Soil Sensors and Plant Wearables for Smart and Precision Agriculture

Interaction of plants and metal nanoparticles: Exploring its molecular mechanisms for sustainable agriculture and crop improvement

Metal nanoparticles offer promising prospects in agriculture, enhancing plant growth and ensuring food security. Silver, gold, copper, and zinc nanoparticles possess unique properties making them attractive for plant applications. Understanding molecular interactions between metal nanoparticles and plants is crucial for unlocking their potential to boost crop productivity and sustainability. This review explores metal nanoparticles in agriculture, emphasizing the need to understand these interactions. By elucidating mechanisms, it highlights the potential for enhancing crop productivity, stress tolerance, and nutrient-use efficiency, contributing to sustainable agriculture and food security. Quantifying benefits and risks reveal significant advantages. Metal nanoparticles enhance crop productivity by 20% on average and reduce disease incidence by up to 50% when used as antimicrobial agents. They also reduce nutrient leaching by 30% and enhance soil carbon sequestration by 15%, but concerns about toxicity, adverse effects on non-target organisms, and nanoparticle accumulation in the food chain must be addressed. Metal nanoparticles influence cellular processes including sensing, signaling, transcription, translation, and post-translational modifications. They act as signaling molecules, activate stress-responsive genes, enhance defense mechanisms, and improve nutrient uptake. The review explores their catalytic role in nutrient management, disease control, precision agriculture, nano-fertilizers, and nano-remediation. A bibliometric analysis offers insights into the current research landscape, highlighting trends, gaps, and future directions. In conclusion, metal nanoparticles hold potential for revolutionizing agriculture, enhancing productivity, mitigating environmental stressors, and promoting sustainability. Addressing risks and gaps is crucial for their safe integration into agricultural practices.

Wearable sensor supports in-situ and continuous monitoring of plant health in precision agriculture era

Plant health is intricately linked to crop quality, food security and agricultural productivity. Obtaining accurate plant health information is of paramount importance in the realm of precision agriculture. Wearable sensors offer an exceptional avenue for investigating plant health status and fundamental plant science, as they enable real-time and continuous in-situ monitoring of physiological biomarkers. However, a comprehensive overview that integrates and critically assesses wearable plant sensors across various facets, including their fundamental elements, classification, design, sensing mechanism, fabrication, characterization and application, remains elusive. In this study, we provide a meticulous description and systematic synthesis of recent research progress in wearable sensor properties, technology and their application in monitoring plant health information. This work endeavours to serve as a guiding resource for the utilization of wearable plant sensors, empowering the advancement of plant health within the precision agriculture paradigm.

Flexible wearable sensors for crop monitoring: a review

Crops were the main source of human food, which have met the increasingly diversified demand of consumers. Sensors were used to monitor crop phenotypes and environmental information in real time, which will provide a theoretical reference for optimizing crop growth environment, resisting biotic and abiotic stresses, and improve crop yield. Compared with non-contact monitoring methods such as optical imaging and remote sensing, wearable sensing technology had higher time and spatial resolution. However, the existing crop sensors were mainly rigid mechanical structures, which were easy to cause damage to crop organs, and there were still challenges in terms of accuracy and biosafety. Emerging flexible sensors had attracted wide attention in the field of crop phenotype monitoring due to their excellent mechanical properties and biocompatibility. The article introduced the key technologies involved in the preparation of flexible wearable sensors from the aspects of flexible preparation materials and advanced preparation processes. The monitoring function of flexible sensors in crop growth was highlighted, including the monitoring of crop nutrient, physiological, ecological and growth environment information. The monitoring principle, performance together with pros and cons of each sensor were analyzed. Furthermore, the future opportunities and challenges of flexible wearable devices in crop monitoring were discussed in detail from the aspects of new sensing theory, sensing materials, sensing structures, wireless power supply technology and agricultural sensor network, which will provide reference for smart agricultural management system based on crop flexible sensors, and realize efficient management of agricultural production and resources.

Digital Twins in Agriculture: Orchestration and Applications

Digital Twins have emerged as an outstanding opportunity for precision farming, digitally replicating in real-time the functionalities of objects and plants. A virtual replica of the crop, including key agronomic development aspects such as irrigation, optimal fertilization strategies, and pest management, can support decision-making and a step change in farm management, increasing overall sustainability and direct water, fertilizer, and pesticide savings. In this review, Digital Twin technology is critically reviewed and framed in the context of recent advances in precision agriculture and Agriculture 4.0. The review is organized for each step of agricultural lifecycle, edaphic, phytotechnologic, postharvest, and farm infrastructure, with supporting case studies demonstrating direct benefits for agriculture production and supply chain considering both benefits and limitations of such an approach. Challenges and limitations are disclosed regarding the complexity of managing such an amount of data and a multitude of (often) simultaneous operations and supports.

Underground Ink: Printed Electronics Enabling Electrochemical Sensing in Soil

Improving agricultural production relies on the decisions and actions of farmers and land managers, highlighting the importance of efficient soil monitoring techniques for better resource management and reduced environmental impacts. Despite considerable advancements in soil sensors, their traditional bulky counterparts cause difficulty in widespread adoption and large-scale deployment. Printed electronics emerge as a promising technology, offering flexibility in device design, cost-effectiveness for mass production, and a compact footprint suitable for versatile deployment platforms. This review overviews how printed sensors are used in monitoring soil parameters through electrochemical sensing mechanisms, enabling direct measurement of nutrients, moisture content, pH value, and others. Notably, printed sensors address scalability and cost concerns in fabrication, making them suitable for deployment across large crop fields. Additionally, seamlessly integrating printed sensors with printed antenna units or traditional integrated circuits can facilitate comprehensive functionality for real-time data collection and communication. This real-time information empowers informed decision-making, optimizes resource management, and enhances crop yield. This review aims to provide a comprehensive overview of recent work related to printed electrochemical soil sensors, ultimately providing insight into future research directions that can enable widespread adoption of precision agriculture technologies.

PCB-C4D coupled with paper-based microfluidic sampling for the rapid detection of liquid conductivity

The detection of liquid electrical conductivity has board applications in food safety testing, water quality monitoring, and agricultural soil analysis. Electrodes used in traditional liquid electrical conductivity detection come into direct contact with liquid, leading to electrode contamination and affecting the accuracy of the detection results. The capacitively coupled contactless conductivity detection (C4D) method effectively addresses this issue. However, impurity particles present in the solution can compromise the consistency and repeatability of detection results. This study combines paper-based microfluidic technology with printed circuit board-capacitively coupled contactless conductivity detection (PCB-C4D) to address this issue. Prior to sample detection, in situ rapid filtration is employed to remove impurity particles from the raw solution sample, significantly enhancing detection consistency and reliability. Simultaneously, Optimization of PCB-C4D parameters, channel size, filtration time, and solution drop rate ensures optimal detection conditions. A compact kit design facilitates reliable assembly of the PCB-C4D electrodes and paper-based channel, enhancing practicality. Practical measurements on the conductivity of orange juice, cucumber, and soil solution further validate the method's accuracy, rapidity, and effectiveness in in situ conductivity detection. This work advances the practical application of PCB-C4D technology.

