Detection of Food Contaminants Based on Dual‐Mode Electrochemical and Optical Aptasensors: A Review

ABSTRACT

Food safety is crucial for human health, and the development of rapid and sensitive detection technologies is of great significance for pollutant monitoring. The integration of electrochemical and optical approaches in dual‐mode aptamer (APT) sensors has been shown to enhance detection reliability via complementary signal verification. While current implementations focus mainly on single‐target detection, the modularity of APT recognition elements and the multiplexing capability of optical readouts such as surface‐enhanced Raman spectroscopy (SERS) and fluorescence, provide a clear route toward simultaneous ultratrace monitoring of multiple contaminants in future developments. This review comprehensively evaluated the working principles and analytical performance of dual‐mode sensors, including electrochemical‐colorimetric, electrochemical‐fluorescent, and electrochemical‐SERS, among others, as well as focused on the impact of their integrated signal amplification strategies on sensitivity and detection range. Studies have shown that dual‐mode sensors perform well in the laboratory, but still face some challenges such as insufficient stability of nanomaterials, limited multi‐target detection capability of APTs and high cost of equipment. In order to further promote its practical application in the field of food safety, this paper also provided theoretical framework on the optimization and innovation of dual‐modal sensing technology, to facilitate the construction of an efficient food contaminant monitoring system.

Combining electrochemical (amperometry/impedance) and optical (colorimetry, fluorescence, SERS) readouts, this aptasensor offers complementary signal verification for reliable, sensitive food contaminant detection. Nanostructures and nucleic acid circuits amplify signals. Stability, multiplexing, and cost remain key challenges for future optimization.

1. Introduction

Food safety is predominantly compromised by multiple contamination vectors, including pathogenic microorganisms, mycotoxins, persistent organic pollutants (POPs), and heavy metal ions. These hazardous agents are primarily introduced through agricultural and industrial contamination pathways along the food supply chain [1, 2]. Food contamination is defined as the introduction of harmful biological agents, toxic chemical compounds, or foreign particulates into food products. Based on the origin of contaminants, it is systematically categorized into three distinct classes: biological contamination, chemical contamination, and physical contamination [3]. The ingestion of contaminated foodstuffs induces acute/chronic toxicological manifestations, including teratogenic effects, genomic instability, and carcinogenic progression. As a critical global public health challenge, foodborne contaminants contribute substantially to the global disease burden.

Conventional analytical platforms, including high‐performance liquid chromatography (HPLC), enzyme‐linked immunosorbent assay (ELISA), and capillary electrophoresis (CE) demonstrated superior sensitivity and specificity. However, these laboratory‐bound techniques impose significant limitations: (i) prolonged analysis duration, (ii) high operational costs and equipment depreciation, and (iii) technical complexity requiring, which limited their application [4]. For example, liquid chromatography‐based detection needs rigorous sample pretreatment protocols to achieve interference suppression and analyte preconcentration. Furthermore, ELISA method also usually suffers from poor reproducibility, false positives, and are highly affected by temperature and time [5]. Therefore, this necessitates the urgent development of robust detection platforms integrating high sensitivity, multiplex analysis capability, and real‐time monitoring.

Aptamer (APT)‐based biosensing platforms demonstrate superior analytical performance over conventional methods, such as high sensitivity, real‐time detection, and instrumentation miniaturization [6]. To date, various aptasensors based on fluorescence, colorimetric, surface‐enhanced Raman spectroscopy (SERS), chemiluminescence, and electrochemical techniques have been developed. Among these, electrochemical aptasensors have shown significant advantages in biomedical diagnostics and food quality control due to their high sensitivity, low cost, and excellent compatibility [7]. However, traditional electrochemical aptasensors primarily rely on single‐signal detection modes [8]. These systems are susceptible to interference from electrode modification processes and complex environmental conditions, resulting in compromised reliability for trace‐level analysis. To address these limitations, dual‐signal electrochemical aptasensors have been progressively developed, demonstrating enhanced reproducibility in challenging operational scenarios [9]. This review systematically examines the evolution from single‐mode to dual‐mode electrochemical‐optical aptasensors, focusing on how integrating complementary optical readouts with electrochemical detection addresses the inherent limitations of single‐signal platforms.

Conventional single‐mode detection systems exhibit inherent vulnerabilities to environmental variability and procedural inconsistencies. Dual‐mode sensing platforms, conversely, operate through integrated dual‐signal transduction pathways that synergistically combine modality‐specific merits while enabling cross‐verification of analytical outputs. The operational independence between modalities ensures distinct recognition mechanisms [10]. This paradigm has driven the development of dual‐mode platforms employing complementary response mechanisms for food contaminant screening. Dual‐mode and ratiometric single‐mode strategies both provide self‐calibration. Zhang et al. built a voltage‐resolved PEC aptasensor with Ru(bpy)₃ ²⁺‐BiOBr; bias (±0.1 V) switched Type II/Z scheme, generating anodic/cathodic currents for self‑correction, improving chloramphenicol detection and enabling portable DMM readout [11]. Such designs reflect the demand for reliable food safety sensing. Practical realization, however, relies on rational nanomaterial design and signal amplification, which is discussed below.

Among these techniques, electrochemical and optical analytical platforms hold potential for accurate identification of bacteria due to their low interference and high sensitivity [12]. A crucial determinant in optimizing these analytical platforms lies in the strategic engineering of bifunctional nanohybrid materials [13]. Through the development of nanocomposites that enable synergy between the nanomaterials' intrinsic properties and functionalities, researchers have harnessed nanotechnology advancements to create the integrated electrochemical and optical sensing architectures [14, 15]. This technological progression established robust for dual‐mode detection frameworks. Noble metal nanomaterials, particularly gold nanoparticles (AuNPs), have been predominantly implemented in aptasensor development owing to their superior electron transfer kinetics [16, 17, 18]. These nanomaterials demonstrate exceptional compatibility with electrochemical aptasensing frameworks, serving as multifunctional components in bio interface, signal transduction, and amplification cascades [19, 20, 21]. The covalent Au─S bond formation between gold nanostructures and thiolated APTs enables robust immobilization of biorecognition elements at sensor interfaces through spontaneous self‐assembly processes. This conjugation mechanism synergizes with the biocompatibility of AuNPs, which optimally preserves the structural integrity and biological activity of immobilized biomolecules. Beyond conventional noble metal nanomaterials, covalent organic frameworks (COFs) have emerged as photoactive materials for biosensing. Unlike metal‐based ones, COFs are porous crystalline organic frameworks linked by covalent bonds, offering low biotoxicity, good biocompatibility, and better water stability than MOFs. In situ growth of 2D COF films on electrodes under mild conditions accelerates charge transfer and improves stability, offering a new paradigm for high‑performance interfaces [22]. Complementing these interfacial engineering advantages, enzyme‐free hybridization chain reaction (HCR) amplification leverages thermodynamic driving forces to achieve autonomous chain elongation [23]. Ultimately, it generates double‐stranded DNA (dsDNA), which exhibits abundant conformational changes and provides numerous binding sites for signal probes [24]. Meanwhile, nuclease‐assisted cyclic amplification strategies have also been integrated into aptasensor designs to further enhance sensitivity, enabling the conversion of a single target recognition event into multiple signal outputs. This dual‐phase amplification strategy establishes a paradigm for high‐fidelity signal enhancement in next‐generation biosensing systems. Building on these material and amplification strategies, the following section categorizes and critically evaluates five principal electrochemical‐optical dual‐mode aptasensing platforms for food contaminant detection.

Given the potential of multimodal sensing in food safety monitoring, this review systematically evaluates the electrochemical‐optical dual‐mode APT‐based biosensing platforms for detecting critical food contaminants‐including mycotoxins, pesticide residues, and foodborne pathogens. The platforms are categorized into five principal modalities: (i) electrochemical‐colorimetric, (ii) electrochemical‐surface enhanced Raman spectroscopy (EC‐SERS), (iii) electrochemical‐fluorescence, (iv) electrochemical‐surface plasmon resonance (EC‐SPR), and (v) electrochemical‐photo electrochemical (EC‐PEC) detection frameworks. And this review culminates in a critical analysis of the technological bottlenecks and emerging innovation frontiers confronting dual‐mode biosensing platforms. Scheme 1 summarizes the framework of electrochemical–optical dual‐mode aptasensing platforms for food contaminant detection, covering target analytes (Panel A), working principle (Panel B), five sensing modalities (Panel C), and advantages over single‐mode detection (Panel D).

SCHEME 1.

Electrochemical‐optical dual‐mode aptasensing platforms for food contaminant detection.

2. Electrochemical Biosensor Principle

Electrochemical biosensors have emerged as indispensable analytical tools for quantifying foodborne contaminants due to their operational portability and high precision [25, 26]. These systems integrate biological recognition elements including enzymes, antibodies, APTs, and nucleic acids with transducing electrodes through advanced immobilization techniques [26, 27]. A common feature of all electrochemical sensors is their simplicity, rapid detection, low cost‐effectiveness, and ease of miniaturization, which are essential for point‐of‐care (POC) applications of biosensors. When target molecules generate physical or chemical signals at the electrode surface, the sensor converts these signals into measurable electrical signals (such as current or impedance) to detect the analyte through their changes [28, 29]. They can be classified based on whether they measure current (via voltammetry and amperometry) and potential (or charge) accumulation (potentiometry), or the conductivity of reactants and the medium (impedance or conductance methods). These include potentiometry, amperometry, linear sweep voltammetry (LSV), cyclic voltammetry (CV), differential pulse voltammetry (DPV), square wave voltammetry (SWV), and electrochemical impedance spectroscopy (EIS) [30, 31].

