Search Results (174)

The phytohormone abscisic acid (ABA) plays a central role in organizing adaptive responses in plants to various abiotic stresses, helping the plant minimize the negative impact on growth and development. Rapid and direct detection of ABA is valuable for investigating plant responses to abiotic stress. In this work, we propose a novel label-free, non-competitive immunoassay for detecting and quantifying ABA easily and rapidly using a surface plasmon resonance (SPR) biosensor. The SPR sensor chip was functionalized with a commercial anti-ABA antibody, characterized for its affinity, binding kinetics, and specificity using the same platform. The direct assay demonstrated high specificity and sensitivity, with a calculated limit of detection of 1.36 ng/mL in buffer. The new immunosensor was applied to determine ABA concentrations directly in xylem sap samples from tomato plants subjected to abiotic stress (drought and high salinity) and was able to accurately reflect ABA levels corresponding to the applied stress. The results were comparable to the reference method, ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS), establishing this new immunosensor as a novel detection method for rapid and reliable monitoring of ABA levels associated with abiotic stress in tomato plants. Full article

Salicylic acid (SA) is a key phytohormone that coordinates plant innate immunity and systemic acquired resistance. Because SA levels and signaling are highly dynamic in space and time, a suite of SA-focused tools, including SA-specific microbial biosensors and SA-responsive transcriptional and chemical reporters, has been developed to study them. This review compares three classes of tools in terms of sensitivity, specificity, temporal resolution, invasiveness, quantifiability, and suitability across species. We describe developing genetically encoded sensors that can directly sense salicylic acid and report it, for example, via a fluorescence resonance energy transfer signal or another real-time output. We offer recommendations on method selection by research goal and plant species, as well as combined protocols (long-term autoluminescence plus local probes/biosensors) for cross-validation. Future work should prioritize substrate-free, quantitative SA reporters deployable in crops and the field; coupled with CRISPR-based editing and screening, these tools would enable reporter-guided discovery of immunity genes and rapid engineering of durable disease resistance. Full article

Phosphate (Pi) is a vital macronutrient for plant growth and development, and precise monitoring of its cellular dynamics is essential to understanding Pi homeostasis and its interaction with stress responses. Genetically encoded FRET-based biosensors such as FLIPPi enable real-time, non-invasive visualization of cytosolic Pi levels in living tissues. In this study, Arabidopsis and rice lines expressing a FLIPPi biosensor were used to monitor cytosolic Pi dynamics in root epidermal cells. Sensor functionality was confirmed by measuring FRET responses to graded Pi supplies, revealing a consistent reduction in FRET ratios with increasing Pi concentrations, reflecting elevated cytosolic Pi levels. Comparisons with a Pi-insensitive FLIPPi variant confirmed the specificity of the observed changes. Furthermore, live imaging demonstrated rapid and dynamic alterations in cytosolic Pi upon treatment with defense-related hormones and elicitors of immune responses supporting a link between Pi signaling and plant immunity. Finally, the application of phosphite, an analog of Pi, altered Pi dynamics in both Arabidopsis and rice, suggesting an interference with Pi accumulation. Collectively, our findings establish FLIPPi as a reliable tool for in vivo monitoring of Pi in Arabidopsis and rice plants, the model systems for studies in dicotyledonous and monocotyledonous species, respectively. Full article

Deoxyribonucleic acid (DNA)-based biosensors are rapid, cost-effective, and portable devices for monitoring crop pathogens. However, their on-field operations rely on a laboratory-bound heating block, which controls temperature during sample preparation. This study aimed to develop a field-deployable heating block to assist in the DNA hybridization protocol of DNA-based biosensors. It should maintain $95 °\mathrm{C}$, $55 °\mathrm{C}$, and $20 °\mathrm{C}$ for 5, 10, and 5 min, respectively. It had aluminum bars, positive thermal coefficient ceramic heaters, a Peltier thermoelectric module, and DS18B20 thermistors, serving twelve 0.2 mL polymerase chain reaction (PCR) tubes. An Arduino microcontroller employing a proportional–integral–derivative (PID) algorithm with a solid-state relay was utilized. Machine performance for distilled water-filled PCR tubes showed a maximum $10 °\mathrm{C}$ thermal variation. The machine maintained $(96.00\pm 0.97) °\mathrm{C}$, $(55.15\pm 2.17) °\mathrm{C}$, and $(17.75\pm 0.71) °\mathrm{C}$ with root mean square errors (RMSEs) of $1.40 °\mathrm{C}$, $2.18 °\mathrm{C}$, and $2.36 °\mathrm{C}$, respectively. The average thermal rates were $(0.16\pm 0.11) °\mathrm{C}/\mathrm{s}$, $(0.29\pm 0.11) °\mathrm{C}/\mathrm{s}$, and $(0.14\pm 0.07) °\mathrm{C}/\mathrm{s}$ from ambient to $95 °\mathrm{C}$, $95 °\mathrm{C}$ to $55 °\mathrm{C}$, and $55 °\mathrm{C}$ to $20 °\mathrm{C}$, respectively. Overall, the low standard deviations and RMSEs demonstrate thermostable results and robust temperature control. Full article

