**Advances in Visual Immunoassays for Sensitive Detection of Mycotoxins in Food—A Review †**

**Meijuan Liang 1,2,3,4,5 , Qi Zhang 1,2,3,4,5,\* and Peiwu Li 1,2,3,4,5,\***


**Abstract:** Mycotoxins are the toxic secondary metabolites naturally produced by fungi; their contamination in agricultural products and food severely threatens food safety and public health worldwide. The reliable, efficient, and sensitive quantification of mycotoxins in food has become increasingly challenging to tackle due to the complexity of food matrices and their low level. Visual detection has emerged as a popular trend toward miniaturization and simplification of mycotoxins assays yet is constrained with their limited sensitivity. This review mainly focuses on the various sensitive visual immunoassays for signal amplified detection of mycotoxins. These signal amplified immunoassays for the improved sensitivity of mycotoxins detection in food through nanomaterials for encapsulation enzyme, enzyme-mediated nanomaterials as the amplified signal readout, and nanozyme. Furthermore, the underlying principle and the advantages of visual immunoassays for mycotoxins have been proposed. And the challenges and perspectives have been proposed to develop improved efficient visual immunoassays for mycotoxins in food.

**Keywords:** mycotoxins; nanomaterials; catalysis; immunoassay; visualization

#### **1. Introduction**

Mycotoxins are toxic secondary metabolites secreted by fungi under suitable temperature and humidity pre- and/or post-harvest [1–3]. Mycotoxins can affect the quality and safety of agriculture products, the associated processed foodstuffs, feedstuff, and animals. Over 400 mycotoxins have recently been identified, the worldwide occurrence of mycotoxins involving aflatoxin (AF), ochratoxin (OT), zearalenone (ZEN), deoxynivalenol (DON), fumonisin (FB), and T-2 toxin [4,5]. It is well known that aflatoxin is the representative mycotoxins, including AFB1, AFB2, AFG1, and AFG2, which has been confirmed to be immunosuppressive, teratogenic, and mutagenic [6,7]. Meanwhile, AFB1 could be metabolized into the toxic hydroxyl metabolite of AFM1, which is widespread presence of milk and dairy products.

Additionally, ZEN with a strong estrogenic effect and OTA with neurotoxicity and hepatotoxicity could adversely affect animals and humans. To protect humans from exposure mycotoxins, strict standards of limiting mycotoxin levels in food and the associated products have been regulated in many countries worldwide [8]. The monitoring of mycotoxins has been recognized as a significant way to safeguard food safety. However, mycotoxins detection in food matrices is challenging due to their low levels and complex food matrices.

**Citation:** Liang, M.; Zhang, Q.; Li, P. Advances in Visual Immunoassays for Sensitive Detection of Mycotoxins in Food—A Review. *Chem. Proc.* **2021**, *5*, 25. https://doi.org/10.3390/ CSAC2021-10443

Academic Editor: Huangxian Ju

Published: 30 June 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

Accordingly, it is highly desirable to conduct the effective, reliable and sensitive analytical strategy for screening mycotoxins in food matrices.

Nowadays, many efforts have been made to detect mycotoxins in food, involving instrumental analysis [9–13] and immunoassays [14–16]. The instrumental analysis requires expensive, sophisticated instruments, a time-consuming sample preparation process, and well-trained staff, which is not suitable for rapid screening numerous samples, and precludes their wide application in resource-constrained regions [17]. Immunoassays have been extensively identified as promising specific recognition for quantifying mycotoxins thanks to their sensitivity, on-site, as well as high-throughput screening capability. The specific recognition interaction between antibody and antigen has generally favored highly selective and reliable monitoring of mycotoxins. Various signal transduction techniques have currently been utilized to conduct mycotoxins immunoassays, such as fluorescence [18–20], electrochemistry [21–24], chemiluminescence [25], and colorimetry [26–28]. Attractively, visual detection, a popular trend toward miniaturization and simplification analysis, is capable of directly observing the results by the naked eye without other sophisticated instruments [29–31].

Currently, various immunoassays involving enzyme-linked immunosorbent assay (ELISA) [32,33], lateral flow immunoassay (LFI) [34–37] have been demonstrated as an excellent platform for discrimination of mycotoxins. Among them, ELISA and LFI served as the representative visual immunoassay, have attracted continuous interest due to their advantages of simple, and on-sites for rapid screening mycotoxins. Yet, the sensitivity of these conventional visual detection methods require improvement to monitor trace amounts of mycotoxins in complex food matrices. Thus, numerous studies have currently been devoted to the construction of the visualized immunoassays for enhancing the sensitivity of mycotoxins detection via signal amplification.

Recently, the robust enzyme catalytic amplification has been confirmed to enhance the sensitivity of immunoassays. Particularly, elaborate enzymatic strategies for improving the limited enzyme amount and the catalytic activity have been engineered as efficient and sensitive immunoassays for high-performance sensing targeted analytes. The emerging nanomaterials with unique optical, electrical, magnetic, and catalytic properties provide new opportunities for improving enzymatic immunoassays [38–42]. More evidence has revealed that the integration of novel nanomaterials promoted sensitivity improvements on mycotoxins detection [43–45]. For instance, Au nanoparticles (AuNPs) functionalized with antibodies, effectively discriminating the immune complex and enzyme to catalytic reaction substrate, significantly elevated their analytical performance [46–48]. Accordingly, the combination of nanomaterials and enzymatic immunoassays provides a potent signal amplified platform for highly sensitive and specific rapidly screening of mycotoxins. Herein, we summarize the improvements on visual immunoassays of mycotoxins by integrating nanomaterials and enzymatic signal amplification. The improvements in sensitivity of mycotoxin in food were emphasized with the assistance of nanomaterials for encapsulation enzyme, enzyme-mediated nanomaterials as the amplified signal readout, and nanomaterials for enzyme-mimics. Challenges and outlook of mycotoxin detection have been proposed to develop improved and efficient visual immunoassays in food.

#### **2. The Signal Amplified Strategies**

Natural enzymes, as potent biocatalysts have been widely used in countless laboratories, medical and food safety fields thanks to their high catalytic activities, substrate specificity, good biocompatibility, and wide range of biocatalysis [49,50]. ELISA is a classical enzyme-based visual immunoassay, which mainly includes the sorbent substrate, immunorecognition and enzyme labels. The antigen or antibody serves as sorbent substrate to immobilize onto the supporting material, enzyme-labeled molecule then immobilized to sorbent [51]. The sensing principle of ELISA mainly relies on the specific immune reaction between antibodies and antigens. Generally, after precoating the antibody or antigen on the sorbent substrate through physical absorption, the antigen or antibody were captured

via specific immuno-recognition, and further immobilized on the substrate. The enzymelabeled antibody would bind to the antigens to form a bioconjugation. Significantly, the enzyme catalyzes the colorless chromogenic substrate to generate colorimetric output, and the resultant colorimetric signal is recorded by UV-vis spectrophotometer or microplate reader to quantify the analyte concentration [52,53]. The sensitivity of ELISA could be effectively enhanced by improving the absorbent substrate, the recognition element, enzyme label, or chromogenic reagent. Among them, natural enzymes represent robust signal amplification, which has been extensively utilized to develop the highly sensitive immunoassays for trace level mycotoxins because of the catalytically amplified signal.

The peroxidase activity of horseradish peroxidase (HRP) has been used in the traditional ELISA, where HRP served as signal amplification for catalysis H2O2 into hydroxyl radical (•OH) that can react with the colorless chromogenic substrate 3,3 ,5,5 tetramethylbenzidine (TMB), 2,2 -azino-bis-(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) or o-phenylenediamine (OPD) into blue TMBox, green ABTS<sup>+</sup>•, or yellow OPDox under acidic condition. The colorimetric signal intensity is associated with the anchored HRPlabeled antigen or antibody for catalysis chromogenic substrates [54]. Accordingly, the analytes can be quantified through a direct method or an enzyme-labeled secondary antibody. In the previous studies, HRP-labeled antibodies were the most commonly used in the traditional ELISA to realize the various mycotoxin detection in foods [55–59]. The aforementioned ELISA adopted enzyme-labeled secondary antibodies through chemical conjugation to generate a signal. Yet, the chemical conjugation of the enzyme might result in the loss of enzyme activity, low stability for reagents labeling, and decreased sensitivity and specificity of the ELISA [60]. More evidence was revealed that the fusion protein had been recognized as an immunological agent for mycotoxins detection since its good antigen binding and enzyme activity. A nanobody-alkaline phosphatase (ALP) fusion protein has been revealed to improve the sensitivity for FB1 and OTA detection in argo-products [61–63].

