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Review

Nitrite: From Application to Detection and Development

State Key Laboratory of Food Science and Resources, Nanchang University, Nanchang 330047, China
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2024, 14(19), 9027; https://doi.org/10.3390/app14199027 (registering DOI)
Submission received: 26 June 2024 / Revised: 20 September 2024 / Accepted: 2 October 2024 / Published: 6 October 2024
(This article belongs to the Special Issue Advanced Technologies for Food Packaging and Preservation)

Abstract

:
Nitrite, a collective term for a group of inorganic compounds containing nitrite ions (NO2), is widely present in the natural environment and in the human body. It has a wide range of applications in the medical, food and environmental fields, such as food additives, water treatment agents and drugs. However, the excessive intake of nitrite poses indirect carcinogenic, teratogenic and mutagenic risks to humans. With the in-depth study of the functional properties of nitrite, there is an increasing demand for accurate and efficient methods for its detection. This paper presents a review of methods for the detection of nitrite, which will cover different principles and technologies, including traditional methods, optical methods, electrochemical sensors, and biosensors, and their prospects. By comparing and evaluating the different methods, it will provide references and valuable suggestions for choosing the most suitable nitrite detection methods and the scientific selection of alternatives for nitrite.

1. Introduction

Nitrite is a collective term for a group of inorganic compounds containing nitrite ions (NO2) and sodium nitrite (NaNO2) is an important compound of nitrite. Nitrite has been shown to pose a significant threat to human health and are commonly detected in water and food [1]. In food, it is widely used as a common color developer, antioxidant, and preservative in fermented meat products, inhibiting the growth of spoilage and pathogenic bacteria such as Clostridium botulinum and Listeria monocytogenes [2]. Thus, nitrite is irreplaceable for its antimicrobial, antioxidant, color development and flavor production properties [3]. In the medical field, nitrite is used as a mammalian vasodilator to save mammalian lives during periods of hypoxia. For asthmatics, atomized nitrite has the effect of slowing the deterioration of asthma [4]. On the other hand, the intake of sodium nitrite induces methemoglobinemia, which can lead to toxicity [5]. Meanwhile, nitrite is strongly associated with the risk of prostate cancer [6]. In addition to this, nitrite intake is associated with the activation of genes controlling apoptosis in liver and kidney tissues, with some genotoxicity, making tissue lesions [7]. According to the EPA, in the drinking water standard, the MCLG (Maximum Contaminant Level Goal) for nitrite is 1 mg/L, and the MCL (Maximum Contaminant Level) is 1 mg/L [8]. Despite such toxicity and carcinogenicity, nitrite is often used as food additives [9]. It is clear that nitrite is a controversial substance with great hazards; thus, there is an urgent need to establish effective methods for detecting nitrite. At the same time, it is necessary to seek other less harmful alternatives to nitrite.
In China’s national standard [10] for the detection of nitrite in food, traditional methods for the detection of nitrite in fruits and vegetables mainly include ion chromatography, spectrophotometry and ultraviolet spectrophotometry. The U.S. Geological Survey (USGS) National Water Quality Laboratory (NWQL) have validated enzymatic reduction and colorimetric determinative methods for nitrate and nitrite in filtered water by automated discrete analysis. Nitrate is reduced to nitrite by nontoxic, soluble nitrate reductase [11]. Furthermore, the EU usually uses a spectrophotometric method to detect nitrite and sets limits for nitrite [12].
However, the methods involved in these national standards cannot more comprehensively reflect the current situation and future development of nitrite testing, with the growing demand for food safety, environmental greening and other needs. Therefore, it is urgent to seek a method that can quickly, efficiently, accurately and sensitively detect the content of nitrite. In order to make up for the gap of domestic detection methods, we explored domestic and international detection methods and launched a review of them, aiming to find the best method for detecting nitrite so as to improve the detection efficiency, enhance the sensitivity, and so on.
Generally speaking, there are optical methods, electrochemical sensors, biosensors, intelligent detection methods for detecting nitrite in food, human body, environment, etc. The above methods and their latest progress will be summarized, and we will make corresponding comparisons and analyses, mainly for their detection of nitrite sensitivity, specificity, selectivity and other aspects of the comprehensive comparison. This will provide the relevant researchers with a clearer understanding of the nitrite content detection. At the same time, because nitrite has the risk of indirect carcinogenicity, teratogenicity and mutagenicity to human body, the related personnel are also actively exploring the alternatives to nitrite as a food additive, so as to facilitate the subsequent research to provide some new suggestions. Finally, the difficulties, challenges and future perspectives of today’s nitrite detection are comprehensively discussed.

2. Traditional Detection Methods

Nitrite is widely present in human body, food and environment, and its detection methods are being improved with the continuous advancement of research. Its detection methods include ion chromatography, electrochemical methods, optical detection methods, biosensor methods, and so on. The classification of relevant methods is presented in Figure 1.
Firstly, ion chromatography, as a representative of the traditional methods, is mainly introduced. Traditional methods have a great degree of accuracy and reliability, while there are limitations such as cumbersome operation, a long analysis period and high requirements for equipment. However, these traditional detection methods are constantly being improved to achieve better detection purposes.

Ion Chromatography

Ion chromatography, as a traditional detection method, is used in many fields of detection, including food, medicine, environment and others. In the medical field, ion chromatography has been usually used in the detection of nitrite in drugs and human blood. For example, researchers have used ion chromatography to determine DMA(N,N-Dimethylacetamide) and nitrite in five medicines, including metformin, losartan, ranitidine, Nytol, and Benadyrl, as well as two drug substances, losartan potassium and metformin hydrochloride [13], along with the determination of nitrite ions in rifampicin and rifapentine capsules by solid phase extraction ion chromatography [14]. The nitrite content in homogeneous meat samples of infant food was detected by ion chromatography and conductivity [15]. A simple ion chromatographic method [16] can be used for the analysis of nitrite in processed foods. The detection of nitrite in freshwater can be performed by one-dimensional ion chromatography [17]. The steps of ion chromatography are mainly divided into the following steps: The first step is to pre-treat the sample, then adjust the chromatographic conditions, including the adjustment of the chromatographic conditions of the column, eluent, flow rate, column temperature, suppressor, detector, and injection volume. Next, draw a standard curve, and finally the specimen determination and qualitative determination.
Looking at the general steps of the determination, we can learn that the steps for determining nitrite content are complicated. Therefore, more and more researchers have been targeting the improvement in each part of the above steps. Based on further improving the detection efficiency, researchers firstly improved the strategy from the pretreatment of raw materials, using a simple ultrafiltration method for sample preparation, which can shorten the time of pretreatment of samples and improve the detection efficiency. Ultrasonic extraction followed by static separation is also a good pretreatment method [18]. Solid phase extraction (SPE) technology [14] simplifies the pretreatment process and also improves the efficiency of pretreatment.
Choosing the right column temperature is an essential part of achieving better detection results because a stable column temperature is conducive to maintaining good column performance. Generally speaking, a column temperature of 30 °C and a detector temperature of 35 °C have been commonly used for the detection of nitrite [19]. Additionally, the selection of separation column, eluent and detector are very important. Taking the determination of nitrite in valsartan and other sartans as an example, the sensitivity and accuracy of the detection were improved by optimizing the relevant chromatographic conditions. A KOH (potassium hydroxide) solution generated by an in-line eluent generator (EG) was used as the 2D mobile phase for gradient elution at a rate of 1 mL/min. Water and acetonitrile were used as 1D mobile phases for gradient elution at 0.5 mL/min. All of these mentioned parameters are the better parameter conditions derived by the experimenter through continuous trying.
In recent years, as detection requirements have rapidly increased, more and more studies have shown that ion chromatography is seldom used as a stand-alone detection method, but rather in combination with other instruments or methods for the detection of target substances. For example, UPLC-MS (Ultra Performance Liquid Chromatography-Mass Spectrometry) can be used for the detection of nitrite in a variety of pharmaceutical products [20]. The gas-chromatography-negative chemical ionization–mass spectrometry derivatization method can also make up for the shortcomings of ion chromatography detection methods. The proposed ion chromatography–mass spectrometry method solves the ion suppression problem of MS (mass spectrometry) detection. The loss of sensitivity due to the accumulation of trace salts in the ion source is avoided [21]. The combined method of HPLC (high-performance liquid chromatography) and IC (ion chromatography) for the determination of nitrite can achieve rapidity and accuracy and avoid the problem of labor intensity [22]. The four-stage liquid flow path of the HPLC-IC system is shown in Figure 2.
The combination of ion chromatography and automated techniques can improve reproducibility and selectivity. Portable automated ion chromatography systems with dual capabilities are now available for the analysis of freshwater nitrite, achieving an analytical range of 0.1 mg/L–40 mg/L NO2 for marine analyses, as well as nitrite analysis [17]. A smart wastewater quality monitoring system is shown in Figure 3. The range of analysis is suitable for freshwater analysis. In today’s era of big data, the empowerment of smart devices in detection has led to a significant improvement in the detection of traditional methods as well. Related research has developed a low-cost water quality testing device consisting of a nitrate and nitrite analyzer based on a novel ion chromatography method. In addition, the analytical device was integrated using an IoT software platform based on the middleware called thethings.io, which was found to be reliable after careful comparisons [23].
Ion chromatography, as a representative of the traditional method, has the following advantages: (1) high sensitivity and accuracy [16]. (2) The detection is standardized, and there are relevant national standards at home and abroad to regulate it [12]. (3) Pre-treatment of the sample is required [18].
In short, when using ion chromatography for the determination of nitrite, investigators have improved the method mainly in terms of the following aspects. (1) Select suitable eluent. (2) Adjust the flow rate of eluent. (3) Change the ionic strength to improve the stability of nitrite. (4) Control the column temperature. (5) Choose a suitable detector. (6) Improve the pretreatment step. All these steps should be adjusted according to the specific experimental conditions and experimental objectives and verified by experiments. For the determination of nitrite by ion chromatography, we need to try many times in practice so that we can find the best combination of parameters.

3. Optical-Based Detection Methods

3.1. Spectrophotometry

The most common spectrophotometric method used for the detection of nitrite is the Griess method, which is the reference method. Firstly, the appropriate aromatic amines are diazotized, and then the azo reaction is carried out to form pigment chromophores, and the absorbance of the reaction products is detected by the relevant instruments. Then it can indirectly determine the content of nitrite. In many cases, the violet-red product formed by naphthalene ethylenediamine hydrochloride under weak acid conditions has the maximum absorbance at 540 nm [24]. With this principle, it can detect most of the nitrite. However, some improvements need to be made to obtain higher accuracy and sensitivity. At present, spectrophotometry has become one of the internationally accepted methods for the detection of nitrite, whose advantages include simplicity, rapidity, accuracy, high sensitivity and low cost. However, the method has some shortcomings, such as the need to use a large number of reagents and steps such as pre-treatment, as well as the problem of cross-reactivity. Therefore, future research should focus on how to improve the selectivity of the spectrophotometric method, reduce the detection limit and simplify the operation process.
To address these issues, researchers have begun to explore a number of new technologies and approaches, for example, the use of fluorescent probes to improve detection sensitivity and selectivity; the combination of other technical methods, such as mass spectrometry and nuclear magnetic resonance, to achieve more accurate and comprehensive detection; and the development of new types of reagents. These innovations will help to further improve the performance and application scope of spectrophotometry and provide more reliable technical support for food safety.
While using the Griess reaction as a reference method for spectrophotometry, the principle of its detection has been optimized, and a fluorescent sensor has been designed that also works by detecting colored azo compounds, in which the nitrite content is indirectly measured through the detection of shades of brown. Its use of 3-acetoacetyl-7-diethylaminocoumarin and 3-aminophenol (Figure 4a) for the highly selective detection of nitrites is a good improvement strategy for the simplification of the Griess reagent assay [25]. Detailed information has been shown in Figure 4 and is described below.
Under acidic conditions, fenugreek is also detectable as a dye [26], which is not a new way. In addition, for the determination of nitrate concentration in natural water, using premixed vanadium and Griess reagents is fast and efficient [27].
A stable optical nano sensor was fabricated by immobilizing 1-naphthylamine on mesoporous silica nanospheres. The determination of nitrite is based on the reaction of nitrite with the optical sensor and the formation of diazonium salts, which are then coupled to form a stable brown azo dye for simple, sensitive and rapid detection. Additionally, a time-saving and high-recovery method for the spectrophotometric analysis of nitrite based on the diazonium coupling reaction is promising [28].
In the Griess reagent test, N-(1-naphthalenyl) ethylenediamine dihydrochloride is a substance with a certain degree of toxicity, while the exposure of the detector may be harmful to the organism or the environment. Therefore, researchers have been looking for a more environmentally friendly reagent, which is very critical and of strategic significance for sustainable development. For example, based on the redox reaction with iodide ions under acidic conditions of nitrite, the developed method combined with microtiter plate detection can achieve the low consumption of reagents required, greatly saving manpower, financial and material resources [29].
In addition, the use of p-aminobenzene sulfonamide and α-amino-β-imidazolyl propionic acid in water experiments avoids the use of toxic substances [30]. In an acidic solution, sulfathiazole is first treated with sodium nitrite. Then, a phosphate buffer is added. Coupling reagents like N-(1-naphthalenyl)ethylenediamine are not needed [31] (Figure 4b). Additionally, butane dioic acid, tartaric acid, and malic acid can replace concentrated hydrochloric acid as the acidic medium. The detection time can be shortened by 5–14 min, which improves safety and efficiency. In the acidic medium, nitrite reacts with senna to generate a blue dye. Then, the solution is checked for this blue dye, which is a simple and low-cost method [26].
In the specific detection steps of the spectrophotometer, the influence of interfering substances often occurs, which may cause some errors. Therefore, if the error is large, it is undoubtedly fatal to the detection. To eliminate matrix interference, the standard addition method is widely used. However, it is time-consuming and laborious; thus, researchers have developed a feedback addition method coupled with flow injection analysis. The advantage of it is that it can automatically prepare the spiked samples, which greatly improves the efficiency of the operation [32]. In terms of sensitivity, the design of the flow cell as a liquid-core waveguide can effectively improve the sensitivity of the spectrophotometer [33]. Often, the absorbance is used to reflect the concentration; however, some studies have used the inflection point in the derived absorbance for the corresponding determination, which can also serve the purpose well [34]. While achieving simplicity, speed, sensitivity, and environmental protection, the spectrophotometer and smartphone are closely integrated to achieve on-site analysis [35] (Figure 4c).
In conclusion, spectrophotometry has high sensitivity, high accuracy, high efficiency and wide applicability. The principle of it has been improved to further simplify the operation steps and reduce the manpower and material resources. New detection instruments have been researched, and a series of sensors based on the principles of traditional spectrophotometry have been made to ensure the stability. In terms of environmental protection, the combination of micro-detection techniques reduces the use of reagents and avoids the generation and exposure of some unnecessary toxic substances, which is conducive to sustainable development. In the future, more efficient and accurate detection methods and technologies should be developed to meet the needs of nitrite detection in different fields. For example, we can combine new technologies such as mass spectrometry and nanomaterials to improve detection sensitivity and selectivity. In addition, standardization work should be strengthened. Furthermore, unified standard system and technical specifications should be established to ensure the comparability and reliability of detection results.