Zeolitic Imidazolate-Framework-Engineered Heterointerface Catalysis for the Construction of Plant-Wearable Sensors

Plant-wearable sensors provide real-time information that enables pesticide inputs to be finely tuned and play critical roles in precision agriculture. However, tracking pesticide information in living plants remains a formidable challenge owing to inadequate shape adaptabilities and low in-field sensor sensitivities. In this study, plant-wearable hydrogel discs are designed by embedding a dual-shelled upconversion-nanoparticles@zeolitic-imidazolate-framework@polydopamine (UCNPs@ZIF@PDA) composite in double-network hydrogels to deliver on-site pesticide-residue information. Benefiting from the enzyme-mimetic catalytic activity of ZIFs and enzyme triggered-responsive property of PDA shell, the hydrogel discs are endowed with high sensing sensitivity toward 2,4-dichlorophenoxyacetic acid pesticide at the nanogram per milliliter level via boosting fluorescence quenching efficiency. Notably, hydrogel discs mounted on tomato plants exhibit sufficient adaptability to profile dynamic pesticide degradation when used in conjunction with an ImageJ processing algorithm, which is practically applicable. Such hydrogel discs form a noninvasive and low-cost toolkit for the on-site acquisition of pesticide information, thereby contributing to the precise management of the health status of a plant and the judicious development of precision agriculture.

A Roadmap from Functional Materials to Plant Health Monitoring (PHM)

Soft bioelectronics have great potential for the early diagnosis of plant diseases and the mitigation of adverse outcomes such as reduced crop yields and stunted growth. Over the past decade, bioelectronic interfaces have evolved into miniaturized conformal electronic devices that integrate flexible monitoring systems with advanced electronic functionality. This development is largely attributable to advances in materials science, and micro/nanofabrication technology. The approach uses the mechanical and electronic properties of functional materials (polymer substrates and sensing elements) to create interfaces for plant monitoring. In addition to ensuring biocompatibility, several other factors need to be considered when developing these interfaces. These include the choice of materials, fabrication techniques, precision, electrical performance, and mechanical stability. In this review, some of the benefits plants can derive from several of the materials used to develop soft bioelectronic interfaces are discussed. The article describes how they can be used to create biocompatible monitoring devices that can enhance plant growth and health. Evaluation of these devices also takes into account features that ensure their long-term durability, sensitivity, and reliability. This article concludes with a discussion of the development of reliable soft bioelectronic systems for plants, which has the potential to advance the field of bioelectronics.

Building Feedback-Regulation System Through Atomic Design for Highly Active SO2 Sensing

Reasonably constructing an atomic interface is pronouncedly essential for surface-related gas-sensing reaction. Herein, we present an ingenious feedback-regulation system by changing the interactional mode between single Pt atoms and adjacent S species for high-efficiency SO2 sensing. We found that the single Pt sites on the MoS2 surface can induce easier volatilization of adjacent S species to activate the whole inert S plane. Reversely, the activated S species can provide a feedback role in tailoring the antibonding-orbital electronic occupancy state of Pt atoms, thus creating a combined system involving S vacancy-assisted single Pt sites (Pt-Vs) to synergistically improve the adsorption ability of SO2 gas molecules. Furthermore, in situ Raman, ex situ X-ray photoelectron spectroscopy testing and density functional theory analysis demonstrate the intact feedback-regulation system can expand the electron transfer path from single Pt sites to whole Pt-MoS2 supports in SO2 gas atmosphere. Equipped with wireless-sensing modules, the final Pt1-MoS2-def sensors array can further realize real-time monitoring of SO2 levels and cloud-data storage for plant growth. Such a fundamental understanding of the intrinsic link between atomic interface and sensing mechanism is thus expected to broaden the rational design of highly effective gas sensors.

All-organic transparent plant e-skin for noninvasive phenotyping

Real-time in situ monitoring of plant physiology is essential for establishing a phenotyping platform for precision agriculture. A key enabler for this monitoring is a device that can be noninvasively attached to plants and transduce their physiological status into digital data. Here, we report an all-organic transparent plant e-skin by micropatterning poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) on polydimethylsiloxane (PDMS) substrate. This plant e-skin is optically and mechanically invisible to plants with no observable adverse effects to plant health. We demonstrate the capabilities of our plant e-skins as strain and temperature sensors, with the application to Brassica rapa leaves for collecting corresponding parameters under normal and abiotic stress conditions. Strains imposed on the leaf surface during growth as well as diurnal fluctuation of surface temperature were captured. We further present a digital-twin interface to visualize real-time plant surface environment, providing an intuitive and vivid platform for plant phenotyping.

Recent advances of microneedles biosensors for plants

As the lack of plants can affect the energy operation of the entire ecosystem, monitoring and improving the health status of plants is crucial. However, ordinary biosensing platforms lack accuracy and timeliness in monitoring plant growth status. In addition, the prevention and control of plant diseases often involve spraying and administering drugs, which is inefficient and prone to pollution. Microneedles have unique dimensions and shapes, and they have significant advantages as biosensors in the fields of sensing, detection, and drug delivery. Recent evidence suggests that microneedle biosensors can become effective tools for plant diagnosis and treatment. In this review, the comprehensive development of the application of microneedle biosensors in the field of plants is introduced, as well as their manufacturing processes and sensing and detection functions. Furthermore, the application of microneedle biosensors in this field is discussed, and future development directions are proposed.

A Leaf-Patchable Reflectance Meter for In Situ Continuous Monitoring of Chlorophyll Content

Plant wearable sensors facilitate the real-time monitoring of plant physiological status. In situ monitoring of the plant chlorophyll content over days can provide valuable information on the photosynthetic capacity, nitrogen content, and general plant health. However, it cannot be achieved by current chlorophyll measuring methods. Here, a miniaturized and plant-wearable chlorophyll meter for rapid, non-destructive, in situ, and long-term chlorophyll monitoring is developed. The reflectance-based chlorophyll sensor with 1.5 mm thickness and 0.2 g weight (1000 times lighter than the commercial chlorophyll meter), includes a light emitting diode (LED) and two symmetric photodetectors (PDs) on a flexible substrate, and is patched onto the leaf upper epidermis with a conformal light guiding layer. A chlorophyll content index (CCI) calculated based on the sensor shows a better linear relationship with the leaf chlorophyll content (r2 > 0.9) than the traditional chlorophyll meter. This meter can wirelessly communicate with a smartphone to monitor the leaf chlorophyll change under various stresses and indicate the unhealthy status of plants for long-term application of plants under various stresses earlier than chlorophyll meter and naked-eye observation. This wearable chlorophyll sensing patch is promising in smart and precision agriculture.

