A UV-vis-fluorescence-smartphone-assisted hydrogel “three-in-one” platform based on light-responsive carbon dot nanozyme for multimodal glyphosate detection

A UV-vis-fluorescence-smartphone-assisted hydrogel “three-in-one” platform based on light-responsive carbon dot nanozyme for multimodal glyphosate detection | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A UV-vis-fluorescence-smartphone-assisted hydrogel “three-in-one” platform based on light-responsive carbon dot nanozyme for multimodal glyphosate detection Wanqi Yang, Haodong Yang, Yaxin Ma, Ao Hou, Xiangyu Yang, Pengjuan Ni, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8637701/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Apr, 2026 Read the published version in Microchimica Acta → Version 1 posted 10 You are reading this latest preprint version Abstract The establishment of a fast and precise method for glyphosate detection holds critical importance in ensuring food safety. Herein, a multimodal sensing platform that integrated UV-vis, fluorescence and smartphone-assisted portable hydrogel kit was applied to detect glyphosate relying on the light-responsive oxidase-mimicking activity and intrinsic fluorescence of carbon dots (C-dots). C-dots enable the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB), resulting in blue-colored oxidized TMB (oxTMB) along with enhanced absorbance at 652 nm. Simultaneously, the inner filter effect between oxTMB and C-dots induces the fluorescence quenching of C-dots. However, the introduction of copper ions can capture photogenerated electrons, thereby inhibiting the oxidase-mimicking catalytic activity of C-dots, leading to a decrease in absorbance and the restoration of fluorescence. Once glyphosate is present in the system, it can coordinate with copper ions to restore the catalytic activity of C-dots, thereby causing an increase in absorbance and a simultaneous decrease in fluorescence. Consequently, quantification detection of glyphosate can be realized via UV-vis and fluorescence modes. More importantly, in light of the changes in solution color, a smartphone-assisted portable hydrogel kit was also developed for glyphosate detection. Therefore, a UV-vis-fluorescence-smartphone-assisted hydrogel “three-in-one” platform was established for glyphosate analysis with corresponding limits of detection as low as 0.31, 0.12 and 5.07 µg/mL. This platform can achieve glyphosate detection within just one minute. Moreover, compared with single-mode detection platforms, this multi-mode detection platform ensures greater accuracy, thus holding broader application prospects. Carbon dots Nanozyme Colorimetry Fluorescence Glyphosate Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Glyphosate (N-(phosphoxymethyl) glycine), a broad-spectrum organophosphorus herbicide, is extensively applied in agricultural production due to its high efficiency and low cost. However, the inappropriate application of glyphosate has given rise to a significant augmentation of its residues in agricultural crops, subsequently presenting a danger to human health [ 1 ]. Consequently, it is of substantial importance to set up a rapid, sensitive, accurate, and convenient method for detecting glyphosate. Up to now, high performance liquid chromatography-mass spectrometry [ 2 ], ion chromatography [ 3 ], enzyme-linked immunosorbent assay [ 4 ] and capillary electrophoresis [ 5 ] have been used for glyphosate detection. Although these techniques exhibit relatively high sensitivity and accuracy, they suffer from drawbacks such as complicated and time-consuming sample pretreatment, reliance on large-scale instruments, high cost and poor portability, which limit their practical applications. Presently, newly designed colorimetric or fluorescent sensors have been ascertained to be a promising alternative for glyphosate determination, given their inherent simplicity, low cost and rapid response. Among them, a variety of analytical strategies based on the enzyme-inhibition mechanism have been successfully established for glyphosate detection [ 6 – 8 ]. However, the instability of enzyme may affect the sensitivity and accuracy of these methods. Consequently, the development of enzyme-free optical sensors for glyphosate detection is highly desirable. Fluorescent carbon dots (C-dots) have received widespread interests in the field of fluorescent assays by virtue of their unique optical properties, cost-effectiveness, low toxicity, enhanced stability and straightforward synthesis [ 9 – 11 ]. As a result, a multitude of enzyme-free fluorescent assays leveraging C-dots for glyphosate detection have been developed [ 12 – 14 ]. However, the single fluorescent assay is susceptible to the disturbances of environmental factors, thus leading to inaccurate readings. To address this challenge, significant advancements have been achieved in colorimetric and fluorescent dual-channel assays by leveraging the peroxidase-mimicking activity of C-dots and integrating their inherent fluorescence properties [ 15 , 16 ]. Though these dual-channel assays integrate the merits of colorimetry and fluorescence, thy are hindered by certain limitations. One key issue is that the colorimetric mode relying on the peroxidase-like activity of C-dots depends on unstable hydrogen peroxide to drive the oxidation 3,3',5,5'-tetramethylbenzidine (TMB) and this catalytic reaction is not easily subject to precise control, which may potentially compromise the accuracy of the assay. Another critical drawback is that neither of these strategies is suitable for one-site detection due to their dependence on laboratory equipment. The development of light-responsive C-dots oxidase mimetics is an effective approach to address the above issue, as they are capable of catalyzing TMB oxidation without the involvement of hydrogen peroxide [ 17 – 19 ]. Moreover, the reaction can be precisely regulated by switching the light source on and off, which in turn significantly enhances the reliability of the detection method. On the basis of the light-driven oxidase-mimicking activity of C-dots, colorimetric detection of antioxidant capacity [ 20 , 21 ], acid phosphatase [ 22 ], acetaldehyde [ 23 ] and metal ions [ 24 ] have been fulfilled. However, light-responsive C-dots oxidase mimetics have not been utilized for glyphosate detection. Recently, smartphone-based detection platform integrated with optical sensors has achieved striking advancements in the point-of-care testing approaches for diverse analytes [ 25 – 29 ]. It eliminates the need for laboratory instruments, making it ideal for rapid on-site detection. Considering the above discussions, the light-responsive C-dots oxidase mimetic-mediated tri-mode platform was established for glyphosate detection. When exposed to visible light, C-dots prompted the oxidation of colorless TMB, generating blue-colored oxidized TMB (oxTMB) with augmented absorbance at 652 nm. Meanwhile, the generated oxTMB causes fluorescence quenching of the C-dots on account of the inner filter effect (IFE). The introduction of copper ions can capture the photogenerated electrons, thereby inhibiting the catalytic activity of C-dots. Consequently, it is manifested as a decline in absorbance at 652 nm and the fluorescence recovery of C-dots. Once glyphosate is added, it will coordinate with copper ions, thereby leading to a rise in absorbance and a reduction in the fluorescence of C-dots. As a result, quantitative determination of glyphosate can be realized via UV-vis and fluorescence modes. More significantly, by leveraging the color changes of the solution, a portable hydrogel kit with the assistance of a smartphone has been developed for the sensing of glyphosate. This tri-mode detection platform using C-dots nanozyme enhances detection accuracy, providing new perspectives for glyphosate determination and widening the application scopes of photo-responsive nanozymes. Experimental Synthesis of C-dots C-dots were successfully prepared employing tartaric acid and 3-aminophenol as precursors [ 18 ]. A total mass of 6 g of these two materials (molar ratio of 1:1) was dissolved in 30 mL of ultrapure water. Subsequently, it was transferred to a 100 mL of Teflon-lined stainless steel autoclave and subjected to heating at 160 ℃ for 12 h. Once cooled to ambient temperature, the solution was filtered through a 0.22 µm microporous filter and further purified by dialysis using 1000 Da cellulose dialysis bags. The resulting solution was stored in a refrigerator for subsequent use. Detection of glyphosate by UV-vis and fluorescence mode C-dots (100 µL), CuCl 2 (10 µL, 4 mM), varying concentrations of glyphosate (50 µL) and TMB (100 µL, 5 mM) were sequentially added into 740 µL of HAc-NaAc buffer (0.1 M, pH 4.0). After mixing evenly, the obtained solution was exposed to a Xe lamp (λ ≥ 420 nm) for 1 min. Then, the corresponding UV-vis absorption spectra and the fluorescence emission spectra were recorded. Detection of glyphosate by the smartphone-assisted hydrogel kit First, 50 mg of agarose was dissolved in 5 mL of distilled water, followed by heating at 120°C under continuous stirring until a clear solution was formed. When the solution temperature dropped to 40 ℃, 4 mL of C-dots was introduced dropwise, after which the mixture was stirred vigorously to achieve thorough mixing, evenly spread onto a centrifuge tube lid, and left to cool and solidify for subsequent use. Next, a 400 µL of mixture containing HAc-NaAc (0.1 M, pH 4.0), CuCl₂, various concentrations of glyphosate and TMB were introduced. After the exposure of a Xe lamp for 1 min, the sample was placed in a photo box for image capture. Finally, the RGB (red, green and blue channels) values were obtained using Color Picker software. The intensity ratio of the red channel (R) and the blue channel (B) was employed for the quantitative determination of glyphosate. Analysis of glyphosate in actual samples Apples, cucumbers and pears were acquired form a nearby supermarket. 