Colorimetric Sensor Array for Monitoring, Modelling and Comparing Spoilage Processes of Different Meat and Fish Foods

Food for Thought: Optical Sensor Arrays and Machine Learning for the Food and Beverage Industry

Arrays of cross-reactive sensors, combined with statistical or machine learning analysis of their multivariate outputs, have enabled the holistic analysis of complex samples in biomedicine, environmental science, and consumer products. Comparisons are frequently made to the mammalian nose or tongue and this perspective examines the role of sensing arrays in analyzing food and beverages for quality, veracity, and safety. I focus on optical sensor arrays as low-cost, easy-to-measure tools for use in the field, on the factory floor, or even by the consumer. Novel materials and approaches are highlighted and challenges in the research field are discussed, including sample processing/handling and access to significant sample sets to train and test arrays to tackle real issues in the industry. Finally, I examine whether the comparison of sensing arrays to noses and tongues is helpful in an industry defined by human taste.

Recent advancements in chemosensors for the detection of food spoilage

The need for reliable sensors has become a major requirement to confirm the quality and safety of food commodities. Chemosensors are promising sensing tools to identify contaminants and food spoilage to ensure food safety. Chemosensing materials are evolving and becoming potential mechanisms to enable onsite and real-time monitoring of food safety. This review summarizes the information about the basic four types of chemosensors (colorimetric, optical, electrochemical, and piezoelectric) employed in the food sector, the latest advancements in the development of chemo-sensing mechanisms, and their food applications, with special emphasis on the future outlook of them. In this review, we discuss the novel chemosensors developed from the year 2018 to 2022 to detect spoilage in some common types of food like fish, meat, milk, cheese and soy sauce. This work will provide a fundamental step toward further development and innovations of chemosensors targeting different arenas in the food industry.

A new cysteamine-copper chemically modified screen-printed gold electrode for glyphosate determination

A chemically modified screen-printed gold electrode has been prepared by covering the electrode surface with a cysteamine-copper self-assembled monolayer (SAM). The sensor was effective for the voltammetric sensing of glyphosate. The method exploits the interaction of glyphosate with copper ions complexed by cysteamine, which results in a decrease in the intensity of copper redox current. Cyclic voltammetry was employed as a measuring technique. When dealing with voltammograms with numerous peaks changing in shape and size, it is difficult to define which signal is the most significant for the analyte determination; in these cases, a helpful approach is chemometrics. In this work, PLS (Partial Least Square regression) has been applied to build models to correlate the signal with the glyphosate concentration in standard aqueous solutions and tap water samples (matrix-matched calibration). The method's figures of merits were evaluated, obtaining a limit of quantification of about 5 μM. The reliability of the proposed sensor was verified by analyzing tap water spiked with glyphosate; recoveries higher than 90 % were achieved.

Advanced technologies in biodegradable packaging using intelligent sensing to fight food waste

The limitation of conventional packaging in demonstrating accurate and real-time food expiration dates leads to food waste and foodborne diseases. Real-time food quality monitoring via intelligent packaging could be an effective solution to reduce food waste and foodborne illnesses. This review focuses on recent technological advances incorporated into food packaging for monitoring food spoilage, with a major focus on paper-based sensors and their combination with smartphone. This review paper offers a comprehensive exploration of advanced macromolecular technologies in biodegradable packaging, a general overview of paper-based probes and their incorporation into food packaging coupled with intelligent sensing mechanisms for monitoring food freshness. Given the escalating global concerns surrounding food waste, our manuscript serves as a pivotal resource, consolidating current research findings and highlighting the transformative potential of these innovative packaging solutions. We also highlight the current intelligent paper-based food freshness sensors and their various advantages and limitations. Examples of implementation of paper-based sensors/probes for food storage and their accuracy are presented. Finally, we examined how intelligent packaging can be an alternative to reduce food waste. Several technologies discussed here have good potential to be used in food packaging for real-time food monitoring, especially when combined with smartphone diagnosis.