On the rise: Development of a multi-tiered, indoor duckweed cultivation system

Duckweed species (Lemnaceae) are suitable for remediation and valorization of agri-feed industry wastewaters and therefore can contribute to a more sustainable, circular economy where waste is a resource. Industrial applications will, however, require space efficient cultivation methods that are not affected by prevailing weather conditions. Here, the development and operation of a multi-tiered duckweed bioreactor is described. The developed prototype bioreactor depicted in this paper is composed of four cultivation layers (1 m2 each) with integrated LED lighting (generating up to 150 μmol m-2  s-1 ), a system of pumps and valves to manage the recirculatory flow (2.5 L min-1 ) of wastewater, and an automatic harvesting system. Using a nutrient poor medium, good growth of the duckweed species Lemna minor was achieved in the bioreactor, and this was matched by strong nutrient depletion from the medium, especially for phosphorus (45-mg total phosphorus [TP] removed per m-2  day-1 ). A fully automatic harvesting arm reliably captured similar amounts of duckweed biomass across multiple harvesting cycles, revealing a future scenario whereby labor and interventions by human operators are minimized. Further developments to advance the system towards fully automated operation will include, for example, the use of specific nutrient sensors to monitor and control medium composition. It is envisaged that multi-tiered, indoor bioreactors can be employed in the agri-feed industry where wastewaters are, in many cases, continuously generated throughout the year and need remediating immediately to avoid costly storage. Given the extensive use of automation technology in conventional wastewater treatment plants, multi-tiered duckweed bioreactors can be realistically integrated within the operating environment of such treatment plants. PRACTITIONER POINTS: Duckweed is suitable for remediation and valorization of agri-feed wastewater. Industrial duckweed applications require space efficient cultivation methods. Development and operation of a multi-tiered duckweed bioreactor is detailed. Flow dynamics and automatic harvesting in the bioreactor are optimized. It is concluded that a multi-tiered bioreactor can be used in industry.

Field Plant Monitoring from Macro to Micro Scale: Feasibility and Validation of Combined Field Monitoring Approaches from Remote to in Vivo to Cope with Drought Stress in Tomato

Monitoring plant growth and development during cultivation to optimize resource use efficiency is crucial to achieve an increased sustainability of agriculture systems and ensure food security. In this study, we compared field monitoring approaches from the macro to micro scale with the aim of developing novel in vivo tools for field phenotyping and advancing the efficiency of drought stress detection at the field level. To this end, we tested different methodologies in the monitoring of tomato growth under different water regimes: (i) micro-scale (inserted in the plant stem) real-time monitoring with an organic electrochemical transistor (OECT)-based sensor, namely a bioristor, that enables continuous monitoring of the plant; (ii) medium-scale (<1 m from the canopy) monitoring through red-green-blue (RGB) low-cost imaging; (iii) macro-scale multispectral and thermal monitoring using an unmanned aerial vehicle (UAV). High correlations between aerial and proximal remote sensing were found with chlorophyll-related indices, although at specific time points (NDVI and NDRE with GGA and SPAD). The ion concentration and allocation monitored by the index R of the bioristor during the drought defense response were highly correlated with the water use indices (Crop Water Stress Index (CSWI), relative water content (RWC), vapor pressure deficit (VPD)). A high negative correlation was observed with the CWSI and, in turn, with the RWC. Although proximal remote sensing measurements correlated well with water stress indices, vegetation indices provide information about the crop's status at a specific moment. Meanwhile, the bioristor continuously monitors the ion movements and the correlated water use during plant growth and development, making this tool a promising device for field monitoring.

IoT-Based Agro-Toolbox for Soil Analysis and Environmental Monitoring

The agricultural sector faces numerous challenges in ensuring optimal soil health and environmental conditions for sustainable crop production. Traditional soil analysis methods are often time-consuming and labor-intensive, and provide limited real-time data, making it challenging for farmers to make informed decisions. In recent years, Internet of Things (IoT) technology has emerged as a promising solution to address these challenges by enabling efficient and automated soil analysis and environmental monitoring. This paper presents a 3D-printed IoT-based Agro-toolbox, designed for comprehensive soil analysis and environmental monitoring in the agricultural domain. The toolbox integrates various sensors for both soil and environmental measurements. By deploying this tool across fields, farmers can continuously monitor key soil parameters, including pH levels, moisture content, and temperature. Additionally, environmental factors such as ambient temperature, humidity, intensity of visible light, and barometric pressure can be monitored to assess the overall health of agricultural ecosystems. To evaluate the effectiveness of the Agro-toolbox, a case study was conducted in an aquaponics floating system with rocket, and benchmarking was performed using commercial tools that integrate sensors for soil temperature, moisture, and pH levels, as well as for air temperature, humidity, and intensity of visible light. The results showed that the Agro-toolbox had an acceptable error percentage, and it can be useful for agricultural applications.

A green compliant hand-held selective electrode device for monitoring active pharmaceuticals and the kinetics of their degradation

An in-line smartphone connected to a screen-printed selective electrode hand-held device was used to determine the concentration of distigmine bromide (DB) in its pure and dosage forms as well as its degradation kinetics by continuously measuring the change in the produced emf over time. The main objective, supported by the data presented, is to produce a highly reliable smartphone integrated selective sensor as a portable analyzer with potential high cloud connectivity combining a wide linear dynamic range, the fastest response time with the lowest limits of detection and quantitation while best integrating green analytical chemistry principles. The choice of ionophore used in this approach was guided by computation and the data obtained was compared with traditional analytical techniques. DB, for which there are no previously reported stability-indicating methods and for which four novel such methods are proposed here, was selected as a model drug for this work. At-line UV-spectrophotometry DB assay was obtained by measuring the difference between the spectra of the degradation product and the same concentration of intact drug. The degradation kinetics were studied by this method through tracking the decrease of DB absorbance and/or the increase of a generated degradation product signal over time. Off-line separation based HPLC and TLC stability-indicating methods for DB were also presented. All methods employed in this work were validated for accuracy, precision, specificity, repeatability, linearity, range, detection and quantification limits according to the ICH guidelines and were applied to the analysis of laboratory prepared mixtures as well as commercial products. While all methods proposed were shown to be highly reliable, the smartphone integrated selective sensor is highlighted as a portable analyzer with potential high cloud connectivity and was shown to combine a wide linear dynamic range, the fastest response time with the lowest limits of detection and quantitation while best integrating green analytical chemistry principles.