Note that the enzyme-labeled antigen or antibody revealed the limited enzyme molecules. For instance, HRP-labeled conjugate always presented the limited HRP molecules with approximately 2–3 HRP per antibody [64], which remarkably weakened the enzymatic signal amplification and the sensitivity of immunoassays. Besides the limited enzyme molecules, the low economy of the conjugated enzyme might lead to an increase the production cost of the immunoassays [65,66]. Meanwhile, enzyme-label is susceptible to decreasing or even losing catalytic activity upon practical detection [67]. Thus, the efficient strategies of augmenting enzyme amounts contribute to amplifying the sensitivity of visual immunoassay. Various enzymatic signal amplification immunoassays using nanomaterials as a robust scaffold for enzyme immobilization, enzyme-mediated nanomaterials for amplified signal readout, and nanozyme as an alternative for natural enzyme have recently been used to improve the enzyme loading and catalytic activity.

#### *2.1. Immobilized Natural Enzymes on Nanomaterials for Amplification*

Increasing the enzyme amounts in the final antigen–antibody–enzyme complex facilitates the catalysis of the substrate and signal amplification in a single recognition reaction (Figure 1A). Attractively, nanomaterials can execute as excellent carriers for loading and immobilizing enzymes by virtue of their large surface area-to-volume ratio, high loading capacity, facile fabrication, ease of functionalization, and high chemical stability. The multienzymes and antibodies immobilized on the surface of a single nanomaterial to effectively amplify the detectable signal, and thus enhance the sensitivity [68]. The emerging nanomaterials of metal/metal oxides nanoparticles, silica nanoparticles [69], carbon nanomaterials, and metal-organic frameworks have been demonstrated as excellent carriers for immobilizing natural enzymes for sensitive analysis. For instance, Zhu et al. utilized botryoid-shaped Au/Ag nanoparticles (BSNPs) loading HRP–IgG to construct indirect competitive ELISA for amplified ochratoxin A (OTA) detection in four wheat samples. After precoating the OTA-OVA antigen, the analyte of OTA was introduced as a competing component, followed by the addition of an anti-OTA antibody. Thus HRP-IgG-BSNPs complex was used

as the enzyme-labeled secondary antibody for catalysis colorless TMB into blue oxidized TMB with the assistance of H2O2. And the colorimetric intensity was recorded by a microplate reader to examine the OTA level. The high loading amount of HRP–IgG onto the BSNPs contributed to improved sensitivity of OTA with the IC50 of 0.05 ng/mL, which revealed a 30-fold improvement compared to the conventional ELISA [70].

**Figure 1.** (**A**) The improved immunoassays using nanomaterials for immobilization natural enzymes. (**B**) AuNPs-HRP-goat anti-mouse IgA enhanced ELISA for FB1. Reprinted from ref. [71]. Copyright 2018 Royal Society of Chemistry. (**C**) Zeolitic imidazolate framework-encapsulated HRP-based ELISA for ZEN. Reprinted from ref. [72]. Copyright 2021 Elsevier. (**D**) SiO2 NPs carrying poly (acrylic acid)@CAT-based ELISA for OTA. Reprinted from ref. [73]. Copyright 2016 American Chemical Society.

Similarly, Li et al. [71] developed an indirect competitive ELISA for the total FB1, FB2, and FB3 detection in maize samples based on AuNPs immobilized HRP-goat anti-mouse IgA. The enhanced sensitivity was approximately ten times compared to the conventional ELISA (Figure 1B). Liu et al. [72] developed metal-organic frameworks (MOFs)-loaded HRP and goat anti-mouse IgG for ZEN detection in argo-products. The LOD of this immunoassay achieved 0.5 ng/L for ZEN detection, which showed an approximately 126-fold enhancement relative to conventional HRP-based immunoassay (Figure 1C). Besides single nanomaterials, polymer-coated nanomaterials as enzyme containers have demonstrated to be the amplified strategies of conventional nanomaterials for further elevating the enzyme loading capacity of nanomaterials. Xiong's group presented that SiO2 NPs carrying poly (acrylic acid) (PAA) brushes as a "CAT container" were used to amplify the sensitivity of OTA in various argo-products [73]. In this case, the SiO2@PAA@CAT could generate a signal amplification for plasmonic ELISA by using catalase (CAT)-catalyzed the changed plasmonic signal readout of AuNPs. The LOD by naked eye and microplate reader was <sup>10</sup>−<sup>18</sup> and 5 × <sup>10</sup>−<sup>20</sup> g/mL, which was seven and eight orders of magnitude lower than that of CAT-based ELISA (10−<sup>11</sup> g/mL by the naked eye) and HRP-based conventional ELISA (10−<sup>11</sup> g/mL by the microplate reader) (Figure 1D).

#### *2.2. Natural Enzyme-Mediated Nanomaterials for Amplified Signal Readout*

In addition to the typical chromogenic substrate, natural enzyme-catalyzed products enable to regulate the color change of nanomaterials, especially for plasmonic property of AuNPs, achieving the visual detection of mycotoxins (Figure 2A). For instance, Xiong's group [74] developed a direct competitive ELISA through CAT-mediated AuNPs aggregation using HRP + H2O2 + tyramine system. In this case, phenol polymerization of tyramine by •OH from HRP-catalyzed H2O2 triggered AuNPs aggregation. The competitive antigen of OTA-labeled CAT was employed to catalyze H2O2 into H2O and O2. AuNPs presented monodisperse (red) without OTA, while the AuNPs aggregation (blue) was observed with OTA, and the extinction spectra of AuNPs were used as the signal recorder. The combined advantages of ultrahigh CAT catalytic activity and color change of AuNPs contributed to sensitively detecting OTA in corn samples. The IC50 and LOD (IC10) of OTA were 84.75 and 17.8 pg/mL, which revealed a 2.9- and 2.7-fold enhancement compared with the conventional ELISA (Figure 2B).

Meanwhile, this group also utilized the glucose oxidase (GOx) -catalyzed glucose into H2O2, which reduces Au3+ into Au<sup>0</sup> on the surface of Au seeds with an obvious color change for a direct competitive ELISA for FB1 detection in maize samples. The IC50 was 1.86 ng/mL, approximately 13-fold lower than that of HRP-based conventional ELISA [75]. Apart from AuNPs, enzyme-assisted etching of Au nanorods (NRs) triggered visual detection of mycotoxins. HRP-assisted AuNRs-etching direct competitive ELISA was developed to sensitively detect AFB1 in corn samples. The competitive antigen of AFB1-labeled GOx could catalyze glucose molecules into H2O2, and HRP simultaneously catalyze H2O2 to form •OH. The rod-like morphology AuNRs was chemically etched to spherical morphology by •OH, leading to visual signal output. The etching process of AuNRs efficiently occurred without AFB1, yet the blocking of AuNRs etching was clearly presented in the presence of AFB1. The decreased optical density and the apparent color change from bluish-green to red were collected by a microplate reader or the naked eye for qualitative AFB1 detection. The method allowed sensitive determination of AFB1 with IC50 of 22.3 pg/mL, which enhanced 32 times compared to the traditional ELISA [76].

