Emerging techniques for determining the quality and safety of tea products: A review

Non-invasive anticipation of infusion taste in fine-manipulated green teas through hyperspectral appearance analysis guided by ECG content

The high catechin content in summer-to-autumn tea leaves often results in strong, unpleasant tastes, leading to significant resource waste and economic losses due to lignification of unpicked leaves. This study aims to improve the taste quality of summer-to-autumn green teas by combining fine manipulation techniques with hyperspectral observation. Fine manipulation notably enhanced infusion taste quality, particularly in astringency and its aftertaste (aftertasteA). Using Partial Least Squares Discriminant Analysis (PLSDA) on hyperspectral data, 100% prediction accuracy was achieved for dry tea appearance in the near-infrared spectrum. Astringency and aftertasteA correlated with hyperspectral data, allowing precise estimation with over 90% accuracy in both visible and near-infrared spectrums. Epicatechin gallate (ECG) emerged as a key taste compound, enabling non-invasive taste prediction. Practical applications in processing and quality control are demonstrated by the derived equations (Astringency = -0.88 × ECG + 45.401, AftertasteA = -0.353 × ECG + 18.609), highlighting ECG's role in shaping green tea taste profiles.

Advances in Chromatographic Analysis of Phenolic Phytochemicals in Foods: Bridging Gaps and Exploring New Horizons

Chromatographic analysis of phenolic phytochemicals in foods has significantly advanced over the past decade (2014-2024), meeting increasing demands for precision and efficiency. This review covers both conventional and advanced chromatographic techniques used for detecting phenolic phytochemicals in foods. Conventional methods like High-Performance Liquid Chromatography, Ultra High-Performance Liquid Chromatography, Thin-Layer Chromatography, and Gas Chromatography are discussed, along with their benefits and limitations. Advanced techniques, including Hydrophilic Interaction Liquid Chromatography, Nano-LC, Multidimensional Liquid Chromatography, and Capillary Electrophoresis, are highlighted for their innovations and improved capabilities. The review addresses challenges in current chromatographic methods, emphasizing the need for standardized and validated procedures according to the Food and Drug Administration, European Cooperation for Accreditation of Laboratories, and The International Organization for Standardization guidelines to ensure reliable and reproducible results. It also considers novel strategies for reducing the environmental impact of chromatographic methods, advocating for sustainable practices in analytical chemistry.

Combining AI Tools with Non-Destructive Technologies for Crop-Based Food Safety: A Comprehensive Review

On a global scale, food safety and security aspects entail consideration throughout the farm-to-fork continuum, considering food's supply chain. Generally, the agrifood system is a multiplex network of interconnected features and processes, with a hard predictive rate, where maintaining the food's safety is an indispensable element and is part of the Sustainable Development Goals (SDGs). It has led the scientific community to develop advanced applied analytical methods, such as machine learning (ML) and deep learning (DL) techniques applied for assessing foodborne diseases. The main objective of this paper is to contribute to the development of the consensus version of ongoing research about the application of Artificial Intelligence (AI) tools in the domain of food-crop safety from an analytical point of view. Writing a comprehensive review for a more specific topic can also be challenging, especially when searching within the literature. To our knowledge, this review is the first to address this issue. This work consisted of conducting a unique and exhaustive study of the literature, using our TriScope Keywords-based Synthesis methodology. All available literature related to our topic was investigated according to our criteria of inclusion and exclusion. The final count of data papers was subject to deep reading and analysis to extract the necessary information to answer our research questions. Although many studies have been conducted, limited attention has been paid to outlining the applications of AI tools combined with analytical strategies for crop-based food safety specifically.

The Cultivar Effect on the Taste and Aroma Substances of Hakka Stir-Fried Green Tea from Guangdong

The flavor and quality of tea largely depends on the cultivar from which it is processed; however, the cultivar effect on the taste and aroma characteristics of Hakka stir-fried green tea (HSGT) has received little attention. High-performance liquid chromatography (HPLC), gas chromatography-mass spectrometry (GC-MS), and sensory evaluations were used to detect and predict the essential taste and aroma-contributing substances of HSGTs made from Huangdan (HD), Meizhan (MZ) and Qingliang Mountain (QL) cultivars. Orthogonal partial least squares data analysis (OPLS-DA) ranked four substances that putatively distinguished the tastes of the HSGTs, epigallocatechin gallate (EGCG) > theanine > epigallocatechin (EGC) > epicatechin gallate (ECG). Ten substances with variable importance in projections (VIPs) ≥ 1 and odor activation values (OAVs) ≥ 1 contributed to their overall aromas, with geranylacetone having the most significant effect on HD (OAV 1841), MZ (OAV 4402), and QL (OAV 1211). Additionally, sensory evaluations found that HD was relatively equivalent to QL in quality, and both were superior to MZ. HD had a distinct floral aroma, MZ had a distinct fried rice aroma, and QL had a balance of fried rice and fresh aromas. The results provide a theoretical framework for evaluating the cultivar effect on the quality of HSGT and put forward ideas for future HSGT cultivar development.