Positively Charged Organosilanes Covalently Linked to the Silica Network as Modulating Tools for the Salinity Correction of pH Values Obtained with Colorimetric Sensor Arrays (CSAs)

Seven increasing levels of water salinity from 0.029 to 0.600 M (as NaCl) were used to investigate the dependence of pH measurement, performed using colorimetric sensor arrays (CSAs), on ionic strength. The CSAs were arrays of sensing spots prepared in the form of sol-gel-embedding Bromothymol Blue (BB) and Bromocresol Green (BCG) in a porous nitrocellulose support. The support was impregnated over the entire thickness (≈100 µm), allowing for the signal (Hue) acquisition on the opposite side to the contact with the sample solution. Three CSAs were prepared, M1, M2, and M3. M1 contained a free cationic surfactant, hexadecyltrimethylammonium p-toluenesulfonate (CTApTs), for modulating the pKa of the indicators. In M2, the surfactant dimethyloctadecyl[3-(trimethoxysilyl)propyl]ammonium chloride (DTSACl) was covalently bonded to the sol-gel. M3 was prepared like M2 but using a larger amount of ethanol as the solvent for the synthesis. The modulation of the CTApTs or the DTSACl concentration enabled the tuning of the pKa. In general, the pKa modulation ability decreased with the increase in salinity. The presence of a surfactant covalently linked to the backbone partially reduced the competitiveness of the anionic species, improving the results. Nevertheless, the salt effect was still present, and a correction algorithm was required. Between pH 5.00 and 12.00, this correction could be made automatically by using spots taken as references to produce sensors independent of salinity. As the salt effect is virtually absent above 0.160 M, M2 and M3 can be used for future applications in seawater.

Critical importance of RGB color space specificity for colorimetric bio/chemical sensing: A comprehensive study

The use of the RGB color model in colorimetric chemical sensing via imaging techniques is widely prevalent in the literature. However, the lack of specificity in the selection of RGB color space during capture and analysis presents a significant challenge in creating standardised methods for this field and possible discrepancies. In this study, we conducted a comprehensive comparison and contrast of a total of 68 RGB color spaces to evaluate their respective impacts on colorimetric bio/chemical sensing. We explore the impact of dynamic range, sensitivity, and limit of detection, and show that the lack of specificity in RGB color space selection can significantly impact colorimetric chemical sensing by 42-77%. We also explore the impact of underlying RGB comparisons and demonstrate a further 18.3% discrepancy between RGB color spaces. By emphasising the importance of proper RGB color space selection and handling, our findings contribute to a better understanding of this critical area and present valuable opportunities for future research. We further provide valuable insights for creating standardised methods in this field, which can be utilised to avoid discrepancies and ensure accurate and reliable analysis in colorimetric bio/chemical sensing.

The colorful world of sulfonephthaleins: Current applications in analytical chemistry for "old but gold" molecules

Sulfonephthaleins represent one of the most common and widely employed reactive dyes in analytical chemistry, thanks to their stability, low-cost, well-visible colors, reactivity and possibilities of chemical modification. Despite being first proposed in 1916, nowadays, these molecules play a fundamental role in biological and medical applications, environmental analyses, food quality monitoring and other fields, with a particular focus on low-cost and disposable devices or methods for practical applications. Since up to our knowledge, no reviews or book chapters focused explicitly on sulfonephthaleins have ever been published, in this review, we will briefly describe sulfonephthaleins history, their acid-base properties will be discussed, and the most recent applications in different fields will be presented, focusing on the last ten years literature (2014-2023). Finally, safety and environmental issues will be briefly discussed, despite being quite controversial.

Application of colorimetric sensor array coupled with machine-learning approaches for the discrimination of grains based on freshness

BACKGROUND

Volatile organic compounds (VOCs) in grain fluctuate depending on the degree of grain freshness. A new colorimetric sensor array (CSA) was developed as capture probes for the quantification of VOCs in grains in this work, and it was designed to monitor the variation of grain VOCs. CSA spectral data acquisition using visible-near-infrared spectroscopy and image processing of CSA's image imformation by computer were used comparatively. Then, machine-learning-based models - for example, synergistic interval partial least squares, genetic algorithm, competitive adaptive reweighted sampling (CARS) algorithm, and ant colony optimization (ACO) algorithm - were introduced to optimize variables. Moreover, principal component analysis, and linear discriminant analysis (LDA), and K-nearest neighbors (KNN) were used for the classification. Ultimately, quantitative models for detecting grain freshness are developed using various variable selection strategies.

RESULTS

Compared with the pattern recognition results of image processing, visible-near-infrared spectroscopy could better separate the grains with different freshness from principal component analysis, and the prediction set of LDA models could correctly identify 100% of rice, 96.88% of paddy, and 97.9% of soybeans. In addition, compared with CARS and ACO, the LDA model and KNN model based on genetic algorithms show the best prediction performance. The prediction set could correctly identify 100% of rice and paddy samples and 95.83% of soybean samples.

CONCLUSION

The method developed could be used for non-destructive detection of grain freshness. © 2023 Society of Chemical Industry.

