食品中18种重金属元素(Pb、Cd、As、Hg、Cu、Pt、Pd、Ir、Rh、Ru、Os、Mo、Ni、Cr、V、Mn、Fe、Zn)的方法。采用微波消解法处理口服液样品,以Ge、In、Bi元素作为校正基体效应与信号漂移的内标元素,使用ICP-MS对十批样品中18种重金属进行含量测定。结果显示18种重金属标准曲线线性关系良好,R2≥0.999,各元素的检出限在0.0001～2.743 ng/mL之间,精密度RSD在0.49%～4.29%之间,重复性RSD值在1.2%～15%之间,加样回收率在82.74%～122.7%之间;检测两种口服液中18种重金属元素均未超标。表明该方法操作简便、分析速度快、灵敏度高、准确性好,适用于口服液类保健食品中重金属检测,可为保健食品安全性评价提供依据。     

超高效液相色谱-四极杆/静电场轨道阱高分辨质谱快速筛查测定几种食品中的8种碱性色素

本文研究了超高效液相色谱-四极杆/静电场轨道阱高分辨质谱法快速测定面包、橙汁、卤豆干等食品中8种碱性色素的方法。样品用乙酸乙酯提取后,以C18(3.0 mm×100 mm,1.8μm)色谱柱分离,乙腈和10 mmol/L乙酸铵水溶液为流动相梯度洗脱,在正负离子切换模式下检测8种碱性色素。在全扫描模式下提取8种碱性色素的保留时间和一级母离子精确质量数以及同位素丰度比,实现对食品中8种碱性色素的快速测定;以自动触发采集的二级碎片离子精确质量数进行确证。8种碱性线性关系较好,相关系数(R2)大于0.99,回收率在82.2%～105.3%之间,相对标准偏差在6.0%～9.9%之间。该方法简单、快速、可靠,可定性筛查和定量分析食品中8种碱性色素。     

QuEChERS-UPLC-MS/MS测定焙烤食品中4种链格孢菌毒素

建立了超高效液相色谱-串联质谱法测定焙烤食品中4种链格孢菌毒素(腾毒素、链格孢菌酚、交链胞酚单甲醚、细交链胞菌酮酸)快速检测方法。样品经乙腈-0.1 mol/L盐酸溶液超声萃取,萃取液经QuEChERS净化处理,在RP18色谱柱(2.1 mm×100mm,1.7μm)上以乙腈和1 mmol/L碳酸氢铵为流动相梯度洗脱,采用电喷雾离子源、正负离子多反应监测模式检测,外标法定量。结果表明,4种待测物在相应的浓度范围内线性良好,相关系数均大于0.999;方法定量限(S/N≥10)为0.03～0.3μg/kg;进行3个水平的添加回收实验,平均回收率(n=6)为83.2%～105.3%;相对标准偏差(RSD,n=6)为1.2%～6.4%。应用本方法检测45个焙烤食品样品,4种真菌毒素均有检出。其中24份样品检出AME,含量为0.1～4.6μg/kg;6份样品检出AOH,含量为0.47～1.5μg/kg;27份样品检出Te A,含量为0.6～3.7μg/kg;9份样品检出TEN,含量为0.3～2.1μg/kg。