Glyphosate Separating and Sensing for Precision Agriculture and Environmental Protection in the Era of Smart Materials

The present article critically and comprehensively reviews the most recent reports on smart sensors for determining glyphosate (GLP), an active agent of GLP-based herbicides (GBHs) traditionally used in agriculture over the past decades. Commercialized in 1974, GBHs have now reached 350 million hectares of crops in over 140 countries with an annual turnover of 11 billion USD worldwide. However, rolling exploitation of GLP and GBHs in the last decades has led to environmental pollution, animal intoxication, bacterial resistance, and sustained occupational exposure of the herbicide of farm and companies' workers. Intoxication with these herbicides dysregulates the microbiome-gut-brain axis, cholinergic neurotransmission, and endocrine system, causing paralytic ileus, hyperkalemia, oliguria, pulmonary edema, and cardiogenic shock. Precision agriculture, i.e., an (information technology)-enhanced approach to crop management, including a site-specific determination of agrochemicals, derives from the benefits of smart materials (SMs), data science, and nanosensors. Those typically feature fluorescent molecularly imprinted polymers or immunochemical aptamer artificial receptors integrated with electrochemical transducers. Fabricated as portable or wearable lab-on-chips, smartphones, and soft robotics and connected with SM-based devices that provide machine learning algorithms and online databases, they integrate, process, analyze, and interpret massive amounts of spatiotemporal data in a user-friendly and decision-making manner. Exploited for the ultrasensitive determination of toxins, including GLP, they will become practical tools in farmlands and point-of-care testing. Expectedly, smart sensors can be used for personalized diagnostics, real-time water, food, soil, and air quality monitoring, site-specific herbicide management, and crop control.

Direct Synthesis of Ammonia from Nitrate on Amorphous Graphene with Near 100% Efficiency

Ammonia is an indispensable commodity in the agricultural and pharmaceutical industries. Direct nitrate-to-ammonia electroreduction is a decentralized route yet challenged by competing side reactions. Most catalysts are metal-based, and metal-free catalysts with high nitrate-to-ammonia conversion activity are rarely reported. Herein, it is shown that amorphous graphene synthesized by laser induction and comprising strained and disordered pentagons, hexagons, and heptagons can electrocatalyze the eight-electron reduction of NO₃ ^- to NH₃ with a Faradaic efficiency of ≈100% and an ammonia production rate of 2859 µg cm^-2 h^-1 at -0.93 V versus reversible hydrogen electrode. X-ray pair-distribution function analysis and electron microscopy reveal the unique molecular features of amorphous graphene that facilitate NO₃ ^- reduction. In situ Fourier transform infrared spectroscopy and theoretical calculations establish the critical role of these features in stabilizing the reaction intermediates via structural relaxation. The enhanced catalytic activity enables the implementation of flow electrolysis for the on-demand synthesis and release of ammonia with >70% selectivity, resulting in significantly increased yields and survival rates when applied to plant cultivation. The results of this study show significant promise for remediating nitrate-polluted water and completing the NO_x cycle.

Better richer than environmentally friendly? Describing preferences toward and factors affecting precision agriculture adoption in Italy

Precision agriculture is expected to support and strengthen the sustainability of food production. In spite of the demonstrated benefits of the application of Information Technology to improve agricultural practices, such as yield increase and input reduction, in Italy its adoption still lags behind. In order to understand limits of and perspectives on the adoption of such technologies, we conducted an explorative study. A survey with a choice experiment was carried out in Italy among 471 farmers and people interested in agricultural machinery and technologies. The results highlight how specific factors, such as excessive costs and lack of incentive policies, may limit the spread of precision agriculture. Conversely, the provision of adequate technical support would likely favor its adoption. Furthermore, latent class modeling was used to identify three segments of potential buyers: sustainability seekers; precision agriculture best features supporters; low emissions fans. Potential policy and market implications of this explorative study are discussed in the conclusion.

Emerging Frontiers in Nanotechnology for Precision Agriculture: Advancements, Hurdles and Prospects

This review article provides an extensive overview of the emerging frontiers of nanotechnology in precision agriculture, highlighting recent advancements, hurdles, and prospects. The benefits of nanotechnology in this field include the development of advanced nanomaterials for enhanced seed germination and micronutrient supply, along with the alleviation of biotic and abiotic stress. Further, nanotechnology-based fertilizers and pesticides can be delivered in lower dosages, which reduces environmental impacts and human health hazards. Another significant advantage lies in introducing cutting-edge nanodiagnostic systems and nanobiosensors that monitor soil quality parameters, plant diseases, and stress, all of which are critical for precision agriculture. Additionally, this technology has demonstrated potential in reducing agro-waste, synthesizing high-value products, and using methods and devices for tagging, monitoring, and tracking agroproducts. Alongside these developments, cloud computing and smartphone-based biosensors have emerged as crucial data collection and analysis tools. Finally, this review delves into the economic, legal, social, and risk implications of nanotechnology in agriculture, which must be thoroughly examined for the technology’s widespread adoption.

Rational Design of Cellulosic Triboelectric Materials for Self-Powered Wearable Electronics

With the rapid development of the Internet of Things and flexible electronic technologies, there is a growing demand for wireless, sustainable, multifunctional, and independently operating self-powered wearable devices. Nevertheless, structural flexibility, long operating time, and wearing comfort have become key requirements for the widespread adoption of wearable electronics. Triboelectric nanogenerators as a distributed energy harvesting technology have great potential for application development in wearable sensing. Compared with rigid electronics, cellulosic self-powered wearable electronics have significant advantages in terms of flexibility, breathability, and functionality. In this paper, the research progress of advanced cellulosic triboelectric materials for self-powered wearable electronics is reviewed. The interfacial characteristics of cellulose are introduced from the top-down, bottom-up, and interfacial characteristics of the composite material preparation process. Meanwhile, the modulation strategies of triboelectric properties of cellulosic triboelectric materials are presented. Furthermore, the design strategies of triboelectric materials such as surface functionalization, interfacial structure design, and vacuum-assisted self-assembly are systematically discussed. In particular, cellulosic self-powered wearable electronics in the fields of human energy harvesting, tactile sensing, health monitoring, human-machine interaction, and intelligent fire warning are outlined in detail. Finally, the current challenges and future development directions of cellulosic triboelectric materials for self-powered wearable electronics are discussed.

Abaxial leaf surface-mounted multimodal wearable sensor for continuous plant physiology monitoring

Wearable plant sensors hold tremendous potential for smart agriculture. We report a lower leaf surface-attached multimodal wearable sensor for continuous monitoring of plant physiology by tracking both biochemical and biophysical signals of the plant and its microenvironment. Sensors for detecting volatile organic compounds (VOCs), temperature, and humidity are integrated into a single platform. The abaxial leaf attachment position is selected on the basis of the stomata density to improve the sensor signal strength. This versatile platform enables various stress monitoring applications, ranging from tracking plant water loss to early detection of plant pathogens. A machine learning model was also developed to analyze multichannel sensor data for quantitative detection of tomato spotted wilt virus as early as 4 days after inoculation. The model also evaluates different sensor combinations for early disease detection and predicts that minimally three sensors are required including the VOC sensors.

