A review: Integration of NIRS and chemometric methods for tea quality control-principles, spectral preprocessing methods, machine learning algorithms, research progress, and future directions.

With the steady rise in tea production, the need for effective tea quality monitoring has become increasingly pressing. Traditional sensory evaluation and wet chemical detection methods are insufficient for real-time tea quality monitoring. As an emerging technology, near infrared spectroscopy (NIRS) offers numerous advantages, such as preserving sample integrity, generating objective results, and enabling rapid, straightforward assessments.

Exploring the colorimetric sensing mechanism of metal porphyrin on the degree of roasting from the perspective of density functional theory.

Aroma quality is a key indicator of the degree of roasting of large-leaf yellow tea (LYT). In this study, a colorimetric sensing array (CSA) composed of tetraphenylporphyrin (TPP) was designed for the rapid quantitative detection of key volatile organic compounds (VOCs) in LYT. First, the responses of the CSA system were compared under three environmental conditions.

Simultaneous detection of mixed colorants adulterated in black tea based on various morphological SERS sensors.

Colorant adulteration is a common problem in tea safety control; thus, a rapid identification method is required. In this study, we optimized the fabrication parameters of various sensors to enhance their performance. R6G was used as a probe molecule, demonstrating that the sensnor remained stable for 120 days.

Revealing the differences in aroma of black tea under different drying methods based on GC-MS, GC-O.

Drying greatly affects the aroma of black tea. In this study, the differences in aroma of black tea under hot-air drying (HD), sun drying (SD), and pan-fired drying (PD) were investigated through quantitative descriptive analysis. Headspace solid-phase microextraction and solvent assisted flavor evaporation combined with gas chromatography-mass spectrometry and gas chromatography-olfactory were used to analyze the overall aroma profile of black tea.

Monitoring quality changes in green tea during storage: A hyperspectral imaging method.

The quality of green tea deteriorates the longer it is stored. However, there is a lack of accurate and rapid methods for determining the storage period of tea. In this study, hyperspectral imaging (HSI) was used to determine the storage period of green teas stored at 4 °C (set 1) and 25 °C (set 2), and to quantify and visualize the main chemical components (e.

E-nose and colorimetric sensor array combining homologous data fusion strategy discriminating the roasting degree of large-leaf yellow tea.

Different degrees of roasting result in differences in the quality and flavor of large-leaf yellow tea. The current sensory evaluation and chemical detection methods cannot meet the requirement of online differentiation of LYT roasting degree, so an accurate and comprehensive assessment method needs to be developed urgently. First, the two aroma sensing technologies were compared.

Rapid and comprehensive grade evaluation of Keemun black tea using efficient multidimensional data fusion.

To develop a comprehensive evaluation method for Keemun black tea, we used micro-near-infrared spectroscopy, computer vision, and colorimetric sensor array to collect data. We used support vector machine, least-squares support vector machine (LS-SVM), extreme learning machine, and partial least squares discriminant analysis algorithms to qualitatively discriminate between different grades of tea. Our results indicated that the LS-SVM model with mid-level data fusion attained an accuracy of 98.

Cytokine-armed dendritic cell progenitors for antigen-agnostic cancer immunotherapy.

Dendritic cells (DCs) are antigen-presenting myeloid cells that regulate T cell activation, trafficking and function. Monocyte-derived DCs pulsed with tumor antigens have been tested extensively for therapeutic vaccination in cancer, with mixed clinical results. Here, we present a cell-therapy platform based on mouse or human DC progenitors (DCPs) engineered to produce two immunostimulatory cytokines, IL-12 and FLT3L.

Predicting the storage time of green tea by myricetin based on surface-enhanced Raman spectroscopy.

The quality of green tea changes rapidly due to the oxidation and degradation of polyphenols during storage. Herein, a simple and fast Surface-enhanced Raman spectroscopy (SERS) strategy was established to predict changes in green tea during storage. Raman spectra of green tea with different storage times (2020-2015) were acquired by SERS with silver nanoparticles.

A rapid aroma quantification method: Colorimetric sensor-coupled multidimensional spectroscopy applied to black tea aroma.

Aroma affects the quality of black tea, and the rapid evaluation of aroma quality is the key to realize the intelligent processing of black tea. A simple colorimetric sensor array coupled with a hyperspectral system was proposed for the rapid quantitative detection of key volatile organic compounds (VOCs) in black tea. Feature variables were screened based on competitive adaptive reweighted sampling (CARS).

Monitoring the baking quality of Tieguanyin via electronic nose combined with GC-MS.

Roasting is extremely important for Tieguanyin oolong tea production because it strongly affects its chemical composition and sensory quality. In addition, there were significant differences in the preference for roasted tea among different people. However, the effect of roasting degree on the aroma characteristics and flavor quality of Tieguanyin tea is still unclear.

Rapid detection of multiple colorant adulteration in Keemun black tea based on hemp spherical AgNPs-SERS.