200 µL of different concentrations of glyphosate solutions were uniformly sprayed onto the surface of each 2 g sample. After that, these samples were dried under ambient condition for 24 hours to mimic the actual spraying process. Finally, the surfaces of these samples were repeatedly rinsed with ultrapure water, and the obtained eluent was gathered for the subsequent detection of glyphosate. Results and discussions Synthesis and characterization of C-dots C-dots were prepared via a hydrothermal approach, employing 3-aminophenol and tartaric acid as the starting materials (Fig. 1 A). As revealed by transmission electron microscopy (TEM) images, C-dots were spherical and randomly dispersed, with an average diameter of approximately 5.38 nm (Fig. 1 B and Fig. S1 ). The UV-vis absorption spectra of C-dots exhibited two distinct absorption bands positioned at 280 nm and 385 nm, which were ascribed to the absorption bands of n-π * transition [ 18 , 30 ]. The yellow C-dots emitted green fluorescence when exposed to a UV lamp excited at 365 nm (inset of Fig. 1 C). Upon excitation at 390 nm, the emission spectrum exhibited a maximum peak at 526 nm. Fourier transform infrared spectroscopy (FT-IR) was utilized to explore the chemical functional groups of C-dots. As revealed in Fig. 1 D, a wide absorption around 3425 nm was considered to be the stretching vibrations of O-H or N-H bonds. Two distinguished peaks centered at 1735 cm − 1 and 1403 cm − 1 stemmed from C = O and C-OH bonds, which reasonably inferred that numerous carboxylate groups were present on the surface of C-dots. In addition, two peaks at 1613 cm − 1 and 1263 cm − 1 were associated with the C = N stretching vibration within the quinone ring and C-N bonds, which confirmed the successful introduction of N into C-dots. The chemical composition of C-dots was further analyzed by X-ray photoelectron spectroscopy (XPS). The peaks at 284.6 eV, 399.9 eV, and 532.2 eV corresponded to C, N and O elements (Figure. 1E). High-resolution C 1s spectra showed three peaks centered at 284.8 eV (C-C/C = C), 286.5 eV (C-C/C-N) and 288.7 eV (C = O) (Fig. 1 F) [ 30 ]. The N 1s band was deconvoluted into three peaks located at 399.7, 400.5 and 402.2 eV, which were ascribed to pyridinic N, pyrrolic N and graphitic N (Fig. 1 G) [ 18 ], further implying the presence of N in C-dots. The O 1 s spectrum revealed two prominent peaks at 531.7 and 533.2 eV (Fig. S2 ), corresponding to C = O and C-O, respectively [ 30 ]. In summary, the as-synthesized incorporated numerous nitrogen- and oxygen-containing groups. Light-responsive oxidase-like activity of C-dots The light-responsive oxidase-mimicking activity of C-dots was evaluated using 3,3′,5,5′-tetramethylbenzidine (TMB) as the chromogenic substrate. In the presence of visible light irradiation, C-dots facilitated the oxidation of TMB, generating blue-colored oxidized TMB (oxTMB) accompanied by a characteristic absorption peak centered at 652 nm (Fig. 2 A). Conversely, without light irradiation, TMB failed to be oxidized in the presence of C-dots, revealing that light is essential to the oxidase-mimicking activity of C-dots. Additionally, without C-dots, TMB was barely oxidized under the illumination of light. Then, the light-controlled oxidase-like activity of C-dots was further explored (Fig. 2 B). When exposure to visible light, the absorbance rose sharply. Whereas, once the light source was switched off, the oxidation of TMB terminated abruptly and the absorbance remained essentially unchanged. Consequently, the catalytical activity of C-dots exhibited a staircase-like pattern via the successive termination and initiation of light irradiation. This phenomenon implied that the oxidation and termination processes of TMB was finely tuned at any suitable time, which was beneficial to improve the accuracy of colorimetric assays. Considering the above discussions, C-dots exhibited light-driven oxidase-mimicking catalytical activity. Subsequently, we thoroughly investigated several experimental conditions that may affect the catalytical activity of C-dots, including pH values of buffer solution, the irradiation time, the dosages of C-dots and TMB. As depicted in Fig. S3 A, the optimum pH value was found to be 4.0. While its catalytical activity exhibited a progressive augmentation as the reaction time prolonged and the dosages of C-dots and TMB increased (Fig. S3 B-S3D). In view of short detection time and low cost, illumination time of 1 min, 100 µL of C-dots and 0.5 mM TMB were chosen. Under the relatively optimal conditions, steady-state kinetics was employed to assess the oxidase-mimicking activity of C-dots. By varying TMB concentration, the typical Michaelis-Menten curve for C-dots was obtained (Fig. 2 C). According to the Lineweaver-Burk double reciprocal plots (Fig. 2 D), K m and V max were respectively determined to be 0.26 mM and 8.94 × 10 − 7 M•s − 1 , indicating a strong affinity for TMB and an exceptionally high catalytic rate. Catalytic mechanism of C-dots as light-responsive oxidase mimetic It is widely acknowledged that light-responsive oxidase mimetics can initiate the activation of dissolved oxygen, thereby generating reactive oxygen species (ROS) that subsequently facilitates their catalytic activity. Consequently, the catalytical activity of C-dots under different atmosphere conditions was firstly explored in order to gain a deeper understanding of the catalytic mechanism. As depicted in Fig. S4A, a remarkable augmentation in absorbance was observed under oxygen atmosphere, while a conspicuous decline in absorbance was noted under nitrogen atmosphere, implying the indispensable role of the dissolved oxygen. Subsequently, the ROS trapping experiment was conducted to pinpoint the ROS that contributed to the oxidase-mimicking activity of C-dots by introduction of various scavengers. Detailedly, mannitol, nitrotetrazolium blue chloride (NBT), tryptophan, edetate disodium (EDTA-2Na) and CuCl 2 were used for eliminating hydroxyl radical ( • OH), superoxide radical ( • O 2 – ), singlet oxygen ( 1 O 2 ), photogenerated hole (h + ) and electrons (e − ), respectively. The introduction of CuCl 2 led to a decline in the oxidase-mimicking activity of C-dots As (Fig. S4B), which was attributed to that the capture of electrons impeded the reaction. Moreover, its oxidase-like activity also decreased after the addition of NBT, suggesting the formation of O 2 •− during the catalytic process. In contrast, the other scavengers scarcely exerted any influence on the catalytic activity of C-dots. Electron paramagnetic resonance (EPR) spectroscopy was employed to further validate the generation of O 2 •− during the catalytic process. Fig. S4C displayed the characteristic 1:1:1:1 quadruple signal of DMPO-O 2 •− adducts when subjected to visible light irradiation, verifying the generation of O 2 •− . Relying on the aforementioned observations, a conceivable mechanism of the C-dots-facilitated TMB oxidation reaction was summarized and presented in Fig. S4D. When exposure to visible light, C-dots involved the oxygen activation to generate O 2 •− , electron transfer and TMB oxidation. Verification of the feasibility and exploration of the detection mechanism for glyphosate We firstly versified the feasibility of C-dots/TMB/Cu 2+ system for glyphosate detection. As depicted in Fig. 3 A and 3 B, C-dots catalyzed TMB oxidation to form blue oxTMB featuring a strong absorption peak center at 652 nm. Meanwhile, the resulting oxTMB led to a reduction in the fluorescence of C-dots. While the introduction of Cu 2+ suppressed the catalytic ability of C-dots because of the capture of e − , causing a reduction in absorbance and the fading of solution color, which in turn caused the fluorescence recovery of C-dots. However, when glyphosate was introduced into C-dots/TMB/Cu 2+ system, Cu 2+ complexed with glyphosate. Consequently, the recovery of the catalytic capacity of C-dots resulted in a substantial increase in absorbance, a considerable deepening of the solution color, and a notable decrease in fluorescence. In addition, the introduction of glyphosate alone exerted virtually no influence on the both absorbance and fluorescence of C-dot/TMB. The above experimental phenomena indicated that C-dots/TMB/Cu 2+ system could be used for the detection of glyphosate via UV-vis and fluorescence modes. Moreover, taking into account the variations in the solution colors, a smartphone-assisted portable hydrogel kit was also devised for glyphosate detection (Fig. S5). Then the quenching mechanism of C-dots by oxTMB was explored. As revealed in Fig. 3 C, a marked overlap was observed between the fluorescence excitation spectrum of C-dots and the UV-vis absorption spectrum of oxTMB. Meanwhile, the fluorescent lifetime of C-dots remained nearly unchanged following the formation of oxTMB (Fig. 3 D). These findings suggested that the fluorescence quenching was mainly ascribed to the inner filter