Recent studies further demonstrate electrochemical aptasensors for pathogen detection. A GO‑BSA aptasensor detected Salmonella in chicken with LOD 3 CFU/mL and 28‐day stability [32]. A paper‐based cellulose nanocrystal aptasensor detected Salmonella with LOD 3.50 CFU/mL and response <30 min [33]. A Ag‐decorated magnetic bead paper aptasensor for Shigella achieved LODs 90 CFU/mL (DPV) and 8.09 CFU/mL (EIS) with NFC [34]. A superhydrophobic magneto‐flow aptasensor for Salmonella achieved LOD 10.01 CFU/mL and linear range 10‐10⁵ CFU/mL without pumps [35]. These examples show versatility and practical potential across diverse matrices and detection modes.

Table 1 compares single‐mode EC and dual‐mode EC/optical aptasensors in advantages, limitations, and key features. Single‐mode EC sensors are simple, low‐cost, and easy to interpret, suitable for routine screening in well‐characterized matrices. However, reliance on a single pathway makes them susceptible to electrode fouling, nonspecific adsorption, and environmental fluctuations, compromising reliability in complex samples. In contrast, dual‐mode systems add an independent optical signal for cross validation, reducing false positives/negatives. Their two modalities often show complementary linear ranges, extending the dynamic range beyond either mode alone. While dual‐mode platforms increase instrumentation complexity and per‐test cost modestly, they offer higher analytical confidence—critical for food safety monitoring where reliability is essential.

TABLE 1.

Comparison of single‐mode electrochemical and dual‐mode electrochemical‐optical aptasensors for food contaminant detection.

Features	Single‐mode EC aptasensor	Dual‐mode EC‐optical aptasensor
Signal transduction	Single pathway (current/impedance/potential)	Two independent pathways (EC + optical: COL/FL/SERS/SPR/PEC/ECL)
Result verification	Cannot self‐validate; relies on replicate measurements	Built‐in cross‐validation between two independent modalities
False positive risk	High (susceptible to electrode fouling, nonspecific adsorption, and interfering electroactive species)	Low (positive result requires simultaneous response from both channels)
False negative risk	Moderate (signal suppression by matrix effects or electrode passivation)	Low (optical modality provides independent readout unaffected by electrode surface changes)
Sensitivity	Excellent (depends on EC technique and amplification)	Comparable or enhanced (two independent signal generation mechanisms)
Dynamic range	Often limited by electrode saturation or signal‐to‐noise constraints	Extended (two modalities often have complementary linear ranges)
Matrix tolerance	Poor to Moderate (complex matrices interfere with electron transfer)	Good to Excellent (optical signal is generally immune to electroactive interferents)
Instrumentation	Simple, portable potentiostat	More complex (EC workstation + optical readout system)
Cost per test	Low	Moderate to High
Operational complexity	Low	Moderate
Data interpretation	Straightforward (univariate signal change)	More complex (requires correlation of two independent signals, but offers richer information)
Ideal application	Routine quantitative screening in well‐characterized, low‐interference matrices	Confirmatory analysis in complex matrices; regulatory testing requiring high confidence

3. Principles of Optical Biosensors

Optical biosensors are constructed based on different properties of light (such as luminescence, absorption, fluorescence, refractive index, and light scattering) to detect changes when optically active analytes interact with bio‐receptors/bio‐ligands. This process enables the interaction between the recognition element and the target to be converted into optical signals directly related to the target concentration [36]. Optical biosensors can be categorized into colorimetric, fluorescence, electrochemiluminescence, chemiluminescence, SERS, and surface plasmon resonance (SPR) biosensors [37]. Typical optical biosensors are produced by immobilizing bio‐recognition elements on the sensor surface [38], with the bio‐recognition layer subsequently used to capture target analytes such as bacteria, proteins, nucleic acids, and cells [39]. The formation of the bio‐interface layer largely depends on the surface parameters of the transducer [38]. The generated optical signals have minimal noise and are often unaffected by external interference, making them more beneficial than other physical signals, such as thermal or electrical signals.

Electrochemical and optical biosensors are complementary rather than competing. Electrochemical detection offers high sensitivity, fast response, and ease of miniaturization, suitable for routine quantitative and POC analysis. However, relying on a single transduction pathway makes it susceptible to environmental and interfacial changes, compromising trace‐level reliability, especially in complex matrices [40]. Optical biosensors provide richer molecular information via SERS, SPR, or fluorescence. They are more robust against non‑specific interference, but their deployment is limited by equipment complexity, substrate uniformity, and, in some modes, poor sensitivity to small targets or reliance on labeling [41]. This complementarity drives their integration into dual‐mode architectures to combine strengths and offset limitations.

4. Application of Dual‐Mode Electrochemical‐Optical Biosensors in Food Contaminant Detection

Dual‐mode sensing superiority is not merely the sum of two LODs. Its advantages are threefold. First, cross‑validation via two independent pathways reduces false positives from electrode fouling or nonspecific adsorption. As shown by He et al. [8], physical separation of EC and fluorescence enables each mode to operate optimally, and signal agreement confirms target presence. Second, EC offers high sensitivity but suffers matrix suppression, while optical readouts resist nonelectroactive interferents. Li et al. [42] integrated a smartphone RGB readout for visual screening and EC for quantitative confirmation. Third, the two channels saturate at different concentrations, extending the dynamic range; Zhang et al. [43] reported that the PEC mode extends limits by about two orders of magnitude. These advantages, such as cross, validation, complementarity, and extended range, make dual‐mode more reliable than single‐mode.

4.1. Electrochemical‐Colorimetric Mode

Colorimetric methods are widely used biochemical diagnostic techniques that quantify target components by measuring the color intensity arising from chromogenic reactions upon formation of colored products. This approach is cost‐effective, rapid, user‐friendly, and requires no external instruments or power sources. Moreover, it is robust against common interferents such as sample impurities, moisture, and dust [44]. However, colorimetric readings based on subjective visual assessment exhibit low discriminative resolution. This inherent limitation can lead to judgment inaccuracies and results in a relatively high limit of detection [45]. Consequently, a synergistic combination with complementary analytical techniques is often employed to achieve trace‐level detection. Electrochemical methods, for instance, offer a compelling solution due to their high sensitivity, excellent selectivity, and rapid response, thereby effectively addressing the constraints associated with standalone colorimetric sensors [46].

Owing to their intrinsic enzyme‐mimetic activity, coupled with favorable properties including high stability, potent catalytic performance, and tunable characteristics, nanozymes are frequently employed in the fabrication of dual‐mode colorimetric/electrochemical sensors [47]. Cu₂O is a typical p‐type semiconductor with extensive applications in catalysis [48]. A distinct concave architecture in Pd‐Cu₂O was achieved by Chen et al. through the selective etching of octahedral Cu₂O templates with PdCl₂. This structural design enhanced the exposure of active sites and mitigated particle aggregation [49]. Both Pt and Pd exhibit catalytic activity in decomposing H₂O₂ to generate hydroxyl radicals. Their synergistic interaction further enhances the catalytic oxidation of 3,3',5,5'‐tetramethylbenzidine (TMB). The resultant nanocomposite, PtNPs/Pd‐Cu₂O, provides an increased number of active sites and a larger surface area, thereby serving dual functions: efficiently catalyzing the chromogenic reaction of TMB and accommodating a high loading capacity of methylene blue (MB) as signal molecules [50]. Building upon these principles, the Yu et al. [51] constructed a dual‐mode electrochemical‐colorimetric aptasensing platform for the detection of aflatoxin B1 (AFB1), a potent carcinogenic contaminant in food, utilizing the bifunctional nanozyme PtNPs/Pd‐Cu₂O. As illustrated in Figure 1, the synthesized PtNPs/Pd‐Cu₂O was functionalized separately to obtain two probes: HP₂‐MB/PtNPs/Pd‐Cu₂O and HP₃‐PtNPs/Pd‐Cu₂O. Upon introduction of AFB1, it specifically binds to its APT, which carries two complementary sequences. Following magnetic separation, the supernatant undergoes a catalytic hairpin assembly (CHA) reaction on the electrode surface. This process immobilizes numerous HP₂‐MB/PtNPs/Pd‐Cu₂O probes loaded with MB as an electrochemical reporter, thereby generating a measurable current signal. Concurrently, HP₃‐PtNPs/Pd‐Cu₂O in the precipitate first participates in a HCR, leading to partial consumption, and subsequently catalyzes the H₂O₂‐mediated oxidation of TMB to yield a blue‐colored product for colorimetric readout. The sensor demonstrated a wide linear range from 0.001 to 1000 ng/mL for electrochemical detection, with a limit of detection (LOD) as low as 0.76 pg/mL. The colorimetric mode exhibited a linear range of 0.001‐500 ng/mL and achieved a LOD of 0.49 pg/mL.

FIGURE 1.