3.2. Detection Methods Based on Colorimetric Methods

The colorimetric detection of nitrite is a classical method based on a chromogenic reaction that generates colored compounds. The method generally consists of two steps: firstly, the selection of an appropriate chromogenic reagent reacts with the component to be tested to form a colored compound, and then the color depth of the colored compounds is compared and measured. In addition, there are two main types of colorimetric methods: visual colorimetry and photoelectric colorimetry. The former directly derives the amount of the substance to be measured by comparing the color depth of the sample through naked eye observation. The latter uses a spectrophotometer for absorbance measurement, which can more accurately measure the concentration of the substance to be measured. For example, the method based on the principle that the color of the detection system changes from brown to yellow as the concentration of NO2 increases has been developed for the simple colorimetric detection [36].
The naked eye can determine the content of the sample, while the measured concentration is not very accurate. Therefore, more and more researchers are studying related optical testing instruments and exploring new methods in order to improve sensitivity. In addition, colorimetric methods generally have low accuracy due to complex interference; therefore, high-purity samples and sensitivity and selectivity assays are necessary to solve the interference problem. At present, the most basic method used in colorimetric assay is still the Griess reagent assay. On the basis of this standard assay, many of related sensors have been derived. These sensors tend to meet the requirements of rapid detection and show good advantages in terms of selectivity. For example, a hydrogel-based chemo sensor (Figure 5a,b) has shown high sensitivity for the detection of nitrite. In addition, the interference testing of this chemo sensor has confirmed its high selectivity for NO2 in the presence of environmentally relevant competing ions [37]. The sensor has achieved great success in detection with its good stability and high sensitivity. Thus, many researchers are making a series of preparations to improve its detection performance, and some nanomaterials have been applied in colorimetric detection such as AuNP–CeO2 NP@graphene oxide [38], mesoporous silica [39], and MnO2 NPs [40]. There is no doubt that the application of these nanomaterials is crucial to improve the sensitivity of the detection. Due to the protective effect of PAN (polyacrylonitrile) on the reagent, the researchers used PAN-NSS (modified polyacrylonitrile) [41] as a nitrite color sensor. With this, the validity of the reagent can be extended based on the Griess reagent detection. In addition, it has ensured the stability and long-term validity of the reagent detection to a certain extent.
Due to the large amount of reagents required in the Griess reagent assay, the researchers attempted to develop a PAD (paper-based analytical device) [42] colorimetric assay for the determination of nitrite in foodstuffs to reduce the amount of reagents used. Furthermore, it most importantly does not require an instrument to achieve the assay. Similarly, the researchers have proposed a microfluidic colorimetric system consisting of a colorimetric paper device and a micro-analysis cartridge (Figure 5d) for the detection of nitrite concentration in foodstuffs to achieve a low-cost, low-reagent-use assay [43]. In addition, the researchers have utilized a microfluidic colorimetric system using phenanthrene. Additionally, researchers used phenosafranin for the detection of nitrite in food [44]. The use of it as an alternative to Griess reagent is also promising.
Despite the high speed of colorimetric methods, many researchers have been trying to shorten the detection time. For example, the rapid colorimetric detection of nitrite based on the interfacial reaction of propylene glycol alginate (PGA) gels can be completed in less than 5 min [45]. Furthermore, the method based on the reaction of nitrite with 60 mM HCl to produce free radicals, which further oxidizes ABTS (50 μM) to form a water-soluble blue-green product that can be measured at a maximum absorption wavelength of 412.5 nm in only 2 min [46]. In addition, nitrite ions were detected using a polyethylene glycol (PEG) hydrogel overlaid with glass fiber membrane strips, and a colorimetric Griess assay was carried out on a hydrogel modified with N-(1-naphthyl) ethylenediamine by dropping a solution of nitrite and sulfanilamide. The colorimetric reaction (Figure 5c) can be completed in a few seconds and is suitable in clinical samples due to its excellent specificity [47].
The use of different strategies for the simultaneous detection of nitrite is essential to the reliability and accuracy of the experiment. A novel red carbon dot (r-CD) fluorescent probe (Figure 5e) was prepared for the dual-mode detection of nitrite, which allows both convenient colorimetric analysis and accurate fluorescence detection [48]. Similarly, a novel colorimetric fluorescent probe, ND-1, based on the photogenerated electron transfer effect (PET), was strategically constructed using naphthalimide as the fluorescent moiety and o-phenylenediamine as the specific recognition site for NO2 [49]. Furthermore, a colorimetric-fluorescent bimodal sensing probe with a unique photophysical process was designed [50]. Similarly, a bimodal proportional colorimetric/fluorescent method was developed for the high-performance determination of nitrite in complex matrices [51], and the synthesis and evaluation of an azulene-based nitrite chemodosimeter revealed that azulene probes can also detect the presence of nitrite [52]. The fluorescent colorimetric probe P-NO2 has been used for detection in the real environment [53]. In addition, the Cu-MOF-modified exfoliated graphite paper (EGP) was used as a signal reporter gene for visual and electrochemical dual-mode sensing of nitrite [54]. On the one hand, the dual-mode combined detection of colorimetric and fluorescence improves the accuracy of the detection and enhances the flexibility of the application; on the other hand, the combination of colorimetric and chemical sensors enables sensitive detection in real time. Therefore, it is of great significance that multimodal detection permits the simultaneous detection and verification of multiple entities.
To further improve detection rate and accuracy, in recent years, more and more studies have been conducted to combine the smartphone with the colorimetric method. Generally speaking, the principal method of detection is the utilization of a mobile phone’s camera or another identification tool to ascertain the color shade of the reagent subsequent to the color development reaction, and the processing of this data by a specific application or software on the mobile phone. Then, the processed data are the corresponding nitrite level. Therefore, this allows for the ultra-sensitive multimodal detection of nitrite. Compared with single-signal detection, the multimode sensing system can achieve self-verification and obtain more reliable detection results [55]. The plasma-enhanced oxidase-like activity provides an intelligent method for achieving high sensitivity [56]. Similarly, the dual-channel colorimetric sensor has made some progress while detecting nitrite. It is worth mentioning that researchers have made the first full-wavelength-coverage visible light stimulated dual-channel colorimetric sensor for visual detection [57]. For on-site quantification, the Griess-reagent-doped hydrogel kit combined with a smartphone makes it easier and more environmentally friendly to quantify nitrate and nitrite on-site [58]. A similar method has the advantage of being environmentally friendly [59]. In addition to the kits, there is also research on portable spectrophotometers, which do not differ from commercial kit measurements. Most importantly, they are noteworthy for their low price and simplicity of operation, making them a low-cost alternative to commercial kit testing equipment [60]. Other investigators have also demonstrated an affordable, smartphone-based field sensing tool that provides results for nitrite that are in good agreement with laboratory-grade spectrophotometers [61].
Colorimetric detection is a very widely used method that relies on the shade of the reaction color between the sample and the reagent for quantification [37]. In some of the existing cutting-edge research work, it has been learned that the use of nanomaterials, smartphones, and combination with a variety of modalities is possible. Therefore, it might play an important role in the future of the colorimetric detection of nitrite.

3.3. Methods Based on Fluorescence Detection

Fluorescence detection is a widely used assay for nitrite detection. Its working principle is mainly based on the energy level jump mechanism of the absorption and fluorescence spectra of material molecules, when the material molecules absorb a certain wavelength of light. They can instantly emit light longer than the wavelength of excitation light, i.e., fluorescence. In recent years, although fluorescence spectroscopy analysis is used as a good detection method with its high selectivity and sensitivity, there are some shortcomings in its application. For example, only a few compounds can produce fluorescence, and most molecules cannot emit fluorescence. To solve this problem, researchers usually introduce derivable functional groups to convert non-fluorescent substances into fluorescent ones.
Fluorescent probes are molecules with special fluorescent properties that respond sensitively to changes in the environment in which they are found. Such molecules have characteristic fluorescent properties in the ultraviolet–visible–near-infrared region. For this reason, fluorescent probes are also known as fluorescent chemical sensors or “molecular devices”. Overall, due to their high sensitivity and wide range of applications, fluorescent probes have become an indispensable tool in modern scientific research.
The presence of fluorescent probes is widely used for their excellent specificity, and nitrite in water samples and sausages can be determined using the fluorescent probe colorimetric method [62]. Detailed information is shown in (Figure 6a) and described below.
In recent years, much attention has been paid to modifying the recognition groups in fluorescent moieties and modulating the energy transfer process for efficient analyte detection. Therefore, it is of great importance to design specific functional probes through the precise modulation of the binding sites of fluorescent moieties. For example, scientists have chosen 2-(2-amino-4-carboxyphenyl)benzothiazole (ortho-BT) to design a probe for the detection of nitrite by precisely modulating the benzothiazole binding site. Only the fluorophore bond in the orthogonal position of the aniline portion of the fluorophore can specifically recognize nitrite [63].
The materials required for fluorescent probes have increasingly become a key direction of research; therefore, many materials have been developed as fluorescent probes. For example, a series of explorations have been made on amphiphilic carbon dots, and an amphiphilic carbon dot has been prepared from white berries [64]. Meanwhile, ternary ZnCdS quantum dots have been synthesized by aqueous synthesis using air-stabilized compounds [65]. CdS quantum dots capped with polyethyleneimine [66] have also been used in fluorescent probes. Similarly, a new near-infrared fluorescent probe was designed and synthesized using the principle of “covalent assembly”, which showed excellent selectivity and high sensitivity to nitrite [67]. In addition, fluorescent silicon quantum dots were designed and synthesized. Additionally, fluorescent silicon quantum dots (Si QDs) have excellent water dispersibility, photostability and salt resistance [68]. The highly fluorescent carbon dots (R-CDs) synthesized from sodium ascorbate and polyethyleneimine at room temperature are energy-saving, environmentally friendly and easy to put online [69]. Researchers have continued innovating and a new type of Fe-CDs (Fe-doped carbon dots) has been prepared by MDES (metal deep eutectic solvent) with high sensitivity and selectivity [70]. Furthermore, a carbon quantum dot based on a primary aryl amine such as resorcinol was constructed and prepared by an efficient one-pot hydrothermal route using isophthalamide [71]. Additionally, acenaphthene [1,2-d]imidazole derivatives were used as proportional colorimetric probes [72]. Similarly, the Rh6G@MOF-5 nanoprobe provides insights into the fabrication of low-cost and conveniently operated MOF sensors in analyte detection [73].
The combination with nanomaterials has improved the performance of fluorescence detection. The fluorescence of gold nanoparticles (AuNPs) is strongly burst by Mb, for the sulfhydryl or amino structure on the surface of Mb can be bonded to the surface of AuNPs through the formation of Au-S or Au-N bonds. Furthermore, Mb readily reacts with nitrite to form azo products in acidic media. Then, with the increase in nitrite concentration, the fluorescence of Mb-AuNPs was gradually restored, the turn-on fluorescence sensing of nitrite was achieved. This provides a feasible solution for the rapid response [74] (Figure 6b). In addition, tannic-acid-protected fluorescent copper nanoclusters (TA-Cu NCs) [75] have also been used as good nanomaterials.
Multifunctional and multimodal detection through the development of new detection modes has also been a development. Researchers have developed a smartphone-integrated paper sensor based on manganese-doped silicon quantum dots (Mn-Si QDs) for the visual dual-mode multicolor/multi fluorescence determination of nitrite [76]. A lot of studies have been carried out on bifunctional fluorescent probes, and 2-(1H-benzimidazol-2-yl) aniline (BMA) has been used as a simple bifunctional probe for the samples in different environments. The response of BMA to nitrite under acidic conditions has been highly selective and sensitive. Most importantly, BMA has been successfully used for detection in foods, and good recoveries were obtained by adding standard sodium nitrite [77].
Novel fluorescence sensors have also been hotspots for development in recent years. Similar to colorimetric methods, fluorescence methods are often combined with smartphones, and many advanced technologies are gradually being applied to fluorescence detection as research work advances. Researchers have constructed a new fluorescence sensor that combines a power source, light source, filter, sample cell, and smartphone. The sensor has been used to detect nitrite in cured meat and pickles, and it is interesting that the results have been found to be consistent with the results of fluorescence and spectrophotometer methods [78]. In other words, the sensor has the advantages of both fluorescence and spectrophotometer methods. Similarly, based on a self-programmed python program (Figure 6c,d), researchers also prepared a portable fluorescent device based on smartphones, whose good sensing performance provides a good fluorescence platform [79]. The platform has chosen NSGQD (nitrogen-sulfur co-doped graphene quantum dots) for the quantification of nitrite, which is coupled with a smartphone using color detection by its software [80]. Hydrogels are three-dimensional networks of polymers that can hold a large amount of water. In modern assays, the use of fluorescent probes/hydrogels [81] in combination with smartphone technology allows for immediate and simultaneous ultra-sensitive detection of nitrite. In a word, the use of fluorescent probes/hydrogels has improved the performances of traditional fluorescent methods. In addition, a new detection strategy using IR780 dye as a NIR (near-infrared) probe has been invented by combining NIR probe technology with smartphone imaging. The new system is capable of detecting NO2 ions in water resources and complex food matrices with high sensitivity and selectivity [82].
Fluorescent probes have become one of the most important methods for the detection of nitrite in small-volume systems due to their simplicity of preparation, stability, sensitivity and suitability [74]. However, the sensing performance of fluorescent probes depends largely on the materials used in them. Different fluorescent materials have their own drawbacks, such as the high toxicity of organic fluorescent dyes that are harmful to human body and the low fluorescence intensity of carbon-based fluorescent nanomaterials. Therefore, the development of nanomaterials can improve the security of fluorescent probes. More and more experimental studies have shown that the use of some advanced instruments can contribute positively to the harmlessness and environmental friendliness. Thus, it is important to note that scientific research should be conducted while maintaining the concept of green and sustainable development.