effect (IFE). Given the above facts, a “three-in-one” platform based on light-responsive C-dots nanozyme for multimodal glyphosate detection was proposed and the detection scheme was shown in Fig. 3 E. Detection of glyphosate by UV-vis and fluorescence mode Several key parameters including pH values of buffer solution, the concentrations of Cu 2+ and TMB, the volumes of C-dots and the irradiation time were investigated in order to obtain the optimal analytical performance. ΔA was employed as a reference criterion to obtain the corresponding optimal conditions. Specifically, it denoted the difference in absorbance measured at 652 nm within the detection system before and after the introduction of glyphosate. ΔA reached the maximum when the buffer solution was at pH 4.0 (Fig. S6A) and the concentration of Cu 2+ was 0.04 mM (Fig. S6B). Regarding the concentration of TMB and volume of C-dots (Fig. S6C and 6D), initially, ΔA progressively augmented in tandem with the increasing concentrations of TMB and volumes of C-dots. Subsequently, ΔA remained essentially constant when the concentration of TMB exceeded 0.5 mM and the volumes of C-dots was greater than 100 µL. As the illumination time prolonged, ΔA first progressively increased and then gradually decreased. The ΔA remained basically constant between 1 minute and 2 minutes (Fig. S6E and S6F). Consequently, the buffer solution with pH 4.0, 0.04 mM Cu 2+ , 0.5 mM TMB, 100 µL of C-dots and illumination time of 1 minute were chosen as the suitable conditions. Under the optimal experimental conditions, the UV-vis absorption spectra of C-dots/Cu 2+ /TMB system in response to a series of glyphosate concentrations were investigated (Fig. 4 A). A progressive elevation of the absorbance at 652 nm ensued as the glyphosate concentrations ascended. The absorbance of C-dots/TMB/Cu 2+ exhibited a direct proportional relationship with glyphosate concentration ranging from 1 to 35 µg/mL, with a linear equation of y 1 = 0.012x + 0.15 (R 2 = 0.995) (Fig. 4 B). When the concentrations of glyphosate ranged from 35 µg/mL to 100 µg/mL, the linear regression equation was y 2 = 0.006x + 0.38 (R 2 = 0.999). In light of a three-fold signal-to-noise ratio, the detection limit was estimated to be 0.31 µg/mL. As illustrated in Fig. 4 C, the fluorescence diminished gradually with the increasing concentrations of glyphosate. The fluorescence intensity manifested a favorable relationship with glyphosate concentration in the range from 1 µg/mL to 15 µg/mL, with a linear regression equation of y 1 =-3796.27x + 210519.22 (R 2 = 0.996) (Fig. 4 D). When glyphosate concentrations ranged from 15 to 50 µg/mL, the linear regression equation was y 2 =-1921.73x + 182283.96 (R 2 = 0.999). Based on a signal-to-noise ratio of 3, the detection limit was computed as 0.12 µg/mL. The sensitivity of this method by UV-vis and fluorescence modes are comparable or even superior to other methods (Table S1 ). Moreover, this method exhibited the remarkable superiority in terms of short detection time, facilitating its practical applications. To assess the selectivity and anti-interference ability of this detection platform, a diverse range of potential interfering substances that might coexist in food samples were added individually or introduced together with glyphosate (Fig. 4 E and 4 F). Neonicotinoid pesticides (acetamiprid, thiamethoxam, clothianidin, imidacloprid), organophosphorus pesticide (dimethoate), organochlorine pesticide (methylviologen), metal ions (Na + , K + , Mg 2+ ) and fructose were included. Notable changes in absorbance and fluorescence intensity were observed when glyphosate was added, while other interfering substances exerted a negligible influence on the detection system. When these possible interferences were simultaneously introduced with glyphosate, both the absorbance and fluorescence intensity remained basically unchanged compared to blank solutions. These findings demonstrated that the detection system exhibited high selectivity and good anti-interference ability. Detection of glyphosate by a smartphone-assisted hydrogel platform To facilitate the on-site quantitative determination of glyphosate and eliminate the reliance on large laboratory instruments, a portable glyphosate detection sensor based on agarose hydrogel integrated with a smartphone was developed as presented in Fig. 5 A. The response of the fabricated hydrogel to various concentrations of glyphosate was explored. As anticipated, with the increasing concentration of glyphosate, the initially colorless hydrogels progressively changed to blue (Fig. S7), corresponding to the steady reduction of the R/B value (Fig. 5 B). A favorable linear relationship was observed with the glyphosate concentration within two linear ranges, namely 6–55 µg/mL and 55–110 µg/mL. The corresponding regress equation were y 1 =-0.002x + 0.93 and y 2 =-0.001x + 0.85. The detection limit was computed as 5.07 µg/mL. The selectivity and anti-interference ability of interference of the hydrogel sensor was further evaluated. When these interfering substances were added alone, the R/B value remained basically unchanged compared with the blank solution, while the R/B value decreased after glyphosate was added (Fig. 5 C). When these interfering substances and glyphosate were added simultaneously, the R/B value was basically consistent with that when only glyphosate was added (Fig. 5 D). These results manifested the constructed hydrogel sensor could be utilized for glyphosate detection with high selectivity and excellent anti-interference ability. In summary, the smartphone-assisted hydrogel sensor featured easy operation and rapid response, facilitating the one-site detection of actual samples. Analysis glyphosate in actual samples To assess the potential of the triple-mode sensor for practical applications, glyphosate was detected in the washing water of apples, cucumbers and pears and the findings were presented in Table 1 . The recoveries by UV-vis mode were in the range of 90.4%-106.4% with the relative standard deviations (RSD) less than 9.72%. The recoveries by fluorescence mode fell within 91.6%-107.2% range and the RSD remained below 8.60%. The recoveries by the smartphone-assisted hydrogel sensor ranged from 91.2% to 108.3% with RSD below 8.76%. The satisfactory recoveries and low RSD signified that the proposed triple-mode detection platform possessed a promising prospect for detecting glyphosate in actual samples. Table 1 Results of detection glyphosate in actual samples via the triple-mode sensing platform. Mode Samples Added (µg/mL) Detected (µg/mL) Recovery (%) RSD (%) UV-vis Apple 5 5.3 106.0 6.1 10 9.9 99.0 1.4 25 23.0 92.0 8.0 37.5 35.3 94.1 5.9 Cucumber 5 5.4 108.0 8.5 10 10.2 102.0 2.2 25 22.6 90.4 9.7 37.5 36.9 98.4 1.5 Pear 5 5.5 110.0 9.8 10 10.2 102.0 2.2 25 26.6 106.4 6.5 37.5 39.9 106.4 6.4 Fluorescence Apple 5 5.1 102.0 1.1 10 9.7 97.0 3.1 25 25.8 103.2 3.2 37.5 36.4 97.1 2.9 Cucumber 5 5.2 104.0 4.8 10 10.1 101.0 1.0 25 22.9 91.6 8.6 37.5 38.2 101.9 2.0 Pear 5 5.4 108.0 8.9 10 10.6 106.0 5.6 25 26.8 107.2 7.2 37.5 36.6 97.6 2.3 Smartphone Apple 10 10.9 109.0 9.3 15 14.0 93.3 6.8 25 25.6 102.4 2.36 37.5 40.6 108.3 8.1 Cucumber 10 10.7 107.0 6.6 15 15.6 104.0 3.8 25 24.4 97.6 2.5 37.5 35.2 93.9 6.1 Pear 10 9.8 98.0 2.5 15 14.3 95.3 4.8 25 22.8 91.2 8.8 37.5 37.6 100.3 0.3 Conclusion In this study, C-dots as a bifunctional nanomaterial with both light-responsive oxidase-mimicking activity and fluorescence was prepared and utilized to construct a triple-mode sensing platform for glyphosate detection. Compared to the single-signal glyphosate sensor, this detection platform exhibited many significant advantages: (i) this triple-mode detection platform offered three independent response signals for glyphosate detection, which were applicable for mutual cross-checking to curtail false positive outcomes and helpful to improve the reliability of analysis results; (ii) this platform used the bifunctional C-dots, instead of employing two or more nanoprobes to generate triple-mode signals, making it simpler; (iii) the synthesis of the bifunctional C-dots was simple and economical. In summary, this triple-mode detection platform integrated the advantages of UV-vis, fluorescence and portable hydrogel detection system, thus enabled quantitative analysis of glyphosate with high accuracy, outstanding sensitivity, excellent selectivity, strong anti-interference ability and short detection time. This multi-mode detection platform is expected to show extensive application prospects in food safety. Declarations Supplementary Information The online version contains supplementary material available at https://doi . Competing interests The authors declare no competing interests. Funding The authors acknowledge support from the Natural Science Foundation of Shandong Province (ZR2022QB192), the National Natural Science Foundation of China (32202145 and 22172063), the Shandong Provincial College Students' Innovation and Entrepreneurship Training Program (S202510427053), the Independent Cultivation Program of Innovation Team of Jinan City (2021GXRC052). Author Contribution Wanqi Yang: Methodology, Writing–original draft. Haodong Yang: Writing–review & editing. Yaxin Ma: Investigation. Ao Hou: Methodology. Xiangyu Yang: Formal analysis. Pengjuan Ni: Writing–review & editing, Funding acquisition. Yizhong Lu: Funding acquisition. Data availability No datasets were generated or analysed during the current study. 