Search Results (3,103)

Water pollution caused by pesticides, such as the toxic herbicide Dichlorprop-P (2,4-DP), represents a major global concern. This study reports a novel inhibition-based electrochemical biosensor for the ultra-trace determination of Dichlorprop-P in surface waters, fabricated by modifying a screen-printed carbon electrode with Prussian Blue and tyrosinase. The optimized platform was obtained after 30 drop-casting steps, corresponding to 75 μL Prussian Blue at 8.59 mg/mL, followed by immobilization of 10 μL tyrosinase solution at 50 mg/mL. Fourier-transform infrared spectroscopy and cyclic voltammetry confirmed the successful deposition of the mediator and enzyme. To the best of our knowledge, this is the first tyrosinase-based biosensor proposed for Dichlorprop-P detection. The sensing principle relies on the decrease in the catalytic current generated by tyrosinase-mediated tyrosine oxidation in the presence of the Prussian Blue mediator. The biosensor showed a linear response between 0 and 0.1 μM, with a detection limit of 0.02 μM, a quantification limit of 0.09 μM, and good linearity (R² = 0.9906). Application to Danube River water samples yielded recoveries of 97–105%, supporting its suitability for environmental monitoring. Full article

Green undersown crops (GUCs) are increasingly promoted as a sustainable management strategy to improve soil quality and ecosystem services in Mediterranean orchards, particularly in the calcareous, low-organic-matter soils typical of Eastern Spain. In this context, soil quality is understood as the soil’s overall functional capacity, integrating physical structure, chemical balance, and biological activity, whereas soil fertility refers specifically to the soil’s ability to supply nutrients to plants; soil quality therefore encompasses a broader set of ecosystem functions beyond nutrient provision. However, their effects on the calcareous, low-organic-matter soils typical of Eastern Spain remain insufficiently quantified. This study evaluates the effects of seeded undersown (grasses, legumes, and flower mixtures), spontaneous vegetation, and herbicide-managed bare soil on topsoil (0–15 cm) physicochemical and biological indicators in 54 plots across three irrigated persimmon orchard sites (Granja, Cargol, and Alginet) over 18 months of treatment in the València region (Eastern Spain). Seasonal sampling was conducted at the START (early winter) and END (late spring) of the experiment period. Soil measurements at both sampling times included soil organic matter (SOM), nitrogen (N), C/N ratio, pH, electrical conductivity (EC), soil respiration rate (RR), collembolan abundance, mite abundance, and the QBS-ar index of soil arthropods. Legumes increased SOM by +1.12%, grasses by +0.22%, whereas flower mixtures (−0.44%) and spontaneous vegetation (−1.36%) showed SOM reductions associated with rapid biomass turnover. RR increased under all GUCs (+0.06 to +0.16 g CO₂ m⁻² h⁻¹), and QBS-ar improved markedly under grasses (+26.6) and spontaneous vegetation (+36.7). EC decreased across all treatments (−16 to −84 µS cm⁻¹). These results were analysed using principal component analysis (PCA). Four PCA components explained 74% of the total variance, revealing functional gradients driven by SOM, N, EC, RR and mesofauna. After 18 months, microbial biomass carbon (MBC) increased by +45–60% under legumes, water-soluble organic carbon (WSOC) by +30–50% under legumes and flower mixtures, and the enzyme activities (EA) by +20–40% under all GUCs. Herbicide-managed soils showed reduced biological activity and detectable residues of glyphosate and oxyfluorfen. PCA and linear discriminant analysis (LDA) were used to identify functional gradients and treatment separation. GUCs significantly increased SOM, MBC, EA, and mesofauna abundance compared with herbicide treatments, which showed reduced biological activity and detectable residues of glyphosate and oxyfluorfen. Legumes and flower mixtures produced the strongest improvements in biological functioning due to higher MBC, WSOC, EA and RR. PCA and LDA confirmed clear separation between GUCs and herbicide-managed soils based on multivariate differences in SOM, N, EC, RR, MBC, WSOC and mesofauna indicators. Overall, GUCs modulated soil chemistry and biodiversity and enhanced soil functioning and biological quality, supporting their adoption as a sustainable management strategy in Mediterranean orchards. Legume-based covers are recommended for rapid biological activation, whereas grass-based covers favour longer-term SOM stabilisation. These findings highlight their role as key tools for improving soil resilience in Mediterranean persimmon orchards. Full article