4. Biosensors

In recent years, biosensors have attracted attention in nitrite detection for their high specificity and great real-time performance. The biosensor was first used for glucose detection, which was made by including glucose oxidase in a polyacrylamide colloid and curing it. Then, the colloidal membrane was fixed on the tip of a diaphragm oxygen electrode. It is worth mentioning that this type of sensor belongs to the class of enzyme-based biosensors, which laid the detection foundation for the later generation of various biosensors.
Biosensors are usually made with biologically active materials and physicochemical transducers organically. There can be many kinds of applications regarding bioactive materials. Both anthocyanin encapsulated in the CMC/PVA (carboxymethyl cellulose/polyvinyl alcohol) matrix [83] and diastase have great potential as biologically active materials. As another example, scientists have studied HS-β-cyclodextrin coordination methanobactin/gold nanoparticles as a biologically active material [84] and it has a high sensitivity, which has provided another good idea for us. The main types of biosensors used in the detection of nitrite include the following. (1) Enzyme-based biosensors: specific enzymes are used as biorecognition elements to quantify nitrite by metabolites produced or substrates consumed in enzymatic reactions. (2) Microbe-based biosensors: metabolic pathways within the microbial cells are used to respond to the presence of nitrite. Typically, they have good stability and reusability and are suitable for rapid on-site testing. (3) Nucleic acid-based biosensors.
Biosensor technology, although highly specific, has a relatively short lifespan, and its stability is not long-term. Therefore, future biosensors could be improved in terms of lifespan to obtain long-term stability [85]. To address this issue, scientists have made some progress in longevity through the combination of the nitrate reductase (NR) enzyme from the fungus Neurospora crassa and an electrochemical biosensor, which retained more than 70 per cent of its activity over 3 months [86].
In the actual operation of detecting nitrite, the biosensor technology is often cross-used with other technologies to enable multi-mode detection and mutual verification. For example, a novel nitrite biosensor based on carbon quantum dots (PA-CDs), constructed and prepared by an efficient one-pot hydrothermal route using primary aryl amines (PA), is not only a combination of fluorescence detection technology and biosensing technology but also broadens new nano-sensor detection methods [71]. As another example, the combination of biosensor and electrochemical technology is also an improved technique. Hemoglobin (Hb), as a biologically active material, was immobilized on the Co3O4-CNF/CILE surface. The electrochemical biosensors were prepared using Nafion as a protective film to improve immunity to interference and selectivity and have been used for the quantitative detection of real samples [87]. Similarly, a novel electrochemical biosensor for nitrite was synthesized using sodium carboxymethyl cellulose as a reducing and stabilizing agent in the form of Au-MoS2 nanoflower-modified nanocomposites. The proposed electrochemical biosensor for nitrite is characterized by a wider linear range, a lower detection limit, and higher sensitivity [88]. In addition to this, the novel cyanide voltametric biosensor based on the inhibitory effect of cyanide on cytochrome c nitrite reductase (ccNiR) is promising in the quantification of nitrite [89].
The combination of a biosensor and a 3D printed sensor has been applied to analyze real biological samples, demonstrated by the amperometry detection of uric acid and nitrite in the linear range of 0.5–250 μmol L−1, with LODs of 0.03 μmol L−1 for nitrite. Furthermore, not only can it be seen to be comparable to traditional modified electrodes in terms of analytical properties, but the surface treatment of the 3D printed sensor also provided improved electrochemical performance for the direct determination of nitrite [90].
Nitrite detection in medicine has suffered from low sensitivity and cumbersome operation, which make it hard to meet the immediate detection needs of nitrite detection in precision medicine. Thus, researchers proposed a cyanocobalamin (VB12) bionic enzyme-assisted ion-selective amperometry biosensor based on a 3D porous conductive matrix (PCM). This can facilitate rapid and accurate nitrite monitoring in complex biofluids with results that are very close to those of commercial nitrite analyzers. Most importantly, it costs less than commercial nitrite analyzers and can be a useful tool in home healthcare realization by providing a possible tool [91].
Biosensors have been effectively used to determine the levels of the environmental pollutant nitrite. It is reported that a new type of electrochemical biosensors based on the MT-NBEB (metronidazole-treated biocathode), a novel electrochemical biosensor for nitrite-reducing bacteria successfully detected nitrite in five wastewaters [92]. J. Wang et al. have conducted studies that have determined the nitrite content of wastewater. This provides a feasible direction for future biosensors to detect the corresponding specific substances [93]. Furthermore, it is worth mentioning that when detecting nitrite in the environment, biosensors based on microbial fuel cells (MFCs) are more likely to be in bioelectrochemical early warning devices [94].
Electro enzyme sensors have been a very promising nitrite detector, while the difficulty of its production and storage stability remains a difficult problem. The transformation of the process (Figure 7a–c) should be studied again, thus reducing the difficulty of manufacturing and further storage stability [95]. For example, the synthesis of a surfactant-free CuBr@Pt nanoparticles (CuBr@Pt NPs) contributed to the reduction of the electrocatalyst and the increase in the detection range. CuBr@Pt-15% has also shown a better behavior than previous work, which reveals the material is promising [96]. In this aspect of cost reduction, a wooden (bio)sensing device fabricated by a diode laser-induced graphitization provides an idea for related scientific work. It is worth mentioning that this sensor has a wide range of applicability [97]. Therefore, cost reductions and process improvements are important. Research in recent years has been moving toward multifunctionality and multi-analyte biosensor (Figure 7d). This is a trend for future development [98].
Continuous technological innovation has led to a shift from traditional enzyme-based sensors to cellular receptor-based biosensors. This shift has improved the sensitivity and specificity of detection and broadened their application in complex samples. Despite significant progress, biosensors remain challenges in nitrite detection. For instance, to meet the requirements of long-term monitoring, it is necessary to further enhance the stability and reusability of the sensors. Additionally, further research and optimization are required to enable the detection of extreme environmental conditions, such as high salinity or extreme pH conditions. The development of biosensors will continue to focus on achieving high sensitivity, high selectivity, low cost, and user-friendliness. Some of important methods described above and the involved detection information are shown in Table 1. Definitions and explanations corresponding to the abbreviations are shown in Table 2.
From the several representative detection methods listed in the Table 1, it can be found that the fluorescence method based on BDP-OPD for the detection of nitrite concentration has a relatively low detection limit, which can be as low as 0.17 nM; that is to say, its detection sensitivity is higher. This provides a good idea for corresponding researchers; for example, in the corresponding experimental detection process, the content of nitrite to be measured is very low, so the fluorescence method will be a good choice. Combined with the methods mentioned in the table, we can see that the detection ranges of these four methods are relatively wide, and there is no significant difference. In the actual detection, it can also be based on the cost of the experiment and the difficulty of handling the material to select the appropriate method.

5. Electrochemical Sensors

Electrochemical sensor is a kind of instrument that uses the electrochemical properties of the measured substance to convert its chemical quantity into electrical quantity. With high sensitivity and selectivity, it is widely used in detecting the content of nitrite. Its specific working principle is to use the material and nitrite to interact; the redox reaction occurs, producing an electrochemical active substance. This active substance can be converted into the detected electrochemical signals, and nitrite can be oxidized directly on the surface of the electrode. According to different output signals, electrochemical sensors can be classified as potentiometric, voltametric, impedance, and other sensors. There are also many different methods, such as differential pulse voltammetry, amperometry, etc. However, in the actual measurement of nitrite, it is the material used in the electrochemical sensor that affects the accuracy to a great extent.
The applications of different nanomaterials in the field of electrode materials in recent years has been reviewed, providing a reference for the screening and application of suitable electrode materials for nitrite electrochemical detection sensors in the future.
The nanomaterials are classified into three categories, namely, precious metal materials, carbon materials, and nanocomposites. Among the three, nanocomposites are nowadays widely used in the fabrication of chemical sensors for nitrite, which has a very good development prospect. The detection range and limit of detection of different electrodes for the determination of nitrite are shown in Table 3. Definitions and explanations corresponding to the abbreviations are shown in Table 4.
Some of the advances in metal nanomaterials include the development by researchers of an easily produced bimetallic composite of palladium and silver bimetallic nanoparticles loaded on carbon black and tapioca for modified glassy carbon electrodes. The fabricated sensor was used for the electrochemical determination of nitrite using differential pulse voltammetry with a linear range of 5.0–1000 μmol L−1 and a detection limit of 1.24 μmol L−1. The proposed method was applied to the detection of target analytes in environmental and food samples and was sensitive to the electrochemical sensing of nitrite [99].
The majority of electrochemical sensor electrodes are made up of electrodes made of nanocomposites. Researchers prepared and modified gold nanorods (AuNRs) and tungsten disulfide (WS2) nanocomposites on the surface of a carbon ionic liquid electrode (CILE). Hemoglobin (Hb) with peroxidase activity was further immobilized on the electrode surface, and a novel modified electrode (Nafion/Hb/AuNRs-WS2/CILE) was prepared, which has high conductivity and good biocompatibility [100]. Furthermore, well-dispersed and uniformly sized silver nanoparticles dispersed on polyaniline/reduced graphene oxide nanocomposites were prepared by a biphasic method in the absence of external oxidants. With a wider peak separation window, they can be used for the electrochemical detection of two analytes in water sources [101]. Layered FeTMPyP/Sr2Nb3O10 nanocomposites have been successfully synthesized by embedding positively charged iron 5,10,15,20-tetrakis(N-methylpyridin-4-yl) porphyrin (FeTMPyP) in KSr2Nb3O10. The results showed that FeTMPyP/Sr2Nb3O10 exhibited excellent performance for the electrochemical oxidation of nitrite. In addition, this nanocomposite exhibited good stability and excellent interference resistance [102]. Novel bismuth molybdate@polydopamine-Au nanocomposites (Bi2MoO6@PDA-Au) were synthesized, which exhibited good reproducibility, reusability, long-term stability, fast response time, and anti-interference properties [103]. Au@CQDs-MXene nanocomposites with good electrical conductivity and electrocatalysis were prepared using MXene (two-dimensional transition metal carbides, nitrides) with good electrical conductivity as the immobilized matrix [104]. An electrochemical sensor for nitrite based on in situ prepared copper oxide nanoparticles modified carbon cloth (Cu NPs/CC) was prepared with simple and efficient detection [105]. A novel and sensitive surface-enhanced Raman scattering (SERS) platform for silver-coated nanofibers was developed, and silver nanoparticles (NPs) were assembled on nanofibers for the first time using electrospray technology [106]. Additionally, the researchers prepared a novel non-enzymatic nitrite (NO2) electrochemical sensor based on Au-poly(thionine)-tin oxide/graphene nanosheets (Au-PTH/SGN) nanocomposites [107]. Furthermore, AuNP/MnOx-VOx/ERGO electrode was employed for the determination of hydrazine and nitrite in river water and food samples, which showed recoveries ranging from 91.0% to 113.0% [108].
In the pursuit of higher sensitivity, better stability, wider linear range, and excellent selectivity of nitrite chemical sensors, the focus of research has shifted to the nanomaterials used. Therefore, more and more developments in these nanomaterials have been made in recent years. A simple and highly selective electrochemical sensor based on carbonized lotus root (CLS) has been developed, and the intrinsic structure of this natural biomass is expected to be used to design porous carbon for electrochemical sensors [109]. One-dimensional honeycomb carbon nanofibers (HCNFs) were synthesized by electronic techniques with good properties and recyclability [110]. A UCL nano sensor was designed, which is expected to be used in the future as a technique for detecting nitrite in food products [111]. As another example, ZrNPs/Fe3O4/GO nanocomposites have been prepared by in situ synthesis for the first time, and modified glassy carbon electrodes were prepared using the synthesized nanocomplexes as modifiers for the detection of nitrite ions in foods [112]. In addition, Au/Ni nanotubes were prepared on carbon paper by depositing Au nanoparticles on Ni nanotubes, and Au nanoparticles were uniformly distributed on Ni nanotubes. This has led to great improvement in the sensing performance of the sensor due to the synergistic effect of the two [113]. In addition, an electrochemical sensing platform based on acid-treated Fe3O4@SiO2 nanoparticles was used to detect nitrate and nitrite [114]. Scientists used β-cyclodextrin-modified gold nanoparticles (SH-β-CD@AuNPs) substrate, metal nanoparticles, and cyclodextrin supramolecular compounds to prepare a super-selective and Raman-active substrate. It can be used for the detection of nitrite and nitrate–nitrogen assays [115].
A polyaniline-linked tetra amino cobalt phthalocyanine surface functionalized ZnO hybrid nanomaterial (PA-TaCoPc@ZnO) for the sensitive electrochemical detection of nitrite is constantly moving toward achieving cost-effectiveness [116]. Similarly, nanocomposites of ZIF-8@ZIF-67/Au core–shell metal organic framework were easy to design and synthesize at low cost. The sensors made from them have the same advantages in detection that most nanomaterials possess [117].
Regarding the quantitative methods of electrochemical sensors, they can be mainly classified into potentiometry measurement, voltammetry measurement, impedance measurement, and other methods. Differential pulse voltammetry (DPV) and amperometry methods of GCE are usually used for the quantitative electrochemical analyses of trace level nitrite ions. Meanwhile related studies have investigated the inferred effect of various anions and cations on the oxidation peak current of nitrite by employing an amperometry method. A stable and reliable current response was obtained for the analysis of nitrite in water samples [118]. As another example, the electrochemical performance of a sensor developed using NPs was investigated using electrochemical methods to quantify nitrite [119]. In addition to this, the combination of electrochemical sensors and smart devices further improves detection efficiency. A combination of sensors, colorimetry, and smartphones detect nitrites using gold-covered graphene [120].
In short, electrochemical sensors in the detection of nitrite in the future direction of development may be (1) more sensitive, more selective [110], and combined with a variety of detection methods and new materials to achieve the rapid, accurate, and reliable detection of nitrite; (2) more and more miniaturized and portable, easy to carry, and able to adapt to a variety of complex environments and applications; (3) including a variety of functions [120], such as the simultaneous detection of multiple substances and real-time monitoring, to meet different needs; (4) more intelligent and able to judge and process data independently, improving detection efficiency and accuracy; and (5) more low-cost, reducing the cost [116] of use and promoting its application in a wider range of fields.
Table 3. Detection range and detection limit of different electrodes for the determination of nitrite.
Table 3. Detection range and detection limit of different electrodes for the determination of nitrite.
ElectrodesDetection RangeDetection LimitReferences
PdAg/C/TP/GCE5.0–1000 μM1.24 μM[95]
Nafion/Hb/AuNRs-WS2/CILE1.0–22.0 mM0.33 mM[96]
AgNPs@PANI/rGO/GCE1.0–28.2 μM56 nM[97]
FeTMPyP/Sr2Nb3O100.02–1.35 mM1.2 μM[98]
Bi2MoO6@PDA-Au0.3 μM–4.4 mM0.08 μM[99]
CuO NPs/CC0.5–3000 μM0.043 μM[101]
Ag-coated Nanofiber SERS Platform10−1–10−4 M2.216 × 10−12 μM[102]
AuNPs-PTH/SGN/GCE0.0002–0.1277
0.1277–2.8 mM
0.06 μM[103]
AuNP/MnOx-VOx/ERGO/GCE30–1000 μM10.0 μM[104]
CLS/GCE0.5–4000 nM0.09 μM[105]
Bi/HCNFs-SPE0.1–800 μM19 nM[106]
Au/Ni-60s NTs0.4–40,000 μM
40–130 mM
0.13 μM[109]
Fe3O4@SiO20.01–1.0 mM3.33 μM[110]
PA-TaCoPc@ZnO1–10 μM21 nM[112]
AGO0.5–85 μM250 nM[116]
Table 4. Definitions and explanations corresponding to the abbreviations appearing in the Table 3.
Table 4. Definitions and explanations corresponding to the abbreviations appearing in the Table 3.
NomenclatureDefinitions and Explanations
Nafion/Hb/AuNRs-WS2/CILENafion/Hb/AuNRs-WS2/CILE is a composite system containing a combination of Nafion, haemoglobin (Hb), gold nanorods—tungsten disulphide (AuNRs-WS2), and carbon fiber ionic liquid electrode (CILE)
AgNPs@PANI/rGO/GCEA glassy carbon electrode (GCE) modified by silver nanoparticles modified polyaniline/reduced graphene oxide complexes
FeTMPyP/Sr2Nb3O10A complex consisting of tetramethylpyrrolidine cationic iron complex (FeTMPyP) with strontium niobate columbium (Sr2Nb3O10) in a layered chalcogenide structure
PDAPolydopamine (PDA), which can form a uniform coating on a wide range of surfaces and enhance material stability and functionality
CuO NPs/CCCarbon fiber complexes modified by copper oxide nanoparticles
Ag-coated Nanofiber SERS PlatformPlatform with superb surface-enhanced Raman scattering effect from silver-coated nanofibers
AuNPs-PTH/SGN/GCEComposite combining gold nanoparticles, polythiophene and graphite nanosheets with glassy carbon electrodes
AuNP/MnOx-VOx/ERGO/GCEAn innovative composite system combining the advantages of gold nanoparticles, manganese oxides, vanadium oxides and graphene oxide with glassy carbon electrodes
PdAg/C/TP/GCEComposite structure combining palladium-silver alloy, carbon material and triphenylamine on a glassy carbon electrode
CLS/GCECell lysate conjugate to glassy carbon electrode
AGOamine-functionalized graphene oxide
Bi/HCNFs-SPEA composite material formed by combining bismuth with hyperbranched carbon nanofibers and applying it in a solid phase extraction technique
Au/Ni-60s NTsComposites composed of gold, nickel and nanotubes
PA-TaCoPc@ZnOA polyaniline-linked tetra amino cobalt phthalocyanine surface functionalized ZnO hybrid nanomaterial