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Sens Actuators B Chem 367:132048. https://doi.org/https://doi.org/10.1016/j.snb.2022.132048 Additional Declarations No competing interests reported. Supplementary Files graphicabstract.docx SupplementaryMaterial2.docx SupplementaryMaterial1.docx Cite Share Download PDF Status: Published Journal Publication published 29 Apr, 2026 Read the published version in Microchimica Acta → Version 1 posted Editorial decision: Revision requested 04 Mar, 2026 Reviews received at journal 08 Feb, 2026 Reviewers agreed at journal 06 Feb, 2026 Reviewers agreed at journal 03 Feb, 2026 Reviews received at journal 03 Feb, 2026 Reviewers agreed at journal 29 Jan, 2026 Reviewers invited by journal 29 Jan, 2026 Editor assigned by journal 26 Jan, 2026 Submission checks completed at journal 25 Jan, 2026 First submitted to journal 19 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8637701","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":587678718,"identity":"4f671fe4-e1f1-4cad-beab-6d16c6457fa5","order_by":0,"name":"Wanqi Yang","email":"","orcid":"","institution":"University of Jinan","correspondingAuthor":false,"prefix":"","firstName":"Wanqi","middleName":"","lastName":"Yang","suffix":""},{"id":587678719,"identity":"a7e4af65-63d9-45cc-9007-4ec7fd3db95a","order_by":1,"name":"Haodong Yang","email":"","orcid":"","institution":"University of Jinan","correspondingAuthor":false,"prefix":"","firstName":"Haodong","middleName":"","lastName":"Yang","suffix":""},{"id":587678720,"identity":"8801bb2b-e6a1-44ed-ab16-df0be44c3b29","order_by":2,"name":"Yaxin Ma","email":"","orcid":"","institution":"University of Jinan","correspondingAuthor":false,"prefix":"","firstName":"Yaxin","middleName":"","lastName":"Ma","suffix":""},{"id":587678721,"identity":"ee1e1adf-4214-40fd-9586-8e3aa4f943fc","order_by":3,"name":"Ao Hou","email":"","orcid":"","institution":"University of Jinan","correspondingAuthor":false,"prefix":"","firstName":"Ao","middleName":"","lastName":"Hou","suffix":""},{"id":587678722,"identity":"6427b032-b27f-4ddb-b636-eba062dc9083","order_by":4,"name":"Xiangyu Yang","email":"","orcid":"","institution":"University of Jinan","correspondingAuthor":false,"prefix":"","firstName":"Xiangyu","middleName":"","lastName":"Yang","suffix":""},{"id":587678723,"identity":"f9396924-e226-4c54-8ccb-049ed298a37e","order_by":5,"name":"Pengjuan Ni","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0ElEQVRIie3RrQrDMBDA8RuBxQRqM7FHGAQKNYM9S0ohNWVUTkxEdbK2jxMITHXURlRUVVdOjLEmTPfDDZa/uYj7wUEAfL6fjQEKAPj4QivITq4jVik3FpBDqRXK8xaHhvcdXI6xxA81SSIjOKpYjyLDUwZ1Gkty5jOEMESYtkTQTaFjSQmbJk0zOBJWlryXEJWBI4xaIpcQI+xhPaJ1Jyi/p2FBsrnDdIfIq02CWybocD3uS1xPkzH8BFAJAOHuM7dz+9/UaaRq4bLP5/P9Wx91eUFHxG/PrQAAAABJRU5ErkJggg==","orcid":"","institution":"University of Jinan","correspondingAuthor":true,"prefix":"","firstName":"Pengjuan","middleName":"","lastName":"Ni","suffix":""},{"id":587678726,"identity":"d8760349-0ca1-410d-b0aa-506518554544","order_by":6,"name":"Yizhong Lu","email":"","orcid":"","institution":"University of Jinan","correspondingAuthor":false,"prefix":"","firstName":"Yizhong","middleName":"","lastName":"Lu","suffix":""}],"badges":[],"createdAt":"2026-01-19 09:38:53","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8637701/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8637701/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00604-026-08031-5","type":"published","date":"2026-04-29T15:58:17+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":102398274,"identity":"a3ee49f4-8fa3-4360-ba73-a42ca0479fa3","added_by":"auto","created_at":"2026-02-11 10:22:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":84170,"visible":true,"origin":"","legend":"\u003cp\u003e(A) A schematic fabrication of C-dots. (B) TEM image of C-dots. (C) UV-vis absorption and fluorescence excitation and emission spectra of C-dots, inset shows the color change of C-dots under sunlight and a UV lamp. (D) FT-IR spectrum of C-dots. (E) XPS spectrum of the C-dots, and the corresponding C 1 s (F) and N 1 s (G) spectra.\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8637701/v1/e2d02ed5827addc3908b877a.png"},{"id":102352067,"identity":"43b23f0c-58dd-4d62-b1c9-511d3a95f99a","added_by":"auto","created_at":"2026-02-10 19:11:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":44889,"visible":true,"origin":"","legend":"\u003cp\u003e(A) UV-vis absorption spectra of different solutions including TMB under light irradiation, C-dots-TMB in the absence and presence of visible light. Inset shows the corresponding solution pictures. (B) Light-controllable oxidase-mimicking activity of C-dots. (C) Michaelis-Menten curves and (E) the corresponding Lineweaver-Burk plot for C-dots using TMB as the substrate.\u003c/p\u003e","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8637701/v1/ac19fa1c394874caf317780b.png"},{"id":102397602,"identity":"ec508557-a700-43bc-b50f-f613f98efa29","added_by":"auto","created_at":"2026-02-11 10:18:22","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":95118,"visible":true,"origin":"","legend":"\u003cp\u003e(A) UV-vis absorption and (B) fluorecence emission spectra of C-dots-TMB, C-dots-TMB-Cu\u003csup\u003e2+\u003c/sup\u003e, C-dots-TMB-Cu\u003csup\u003e2+\u003c/sup\u003e-glyphosate, C-dots-TMB-glyphosate. (C) Fluorescence excitation and emission spectra of C-dots and UV-vis absorption spectrum of oxTMB. (D) Fluorescence decay curves of C-dots-TMB with and without visible light exposure. (E) Schematic representation of C-dots for multimodal sensing of glyphosate.\u003c/p\u003e","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8637701/v1/c4f8b44b9fc9cd80abe8f0b0.png"},{"id":102352070,"identity":"c7a148ea-4788-49b7-abc3-67ad9575ff9a","added_by":"auto","created_at":"2026-02-10 19:11:10","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":90148,"visible":true,"origin":"","legend":"\u003cp\u003e(A, C) Impact of glyphosate at various concentrations on the absorbance and fluorescence of the detection platform. (B, D) Linear relationship between glyphosate concentration and absorbance or fluorescence. (E, F) The selectivity and anti-interference ability of the established detection platform by UV-vis and fluorescence mode.\u003c/p\u003e","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8637701/v1/5d815cabbaceac2e6e1ea152.png"},{"id":102352073,"identity":"19fe722b-7924-46cd-95d4-21a2a30e516b","added_by":"auto","created_at":"2026-02-10 19:11:10","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":46230,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Diagrammatic representation of glyphosate detection by the smartphone-assisted hydrogel sensor. (B) The correlation of R/B value with glyphosate content. Inset shows the linear relationship of R/B valueversus glyphosate content.(C) The selectivity and (D) anti-interference ability of the hydrogel sensor.\u003c/p\u003e","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8637701/v1/a79c2341e08dd76632f74476.png"},{"id":108437811,"identity":"d38116d6-48c8-4fcb-b5d3-3cdd8bdc3a9b","added_by":"auto","created_at":"2026-05-04 16:03:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":833711,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8637701/v1/def3eb65-f9b2-4a50-b653-69ccbecfea2b.pdf"},{"id":102352071,"identity":"0f7498ad-6957-4666-8e72-f30ca7288eb9","added_by":"auto","created_at":"2026-02-10 19:11:10","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":153097,"visible":true,"origin":"","legend":"","description":"","filename":"graphicabstract.docx","url":"https://assets-eu.researchsquare.com/files/rs-8637701/v1/c58f12aa3b966b7cbdf3d98a.docx"},{"id":102352069,"identity":"edb33c91-acb2-44f6-b2f4-05117444e9d2","added_by":"auto","created_at":"2026-02-10 19:11:10","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":201058,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial2.docx","url":"https://assets-eu.researchsquare.com/files/rs-8637701/v1/8876d848be17a4f86ecc2005.docx"},{"id":102397963,"identity":"41582091-4309-4edb-95b7-e34eb7b21161","added_by":"auto","created_at":"2026-02-11 10:20:18","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1535299,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8637701/v1/1cb93c5521682f0f32b4abbf.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"A UV-vis-fluorescence-smartphone-assisted hydrogel “three-in-one” platform based on light-responsive carbon dot nanozyme for multimodal glyphosate detection","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGlyphosate (N-(phosphoxymethyl) glycine), a broad-spectrum organophosphorus herbicide, is extensively applied in agricultural production due to its high efficiency and low cost. However, the inappropriate application of glyphosate has given rise to a significant augmentation of its residues in agricultural crops, subsequently presenting a danger to human health [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Consequently, it is of substantial importance to set up a rapid, sensitive, accurate, and convenient method for detecting glyphosate. Up to now, high performance liquid chromatography-mass spectrometry [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], ion chromatography [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], enzyme-linked immunosorbent assay [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] and capillary electrophoresis [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] have been used for glyphosate detection. Although these techniques exhibit relatively high sensitivity and accuracy, they suffer from drawbacks such as complicated and time-consuming sample pretreatment, reliance on large-scale instruments, high cost and poor portability, which limit their practical applications. Presently, newly designed colorimetric or fluorescent sensors have been ascertained to be a promising alternative for glyphosate determination, given their inherent simplicity, low cost and rapid response. Among them, a variety of analytical strategies based on the enzyme-inhibition mechanism have been successfully established for glyphosate detection [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, the instability of enzyme may affect the sensitivity and accuracy of these methods. Consequently, the development of enzyme-free optical sensors for glyphosate detection is highly desirable.