This study synthesized stable and sensitive hemp spherical AgNPs as the SERS substrate for the simultaneous and rapid detection of sunset yellow, lemon yellow, carmine and erythrosine adulteration in black tea. With R6G as the probe molecule, the AgNPs were determined to have satisfactory stability over 60 days with an enhancement factor of 10. The effects of three variable screening methods on model performance were compared.

Sensomics analysis of the effect of the withering method on the aroma components of Keemun black tea.

Withering is a key process that affects the aroma of Keemun black tea (KBT). In this study, the aroma composition of KBT through natural withering, sun withering, and warm-air withering was analysed using gas chromatography-mass spectrometry. The results revealed significant differences in the three samples.

Rapid monitoring of black tea fermentation quality based on a solution-phase sensor array combined with UV-visible spectroscopy.

Rapid monitoring of fermentation quality has been the key to realizing the intelligent processing of black tea. In our study, mixing ratios, sensing array components and reaction times were optimized before an optimal solution phase colorimetric sensor array was constructed. The characteristic spectral information of the array was obtained by UV-visible spectroscopy and subsequently combined with machine learning algorithms to construct a black tea fermentation quality evaluation model.

Rapid and real-time detection of black tea fermentation quality by using an inexpensive data fusion system.

Intelligent identification of black tea fermentation quality is becoming a bottleneck to industrial automation. This study presents at-line rapid detection of black tea fermentation quality at industrial scale based on low-cost micro-near-infrared spectroscopy (NIRS) and laboratory-made computer vision system (CVS). High-performance liquid chromatography and a spectrophotometer were used for determining the content of catechins and theaflavins, and the color of tea samples, respectively.

Quality evaluation of Keemun black tea by fusing data obtained from near-infrared reflectance spectroscopy and computer vision sensors.

Keemun black tea is classified into 7 grades according to the difference in its quality. The appearance and flavour are crucial indicators of its quality. This research demonstrates a rapid grading method of jointly using near-infrared reflectance spectroscopy (NIRS) and computer vision systems (CVS) to evaluate the flavour and appearance quality of tea.

Green analytical assay for the quality assessment of tea by using pocket-sized NIR spectrometer.

Rapid and low-cost testing tools provide new methods for the evaluation of tea quality. In this study, a micro near-infrared (NIR) spectrometer was used for the qualitative and quantitative evaluation of tea. A total of 360 tea samples consisting of black, green, yellow, and oolong tea were collected from different countries.

Potential of smartphone-coupled micro NIR spectroscopy for quality control of green tea.

Green tea adulterated with sugar and glutinous rice flour has an increased sensitivity to water, which affects the safety of the tea. A total of 475 samples of pure tea, sugar-adulterated tea, and glutinous-rice-flour-adulterated tea were prepared and scanned using micro near infrared spectroscopy (NIRS). The collected NIRS data were qualitatively and quantitatively detected by a multi-layer algorithm model.

Evaluation of black tea by using smartphone imaging coupled with micro-near-infrared spectrometer.

Tea quality is generally assessed through panel sensory evaluation, which requires elaborate sample preparation steps. Here, a novel and low-cost evaluation method of using smartphone imaging coupled with micro-near-infrared (NIR) spectrometer based on digital light processing is proposed to classify the quality grades of Keemun black tea. RGB color information was obtained by Image J software, eight texture characteristics, including scheme, contrast, dissimilarity, entropy, correlation, second moment and variance, and homogeneity were obtained by ENVI software based on co - occurrence method from smartphone images, and spectral data were preprocessed with standard normal variate.

Quality assessment of instant green tea using portable NIR spectrometer.

Caffeine and catechin are two main components of instant green tea, and are essential components of tea quality. This paper mainly focuses on the feasibility of rapidly determining instant green tea components by using a portable near infrared (NIR) spectrometer. The two main components (caffeine and catechin) were studied.

Micro-NIR spectrometer for quality assessment of tea: Comparison of local and global models.

Near-infrared (NIR) spectroscopy is an effective tool for analyzing components relevant to tea quality, especially catechins and caffeine. In this study, we predicted catechins and caffeine content in green and black tea, the main consumed tea types worldwide, by using a micro-NIR spectrometer connected to a smartphone. Local models were established separately for green and black tea samples, and these samples were combined to create global models.

Qualitative discrimination of Chinese dianhong black tea grades based on a handheld spectroscopy system coupled with chemometrics.

The evaluation of Chinese dianhong black tea (CDBT) grades was an important indicator to ensure its quality. A handheld spectroscopy system combined with chemometrics was utilized to assess CDBT from eight grades. Both variables selection methods, namely genetic algorithm (GA) and successive projections algorithm (SPA), were employed to acquire the feature variables of each sample spectrum.

Rapid detection of quality index of postharvest fresh tea leaves using hyperspectral imaging.

Background: The quality of fresh tea leaves after harvest determines, to some extent, the quality and price of commercial tea. A fast and accurate method to evaluate the quality of fresh tea leaves is required.

Results: In this study, the potential of hyperspectral imaging in the range of 328-1115 nm for the rapid prediction of moisture, total nitrogen, crude fiber contents, and quality index value was investigated.