Sustainable agricultural production requires environmentally friendly weed management solutions. Steam-based thermal weed control is a promising alternative to conventional herbicide-based weed management. However, optimizing steam delivery systems remains computationally expensive due to the repeated simulation-based design evaluations required. This paper presents a design optimization framework for a novel root-targeted steam injection module intended for integration into an autonomous agricultural platform for sustainable thermal weed management. The mechanical behavior of different nozzle geometries was evaluated using finite element analysis using the ABAQUS/CAE software, generating the simulation dataset used for optimization. To reduce the computational cost associated with repeated finite element simulations, a Kriging surrogate model was constructed from this dataset and coupled with an evolutionary optimization algorithm to identify the optimal nozzle geometry. The evaluated nozzle geometries exhibited maximum stresses ranging from 5.12 to 20.41 N/mm². The stress value predicted by the Kriging model for the optimized configuration was validated through an additional finite element simulation, showing a deviation of only 6.6%. Furthermore, an artificial neural network model implemented in PyTorch 2.7.1 was trained on the simulation dataset and used as an independent validation tool to estimate the stress corresponding to the optimized nozzle geometry, with a prediction deviating by approximately 5.4% from the corresponding finite element result. The proposed approach significantly reduces computational cost while maintaining high accuracy in stress prediction, enabling the identification of a structurally reliable nozzle geometry for sustainable herbicide-free thermal weed management. Full article

Increased herbicide use in agriculture is a major threat to adjacent aquatic and wetland ecosystems. In Morocco, the herbicide 2,4-dichlorophenoxyacetic acid (2,4-D) poses a risk to temporary ponds found in agricultural landscapes. This study used mesocosm experiments to assess the effects of 2,4-D concentration (0, 0.10, 0.20, and 0.30 mg·L⁻¹) and application timing (early vs. late in the hydrological cycle) on water quality and aquatic plant communities from forest ponds not previously exposed to herbicides. At the highest concentration (0.30 mg·L⁻¹), conductivity increased from 206 to 274 µS and pH from 7.5 to 8.4 under early application. At the same time, species richness and total abundance significantly decreased with increasing 2,4-D concentrations, with the strongest effects observed under early application. Community composition shifted markedly in response to 2,4-D, with annual and submerged species showing greater sensitivity, whereas perennial and emergent species were relatively tolerant. These findings highlight the need to adopt more sustainable agricultural practices to conserve pond biodiversity. Specifically, herbicide applications should be avoided near ponds, at high application rates, and during periods early in the hydroperiod. Lastly, land-use strategies should balance agricultural productivity with the conservation of biodiversity in temporary pond ecosystems. Full article

UAV-based weed detection in precision agriculture is constrained by asymmetric error costs: a missed weed patch causes herbicide under-treatment and yield loss, whereas a false alarm only prompts an unnecessary spot treatment. Cost-sensitive active learning (cAL) addresses this through an asymmetric misclassification penalty $r^{+}$, but the optimal value is scene-dependent and cannot be determined without domain expertise or advance knowledge of scene difficulty—a fundamental barrier to autonomous UAV monitoring workflows. We propose AdaRisk-Agent, the first LLM-orchestrated framework for adaptive $r^{+}$ calibration in cAL-based UAV weed detection. We validate the framework on four UAV multispectral scenes from two public datasets—WeedsGalore (Germany, five-band maize) and WeedyRice (Vietnam, four-band paddy)—spanning two crop types, two sensor configurations, and weed prevalence from 3.1% to 30.5%. Adaptive calibration reduces the false-negative rate (FNR) by up to $80\%$ relative to symmetric-cost baselines across all scenes. The deterministic surrogate (AdaRisk-Rule) surpasses the fixed-policy oracle (cAL $r^{+}=7$) on two of four scenes without advance scene knowledge, achieving a $50\%$ FNR reduction on the most spectrally challenging scene. A context-feature ablation confirms that budget urgency is the primary calibration signal and that test-set-independent deployment is feasible. Each calibration decision is accompanied by a natural-language justification, enabling auditable deployment in operational precision agriculture workflows. Future work will extend AdaRisk-Agent to multi-class weed species detection and multi-scene meta-learning for compact offline surrogate policies. Full article