\u003c/p\u003e \u003cp\u003eFluorescent carbon dots (C-dots) have received widespread interests in the field of fluorescent assays by virtue of their unique optical properties, cost-effectiveness, low toxicity, enhanced stability and straightforward synthesis [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. As a result, a multitude of enzyme-free fluorescent assays leveraging C-dots for glyphosate detection have been developed [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. However, the single fluorescent assay is susceptible to the disturbances of environmental factors, thus leading to inaccurate readings. To address this challenge, significant advancements have been achieved in colorimetric and fluorescent dual-channel assays by leveraging the peroxidase-mimicking activity of C-dots and integrating their inherent fluorescence properties [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Though these dual-channel assays integrate the merits of colorimetry and fluorescence, thy are hindered by certain limitations. One key issue is that the colorimetric mode relying on the peroxidase-like activity of C-dots depends on unstable hydrogen peroxide to drive the oxidation 3,3',5,5'-tetramethylbenzidine (TMB) and this catalytic reaction is not easily subject to precise control, which may potentially compromise the accuracy of the assay. Another critical drawback is that neither of these strategies is suitable for one-site detection due to their dependence on laboratory equipment.\u003c/p\u003e \u003cp\u003eThe development of light-responsive C-dots oxidase mimetics is an effective approach to address the above issue, as they are capable of catalyzing TMB oxidation without the involvement of hydrogen peroxide [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Moreover, the reaction can be precisely regulated by switching the light source on and off, which in turn significantly enhances the reliability of the detection method. On the basis of the light-driven oxidase-mimicking activity of C-dots, colorimetric detection of antioxidant capacity [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], acid phosphatase [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], acetaldehyde [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] and metal ions [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] have been fulfilled. However, light-responsive C-dots oxidase mimetics have not been utilized for glyphosate detection. Recently, smartphone-based detection platform integrated with optical sensors has achieved striking advancements in the point-of-care testing approaches for diverse analytes [\u003cspan additionalcitationids=\"CR26 CR27 CR28\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. It eliminates the need for laboratory instruments, making it ideal for rapid on-site detection.\u003c/p\u003e \u003cp\u003eConsidering the above discussions, the light-responsive C-dots oxidase mimetic-mediated tri-mode platform was established for glyphosate detection. When exposed to visible light, C-dots prompted the oxidation of colorless TMB, generating blue-colored oxidized TMB (oxTMB) with augmented absorbance at 652 nm. Meanwhile, the generated oxTMB causes fluorescence quenching of the C-dots on account of the inner filter effect (IFE). The introduction of copper ions can capture the photogenerated electrons, thereby inhibiting the catalytic activity of C-dots. Consequently, it is manifested as a decline in absorbance at 652 nm and the fluorescence recovery of C-dots. Once glyphosate is added, it will coordinate with copper ions, thereby leading to a rise in absorbance and a reduction in the fluorescence of C-dots. As a result, quantitative determination of glyphosate can be realized via UV-vis and fluorescence modes. More significantly, by leveraging the color changes of the solution, a portable hydrogel kit with the assistance of a smartphone has been developed for the sensing of glyphosate. This tri-mode detection platform using C-dots nanozyme enhances detection accuracy, providing new perspectives for glyphosate determination and widening the application scopes of photo-responsive nanozymes.\u003c/p\u003e"},{"header":"Experimental","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSynthesis of C-dots\u003c/h2\u003e \u003cp\u003eC-dots were successfully prepared employing tartaric acid and 3-aminophenol as precursors [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. A total mass of 6 g of these two materials (molar ratio of 1:1) was dissolved in 30 mL of ultrapure water. Subsequently, it was transferred to a 100 mL of Teflon-lined stainless steel autoclave and subjected to heating at 160 ℃ for 12 h. Once cooled to ambient temperature, the solution was filtered through a 0.22 \u0026micro;m microporous filter and further purified by dialysis using 1000 Da cellulose dialysis bags. The resulting solution was stored in a refrigerator for subsequent use.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDetection of glyphosate by UV-vis and fluorescence mode\u003c/h3\u003e\n\u003cp\u003eC-dots (100 \u0026micro;L), CuCl\u003csub\u003e2\u003c/sub\u003e (10 \u0026micro;L, 4 mM), varying concentrations of glyphosate (50 \u0026micro;L) and TMB (100 \u0026micro;L, 5 mM) were sequentially added into 740 \u0026micro;L of HAc-NaAc buffer (0.1 M, pH 4.0). After mixing evenly, the obtained solution was exposed to a Xe lamp (λ\u0026thinsp;\u0026ge;\u0026thinsp;420 nm) for 1 min. Then, the corresponding UV-vis absorption spectra and the fluorescence emission spectra were recorded.\u003c/p\u003e\n\u003ch3\u003eDetection of glyphosate by the smartphone-assisted hydrogel kit\u003c/h3\u003e\n\u003cp\u003eFirst, 50 mg of agarose was dissolved in 5 mL of distilled water, followed by heating at 120\u0026deg;C under continuous stirring until a clear solution was formed. When the solution temperature dropped to 40 ℃, 4 mL of C-dots was introduced dropwise, after which the mixture was stirred vigorously to achieve thorough mixing, evenly spread onto a centrifuge tube lid, and left to cool and solidify for subsequent use. Next, a 400 \u0026micro;L of mixture containing HAc-NaAc (0.1 M, pH 4.0), CuCl₂, various concentrations of glyphosate and TMB were introduced. After the exposure of a Xe lamp for 1 min, the sample was placed in a photo box for image capture. Finally, the RGB (red, green and blue channels) values were obtained using Color Picker software. The intensity ratio of the red channel (R) and the blue channel (B) was employed for the quantitative determination of glyphosate.\u003c/p\u003e\n\u003ch3\u003eAnalysis of glyphosate in actual samples\u003c/h3\u003e\n\u003cp\u003eApples, cucumbers and pears were acquired form a nearby supermarket. 200 \u0026micro;L of different concentrations of glyphosate solutions were uniformly sprayed onto the surface of each 2 g sample. After that, these samples were dried under ambient condition for 24 hours to mimic the actual spraying process. Finally, the surfaces of these samples were repeatedly rinsed with ultrapure water, and the obtained eluent was gathered for the subsequent detection of glyphosate.\u003c/p\u003e"},{"header":"Results and discussions","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSynthesis and characterization of C-dots\u003c/h2\u003e \u003cp\u003eC-dots were prepared via a hydrothermal approach, employing 3-aminophenol and tartaric acid as the starting materials (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). As revealed by transmission electron microscopy (TEM) images, C-dots were spherical and randomly dispersed, with an average diameter of approximately 5.38 nm (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB and Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The UV-vis absorption spectra of C-dots exhibited two distinct absorption bands positioned at 280 nm and 385 nm, which were ascribed to the absorption bands of n-π * transition [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The yellow C-dots emitted green fluorescence when exposed to a UV lamp excited at 365 nm (inset of Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Upon excitation at 390 nm, the emission spectrum exhibited a maximum peak at 526 nm. Fourier transform infrared spectroscopy (FT-IR) was utilized to explore the chemical functional groups of C-dots. As revealed in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD, a wide absorption around 3425 nm was considered to be the stretching vibrations of O-H or N-H bonds. Two distinguished peaks centered at 1735 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 1403 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e stemmed from C\u0026thinsp;=\u0026thinsp;O and C-OH bonds, which reasonably inferred that numerous carboxylate groups were present on the surface of C-dots. In addition, two peaks at 1613 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 1263 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e were associated with the C\u0026thinsp;=\u0026thinsp;N stretching vibration within the quinone ring and C-N bonds, which confirmed the successful introduction of N into C-dots. The chemical composition of C-dots was further analyzed by X-ray photoelectron spectroscopy (XPS). The peaks at 284.6 eV, 399.9 eV, and 532.2 eV corresponded to C, N and O elements (Figure. 