Vanadium Oxide-Doped Laser-Induced Graphene Multi-Parameter Sensor to Decouple Soil Nitrogen Loss and Temperature

Monitoring nitrogen utilization efficiency and soil temperature in agricultural systems for timely intervention is essential for crop health with reduced environmental pollution. Herein, this work presents a high-performance multi-parameter sensor based on vanadium oxide (VOX )-doped laser-induced graphene (LIG) foam to completely decouple nitrogen oxides (NOX ) and temperature. The highly porous 3D VOX -doped LIG foam composite is readily obtained by laser scribing vanadium sulfide (V5 S8 )-doped block copolymer and phenolic resin self-assembled films. The heterojunction formed at the LIG/VOX interface provides the sensor with enhanced response to NOX and an ultralow limit of detection of 3 ppb (theoretical estimate of 451 ppt) at room temperature. The sensor also exhibits a wide detection range, fast response/recovery, good selectivity, and stability over 16 days. Meanwhile, the sensor can accurately detect temperature over a wide linear range of 10-110 °C. The encapsulation of the sensor with a soft membrane further allows for temperature sensing without being affected by NOX . The unencapsulated sensor operated at elevated temperature removes the influences of relative humidity and temperature variations for accurate NOX measurements. The capability to decouple nitrogen loss and soil temperature paves the way for the development of future multimodal decoupled electronics for precision agriculture and health monitoring.

Scalable and green formation of graphitic nanolayers produces highly conductive pyrolyzed paper toward sensitive electrochemical sensors

While pyrolyzed paper (PP) is a green and abundant material that can provide functionalized electrodes with wide detection windows for a plethora of targets, it poses long-standing challenges against sensing assays such as poor electrical conductivity, with resistivities generally higher than 200.0 mΩ cm (e.g., gold and silver show resistivities 1000-fold lower, ∼0.2 mΩ cm). In this regard, the fundamental hypothesis that drives this work is whether a scalable, cost-effective, and eco-friendly strategy is capable of significantly reducing the resistivity of PP electrodes toward the development of sensitive electrochemical sensors, whether faradaic or capacitive. We address this hypothesis by simply annealing PP under an isopropanol atmosphere for 1 h, reaching resistivities as low as 7 mΩ cm. Specifically, the annealing of PP at 800 or 1000 °C under isopropanol vapor leads to the formation of a highly graphitic nanolayer (∼15 nm) on the PP surface, boosting conductivity as the delocalization of π electrons stemming from carbon sp² is favored. The reduction of carbonyl groups and the deposition of dehydrated isopropanol during the annealing process are hypothesized herein as the dominant PP graphitization mechanisms. Electrochemical analyses demonstrated the capability of the annealed PP to increase the charge-transfer kinetics, with the optimum heterogeneous standard rate constant being roughly 3.6 × 10^-3 cm s^-1. This value is larger than the constants reported for other carbon electrodes and indium tin oxide. Furthermore, freestanding fingers of the annealed PP were prototyped using a knife plotter to fabricate impedimetric on-leaf electrodes. These wearable sensors ensured the real-time and in situ monitoring of the loss of water content from soy leaves, outperforming non-annealed electrodes in terms of reproducibility and sensitivity. Such an application is of pivotal importance for precision agriculture and development of agricultural inputs. This work addresses the foundations for the achievement of conductive PP in a scalable, low-cost, simple, and eco-friendly way, i.e. without producing any liquid chemical waste, providing new opportunities to translate PP-based sensitive electrochemical devices into practical use.

Technology Roadmap for Flexible Sensors

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative efforts, scientific breakthroughs can be made sooner and capitalized for the betterment of humanity.

Analysis of the Development Status and Prospect of China's Agricultural Sensor Market under Smart Agriculture

Agricultural sensors are essential technologies for smart agriculture, which can transform non-electrical physical quantities such as environmental factors. The ecological elements inside and outside of plants and animals are converted into electrical signals for control system recognition, providing a basis for decision-making in smart agriculture. With the rapid development of smart agriculture in China, agricultural sensors have ushered in opportunities and challenges. Based on a literature review and data statistics, this paper analyzes the market prospects and market scale of agricultural sensors in China from four perspectives: field farming, facility farming, livestock and poultry farming and aquaculture. The study further predicts the demand for agricultural sensors in 2025 and 2035. The results reveal that China's sensor market has a good development prospect. However, the paper garnered the key challenges of China's agricultural sensor industry, including a weak technical foundation, poor enterprise research capacity, high importation of sensors and a lack of financial support. Given this, the agricultural sensor market should be comprehensively distributed in terms of policy, funding, expertise and innovative technology. In addition, this paper highlighted integrating the future development direction of China's agricultural sensor technology with new technologies and China's agricultural development needs.

Innovative Photonic Sensors for Safety and Security, Part III: Environment, Agriculture and Soil Monitoring

In order to complete this set of three companion papers, in this last, we focus our attention on environmental monitoring by taking advantage of photonic technologies. After reporting on some configurations useful for high precision agriculture, we explore the problems connected with soil water content measurement and landslide early warning. Then, we concentrate on a new generation of seismic sensors useful in both terrestrial and under water contests. Finally, we discuss a number of optical fiber sensors for use in radiation environments.

Reliability of printed stretchable electronics based on nano/micro materials for practical applications

Recent decades have witnessed the booming development of stretchable electronics based on nano/micro composite inks. Printing is a scalable, low-cost, and high-efficiency fabrication tool to realize stretchable electronics through additive processes. However, compared with conventional flexible electronics, stretchable electronics need to experience more severe mechanical deformation which may cause destructive damage. Most of the reported works in this field mainly focus on how to achieve a high stretchability of nano/micro composite conductors or single working modules/devices, with limited attention given to the reliability for practical applications. In this minireview, we summarized the failure modes when printing stretchable electronics using nano/micro composite ink, including dysfunction of the stretchable interconnects, the stress-concentrated rigid-soft interfaces for hybrid electronics, the vulnerable vias upon stretching, thermal accumulation, and environmental instability of stretchable materials. Strategies for tackling these challenges to realize reliable performances are proposed and discussed. Our review provides an overview on the importance of reliable, printable, and stretchable electronics, which are the key enablers in propelling stretchable electronics from fancy demos to practical applications.