The valorization of agricultural by-products represents a sustainable strategy to reduce waste and create high-value biotechnological products. This review highlights Colombian plant-derived peroxidases (PODs) obtained from Guinea grass, royal palm, African oil palm, lemongrass, sleepy plant, and sweet potato. These enzymes catalyze oxidative reactions and show potential in biosensing, polymer synthesis, environmental remediation, and health monitoring. We summarize extraction and purification strategies while addressing current challenges such as operational stability, scalability, and cost. Special emphasis is given to applications like cross-linked enzymatic aggregates (CLEAs) and electrochemical biosensors, where Colombian PODs demonstrate superior stability and sensitivity compared to horseradish peroxidase (HRP). This review frames these advances within the circular bioeconomy, presenting insights into waste reduction and CO₂ savings. By integrating local biodiversity into innovative processes, Colombian PODs can drive sustainable technologies and provide industrial and environmental solutions. Full article

The global need for tissue and organ transplantation paved the way for plant-based scaffolds as cheap, ethical, and valuable alternatives to synthetic and animal-derived matrices for tissue regeneration. Over the years, the field has outgrown its initial scope, including the development of tissue models, platforms for drug testing and delivery, biosensors, and laboratory-grown meat. In this scoping review, we aimed to shed light on the frequency of the use of different plant matrices, the main techniques for decellularization, the functionalization methods for stimulating mammalian cell attachment, and the main results. To that purpose, we searched the keywords “decellularized” AND “scaffold” AND (“plant” OR “vegetable”) in online-available databases (Science Direct, Scopus, PubMed, and Sage Journals). From the selection and study of 71 articles, we observed a multitude of plant sources and tissues, along with a large and inhomogeneous body of protocols used for decellularization, functionalization and recellularization of plant matrices, which all led to variable results, with different extents of success (mostly in vitro). Since the field of plant-based scaffolds shows high potential for growth in the next few years, driven by emerging biotechnological applications, we conclude that future research should focus on plant sources with low economic and environmental impacts while also pursuing the standardization of the methods involved and a much deeper characterization of the scaffold performance in vivo. Full article

Plant-derived toxins such as ricin and abrin represent some of the most potent biological agents known, posing significant threats to public health and security due to their high toxicity, relative ease of extraction, and widespread availability. These ribosome-inactivating proteins (RIPs) have been implicated in politically and criminally motivated events, underscoring their critical importance in the context of biodefense. Public safety agencies, including law enforcement, customs, and emergency response units, require rapid, sensitive, and portable detection methods to effectively counteract these threats. However, many existing screening technologies lack the capability to detect biotoxins unless specifically designed for this purpose, revealing a critical gap in current biodefense preparedness. Consequently, there is an urgent need for robust, field-deployable detection platforms that operate reliably under real-world conditions. End-users in the security and public health sectors demand analytical tools that combine high specificity and sensitivity with operational ease and adaptability. This review provides a comprehensive overview of the biochemical characteristics of ricin and abrin, their documented misuse, and the challenges associated with their detection. Furthermore, it critically assesses key detection platforms—including immunoassays, mass spectrometry, biosensors, and lateral flow assays—focusing on their applicability in operational environments. Advancing detection capabilities within frontline services is imperative for effective prevention, timely intervention, and the strengthening of biosecurity measures. Full article

Recent advances in plant electrophysiology and machine learning suggest that bioelectric signals in plants may encode environmentally relevant information beyond physiological processes. In this study, we present a novel framework to analyse waveforms from real-time bioelectrical potentials recorded in vascular plants. Using a multi-channel electrophysiological monitoring system, we acquired continuous data from Vitis vinifera samples in a vineyard plantation under natural conditions. Plants were in different health conditions: healthy; under the infection of Flavescence dorée; plants in recovery from the same disease; and dead stumps. These signals were used as input features for an ensemble of complex machine learning models, including recurrent neural networks, trained to infer short-term meteorological parameters such as temperature and humidity. The models demonstrated predictive capabilities, with accuracy comparable to sensor-based benchmarks between one and two degree Celsius for temperature, particularly in forecasting rapid weather transitions. Feature importance analysis revealed plant-specific electrophysiological patterns that correlated with ambient conditions, suggesting the existence of biological pre-processing mechanisms sensitive to microclimatic fluctuations. This bioinspired approach opens new directions for developing plant-integrated environmental intelligence systems, offering passive and biologically rooted strategies for ultra-local forecasting—especially valuable in remote, sensor-sparse, or climate-sensitive regions. Our findings contribute to the emerging field of plant-based sensing and biomimetic environmental monitoring, expanding the role of flora to biosensors, useful in Earth system observation tasks. Full article