1E). High-resolution C 1s spectra showed three peaks centered at 284.8 eV (C-C/C\u0026thinsp;=\u0026thinsp;C), 286.5 eV (C-C/C-N) and 288.7 eV (C\u0026thinsp;=\u0026thinsp;O) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF) [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The N 1s band was deconvoluted into three peaks located at 399.7, 400.5 and 402.2 eV, which were ascribed to pyridinic N, pyrrolic N and graphitic N (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], further implying the presence of N in C-dots. The O 1 s spectrum revealed two prominent peaks at 531.7 and 533.2 eV (Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e), corresponding to C\u0026thinsp;=\u0026thinsp;O and C-O, respectively [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In summary, the as-synthesized incorporated numerous nitrogen- and oxygen-containing groups.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eLight-responsive oxidase-like activity of C-dots\u003c/h3\u003e\n\u003cp\u003eThe light-responsive oxidase-mimicking activity of C-dots was evaluated using 3,3\u0026prime;,5,5\u0026prime;-tetramethylbenzidine (TMB) as the chromogenic substrate. In the presence of visible light irradiation, C-dots facilitated the oxidation of TMB, generating blue-colored oxidized TMB (oxTMB) accompanied by a characteristic absorption peak centered at 652 nm (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Conversely, without light irradiation, TMB failed to be oxidized in the presence of C-dots, revealing that light is essential to the oxidase-mimicking activity of C-dots. Additionally, without C-dots, TMB was barely oxidized under the illumination of light. Then, the light-controlled oxidase-like activity of C-dots was further explored (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). When exposure to visible light, the absorbance rose sharply. Whereas, once the light source was switched off, the oxidation of TMB terminated abruptly and the absorbance remained essentially unchanged. Consequently, the catalytical activity of C-dots exhibited a staircase-like pattern via the successive termination and initiation of light irradiation. This phenomenon implied that the oxidation and termination processes of TMB was finely tuned at any suitable time, which was beneficial to improve the accuracy of colorimetric assays. Considering the above discussions, C-dots exhibited light-driven oxidase-mimicking catalytical activity. Subsequently, we thoroughly investigated several experimental conditions that may affect the catalytical activity of C-dots, including pH values of buffer solution, the irradiation time, the dosages of C-dots and TMB. As depicted in Fig. \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003eA, the optimum pH value was found to be 4.0. While its catalytical activity exhibited a progressive augmentation as the reaction time prolonged and the dosages of C-dots and TMB increased (Fig. \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003eB-S3D). In view of short detection time and low cost, illumination time of 1 min, 100 \u0026micro;L of C-dots and 0.5 mM TMB were chosen. Under the relatively optimal conditions, steady-state kinetics was employed to assess the oxidase-mimicking activity of C-dots. By varying TMB concentration, the typical Michaelis-Menten curve for C-dots was obtained (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). According to the Lineweaver-Burk double reciprocal plots (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD), K\u003csub\u003em\u003c/sub\u003e and V\u003csub\u003emax\u003c/sub\u003e were respectively determined to be 0.26 mM and 8.94 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;7\u003c/sup\u003e M\u0026bull;s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, indicating a strong affinity for TMB and an exceptionally high catalytic rate.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eCatalytic mechanism of C-dots as light-responsive oxidase mimetic\u003c/h3\u003e\n\u003cp\u003eIt is widely acknowledged that light-responsive oxidase mimetics can initiate the activation of dissolved oxygen, thereby generating reactive oxygen species (ROS) that subsequently facilitates their catalytic activity. Consequently, the catalytical activity of C-dots under different atmosphere conditions was firstly explored in order to gain a deeper understanding of the catalytic mechanism. As depicted in Fig. S4A, a remarkable augmentation in absorbance was observed under oxygen atmosphere, while a conspicuous decline in absorbance was noted under nitrogen atmosphere, implying the indispensable role of the dissolved oxygen. Subsequently, the ROS trapping experiment was conducted to pinpoint the ROS that contributed to the oxidase-mimicking activity of C-dots by introduction of various scavengers. Detailedly, mannitol, nitrotetrazolium blue chloride (NBT), tryptophan, edetate disodium (EDTA-2Na) and CuCl\u003csub\u003e2\u003c/sub\u003e were used for eliminating hydroxyl radical (\u003csup\u003e\u0026bull;\u003c/sup\u003eOH), superoxide radical (\u003csup\u003e\u0026bull;\u003c/sup\u003eO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026ndash;\u003c/sup\u003e), singlet oxygen (\u003csup\u003e1\u003c/sup\u003eO\u003csub\u003e2\u003c/sub\u003e), photogenerated hole (h\u003csup\u003e+\u003c/sup\u003e) and electrons (e\u003csup\u003e\u0026minus;\u003c/sup\u003e), respectively. The introduction of CuCl\u003csub\u003e2\u003c/sub\u003e led to a decline in the oxidase-mimicking activity of C-dots As (Fig. S4B), which was attributed to that the capture of electrons impeded the reaction. Moreover, its oxidase-like activity also decreased after the addition of NBT, suggesting the formation of O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026bull;\u0026minus;\u003c/sup\u003e during the catalytic process. In contrast, the other scavengers scarcely exerted any influence on the catalytic activity of C-dots. Electron paramagnetic resonance (EPR) spectroscopy was employed to further validate the generation of O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026bull;\u0026minus;\u003c/sup\u003e during the catalytic process. Fig. S4C displayed the characteristic 1:1:1:1 quadruple signal of DMPO-O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026bull;\u0026minus;\u003c/sup\u003e adducts when subjected to visible light irradiation, verifying the generation of O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026bull;\u0026minus;\u003c/sup\u003e. Relying on the aforementioned observations, a conceivable mechanism of the C-dots-facilitated TMB oxidation reaction was summarized and presented in Fig. S4D. When exposure to visible light, C-dots involved the oxygen activation to generate O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026bull;\u0026minus;\u003c/sup\u003e, electron transfer and TMB oxidation.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eVerification of the feasibility and exploration of the detection mechanism for glyphosate\u003c/h2\u003e \u003cp\u003eWe firstly versified the feasibility of C-dots/TMB/Cu\u003csup\u003e2+\u003c/sup\u003e system for glyphosate detection. As depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, C-dots catalyzed TMB oxidation to form blue oxTMB featuring a strong absorption peak center at 652 nm. Meanwhile, the resulting oxTMB led to a reduction in the fluorescence of C-dots. While the introduction of Cu\u003csup\u003e2+\u003c/sup\u003e suppressed the catalytic ability of C-dots because of the capture of e\u003csup\u003e\u0026minus;\u003c/sup\u003e, causing a reduction in absorbance and the fading of solution color, which in turn caused the fluorescence recovery of C-dots. However, when glyphosate was introduced into C-dots/TMB/Cu\u003csup\u003e2+\u003c/sup\u003e system, Cu\u003csup\u003e2+\u003c/sup\u003e complexed with glyphosate. Consequently, the recovery of the catalytic capacity of C-dots resulted in a substantial increase in absorbance, a considerable deepening of the solution color, and a notable decrease in fluorescence. In addition, the introduction of glyphosate alone exerted virtually no influence on the both absorbance and fluorescence of C-dot/TMB. The above experimental phenomena indicated that C-dots/TMB/Cu\u003csup\u003e2+\u003c/sup\u003e system could be used for the detection of glyphosate via UV-vis and fluorescence modes. Moreover, taking into account the variations in the solution colors, a smartphone-assisted portable hydrogel kit was also devised for glyphosate detection (Fig. S5). Then the quenching mechanism of C-dots by oxTMB was explored. As revealed in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC, a marked overlap was observed between the fluorescence