Effects of processing procedures on the formation of aroma intensity and odor characteristic of Benshan tea (Oolong tea, Camellia sentences)

Benshan tea is a kind of oolong tea, and Benshan (Camellia sinensis) tea tree originates from Anxi County of Fujian Province in China, which is a national tea tree breed. Tea processing is the key to the formation of its odor characteristics. It is extremely important to step by step analyze effects of tea processing on aroma intensity and the formation of odor characteristics for optimizing tea processing process and improving tea quality. The results of this study showed that processing resulted in a significant increase in the content of volatile compounds in tea leaves, i.e., from 25.213 μg/kg to 111.223 μg/kg, in which the volatile compounds were mainly terpenoids. Secondly, the analysis found that 20 kinds of key compounds constituted to odor characteristics of Benshan tea leaves, among which geraniol, trans-β-ionone, gerol, citronellol, benzeneacetaldehyde, and trans-nerolidol were the most key six. Floral and fruity aromas, especially floral aroma, mainly formed odor characteristics of Benshan tea after processing, while floral aroma mainly came from the contribution of geraniol, which was the foremost compound in the formation of floral aroma of Benshan tea.

Effect of processing on aroma intensity and odor characteristics of Shuixian (Camellia sinensis) tea

Processing is extremely important for the formation of aroma characteristic of tea leaves. In this study, the effects of processing on the content of volatile compounds, aroma intensity and odor characteristic of Shuixian tea were analyzed. The results showed that the content of volatile compounds in Shuixian tea increased significantly after processing, among which terpenoids and esters were the highest. There were 18 key compounds constituting the aroma characteristics of Shuixian tea, among which geraniol and nerol were the most important compounds, which contributed 96.28% to the aroma of Shuixian tea. The odor characteristics of Shuixian tea were mainly floral and fruity and the contribution of floral mainly came from geraniol, while fruity mainly came from nerol. Geraniol and nerol compounds increased rapidly after the withering process of tea leaves. This study provided an important reference for the improvement of processing technology and quality enhancement of Shuixian tea.

Topics and trends in fresh tea (Camellia sinensis) leaf research: A comprehensive bibliometric study

Tea plant (Camellia sinensis) is a widely cultivated cash crop and tea is a favorite functional food in the world. Fresh tea leaves (FTLs) play a critical role in bridging the two fields closely related to tea cultivation and tea processing, those are, tea plant biology and tea biochemistry. To provide a comprehensive overview of the development stages, authorship collaboration, research topics, and hotspots and their temporal evolution trends in the field of FTLs research, we conducted a bibliometric analysis, based on 971 publications on FTLs-related research published during 2001-2021 from Web of Science Core Collection. CiteSpace, R package Bibliometrix, and VOSviewer were employed in this research. The results revealed that the development history can be roughly divided into three stages, namely initial stage, slow development stage and rapid development stage. Journal of Agricultural & Food Chemistry published most articles in this field, while Frontiers in Plant Science held the highest total citations and h-index. The most influential country, institution, and author in this field was identified as China, the Chinese Academy of Agricultural Sciences, and Xiaochun Wan, respectively. FTLs-related research can be categorized into three main topics: the regulation mechanism of key genes, the metabolism and features of essential compounds, and tea plants' growth and stress responses. The most concerning hotspots are the application of advanced technologies, essential metabolites, leaf color variants, and effective cultivation treatments. There has been a shift from basic biochemical and enzymatic studies to studies of molecular mechanisms that depend on multi-omics technologies. We also discussed the future development in this field. This study provides a comprehensive summary of the research field, making it easier for researchers to be informed about its development history, status, and trends.