Although these approaches achieved superior sensitivity, most of them rely on traditional single-signal readout mode. And these strategies might encounter the limitation of inaccuracy for mycotoxins evaluation, which was partly ascribed to external interferences, such as nonstandard test processes, different operators, or diverse surrounding environments [77–79]. Recent development in mycotoxins immunoassays enable the integration of visual and various signal transduction techniques into dual-signal strategies, and thus offering multi models for mycotoxins detection because of their self-calibration. Typically, by using the changed multiple color and LSPR shifts of Au nanobipyramids etched by •OH generated from HRP-catalyzed H2O2, and the changed photocurrent of CdS etched by the oxidized HRP. Wei et al. [80] developed an improved colorimetric and photoelectrometric immunoassay for ochratoxins (Figure 2C). The nanoliposomes as the vehicle for carrying more secondary antibodies and encapsulating HRP significantly amplified the detection signal, realizing the simultaneous detection of three ochratoxins (OTA, OTB, and OTC). The dual-modality immunoassay showed high sensitivity with LOD of 0.7 and 1.7 ng/L for photoelectrometric and colorimetric readouts, respectively. Attractively, the dual-modality response immunoassays showed a more accurate and reliable outcome compared with the single modality.

**Figure 2.** (**A**) The enzymes-catalyzed products-mediated nanomaterials for signal readout. (**B**) CATmediated AuNPs aggregation-based ELISA for OTA. Reprinted from ref [74]. Copyright 2018 Elsevier.(**C**) HRP-mediated Au nanobipyramids etching process-based immunoassay for ochratoxins. Reprinted from ref. [80]. Copyright 2019 American Chemical Society.

#### *2.3. Nanozyme for Signal Amplification*

Although natural enzymes are extensively used in various fields, their catalytic activities were still susceptible to the extreme environment, e.g., heat, pH, organic solvents, mechanical stress, heavy metal, etc. Meanwhile, they present many shortcomings, such as high expense, low recyclability, poor operational stability and limited practical applications, e.g., the preparation, reaction, and storage requirements [81–83]. Nanomaterials-based artificial enzymes (nanozyme) have been particularly attractive since the discovery of Fe3O4 NPs with peroxidase-like activity by Yan's group in 2007 [84]. Nanozymes are ideal candidates for alternative natural enzymes due to their high catalytic activity, tunable catalytic activity and types, multienzyme mimetic activity, high stability, low cost, durability and ease of functionalization [62]. Nowadays, various nanozymes have been served as catalytic labels for multi-category signal amplification in newly developed immunoassays. Numerous studies revealed that metal NPs (Au, Ag, Pt, Pd) [85,86], metal oxide NPs (Fe3O4, CeO2, MnO2, CuO) [87–92], carbon-based (graphene oxide, carbon nitride, carbon dots) [93–96], and MOFs-based nanomaterials [97–99] with peroxidase-, catalase-, oxidase-, superoxide dismutase-mimicking properties.

These nanozymes have been designed to amplify the sensing of mycotoxins (Figure 3A). For example, Xu et al. [100] developed an indirect competitive MOFs -linked immunosorbent assay for the high throughput and sensitive detection of AFB1 in grain drinks. Peroxidase-like activity of MOFs (MIL-88) was conjugated to a secondary antibody to substitute natural HRP-labeled secondary antibody. The MOFs-based immunoassay allowed to sensitively detect AFB1 with the LOD of 0.009 ng/L with 20 times improvement compared to the conventional ELISA. The enhanced sensitivity might arise from their good dispersity, more active sites, and pores of MOFs-labeled antibodies promoted the catalytic reaction between MOFs-labeled antibody nanozyme and substrate. Significantly, the immunoassay could successfully decrease the occurrence of false positives and false negatives during the detection of AFB1 (Figure 3B).

Furthermore, Zhu et al. [101] developed a competitive ELISA that was constructed to sensitively monitor OTA in millet samples through octahedral Cu2O nanoparticles etching of Au nanobipyramids. Peroxidase-mimicking activity of Cu2O could oxidize TMB in the presence of H2O2, and the yellow product TMB2+ could etch the Au nanobipyramids, triggering a significant longitudinal peak blue shift of local surface plasmon resonance. In this case, a dopamine-coated microplate was used to capture OTA antigens, and followed by the immunoreaction between OTA antibodies and the Cu2O-labled secondary antibody. The growing concentration of OTA resulted in a decrease of Cu2O-labled secondary antibody amount, further imposing adverse effects on the generation of catalytic product TMB2+ and the etching process of AuNRs (Figure 3C). The method allowed to sensitively detect OTA with LOD of 0.47 ng/L.

Apart from the single nanozyme for signal amplification, multienzyme-based cascade catalysis is another important signal transduction and amplification strategy. In the catalytic cascade system, the decreased diffusion path of intermediates between the enzymes enables the improvement of unstable intermediates, facilitating their efficiency and specificity [102–104]. Meanwhile, the single substrate can be converted into more signal molecule through the multienzyme-associated continuous catalysis reaction and contributes to the signal amplification [68,83,105]. Lai et al. [105] proposed a competitive cascade amplified immunoassay for AFB1 detection in peanut samples by a combination of ascorbate oxidase (AOx)/anti-AFB1 antibody-labeled AuNPs and oxidase-mimics MnO2 (Figure 3D). With the assistance of ascorbic acid (AA), a blue MnO2-TMB system was converted into a colorless system because of the dissolution of MnO2 into Mn2+. Once introduced AOx, the color change could be suppressed since AOx catalysis AA to dehydroascorbic acid. The cascade signal amplification remarkably improved the sensitivity of AFB1 with LOD of 6.5 pg/mL, which approximately enhanced 15-, 7-, and 38-fold compared to the existing commercialized AFB1 kits (e.g., QuickingBiotech:100 ppt; Max Signals: 50 pg/mL; MyBioSource: 250 pg/mL). Similarly, Lai further developed a competitive immunoassay for sensitive screening AFB1 in a peanut sample (LOD: 0.1 ng/mL), based on the just-in-time generation of an oxidase, mimics MnO2 through the reaction KMnO4 and Mn2+ with the assistance of AOx [106].

Similar to ELISA, LFI is another important visual immunoassay for nanomaterialslabeled one-step immunochromatographic paper-based point-of-care tests. LFI is widely used in food safety owing to its low cost, speed, and ease of use [107–109]. The components of LFI mainly include a sample pad, a nitrocellulose (NC) membrane containing the test and control zones, conjugate and absorbent pads from cellulose, and a polyvinyl chloride backing card for assembling the components [110]. Once the sample solution is dropped onto the sample pad, it can migrate along the strips driven by capillary forces. Then, the sample dissolves the detection reagent in the conjugation pad, followed by flows along the strip within the porous membrane, where the analyte and the signal reporter were captured on the test line, thereby leading to the generation of a detectable signal. The sensing principle of LFI for analytes mainly includes the competitive and sandwich types. Generally, the competitive LFI is utilized to analyze mycotoxins due to their low-molecular weight. For the competitive LFI, the analyte competes with the same molecule, or the analyte blocks the capture agent attached on reporter tags in conjugation [111,112]. The resultant detectable signal intensity of the test line decreased upon the growing concentration of mycotoxins.

**Figure 3.** (**A**) Nanozyme-based immunoassays. (**B**) MOFs-linked immunosorbent assay for AFB1 detection. Reprinted from ref. [100]. Copyright 2021 Elsevier.(**C**) Peroxidase-like activity of Cu2Obased immunoassay for OTA detection. Reprinted from ref. [101]. Copyright 2021 Springer Nature. (**D**) MnO2-AOx cascade amplified immunoassay for AFB1 detection. Reprinted from ref. [105]. Copyright 2017, Elsevier.

For colorimetric LFI, AuNPs are the common signal labeled material for visual output through non-covalent electrostatic adsorption of antibodies or antigens [113]. Aunanomaterials-based LFI have been extensively developed for analysis multiplex mycotoxins including FB1 [114], AFB1 [115], OTA [116], ZEN [117] etc. In addition, natural enzymes also provide signals through conjugating to mycotoxin-protein and are executed as the signal transducer to achieve visual detection, such as HRP-labeled antibodies or /antigen for immunological recognition construction LFI [118,119]. Nowadays, numerous nanozymes have been used to label antibodies or antigens for rapid visual LFI. The evidence of Fe3O4 nanozyme for enhanced detection Ebola virus with 100 times enhancement compared to the conventional AuNPs-based LFI, revealing the signal amplification ability of nanozyme [120]. Various fascinating nanozyme, such as AuPt nanoflowers [121], Pt nanocatalyst [122], Pt-Ni(OH)2 nanosheets [123], Prussian blue NPs (PBNPs) [124], have been used to construct LFI, and realized their widely application in food safety. For example, Tian et al. developed PBNPs as a marker signal LFI platform for OTA in soybeans samples. The new signal of PBNPs can be amplified via the TMB cascaded signal. The colorimetric signal of PBNPs accumulated on the test line through specific immune interactions, triggering the formation of a visible blue line. Meanwhile, the colorimetric signal could be further amplified via the peroxidase-mimic property of PBNPs. The resultant colorimetric images and grey intensity for OTA concentration were collected and analyzed by a smartphone and software Image J, respectively. This proposed LFI significantly improved the sensitivity of OTA with 2–3 orders of magnitude relative to commercial AuNPs-based LFI [125]. Although nanozyme have been extensively applied in food analysis, their poor substrate specificity, unclear mechanism, lack of standards and reference materials, and potential toxicity remained the major challenges for their further application.