6. Intelligent Detection Methods

With the development of IoT and AI technologies, intelligent detection methods have been gradually emerging in nitrite detection. The application of smart sensors and wireless transmission technology makes online monitoring and the real-time reporting of nitrite possible. In addition, data processing methods based on machine learning and deep learning have provided new ideas and solutions for nitrite detection, and there are some gas sensors that can be used as a method of detection.
The designed handheld detector transmits the excitation signal indirectly via Bluetooth to transmit the response data to a smartphone [121]. Similarly, a new sensor for aquaculture was proposed with a wireless portable intelligent sensing system that was used to monitor water quality in real time and receive feedback from experts. Furthermore, machine learning algorithms were used to train the microcontroller-based system, determine the temperature of the water samples, and read the concentration of the substances. The performance of the sensors and sensing system is highly reproducible, reliable, and stable and is part of a smart sensing network for continuous water quality monitoring [122]. In addition, automated analyzers based on pulsed-flow analysis systems using solenoidal micropumps have emerged. They perform analysis cycles every six hours, making them suitable as versatile analytical platforms for environmental research [123]. In addition, a convenient portable gas manometer method was developed for the detection of nitrite (NO2). NO2 and sweeteners reacted specifically under acidic conditions to produce cyclohexene and nitrogen, and the pressure of the reaction bottle was measured with a portable gas manometer. A gradual increase in pressure inside the bottle is proportional to the increase in NO2 concentration, resulting in the detection of NO2 [124]. In addition, compared to the traditional method, the stacked limit learning machine model based on information entropy weights will have a higher measurement accuracy than the traditional model, and the test will be faster than the traditional method [125].
Future directions of detection may include the following: (1) the application of new nanomaterials, e.g., gold nanoparticles and carbon nanotubes, which can improve the sensitivity and selectivity of detection methods; (2) the combination of multimodal detection techniques, including spectroscopy combined with electrochemical methods, which can achieve the combined advantages of high sensitivity, high selectivity, and low cost; (3) intelligent data processing and analysis [121] using big data, cloud computing, and other technologies to intelligently process and analyses the detection results to improve detection efficiency and accuracy.

7. Nitrite Alternatives and Degradation

Nitrite is widely used as coloring agents and preservatives in food. In recent decades, new technologies have been explored to replace synthetic chemical preservatives with natural preservatives that have potential applications in the meat industry [126]. Also, as a coloring agent, the corresponding coloring agents are likewise being sought to replace nitrite.
Relevant studies have shown that low doses of sodium nitrite promote the dynamic conversion of nitrosylated peptide fragments of myoglobin, thereby preserving the color of meat [127]. Therefore, the development of alternative additives is perhaps the best way to replace nitrite in meat products [128].
Motivated by the study of the effects of nitrite on meat products, a similar low-hazard alternative has been actively sought based on similar principles of color development. It was found that the cochineal dye was observed to be adsorbed on the surface of the layered compounds and on the mortar storage. It ensured a more stable pink/red color than the other product formulations. Therefore, layered matrices adsorbed with cochineal may be a suitable alternative for obtaining the pink/red color characteristics of cooked meat products through the application of natural hybrid dyes [129]. In addition, researchers selected two strains from fermented foods with excellent myoglobin and high myoglobin conversion capacity (Met-Mb) to red nitrosomyoglobin (Mb-NO) as natural bio-coloring agents and preservatives to replace nitrite in meat products, and the application of these two strains will reduce the health risk of nitrite [130]. The effects of black tea broth on the basic composition, texture, surface color, sensory, antioxidant activity, fat oxidation, protein oxidation, and microbiological quality of steamed beef have been investigated using black tea broth as a research object, and it was found that black tea broth had comparable effects on the texture, flavor improvement, and antioxidant effects of steamed beef as those of nitrite, which provides theoretical support for the application of black tea broth as a natural alternative to nitrite in the preservation of beef [131]. In addition to this, natural extracts have been used [132] of beetroot powder (BP) [133] instead of nitrite. Similarly, it has been found that the use of fruit and vegetable powders in fried beef meatballs can also replace sodium nitrite in the meat processing industry [134]. Detailed information is listed in the Table 5.
In food and the environment, too much nitrite tends to bring bad effects, so the degradation of nitrite is of great importance. There are chemical and biosafety problems in fermented vegetables, and biogenic amines and nitrite generation can be solved by using unique fermentation agents, high pressure, ultrasonic, and cold plasma [135]. Meanwhile, the corresponding studies have shown that electrochemical catalysis of nitro nitrate generation of nucleophilic intermediates facilitates nitrite removal and degradation [136]. In addition, anaerobic ammonia oxidation can be used for economic treatment of wastewater without addition of organic matter and aeration [137]. In the study of nitrite reduction to nitric oxide in fungi, the two synthesis mechanisms of nitric oxide provide some ideas for the degradation of nitrite [138]. In addition, RAS (Return Activated Sludge) water treatment plants can also be used to treat nitrite [139].

8. Conclusions and Prospects

The efficacy of nitrite, the various ways of detecting nitrite, and the outlook for the future development of nitrite are summarized above. Nitrite, a substance widely present in food, the human body, and the environment, has played a positive role in coloring agent, preservative in food and medicine. But on the contrary, it is known for its teratogenic, carcinogenic, and mutagenic effects on living organisms. Also, it is a pollutant in the environment such as in the water. Therefore, nitrite is a very controversial substance, and the various testing methods mentioned above aim to limit and monitor nitrite. From the point of view of the detection of nitrite, the detection methods can be divided into traditional methods, optical detection methods, biosensor methods, electrochemical sensor methods, and intelligent detection methods. Each of these methods has its own advantages and disadvantages. The details are listed in Table 6.
Traditional detection methods have long been used for their sensitivity and precision, while in recent years, research has led to innovations such as the preparation of more efficient detectors and the optimization of pre-treatment protocols. Among the various optical methods, fluorescence and colorimetric methods account for a large proportion, and both have high sensitivity and specificity. However, fluorescence methods are susceptible to interference from autofluorescence or background fluorescence, and colorimetric methods need to be further improved due to their low sensitivity and system instability. The vast majority of research nowadays has possessed new fluorescent probes for the purpose of achieving less matrix interference and accurate detection.
In conclusion, nitrite has great challenges in future development. (1) Regarding the sensitivity and specificity of the detection, we can choose the most suitable detection methods and detection equipment available in combination with actual needs. (2) There are many interfering substances in food samples, and it is important to establish suitable pretreatment steps and develop more advanced detection equipment. (3) The existing biosensors for nitrite detection are still in the research stage, and it is expected biosensors with longer stability periods as well as detection specificity will be studied, combining multiple detection methods to achieve multi-modal detection. (4) New composite nanomaterials should be introduced for use in various types of sensors on the enhancement of sensitivity and detection efficiency. (5) The monitoring of nitrite should be enhanced, and the intake of excessive nitrite will greatly enhance the probability of human cancer, which needs to be taken seriously by the regulatory authorities. (6) New alternatives to nitrite as food additives should be actively explored, which can be targeted from natural extracts, pinpointing the gradual substitution of natural extracts for nitrite. (7) The multi-modal combinations of the degradation of nitrite concentration should be studied. (8) Materials, etc., should be developed.
In the future, it will be wise to avoid the shortcomings of different detection methods and develop their advantages so as to achieve more sensitive, rapid, effective and efficient detection of nitrite in food, the human body, and the environment. This will have an important impact on the human living environment. Corresponding laws and regulations should also be strengthened to limit nitrite to improve human life and health and provide protection for life safety.

Author Contributions

H.L.: Conceptualization, Methodology, Data Curation, Writing—original draft. Y.S.: Validation, Data Curation, Writing—review and editing. B.Z.: Conceptualization, Resources, Writing—review and editing. H.X.: Conceptualization, Resources, Writing—review and editing, Supervision, Project administration, Funding acquisition. All authors have read and agreed to the published version of the manuscript.

Funding

This review was supported by the Research Project of State Key Laboratory of Food Science and Resources, Nanchang University, China (SKLF-ZZB-202328).