NIR Spectrometric Approach for Geographical Origin Identification and Taste Related Compounds Content Prediction of Lushan Yunwu Tea

Lushan Yunwu Tea is one of a unique Chinese tea series, and total polyphenols (TP), free amino acids (FAA), and polyphenols-to-amino acids ratio models (TP/FAA) represent its most important taste-related indicators. In this work, a feasibility study was proposed to simultaneously predict the authenticity identification and taste-related indicators of Lushan Yunwu tea, using near-infrared spectroscopy combined with multivariate analysis. Different waveband selections and spectral pre-processing methods were compared during the discriminant analysis (DA) and partial least squares (PLS) model-building process. The DA model achieved optimal performance in distinguishing Lushan Yunwu tea from other non-Lushan Yunwu teas, with a correct classification rate of up to 100%. The synergy interval partial least squares (siPLS) and backward interval partial least squares (biPLS) algorithms showed considerable advantages in improving the prediction performance of TP, FAA, and TP/FAA. The siPLS algorithms achieved the best prediction results for TP (R_P = 0.9407, RPD = 3.00), FAA (R_P = 0.9110, RPD = 2.21) and TP/FAA (R_P = 0.9377, RPD = 2.90). These results indicated that NIR spectroscopy was a useful and low-cost tool by which to offer definitive quantitative and qualitative analysis for Lushan Yunwu tea.

Lightweight tea bud recognition network integrating GhostNet and YOLOv5

Aiming at the problems of low detection accuracy and slow speed caused by the complex background of tea sprouts and the small target size, this paper proposes a tea bud detection algorithm integrating GhostNet and YOLOv5. To reduce parameters, the GhostNet module is specially introduced to shorten the detection speed. A coordinated attention mechanism is then added to the backbone layer to enhance the feature extraction ability of the model. A bi-directional feature pyramid network (BiFPN) is used in the neck layer of feature fusion to increase the fusion between shallow and deep networks to improve the detection accuracy of small objects. Efficient intersection over union (EIOU) is used as a localization loss to improve the detection accuracy in the end. The experimental results show that the precision of GhostNet-YOLOv5 is 76.31%, which is 1.31, 4.83, and 3.59% higher than that of Faster RCNN, YOLOv5 and YOLOv5-Lite respectively. By comparing the actual detection effects of GhostNet-YOLOv5 and YOLOv5 algorithm on buds in different quantities, different shooting angles, and different illumination angles, and taking F1 score as the evaluation value, the results show that GhostNet-YOLOv5 is 7.84, 2.88, and 3.81% higher than YOLOv5 algorithm in these three different environments.

Mycotoxins in Tea ((Camellia sinensis (L.) Kuntze)): Contamination and Dietary Exposure Profiling in the Chinese Population

Tea is popular worldwide with multiple health benefits. It may be contaminated by the accidental introduction of toxigenic fungi during production and storage. The present study focuses on potential mycotoxin contamination in tea and the probable dietary exposure assessments associated with consumption. The contamination levels for 16 mycotoxins in 352 Chinese tea samples were determined by ultra-performance liquid chromatography-tandem mass spectrometry. Average concentrations of almost all mycotoxins in tea samples were below the established regulations, except for ochratoxin A in the dark tea samples. A risk assessment was performed for the worst-case scenarios by point evaluation and Monte Carlo assessment model using the obtained mycotoxin levels and the available green, oolong, black, and dark tea consumption data from cities in China. Additionally, we discuss dietary risk through tea consumption as beverages and dietary supplements. In conclusion, there is no dietary risk of exposure to mycotoxins through tea consumption in the Chinese population.

Health Hazard Assessment Due to Slimming Medicinal Plant Intake

According to the World Health Organization (WHO), about 80% of people rely on medicinal plants for their primary health needs. Traditional medicine's principal benefits are their vast population knowledge, low severe adverse effects rate, low cost, and the lack of a medical prescription to use them. While obesity has become a global health issue, an increase in finding cheap and fast ways to lose weight escalates medicinal herbs' use for this purpose, both in dietary supplements or in teas. At the same time that Brazil aims to expand traditional medicine, reports regarding toxicology and poisoning put natural products' safety in check. Plants can accumulate heavy metals and metalloids leading to health risks; however, there is a lack of information on that matter, possibly due to a lack of international standardization regarding elemental contamination - this study aimed to determine metal and metalloid concentrations in slimming medicinal plants and their respective teas and evaluate their safety consumption. Metal and metalloid content were determined by inductively coupled plasma optical emission spectrometry (ICP OES). All plants and teas were within the set limits for tolerable upper intake level (UL), provisional tolerable daily maximum intake (PTDMI), and provisional tolerable weekly intake (PTWI). The hazard quotient index (HQ) was above 1 for almost all plants, and the Hibiscus sabdariffa tea regarding aluminum content. The arsenic level was above the Brazilian Pharmacopeia limit in natura plants demonstrating risk in their consumption. Some herbs also presented detection for elements with no safety limits set, such as lead, cadmium, and arsenic, which could mark as a red flag for consumption once their security intake is not precise yet.