#### **3. Conclusions and Outlook**

Mycotoxin contamination is a continuous global concern for food safety. Visual immunoassays remain simple, rapid, on-site detection of mycotoxins contamination as an alternative to traditional sophisticated techniques. The combination between conventional visual immunoassays and nanomaterials, novel visual immunoassays tend to be popular for mycotoxins by using the signal amplified strategies for tackling their inherent limited sensitivity. The representative immunoassays based on various nanomaterials could achieve the enhanced sensitive detection of mycotoxins using signal amplified strategies. Enzyme-immobilized onto nanomaterials, enzyme-mediated nanomaterials for amplified signal readout, nanozyme for amplifying the sensitivity of mycotoxins detection.

Although the aforementioned sensitive visual immunoassays for mycotoxins have revealed outstanding analytical performance and a fascinating prospect, many challenges still need to be tackled.

(1) The visual signal is obtained by the naked eye. Yet, the reliance on manual observation rather than instrumental measurement might cause large subjective uncertainty, as well as difficulty in quantitative data. The integration of digital technology [126] (e.g., machine vision) to simulate human visual ability and objective perception, the accurate and reliable results could be easily quantified, and thus reducing subjective errors in manual observations.

(2) Compared to the traditional immunoassays, the limited reproducibility and stability of nanomaterials-based immunoassays is the important obstacle for further application in food analysis due to their experimental and systemic factors. The standardization of nanomaterials preparation could effectively guarantee the reproducibility and stability of nanomaterials-based immunoassays.

(3) Most visual immunoassays are developed for single mycotoxin, while mycotoxins always co-occurred with the others in actual food samples. Thus, the simultaneous monitoring multi-mycotoxins by combing the multi-recognition elements in immunoassays facilitate to shorten the required time, save costs and alleviate the required labor.

(4) The integration of the visual analysis technology and multi-analysis technologies (e.g., magnetic, optical, and thermal properties, etc.), multi-signal immunoassays of mycotoxins contribute to minimum background signal and false-positive errors.

(5) Further exploiting the smart, automatic, miniaturized detector with the integration of smartphone, a portable and high-resolution device for the highly sensitive screening of mycotoxin contamination.

**Author Contributions:** M.L.: conceptualization, writing the original draft, and writing–review & editing. Q.Z.: conceptualization, project administration, and funding acquisition. P.L.: funding acquisition, project administration, and supervision. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by the National Key R&D Program of China (2018YFC1602500), the Key Project of National Science Foundation of China (32030085), Agricultural Science and Technology Innovation Program of CAAS (CAAS-ZDRW202011), Natural Science Foundation of Hubei Province (2021CFB181).

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


### *Proceeding Paper* **Reproductivity Study of Metal Oxide Gas Sensors Using Two Different Temperature Setups †**

**Giulia Zambotti 1,2,\* and Andrea Ponzoni 1,2**


**Abstract:** The use of the electronic nose as a screening device is of great interest in various types of applications, including food quality control and environmental monitoring. It is an easy-to-use device and produces a much faster response than that obtained by classical chemical and microbiological techniques. The reproductivity of nominally identical electronic noses and sensors is critical. Four identical MOX sensors were compared using two different working methods, namely, the temperature modulation mode and isothermal mode. Each sensor was tested with two standard compounds, water and lactic acid, often identified in food matrices, which are potential applications of the electronic nose.

**Keywords:** sensor reproductivity; modulation of temperature; isothermal mode; electronic nose; MOX sensors

**Citation:** Zambotti, G.; Ponzoni, A. Reproductivity Study of Metal Oxide Gas Sensors Using Two Different Temperature Setups. *Chem. Proc.* **2021**, *5*, 26. https://doi.org/10.3390/ CSAC2021-10613

Academic Editor: Nicole Jaffrezic-Renault

Published: 6 July 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

#### **1. Introduction**

Sensor reproductivity is an important issue to ensure the reliability of the final instrument, such as electronic noses, in which individual sensors are implemented [1]. The core of the electronic nose is made of an MOX sensor array [2], which may work in isothermal and/or temperature modulation mode. These two different types of working modes can affect the sensitivity of the sensor in respect to the gases.

For temperature modulation, a periodic signal is applied to the heater to periodically change the sensor temperature in order to activate and inactivate the oxidation–reduction reactions between the sensitive material and gases [3,4]. As a consequence, the sensor resistance changes periodically with time, and parameters describing this curve can be extrapolated and used as input (features) to the pattern recognition algorithm. These parameters play the same roles as those attributed to the responses of individual sensors that work at a constant temperature, i.e., a fixed voltage applied to the heater [5].

Electronic noses have been used for different types of applications, for example, in the environmental field [6], medicine [7], security and safety [8], and food control [9,10].

For commercial applications (medical, food, environmental), three different aspects are important to develop an effective electronic nose: the system must guarantee good performance in order to achieve sensitivity and specificity; the database and the pattern recognition software should work on different nominally identical electronic noses with minimal adaptation work; and sensors should be interchangeable with nominally identical ones in case of failure. For these reasons, in this work, the reproductivity of nominally identical sensors was tested comparing the features extrapolated with sensors working in the two modes: isothermal and temperature modulation.

#### **2. Material and Methods**

In this work, we used a JLM MOX STICK (JLMInnovation Gmbh) device (Figure 1) to perform experiments. This instrument includes sensor control software and the electronic part. The experiments were conducted using 4 commercial sensors (TGS 2620—Figaro Sensor) exposed to vapors from a pure solution of water and lactic acid.

**Figure 1.** JLM MOX STICK device (JLMInnovation Gmbh) equipped with a commercial (Figaro TGS2620) sensor.

For the constant temperature mode, each sensor was tested with a constant voltage of 3.5 applied to the heater. For temperature modulation, the first part of the period lasted 10 s (4 volts) and the second part of the period lasted 10 s (3 volts). We chose these voltage and time values to have the same average temperature for both modes during a single thermal period.

Each sensor was turned on and exposed to ambient air (environmental temperature 21 ◦C) for one hour in order to stabilize it before performing the planned series of measurements.

Two vials were prepared using 10 mL of water and 10 mL of lactic acid. Both were sealed with parafilm and left in the room for one hour to create the headspace. A hole was then created in the parafilm, and the sensor was inserted. Measurement times were as follows: 10 min in contact with the compound vapors and 10 min in air to allow for baseline recovery. Each substance was replicated 3 times.

The following features were used for the elaboration on the temperature modulation dataset and to describe the resistance versus time curve. Using this method of measurement, it is possible to extrapolate several features to be used to analyze the data, unlike the isothermal method that allows the processing of a single parameter, R/R0. The value of R/R0 was calculated using the minimum resistance value reached by the gas in contact with the sensor (R), divided by the starting value of the sensor in air (R0). For the temperature modulation method, 2 significant features were extrapolated:


All of this information is shown in Figure 2.

(**a**) (**b**)

**Figure 2.** (**a**) The light blue line represents the modulation of the heater voltage between 3 and 4 volts. The red curve is an example of sensor resistance measured during exposure to water vapors. DeltaR-C = R1 − R2; Ratio-CH = R2/R3. (**b**) The isothermal example shows the voltage applied to the heater with a light blue line, while the red curve shows an example of sensor resistance measured during exposure to water vapors (response calculated as R/R0).