Colorimetric Paper-Based Analytical Devices (PADs) Backed by Chemometrics for Pd(II) Detection

This paper presents the development of cheap and selective Paper-based Analytical Devices (PADs) for selective Pd(II) determination from very acidic aqueous solutions. The PADs were obtained by impregnating two cm-side squares of filter paper with an azoic ligand, (2-(tetrazolylazo)-1,8 dihydroxy naphthalene-3,6,-disulphonic acid), termed TazoC. The so-obtained orange TazoC-PADs interact quickly with Pd(II) in aqueous solutions by forming a complex purple-blue-colored already at pH lower than 2. The dye complexes no other metal ions at such an acidic media, making TazoC-PADs highly selective to Pd(II) detection. Besides, at higher pH values, other cations, for example, Cu(II) and Ni(II), can interact with TazoC through the formation of stable and pink-magenta-colored complexes; however, it is possible to quantify Pd(II) in the presence of other cations using a multivariate approach. To this end, UV-vis spectra of the TazoC-PADs after equilibration with the metal ions solutions were registered in the 300-800 nm wavelength range. By applying Partial Least Square regression (PLS), the whole UV-vis spectra of the TazoC-PADs were related to the Pd(II) concentrations both when present alone in solution and also in the presence of Cu(II) and Ni(II). Tailored PLS models obtained with matrix-matched standard solutions correctly predicted Pd(II) concentrations in unknown samples and tap water spiked with the metal cation, making the method promising for quick and economical sensing of Pd(II).

Applications, challenges and prospects of bionic nose in rapid perception of volatile organic compounds of food

Bionic nose, a technology that mimics the human olfactory system, has been widely used to assess food quality due to their high sensitivity, low cost, portability and simplicity. This review briefly describes that bionic noses with multiple transduction mechanisms are developed based on gas molecules' physical properties: electrical conductivity, visible optical absorption, and mass sensing. To enhance their superior sensing performance and meet the growing demand for applications, a range of strategies have been developed, such as peripheral substitutions, molecular backbones, and ligand metals that can finely tune the properties of sensitive materials. In addition, challenges and prospects coexist are covered. Cross-selective receptors of bionic nose will help and guide the selection of the best array for a particular application scenario. It provides an odour-based monitoring tool for rapid, reliable and online assessment of food safety and quality.

Colorimetric Paper Sensor for Food Spoilage Based on Biogenic Amine Monitoring

Biogenic amines (BAs), nitrogenous molecules usually present in different foods, can be considered an indicator of freshness and food quality since their amount increases during food spoilage. Their detection, possibly in real time via the use of smart packaging, is therefore of crucial importance to ensure food safety and to fulfill consumers' demand. To this end, colorimetric sensors are considered one of the most feasible solutions. Here, we report a user-friendly colorimetric sensing paper able to detect BAs via the naked eye. The sensing molecule is the aglycone genipin, a natural cross-linking agent extracted from gardenia fruit, able to bind BAs producing water-soluble blue pigments. The paper sensor was applied to chicken meat quality monitoring and a quantitative analysis was performed with image acquisition via a smartphone camera, achieving a limit of detection equivalent to 0.1 mM of putrescine. The suitability of the BA sensing paper was assessed by integrating the sensor into smart packaging and analyzing commercial chicken meat samples stored at different temperatures; the results of the sensor paralleled the "best before date" indicated on the label, confirming the potential applicability of the sensor as a smart label.

Use of industry 4.0 technologies to reduce and valorize seafood waste and by-products: A narrative review on current knowledge

Fish and other seafood products represent a valuable source of many nutrients and micronutrients for the human diet and contribute significantly to global food security. However, considerable amounts of seafood waste and by-products are generated along the seafood value and supply chain, from the sea to the consumer table, causing severe environmental damage and significant economic loss. Therefore, innovative solutions and alternative approaches are urgently needed to ensure a better management of seafood discards and mitigate their economic and environmental burdens. The use of emerging technologies, including the fourth industrial revolution (Industry 4.0) innovations (such as Artificial Intelligence, Big Data, smart sensors, and the Internet of Things, and other advanced technologies) to reduce and valorize seafood waste and by-products could be a promising strategy to enhance blue economy and food sustainability around the globe. This narrative review focuses on the issues and risks associated with the underutilization of waste and by-products resulting from fisheries and other seafood industries. Particularly, recent technological advances and digital tools being harnessed for the prevention and valorization of these natural invaluable resources are highlighted.