Data Availability Statement

No data were used in the manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Tang, T.T.; Zhang, M.; Law, C.L.; Mujumdar, A.S. Novel strategies for controlling nitrite content in prepared dishes: Current status, potential benefits, limitations and future challenges. Food Res. Int. 2023, 170, 112984. [Google Scholar] [CrossRef] [PubMed]
  2. Shen, Q.; Zeng, X.; Kong, L.; Sun, X.; Shi, J.; Wu, Z.; Guo, Y.; Pan, D. Research Progress of Nitrite Metabolism in Fermented Meat Products. Foods 2023, 12, 1485. [Google Scholar] [CrossRef]
  3. Honikel, K.O. The use and control of nitrate and nitrite for the processing of meat products. Meat Sci. 2008, 78, 68–76. [Google Scholar] [CrossRef] [PubMed]
  4. Sriboonyong, T.; Kawamatawong, T.; Sriwantana, T.; Srihirun, S.; Titapiwatanakun, V.; Vivithanaporn, P.; Pornsuriyasak, P.; Sibmooh, N.; Kamalaporn, H. Efficacy and safety of inhaled nebulized sodium nitrite in asthmatic patients. Pulm. Pharmacol. Ther. 2021, 66, 101984. [Google Scholar] [CrossRef] [PubMed]
  5. Zhang, M.; Truver, M.T.; Hoyer, J.L.; Chronister, C.W.; Goldberger, B.A. Presumptive identification of nitrite by Griess reagent test strips-Case reports of fatal poisoning with sodium nitrite. J. Anal. Toxicol. 2023, 47, 746–749. [Google Scholar] [CrossRef] [PubMed]
  6. Chazelas, E.; Pierre, F.; Druesne-Pecollo, N.; Esseddik, Y.; de Edelenyi, F.S.; Agaesse, C.; De Sa, A.; Lutchia, R.; Gigandet, S.; Srour, B.; et al. Nitrites and nitrates from food additives and natural sources and cancer risk: Results from the NutriNet-Sante cohort. Int. J. Epidemiol. 2022, 51, 1106–1119. [Google Scholar] [CrossRef] [PubMed]
  7. El-Nabarawy, N.A.; Gouda, A.S.; Khattab, M.A.; Rashed, L.A. Effects of nitrite graded doses on hepatotoxicity and nephrotoxicity, histopathological alterations, and activation of apoptosis in adult rats. Environ. Sci. Pollut. Res. 2020, 27, 14019–14032. [Google Scholar] [CrossRef] [PubMed]
  8. National Primary Drinking Water Regulations. Technical Factsheet on Nitrate/Nitrite. Available online: https://nepis.epa.gov/Exe/ZyPURL.cgi?Dockey=P10154E3.txt (accessed on 25 June 2024).
  9. Kotopoulou, S.; Zampelas, A.; Magriplis, E. Dietary nitrate and nitrite and human health: A narrative review by intake source. Nutr. Rev. 2022, 80, 762–773. [Google Scholar] [CrossRef]
  10. GB 5009.33-2016; National Food Safety Standard-Determination of Nitrite and Nitrate in Foods. National Health and Family Planning Commission of the People’s Republic of China; State Food and Drug Administration: Beijing, China, 2016.
  11. Charles, J.P.; Jennifer, R.K. Colorimetric Determination of Nitrate Plus Nitrite in Water by Enzymatic Reduction, Automated Discrete Analyzer Methods; USGS Numbered Series; US Geological Survey (USGS): Reston, VA, USA, 2011; Volume 34. [CrossRef]
  12. Ding, H.; Zhang, J.Y.; Zhang, J.B. Discussion on standard management of food additives nitrate and nitrite in meat products. Chin. J. Food Hyg. 2021, 33, 364–368. [Google Scholar]
  13. Hu, J.; Christison, T.; Rohrer, J. Determination of dimethylamine and nitrite in pharmaceuticals by ion chromatography to assess the likelihood of nitrosamine formation. Heliyon 2021, 7, e06179. [Google Scholar] [CrossRef] [PubMed]
  14. Tian, Y.; Feng, Y.; Tao, X.; Yao, S.; Chong, X.; Yin, L. Determination of nitrite ion in rifampicin and rifapentine capsules by solid phase extraction-ion chromatography. Chin. J. New Drugs 2023, 32, 2218–2224. [Google Scholar]
  15. Coviello, D.; Pascale, R.; Ciriello, R.; Salvi, A.M.; Guerrieri, A.; Contursi, M.; Scrano, L.; Bufo, S.A.; Cataldi, T.R.I.; Bianco, G. Validation of an Analytical Method for Nitrite and Nitrate Determination in Meat Foods for Infants by Ion Chromatography with Conductivity Detection. Foods 2020, 9, 1238. [Google Scholar] [CrossRef] [PubMed]
  16. Lim, H.S.; Lee, S.J.; Choi, E.; Lee, S.B.; Nam, H.S.; Lee, J.K. Development and validation of an ionic chromatography method for nitrite determination in processed foods and estimation of daily nitrite intake in Korea. Food Chem. 2022, 382, 132280. [Google Scholar] [CrossRef]
  17. Fitzhenry, C.; Jowett, L.; Roche, P.; Harrington, K.; Moore, B.; Paull, B.; Murray, E. Portable analyser using two-dimensional ion chromatography with ultra-violet light-emitting diode-based absorbance detection for nitrate monitoring within both saline and freshwaters. J. Chromatogr. A 2021, 1652, 462368. [Google Scholar] [CrossRef]
  18. Liu, F.; Wang, Y.; Qian, C.; Li, J.; Jiang, X.; Shao, P.; Zu, W. Determination of Nitrite in Hams by Gas Phase Molecular Absorption Spectrometry with Ultrasonic Assisted Extraction. J. Anal. Sci. 2022, 38, 89–93. [Google Scholar]
  19. Liu, X.; Hu, T. Simultaneous Determination of Nitrite and Azide Ions in Valsartan. J. Chromatogr. Sci. 2021, 59, 758–761. [Google Scholar] [CrossRef] [PubMed]
  20. Kim, M.; Kim, S.; Yang, W.; Sim, J. Determination of nitrite and nitrate in postmortem whole blood samples of 10 sodium nitrite poisoning cases: The importance of nitrate in determining nitrite poisoning. Forensic Sci. Int. 2022, 335, 111279. [Google Scholar] [CrossRef]
  21. Zhu, K.; Kerry, M.; Serr, B.; Mintert, M. Parts per billion of nitrite in microcrystalline cellulose by ion chromatography mass spectrometry with isotope labeled internal standard. J. Pharm. Biomed. Anal. 2023, 235, 115648. [Google Scholar] [CrossRef] [PubMed]
  22. Lei, J.; Zheng, H.; Liu, L.; Li, W. Simultaneous determination of six nitroaromatic compounds and three anions in environmental matrices using a liquid chromatography-ion chromatography coupled system. Se Pu=Chin. J. Chromatogr. 2024, 42, 92–98. [Google Scholar] [CrossRef]
  23. Martinez, R.; Vela, N.; El Aatik, A.; Murray, E.; Roche, P.; Navarro, J.M. On the Use of an IoT Integrated System for Water Quality Monitoring and Management in Wastewater Treatment Plants. Water 2020, 12, 1096. [Google Scholar] [CrossRef]
  24. Yuan, L.; Zhang, J.Y.; Wu, X. The Determination of Nitrite Content in Market Sausages. In Proceedings of the 3rd International Conference on Air Pollution and Environmental Engineering, ELECTR NETWORK, Xi’an, China, 28–29 September 2020. [Google Scholar]
  25. Wang, X.; Hou, J.; Shen, X.; He, Q.; Hou, C.; Huo, D. Fluorescence-based measurements for the determination of nitrite using a coumarin derivative sensor based on inner filter effect. Anal. Methods 2020, 12, 1107–1114. [Google Scholar] [CrossRef]
  26. Salimi, M.; Nouroozi, S. Inexpensive spectrophotometric determination of nitrite with a laboratory-constructed flow cell. Instrum. Sci. Technol. 2023, 51, 132–143. [Google Scholar] [CrossRef]
  27. Pai, S.-C.; Su, Y.-T.; Lu, M.-C.; Chou, Y.; Ho, T.-Y. Determination of Nitrate in Natural Waters by Vanadium Reduction and the Griess Assay: Reassessment and Optimization. ACS EST Water 2021, 1, 1524–1532. [Google Scholar] [CrossRef]
  28. Lim, H.S.; Choi, E.; Lee, S.J.; Nam, H.S.; Lee, J.K. Improved spectrophotometric method for nitrite determination in processed foods and dietary exposure assessment for Korean children and adolescents. Food Chem. 2022, 367, 130628. [Google Scholar] [CrossRef]
  29. Thipwimonmas, Y.; Jaidam, J.; Samoson, K.; Khunseeraksa, V.; Phonchai, A.; Thiangchanya, A.; Chang, K.H.; Abdullah, A.F.L.; Limbut, W. A Simple and Rapid Spectrophotometric Method for Nitrite Detection in Small Sample Volumes. Chemosensors 2021, 9, 161. [Google Scholar] [CrossRef]
  30. Li, Z.; Wang, Y.; Zhang, J.; Fu, Z.; Shan, M.e. Spectrophotometric Determination of Nitrite Nitrogen in Environmental Water with Sulfanilamide and L-Histidine System. Environ. Monit. China 2021, 37, 186–192. [Google Scholar]
  31. El Hani, O.; Karrat, A.; Digua, K.; Amine, A. Development of a simplified spectrophotometric method for nitrite determination in water samples. Spectrochim. Acta Part A-Mol. Biomol. Spectrosc. 2022, 267, 120574. [Google Scholar] [CrossRef] [PubMed]
  32. Shichijo, M.; Okamoto, K.; Takahashi, T.; Nomura, M.; Ohira, S.-I.; Mizuguchi, H.; Tanaka, H.; Takeuchi, M. Feedback standard addition method coupled flow injection analysis-Validation by spectrophotometric determination of nitrite in seawater. Microchem. J. 2023, 190, 108721. [Google Scholar] [CrossRef]
  33. Hatta, M.; Ruzicka, J.; Measures, C.I. The performance of a new linear light path flow cell is compared with a liquid core waveguide and the linear cell is used for spectrophotometric determination of nitrite in sea water at nanomolar concentrations. Talanta 2020, 219, 121240. [Google Scholar] [CrossRef]
  34. Xu, L.; Wu, H.; Wang, X.; Chen, Q.; Ostrikov, K. A simple derivative spectrophotometric method for simultaneously detecting nitrate and nitrite in plasma treated water. Plasma Sci. Technol. 2022, 24, 085502. [Google Scholar] [CrossRef]
  35. Yardimci, B. Spectrophotometric and smartphone-based facile green chemistry approach to determine nitrite ions using green tea extract as a natural source. Sustain. Chem. Pharm. 2023, 34, 101175. [Google Scholar] [CrossRef]
  36. Nishan, U.; Rehman, S.; Ullah, R.; Bari, A.; Afridi, S.; Shah, M.; Iqbal, J.; Asad, M.; Badshah, A.; Khan, N.; et al. Fabrication of a colorimetric sensor using acetic acid-capped drug-mediated copper oxide nanoparticles for nitrite biosensing in processed food. Front. Mater. 2023, 10, 1169945. [Google Scholar] [CrossRef]
  37. Tai, Y.T.; Cheng, C.-Y.; Chen, Y.-S.; Ko, F.-H. A hydrogel-based chemosensor applied in conjunction with a Griess assay for real-time colorimetric detection of nitrite in the environment. Sens. Actuators B-Chem. 2022, 369, 132298. [Google Scholar] [CrossRef]
  38. Adegoke, O.; Zolotovskaya, S.; Abdolvand, A.; Daeid, N.N. Rapid and highly selective colorimetric detection of nitrite based on the catalytic-enhanced reaction of mimetic Au nanoparticle-CeO2 nanoparticle-graphene oxide hybrid nanozyme. Talanta 2021, 224, 121875. [Google Scholar] [CrossRef]
  39. Taweekarn, T.; Wongniramaikul, W.; Limsakul, W.; Sriprom, W.; Phawachalotorn, C.; Choodum, A. A novel colorimetric sensor based on modified mesoporous silica nanoparticles for rapid on-site detection of nitrite. Microchim. Acta 2020, 187, 643. [Google Scholar] [CrossRef]
  40. Nishan, U.; Khan, H.U.; Rahim, A.; Asad, M.; Qayum, M.; Khan, N.; Shah, M.; Muhammad, N. Non-enzymatic colorimetric sensing of nitrite in fortified meat using functionalized drug mediated manganese dioxide. Mater. Chem. Phys. 2022, 278, 125729. [Google Scholar] [CrossRef]
  41. Huang, Z.-J.; Luo, J.-Y.; Zheng, F.-Y.; Li, S.-X.; Liu, F.-J.; Lin, L.-X.; Huang, Y.-J.; Man, S.; Cao, G.-X.; Huang, X.-G. Long-term stable, high accuracy, and visual detection platform for In-field analysis of nitrite in food based on colorimetric test paper and deep convolutional neural networks. Food Chem. 2022, 373, 131593. [Google Scholar] [CrossRef]
  42. Ratnarathorn, N.; Dungchai, W. Paper-based Analytical Device (PAD) for the Determination of Borax, Salicylic Acid, Nitrite, and Nitrate by Colorimetric Methods. J. Anal. Chem. 2020, 75, 487–494. [Google Scholar] [CrossRef]
  43. Hou, C.-Y.; Fu, L.-M.; Ju, W.-J.; Wu, P.-Y. Microfluidic colorimetric system for nitrite detection in foods. Chem. Eng. J. 2020, 398, 125573. [Google Scholar] [CrossRef]
  44. Hou, J.; Wu, H.; Shen, X.; Zhang, C.; Hou, C.; He, Q.; Huo, D. Phenosafranin-Based Colorimetric-Sensing Platform for Nitrite Detection Enabled by Griess Assay. Sensors 2020, 20, 1501. [Google Scholar] [CrossRef]
  45. Zhang, J.; Yang, J.; Chen, J.; Zhu, Y.; Hu, K.; Ma, Q.; Zuo, Y. A novel propylene glycol alginate gel based colorimetric tube for rapid detection of nitrite in pickled vegetables. Food Chem. 2022, 373, 131678. [Google Scholar] [CrossRef]