Preparation of signal probes HP₂‐MB/PtNPs/Pd‐Cu₂O and HP₃‐PtNPs/Pd‐Cu₂O (A); (B) schematic diagram of the colorimetric electrochemical dual‐membrane aptasensor detection principle. Reproduced with permission [51]. Copyright 2025, Elsevier Ltd.

Amoxicillin, a semi‐synthetic penicillin widely used in animal husbandry, may cause resistance and residues, posing health risks. Reliable rapid monitoring is needed. Duan et al. [52] constructed a dual‑mode electrochemical‐colorimetric aptasensor using FePOs@CeO₂ as signal probe. As illustrated in Figure 2, FePOs@CeO₂ combines peroxidase‐like activity of FePOs and conductivity from CeO₂ (Ce³⁺/Ce⁴⁺). A truncated APT AMO‐1b was obtained via Capture‐SELEX and molecular docking. Thiolated AMO‑1b was immobilized on gold electrode as capture probe, and FePOs@CeO₂ conjugated with cDNA as signal probe. Hybridization assembled both probes on electrode. FePOs@CeO₂ catalyzes H₂O₂/TMB to produce blue color for colorimetric readout, and its redox states enable electrochemical response. Amoxicillin binds APT, disrupting the duplex and releasing signal probe, thus altering impedance and color. The sensor gave linear ranges 1‐100 µg/mL (colorimetric) and 10⁻⁴‐50 µg/mL (electrochemical), with LODs 0.828 µg/mL and 7.24 × 10⁻⁵ µg/mL, respectively.

FIGURE 2.

Schematic illustration of the colorimetric/electrochemical dual‐mode aptasensor for AMO detection. Reproduced with permission [52]. Copyright 2025, Elsevier Ltd.

In recent years, the miniaturization and intelligent design of electrochemical devices have made point‐of‐care testing (POCT) methods based on smartphones show great potential in bioanalysis [53, 54]. Li et al. [42] developed a smartphone‐integrated dual‐mode aptasensor for OTA using Fe‐MIL‐88, a MOF with dual peroxidase‐like and electroactive functions. The assay employs a competitive binding mechanism coupled with RCA amplification (Figure 3). OTA displaces an MB‐labeled linker DNA, triggering RCA to immobilize Fe‐MIL‐88 signal probes (DNA1@AuNPs/Fe‐MIL‐88) for electrochemical detection via a USB potentiostat. Simultaneously, the POD activity of Fe‐MIL‐88 catalyzes a TMB‐H₂O₂ colorimetric reaction, quantified by UV‐Vis or smartphone RGB analysis. The sensor achieved ultra‐sensitive detection with LODs of 0.22 fg/mL (electrochemical), 0.25 fg/mL (colorimetric), and 0.4 fg/mL (smartphone RGB) across broad linear ranges (up to 250 ng/mL).

FIGURE 3.

Schematic diagram of electrochemical‐colorimetric dual‐mode POCT platform. Reproduced with permission [42]. Copyright 2025, Elsevier Ltd.

A comparison of the three electrochemical‐colorimetric aptasensors (Table 2) reveals distinct trade‐offs in design, performance, and applicability. Yu et al. [51] used PtNPs/Pd‐Cu₂O hollow octahedral nanozyme with magnetic separation, spatially isolating CHA electrochemical signaling from HCR colorimetric readout. This reduces cross‐talk and avoids efficiency losses from co‐localized surface modifications, enhancing hybridization efficiency and selectivity. However, the magnetic workflow requires multiple incubation and washing steps, increasing operational complexity and limiting throughput. Duan et al. [52] used FePOs@CeO₂ as a single‐material dual‐signal probe that integrates peroxidase‐like activity (from FePOs) and electrochemical conductivity (from Ce³⁺/Ce⁴⁺ redox couples). This simplifies fabrication but constrains independent optimization of each mode, possibly explaining the relatively narrow linear range and notable LOD difference. Their APT AMO‐1b also required docking‐assisted truncation for affinity, adding design complexity not present in the other studies. Li et al. [42] developed a smartphone‐based POCT platform using Fe‐MIL‐88 as bifunctional probe, achieving the widest dynamic range (1 fg/mL‐250 ng/mL in EC mode) and the lowest LOD (0.22 fg/mL). However, the smartphone RGB readout gave a higher LOD (0.4 fg/mL) than UV‐Vis spectrophotometry (0.25 fg/mL) in the same assay, demonstrating sensitivity trade‐offs in portable devices.

TABLE 2.

Comparison of electrochemical‐colorimetric dual‐mode aptasensors.

Studies	Design strategy	Performance metrics (ng/mL)	Practical applicability	Key limitations
Yu et al. [51]	PtNPs/Pd‐Cu2O hollow octahedral nanozyme + magnetic separation strategy + CHA/HCR dual signal amplification	EC: 7.60 × 10−4, 0.001‐1000; Col: 4.90 × 10−4, 0.001‐500	Magnetic separation spatially isolates two detection modes, minimizing cross‐talk	Magnetic separation adds operational complexity and limits throughput; CHA/HCR dual amplification adds reaction steps and optimization challenges
Duan et al. [52]	FePOs@CeO2 single‐material dual‐signal probe (POD‐like catalytic activity + Ce3+/Ce4+ electrochemical conductivity) + truncated aptamer optimization	EC: 7.24 × 10−2, 0.1‐5 × 104; Col: 8.28 × 102, 1 × 103‐1 × 105	Single‐material design simplifies fabrication and surface functionalization	Single‐material design constrains independent optimization of each signal modality; large LOD disparity between modes (>4 orders); narrow linear range; aptamer requires molecular docking‐assisted truncation
Li et al. [42]	Fe‐MIL‐88 bifunctional MOF (POD + electrochemical activity) + RCA signal amplification + smartphone‐based RGB readout	EC: 2.20 × 10−7, 1 × 10−6‐2.5 × 102; Col (UV‐Vis): 2.50 × 10−7, 1 × 10−6‐1 × 102; RGB: 4.00 × 10−7, 1 × 10−6‐1 × 102	Smartphone integration enables portability, user‐friendly operation, field‐deployable POCT, and low per‐test cost	RCA adds assay time; RGB sensitivity lower than UV‐Vis and dependent on smartphone camera consistency; variations across phone models may introduce discrepancies

These designs reflect distinct strategic priorities: Yu emphasizes signal fidelity/selectivity, Duan prioritizes fabrication simplicity, and Li targets field applicability with ultra‐low LOD via RCA. The optimal choice depends on the application scenario‐laboratory precision, streamlined manufacturing, or on‐site screening and no single design universally outperforms across all dimensions.

4.2. Electrochemical‐Fluorescence Mode

In recent decades, rapid‐response biosensors based on nanomaterials, such as colorimetric, fluorescent, electrochemical, and electrochemiluminescent methods, have attracted increasing attention [55, 56, 57]. Among these biosensors, electrochemical and fluorescent sensors have been particularly focused on owing to their remarkable sensitivity and selectivity. However, most sensors rely on single‐mode signal output, which often restricts the detection performance‐electrochemical sensors suffer from a limited linear range, while fluorescent sensors exhibit relatively poor sensitivity. In contrast, dual‐mode sensors integrating two physicochemical signals offer self‐validation and self‐calibration capabilities, thereby combining the respective strengths of each modality, such as the high sensitivity of electrochemical detection and the broad detection range of fluorescent assays [58].

COF are crystalline polymers featuring high surface areas and stable, ordered porous structures, enabling efficient loading of various functional species [59, 60]. In fluorescence sensing, COFs can be fluorescent by integrating organic chromophores with π‐conjugated systems and functional groups [61]. Moreover, COFs offer abundant binding sites for specific recognition elements while preserving their activity. Nevertheless, the poor conductivity of COFs limits their direct application in electrochemical sensors. To address this, Liang et al. [62] developed an MB‐encapsulated COF composite (MB@COF) modified with conductive AuNPs and electroactive MB, enabling the construction of a dual‐mode electrochemical and fluorescent aptasensor for tetracycline (TET) detection in food and water samples. The detection mechanism is illustrated in Figure 4. AuNPs and MB are sequentially loaded onto the surface and into the pores of COFs to form MB@AuNPs@COF. Subsequently, the single‐stranded DNA (ssDNA) immobilized on this composite hybridizes with the TET APT pre‐grafted on the electrode. In the absence of TET, the ssDNA‐MB@AuNPs@COF conjugate remains on the electrode, generating an electrochemical signal while the fluorescence signal in solution is quenched. Upon TET addition, specific binding between TET and its APT releases the ssDNA‐MB@AuNPs@COF from the electrode, resulting in fluorescence recovery and electrochemical signal attenuation. Consequently, the system exhibits weak fluorescence without TET, which intensifies with increasing TET concentration. This sensor achieves a detection range of 0.1 nM to 10 mM, with detection limits of 0.03 nM (electrochemical) and 0.05 nM (fluorescence).

FIGURE 4.

Schematic illustration of the COF‐based electrochemical/fluorescence dual‐mode sensor for TET detection. Reproduced with permission [62]. Copyright 2024, Elsevier Ltd.