excitation spectrum of C-dots and the UV-vis absorption spectrum of oxTMB. Meanwhile, the fluorescent lifetime of C-dots remained nearly unchanged following the formation of oxTMB (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). These findings suggested that the fluorescence quenching was mainly ascribed to the inner filter effect (IFE). Given the above facts, a \u0026ldquo;three-in-one\u0026rdquo; platform based on light-responsive C-dots nanozyme for multimodal glyphosate detection was proposed and the detection scheme was shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eDetection of glyphosate by UV-vis and fluorescence mode\u003c/h2\u003e \u003cp\u003eSeveral key parameters including pH values of buffer solution, the concentrations of Cu\u003csup\u003e2+\u003c/sup\u003e and TMB, the volumes of C-dots and the irradiation time were investigated in order to obtain the optimal analytical performance. ΔA was employed as a reference criterion to obtain the corresponding optimal conditions. Specifically, it denoted the difference in absorbance measured at 652 nm within the detection system before and after the introduction of glyphosate. ΔA reached the maximum when the buffer solution was at pH 4.0 (Fig. S6A) and the concentration of Cu\u003csup\u003e2+\u003c/sup\u003e was 0.04 mM (Fig. S6B). Regarding the concentration of TMB and volume of C-dots (Fig. S6C and 6D), initially, ΔA progressively augmented in tandem with the increasing concentrations of TMB and volumes of C-dots. Subsequently, ΔA remained essentially constant when the concentration of TMB exceeded 0.5 mM and the volumes of C-dots was greater than 100 \u0026micro;L. As the illumination time prolonged, ΔA first progressively increased and then gradually decreased. The ΔA remained basically constant between 1 minute and 2 minutes (Fig. S6E and S6F). Consequently, the buffer solution with pH 4.0, 0.04 mM Cu\u003csup\u003e2+\u003c/sup\u003e, 0.5 mM TMB, 100 \u0026micro;L of C-dots and illumination time of 1 minute were chosen as the suitable conditions.\u003c/p\u003e \u003cp\u003eUnder the optimal experimental conditions, the UV-vis absorption spectra of C-dots/Cu\u003csup\u003e2+\u003c/sup\u003e/TMB system in response to a series of glyphosate concentrations were investigated (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). A progressive elevation of the absorbance at 652 nm ensued as the glyphosate concentrations ascended. The absorbance of C-dots/TMB/Cu\u003csup\u003e2+\u003c/sup\u003e exhibited a direct proportional relationship with glyphosate concentration ranging from 1 to 35 \u0026micro;g/mL, with a linear equation of y\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.012x\u0026thinsp;+\u0026thinsp;0.15 (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.995) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). When the concentrations of glyphosate ranged from 35 \u0026micro;g/mL to 100 \u0026micro;g/mL, the linear regression equation was y\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.006x\u0026thinsp;+\u0026thinsp;0.38 (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.999). In light of a three-fold signal-to-noise ratio, the detection limit was estimated to be 0.31 \u0026micro;g/mL. As illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC, the fluorescence diminished gradually with the increasing concentrations of glyphosate. The fluorescence intensity manifested a favorable relationship with glyphosate concentration in the range from 1 \u0026micro;g/mL to 15 \u0026micro;g/mL, with a linear regression equation of y\u003csub\u003e1\u003c/sub\u003e=-3796.27x\u0026thinsp;+\u0026thinsp;210519.22 (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.996) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). When glyphosate concentrations ranged from 15 to 50 \u0026micro;g/mL, the linear regression equation was y\u003csub\u003e2\u003c/sub\u003e=-1921.73x\u0026thinsp;+\u0026thinsp;182283.96 (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.999). Based on a signal-to-noise ratio of 3, the detection limit was computed as 0.12 \u0026micro;g/mL. The sensitivity of this method by UV-vis and fluorescence modes are comparable or even superior to other methods (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Moreover, this method exhibited the remarkable superiority in terms of short detection time, facilitating its practical applications.\u003c/p\u003e \u003cp\u003eTo assess the selectivity and anti-interference ability of this detection platform, a diverse range of potential interfering substances that might coexist in food samples were added individually or introduced together with glyphosate (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF). Neonicotinoid pesticides (acetamiprid, thiamethoxam, clothianidin, imidacloprid), organophosphorus pesticide (dimethoate), organochlorine pesticide (methylviologen), metal ions (Na\u003csup\u003e+\u003c/sup\u003e, K\u003csup\u003e+\u003c/sup\u003e, Mg\u003csup\u003e2+\u003c/sup\u003e) and fructose were included. Notable changes in absorbance and fluorescence intensity were observed when glyphosate was added, while other interfering substances exerted a negligible influence on the detection system. When these possible interferences were simultaneously introduced with glyphosate, both the absorbance and fluorescence intensity remained basically unchanged compared to blank solutions. These findings demonstrated that the detection system exhibited high selectivity and good anti-interference ability.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eDetection of glyphosate by a smartphone-assisted hydrogel platform\u003c/h2\u003e \u003cp\u003eTo facilitate the on-site quantitative determination of glyphosate and eliminate the reliance on large laboratory instruments, a portable glyphosate detection sensor based on agarose hydrogel integrated with a smartphone was developed as presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA. The response of the fabricated hydrogel to various concentrations of glyphosate was explored. As anticipated, with the increasing concentration of glyphosate, the initially colorless hydrogels progressively changed to blue (Fig. S7), corresponding to the steady reduction of the R/B value (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). A favorable linear relationship was observed with the glyphosate concentration within two linear ranges, namely 6\u0026ndash;55 \u0026micro;g/mL and 55\u0026ndash;110 \u0026micro;g/mL. The corresponding regress equation were y\u003csub\u003e1\u003c/sub\u003e=-0.002x\u0026thinsp;+\u0026thinsp;0.93 and y\u003csub\u003e2\u003c/sub\u003e=-0.001x\u0026thinsp;+\u0026thinsp;0.85. The detection limit was computed as 5.07 \u0026micro;g/mL. The selectivity and anti-interference ability of interference of the hydrogel sensor was further evaluated. When these interfering substances were added alone, the R/B value remained basically unchanged compared with the blank solution, while the R/B value decreased after glyphosate was added (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). When these interfering substances and glyphosate were added simultaneously, the R/B value was basically consistent with that when only glyphosate was added (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). These results manifested the constructed hydrogel sensor could be utilized for glyphosate detection with high selectivity and excellent anti-interference ability. In summary, the smartphone-assisted hydrogel sensor featured easy operation and rapid response, facilitating the one-site detection of actual samples.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis glyphosate in actual samples\u003c/h2\u003e \u003cp\u003eTo assess the potential of the triple-mode sensor for practical applications, glyphosate was detected in the washing water of apples, cucumbers and pears and the findings were presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The recoveries by UV-vis mode were in the range of 90.4%-106.4% with the relative standard deviations (RSD) less than 9.72%. The recoveries by fluorescence mode fell within 91.6%-107.2% range and the RSD remained below 8.60%. The recoveries by the smartphone-assisted hydrogel sensor ranged from 91.2% to 108.3% with RSD below 8.76%. The satisfactory recoveries and low RSD signified that the proposed triple-mode detection platform possessed a promising prospect for detecting glyphosate in actual samples.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of detection glyphosate in actual samples via the triple-mode sensing platform.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMode\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSamples\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdded\u003c/p\u003e \u003cp\u003e(\u0026micro;g/mL)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDetected\u003c/p\u003e \u003cp\u003e(\u0026micro;g/mL)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRecovery (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRSD\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUV-vis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eApple\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e106.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e99.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e92.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e94.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCucumber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e108.