Plant-Wear: A Multi-Sensor Plant Wearable Platform for Growth and Microclimate Monitoring

Wearable devices are widely spreading in various scenarios for monitoring different parameters related to human and recently plant health. In the context of precision agriculture, wearables have proven to be a valuable alternative to traditional measurement methods for quantitatively monitoring plant development. This study proposed a multi-sensor wearable platform for monitoring the growth of plant organs (i.e., stem and fruit) and microclimate (i.e., environmental temperature-T and relative humidity-RH). The platform consists of a custom flexible strain sensor for monitoring growth when mounted on a plant and a commercial sensing unit for monitoring T and RH values of the plant surrounding. A different shape was conferred to the strain sensor according to the plant organs to be engineered. A dumbbell shape was chosen for the stem while a ring shape for the fruit. A metrological characterization was carried out to investigate the strain sensitivity of the proposed flexible sensors and then preliminary tests were performed in both indoor and outdoor scenarios to assess the platform performance. The promising results suggest that the proposed system can be considered one of the first attempts to design wearable and portable systems tailored to the specific plant organ with the potential to be used for future applications in the coming era of digital farms and precision agriculture.

Drug Delivery in Plants Using Silk Microneedles

New systems for agrochemical delivery in plants will foster precise agricultural practices and provide new tools to study plants and design crop traits, as standard spray methods suffer from elevated loss and limited access to remote plant tissues. Silk-based microneedles can circumvent these limitations by deploying a known amount of payloads directly in plants' deep tissues. However, plant response to microneedles' application and microneedles' efficacy in deploying physiologically relevant biomolecules are unknown. Here, it is shown that gene expression associated with Arabidopsis thaliana wounding response decreases within 24 h post microneedles' application. Additionally, microinjection of gibberellic acid (GA₃ ) in A. thaliana mutant ft-10 provides a more effective and efficient mean than spray to activate GA₃ pathways, accelerating bolting and inhibiting flower formation. Microneedle efficacy in delivering GA₃ is also observed in several monocot and dicot crop species, i.e., tomato (Solanum lycopersicum), lettuce (Lactuca sativa), spinach (Spinacia oleracea), rice (Oryza Sativa), maize (Zea mays), barley (Hordeum vulgare), and soybean (Glycine max). The wide range of plants that can be successfully targeted with microinjectors opens the doors to their use in plant science and agriculture.

Spatial Distribution and Estimation Model of Soil pH in Coastal Eastern China

Soil pH is an essential indicator for assessing soil quality and soil health. In this study, based on the Chinese farmland soil survey dataset and meteorological dataset, the spatial distribution characteristics of soil pH in coastal eastern China were analyzed using kriging interpolation. The relationships between hydrothermal conditions and soil pH were explored using regression analysis with mean annual precipitation (MAP), mean annual temperature (MAT), the ratio of precipitation to temperature (P/T), and the product of precipitation and temperature (P*T) as the main explanatory variables. Based on this, a model that can rapidly estimate soil pH was established. The results showed that: (a) The spatial heterogeneity of soil pH in coastal eastern China was obvious, with the values gradually decreasing from north to south, ranging from 4.5 to 8.5; (b) soil pH was significantly correlated with all explanatory variables at the 0.01 level. In general, MAP was the main factor affecting soil pH (r = -0.7244), followed by P/T (r = -0.6007). In the regions with MAP < 800 mm, soil pH was negatively correlated with MAP (r = -0.4631) and P/T (r = -0.7041), respectively, and positively correlated with MAT (r = 0.6093) and P*T (r = 0.3951), respectively. In the regions with MAP > 800 mm, soil pH was negatively correlated with MAP (r = -0.6651), MAT (r = -0.5047), P/T (r = -0.3268), and P*T (r = -0.5808), respectively. (c) The estimation model of soil pH was: y = 23.4572 - 6.3930 × lgMAP + 0.1312 × MAT. It has been verified to have a high accuracy (r = 0.7743, p < 0.01). The mean error, the mean absolute error, and the root mean square error were 0.0450, 0.5300, and 0.7193, respectively. It provides a new path for rapid estimation of the regional soil pH, which is important for improving the management of agricultural production and slowing down soil degradation.

Continuous monitoring of chemical signals in plants under stress

Time is an often-neglected variable in biological research. Plants respond to biotic and abiotic stressors with a range of chemical signals, but as plants are non-equilibrium systems, single-point measurements often cannot provide sufficient temporal resolution to capture these time-dependent signals. In this article, we critically review the advances in continuous monitoring of chemical signals in living plants under stress. We discuss methods for sustained measurement of the most important chemical species, including ions, organic molecules, inorganic molecules and radicals. We examine analytical and modelling approaches currently used to identify and predict stress in plants. We also explore how the methods discussed can be used for applications beyond a research laboratory, in agricultural settings. Finally, we present the current challenges and future perspectives for the continuous monitoring of chemical signals in plants.

Monitoring Ambient Parameters in the IoT Precision Agriculture Scenario: An Approach to Sensor Selection and Hydroponic Saffron Cultivation

The world population is on the rise, which demands higher food production. The reduction in the amount of land under cultivation due to urbanization makes this more challenging. The solution to this problem lies in the artificial cultivation of crops. IoT and sensors play an important role in optimizing the artificial cultivation of crops. The selection of sensors is important in order to ensure a better quality and yield in an automated artificial environment. There are many challenges involved in selecting sensors due to the highly competitive market. This paper provides a novel approach to sensor selection for saffron cultivation in an IoT-based environment. The crop used in this study is saffron due to the reason that much less research has been conducted on its hydroponic cultivation using sensors and its huge economic impact. A detailed hardware-based framework, the growth cycle of the crop, along with all the sensors, and the block layout used for saffron cultivation in a hydroponic medium are provided. The important parameters for a hydroponic medium, such as the concentration of nutrients and flow rate required, are discussed in detail. This paper is the first of its kind to explain the sensor configurations, performance metrics, and sensor-based saffron cultivation model. The paper discusses different metrics related to the selection, use and role of sensors in different IoT-based saffron cultivation practices. A smart hydroponic setup for saffron cultivation is proposed. The results of the model are evaluated using the AquaCrop simulator. The simulator is used to evaluate the value of performance metrics such as the yield, harvest index, water productivity, and biomass. The values obtained provide better results as compared to natural cultivation.

Temperature Sensor Based on Surface Plasmon Resonance with TiO2-Au-TiO2 Triple Structure

Temperature sensors have been widely applied in daily life and production, but little attention has been paid to the research on temperature sensors based on surface plasmon resonance (SPR) sensors. Therefore, an SPR temperature sensor with a triple structure of titanium dioxide (TiO₂) film, gold (Au) film, and TiO₂ nanorods is proposed in this article. By optimizing the thickness and structure of TiO₂ film and nanorods and Au film, it is found that the sensitivity of the SPR temperature sensor can achieve 6038.53 nm/RIU and the detection temperature sensitivity is -2.40 nm/°C. According to the results, the sensitivity of the optimized sensor is 77.81% higher than that of the sensor with pure Au film, which is attributed to the TiO₂(film)-Au-TiO₂(nanorods) structure. Moreover, there is a good linear correlation (greater than 0.99) between temperature and resonance wavelength in the range from 0 °C to 60 °C, which can ensure the detection resolution. The high sensitivity, FOM, and detection resolution indicate that the proposed SPR sensor has a promising application in temperature monitoring.