#### **3. Results and Discussion**

Based on our previous experience of food quality control applications [9], we chose the most significant features (Ratio-CH and R/R0) to compare the results obtained from each individual sensor. The statistics of the recorded responses are shown in Figure 3.

**Figure 3.** (**a**) Comparison between Ratio-CH (green color) and R/R0 (yellow color) response to water vapors. (**b**) Response obtained to lactic acid vapors. Light blue rectangles relate to Ratio-CH, while red rectangles concern R/R0.

The value of each single response is the average of the single values obtained during the measurement session (replicated three times). The graphs also show the standard deviation corresponding to each result.

The first thing to note is that for both compounds analyzed and for both methods used, the sensors return a reproducible response. Evaluating, in detail, the response obtained by each method, we can see that the standard deviation (absolute value) for temperature modulation is always lower than that obtained using the isothermal method. This is further

enhanced by normalizing the standard deviation to the average of the response intensity. Indeed, concerning water, the value changes from 0.5% to 2.6% for Ratio-CH, while for R/R0, it changes from 2.25% to 4.65%. It is possible to note the same situation in the measure of lactic acid (Ratio-CH 0.5–3.9%, R/R0 3.80–10.74%).

During the experience gained using the temperature modulation method, we realized that one of the features that introduce a large amount of information in the construction of the PCA (principal component analysis) plot is DeltaR-C, and therefore we decided to analyze it [7–9].

As can be seen in Figure 4, the reproductivity of the sensors towards the analyzed compounds is relatively poor in respect to what was observed concerning the Ratio-CH feature. There is an appreciable variance from sensor to sensor and within individual measurements. We find a standard deviation that ranges from 5.3% to 63% (water) and from 2.5% to 27.6% (lactic acid). However, in any case, it is able to return the most important information combined with other extracted features [7–9]. This means that the reproductivity of sensors depends on the given feature analyzed.

**Figure 4.** Sensor responses measured during exposure to water and lactic acid vapors.

#### **4. Conclusions**

In conclusion, two features were extrapolated and analyzed during experiments carried out using temperature modulation. Both these features were revealed to be useful during our old experiments dedicated to the detection of fish shelf life. The reproductivity of nominally identical sensors showed feature dependence, i.e., the feature Ratio-CH is better than the feature DeltaR-C. For a constant temperature, the normalized feature may be more or less repeatable than that extrapolated from the other mode depending on individual features, though the response extrapolated from this working mode benefits from the normalization to the reference air, while this does not occur for the temperature modulation mode.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/article/10 .3390/CSAC2021-10613/s1.

**Author Contributions:** Conceptualization, G.Z. and A.P.; methodology, G.Z. and A.P.; resources, G.Z. and A.P.; data curation, G.Z. and A.P.; writing—original draft preparation, G.Z. and A.P.; writing review and editing, G.Z. and A.P. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by Lombardia region and Fondazione Cariplo through the project EMPATIA@LECCO.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The main data have been reported in figures (mean and std). Additional data are available from the corresponding author upon reasonable request.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


### *Proceeding Paper* **First Principles Investigation of the Optoelectronic Properties of Molybdenum Dinitride for Optical Sensing Applications †**

**Amall A. Ramanathan**

Department of Physics, The University of Jordan, Amman 11942, Jordan; amallahmad@gmail.com † Presented at the 1st International Electronic Conference on Chemical Sensors and Analytical Chemistry, 1–15 July 2021; Available online: https://csac2021.sciforum.net/.

**Abstract:** The electronic and optical properties of the newly synthesized molybdenum dinitride (MoN2) in the hypothetical 2H structure analogous to MoS2 is investigated using the density functional theory (DFT) full potential linearized augmented plane wave (FP-LAPW) method and the modified Becke–Johnson (mBJ) approximation. The aim is to investigate the optoelectronic properties of this compound for potential optical sensing applications and compare with the capabilities of MoS2 in this field. As compared to MoS2, which is a semiconductor, MoN2 is found to be a semi metal from the band structure plots. The dielectric function, optical conductivity and the optical constants, namely, the refractive index, the reflectivity, the extinction and absorption coefficients, are evaluated and compared with those of MoS2 and discussed with reference to the sensing performance.

**Keywords:** layered materials; electronic structure; dielectric function; optical conductivity; optical constants; optical sensing

**Citation:** Ramanathan, A.A. First Principles Investigation of the Optoelectronic Properties of Molybdenum Dinitride for Optical Sensing Applications. *Chem. Proc.* **2021**, *5*, 27. https://doi.org/10.3390/ CSAC2021-10429

Academic Editor: Elena Benito-Peña

Published: 30 June 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

#### **1. Introduction**

The high potential of transition metal dichalcogenides (TMD) for electronic, sensing, photonic and thermoelectric device applications has been exploited this past decade, and especially MoS2, a prototype TMD material, has shown a lot of promise [1–3]. It has been studied and characterized extensively for structural, electronic, optical and transport properties both in bulk and in the 2D limit [4–6]. Interest in TM nitrides has been rekindled because they exhibit a number of unique and advanced catalytic properties for photo and electrochemical catalysis [7,8]. There were no layered structures in any of these studies. Layered structures provide more flexibility in doping, the ease of going down to lower dimensions and materials design.

The search for layered nitrogen rich TM nitrides, particularly those of the MoS2 type, led to the recent synthesis and discovery of 3R-MoN2, which has the rhombohedral MoS2 structure [9]. It was synthesized through a high P-T route of solid-state ion exchange and has shown great potential for applications in catalysis and hydrogenation. In addition, the very recent first principle study of MoN2 monolayer by Zhang et al. [10] showed the 1H configuration to be the most stable among the structures considered in their study. Their study revealed the importance of 2D MoN2 as a high-capacity electrode material for metal ion batteries. Further, the first principles study of Ramanathan and Khalifeh [11] has shown the 2H MoN2 to be a promising thermoelectric material.

All the above interesting results for MoN2 provide a strong motivation to study this compound. Considering that to date no optical characterization of MoN2 has been performed, the present study is devoted to the determination of the electronic and optical properties from first principles and to look at the various possibilities for optical sensing applications of MoN2. Since an optical sensor measures a physical property of light and, depending upon the sensor usage, converts it to a readable output, it is highly essential to characterize the optical properties of the new layered material MoN2. The hypothetical

2H structure analogous to MoS2 of MoN2 is investigated using the DFT full potential linearized augmented plane wave (FP-LAPW) method and the mBJ approximation. In addition, the 2H MoS2 optoelectronic properties are determined by the same method for the sake of completeness and comparison.

#### **2. Calculation Details**

The geometry of MoN2 is optimized using the ABINIT software program [12,13] with the generalized gradient approximation (GGA) of Perdew, Burke and Ernzerhof (PBE) PAW (projector augmented wave) pseudopotentials [14]. All the structural calculations are performed with convergence criteria of less than 1 × <sup>10</sup>−<sup>6</sup> Ha for the self-consistent field (SCF) iterations and a threshold of less than 1 mRy/a.u. for the optimization of the geometries [15,16]. The fully relaxed MoS2 lattice constant values are taken from our previous work [6].

The optimized structures and lattice constant values are then used with the WIEN2k [17] code to perform full-potential linearized-augmented plane wave (FP-LAPW) calculation employing GGA\_PBE to obtain the ground state energy and electronic properties at a 20 × 20 × 4 k-point grid. The optical properties are evaluated using denser grids of 40 × 40 × 5 with the more accurate mBJ exchange correlation of Trans Blaha (TB-mBJ) [18].

#### **3. Results and Discussion**

#### *3.1. Structural and Electronic*

The 2H-MoN2/MoS2 unit cells have hexagonal symmetry and consist of two stacks of three atomic layers; each stack consists of a Mo atomic plane sandwiched between two N/S atomic planes respectively. The atoms are bonded covalently in plane and the stacks are held together by weak Van der Waals force.