To enhance the aptasensor sensitivity, various signal amplification strategies have been developed, including those based on nanomaterials [63] and DNA‐based methods [64]. Commonly used DNA amplification signal techniques include HCR, hairpin catalytic assembly [65], and rolling circle amplification [66]. HCR is an efficient assembly process in which an initiator triggers sequential hybridization events to form highly ordered long double‐stranded DNA (dsDNA). Notably, dsDNA can serve as a template for the formation of fluorescent copper nanoparticles (CuNPs). In the presence of ascorbic acid (AA) and CuSO_4, CuNPs are synthesized in situ, emitting red fluorescence whose intensity increases with dsDNA chain length [67]. Building on this strategy, He et al. [8] developed an electrochemical‐fluorescence dual‐mode aptasensor with three separable signals for accurate AFB1 quantification in peanut samples. As illustrated in Figure 5, Fc‐labeled AFB1 APTs hybridize with complementary DNA (cDNA) on the electrode to form double‐stranded structures, into which MB molecules are subsequently intercalated as an additional signal tag, generating two distinct electrochemical signals. Upon AFB1 introduction, specific binding releases cDNA and MB, while the Fc‐labeled APTs remain in proximity to the electrode surface, enabling a “signal‐on” for Fc and “signal‐off” for MB. Concurrently, the released cDNA triggers HCR to produce long dsDNA templates in solution, directing the formation of fluorescent CuNPs. This third response signal intensifies with increasing AFB1 concentration. The sensor exhibits detection limits of 2.5 pg/mL (electrochemical, 0.01‐200 ng/mL) and 0.28 pg/mL (fluorescence, 0.001‐200 ng/mL).

FIGURE 5.

Electrochemical‐fluorescence dual‐mode triple‐signal aptasensor for AFB1 detection. Reproduced with permission [8]. Copyright 2024, Elsevier Ltd.

Mercury (Hg²⁺) is a global pollutant with high toxicity to plants and animals [69, 70]. For electrode modification, two‐dimensional (2D) MXene offers advantages such as high electrical conductivity and a large electrochemical active area [71]. However, restacking of MXene nanosheets often compromises sensor performance. To address this, Li et al. [68] transformed 2D MXene (Ti₃C₂T_x) into 3D porous structures using PMMA spheres as sacrificial templates, thereby improving electron transport. The hammerhead‐shaped AuNPs employed exhibit excellent electrochemical properties and fluorescence quenching, while also enhancing probe ssDNA immobilization on the sensing interface. Accordingly, an electrochemical‐fluorescence dual‐mode aptasensor was developed for ultra‐trace Hg²⁺ detection. As shown in Figure 6, the Hg²⁺‐specific APT was first immobilized on a 3D porous AuNPs/MXene‐modified electrode, with Nile Blue (NB) attached to its terminus. Upon Hg²⁺ binding, the APT undergoes conformational change, bringing NB closer to the AuNPs surface, thereby amplifying the electrochemical signal. Meanwhile, due to the quenching effect of AuNPs, the fluorescence of NB is attenuated. Within concentration ranges of 10 fM‐0.1 nM and 5‐100 fM, detection limits of 2.69 fM (electrochemical) and 1.60 fM (fluorescence) were achieved, respectively.

FIGURE 6.

(A) Schematic illustration of the preparation of 3D porous MXene; (B) Schematic diagram of an electrochemical/fluorescence dual‐mode aptasensor. Reproduced with permission [68]. Copyright 2025, Elsevier Ltd.

Comparison of the three electrochemical‐fluorescence aptasensors (Table 3) reveals distinct trade‐offs in probe design, transduction, and performance. Liang et al. [62] used MB@AuNPs@COF as a dual‐functional probe, integrating COF fluorescence emission and MB electrochemical activity. The large surface area and ordered pores of COF enable high loading of AuNPs and MB, allowing simultaneous dual‐signal output from a single probe. However, because both signals originate from the same material, independent optimization of each mode is constrained, reflected in the relatively narrow linear ranges (0.1 nM‐10 mM for both EC and FL) and comparable LODs (0.03 and 0.05 nM). The multi‐step synthesis of COF and subsequent loading also adds fabrication complexity. He et al. [8] adopted a separated design, physically partitioning EC from FL detection. The electrochemical mode uses Fc (signal‐on) and MB (signal‐off), with the combined signa ΔI = |ΔI_Fc| + ΔI_MB yielding better sensitivity. Meanwhile, released cDNA triggers HCR in solution, forming dsDNA templates for in‐situ generation of fluorescent CuNPs as an independent FL signal. This physical separation avoids cross‐interference and enables independent optimization; the FL mode achieved a 10‐fold broader linear range (0.001–200 vs. 0.01–200 ng/mL) and 10‐fold lower LOD (0.28 vs. 2.5 pg/mL) than the EC mode. Each mode can be measured under its own optimal conditions. Li et al. [68] used 3D porous AuNPs/MXene as the platform, with Nile Blue (NB) on the APT terminus as a dual reporter. The 3D MXene architecture provides high surface area and enhanced electron transfer; AuNPs act as EC signal amplifiers and FL quenchers. Upon Hg²⁺ binding, APT conformational change brings NB close to AuNPs, producing EC “turn‐on” and FL “turn‐off” signals. This design gave the lowest LODs (2.69 fM EC, 1.60 fM FL) and widest EC range (10 fM‐0.1 nM), but the proximity‐dependent signal generation requires precise distance control between NB and AuNPs, potentially affecting reproducibility.

TABLE 3.

Comparison of electrochemical‐fluorescence dual‐mode aptasensors.

Studies	Design strategy	Performance metrics (ng/mL)	Practical applicability	Key limitations
Liang et al. [62]	COF‐based dual‐functional probe (MB@AuNPs@COF): COF provides fluorescent scaffold, MB serves as electrochemical reporter; probe captured on electrode via ssDNA‐Apt hybridization	EC: 1.33 × 101, 4.44 × 10−2‐4.44 × 106; FL: 2.22 × 10−2, 4.44 × 10−2‐4.44 × 106	Large surface area and ordered pore structure of COF enable efficient loading of AuNPs and MB, simplifying probe design	Dual signals from the same material constrain independent optimization of each modality; comparable LODs limit the exploitation of fluorescence sensitivity; multiple assembly steps add fabrication complexity
He et al. [8]	Physically separated aptasensor design: electrochemical detection (Fc signal‐on + MB signal‐off, combined signal ΔI = |ΔIFc| + ΔIMB) + HCR‐triggered fluorescent CuNPs (independent solution‐phase detection)	EC: 2.50 × 10−3, 1 × 10−2‐2 × 102; FL: 2.80 × 10−4, 1 × 10−3‐2 × 102	Physical separation avoids cross‐interference and allows independent optimization of each mode; HCR is isothermal and enzyme‐free; FL mode achieves 10‐fold broader linear range and 10‐fold lower LOD than EC mode	Two‐mode operation requires sequential steps, extending assay time; collection of reaction solution for FL detection adds handling steps; CuNP formation is influenced by dsDNA length and reaction conditions
Li et al. [68]	3D porous AuNPs/MXene platform + NB‐labeled aptamer terminus (proximity‐dependent signal modulation): Hg2 + binding induces aptamer conformational change, bringing NB closer to AuNPs cause EC signal‐on + FL signal‐off	EC: 5.40 × 10−7, 2.01 × 10−6‐2.01 × 10−2; FL: 3.21 × 10−7, 1.00 × 10−6‐2.01 × 10−5	3D porous MXene offers large specific surface area; AuNPs serve dual functions as EC signal amplifiers and FL quenchers; complementary validation between the two modes	Signal generation relies on precise distance control between NB and AuNPs, potentially affecting reproducibility; relatively narrow FL linear range; sensitivity may vary with instrumental or experimental conditions affecting proximity

Overall, Liang's single‐probe strategy prioritizes fabrication simplicity; He's separated design emphasizes independent optimization; Li's proximity‐based approach maximizes sensitivity. The optimal choice depends on whether ease of fabrication, independent optimization, or ultra‐high sensitivity is the primary need.

4.3. Electrochemistry‐SERS Mode

SERS relies on localized regions known as “hotspots”, generated through Raman scattering and SPR. These spatially confined areas exhibit extreme electromagnetic field enhancement (EF), such that molecules within hotspots produce significantly stronger Raman signals than those elsewhere. A simple calculation illustrates this: a single molecule in a hotspot with an EF of 10¹⁰ yields a Raman signal equivalent to 10 million molecules with an EF of only 10³ [72]. By irradiating SERS‐active substrates with a laser and analyzing Raman signal variations upon analyte recognition, this technique offers ultra‐high sensitivity and molecular fingerprint specificity [73, 74]. However, reliable SERS detection must overcome signal fluctuations arising from microscopic regional heterogeneity. In contrast, electrochemical signals originate from the entire electrode surface, demonstrating superior stability. Integrating these two modalities thus enhances detection reliability [75].