Crop pathogens threaten global agriculture by causing severe yield and economic losses. Conventional detection methods are often slow and inaccurate, limiting timely intervention. This study introduces a pentagon-shaped terahertz photonic crystal fiber (THz PCF) biosensor, optimized with the decision cascaded 3D return dilated secretary-bird aligned convolutional transformer network (DC3D-SBA-CTN). The biosensor is designed to detect a broad spectrum of pathogens, including fungi (e.g., Fusarium spp.) and bacteria (e.g., Xanthomonas spp.), by identifying their unique refractive index signatures. Integrating advanced neural networks and optimization algorithms, the biosensor achieves a detection accuracy of 99.87%, precision of 99.65%, sensitivity of 99.77%, and specificity of 99.83%, as validated by a 5-fold cross-validation protocol. It offers high sensitivity (up to 7340 RIU⁻¹), low signal loss, and robust performance against morphological variations, making it adaptable for diverse agricultural settings. This innovation enables rapid, precise monitoring of crop pathogens, revolutionizing plant disease management. Full article

The early determination of the type and severity of stresses caused by nutrient deficiency is necessary for taking timely measures and preventing a remarkable yield reduction. This study is an effort to investigate the performance of a machine learning-based model that identifies the type and severity of nitrogen, phosphorus, potassium, and sulfur in rice plants by using the plant microRNA data as model inputs. The concentration of 14 microRNA compounds in plants exposed to nutrient deficiency was measured using an electrochemical biosensor based on the peak currents produced during the probe–target microRNA hybridization. Subsequently, several machine learning models were utilized to predict the type and severity of stress. According to the results, the biosensor used in this work exerted promising analytical performance, including linear range (10⁻¹⁹ to 10⁻¹¹ M), limit of detection (3 × 10⁻²¹ M), and reproducibility during microRNA measurement in total RNA extracted from rice plant samples. Among the microRNAs studied, miRNA167, miRNA162, miRNA169, and miRNA395 exerted the largest contribution in predicting the nutrient deficiency levels based on feature selection methods. Using these four microRNAs as model inputs, the random forest with hyperparameters optimized by the genetic algorithm was capable of detecting the type of nutrient deficiency with an average accuracy, precision, and recall of 0.86, 0.94, and 0.87, respectively, seven days after the application of the nutrient treatment. Within this period, the optimized machine was able to detect the level of deficiency with average MSE and R² of 0.010 and 0.92, respectively. Combining the findings of this study and the results we reported earlier on determining the occurrence of salinity, drought, and heat in rice plants using microRNA biosensors can be useful to develop smart biosensing platforms for efficient plant health monitoring systems. Full article

Electrochemical biosensors have emerged as a promising tool for the early detection of diseases in oilseed crops such as rapeseed, soybean, and peanut. These biosensors offer high sensitivity, portability, and cost-effectiveness. Timely diagnosis is critical, as many pathogens exhibit latent infection phases or produce invisible metabolic toxins, leading to substantial yield losses before visible symptoms occur. This review summarises recent advances in the field of nanomaterial-assisted electrochemical sensing for oilseed crop diseases, with a particular focus on sensor mechanisms, interface engineering, and biomolecular recognition strategies. The following innovations are highlighted: nanostructured electrodes, aptamer- and antibody-based probes, and signal amplification techniques. These innovations have enabled the detection of pathogen DNA, enzymes, and toxins at ultra-low concentrations. Notwithstanding these achievements, challenges persist, including signal interference from plant matrices, limitations in device miniaturization, and the absence of standardized detection protocols. Future research should explore the potential of AI-assisted data interpretation, the use of biodegradable sensor materials, and the integration of these technologies with agricultural IoT networks. The aim of this integration is to enable real-time, field-deployable disease surveillance. The integration of laboratory innovations with field applications has been demonstrated to have significant potential in supporting sustainable agriculture and strengthening food security through intelligent crop health monitoring. Full article