Glyphosate (GLY), one of the most extensively applied broad-spectrum herbicides worldwide, frequently contaminates soil and aquatic ecosystems, posing serious threats to human health, non-target organisms, soil microbial communities, and environmental sustainability. In the present study, phytoremediation using Medicago sativa (MS) was evaluated for the removal of GLY from contaminated soil under greenhouse conditions, with remediation efficiency enhanced through inoculation with two bacterial bioagents, Bacillus sp. h10 (BS) and Pseudomonas aeruginosa KZFS4 (PA). Biochemical parameters, including superoxide dismutase (SOD), catalase (CAT), hydrogen peroxide (H₂O₂), and malondialdehyde (MDA), together with detoxification-related gene expression, were investigated in the roots and leaves of MS exposed to GLY stress. The combined application of MS with BS + PA, followed by MS + PA and MS + BS, significantly decreased GLY residues in soil and increased GLY accumulation in plant roots and leaves after 1, 3, 7, and 10 days compared with MS treatment alone. In vitro batch equilibrium experiments demonstrated that BS and PA desorbed 33.63 and 40.56 µg g⁻¹ of GLY, respectively, thereby enhancing its removal from soil. The persistence of GLY was highest in contaminated soil without treatment, exhibiting a half-life (t₁/₂) of 52.66 days, whereas the shortest half-life (6.69 days) was recorded in soil treated with MS combined with BS and PA relative to sterilized contaminated soil. Furthermore, inoculation with BS and PA markedly increased SOD and CAT activities in MS tissues, while significantly reducing H₂O₂ and MDA accumulation, indicating alleviation of oxidative stress. GLY exposure also triggered substantial upregulation of detoxification-associated genes, including cytochrome P450, glutathione S-transferases (GST), glycosyltransferases (GTs), and ABC transporters in MS. These findings demonstrate that the integration of BS and PA with phytoremediation effectively accelerates GLY dissipation and reduces pesticide-associated toxicity in contaminated soils and plants. Full article

Diflufenican is a herbicide widely used in agricultural systems, but its effects on soil bacterial communities across different soil depths remain insufficiently understood. In this study, we investigated depth-resolved bacterial community responses and functional potential following diflufenican perturbation in agricultural soils. Soil samples collected from different depths were incubated with or without diflufenican, and bacterial communities were analyzed using 16S rRNA gene amplicon sequencing. Co-occurrence network analysis was conducted to explore potential bacterial association patterns, and PICRUSt2 and FAPROTAX were used to infer bacterial functional potential. Diflufenican perturbation altered bacterial alpha diversity and reshaped community composition, with response patterns varying among soil depths. Principal coordinate analysis based on Bray–Curtis dissimilarity showed separation between control and diflufenican-treated soils, indicating treatment-associated shifts in bacterial community structure. Several genera, including Sphingomonas, Pseudarthrobacter, Bacillus, Microvirga, and Phenylobacterium, were enriched in diflufenican-treated soils, suggesting that they may represent candidate diflufenican-associated taxa. Co-occurrence network analysis further indicated changes in potential bacterial association patterns after diflufenican perturbation. Functional inference suggested shifts in bacterial functional potential, particularly in nutrient cycling-related functions, and these shifts differed among soil depths. Overall, these findings indicate that diflufenican perturbation reshapes soil bacterial community structure and alters inferred functional potential in a depth-dependent manner, highlighting the importance of soil vertical depth in assessing herbicide impacts on agricultural soil microbiomes. Full article

Herbicides are widely used in modern agriculture to control weeds and maintain crop productivity, but their persistence in soil raises concerns about unintended effects on non-target organisms. Pendimethalin, a dinitroaniline herbicide extensively applied to cereal and vegetable crops, is designed to target plant microtubules and is generally considered unlikely to pose genotoxic risks to animals. However, information on its sublethal effects on beneficial soil arthropods remains limited. In this study, we investigated the cytotoxic and histopathological effects of a commercial pendimethalin-based formulation on the ground beetle Pterostichus melas italicus, an ecologically relevant predatory species in agroecosystems. Adult males collected from an organic farm were exposed under laboratory conditions to soil treated at the recommended field dose and maintained for up to 7 days, corresponding to subchronic exposure. Individuals were sampled after 2 and 7 days, and the midgut and Malpighian tubules were analysed using histological and transmission electron microscopy. Exposure induced marked but non-lethal ultrastructural alterations, particularly in the Malpighian tubules, including reduction in the basal labyrinth, cytoplasmic vacuolisation, mitochondrial swelling, increased phagolysosome abundance, and nuclear karyorrhexis. These effects were transient under laboratory conditions and occurred without detectable impacts on survival, highlighting the Malpighian tubules as sensitive targets for the early detection of herbicide-induced physiological disturbances. However, the observed recovery may reflect compensatory physiological processes that could entail energetic costs and, under field conditions characterized by multiple concurrent stressors, potentially compromise physiological performance and predatory efficiency. Consequently, this study underscores the necessity of integrating sublethal ultrastructural biomarkers into environmental risk assessment frameworks for non-target beneficial insects. Full article