Employing metal nanoparticle (Au, Ag, Cu)‐loaded substrates has garnered increasing interest in sensing platforms [76]. Zhang's team discovered that introducing calcium ions (Ca²⁺) as aggregating agents in an enhancement system disrupts the surface charge balance of silver nanoparticles (AgNPs), making the particles prone to aggregation. This facilitates further enhancement of the local electric field around the particles, increases electromagnetic effects, and leads to an enhancement of the SERS signal [77]. Based on this condition, Zhang et al. (2022) [76] utilized Ca²⁺ and I⁻ modified silver nanoparticles (Ag@ICNPs) as enhancement substrates to develop a label‐free electrochemical‐SERS dual‐mode aptasensor for detecting residues of malathion in food. As shown in Figure 7, iodide ions remove citrate from the surface of silver nanoparticles [78, 79], allowing nucleic acid molecules to approach the silver nanoparticles without altering their internal structure; calcium ions act as aggregating agents, inducing the formation of hotspots in the silver nanoparticles. The electrochemical detection limit is 1.6 µmol/L. After synthesizing Ag@ICNPs, the substrate surface is further cleaned and enhanced, yielding SERS signals that are not overlapped by impurity signals. This method was applied to detect malathion in apple and bell pepper samples, achieving recovery rates of 89.80%–106.50% and relative standard deviations of 2.51%–6.92%.

FIGURE 7.

Experimental process of specific recognition of malathion by aptame. Reproduced with permission [76]. Copyright 2022, Elsevier Ltd.

Continuing their work, the team developed an electrochemical‐SERS dual‐mode aptasensor integrated with a partial least squares (PLS) model for chlorpyrifos detection in rice and apple samples. Conventional SERS quantification typically relies on univariate models using standard curves, which are prone to interference from measurement conditions and matrix nanomaterials, often failing to achieve a determination coefficient (R²) of 0.99 [81]. To address spectral interference from coexisting pesticides, Zhang et al. (2023) [80] introduced a PLS model, enabling fully selective quantification. As illustrated in Figure 8, 13 standard solutions were designed to establish and validate the calibration model, which was subsequently applied to six real and six spiked samples. In the presence of three pesticide interferents, the method achieved average recoveries of 92.69%–112.55% with relative standard deviations of 3.22%–9.60%, and an electrochemical detection limit of 0.554 µmol/L.

FIGURE 8.

Experimental process of specific recognition of chlorpyrifos by aptame. Reproduced with permission [80]. Copyright 2023, Elsevier Ltd.

AgNP and Cu₂ONP possess adjustable electrooxidation signals near 0.17 V and ‐0.13 V, respectively, along with excellent SERS performance [83, 84]. Upon deposition of a Cu₂O shell onto AgNP (Ag@Cu₂ONP), two independent electrooxidation peaks emerge at these potentials, while the Cu₂O shell provides a plasmonic shielding effect that suppresses EM wave attenuation, resulting in a stronger local EM field and superior SERS activity compared to bare AgNP [85]. MXene nanosheets, offering high specific surface area and conductivity, not only load Ag@Cu₂ONP but also promote their electrochemical oxidation. Moreover, their intrinsic Raman signal at 730 cm⁻¹ serves as an internal reference to calibrate SERS fluctuations. Based on these advantages, Yao et al. [82] developed an electrochemical‐SERS dual‐mode aptasensor for tetrodotoxin (TTX) detection in marine organisms. In this design (Figure 9), Ag@Cu₂ONP labeled with 4‐ATP as Raman reporter was linked via APTs to MXene‐modified electrodes. Ag@Cu₂ONP displayed two strong DPV peaks at ‐0.13 V and 0.17 V, corresponding to Cu⁺ and Ag⁰ oxidation, respectively, alongside strong SERS signals at 1078 cm⁻¹ (4‐ATP) and 730 cm⁻¹ (MXene). Upon TTX addition, preferential APT binding induced Ag@Cu₂ONP detachment from MXene, markedly decreasing both electrooxidation peaks and the 1078 cm⁻¹ SERS intensity, while the 730 cm⁻¹ signal remained stable. Over 100 pg/mL to 10 µg/mL, detection limits of 31.6 pg/mL (electrochemical, I_‐0.13V + I_0.17V) and 38.3 pg/mL (SERS, I₁₀₇₈ / I₇₃₀) were achieved.

FIGURE 9.

Schematic of electroactivity and SERS activity of Ag@Cu₂ONP‐engineered electrochemical/SERS dual‐mode aptasensor for TTX detectio. Reproduced with permission [82]. Copyright 2023, American Chemical Society.

Comparison of three electrochemical‐SERS aptasensors (Table 4) reveals different strategies for addressing SERS variability and quantification accuracy. Zhang et al. (2022) [76] used Ca²⁺ and I⁻ as aggregating/cleaning agents to form hotspots on Ag@ICNPs. This chemical aggregation is simple and low‑cost but suffers from poor reproducibility (RSDs 2.51%–6.92%) and lacks correction for spectral interference from coexisting pesticides, limiting its use in complex matrices. Zhang et al. (2023) [80] added a PLS model for spectral deconvolution to compensate for overlapping pesticide signals without modifying the substrate. This improved recoveries (92.69%–112.55%) over univariate methods, but requires a large training dataset and may not generalize across matrices; the PLS model also adds computational complexity for on‑site use. Yao et al. [82] used core‐shell Ag@Cu₂O NPs with two electrooxidation peaks (‐0.13 V and 0.17 V) and MXene as internal standard for ratiometric SERS. This eliminates external calibration, achieving the lowest LODs (EC 31.6 pg/mL, SERS 38.3 pg/mL) and widest linear range. The combined electrochemical signal (I_‐0.13V + I_0.17V) outperforms single‐peak methods. However, core‐shell synthesis with MXene is more complex than Ag@ICNP aggregation, posing challenges for scale‐up and batch reproducibility.

TABLE 4.

Comparison of electrochemical‐SERS dual‐mode aptasensors.

Studies	Design strategy	Performance metrics (ng/mL)	Practical applicability	Key limitations
Zhang et al. (2022) [76]	Ca2+/I−‐induced hotspot formation on Ag@ICNPs (chemical aggregation)	EC: 5.29 × 102	Simple, cost‐effective, and rapid operation; suitable for preliminary screening	Stochastic aggregation compromises reproducibility (RSD: 2.51%–6.92%); lacks correction for spectral interference from coexisting pesticides; no SERS quantitative linear range reported
Zhang et al. (2023) [80]	Ag@ICNPs + PLS model for spectral deconvolution	EC: 1.94 × 102	Algorithmic compensation improves interference resistance without structural modification; suitable for laboratory analysis with computational support	Requires substantial training dataset; may not generalize across different matrix compositions or instrument conditions; PLS adds computational complexity for real‐time on‐site use; no SERS quantitative linear range reported
Yao et al. [82]	Ag@Cu2ONP core‐shell nanostructure (dual electrooxidation peaks at ‐0.13 V and 0.17 V) + MXene nanosheets as IS (730 cm−1) for ratiometric SERS	EC: 3.16 × 10−2, 0.1‐1 × 104; SERS: 3.83 × 10−2, 0.1‐1 × 104	Lowest LOD and widest linear range among the three; ratiometric design eliminates external calibration; dual‐peak EC signal outperforms single‐peak methods	Core‐shell synthesis and MXene assembly are more complex; potential challenges in large‐scale manufacturing and batch‐to‐batch reproducibility

The three designs show a progression: from simple aggregation (Zhang 2022), to algorithmic compensation (Zhang 2023), to integrated structural/ratiometric design (Yao). The trade‐off is among simplicity, robustness, and sensitivity: Yao excels in sensitivity/interference resistance but requires complex synthesis; Zhang's PLS improves accuracy without structural change but depends on data; Ag@ICNP offers rapid low‐cost screening at the expense of reproducibility and matrix compatibility.

4.4. Electrochemical ‐ SPR Mode

SPR is highly sensitive to interactions on metal films, making it a powerful label‐free technique for investigating surface binding events [86]. SPR sensors enable sensitive, robust, and straightforward detection, and are well‐suited for multiplexed on‐chip integration [87]. Gold and silver are the most commonly employed SPR substrates, as they are readily functionalized with biological or biomimetic recognition elements such as APTs to improve sensor selectivity [86].

Adrian Blidar et al. [86] developed an EC‐SPR dual‐mode aptasensor for ampicillin residues in food, recording real‑time refractive index changes. The system includes a reference channel (exposed only to supporting electrolyte) for baseline correction, so that signal changes are attributed to analyte binding or surface modification. For functionalization, APT in TRIS buffer was passed over the sample channel while the reference received buffer. Multi‐pulse amperometry enhanced APT immobilization, yielding a sevenfold SPR signal increase over passive incubation. After MCH blocking, the sensor gave a detection limit of 1 µmol/L over 2.5–1000 µmol/L. QCM analysis confirmed an APT‐AMP efficiency of 0.85, good selectivity against other penicillins and common drugs, and recoveries of 103%–105% in spiked river water.

However, the SPR signal intensity was modest, which the authors attributed to the use of a bare gold chip (rather than a 3D hydrogel for higher APT loading), the intrinsic limitation of SPR for small molecules (MW 349.4), and moderate instrument sensitivity [87]. Hydrogels would provide higher loading capacity and amplify SPR, whereas SPR is generally less sensitive to small molecules than to macromolecules. Despite these drawbacks, this work is the first SPR aptasensor for AMP and shows that multipulse amperometry can improve immobilization kinetics [86]. The successful application to river water confirms its environmental potential, though sensor improvements such as hydrogel matrices or nanoparticle amplification are necessary to achieve detection limits comparable to EC or fluorescence methods.