The non-magnetic state is the ground state for both the layered compounds and the structural relaxation of the system with a complete relaxation of all the atoms which simultaneously gives us the equilibrium geometry. The lattice parameter a and c values of MoN2 are 3.094 and 11.975 Å, respectively. The lattice parameter values of MoN2 are much smaller than that of MoS2 due to the shorter bond lengths of Mo–N as compared to Mo–S. The lattice parameters for MoS2 a = 3.193 and c = 12.359 Å taken from previous work [6] using the LDA (local density approximation) are in good agreement with the experimental values [19] aexp = 3.16 Å and cexp = 12.29 Å and within 2.3 and 0.6%, respectively.

The equilibrium lattice constant values for MoN2 and MoS2 are used with the GGA-PBE WIEN2k code to extract the electronic band structures with a 20 × 20 × 4 k-point grid.

We notice that there is a change in the electronic distribution of MoN2 as compared to MoS2 which is reflected in the band structure of MoN2, as shown in Figure 1. The MoS2 band structure is also shown on the right panel of Figure 1. The band structures illustrate the change in behavior of MoN2 to a semi metal one from the semiconducting one of MoS2. There is an overlap between the bottom of the conduction band and the top of the valence band in MoN2. This semi-metal feature implies that there is a range of energies for which electrons and holes co-exist. The Mo 4d, S 3p and N 2p atomic orbitals play a decisive role in the band structure properties as shown by the total and partial density of states plots Figures S1 and S2 (a and b).

**Figure 1.** The band structures of (**a**) MoN2 and (**b**) MoS2.

#### *3.2. Optical Properties*

The TB-mBJ proves to be an excellent choice with a 40 × 40 × 5 grid for calculating the optical properties with a high degree of accuracy for MoN2 and MoS2. This section is devoted to the presentation and discussion of the results for the dielectric function and optical conductivity. In addition, the optical constants, namely, the refractive index, the reflectivity, the extinction and absorption coefficients, are obtained and interpreted.

The complex dielectric function (ε = ε<sup>1</sup> + iε2) is a function of the amount of light absorbed by the material. The imaginary part of dielectric function, ε<sup>2</sup> (ω), which represents absorption behavior, can be calculated from the electronic band structure of solids. The real part of dielectric function, ε<sup>1</sup> (ω), which represents the electronic polarization under incident light can be calculated according to Kramers–Kroing relation [20,21]. Figure 2 shows the real and imaginary plots for the dielectric function for MoN2 and MoS2 in the photon energy range of 0–14 eV. We see from the plots the anisotropy of the dielectric function. The general trend is the in-plane values are almost double that of the out-of-plane direction and the peaks for the zz direction are shifted more towards the right, towards higher photon energies. The dielectric plots show the high capability for absorption in the visible part of the spectrum for the in-plane direction and ultra-violet (UV) for the perpendicular direction, thereby effectively covering a wide range of energies.

**Figure 2.** The dielectric function left panel MoN2 and right panel MoS2; (**a**) the real ε<sup>1</sup> (ω) and (**b**) imaginary part ε<sup>2</sup> (ω) for the in-plane (xx) and out of plane (zz) directions.

The complex index of refraction of the medium *<sup>N</sup>* is defined as *<sup>N</sup>* <sup>=</sup> <sup>√</sup>*<sup>ε</sup>* <sup>=</sup> *<sup>n</sup>* <sup>+</sup> *ik*, where *n* is the refractive index and *k* the extinction coefficient. These are depicted in Figure 3.

**Figure 3.** The refractive index top panel and extinction coefficient bottom panel for MoN2 (**a**) and MoS2 (**b**) in the xx in-plane and zz out of plane directions.

Once again, we see the anisotropy in the two directions for these optical constants. The amplitudes in the xx direction are larger and closer to the visible range for both the *n* (ω) and *k* (ω) compounds. We notice that MoN2 has large static (ω = 0) refractive index values of ~11 and 4 in the xx and zz directions, respectively. In contrast the corresponding values for MoS2 are 4 and 3. The larger values of *n* (ω) imply higher electron density. In contrast to MoS2, MoN2 has peak extinction coefficient values at ω = 0 of 4.4 and 0.9 in the xx and zz directions, respectively. Both MoN2 and MoS2 show low *k* (ω) values in the infrared and MoS2 continues to have almost zero values up to 1.5 and 2.5 eV for the xx and zz directions, respectively. The first maxims of MoS2 are at 3 eV of the spectra and the magnitude in the xx direction is almost six times larger than in the zz direction. The second k peak for the zz direction is in the UV region and slightly larger than the first xx peak. Since the extinction coefficient reflects the degree to which light is absorbed, we can see that the in-plane direction is most favorable for both compounds. However, in contrast to MoS2, with MoN2 we have strong absorption in infrared in addition to the visible region of the photon energy.

The conductivity and absorption coefficient graphs for MoN2 and MoS2 are shown in Figure 4. The graphs show for the xx in-plane direction maximum conductivity is in the UV region for MoN2 whereas for MoS2 it is in the visible part of the photon energy. The conductivity in the zz direction has peak positions in the UV region around 8 and 5 eV for MoN2 and MoS2, respectively.

**Figure 4.** The optical conductivity top panel and absorption coefficient bottom panel for MoN2 (**a**) and MoS2 (**b**) in the xx in-plane and zz out of plane directions.

The absorption on the other hand shows the first peak in the visible and second broader peak with a much higher magnitude in the UV region for MoN2; and a very broad peak of almost constant magnitude for MoS2, covering the visible and the UV region in the in-plane xx direction. Beyond 10 eV, both MoN2 and MoS2 show a rise in the absorption coefficient. With respect to the zz direction, there are a set of small peaks beyond the visible and a sharp maximum value peak at around 9 eV of the UV region for MoN2; whereas for MoS2, the peaks are around 6, 10 and 12 eV in the UV region. These characteristics confirm the suitability of MoN2 and MoS2 for visible and UV sensing applications. The reflectance is depicted in Figure 5 and we observe large static reflectance value greater than 0.7 for MoN2 that is double that of MoS2 in the xx direction. In the zz direction, the values are 0.35 and 0.25 for MoN2 and MoS2 respectively. The graphs show that MoN2 is a good infrared reflector, whereas MoS2 reflects best just beyond the visible range.

**Figure 5.** The reflectance R (ω) for MoN2 (**a**) and MoS2 (**b**) in the xx in-plane and zz out of plane directions in the photon energy range of 0–14 eV.

#### **4. Conclusions**

In conclusion, as opposed to MoS2, MoN2 is a semi metal as evinced from the band structure plots. Both the layered materials show anisotropy for all the optical properties with different magnitudes and peak positions, although the shapes of the graphs for the same property are similar in the two directions.

The large values of refractive index and good optical conductivity, absorption and reflectance results obtained reinstate the suitability of these materials for optical sensing applications. In comparison to MoS2, MoN2 shows suitability for infrared sensing applications in addition to visible and UV.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/article/10 .3390/CSAC2021-10429/s1.

**Funding:** No funding was received for this research work.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Data can be provided upon reasonable request.

**Conflicts of Interest:** There are no conflict of interest to declare.

#### **References**


### *Proceeding Paper* **Essential Oils as Possible Candidates to Be Included in Active Packaging Systems and the Use of Biosensors to Monitor the Quality of Foodstuff †**

**Anton Soria-Lopez 1, Maria Carpena <sup>1</sup> , Bernabe Nuñez-Estevez 1,2, Paula Garcia-Oliveira 1,2 , Nicolas Collazo 1, Paz Otero 1, Pascual Garcia-Perez <sup>1</sup> , Hui Cao 1, Jianbo Xiao 1, Márcio Carocho <sup>2</sup> , Lillian Barros <sup>2</sup> , Jesus Simal-Gandara 1,2,\* and Miguel A. Prieto 1,2,\***


**Abstract:** Active packaging has gained interest in recent years. As well as protecting food from the environment, it can incorporate agents with specific properties to extend the shelf life of the food. As a requirement, it is essential that the active agent has a greater affinity for the food than for the packaging material and, in this sense, essential oils (EOs) are potential candidates to be included in this new packaging system. The use of EOs can add to food matrix antimicrobial and antioxidant properties, reduce the permeability of the packaging to water vapor and extend the shelf life of food products. However, their use has been limited because they can produce a strong flavor by interacting with other compounds present in the food matrix and modify the organoleptic characteristics. Although the nanoencapsulation of EOs can provide chemical stability and minimize the impact of the Eos on the organoleptic properties by decreasing their volatilization, some physical modifications have still been observed, such as plasticizing effects and color variations. In this sense, the quality of the food products and consumer safety can be increased by using sensors. This technology indicates when food products are degrading and informs us if specific packaging conditions have changed. This work focuses on highlighting the use of biosensors as a new methodology to detect undesirable changes in the food matrix in a short period of time and the use of nanotechnology to include EOs in active films of natural origin.