2,4-Dichlorophenoxyacetic acid (2,4-D), originally developed as a synthetic auxinic herbicide, is the most widely used chemical inducer of somatic embryogenesis (SE) in plants. Despite extensive use of 2,4-D in plant regeneration, the systems-level regulatory mechanisms connecting hormonal signaling, metabolic reprogramming, translational control, and embryogenic competence remain poorly resolved. Here, we hypothesize that TOR signaling functions as an integrative molecular hub coordinating transcriptional, metabolic, and developmental reprogramming during somatic embryogenesis induction. To investigate the molecular regulatory landscape associated with 2,4-D-induced SE, we performed a systems-level analysis integrating publicly available transcriptomic data from Arabidopsis thaliana with high-confidence protein–protein interaction (PPI) network analyses using STRING v12.0 (confidence score ≥ 0.900). Using a previously published transcriptomic dataset, we identified 1927 upregulated genes associated with SE induction, which were organized into 34 functional modules related to transcriptional regulation, translation metabolism, hormone signaling and cellular homeostasis. Within this interactome, TARGET OF RAPAMYCIN (TOR) kinase emerged as an integrative regulatory hub associated with multiple pathways involved in embryogenic reprogramming. Network analyses revealed three major TOR-associated regulatory axes: (1) the TOR–FKBP12–RPS6A axis, associated with ribosome biogenesis and translational regulation; (2) the TOR–CBP20 axis, connected with transcriptional reprogramming; SE master regulators (LEC1, LEC2, and FUS3); and lipid, sterol, brassinosteroid (BR), and auxin-associated pathways; and (3) the TOR–TAP46 axis, linked with one-carbon metabolism, nucleotide biosynthesis, DNA replication and repair, and genome-stability pathways. Additionally, the network contained 411 embryo-lethal (EMBL) genes distributed across multiple regulatory modules, reinforcing the biological relevance of the identified interactome and highlighting the importance of coordinated developmental, metabolic, and transcriptional regulation during embryogenesis induction. These findings support a systems-level TOR-associated regulatory framework involved in the integration of transcriptional, translational, metabolic, hormonal, and genome-maintenance pathways during embryogenesis. This interactome model provides a foundation for functional studies aimed at dissecting the molecular mechanisms underlying SE and identifying candidate targets to improve regeneration and biotechnological application and crop genetic engineering. Collectively, this study proposes a mechanistic framework in which TOR signaling integrates developmental, metabolic, translational, and genome-stability pathways to orchestrate embryogenic competence, providing candidate molecular targets for improving plant regeneration and genome engineering platforms. Full article

Managing invasive alien species (IAS) is a major challenge for conserving ecosystems because of their deleterious impacts. This study evaluated the efficacy of five selective herbicides and wheat straw mulch against six invasive alien plant (IAP) species in Iran. Field observations from 2021 to 2025 showed that these species are concentrated in agricultural regions, particularly in summer crops in northern Iran. Five available herbicides (pendimethalin 3 lit h⁻¹, imazethapyr 0.75 lit h⁻¹, nicosulfuron 2 lit h⁻¹, bentazone 2 lit h⁻¹, and 2,4-D+MCPA 1.5 lit h⁻¹) and wheat straw mulch (2 tons ha⁻¹) were used to reduce the growth of six IAP species during summer 2025. Pendimethalin (as a pre-emergence herbicide) was effective (>90%) against all species apart from Ipomoea hederacea (≈60%). While 2,4-D+MCPA (as a post-emergence herbicide) effectively controlled five species, bentazone was effective only against Sida rhombifolia and I. hederacea. Nicosulfuron showed high efficacy (80%) only against I. hederacea. Straw mulch was more effective against Euphorbia nutans but was not effective properly against Ipomoea species. The efficacy of mulch and some herbicides depended on species identity, even within the same genera (Ipomoea and Euphorbia). Our results can help in the successful management of these invasive plants in northern Iran to minimize their impact on yield and quality of crops. As IAPs in environmental areas, this result will also be advantageous. Full article