  46. Jantra, J.; Arsawiset, S.; Teepoo, S.; Keeratirawee, K. Rapid colorimetric assay based on the oxidation of 2,2-azino-bis(3-ethylbenzothiazoline)-6-sulfonic acid-diammonium salt for nitrite detection in meat products. J. Environ. Sci. Health Part B-Pestic. Food Contam. Agric. Wastes 2024, 59, 72–80. [Google Scholar] [CrossRef]
  47. Nam, J.; Jung, I.-B.; Kim, B.; Lee, S.-M.; Kim, S.-E.; Lee, K.-N.; Shin, D.-S. A colorimetric hydrogel biosensor for rapid detection of nitrite ions. Sens. Actuators B-Chem. 2018, 270, 112–118. [Google Scholar] [CrossRef]
  48. Yu, M.; Zhang, H.; Liu, Y.; Zhang, Y.; Shang, M.; Wang, L.; Zhuang, Y.; Lv, X. A colorimetric and fluorescent dual-readout probe based on red emission carbon dots for nitrite detection in meat products. Food Chem. 2022, 374, 131768. [Google Scholar] [CrossRef]
  49. Hu, Y.; Shen, L.; Zhang, Y.; Lu, L.; Fu, H.; She, Y. A naphthalimide-based fluorescent probe for rapid detection of nitrite and its application in food quality monitoring. Anal. Chim. Acta 2023, 1268, 341403. [Google Scholar] [CrossRef] [PubMed]
  50. Zhang, T.; Liu, Y.; Li, J.; Ren, W.; Dou, X. High-performance fluorescent and colorimetric dual-mode nitrite sensor boosted by a versatile coumarin probe equipped with diazotization-coupling reaction-sites. Sens. Actuators B-Chem. 2023, 379, 133261. [Google Scholar] [CrossRef]
  51. Wang, M.; Zhu, H.; Liu, B.; Hu, P.; Pan, J.; Niu, X. Bifunctional Mn-Doped N-Rich Carbon Dots with Tunable Photoluminescence and Oxidase-Mimetic Activity Enabling Bimodal Ratiometric Colorimetric/Fluorometric Detection of Nitrite. Acs Appl. Mater. Interfaces 2022, 14, 44762–44771. [Google Scholar] [CrossRef] [PubMed]
  52. Murfin, L.C.; Lopez-Alled, C.M.; Sedgwick, A.C.; Wenk, J.; James, T.D.; Lewis, S.E. A simple, azulene-based colorimetric probe for the detection of nitrite in water. Front. Chem. Sci. Eng. 2020, 14, 90–96. [Google Scholar] [CrossRef]
  53. Xu, J.; Shi, Y.; Yang, S.; Yang, J.; Zhang, X.; Xu, L.; Bian, Z.; Xu, Z.; Zhu, B. Highly selective colorimetric fluorescent probe for detecting nitrite in aqueous solution. Microchem. J. 2021, 169, 106342. [Google Scholar] [CrossRef]
  54. Pan, Y.; Jiang, J.; Kan, X. Diazo-reaction based dual-mode colorimetric-electrochemical sensing of nitrite in pickled food. Analyst 2023, 148, 4869–4876. [Google Scholar] [CrossRef]
  55. Li, Y.; Zhang, Y.; Javed, R.; Li, R.; Zhao, H.; Liu, X.; Zhang, C.; Cao, H.; Ye, D. Nonmetal catalyst boosting amplification of both colorimetric and electrochemical signal for multi-mode nitrite sensing. Food Chem. 2024, 441, 138315. [Google Scholar] [CrossRef] [PubMed]
  56. Tian, L.; Huang, Z.; Lu, X.; Wang, T.; Cheng, W.; Yang, H.; Huang, T.; Li, T.; Li, Z. Plasmon-Mediated Oxidase-like Activity on Ag@ZnS Heterostructured Hollow Nanowires for Rapid Visual Detection of Nitrite. Inorg. Chem. 2023, 62, 1659–1666. [Google Scholar] [CrossRef] [PubMed]
  57. Wang, R.; Ruan, G.; Sun, Y.; Zhao, D.; Yu, H.; Zhang, C.-W.; Li, L.; Liu, J. A full-wavelength coverage colorimetric sensor depending on polymer-carbon nanodots from blue to red for visual detection of nitrite via smartphone. Dye. Pigment. 2021, 191, 109383. [Google Scholar] [CrossRef]
  58. Choodum, A.; Tiengtum, J.; Taweekarn, T.; Wongniramaikul, W. Convenient environmentally friendly on-site quantitative analysis of nitrite and nitrate in seawater based on polymeric test kits and smartphone application. Spectrochim. Acta Part A-Mol. Biomol. Spectrosc. 2020, 243, 118812. [Google Scholar] [CrossRef] [PubMed]
  59. Polat, F. Development of a Simple and Accurate Analytical Method for the Determination of Nitrite in Processed Meat Products by Using an Optical Solid Chemosensor and Smartphone. Food Anal. Methods 2022, 15, 700–706. [Google Scholar] [CrossRef]
  60. Sargazi, M.; Kaykhaii, M. Application of a smartphone-based spectrophotometer for rapid in-field determination of nitrite and chlorine in environmental water samples. Spectrochim. Acta Part A-Mol. Biomol. Spectrosc. 2020, 227, 117672. [Google Scholar] [CrossRef] [PubMed]
  61. Das, P.; Nath, P. Smartphone-based Photometric Detection of Nitrite Level in Water. In Proceedings of the IEEE Workshop on Recent Advances in Photonics (WRAP), Mumbai, India, 4–6 March 2022. [Google Scholar]
  62. Kong, Y.; Cheng, Q.; He, Y.; Ge, Y.; Zhou, J.; Song, G. A dual-modal fluorometric and colorimetric nanoprobe based on graphitic carbon nitrite quantum dots and Fe (II)-bathophenanthroline complex for detection of nitrite in sausage and water. Food Chem. 2020, 312, 126089. [Google Scholar] [CrossRef] [PubMed]
  63. Ma, Z.; Li, J.; Hu, X.; Cai, Z.; Dou, X. Ultrasensitive, Specific, and Rapid Fluorescence Turn-On Nitrite Sensor Enabled by Precisely Modulated Fluorophore Binding. Adv. Sci. 2020, 7, 2002991. [Google Scholar] [CrossRef] [PubMed]
  64. Omer, K.M.; Idrees, S.A.; Hassan, A.Q.; Jamil, L.A. Amphiphilic fluorescent carbon nanodots as a selective nanoprobe for nitrite and tetracycline both in aqueous and organic solutions. New J. Chem. 2020, 44, 5120–5126. [Google Scholar] [CrossRef]
  65. Yang, M.; Yan, Y.; Shi, H.; Liu, E.; Hu, X.; Zhang, X.; Fan, J. A novel fluorescent sensors for sensitive detection of nitrite ions. Mater. Chem. Phys. 2020, 239, 122121. [Google Scholar] [CrossRef]
  66. Li, R.; Li, L.; Wang, B.; Yu, L. Preparation of Quantum Dot-Embedded Photonic Crystal Hydrogel and Its Application as Fluorescence Sensor for the Detection of Nitrite. Nanomaterials 2021, 11, 3126. [Google Scholar] [CrossRef]
  67. Yu, K.K.; Pan, S.L.; Li, K.; Shi, L.; Liu, Y.-H.; Chen, S.Y.; Yu, X.Q. A novel near-infrared fluorescent sensor for zero background nitrite detection via the “covalent-assembly” principle. Food Chem. 2021, 341, 128254. [Google Scholar] [CrossRef] [PubMed]
  68. Wei, N.; Wei, M.X.; Huang, B.H.; Guo, X.F.; Wang, H. One-pot facile synthesis of green-emitting fluorescent silicon quantum dots for the highly selective and sensitive detection of nitrite in food samples. Dye. Pigment. 2021, 184, 108848. [Google Scholar] [CrossRef]
  69. Zhang, G.Q.; Shi, Y.H.; Wu, W.; Zhao, Y.; Xu, Z.H. A fluorescent carbon dots synthesized at room temperature for automatic determination of nitrite in Sichuan pickles. Spectrochim. Acta Part A-Mol. Biomol. Spectrosc. 2023, 286, 122025. [Google Scholar] [CrossRef] [PubMed]
  70. Song, J.; Liu, S.; Zhao, N.; Zhao, L. A new fluorescent probe based on metallic deep eutectic solvent for visual detection of nitrite and pH in food and water environment. Food Chem. 2023, 398, 133935. [Google Scholar] [CrossRef] [PubMed]
  71. Li, W.; Huang, S.; Wen, H.; Luo, Y.; Cheng, J.; Jia, Z.; Han, P.; Xue, W. Fluorescent recognition and selective detection of nitrite ions with carbon quantum dots. Anal. Bioanal. Chem. 2020, 412, 993–1002. [Google Scholar] [CrossRef] [PubMed]
  72. Yilmaz, M.D. A novel ratiometric and colorimetric probe for rapid and ultrasensitive detection of nitrite in water based on an Acenaphtho 1,2-d imidazole derivative. Anal. Chim. Acta 2021, 1166, 338597. [Google Scholar] [CrossRef] [PubMed]
  73. Deng, S.; Liu, H.; Zhang, C.; Yang, X.; Blecker, C. LMOF serve as food preservative nanosensor for sensitive detection of nitrite in meat products. LWT-Food Sci. Technol. 2022, 169, 114030. [Google Scholar] [CrossRef]
  74. Chen, L.; Fan, T.; Li, W.; Song, J.; Zhang, J.; Wang, L.; Han, K. A turn-on fluorescent nano-probe base on methanobactin-AuNPs for simple and efficient detection of nitrite. Spectrochim. Acta Part A-Mol. Biomol. Spectrosc. 2023, 286, 121960. [Google Scholar] [CrossRef] [PubMed]
  75. Cao, X.; Bai, Y.; Li, F.; Liu, F.; Yu, X. A Facile Synthesis of Tannic Acid-Protected Copper Nanoclusters and the Sensitive Fluorescence Detection of Nitrite Ion Under Mild Conditions. Spectroscopy 2021, 36, 22–27. [Google Scholar]
  76. Wang, M.; Liu, B.; Liu, J.; Zhu, H.; Bai, Q.; Hu, P.; Pan, J.; Liang, H.; Niu, X. Bifunctional manganese-doped silicon quantum dot-responsive smartphone-integrated paper sensor for visual multicolor/ multifluorescence dual-mode detection of nitrite. Sens. Actuators B-Chem. 2023, 392, 134143. [Google Scholar] [CrossRef]
  77. Yang, L.; Wang, F.; Zhao, J.; Kong, X.; Lu, K.; Yang, M.; Zhang, J.; Sun, Z.; You, J. A facile dual-function fluorescent probe for detection of phosgene and nitrite and its applications in portable chemosensor analysis and food analysis. Talanta 2021, 221, 121477. [Google Scholar] [CrossRef] [PubMed]
  78. Liang, H.; Wang, Y.; Zhang, L.; Cao, Y.; Guo, M.; Yu, Y.; Lin, B. Construction of integrated and portable fluorescence sensor and the application for visual detection in situ. Sens. Actuators B-Chem. 2022, 373, 132764. [Google Scholar] [CrossRef]
  79. Zeng, L.; Ke, Y.; Yang, X.; Lan, M.; Zhao, S.; Zhu, B. Intramolecular cascade reaction sensing platform for rapid, specific and ultrasensitive detection of nitrite. Food Chem. 2024, 438, 138044. [Google Scholar] [CrossRef]
  80. Duhan, J.; Obrai, S. Highly sensitive and selective fluorescence and smartphone-based sensor for detection of L-dopa using nitrogen sulphur graphene quantum dots. Microchem. J. 2023, 193, 109262. [Google Scholar] [CrossRef]
  81. Zhang, J.; Hu, T.; Xiong, B.; Zheng, X.; Wang, R.; Zhu, P.; Chen, J.; Cong, T.; Li, Y.; Wang, X. Fluorescent probe/hydrogel-based portable platform for ultrasensitive on-site detection of explosive particles containing nitrite. Chem. Eng. J. 2023, 475, 146311. [Google Scholar] [CrossRef]
  82. Yilmaz, M.D. A simple yet effective colorimetric assay for nitrite based on nitration of a near-infrared (NIR) absorbing dye IR780. Microchem. J. 2024, 196, 109554. [Google Scholar] [CrossRef]
  83. Wulandari, A.; Sunarti, T.C.; Fahma, F.; Noor, E.; Enomae, T. Encapsulation of purple sweet potato’s anthocyanin in CMC-PVA matrix for development of paper strips as a colorimetric biosensor. Indian J. Biochem. Biophys. 2021, 58, 292–302. [Google Scholar]
  84. Chen, L.; Song, J.; Wang, L.; Hao, X.; Zhang, H.; Li, X.; Wu, J. A simple electrochemical biosensor based on HS-β-cyclodextrin coordination methanobactin/gold nanoparticles for highly sensitive detection of nitrite. J. Solid State Electrochem. 2024, 28, 305–316. [Google Scholar] [CrossRef]
  85. Revsbech, N.P.; Nielsen, M.; Fapyane, D. Ion Selective Amperometric Biosensors for Environmental Analysis of Nitrate, Nitrite and Sulfate. Sensors 2020, 20, 4326. [Google Scholar] [CrossRef] [PubMed]
  86. Kalimuthu, P.; Kruse, T.; Bernhardt, P.V. A highly sensitive and stable electrochemical nitrate biosensor. Electrochim. Acta 2021, 386, 138480. [Google Scholar] [CrossRef]
  87. Xie, H.; Luo, G.; Niu, Y.; Weng, W.; Zhao, Y.; Ling, Z.; Ruan, C.; Li, G.; Sun, W. Synthesis and utilization of Co3O4 doped carbon nanofiber for fabrication of hemoglobin-based electrochemical sensor. Mater. Sci. Eng. C-Mater. Biol. Appl. 2020, 107, 110209. [Google Scholar] [CrossRef] [PubMed]
  88. Zhu, X.; He, M.; Xiao, L.; Liu, H.; Hu, M.; Li, S.; Zhai, Q.; Chen, Y.; Jiang, Y. Enzymatic biosensor for nitrite detection based on direct electron transfer by CPO-ILEMB/Au@MoS2/GC. J. Appl. Electrochem. 2022, 52, 979–987. [Google Scholar] [CrossRef]
  89. Monteiro, T.; Coelho, A.R.; Moreira, M.; Viana, A.S.; Almeida, M.G. Interfacing the enzyme multiheme cytochrome c nitrite reductase with pencil lead electrodes: Towards a disposable biosensor for cyanide surveillance in the environment. Biosens. Bioelectron. 2021, 191, 113438. [Google Scholar] [CrossRef]