Quick and Easy Covalent Grafting of Sulfonated Dyes to CMC: From Synthesis to Colorimetric Sensing Applications

Carboxymethyl cellulose, the most promising cellulose-derivatives, pulls together low cost, abundancy, biocompatibility, unique properties and, unlike the precursor, chemical reactivity. This latter aspect arouses the curiosity of chemists around the possibility of chemical modification and the production of interesting functional materials. Here, a two-step reaction is proposed for the covalent anchoring of a wide variety of molecules containing sulfonic groups to CMC. The strength points of the proposed pathway have to be found in the quick and easy reactions and workup that allow to obtain ready-to-use functional materials with very high yields. Having in this case exploited a pH-sensitive dye as a sulfonated molecule, the functional material is an interesting candidate for the development of colorimetric miniaturized sensors via the following drop-casting deposition: once optimized sensors preparation by design of experiments, an example of application on real samples is reported.

RGB-Detector: A Smart, Low-Cost Device for Reading RGB Indexes of Microfluidic Paper-Based Analytical Devices

A user-friendly, low-cost detector able to read the RGB indexes of microfluidic paper-based analytical devices (µPADs) was developed. The RGB-detector was built with 3D printing using PLA+ and reused Li-ion batteries. It is Arduino-based, which provides an easy interface between the sensor TCS3200, which reads the quadratic wave of the times corresponding to the RGB numbers, the Arduino itself, whose software translates the times into RGB values, and the touchscreen display, NX3224T028, which shows the results. This detector permits multi-sample analysis since it has a sample holder that can keep up to six µPADs simultaneously and rotate after the display's request. This work shows how the readings of the RGB indexes by the proposed RGB-detector implement the measurements' reproducibility. As a proof-of-concept, the RGB-detector application to a green array of µPADs for pH measurement coupled with chemometric analysis allowed us to achieve good results in terms of precision and agreement with the pH values measured by a classical pH-meter.

A non-porous Fe(II) complex for the colorimetric detection of hazardous gases and the monitoring of meat freshness

Food quality monitoring and freshness assessment are critical for ensuring food safety at a large scale. Ammonia is used as an important indicator of protein rich food spoilage state. However, current ammonia gas sensors suffer from insufficient sensitivity and selectivity, or sophisticated instrumentation, hindering their practical application in in-situ and real-time food quality monitoring. To overcome such limitations, an innovative nonporous colorimetric complex 1 has been synthesized and investigated for the detection of NH_3(g) and its volatile organic derivatives including aliphatic amines, 1,2-diaminopropane_(g), isobutylamine_(g) and ethylenediamine_(g), etc. The sensor operates colorimetrically at room temperature without energy input, with a detection limit to ammonia_(g) of 105 ppb, and show excellent reusability. The colorimetric detection mechanism involves a partial spin state change of Fe(II) ions upon exposure to amines in the gas phase. In addition, the complex was utilized as real-time monitoring of meat freshness using a smartphone. Thus, chemosensor 1 is considered as a ground breaking new-generation portable electronic nose for vapors of volatile organic compounds discrimination at room temperature.

Preparation and Testing of Food Freshness Indicators: an Application-Oriented Learning Module Integrating Basic Concepts of Microbiology and Chemistry Laboratory

We describe a novel 4-day food microbiology laboratory learning module for a first-year, introductory undergraduate course. In the module, the students test the suitability of four different pH indicator dyes as freshness indicators for dairy products. The concepts of serial dilutions, microbial growth, microbial metabolism, pH as well as pKa, and basic microbial laboratory practices are a part of the designed activity. It is a relatively inexpensive module and can be executed with little infrastructural support. It can be delivered as a stand-alone structured inquiry. The associated variables and applications indicate that the activity can perhaps be developed into a more elaborate course-based undergraduate research experience, or CURE.

Recent Progress, Challenges, and Trends in Polymer-Based Sensors: A Review

Polymers are long-chain, highly molecular weight molecules containing large numbers of repeating units within their backbone derived from the product of polymerization of monomeric units. The materials exhibit unique properties based on the types of bonds that exist within their structures. Among these, some behave as rubbers because of their excellent bending ability, lightweight nature, and shape memory. Moreover, their tunable chemical, structural, and electrical properties make them promising candidates for their use as sensing materials. Polymer-based sensors are highly utilized in the current scenario in the public health sector and environment control due to their rapid detection, small size, high sensitivity, and suitability in atmospheric conditions. Therefore, the aim of this review article is to highlight the current progress in polymer-based sensors. More importantly, this review provides general trends and challenges in sensor technology based on polymer materials.