Chiral pesticides, comprising enantiomers with identical physical and chemical properties but different biological effects, call for extra efforts in comprehensively evaluating their risk assessment. However, the defect regarding sensitive analysis of chiral pesticides limits the progress of research. Therefore, an efficient and highly sensitive analytical method for the trace-level analysis of chiral pesticides is imperative. Herein, normal micellar electrokinetic chromatography (MEKC), sweeping-MEKC, and anion-selective exhaustive injection-sweeping-MEKC (ASEI-sweeping-MEKC) were optimized to separate and enrich three chiral phenoxy acid herbicides (cloprop, dichlorprop, and fenoprop). Normal MEKC with 30 mM γ-cyclodextrin, 50 mM SDS, pH 2.5, and 50 mM phosphate buffer background electrolyte (BGE) achieved ideal chiral separation of target herbicides. Then, sweeping-MEKC was modified to enhance the detection sensitivity by 4690 to 10,630-folds with the conditions of pH 2.5, 100 mM phosphate buffer high-conductivity buffer (HCB), 60 s injection time + 30 mM γ-CD, 50 mM SDS, pH 2.5, 50 mM phosphate buffer BGE + 120 s sample injection time. ASEI-sweeping-MEKC achieved further improvement of detection sensitivity by 241,000- to 673,000-fold. And the optimal ASEI-sweeping-MEKC conditions for the target chiral phenoxy acid herbicides were 20% ACN water plug, 30 s injection time + pH 2.5, 100 mM phosphate buffer HCB, 60 s injection time + 30 mM γ-CD, 50 mM SDS, pH 2.5, 50 mM phosphate buffer BGE + 12 min sample injection time. All in all, these findings have validated ASEI-sweeping-MEKC as an efficient and powerful analytical method for the trace-level analysis of the enantiomers of three chiral phenoxy acid herbicides. This approach enables a comprehensive risk assessment and provides guidance for the sustainable application of chiral pesticides. Full article

Acetolactate synthase (ALS; EC 2.2.1.6) catalyzes the first committed step in branched-chain amino acid (BCAA) biosynthesis and is the molecular target of multiple herbicide classes, including the imidazolinones. Here, we performed a genome-wide characterization of the HaALS gene family in sunflower (Helianthus annuus L.) and investigated genotype-dependent transcriptional responses to imazethapyr. A total of 11 HaALS genes were identified and classified into three phylogenetic clades (Groups A–C). All HaALS proteins contained the conserved TPP_enzyme domains (TPP_enzyme_N, TPP_enzyme_M, and TPP_enzyme_C), and purifying selection (Ka/Ks < 1) indicated strong evolutionary constraint on their core enzymatic function. Promoter analyses revealed abundant cis-regulatory elements associated with diverse stress and signaling inputs, supporting regulatory potential for herbicide-triggered transcriptional modulation. qRT-PCR analysis following imazethapyr application (0, 24, and 48 h) showed pronounced genotype-dependent expression reprogramming between the susceptible (S) and resistant (R) cultivars. In the R genotype, multiple HaALS members were strongly induced after treatment; specifically, HaALS4 reached a ~6-fold increase at 24 h and a >10-fold increase at 48 h, and HaALS11 increased to ~6–7-fold at 24 h while remaining above the baseline at 48 h; several additional paralogs exhibited intermediate induction (~3–8-fold by 48 h). In contrast, the S genotype showed limited changes (typically ~0.8–2-fold). Collectively, these findings define the evolutionary features of the sunflower HaALS family and identify herbicide-responsive paralogs that may contribute to imidazolinone tolerance, providing candidates for functional validation and molecular breeding. Full article