  90. Cardoso, R.M.; Silva, P.R.L.; Lima, A.P.; Rocha, D.P.; Oliveira, T.C.; do Prado, T.M.; Fava, E.L.; Fatibello-Filho, O.; Richter, E.M.; Munoz, R.A.A. 3D-Printed graphene/polylactic acid electrode for bioanalysis: Biosensing of glucose and simultaneous determination of uric acid and nitrite in biological fluids. Sens. Actuators B-Chem. 2020, 307, 127621. [Google Scholar] [CrossRef]
  91. Wang, H.; Wang, X.; Cheng, J. Bionic Enzyme-Assisted Ion-Selective Amperometric Biosensor Based on 3D Porous Conductive Matrix for Point-of-Care Nitrite Testing. Acs Nano 2022, 16, 14849–14859. [Google Scholar] [CrossRef]
  92. Lin, Z.; Cheng, S.; Li, H.; Jin, B.; He, X. Highly selective and sensitive nitrite biocathode biosensor prepared by polarity inversion method coupled with selective removal of interfering electroactive bacteria. Biosens. Bioelectron. 2022, 214, 114507. [Google Scholar] [CrossRef]
  93. Wang, J.; Zhan, G.; Yang, X.; Zheng, D.; Li, X.; Zhang, L.; Huang, T.; Wang, X. Rapid detection of nitrite based on nitrite-oxidizing bacteria biosensor and its application in surface water monitoring. Biosens. Bioelectron. 2022, 215, 114573. [Google Scholar] [CrossRef] [PubMed]
  94. Klevinskas, A.; Kantminiene, K.; Zmuidzinaviciene, N.; Jonuskiene, I.; Griskonis, E. Microbial Fuel Cell as a Bioelectrochemical Sensor of Nitrite Ions. Processes 2021, 9, 1330. [Google Scholar] [CrossRef]
  95. Qiu, X.-Y.; Cheng, Y.-Y.; Li, Q.; Yu, Y.-Y.; Xiao, X. An in-field assembled hierarchical mesoporous electroenzymatic sensor for sensitive and real-time monitoring of nitrite. J. Clean. Prod. 2023, 426, 139102. [Google Scholar] [CrossRef]
  96. Liu, X.; Zhou, X.; Yang, C.; Yang, W.; Liu, G.; Li, Y.; Zhang, G.; Zhao, X. Surfactant-free synthesis of CuBr NPs decorated by Pt for glucose and nitrite sensors. J. Ind. Eng. Chem. 2023, 124, 323–330. [Google Scholar] [CrossRef]
  97. Koukouviti, E.; Soulis, D.; Economou, A.; Kokkinos, C. Wooden Tongue Depressor Multiplex Saliva Biosensor Fabricated via Diode Laser Engraving. Anal. Chem. 2023, 95, 6765–6768. [Google Scholar] [CrossRef] [PubMed]
  98. Tseng, W.T.; Chou, Y.Y.; Wu, J.-G.; Wang, Y.C.; Tseng, T.-N.; Pan, S.-W.; Luo, S.-C.; Ho, M.-L. An electrochemical conducting polymer-based biosensor for Leukocyte esterase and nitrite detection for diagnosing urinary tract infections: A pilot study. Microchem. J. 2023, 188, 108493. [Google Scholar] [CrossRef]
  99. de Freitas, R.C.; Orzari, L.O.; de Oliveira, P.R.; Janegitz, B.C. Pd and Ag Binary Nanoparticles Supported on Carbon Black and Tapioca for Nitrite Electrochemical Detection. J. Electrochem. Soc. 2021, 168, 117518. [Google Scholar] [CrossRef]
  100. Jiang, M.; Yin, C.; Du, J.; Fu, W.; Han, X.; Sun, W. Gold nanorods and tungsten disulfide nanocomposite modified electrode for hemoglobin electrochemical biosensing of trichloroacetic acid and nitrite. Int. J. Electrochem. Sci. 2023, 18, 100371. [Google Scholar] [CrossRef]
  101. Kaladevi, G.; Wilson, P.; Pandian, K. Simultaneous and Selective Electrochemical Detection of Sulfite and Nitrite in Water Sources Using Homogeneously Dispersed Ag Nanoparticles over PANI/rGO Nanocomposite. J. Electrochem. Soc. 2020, 167, 027514. [Google Scholar] [CrossRef]
  102. Wu, S.; Wang, H.; Zhao, B.; Cao, T.; Li, L.; Ma, J.; Liu, L.; Ruan, J.; Cao, J.; Tong, Z. Synthesis of strontium niobium-iron porphyrin nanocomposite for nitrite detection in river water. J. Nanoparticle Res. 2021, 23, 151. [Google Scholar] [CrossRef]
  103. Zhang, H.; Liu, X.; Zheng, J. A Novel Non-Enzymatic Sensor Based on Bismuth Molybdate@polydopamine-Gold Nanocomposites for Efficient Nitrite Sensing. J. Electrochem. Soc. 2021, 168, 067519. [Google Scholar] [CrossRef]
  104. Feng, X.; Han, G.; Cai, J.; Wang, X. Au@Carbon quantum Dots-MXene nanocomposite as an electrochemical sensor for sensitive detection of nitrite. J. Colloid Interface Sci. 2022, 607, 1313–1322. [Google Scholar] [CrossRef] [PubMed]
  105. Zhang, J.; Jiang, H.; Gao, J.; Zhang, L.; Zhao, C.; Suo, H. In situ fabrication of copper oxide nanoparticles decorated carbon cloth for efficient electrocatalytic detection of nitrite. Microchem. J. 2023, 194, 109302. [Google Scholar] [CrossRef]
  106. Zhang, Y.; Yang, Z.; Zou, Y.; Farooq, S.; Li, Y.; Zhang, H. Novel Ag-coated nanofibers prepared by electrospraying as a SERS platform for ultrasensitive and selective detection of nitrite in food. Food Chem. 2023, 412, 135563. [Google Scholar] [CrossRef]
  107. Liu, X.; Zhang, H.; Ma, J.; Zheng, J. High performance of nitrite electrochemical sensing based on Au-poly (thionine)-tin oxide/graphene nanosheets nanocomposites. Colloids Surf. A-Physicochem. Eng. Asp. 2022, 642, 128582. [Google Scholar] [CrossRef]
  108. Aslisen, B.; Kocak, S. Preparation of mixed-valent manganese-vanadium oxide and Au nanoparticle modified graphene oxide nanosheets electrodes for the simultaneous determination of hydrazine and nitrite. J. Electroanal. Chem. 2022, 904, 115875. [Google Scholar] [CrossRef]
  109. Lu, Z.; Wang, Y.; Hasebe, Y.; Zhang, Z. Electrochemical Sensing Platform Based on Lotus Stem-derived Porous Carbon for the Simultaneous Determination of Hydroquinone, Catechol and Nitrite. Electroanalysis 2021, 33, 956–963. [Google Scholar] [CrossRef]
  110. Wang, F.; Li, Y.; Yan, C.; Ma, Q.; Yang, X.; Peng, H.; Wang, H.; Du, J.; Zheng, B.; Guo, Y. Bismuth-Decorated Honeycomb-like Carbon Nanofibers: An Active Electrocatalyst for the Construction of a Sensitive Nitrite Sensor. Molecules 2023, 28, 3881. [Google Scholar] [CrossRef]
  111. Yang, Y.; Wei, S.; Wang, J.; Li, J.; Tang, J.; Aaron, A.A.; Cai, Q.; Wang, N.; Li, Z. Highly sensitive and ratiometric detection of nitrite in food based on upconversion-carbon dots nanosensor. Anal. Chim. Acta 2023, 1263, 341245. [Google Scholar] [CrossRef] [PubMed]
  112. Akbari, A.; Dehghan, P.; Divband, B.; Alipour, E.; Moradi, A.H. Facile Synthesis of a Novel Zr/Fe3O4/GO Nanocomposite and Its Application for Modification of Electrode Surfaces and Voltammetric Determination of Nitrite Ions. J. Anal. Chem. 2023, 78, 1070–1078. [Google Scholar] [CrossRef]
  113. Wang, S.; Yin, H.; Qu, K.; Wang, L.; Gong, J.; Zhao, S.; Wu, S. Electrodeposition of Au/Ni nanotubes with highly improved electrochemical performance for non-enzymatic nitrite detection. Int. J. Environ. Anal. Chem. 2023. [Google Scholar] [CrossRef]
  114. Zhang, M.; Yang, Y.; Guo, W. Electrochemical sensor for sensitive nitrite and sulfite detection in milk based on acid-treated Fe3O4@SiO2 nanoparticles. Food Chem. 2024, 430, 137004. [Google Scholar] [CrossRef]
  115. Li, Z.; Hu, Y.; Wang, L.; Liu, H.; Ren, T.; Wang, C.; Li, D. Selective and Accurate Detection of Nitrate in Aquaculture Water with Surface-Enhanced Raman Scattering (SERS) Using Gold Nanoparticles Decorated with beta-Cyclodextrins. Sensors 2024, 24, 1093. [Google Scholar] [CrossRef]
  116. Sudhakara, S.M.; Devendrachari, M.C.; Khan, F.; Thippeshappa, S.; Kotresh, H.M.N. Highly sensitive and selective detection of nitrite by polyaniline linked tetra amino cobalt (II) phthalocyanine surface functionalized ZnO hybrid electrocatalyst. Surf. Interfaces 2023, 36, 102565. [Google Scholar] [CrossRef]
  117. Saeb, E.; Asadpour-Zeynali, K. A novel ZIF-8@ZIF-67/Au core-shell metal organic framework nanocomposite as a highly sensitive electrochemical sensor for nitrite determination. Electrochim. Acta 2022, 417, 140278. [Google Scholar] [CrossRef]
  118. Ranjani, B.; Pandian, K.; Gopinath, S.C.B. Hemin-Modified Halloysite Nanotube as Electrocatalyst for the Enhanced Electrochemical Determination of Nitrite. J. Electrochem. Soc. 2022, 169, 057528. [Google Scholar] [CrossRef]
  119. Kumar, C.R.R.; Betageri, V.S.; Nagaraju, G.; Suma, B.P.; Kiran, M.S.; Pujar, G.H.; Letha, M.S. One-Pot Synthesis of ZnO Nanoparticles for Nitrite Sensing, Photocatalytic and Antibacterial Studies. J. Inorg. Organomet. Polym. Mater. 2020, 30, 3476–3486. [Google Scholar] [CrossRef]
  120. Azhdeh, A.; Mashhadizadeh, M.H.; Buhl, K.B. A visualization method for quickly detecting nitrite ions in breath condensate using a portable closed bipolar electrochemical sensor. Analyst 2024, 149, 1825–1836. [Google Scholar] [CrossRef]
  121. Xu, K.; Chen, Q.; Zhao, Y.; Ge, C.; Lin, S.; Liao, J. Cost-effective, wireless, and portable smartphone-based electrochemical system for on-site monitoring and spatial mapping of the nitrite contamination in water. Sens. Actuators B-Chem. 2020, 319, 128221. [Google Scholar] [CrossRef]
  122. Akhter, F.; Siddiquei, H.R.; Alahi, M.E.E.; Mukhopadhyay, S.C. An IoT-enabled portable sensing system with MWCNTs/PDMS sensor for nitrate detection in water. Measurement 2021, 178, 109424. [Google Scholar] [CrossRef]
  123. Gonzalez, P.; Perez, N.; Knochen, M. Design and construction of a low-cost, in-situ analyzer for nutrients in surface waters, based on open-source hardware and software. Microchem. J. 2022, 175, 107134. [Google Scholar] [CrossRef]
  124. Xiao, J.; Tang, J.; Chen, J.; Li, L.; Zhang, S.; Xiong, X.; Zou, Z. Rapid and selective detection of nitrite in ham sausage and water samples by a portable gas pressure meter. Sens. Actuators B-Chem. 2024, 400, 134914. [Google Scholar] [CrossRef]
  125. Li, Q.; Liu, R.; Shang, Y.; Wei, Y.; Cui, H. A stacked extreme learning machines model on detection of nitrite-nitrogen concentration in surface water with ultraviolet-visible spectroscopy. Int. J. Environ. Sci. Technol. 2024, 21, 6653–6662. [Google Scholar] [CrossRef]
  126. Cheng, C.; Jiang, L.; Li, X.; Song, H.; Fang, W. Can natural preservatives serve as a new line of protective technology against bacterial pathogens in meat and meat products? Food Qual. Saf. 2024, 8, fyad049. [Google Scholar] [CrossRef]
  127. Ma, G.; Wang, Z.; Yu, Q.; Han, L.; Chen, C.; Guo, Z. Effects of low-dose sodium nitrite on the structure of yak meat myoglobin during wet curing. Food Chem.-X 2022, 15, 100434. [Google Scholar] [CrossRef]
  128. Zhang, Y.; Zhang, Y.; Jia, J.; Peng, H.; Qian, Q.; Pan, Z.; Liu, D. Nitrite and nitrate in meat processing: Functions and alternatives. Curr. Res. Food Sci. 2023, 6, 100470. [Google Scholar] [CrossRef]
  129. Ongaratto, G.C.; Oro, G.; Kalschne, D.L.; Trindade Cursino, A.C.; Canan, C. Cochineal carmine adsorbed on layered zinc hydroxide salt applied on mortadella to improve color stability. Curr. Res. Food Sci. 2021, 4, 758–764. [Google Scholar] [CrossRef]
  130. Zhu, Y.; Yang, Q. Isolation of Antibacterial, Nitrosylmyoglobin Forming Lactic Acid Bacteria and Their Potential Use in Meat Processing. Front. Microbiol. 2020, 11, 1315. [Google Scholar] [CrossRef] [PubMed]
  131. Zhang, D.; Ge, X.; Jiao, Y.; Liu, Y. The protective effects of black tea as nitrite replacer on the oxidation, physicochemical and sensory properties of steamed beef. LWT-Food Sci. Technol. 2023, 188, 115375. [Google Scholar] [CrossRef]
  132. Nissen, L.; Casciano, F.; Di Nunzio, M.; Galaverna, G.; Bordoni, A.; Gianotti, A. Effects of the replacement of nitrates/nitrites in salami by plant extracts on colon microbiota. Food Biosci. 2023, 53, 102568. [Google Scholar] [CrossRef]
  133. Sucu, C.; Turp, G.Y. The investigation of the use of beetroot powder in Turkish fermented beef sausage (sucuk) as nitrite alternative. Meat Sci. 2018, 140, 158–166. [Google Scholar] [CrossRef] [PubMed]
  134. Liang, X.Y.; Wang, F.H.; Wang, F.H.; Wang, Y.H. Effects of partial replacement of nitrite with different fruit and vegetable powder on physicochemical and sensory aspects of fried beef meatballs. Int. Food Res. J. 2023, 30, 964–977. [Google Scholar] [CrossRef]
  135. Tan, X.; Cui, F.; Wang, D.; Lv, X.; Li, X.; Li, J. Fermented Vegetables: Health Benefits, Defects, and Current Technological Solutions. Foods 2024, 13, 38. [Google Scholar] [CrossRef] [PubMed]