Microneedles have emerged as a versatile technology for biosensing across biomedical domains and are increasingly being explored for other applications like agriculture. This review highlights recent advancements in the development of microneedle-based biosensors in novel areas. Biomedical applications include continuous glucose monitoring, multiplexed biomarker detection beyond glucose, and numerous recent works presenting fully integrated systems comprising microneedle arrays alongside miniaturized wearable electronics. Agricultural applications largely focus on the detection of plant growth markers, hormones, and nutrient levels. Despite significant progress, challenges remain in overcoming biofouling and electrode degradation, optimizing electrode longevity for long-term (weeks to months) in situ monitoring, and creating scalable sensor fabrication processes. Additionally, there is a need for standardized mechanical and electrical testing protocols, and guidelines specifying critical performance metrics that should be reported to facilitate accurate literature comparisons. The review concludes by outlining key opportunities for future research to address these persisting challenges. Full article

Early and accurate detection of plant diseases is critical for ensuring global food security and agricultural resilience. Ratoon stunting disease (RSD), caused by the bacterium Leifsonia xyli subsp. xyli (Lxx), is among the most economically significant diseases of sugarcane worldwide. Its cryptic nature—characterized by an absence of visible symptoms—renders timely diagnosis particularly difficult, contributing to substantial undetected yield losses across major sugar-producing regions. Here, we report the development of a potential-induced electrochemical (EC) nanobiosensor platform for the rapid, low-cost, and field-deployable detection of Lxx DNA directly from crude sugarcane sap. This method eliminates the need for conventional nucleic acid extraction and thermal cycling by integrating the following: (i) a boiling lysis-based DNA release from xylem sap; (ii) sequence-specific magnetic bead-based purification of Lxx DNA using immobilized capture probes; and (iii) label-free electrochemical detection using a potential-driven DNA adsorption sensing platform. The biosensor shows exceptional analytical performance, achieving a detection limit of 10 cells/µL with a broad dynamic range spanning from 10⁵ to 1 copy/µL (r = 0.99) and high reproducibility (SD < 5%, n = 3). Field validation using genetically diverse sugarcane cultivars from an inoculated trial demonstrated a strong correlation between biosensor signals and known disease resistance ratings. Quantitative results from the EC biosensor also showed a robust correlation with qPCR data (r = 0.84, n = 10, p < 0.001), confirming diagnostic accuracy. This first-in-class EC nanobiosensor for RSD represents a major technological advance over existing methods by offering a cost-effective, equipment-free, and scalable solution suitable for on-site deployment by non-specialist users. Beyond sugarcane, the modular nature of this detection platform opens up opportunities for multiplexed detection of plant pathogens, making it a transformative tool for early disease surveillance, precision agriculture, and biosecurity monitoring. This work lays the foundation for the development of a universal point-of-care platform for managing plant and crop diseases, supporting sustainable agriculture and global food resilience in the face of climate and pathogen threats. Full article

Antimicrobial resistance (AMR) has emerged as a planetary health emergency, driven not only by the clinical misuse of antibiotics but also by diverse environmental dissemination pathways. This review critically examines the role of environmental compartments—water, soil, and air—as dynamic reservoirs and transmission routes for antibiotic-resistant bacteria (ARB) and resistance genes (ARGs). Recent metagenomic, epidemiological, and mechanistic evidence demonstrates that anthropogenic pressures—including pharmaceutical effluents, agricultural runoff, untreated sewage, and airborne emissions—amplify resistance evolution and interspecies gene transfer via horizontal gene transfer mechanisms, biofilms, and mobile genetic elements. Importantly, it is not only highly polluted rivers such as the Ganges that contribute to the spread of AMR; even low concentrations of antibiotics and their metabolites, formed during or after treatment, can significantly promote the selection and dissemination of resistance. Environmental hotspots such as European agricultural soils and airborne particulate zones near wastewater treatment plants further illustrate the complexity and global scope of pollution-driven AMR. The synergistic roles of co-selective agents, including heavy metals, disinfectants, and microplastics, are highlighted for their impact in exacerbating resistance gene propagation across ecological and geographical boundaries. The efficacy and limitations of current mitigation strategies, including advanced wastewater treatments, thermophilic composting, biosensor-based surveillance, and emerging regulatory frameworks, are evaluated. By integrating a One Health perspective, this review underscores the imperative of including environmental considerations in global AMR containment policies and proposes a multidisciplinary roadmap to mitigate resistance spread across interconnected human, animal, and environmental domains. Full article

Polyphenol oxidase (PPO) is a metalloproteinase widely present in plant organelles that plays crucial roles in photosynthesis, pest and disease resistance, growth and development, and flower color formation. Due to the high cost and reuse difficulties of plant PPO in applications, immobilization has emerged as a key technology to improve its stability, recyclability, and reusability. Immobilized plant PPO has been widely used in environmental and detection fields. This review examines different immobilization methods and carrier materials for plant PPO and summarizes its applications in wastewater treatment, biosensor detection, food preservation, and theaflavin synthesis. Finally, current challenges and future opportunities for immobilized plant PPO are discussed. Full article