Microencapsulation of High-Content Actives Using Biodegradable Silk Materials

There is a compelling need across several industries to substitute non-degradable, intentionally added microplastics with biodegradable alternatives. Nonetheless, stringent performance criteria in actives' controlled release and manufacturing at scale of emerging materials hinder the replacement of polymers used for microplastics fabrication with circular ones. Here, the authors demonstrate that active microencapsulation in a structural protein such as silk fibroin can be achieved by modulating protein protonation and chain relaxation at the point of material assembly. Silk fibroin micelles' size is tuned from several to hundreds of nanometers, enabling the manufacturing-by retrofitting spray drying and spray freeze drying techniques-of microcapsules with tunable morphology and structure, that is, hollow-spongy, hollow-smooth, hollow crumpled matrices, and hollow crumpled multi-domain. Microcapsules degradation kinetics and sustained release of soluble and insoluble payloads typically used in cosmetic and agriculture applications are controlled by modulating fibroin's beta-sheet content from 20% to near 40%. Ultraviolet-visible studies indicate that burst release of a commonly used herbicide (i.e., saflufenacil) significantly decreases from 25% to 0.8% via silk fibroin microencapsulation. As a proof-of-concept for agrochemicals applications, a 6-day greenhouse trial demonstrates that saflufenacil delivered on corn plants via silk microcapsules reduces crop injury when compared to the non-encapsulated version.

Integration of Privacy Protection and Blockchain-Based Food Safety Traceability: Potential and Challenges

Concern about food safety has become a hot topic, and numerous researchers have come up with various effective solutions. To ensure the safety of food and avoid financial loss, it is important to improve the safety of food information in addition to the quality of food. Additionally, protecting the privacy and security of food can increase food harvests from a technological perspective, reduce industrial pollution, mitigate environmental impacts, and obtain healthier and safer food. Therefore, food traceability is one of the most effective methods available. Collecting and analyzing key information on food traceability, as well as related technology needs, can improve the efficiency of the traceability chain and provide important insights for managers. Technology solutions, such as the Internet of Things (IoT), Artificial Intelligence (AI), Privacy Preservation (PP), and Blockchain (BC), are proposed for food monitoring, traceability, and analysis of collected data, as well as intelligent decision-making, to support the selection of the best solution. However, research on the integration of these technologies is still lacking, especially in the integration of PP with food traceability. To this end, the study provides a systematic review of the use of PP technology in food traceability and identifies the security needs at each stage of food traceability in terms of data flow and technology. Then, the work related to food safety traceability is fully discussed, particularly with regard to the benefits of PP integration. Finally, current developments in the limitations of food traceability are discussed, and some possible suggestions for the adoption of integrated technologies are made.

Multifunctional Flexible Humidity Sensor Systems Towards Noncontact Wearable Electronics

In the past decade, the global industry and research attentions on intelligent skin-like electronics have boosted their applications in diverse fields including human healthcare, Internet of Things, human-machine interfaces, artificial intelligence and soft robotics. Among them, flexible humidity sensors play a vital role in noncontact measurements relying on the unique property of rapid response to humidity change. This work presents an overview of recent advances in flexible humidity sensors using various active functional materials for contactless monitoring. Four categories of humidity sensors are highlighted based on resistive, capacitive, impedance-type and voltage-type working mechanisms. Furthermore, typical strategies including chemical doping, structural design and Joule heating are introduced to enhance the performance of humidity sensors. Drawing on the noncontact perception capability, human/plant healthcare management, human-machine interactions as well as integrated humidity sensor-based feedback systems are presented. The burgeoning innovations in this research field will benefit human society, especially during the COVID-19 epidemic, where cross-infection should be averted and contactless sensation is highly desired.

Field-Effect Transistor-Based Biosensors for Environmental and Agricultural Monitoring

The precise monitoring of environmental contaminants and agricultural plant stress factors, respectively responsible for damages to our ecosystems and crop losses, has nowadays become a topic of uttermost importance. This is also highlighted by the recent introduction of the so-called "Sustainable Development Goals" of the United Nations, which aim at reducing pollutants while implementing more sustainable food production practices, leading to a reduced impact on all ecosystems. In this context, the standard methods currently used in these fields represent a sub-optimal solution, being expensive, laboratory-based techniques, and typically requiring trained personnel with high expertise. Recent advances in both biotechnology and material science have led to the emergence of new sensing (and biosensing) technologies, enabling low-cost, precise, and real-time detection. An especially interesting category of biosensors is represented by field-effect transistor-based biosensors (bio-FETs), which enable the possibility of performing in situ, continuous, selective, and sensitive measurements of a wide palette of different parameters of interest. Furthermore, bio-FETs offer the possibility of being fabricated using innovative and sustainable materials, employing various device configurations, each customized for a specific application. In the specific field of environmental and agricultural monitoring, the exploitation of these devices is particularly attractive as it paves the way to early detection and intervention strategies useful to limit, or even completely avoid negative outcomes (such as diseases to animals or ecosystems losses). This review focuses exactly on bio-FETs for environmental and agricultural monitoring, highlighting the recent and most relevant studies. First, bio-FET technology is introduced, followed by a detailed description of the the most commonly employed configurations, the available device fabrication techniques, as well as the specific materials and recognition elements. Then, examples of studies employing bio-FETs for environmental and agricultural monitoring are presented, highlighting in detail advantages and disadvantages of available examples. Finally, in the discussion, the major challenges to be overcome (e.g., short device lifetime, small sensitivity and selectivity in complex media) are critically presented. Despite the current limitations and challenges, this review clearly shows that bio-FETs are extremely promising for new and disruptive innovations in these areas and others.

Electrochemical Sensors for Sustainable Precision Agriculture—A Review

Greenhouse gases released by agriculture account for 19% of global greenhouse gas emission. Moreover, the abuse of pesticides and fertilizers is a fundamental cause of soil and water pollution. Finding sustainable countermeasures for these problems requires completely new approaches and the integration of knowledge. Precision agriculture (PA) is a technology that reduces environmental pollution with minimal input (e.g., fertilizer, herbicides, and pesticides) and maximize the production of high-quality crops by monitoring the conditions and environment of farmland and crops. However, the lack of data—a key technology for realizing PA—remains a major obstacle to the large-scale adoption of PA. Herein, we discuss important research issues, such as data managements and analysis for accurate decision-making, and specific data acquisition strategies. Moreover, we systematically review and discuss electrochemical sensors, including sensors that monitor the plant, soil, and environmental conditions that directly affect plant growth.