  136. Udayasurian, S.R.; Li, T. Recent research progress on building C-N bonds via electrochemical NOx reduction. Nanoscale 2024, 16, 2805–2819. [Google Scholar] [CrossRef] [PubMed]
  137. Wang, W.; Li, J.; Qu, Z.; Liu, W.; Wang, A. What innovative nitrite furnishing processes can be coupled with anammox for excellent nitrogen removal? Crit. Rev. Environ. Sci. Technol. 2024, 54, 1195–1217. [Google Scholar] [CrossRef]
  138. Yu, N.-N.; Park, G. Nitric Oxide in Fungi: Production and Function. J. Fungi 2024, 10, 155. [Google Scholar] [CrossRef]
  139. Li, H.; Cui, Z.; Cui, H.; Bai, Y.; Yin, Z.; Qu, K. Hazardous substances and their removal in recirculating aquaculture systems: A review. Aquaculture 2023, 569, 73939. [Google Scholar] [CrossRef]
Figure 1. Classification and characteristics of nitrite detection methods.
Figure 1. Classification and characteristics of nitrite detection methods.
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Figure 2. Schematic diagrams of the liquid flow paths in the four stages of the HPLC-IC system. The system is connected by two six-way valves and one enrichment column. (a) Sample loading. (b) Separation of nitroaromatic compounds and anions. (c) Anion enrichment in the AG20 column. (d) Determination of nitroaromatic compounds and anions.
Figure 2. Schematic diagrams of the liquid flow paths in the four stages of the HPLC-IC system. The system is connected by two six-way valves and one enrichment column. (a) Sample loading. (b) Separation of nitroaromatic compounds and anions. (c) Anion enrichment in the AG20 column. (d) Determination of nitroaromatic compounds and anions.
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Figure 3. EcoSens Aquamonitrix smart wastewater quality monitoring system.
Figure 3. EcoSens Aquamonitrix smart wastewater quality monitoring system.
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Figure 4. (a) Illustration of IFE-based fluorescent sensor for nitrite using ADC. (b) The preparation of paper-based analytical device for the coloration development in nitrite determination. (c) Preparation of the proposed method for NO2 detection using both spectrophotometric and smartphone-based analyses.
Figure 4. (a) Illustration of IFE-based fluorescent sensor for nitrite using ADC. (b) The preparation of paper-based analytical device for the coloration development in nitrite determination. (c) Preparation of the proposed method for NO2 detection using both spectrophotometric and smartphone-based analyses.
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Figure 5. (a) Conventional Griess strategy for the detection of nitrite. (b) Improved hydrogel-based Griess detection approach. (c) The preparation of N-(1-naphthyl) ethylenediamine (1-Nap) preloaded PEG-hydrogel on a glass fiber strip and nitrite ions detection accompanied by sulfanilamide (SA). (d) Microfluidic colorimetric paper–chip device fabrication process. (e) Schematic diagram of probes based on red emitting carbon dots for the colorimetric and fluorometric detection of nitrite.
Figure 5. (a) Conventional Griess strategy for the detection of nitrite. (b) Improved hydrogel-based Griess detection approach. (c) The preparation of N-(1-naphthyl) ethylenediamine (1-Nap) preloaded PEG-hydrogel on a glass fiber strip and nitrite ions detection accompanied by sulfanilamide (SA). (d) Microfluidic colorimetric paper–chip device fabrication process. (e) Schematic diagram of probes based on red emitting carbon dots for the colorimetric and fluorometric detection of nitrite.
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Figure 6. (a) Schematic illustration of the fluorescent and visual detection of nitrite through the IFE of BPS-Fe2+ complex and g-CNQDs. (b) Fluorescence sensing measurement of nitrite by Mb-AuNPs. Schematic diagram of (c) working mechanism and (d) application of the portable sensing platform BDP-OPD for NO2.
Figure 6. (a) Schematic illustration of the fluorescent and visual detection of nitrite through the IFE of BPS-Fe2+ complex and g-CNQDs. (b) Fluorescence sensing measurement of nitrite by Mb-AuNPs. Schematic diagram of (c) working mechanism and (d) application of the portable sensing platform BDP-OPD for NO2.
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Figure 7. The schematic of a “drop & go” approach to nitrite detection. (a) Sol-gel process for mesoITO electrode fabrication. (b) Enzyme immobilization via a simple dropping process. (c) The bioreactor and electrochemical setup for nitrite monitoring in real time. (d) Illustration of LE antibody/Avidin/EDC-NHS/PEDOT-COOH/GCE electrode fabrication process and the electrochemical method for detecting NIT and LE.
Figure 7. The schematic of a “drop & go” approach to nitrite detection. (a) Sol-gel process for mesoITO electrode fabrication. (b) Enzyme immobilization via a simple dropping process. (c) The bioreactor and electrochemical setup for nitrite monitoring in real time. (d) Illustration of LE antibody/Avidin/EDC-NHS/PEDOT-COOH/GCE electrode fabrication process and the electrochemical method for detecting NIT and LE.
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Table 1. Detection information for selected test methods.
Table 1. Detection information for selected test methods.
Detection MethodsMaterial or EquipmentDetection RangeDetection LimitReferences
Spectrophotometry 3-Aph/ADC 0.1–50 μM0.0246 μM[21]
Spectrophotometry PAD 0.09–1.47 μg/mL0.053 μg/mL[27]
Spectrophotometry UV–Vis
Spectrophotometer or
smartphone
0.2–1.1 mg/L
(spectroscopic)
0.05–0.8 mg/L
(smartphone)
0.050 mg/L
(spectroscopic)
0.017 mg/L
(smartphone)
[31]
Colorimetric Acetic acid-capped CuO NPs 0.01–2.40 μM0.2 μM[32]
Colorimetric Microfluidic paper-based 1–100 ppm 1 ppm [39]
Colorimetric Hydrogel sensor 10 μM–5 mM 10 μM [43]
Colorimetric/Fluorescencer-CDs (dual-mode detection) 0.193 μM (colorimetric)
0.149 μM (fluorescence)
[44]
Fluorescence g-CNQDs/BPS-Fe2+ 2.32–34.8 μM [58]
Fluorescence Methanobactin-AuNPs 0–8.0 μM
8.0–50.0 μM
16.21 nM[70]
Fluorescence BDP-OPD 0–4.0 μM0.17 nM[75]
BiosensorsNrfA from S. oneidensis1–140 μM0.59 μM[91]
Biosensors LE antibody/Avidin/EDC-NHS/PEDOT-COOH/GCE 0.2–9.5;
10.1–89.7;
90.3–590 μM
0.2 μM[94]
Table 2. Definitions and explanations of material or equipment in Table 1.
Table 2. Definitions and explanations of material or equipment in Table 1.
NomenclatureDefinitions and Explanations
3-Aph/ADC3-aminophenylalanine/antibody coupled drug,
a form of drug formed by linking 3-aminophenylalanine to an antibody
PADPaper-based analytical device
UV–VisUltraviolet-Visible Spectroscopy
CuO NPscopper oxide nanoparticles
g-CNQDs/BPS-Fe2+graphitic carbon nitrite quantum dots/Fe (II)-bathophenanthroline complex
BDP-OPDpractical sensing platform based on 8-(o-phenylenediamine)-boron dipyrromethene
NrfAa pentahaem, C2-symmetric nitrite reductase with crystal size around 5.15 × 9.59 × 22.38 nm
S. oneidensisShewanella oneidensis, a Gram-negative bacterium
LE antibodyLeukocyte esterase antibody, which is an antibody that binds specifically to leukocyte esterase
Avidinanti-biotin protein, a protein that binds specifically to biotin
EDC-NHS1-(3-dimethylaminopropyl)-3-ethylcarbodiimide and N-hydroxysuccinimide, commonly used in biocoupling reactions
PEDOT-COOHPoly(3,4-ethylenedioxythiophene)-carboxylic acid, a conductive polymer
GCEGlassy carbon electrode, a commonly used electrode material
Table 5. Representative substitutes for nitrite and function.
Table 5. Representative substitutes for nitrite and function.
SubstanceFunction
layered matrices adsorbed with cochinealColoring agent, replacing the coloring effect of nitrites
Met-Mb (strain)Natural biological colorants and preservatives
black tea brothAntioxidant, preventing food spoilage
BP (beetroot powder)Adding color and flavor to food
Table 6. Analysis of the advantages and disadvantages of different detection methods.
Table 6. Analysis of the advantages and disadvantages of different detection methods.
Detection MethodsAdvantagesDisadvantages
Ion ChromatographyHigh sensitivity and selectivity for accurate determination of nitrite in samples. Multiple anions can be determined simultaneously, making it suitable for the analysis of complex samples. High separation efficiency and good reproducibility, making it suitable for the analysis of large quantities of samples.Instrumentation is expensive, with high operating and maintenance costs. Sample pre-treatment is complex and requires specialized operational skills. The analysis process is relatively slow and not suitable for rapid on-site testing.
SpectrophotometryEasy to operate, fast, suitable for rapid on-site testing. The relatively low cost of the equipment makes it easy to popularize and use. Qualitative and quantitative analyses can be performed and are suitable for a wide range of sample types.Relatively low sensitivity and selectivity and susceptible to interference from other pigments in the sample. Requires the use of toxic color developers, with potential risks to the environment and operators. Analytical results may be affected by experimental conditions such as temperature, pH, etc.
ColorimetricSimple and inexpensive to operate, suitable for initial screening and on-site testing. Qualitative results can be obtained quickly and are suitable for preliminary analysis of large samples.Low sensitivity and accuracy, not suitable for micro or trace analysis.
Affected by sample color and turbidity and may require complex pre-treatment steps.
Usually only suitable for specific types of samples and has limited applications.
FluorescenceHigh sensitivity and low detection limit, suitable for the detection of micro and trace nitrite.
Good selectivity reduces interference due to sample complexity. Allows real-time monitoring and imaging, suitable for analyzing dynamic processes.
Equipment is costly and requires specialized operation and maintenance. Sensitive to environmental conditions, e.g., changes in temperature, and pH may affect the fluorescence signal. Requires the use of specific fluorescent probes, which may have stability and toxicity issues.
BiosensorsRapid response allows for real-time monitoring. High sensitivity, can detect low concentrations of nitrite. Portable equipment, suitable for on-site testing and mobile laboratory use.Sensor stability and repeatability may be challenged. Periodic calibration and sensor replacement may be required. For complex samples, additional sample pre-treatment steps may be required.
Electrochemical sensorsHigh sensitivity and fast response time for rapid on-site detection. Specific electrode materials can be designed to improve selectivity and stability. Relatively low equipment cost and easy to deploy on a large scale.May be interfered with by other electroactive substances in the sample. The electrode surface may be contaminated and require periodic cleaning and maintenance. For some applications, complex electrode preparation and modification processes may be required.
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Li, H.; Song, Y.; Zhou, B.; Xu, H. Nitrite: From Application to Detection and Development. Appl. Sci. 2024, 14, 9027. https://doi.org/10.3390/app14199027

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Li H, Song Y, Zhou B, Xu H. Nitrite: From Application to Detection and Development. Applied Sciences. 2024; 14(19):9027. https://doi.org/10.3390/app14199027

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Li, Haoneng, Yang Song, Baoqing Zhou, and Hengyi Xu. 2024. "Nitrite: From Application to Detection and Development" Applied Sciences 14, no. 19: 9027. https://doi.org/10.3390/app14199027

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