Preparation of Mesoporous Silica Nanosphere-Doped Color-Sensitive Materials and Application in Monitoring the TVB-N of Oysters

In this work, a new colorimetric sensor based on mesoporous silica nanosphere-modified color-sensitive materials was established for application in monitoring the total volatile basic nitrogen (TVB-N) of oysters. Firstly, mesoporous silica nanospheres (MSNs) were synthesized based on the improved Stober method, then the color-sensitive materials were doped with MSNs. The “before image” and the “after image” of the colorimetric senor array, which was composed of nanocolorimetric-sensitive materials by a charge-coupled device (CCD) camera were then collected. The different values of the before and after image were analyzed by principal component analysis (PCA). Moreover, the error back-propagation artificial neural network (BP-ANN) was used to quantitatively predict the TVB-N values of the oysters. The correlation coefficient of the colorimetric sensor array after being doped with MSNs was greatly improved; the Rc and Rp of BP-ANN were 0.9971 and 0.9628, respectively when the principal components (PCs) were 10. Finally, a paired sample t-test was used to verify the accuracy and applicability of the BP-ANN model. The result shows that the colorimetric-sensitive materials doped with MSNs could improve the sensitivity of the colorimetric sensor array, and this research provides a fast and accurate method to detect the TVB-N values in oysters.

Freshness Identification of Oysters Based on Colorimetric Sensor Array Combined with Image Processing and Visible Near-Infrared Spectroscopy

Volatile organic compounds (VOCs) could be used as an indicator of the freshness of oysters. However, traditional characterization methods for VOCs have some disadvantages, such as having a high instrument cost, cumbersome pretreatment, and being time consuming. In this work, a fast and non-destructive method based on colorimetric sensor array (CSA) and visible near-infrared spectroscopy (VNIRS) was established to identify the freshness of oysters. Firstly, four color-sensitive dyes, which were sensitive to VOCs of oysters, were selected, and they were printed on a silica gel plate to obtain a CSA. Secondly, a charge coupled device (CCD) camera was used to obtain the “before” and “after” image of CSA. Thirdly, VNIS system obtained the reflected spectrum data of the CSA, which can not only obtain the color change information before and after the reaction of the CSA with the VOCs of oysters, but also reflect the changes in the internal structure of color-sensitive materials after the reaction of oysters’ VOCs. The pattern recognition results of VNIS data showed that the fresh oysters and stale oysters could be separated directly from the principal component analysis (PCA) score plot, and linear discriminant analysis (LDA) model based on variables selection methods could obtain a good performance for the freshness detection of oysters, and the recognition rate of the calibration set was 100%, while the recognition rate of the prediction set was 97.22%. The result demonstrated that the CSA, combined with VNIRS, showed great potential for VOCS measurement, and this research result provided a fast and nondestructive identification method for the freshness identification of oysters.

Nanomaterials in Smart Packaging Applications: A Review

Food wastage is a critical and world-wide issue resulting from an excess of food supply, poor food storage, poor marketing, and unstable markets. Since food quality depends on consumer standards, it becomes necessary to monitor the quality to ensure it meets those standards. Embedding sensors with active nanomaterials in food packaging enables customers to monitor the quality of their food in real-time. Though there are many different sensors that can monitor food quality and safety, pH sensors and time-temperature indicators (TTIs) are the most critical metrics in indicating quality. This review showcases some of the recent progress, their importance, preconditions, and the various future needs of pH sensors and TTIs in food packaging for smart sensors in food packaging applications. In discussing these topics, this review includes the materials used to make these sensors, which vary from polymers, metals, metal-oxides, carbon-based materials; and their modes of fabrication, ranging from thin or thick film deposition methods, solution-based chemistry, and electrodeposition. By discussing the use of these materials, novel fabrication process, and problems for the two sensors, this review offers solutions to a brighter future for the use of nanomaterials for pH indicator and TTIs in food packaging applications.

Application of Spectrometric Technologies in the Monitoring and Control of Foods and Beverages

In order to obtain high-quality products and gain a competitive advantage, food producers seek improved manufacturing processes, particularly when physicochemical and sensory properties add significant value to the product [...].