**Keywords:** active packaging; intelligent packaging; EOs; nanoencapsulation; biosensors

#### **1. Introduction**

There is a vast variety of foods that is sensitive to deterioration through the action of microorganisms and to the oxidation of lipids during storage. Packaging is used to protect foods against external and internal conditions, to ensure food safety and to avoid rapid deterioration caused by chemical and microbiological contamination. Furthermore, nowadays, consumers are more conscious about sustainability as a benefit of safe and healthy foods. As a result, the use of materials of natural origin (proteins, polysaccharides or lipids) as food packaging has gained attention in recent years. Simultaneously, two new technologies have emerged to protect foods and increase food shelf life, namely [1]: (i) intelligent packaging (IP) and (ii) active packaging (AP).

**Citation:** Soria-Lopez, A.; Carpena, M.; Nuñez-Estevez, B.; Garcia-Oliveira, P.; Collazo, N.; Otero, P.; Garcia-Perez, P.; Cao, H.; Xiao, J.; Carocho, M.; et al. Essential Oils as Possible Candidates to Be Included in Active Packaging Systems and the Use of Biosensors to Monitor the Quality of Foodstuff. *Chem. Proc.* **2021**, *5*, 28. https://doi.org/10.3390/ CSAC2021-10485

Academic Editor: Ye Zhou

Published: 30 June 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

AP consists of the inclusion of chemical or bioactive compounds into the packaging system to ensure that the protective function of the packaging has a longer duration. This type of packaging interacts with the product, which can absorb or release components from the food [2,3]. Despite there being AP that contains different chemical additives, the use of bioactive compounds, such as essential oils (EOs), as new additives has gained attention. They are incorporated into films and coatings because of their important biological activities, such as their antioxidant and antimicrobial properties [4]. However, this technology presents some limitations to being applied at industrial level. For this reason, nanoencapsulation has emerged to improve food quality and reduce the limitations of AP in combination with active ingredients.

Regarding IP, its main objective is to control the conditions of packaged foods, such as the environment around them (i.e., storage conditions, food quality, sell by date, etc.). Biosensors are a type of sensor that belong to IP technology that have been widely employed at an industrial level in food processing during recent years. Specifically, electrochemical biosensors are the most used technology. However, they are still in the improvement phase of increasing their applications in packaging systems. These devices can detect undesirable changes or processes that can occur inside packaging systems, and transform them into a certain signal that can be easily analyzed [5,6].

This proceeding paper is focused on the use of EOs as possible natural additives or ingredients to be incorporated into the AP system, in the form of films or coatings, due to their antioxidant and microbial activities, and the use of biosensors as a possible tool to detect any undesirable changes inside of the packaging system. Finally, nanoencapsulation could be a suitable solution to improve food quality and safety even more.

#### **2. Essential Oils in Active Packaging System**

Active packaging (AP) is a novel method mainly utilized to prolong the shelf life of food products and to improve food quality and safety [3]. Many industries are interested in obtaining AP of natural origins that contains ingredients with bioactive compounds in order to avoid the use of chemical additives that can be harmful to human health, minimize the environmental impacts and ensure the acceptance of consumers. Essential oils (EOs) are one of the possible candidates for natural food additives.

EOs are volatile liquids of a lipid nature that can be obtained from plants. They are classified as GRAS (generally recognized as safe) food additives [7], thus their use has gained the attention of many researchers because of their antioxidant and antimicrobial activities. In addition, they can be used such as food preservatives or incorporated into edible films or coatings. Regarding food preservatives, their use is very limited due to their strong flavor and odor. As for edible films, there is a current trend in using materials such as polysaccharides, proteins or lipids as the edible films or coatings of packaging. EOs are used as additives or ingredients in edible emulsified films and coatings and can be incorporated into these edible matrices by several methods, emulsification being the most common. In fact, many studies are focused on using EOs as food additives in the packaging field to compete with the current packaging materials due to their substantial possibilities and adaptability [8–10].

#### *2.1. Effect of the Incorporation of EOs in AP*

The incorporation of EOs into the film matrix leads to a heterogeneous film structure featuring discontinuities, producing modifications to physical properties of the film such as tensile strength (TS), water vapor permeability (WVP), color, transparency and gloss [11]. Regarding TS, studies have shown different responses of TS when incorporating EOs into the film matrix [12–14]. In fact, the effect of the addition of EOs on the tensile properties of edible films depends on the specific interactions between the oil components and the polymer matrix. Concerning WVP, most studies have shown that the incorporation of EOs into the film matrix leads to an improvement of the water vapor barrier properties and a decrease in WVP [15,16]. Keeping this in mind, the hydrophobicity of EOs is a very

fluctuating characteristic because it depends on various factors. Finally, color, transparency and gloss are influenced by the type and concentration of EOs [11]. So, the incorporation of EOs into the matrix leads to specific physical modifications in the packaging that can reduce the quality and safety of the food products.

On the other hand, EOs are known for the presence of chemical compounds with antioxidant and microbial properties, which can be applied to avoid oxidation and increase food quality [11]. The antioxidant activity of the EOs occurs through different mechanisms: acting as O2 scavengers; producing a barrier against O2.; and promoting a specific antioxidant action. In this sense, the incorporation of EOs can lead to the improvement of food quality and a reduction in food waste due to the oxidation [17]. However, their use is limited at an industrial level due to the possible migration of these compounds into the food product and, consequently, the modification of its organoleptic properties. Concerning microbial capacity, it depends on the characteristics of the EO and the type of microorganism. The antimicrobial action mainly inhibits the growth of food pathogens, thus ensuring protection against microbial deterioration [18]. Many industries are interested in obtaining packaging systems with antimicrobial properties, since they will promote a longer shelf life for food products and guarantee a better food quality. Table 1 shows some examples of AP where EOs with antimicrobial and antioxidant properties have been incorporated.

**Table 1.** Recent examples of active films containing EOs as the active agents, showing their main components and biological properties for packaged food products.


Note: ZEO: *Zataria multiflora* essential oil; CEO: cinnamon essential oil; GA: gum arabic; OLEO: *Citrus sinensis* essential oil; OEO: oregano essential oil; PAEO: *Plectranthus amboinicus* essential oil; DPHH: 2,2-diphenyl-1-picrylhydrazyl.

#### *2.2. Nanoencapsulation*

Due to some disadvantages that EOs present when used as food additives (low solubility, high volatility, strong flavor, sensible to heat and light or the possibility of adversely affecting the organoleptic properties of food), many researchers began to focus their studies on the use of nanotechnologies in order to overcome these limitations and contribute to improving food preservation [21]. The nanoencapsulation technique consists of introducing an active agent (EO) into a polymer membrane with a diameter of 0.05–1 μm, known as a nanocapsule (Figure 1). This technique is used to protect the EOs against the previous limiting factors since this membrane acts as a barrier against the external environment, which preventions oxidation, masks unpleasant odors and taste and avoids

the loss of the volatile substances of the EOs. In addition, nanoencapsulation allows the controlled release of the EOs from the capsule, meaning that the release of the active agents occurs at the ideal place and time. Likewise, the nanoencapsulation of EOs can improve their biological activities, since their bioavailability depends on surface/volume ratio and particle size [22,23]. Keeping this in mind, the lower the particle size, the higher the surface/volume ratio or stability during the incorporation into the matrix. Many studies that employed this technique using EOs have shown excellent results in the quality and shelf life of food products [24,25].

**Figure 1.** Biosensor structure, nanoencapsulation of EOs and functions of active films or coatings. Created with BioRender.com.