4.5. Comparative Summary of Dual‐Mode Techniques

To support the selection of suitable dual‐mode sensing strategies for targeted food safety applications, this work presents a systematic comparison of the five electrochemical‐optical modalities outlined above (Table 5). This evaluation covers critical practical parameters beyond basic analytical performance, including associated cost, operational complexity, and system integration challenges. As the comparison shows, no single modality delivers universally superior performance across all cases. Instead, the optimal selection is scenario‐dependent, requiring a balanced assessment of sensitivity requirements, sample matrix complexity, accessible instrumentation, and the intended deployment setting, such as centralized laboratory testing versus field‐based on‐site screening.

TABLE 5.

Comparison of electrochemical‐optical dual‐mode aptasensing modalities for food contaminant detection.

Modalities	Key advantages	Main limitations	Typical LOD	Cost	Operational complexity	Integration challenges	Best suited for
EC‐Colorimetric	Visual readout; low cost; rapid; robust against impurities	Subjective; low resolution; high LOD without amplification	pg/mL – ng/mL (fg/mL with amplification)	Very Low	Low	Smartphone color calibration; ambient light & batch‐to‐batch variation	On‐site rapid screening; resource‐limited settings; yes/no testing
EC‐Fluorescence	High sensitivity; broad dynamic range; well‐established; multiplexing options	Photobleaching; background autofluorescence; requires light source	pg/mL – fg/mL	Moderate	Moderate	Optical alignment; autofluorescence suppression; labeling requirement	Laboratory quantitative analysis; multi‐target detection
EC‐SERS	Molecular fingerprint; ultra‐high sensitivity; multiplexing; water compatible	Hotspot heterogeneity; substrate uniformity issues; complex data analysis	pg/mL – fg/mL	High	High	Substrate reproducibility; spectral deconvolution; instrument miniaturization	Complex matrix analysis; confirmatory identification
EC‐SPR	Real‐time label‐free; excellent surface sensitivity; kinetic data; commercial instruments available	Low sensitivity for small molecules (<500 Da); requires gold chip; temperature‐sensitive; limited throughput	ng/mL – µg/mL (for small molecules); pg/mL (for macromolecules)	High	Moderate	Chip functionalization; temperature/RI control; cross‐contamination	Binding kinetics; real‐time interaction studies; macromolecule detection
EC‐PEC/ECL	Ultra‐low background; exceptional sensitivity; inherent amplification; independent signals	Requires light source (PEC) or co‐reactant (ECL); complex synthesis; photo‐degradation	fg/mL – pg/mL	High	High	Photocathode stability; oxygen interference; electrode passivation	Ultra‐trace analysis; high‐sensitivity lab detection; regulatory compliance

Table 5 showed EC‐colorimetric sensors are the cheapest and simplest to operate, making them suitable for field screening in low‐resource settings, though constrained by subjective visual readout and modest LODs; with nucleic acid amplification, fg/mL detection becomes feasible. EC‐fluorescence and EC‐SERS offer higher sensitivity and multiplexing, with SERS adding molecular fingerprinting for confirmatory analysis, particularly useful for distinguishing structurally similar mycotoxins or pesticide isomers, but both require advanced instrumentation and substrate fabrication, and SERS additionally suffers from hotspot reproducibility. EC‐SPR allows real‐time, label‐free monitoring and provides kinetic data beyond endpoint assays, yet its inherent insensitivity to small targets (e.g., ampicillin, 349.4 Da) restricts it largely to macromolecule detection or binding mechanism studies. EC‐PEC and ECL achieve the highest sensitivities (fg/mL range) via dual‐signal amplification and ultra‐low background, yet they depend on complex nanomaterial synthesis and external excitation or co‐reactants, which confines them to well‐equipped laboratories. Choice ultimately depends on the application: colorimetric for field screening; fluorescence for routine lab quantification; SERS for confirmatory analysis in complex matrices; SPR for binding mechanism studies; and PEC/ECL for ultratrace regulatory compliance.

4.6. Comparative Analysis of Sensor Designs and Nanomaterials

Beyond within modality comparisons, cross‐modal comparison (Table 6) guides material and design choices. Among nanozyme‐based colorimetric/electrochemical platforms, PtNPs/Pd‐Cu₂O hollow octahedra [51] achieve 0.76 pg/mL (EC) and 0.49 pg/mL (colorimetric), outperforming FePOs@CeO₂ [52] by about three orders of magnitude owing to higher surface area and catalytic activity, though with more complex synthesis. For fluorescence, the HCR‐templated CuNP design of He et al. [8] gives an LOD of 0.28 pg/mL for AFB1, substantially better than the COF‐based approach [62] (0.05 nM, ∼16.7 pg/mL), due to the superior signal‐to‐noise ratio from HCR amplification. In SERS, the Ag@Cu₂O/MXene ratiometric design [82] delivers 38.3 pg/mL for TTX, surpassing the Ag@ICNP aggregation strategy [76] by using core‐shell structures and internal calibration to overcome hotspot variability. PEC platforms [43] show the lowest LOD (9.3 fg/mL for AFB1) from photoelectrochemical amplification, but require the most intricate nanomaterial synthesis. As for materials, noble metal nanoparticles (AuNPs, AgNPs) combine favorable conductivity, biocompatibility, and ease of functionalization, whereas MOFs/COFs offer higher loading capacity and structural tunability at the cost of more demanding preparation. Overall, no single material or design is universally superior; the optimal choice depends on analyte, sensitivity, matrix, and instrumentation, demanding a balance between performance and practical constraints.

TABLE 6.

Comparison of representative dual‐mode aptasensor designs and nanomaterials for food contaminant detection.

Modalities	Representative design	Nanomaterial	Target	Best LOD (EC/Optical) (ng/mL)	Key advantage	Main limitation
EC‐Colorimetric	Yu et al. [51]	PtNPs/Pd‐Cu2O	Aflatoxin B1	7.60 × 10−4 / 4.90 × 10−4	Highest sensitivity among nanozymes; CHA/HCR dual amplification	Complex synthesis; magnetic separation steps
EC‐Colorimetric	Duan et al. [52]	FePOs@CeO2	Amoxicillin	7.24 × 10−5 / 8.28 × 102	Single‐material probe simplifies fabrication	Large LOD disparity between modes (∼7 orders)
EC‐Colorimetric	Li et al. [42]	Fe‐MIL‐88 MOF	Ochratoxin a	2.20 × 10−7 / 2.50 × 10−7	Smartphone‐integrated POCT; RCA amplification	RGB sensitivity lower than UV‐Vis
EC‐Fluorescence	Liang et al. [62]	MB@AuNPs@COF	Tetracycline	1.33 × 101 / 2.22 × 101	High loading capacity; ordered pore structure	Dual signals from same material constrain optimization
EC‐Fluorescence	He et al. [8]	CuNPs	Aflatoxin B1	2.50 × 10−3 / 2.80 × 10−4	Physical separation enables independent optimization	Two‐mode sequential operation extends assay time
EC‐Fluorescence	Li et al. [68]	AuNPs/MXene	Mercury	5.40 × 10−7 / 3.21 × 10−7	Proximity‐dependent dual signal modulation	Precise distance control required for reproducibility
EC‐SERS	Zhang et al. (2022) [76]	Ag@ICNPs	Malathion	5.29 × 102 / —	Simple, cost‐effective, rapid operation	Stochastic aggregation compromises reproducibility
EC‐SERS	Zhang et al. (2023) [80]	Ag@ICNPs	Chlorpyrifos	1.94 × 102 / —	Algorithmic compensation for spectral interference	Requires extensive training dataset
EC‐SERS	Yao et al. [82]	Ag@Cu2O/MXene	Tetrodotoxin	3.16 × 10−2 / 3.83 × 10−2	Ratiometric SERS; dual‐peak EC; internal standard	Complex core‐shell synthesis
EC‐PEC	Zhang et al. [43]	AuNPs/PCZIF‐8‐ZnO	aflatoxin B1	3.67 × 10−5 / 9.30 × 10−6	Lowest LOD among all modalities; widest linear range	Complex carbonization + in‐situ reduction synthesis

5. Other Sensors

5.1. Electrochemical—Electrochemiluminescence Mode

Electrochemiluminescence (ECL) is a powerful technique integrating the advantages of electrochemistry with the sensitivity of chemiluminescence (CL) [88]. It involves CL emission triggered during electrochemical redox reactions between reagents immobilized on the working electrode and analytes in the electrolyte, resulting in photon release from an excited state [89]. With features such as operational simplicity, low sample consumption, and high sensitivity, ECL serves as an excellent platform for biosensing applications [90].