Urban water security in many cities in the Global South is increasingly challenged by ageing infrastructure and the presence of persistent chemical contaminants. This study investigated the Harare metropolitan water continuum between 2020 and 2024 using a longitudinal, systems-oriented observational framework encompassing wastewater discharge, surface water reservoirs, drinking water treatment, and municipal distribution networks. A three-stage approach was employed, comprising qualitative screening for selected pharmaceuticals at the Lake Chivero water–sediment interface in 2020, spatial assessment of physicochemical stability across the treatment and distribution system in 2021, and targeted qualitative evaluation of pharmaceutical and agrochemical occurrence in wastewater-impacted matrices in 2024. Sulfamethoxazole and trimethoprim were qualitatively identified using high-performance liquid chromatography (HPLC), while atrazine was confirmed by gas chromatography–mass spectrometry (GC–MS). These analyses indicated the continued presence of pharmaceutical and agrochemical residues within wastewater-impacted aquatic compartments associated with the Harare water supply. Physicochemical monitoring revealed elevated ammonia concentrations and reduced free residual chlorine across sections of the distribution network. These conditions coincided with detectable heterotrophic bacterial regrowth at distal consumer endpoints. Phenotypic antimicrobial susceptibility testing of bacterial isolates recovered at the source interface showed limited inhibition responses to sulfamethoxazole and trimethoprim under the experimental conditions used. While the observational nature of this study precludes causal inference, the co-occurrence of chemical residues, physicochemical instability, and bacterial isolates exhibiting reduced inhibition responses highlights conditions of potential relevance for antimicrobial resistance risk within wastewater-influenced urban water systems. These findings underscore the importance of integrated water management strategies addressing wastewater control, source water protection, and distribution system integrity within a One Health context. Full article

Freshwater is essential for sustaining the health of humans, animals, and ecosystems; however, agricultural activities remain a major source of water pollution globally. This review examines how crop production, livestock farming, and aquaculture contribute to water contamination, the effectiveness of current European policies, and the potential of sustainable mitigation strategies. Evidence from the research identified pesticides, herbicides, veterinary antibiotics, nutrient runoff, aquaculture effluents, and microplastics as the primary agricultural pollutants affecting surface and groundwater quality. These contaminants have been linked to ecosystem degradation, biodiversity loss, endocrine disruption, antimicrobial resistance, and adverse human health outcomes. Despite extensive regulatory frameworks, including the Water Framework Directive, Nitrates Directive, Farm to Fork Strategy, and European Green Deal, significant implementation and monitoring challenges remain. Current evidence indicates that only 40% of European surface waters achieve “good” ecological status, highlighting persistent water quality concerns across the region. The review further identified precision irrigation, Internet of Things (IoT)-enabled monitoring, biopesticides, hydroponic systems, and integrated multi-trophic aquaculture as promising solutions for reducing agricultural impacts on water resources. However, barriers, including high implementation costs, technological limitations, and inconsistent policy enforcement, continue to hinder widespread adoption. Overall, the findings demonstrate that while existing policies have improved water governance, stronger regulatory enforcement, greater investment in sustainable technologies, and increased adoption of nature-based solutions are required to reduce agricultural water pollution. An integrated approach combining technological innovation, policy support, and sustainable farming practices is essential to protect freshwater resources and ensure long-term environmental sustainability. Full article

2,4-Dichlorophenoxyacetic acid (2,4-D) is an extensively applied organic compound, primarily for agricultural weed control and plant growth agents. Although 2,4-D usually exists in the environment in low volumes, the detection of 2,4-D is critical for human health and environmental safety. In this work, a biophotonic biosensor was fabricated by coating the surface of a tapered optical fiber with gold nanoparticles (AuNPs) to excite the localized surface plasmon resonance (LSPR) and functionalizing the fiber with molybdenum disulfide nanosheets (MoS₂-NSs)/zinc oxide nanowires (ZnO-NWs) to extend the effective sensing area. Due to the inhibitory effect of 2,4-D on the hydrolytic activity of ALP, the refractive index (RI) around the sensor surface changes, leading to a shift in the LSPR peak wavelength. According to this sensing technique, the sensor can detect concentrations in the range of 1–10 mg/L, with a limit of detection (LOD) of 0.29 mg/L. The stability, repeatability and selectivity tests show that the sensor has good stability and selectivity. In the actual sample detection experiment, the recovery rates of apples and Chinese cabbage were 96.2–100.4% and 83.8–108.8%, respectively, which indicated that the detection method had good accuracy for the detection of target substances in actual samples. Thus, the proposed sensor has an important application in the detection of 2,4-D herbicides. Full article