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e102.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e98.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e110.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e102.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e106.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e39.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e106.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFluorescence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eApple\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e102.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e103.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCucumber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e104.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e101.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e91.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e101.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e108.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e106.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e107.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmartphone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eApple\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e109.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e93.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e102.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e108.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCucumber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e107.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e104.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e93.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e98.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e95.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e91.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this study, C-dots as a bifunctional nanomaterial with both light-responsive oxidase-mimicking activity and fluorescence was prepared and utilized to construct a triple-mode sensing platform for glyphosate detection. Compared to the single-signal glyphosate sensor, this detection platform exhibited many significant advantages: (i) this triple-mode detection platform offered three independent response signals for glyphosate detection, which were applicable for mutual cross-checking to curtail false positive outcomes and helpful to improve the reliability of analysis results; (ii) this platform used the bifunctional C-dots, instead of employing two or more nanoprobes to generate triple-mode signals, making it simpler; (iii) the synthesis of the bifunctional C-dots was simple and economical. In summary, this triple-mode detection platform integrated the advantages of UV-vis, fluorescence and portable hydrogel detection system, thus enabled quantitative analysis of glyphosate with high accuracy, outstanding sensitivity, excellent selectivity, strong anti-interference ability and short detection time. This multi-mode detection platform is expected to show extensive application prospects in food safety.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eSupplementary Information\u003c/h2\u003e \u003cp\u003eThe online version contains supplementary material available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi\u003c/span\u003e\u003cspan address=\"https://doi\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe authors acknowledge support from the Natural Science Foundation of Shandong Province (ZR2022QB192), the National Natural Science Foundation of China (32202145 and 22172063), the Shandong Provincial College Students' Innovation and Entrepreneurship Training Program (S202510427053), the Independent Cultivation Program of Innovation Team of Jinan City (2021GXRC052).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eWanqi Yang: Methodology, Writing\u0026ndash;original draft. Haodong Yang: Writing\u0026ndash;review \u0026amp; editing. Yaxin Ma: Investigation. Ao Hou: Methodology. Xiangyu Yang: Formal analysis. Pengjuan Ni: Writing\u0026ndash;review \u0026amp; editing, Funding acquisition. Yizhong Lu: Funding acquisition.\u003c/p\u003e\u003ch2\u003eData availability\u003c/h2\u003e \u003cp\u003eNo datasets were generated or analysed during the current study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eEkerim S, Tasci N, Demirkan M (2025) Determination of glyphosate with a novel optic membrane sensor. 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Sens Actuators B Chem 367:132048. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/https://doi.org/10.1016/j.snb.2022.132048\u003c/span\u003e\u003cspan address=\"10.1016/j.snb.2022.132048\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"microchimica-acta","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"miac","sideBox":"Learn more about [Microchimica Acta](https://link.springer.com/journal/604)","snPcode":"604","submissionUrl":"https://submission.springernature.com/new-submission/604/3","title":"Microchimica Acta","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Carbon dots, Nanozyme, Colorimetry, Fluorescence, Glyphosate","lastPublishedDoi":"10.21203/rs.3.rs-8637701/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8637701/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe establishment of a fast and precise method for glyphosate detection holds critical importance in ensuring food safety. Herein, a multimodal sensing platform that integrated UV-vis, fluorescence and smartphone-assisted portable hydrogel kit was applied to detect glyphosate relying on the light-responsive oxidase-mimicking activity and intrinsic fluorescence of carbon dots (C-dots). C-dots enable the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB), resulting in blue-colored oxidized TMB (oxTMB) along with enhanced absorbance at 652 nm. Simultaneously, the inner filter effect between oxTMB and C-dots induces the fluorescence quenching of C-dots. However, the introduction of copper ions can capture photogenerated electrons, thereby inhibiting the oxidase-mimicking catalytic activity of C-dots, leading to a decrease in absorbance and the restoration of fluorescence. Once glyphosate is present in the system, it can coordinate with copper ions to restore the catalytic activity of C-dots, thereby causing an increase in absorbance and a simultaneous decrease in fluorescence. Consequently, quantification detection of glyphosate can be realized via UV-vis and fluorescence modes. More importantly, in light of the changes in solution color, a smartphone-assisted portable hydrogel kit was also developed for glyphosate detection. Therefore, a UV-vis-fluorescence-smartphone-assisted hydrogel \u0026ldquo;three-in-one\u0026rdquo; platform was established for glyphosate analysis with corresponding limits of detection as low as 0.31, 0.12 and 5.07 \u0026micro;g/mL. This platform can achieve glyphosate detection within just one minute. Moreover, compared with single-mode detection platforms, this multi-mode detection platform ensures greater accuracy, thus holding broader application prospects.\u003c/p\u003e","manuscriptTitle":"A UV-vis-fluorescence-smartphone-assisted hydrogel “three-in-one” platform based on light-responsive carbon dot nanozyme for multimodal glyphosate detection","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-10 19:11:04","doi":"10.21203/rs.3.rs-8637701/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-04T06:52:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-08T10:31:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"63849166198435486679828512135780428616","date":"2026-02-06T12:17:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"184007688597621179489695375988331909441","date":"2026-02-03T05:53:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-03T05:07:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"35819943241350491979109850952256620057","date":"2026-01-29T11:04:33+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-29T05:47:50+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-26T16:20:34+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-26T01:01:56+00:00","index":"","fulltext":""},{"type":"submitted","content":"Microchimica Acta","date":"2026-01-19T09:15:57+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"microchimica-acta","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"miac","sideBox":"Learn more about [Microchimica Acta](https://link.springer.com/journal/604)","snPcode":"604","submissionUrl":"https://submission.springernature.com/new-submission/604/3","title":"Microchimica Acta","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"6553a448-2a9d-48fc-89e1-7fde3621e8dc","owner":[],"postedDate":"February 10th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T16:02:45+00:00","versionOfRecord":{"articleIdentity":"rs-8637701","link":"https://doi.org/10.1007/s00604-026-08031-5","journal":{"identity":"microchimica-acta","isVorOnly":false,"title":"Microchimica Acta"},"publishedOn":"2026-04-29 15:58:17","publishedOnDateReadable":"April 29th, 2026"},"versionCreatedAt":"2026-02-10 19:11:04","video":"","vorDoi":"10.1007/s00604-026-08031-5","vorDoiUrl":"https://doi.org/10.1007/s00604-026-08031-5","workflowStages":[]},"version":"v1","identity":"rs-8637701","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8637701","identity":"rs-8637701","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}