Ru(bpy)₃ ²⁺ is a well‐established ECL luminophore often encapsulated within bio‐MOFs (Ru‐MOF) for ECL sensing applications [91]. Cu offers high specific surface area and electrocatalytic activity, facilitating redox reactions, while AuNPs contribute excellent biocompatibility and SPR effects. The resulting Cu@AuNP bimetallic nanostructures exhibit synergistic catalytic effects, effectively amplifying ECL signals in the Ru(bpy)₃ ²⁺/TPrA system [92, 93, 94]. Ferrocenecarboxylic acid (Fca), a conventional electroactive probe, quenches ECL emission. Leveraging these properties, Jiang et al. [95] developed a novel electrochemical‐ECL dual‐mode aptasensor for detecting alternariol (AOH), a mycotoxin posing food safety risks. The detection principle is illustrated in Figure 10. On the electrode, Fca‐DNA₂ quenches ECL via electron transfer and enhances DPV responses through its redox activity. Upon AOH introduction, competitive binding with DNA₁, for which it has higher affinity, releases Fca‐DNA₂ from the electrode. This reduces surface‐bound Fca, thereby decreasing DPV signals while restoring ECL intensity. Within 0.1 pg/mL to 100 ng/mL, detection limits of 0.014 pg/mL (ECL) and 0.083 pg/mL (electrochemical) were achieved.

FIGURE 10.

Schematic diagram of an electrochemical‐ECL dual‐mode aptasensor for AOH detection. Reproduced with permission [95]. Copyright 2023, Elsevier Ltd.

5.2. Electrochemical‐Photoelectrochemical Mode

Photoelectrochemical (PEC) detection, a subset of electrochemical methods, features independent excitation and detection signals, resulting in low background noise and high sensitivity [96]. When integrated with electrochemical modes, the resulting dual‐mode sensor has attracted growing interest due to its operational simplicity, high sensitivity, and cost‐effectiveness [97]. Moreover, both PEC and EC measurements can be conducted using a single electrochemical workstation, offering considerable convenience [98].

The development of sensing substrates with high electroactivity and photoactivity is essential for constructing high‐performance EC/PEC dual‐mode aptasensors [43]. Zeolitic imidazolate frameworks (ZIFs) offer advantages such as structural tunability, facile synthesis, and high specific surface area [99, 100]. Zhang et al. [43] employed ZIF‐8 as a precursor to synthesize porous carbon ZnO (PC_ZIF‐8‐ZnO), in which the PC_ZIF‐8 framework acts as a sensitizer, narrowing the ZnO bandgap and enhancing light absorption, thereby promoting photogenerated charge separation. Conductive AuNPs were subsequently anchored onto PC_ZIF‐8‐ZnO (AuNPs/PC_ZIF‐8‐ZnO) to accelerate electron transfer and improve photoelectric conversion efficiency. Using this composite as the sensing platform, they developed an EC/PEC dual‐mode aptasensor for aflatoxin B1(AFB1) detection (Figure 11). MB‐labeled ssDNA was anchored onto AuNPs/PC_ZIF‐8‐ZnO via Au─S bonds and hybridized with ferrocene (Fc)‐labeled APT to form dsDNA, positioning MB away from and Fc close to the interface. This configuration yielded strong Fc and weak MB oxidation peaks in EC mode, along with suppressed photocurrent due to Fc inhibition. In the presence of AFB1, structural switching of ssDNA altered the distances of MB and Fc from the substrate, modulating both EC and PEC signals. The sensor achieved detection limits of 36.7 fg/mL (EC, 0.1 pg/mL‐100 ng/mL) and 9.3 fg/mL (PEC, 0.02 pg/mL‐1000 ng/mL).

FIGURE 11.

Construction and Analysis Schematic of EC/PEC Dual‐Mode Adapter. Reproduced with permission [43]. Copyright 2024, Elsevier Ltd.

A comparison of three dual‐mode AFB1 aptasensors (Table 7) reveals distinct design philosophies and performance trade offs among electrochemical, fluorescence, colorimetric, and photoelectrochemical readouts. Yu et al. [51] used a colorimetric EC platform with PtNPs/Pd‐Cu₂O hollow octahedral nanozyme as bifunctional probe, combined with CHA/HCR amplification and magnetic separation. This spatially isolates the two modes, minimizing crosstalk, but magnetic separation adds washing steps and the single nanozyme limits independent optimization, as seen in the LOD disparity (0.76 pg/mL EC vs. 0.49 pg/mL colorimetric) and narrower colorimetric range (0.001‐500 ng/mL EC vs. 0.001‐1000 ng/mL). He et al. [8] adopted a physically separated EC‐fluorescence strategy: the EC mode gives a dual‐signal “on‐off” response (Fc/MB) with combined ΔI, while released cDNA triggers HCR to generate dsDNA templates for fluorescent CuNPs. This allows independent optimization and avoids interference‐the fluorescence mode achieved 10‐fold broader linear range (0.001‐200 vs. 0.01‐200 ng/mL) and 10‐fold lower LOD (0.28 vs. 2.5 pg/mL) than EC. However, dual mode‐operation extends assay time, and CuNP formation depends on dsDNA length and conditions, affecting reproducibility. Zhang et al. [43] introduced a distance modulation strategy with Au NPs/PC_ZIF‐8‐ZnO as bifunctional substrate, serving both as electroactive interface for ratiometric EC and photoactive material for “off‐on” PEC. The PEC mode exploits inherent high sensitivity, achieving the lowest LODs (36.7 fg/mL EC, 9.3 fg/mL PEC) and widest linear ranges (0.1 pg/mL‐100 ng/mL EC, 0.02 pg/mL‐1000 ng/mL PEC). The PEC mode extends detection limits by about two orders over the EC mode of the same platform, highlighting its superior sensitivity. However, synthesis of Au NPs/PC_ZIF‐8‐ZnO involves carbonization and in‐situ reduction, more complex than simple nanozymes or colloids.

TABLE 7.

Comparison of dual‐mode aptasensors for AFB1 detection.

Study	Sensor type	Design strategy	Performance metrics (ng/mL)	Practical applicability	Key limitations
Yu et al. [51]	EC/Colorimetric	PtNPs/Pd‐Cu2O hollow octahedral nanozyme + magnetic separation + CHA/HCR dual amplification	EC: 7.60 × 10−4, 0.001‐1000; Col: 4.90 × 10−4, 0.001‐500	Simple, cost‐effective, rapid; suitable for preliminary screening	Magnetic separation adds operational complexity; single nanozyme constrains optimization; large LOD disparity between modes
He et al. [8]	EC/Fluorescence	Physically separated design: EC dual‐signal (Fc signal‐on + MB signal‐off)	EC: 2.50 × 10−3, 0.01‐200; FL: 2.80 × 10−4, 0.001‐200	Algorithmic compensation improves interference resistance; suitable for lab analysis with computational support	Two‐mode sequential operation extends assay time; CuNP formation influenced by dsDNA length and reaction conditions; additional handling for FL detection
Zhang et al. [43]	EC/PEC	Au NPs/PCZIF‐8‐ZnO sensing substrate + distance‐modulation strategy + ratiometric EC + “off‐on” PEC	EC: 3.67 × 10−5, 0.0001‐100; PEC: 9.30 × 10−6, 0.00002‐1000	Lowest LOD and widest linear range; ratiometric design eliminates external calibration; dual‐peak EC outperforms single‐peak methods	Complex material synthesis (carbonization + in‐situ reduction); PEC requires light source and optical alignment; paper‐based chip integration may affect reproducibility

In summary, Yu's design prioritizes signal fidelity through physical isolation; He's emphasizes independent optimization and HCR amplification; Zhang's leverages PEC to maximize sensitivity and range. The choice depends on whether the priority is fabrication simplicity (Yu), independent validation with amplified readout (He), or ultrahigh sensitivity and broadest range (Zhang) ‐no single design universally excels across all metrics.

Table 8 summarized the analytical performance and practical applications of the dual‐mode aptasensors discussed in this work for detecting food contaminants. Note: All LOD and linear range values have been converted to ng/mL based on the molecular weights of the respective targets (AFB1: 312.3 g/mol; amoxicillin: 365.4 g/mol; OTA: 403.8 g/mol; TET: 444.4 g/mol; TTX: 319.3 g/mol; alternariol: 258.2 g/mol; malathion: 330.4 g/mol; chlorpyrifos: 350.6 g/mol; ampicillin: 349.4 g/mol; mercury: 200.59 g/mol). “—” indicates the value was not reported.

TABLE 8.

Review of Dual‐mode Aptasensors for Detecting Food Contaminants.