#### **3. Biosensors**

Besides AP, another technology has emerged in recent years, known as intelligent packaging (IP). IP is a packaging system that contains a certain device that provides information to the retailer or consumer about the state of the food product and its surrounding environment. In this sense, IP allows a constant communication about the state of the system with all steps of the supply chain, which is an important characteristic of this technology [3,26]. Keeping this in mind, this technology allows for the quick detection of unpleasant changes in the packaging system, an increase in food safety and the production of less food waste. Sensors, indicators and identification systems are the main components of IP, with sensors being the most common components and the ones that have received the most attention in recent years. All sensors contain: (i) a detection system, known as a receptor, which can detect specific analytes and transform its presence into an electric signal; (ii) a signal processor, known as a transducer, which is responsible for processing the generated signal; and (iii) an electronic system, which is responsible for displaying the measured properties. Depending on the type of analyte that they can detect, sensors can be chemical or biological, with the latter being the most promising technology to develop and improve IP systems. Biosensors are responsible for transforming biological responses into a processed signal, with enzymes, receptor proteins, antibodies and nucleic acids being the recognition elements (Figure 1) [5]. In fact, the use of enzymes as recognition elements is widely employed due to low production costs, lack of the need for additional instrumentation, small size and ease of use. Regarding the transducer group, biosensors

can be optical, mass-based, calorimetric or electrochemical, with the latter being the most used and the one that has gained the most attention. Electrochemical biosensors consist of devices that measure the electrochemical signal that is proportional to the analyte concentration [27]. However, their current applications in IP are limited to certain conditions since the biosensor structure can present biological components that have harmful effects. Furthermore, important improvements are needed in the biosensor structures in order to avoid the pretreatment of food samples and include degradation markers in packaging systems [28]. Therefore, more studies are required to improve and reduce these limitations.

#### **4. Conclusions**

In recent decades, both AP and IP have emerged as technologies that protect foods and increase food shelf life. In addition, due to a large percentage of consumers being conscious of environmental sustainability, many industries have employed natural food additives or ingredients, such as Eos, to replace synthetic chemical additives and the use of natural materials (i.e., proteins, polysaccharides or lipids) to reduce major waste. However, there are some limitations concerning the use of EOs as active agents, such as their low solubility, high volatility, strong taste and flavor, sensibility to heat and light, changes in organoleptic properties and modifications of the physical properties of the films or coatings. Nanotechnology, specifically the nanoencapsulation of EOs, has gained attention during recent years and has been presented as a new alternative to improve the quality of food products as many studies suggest that they have major benefits. On the other hand, biosensors, specifically electrochemical biosensors, could be the most promising technology for IP systems. In fact, the combination of AP with nanocapsules containing EOs and biosensors could lead to important improvements in food safety, an extension of products' shelf life and higher protection against oxidation and food deterioration mediated by the action of microorganisms.

**Author Contributions:** Conceptualization, A.S.-L., M.C. (Maria Carpena), B.N.-E., P.G.-O. and N.C.; investigation, A.S.-L., M.C. (Maria Carpena), B.N.-E., P.G.-O., N.C., P.O., P.G.-P., H.C. and M.C. (Márcio Carocho); resources, J.X., L.B., J.S.-G. and M.A.P.; writing—original draft preparation, A.S.-L., Maria Carpena, B.N.-E., P.G.-O. and N.C.; writing—review and editing, P.O., P.G.-P., H.C. and M.C. (Márcio Carocho); visualization, J.X., L.B., J.S.-G. and M.A.P.; supervision, J.X., L.B., J.S.-G. and M.A.P.; project administration, J.X., L.B., J.S.-G. and M.A.P.; funding acquisition, J.X., L.B., J.S.-G. and M.A.P. All authors have read and agreed to the published version of the manuscript.

**Funding:** The JU receives support from the European Union's Horizon 2020 research and innovation program and the Bio Based Industries Consortium. The project, SYSTEMIC Knowledge hub on Nutrition and Food Security, has received funding from national research funding parties in Belgium (FWO), France (INRA), Germany (BLE), Italy (MIPAAF), Latvia (IZM), Norway (RCN), Portugal (FCT) and Spain (AEI) in a joint action of JPI HDHL, JPI-OCEANS and FACCE-JPI, launched in 2019 under the ERA-NET ERA-HDHL (n◦ 696295).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Acknowledgments:** The research leading to these results was supported by: MICINN, for providing the Ramón y Cajal grant for M.A. Prieto (RYC-2017-22891); Xunta de Galicia, for providing the EXCELENCIA-ED431F 2020/12 program and the predoctoral grant for P. García-Oliveira (ED481A-2019/295); the University of Vigo, for providing the predoctoral grant for M. Carpena (Uvigo-00VI 131H 6410211); the EcoChestnut Project (Erasmus+ KA202) for supporting the work of B. Nuñez-Estevez; the Bio Based Industries Joint Undertaking (JU) under grant agreement No 888003 UP4HEALTH Project (H2020-BBI-JTI-2019) for supporting the work of P. Otero and P. Garcia-Perez; and the Ibero-American Program on Science and Technology (CYTED—AQUA-CIBUS, P317RT0003). The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for its financial support through the national funds FCT/MCTES to CIMO (UIDB/00690/2020), and to the national funding from FCT, P.I., through the institutional scientific employment program contract for L. Barros. **Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


### *Abstract* **From Single Nanowires to Smart Systems: Different Ways to Assess Food Quality †**

**Matteo Tonezzer 1,\* , Franco Biasioli <sup>2</sup> and Flavia Gasperi <sup>3</sup>**


**Abstract:** Recently, low-dimensional (1D, 2D) nanostructured materials have been attracting more and more interest as building blocks for innovative systems. Metal oxide nanowires are one of the most widely used materials for solid-state gas sensors, as they are simple to make, inexpensive, and sensitive to a wide range of gases and volatiles. Unfortunately, their broad sensitivity has a price to pay, which is very low selectivity. Fortunately, this flaw is not a problem for all applications. Where the boundary conditions are defined and "simple" (only the presence of a target gas is expected, without any interfering gases), a single traditional chemiresistor may be the best choice, while in cases where the variables are many, it is better to use an intelligent system. In this paper, we will show a resistive sensor based on a single SnO2 nanowire which, working at three temperatures (200, 250, and 300 ◦C), is able to detect tens of ppb of ammonia (30 ppb at 300 ◦C). The limit of detection (LoD) was calculated as 3 N/S, where N is the standard deviation of the sensor signal in air and S is the sensor sensitivity. We will show that the performance of this nanosensor is excellent and can be used in various applications, including agri-food quality monitoring. We will demonstrate that the SnO2 nanowire in a thermal gradient can act as a nano-electronic nose thanks to machine learning algorithms. The single nanowire-based sensor can estimate the total viable count with an error of 2.32% on mackerel fish samples stored at room temperature (25 ◦C) and in a fridge (4 ◦C). The integration of such a small (less than one square mm) and cheap device into the food supply chain would greatly reduce waste and the frequency of food poisoning.

**Keywords:** gas sensors; metal oxide; nanowire; electronic nose; machine learning

**Supplementary Materials:** The following are available online at https://www.mdpi.com/article/10 .3390/CSAC2021-10605/s1.

**Author Contributions:** Conceptualization, M.T.; methodology, M.T.; software, M.T.; validation, M.T., F.B. and F.G.; formal analysis, M.T.; investigation, M.T.; resources, F.B., F.G.; data curation, M.T.; writing—original draft preparation, M.T.; writing—review and editing, M.T., F.B. and F.G.; visualization, M.T.; supervision, F.B. and F.G.; project administration, F.B. and F.G.; funding acquisition, F.B. and F.G. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.


**Citation:** Tonezzer, M.; Biasioli, F.; Gasperi, F. From Single Nanowires to Smart Systems: Different Ways to Assess Food Quality. *Chem. Proc.* **2021**, *5*, 29. https://doi.org/10.3390/ CSAC2021-10605

Academic Editor: Ye Zhou

Published: 5 July 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

**Data Availability Statement:** The data presented in this study are openly available in Open Science Framework at doi:10.17605/OSF.IO/83SMW.

**Conflicts of Interest:** The authors declare no conflict of interest.

*Proceeding Paper*