Intelligent Packaging for Real-Time Monitoring of Food-Quality: Current and Future Developments

Food packaging encompasses the topical role of preserving food, hence, extending the shelf-life, while ensuring the highest quality and safety along the production chain as well as during storage. Intelligent food packaging further develops the functions of traditional packages by introducing the capability of continuously monitoring food quality during the whole chain to assess and reduce the insurgence of food-borne disease and food waste. To this purpose, several sensing systems based on different food quality indicators have been proposed in recent years, but commercial applications remain a challenge. This review provides a critical summary of responsive systems employed in the real-time monitoring of food quality and preservation state. First, food quality indicators are briefly presented, and subsequently, their exploitation to fabricate intelligent packaging based on responsive materials is discussed. Finally, current challenges and future trends are reviewed to highlight the importance of concentrating efforts on developing new functional solutions.

A Long-Term Stable Sensor Based on Fe@PCN-224 for Rapid and Quantitative Detection of H2O2 in Fishery Products

Hydrogen peroxide (H2O2) has been reported to be used for the illegal treatment of fishery products in order to obtain "fake" freshness. Residues of H2O2 in food may be of toxicology concern. In this study, a nonenzymatic sensor was developed based on Fe@PCN-224 metal-organic frameworks wrapped by Nafion to detect H2O2 concentration. The hybrid structure of Fe@PCN-224 was fabricated by incorporated free FeIII ions into the center of PCN-224, which was ultra-stable due to the strong interactions between Zr6 and the carboxyl group. Scanning electron spectroscopy images exhibited that Nafion sheets crossed together on the surface of Fe@PCN-224 nanoparticles to form a hierarchical and coherent structure for efficient electron transfer. Electrochemical investigations showed that the Fe@PCN-224/Nafion/GCE possessed good linearity from 2 to 13,000 μM (including four orders of magnitude), low detection limits (0.7 μM), high stability in continuous monitoring (current remained nearly stable over 2300 s) and in long-term measurement (current decreased 3.4% for 30 days). The prepared nanohybrid modified electrode was effectively applied to H2O2 detection in three different fishery products. The results were comparable to those measured using photometrical methods. The developed electrochemical method has a great potential in detecting the illegal management of fishery products with H2O2.

User-friendly lab-on-paper optical sensor for the rapid detection of bacterial spoilage in packaged meat products

A lab-on-paper colorimetric sensor for detection and quantification of bacterial meat spoilage is reported.

Disposable and Low-Cost Colorimetric Sensors for Environmental Analysis

Environmental contamination affects human health and reduces the quality of life. Therefore, the monitoring of water and air quality is important, ensuring that all areas are acquiescent with the current legislation. Colorimetric sensors deliver quick, naked-eye detection, low-cost, and adequate determination of environmental analytes. In particular, disposable sensors are cheap and easy-to-use devices for single-shot measurements. Due to increasing requests for in situ analysis or resource-limited zones, disposable sensors’ development has increased. This review provides a brief insight into low-cost and disposable colorimetric sensors currently used for environmental analysis. The advantages and disadvantages of different colorimetric devices for environmental analysis are discussed.

Nondestructive monitoring of polyphenols and caffeine during green tea processing using Vis-NIR spectroscopy

Increasing consumption of green tea is attributed to the beneficial effects of its constituents, especially polyphenols, on human health, which can be varied during leaf processing. Processing technology has the most important effect on green tea quality. This study investigated the system dynamics of eight catechins, gallic acid, and caffeine in the processing of two varieties of tea, from fresh leaves to finished tea. It was found that complex biochemical changes can occur through hydrolysis under different humidity and heating conditions during the tea processing. This process had a significant effect on catechin composition in the finished tea. The potential application of visible and near-infrared (Vis-NIR) spectroscopy for fast monitoring polyphenol and caffeine contents in tea leaves during the processing procedure has been investigated. It was found that a combination of PCA (principal component analysis) and Vis-NIR spectroscopy can successfully classify the two varieties of tea samples and the five tea processing procedures, while quantitative determination of the constituents was realized by combined regression analysis and Vis-NIR spectra. Furthermore, successive projections algorithm (SPA) was proposed to extract and optimize spectral variables that reflected the molecular characteristics of the constituents for the development of determination models. Modeling results showed that the models had good predictability and robustness based on the extracted spectral characteristics. The coefficients of determination for all calibration sets and prediction sets were higher than 0.862 and 0.834, respectively, which indicated high capability of Vis-NIR spectroscopy for the determination of the constituents during the leaf processing. Meanwhile, this analytical method could quickly monitor quality characteristics and provide feedback for real-time controlling of tea processing machines. Furthermore, the study on complex biochemical changes that occurred during the tea processing would provide a theoretical basis for improving the content of quality components and effective controlling processes.