Sensor type	Main materials	Target	Linear range (ng/mL)	LOD (ng/mL)	References
EC‐COL	PtNPs/Pd‐Cu2O	Aflatoxin B1	EC: 0.001‐1000; COL: 0.001‐500	EC: 7.60 × 10−4; COL: 4.90 × 10−4	[51]
EC‐COL	FePOs@CeO2	Amoxicillin	EC: 0.1‐5 × 104; COL: 1 × 103‐1 × 105	EC: 7.24 × 10−2; COL: 8.28 × 102	[52]
EC‐COL/RGB	Fe‐MIL‐88 MOF	Ochratoxin a	EC: 1 × 10−6‐2.5 × 102; COL: 1 × 10−6‐1 × 102; RGB: 1 × 10−6‐1 × 102	EC: 2.20 × 10−7; COL: 2.50 × 10−7; RGB: 4.00 × 10−7	[42]
EC‐FL	MB@AuNPs@COF	Tetracycline	EC: 4.44 × 10−2‐4.44 × 106; FL: 4.44 × 10−2‐4.44 × 106	EC: 1.33 × 101; FL: 2.22 × 10−2	[62]
EC‐FL	CuNPs	Aflatoxin B1	EC: 1 × 10−2‐2 × 102; FL: 1 × 10−3‐2 × 102	EC: 2.50 × 10−3; FL: 2.80 × 10−4	[8]
EC‐FL	AuNPs/MXene	Mercury	EC: 2.01 × 10−6‐2.01 × 10−2; FL: 1.00 × 10−6‐2.01 × 10−5	EC: 5.40 × 10−7; FL: 3.21 × 10−7	[68]
EC‐SERS	Ag@ICNPs	Malathion	—	EC: 5.29 × 102	[76]
EC‐SERS	Ag@ICNPs	Chlorpyrifos	—	EC: 1.94 × 102	[80]
EC‐SERS	Ag@Cu2O/MXene	Tetrodotoxin	EC: 0.1‐1 × 104; SERS: 0.1‐1 × 104	EC: 3.16 × 10−2; SERS: 3.83 × 10−2	[82]
EC‐SPR	Gold chip	Ampicillin	EC/SPR: 8.74 × 102‐3.49 × 105	SPR: 3.49 × 102	[86]
EC‐ECL	Fca‐DNA2	Streptococcal toxin	1.00 × 10−4‐1.00 × 102	EC: 8.30 × 10−5; ECL: 1.40 × 10−5	[95]
EC‐PEC	AuNPs/PCZIF‐8‐ZnO	aflatoxin B1	EC: 1.00 × 10−4‐1.00 × 102; PEC: 2.00 × 10−5‐1.00 × 103	EC: 3.67 × 10−5; PEC: 9.30 × 10−6	[43]

6. Conclusions

In recent years, electrochemical‐optical dual‐mode aptasensors have attracted growing interest for food contaminant detection, owing to their complementary signal readout mechanisms. By combining the high sensitivity of electrochemical methods with the broad dynamic range and robustness of optical techniques‐such as colorimetry, fluorescence, and SERS‐these platforms overcome key limitations of single‐mode systems and significantly improve detection reliability. APTs serve as specific recognition elements, offering advantages including low cost, facile modification, and high affinity. When integrated with functional nanomaterials (e.g., AuNPs, MOFs, MXene), they enable ultrasensitive quantification of diverse hazards including aflatoxins, organophosphorus pesticides, and heavy metal ions. Representative designs include electrochemical‐colorimetric sensors based on nanozyme catalysis, electrochemical‐fluorescence platforms enhanced by DNA amplification, and electrochemical‐SERS systems leveraging electromagnetic hotspot effects. Despite these advances, several challenges remain.

7. Challenges and Future Perspectives

7.1. Nanomaterial Stability and Reproducibility

Performance of dual‐mode aptasensors depends critically on physicochemical properties of nanomaterials, but practical application is constrained by stability and reproducibility. Noble metal nanoparticles (Au, Ag) tend to aggregate during synthesis, storage, or sensing, causing batch‐to‐batch variability [101]. MOFs have high surface area and porosity but limited hydrolytic stability in aqueous media; carboxylate‐based ligands degrade more readily than nitrogen‐containing ones [102]. Nanozyme activity is also sensitive to pH, temperature, and interferents, leading to signal fluctuations.

Addressing these issues requires a multi‐pronged approach. Core‐shell architectures like Au@COF or MXene/MOF heterojunctions can integrate catalytic, conductive, and optical functions while protecting the core. In‐situ growth of COFs and MOFs on electrodes improves adhesion and integrity. For storage, freeze‐drying or encapsulation in protective matrices should be explored. Continuous‐flow microfluidic synthesis enables precise control over size, morphology, and composition, and scalable production with high reproducibility [103]. These approaches promise to enhance robustness and reliability.

7.2. Aptamer Development and Multiplexing Capability

Aptasensor functionality is constrained by current screening and engineering methods. Traditional SELEX requires 10‐15 rounds over weeks and is often limited to well‐binding targets. Worse, most APTs are single‐analyte, restricting multiplexing needed for food safety where multiple contaminants coexist.

High‐throughput platforms offer improvements. Microfluidic SELEX miniaturizes and automates selection, tightening control over kinetics and partitioning while reducing time and reagent use [104]; paired with high‐throughput sequencing, it enables parallel screening of multiple targets. Computational approaches (docking, machine learning) accelerate identification of high‐affinity sequences and rational truncation. Multivalent APT constructs and DNA logic gates allow programmable simultaneous detection. These advances will boost multiplexing for comprehensive food contaminant screening.

For dual‐mode electrochemical‐optical aptasensors, multiplexing can be achieved with sensor arrays having multiple working electrodes, each carrying a distinct APT and sharing counter/reference electrodes for compactness. El‐Akaad et al. used reduced graphene oxide with eight working electrodes to detect three neonicotinoids [105]. Alternatively, inherently multiplexing optical modes (SERS with distinct Raman reporters, or fluorescence with resolvable wavelengths) can be combined with electrochemistry for multi‐target detection on a single platform. Wang et al. demonstrated this with a dual ratiometric electrochemical aptasensor for malathion and omethoate using hairpin and linear DNA [106]. Although most studies reviewed here are single‐analyte proof of concepts, the principles and materials are extendable to multi‐target assays. Future work should validate these multiplexed systems with real samples containing coexisting contaminants, reflecting actual food safety conditions.

7.3. On‐Site Deployment and Instrumentation

Despite excellent lab performance, electrochemical‐optical dual‐mode aptasensors are hard to deploy on‐site. Most platforms still depend on bench top workstations, sophisticated optical instruments, and skilled operators, which limits their use for real‐time monitoring across the food supply chain from production to retail.

Portable, user‐friendly devices are therefore key to field translation. Smartphone‑integrated biosensing is especially promising, leveraging ubiquitous phones for data acquisition and transmission [107]. Recent work shows USB‐powered potentiostats for electrochemical detection, and smartphone cameras for colorimetric or SERS readouts. Flexible and wearable platforms, from printed electronics, enable noninvasive, continuous monitoring. Microfluidic chips can integrate sample prep, detection, and readout into a single disposable device, simplifying operation and minimizing user steps. Miniaturized Raman spectrometers and electrochemical workstations, along with mass‑production cost cuts, will further boost accessibility for point‐of‐need testing.

7.4. Emerging Opportunities

Machine learning, particularly deep learning, can refine multi‐modal signal analysis for SERS and electrochemical data [108]. AI‐assisted data fusion can deconvolve overlapping peaks, self‐calibrate instrument drift, and quantify analytes in complex matrices where univariate models fail. As data volumes grow, convolutional neural networks will become valuable for extracting subtle features to distinguish targets from interferents [13]. Integration with IoT could establish real‐time surveillance networks across the food supply chain, providing early warnings and shifting from reactive to proactive management [107]. Multifunctional platforms that combine detection with remediation, such as photocatalytic degradation, offer integrated solutions. Advances in flexible, biodegradable, and energy harvesting technologies may enable autonomous, self‐powered sensors for remote or resource‐limited settings. Moving from single‐target proof of concept to practical multiplexed surveillance requires APT arrays and spatially resolved architectures for simultaneous quantification of multiple contaminants in a single assay. Overall, these sensors hold promise for both research and deployment; interdisciplinary advances in materials, biology, electronics, and data science can overcome current barriers and establish them as core tools for global food safety monitoring.

Author Contribution

Yulin Meng: conceptualization, literature search, study selection, methodology, writing – original draft, and reference management. Chao Han: data extraction and discussion. Haoyu Zhai: writing – original draft and data curation. Xueli Zhang: data extraction and discussion. Haibin Liu: writing – literature review, and conclusion drafting. Hongshuo Chen: literature search, study selection, data extraction, validation, formal analysis, and data curation.

Conflicts of Interest

The authors declare no conflicts of interest.

Biographies

Yulin Meng was born in 2002 in Hebei, China, and is currently a master's student at the School of Electrical Engineering, North China University of Science and Technology. He is interested in nanomaterials and electro‐ chemistry. This scholar's current research focuses on the construction of biosensors.

Chao Han was born in 1984 in Handan. He earned his B.E. at Hebei Normal University in 2007. He earned his Ph.D. in 2014 from Zhengzhou University. He is currently an associate professor at North China University of Science and Technology, working in the field of electrochemistry.

Haoyu Zhai was born in 2005 in Hebei, China, and is currently an undergraduate student at the School of Electrical Engineering, North China University of Science and Technology. His research interests include nanomaterials and electrochemistry, and he is currently involved in the research on the construction of biosensors.

Xueli Zhang was born in 1983. She earned her Bachelor of Arts degree from Beihang University (Beijing University of Aeronautics and Astronautics) in 2007 and her Ph.D. from Eternal University, Philippines, in 2023. She is currently an associate professor at North China University of Science and Technology, specializing in research on data statistics.

Haibin Liu was born in 1987. She earned her B.E. at Heilongjiang Bayi Agricultural University in 2013. She earned her Ph.D. in 2018 from Tianjin University of Science and Technology. She is currently an associate professor at North China University of Science and Technology, working in the field of Rapid detection of pathogenic bacteria.

Hongshuo Chen was born in 1981 in Xingtai. He earned his B.E. at Hebei University of Science and Technology in 2005. He earned his Ph.D. in 2020 from Shanxi Agricultural University. He is currently an associate professor at North China University of Science and Technology, working in the field of nanomaterial‐based biosensors.

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.