Digital Transformation in Smart Farm and Forest Operations Needs Human-Centered AI: Challenges and Future Directions

The main impetus for the global efforts toward the current digital transformation in almost all areas of our daily lives is due to the great successes of artificial intelligence (AI), and in particular, the workhorse of AI, statistical machine learning (ML). The intelligent analysis, modeling, and management of agricultural and forest ecosystems, and of the use and protection of soils, already play important roles in securing our planet for future generations and will become irreplaceable in the future. Technical solutions must encompass the entire agricultural and forestry value chain. The process of digital transformation is supported by cyber-physical systems enabled by advances in ML, the availability of big data and increasing computing power. For certain tasks, algorithms today achieve performances that exceed human levels. The challenge is to use multimodal information fusion, i.e., to integrate data from different sources (sensor data, images, *omics), and explain to an expert why a certain result was achieved. However, ML models often react to even small changes, and disturbances can have dramatic effects on their results. Therefore, the use of AI in areas that matter to human life (agriculture, forestry, climate, health, etc.) has led to an increased need for trustworthy AI with two main components: explainability and robustness. One step toward making AI more robust is to leverage expert knowledge. For example, a farmer/forester in the loop can often bring in experience and conceptual understanding to the AI pipeline-no AI can do this. Consequently, human-centered AI (HCAI) is a combination of "artificial intelligence" and "natural intelligence" to empower, amplify, and augment human performance, rather than replace people. To achieve practical success of HCAI in agriculture and forestry, this article identifies three important frontier research areas: (1) intelligent information fusion; (2) robotics and embodied intelligence; and (3) augmentation, explanation, and verification for trusted decision support. This goal will also require an agile, human-centered design approach for three generations (G). G1: Enabling easily realizable applications through immediate deployment of existing technology. G2: Medium-term modification of existing technology. G3: Advanced adaptation and evolution beyond state-of-the-art.

Star Polymers with Designed Reactive Oxygen Species Scavenging and Agent Delivery Functionality Promote Plant Stress Tolerance

Plant abiotic stress induces reactive oxygen species (ROS) accumulation in leaves that can decrease photosynthetic performance and crop yield. Materials that scavenge ROS and simultaneously provide nutrients in vivo are needed to manage this stress. Here, we incorporated both ROS scavenging and ROS triggered agent release functionality into an ∼20 nm ROS responsive star polymer (RSP) poly(acrylic acid)-block-poly((2-(methylsulfinyl)ethyl acrylate)-co-(2-(methylthio)ethyl acrylate)) (PAA-b-P(MSEA-co-MTEA)) that alleviated plant stress by simultaneous ROS scavenging and nutrient agent release. Hyperspectral imaging indicates that all of the RSP penetrates through the tomato leaf epidermis, and 32.7% of the applied RSP associates with chloroplasts in mesophyll. RSP scavenged up to 10 μmol mg^-1 ROS in vitro and suppressed ROS in vivo in stressed tomato (Solanum lycopersicum) leaves. Reaction of the RSP with H₂O₂in vitro enhanced the release of nutrient agent (Mg²⁺) from star polymers. Foliar applied RSP increased photosynthesis in plants under heat and light stress compared to untreated controls, enhancing the carbon assimilation, quantum yield of CO₂ assimilation, Rubisco carboxylation rate, and photosystem II quantum yield. Mg loaded RSP improved photosynthesis in Mg deficient plants, mainly by promoting Rubisco activity. These results indicate the potential of ROS scavenging nanocarriers like RSP to alleviate abiotic stress in crop plants, allowing crop plants to be more resilient to heat stress, and potentially other climate change induced abiotic stressors.

Biocompatible Wearable Electrodes on Leaves toward the On-Site Monitoring of Water Loss from Plants

Impedimetric wearable sensors are a promising strategy for determining the loss of water content (LWC) from leaves because they can afford on-site and nondestructive quantification of cellular water from a single measurement. Because the water content is a key marker of leaf health, monitoring of the LWC can lend key insights into daily practice in precision agriculture, toxicity studies, and the development of agricultural inputs. Ongoing challenges with this monitoring are the on-leaf adhesion, compatibility, scalability, and reproducibility of the electrodes, especially when subjected to long-term measurements. This paper introduces a set of sensing material, technological, and data processing solutions that overwhelm such obstacles. Mass-production-suitable electrodes consisting of stand-alone Ni films obtained by well-established microfabrication methods or ecofriendly pyrolyzed paper enabled reproducible determination of the LWC from soy leaves with optimized sensibilities of 27.0 (Ni) and 17.5 kΩ %-1 (paper). The freestanding design of the Ni electrodes was further key to delivering high on-leaf adhesion and long-term compatibility. Their impedances remained unchanged under the action of wind at velocities of up to 2.00 m s-1, whereas X-ray nanoprobe fluorescence assays allowed us to confirm the Ni sensor compatibility by the monitoring of the soy leaf health in an electrode-exposed area. Both electrodes operated through direct transfer of the conductive materials on hairy soy leaves using an ordinary adhesive tape. We used a hand-held and low-power potentiostat with wireless connection to a smartphone to determine the LWC over 24 h. Impressively, a machine-learning model was able to convert the sensing responses into a simple mathematical equation that gauged the impairments on the water content at two temperatures (30 and 20 °C) with reduced root-mean-square errors (0.1% up to 0.3%). These data suggest broad applicability of the platform by enabling direct determination of the LWC from leaves even at variable temperatures. Overall, our findings may help to pave the way for translating "sense-act" technologies into practice toward the on-site and remote investigation of plant drought stress. These platforms can provide key information for aiding efficient data-driven management and guiding decision-making steps.

Self-Healing, Self-Adhesive and Stable Organohydrogel-Based Stretchable Oxygen Sensor with High Performance at Room Temperature

With the advent of the 5G era and the rise of the Internet of Things, various sensors have received unprecedented attention, especially wearable and stretchable sensors in the healthcare field. Here, a stretchable, self-healable, self-adhesive, and room-temperature oxygen sensor with excellent repeatability, a full concentration detection range (0-100%), low theoretical limit of detection (5.7 ppm), high sensitivity (0.2%/ppm), good linearity, excellent temperature, and humidity tolerances is fabricated by using polyacrylamide-chitosan (PAM-CS) double network (DN) organohydrogel as a novel transducing material. The PAM-CS DN organohydrogel is transformed from the PAM-CS composite hydrogel using a facile soaking and solvent replacement strategy. Compared with the pristine hydrogel, the DN organohydrogel displays greatly enhanced mechanical strength, moisture retention, freezing resistance, and sensitivity to oxygen. Notably, applying the tensile strain improves both the sensitivity and response speed of the organohydrogel-based oxygen sensor. Furthermore, the response to the same concentration of oxygen before and after self-healing is basically the same. Importantly, we propose an electrochemical reaction mechanism to explain the positive current shift of the oxygen sensor and corroborate this sensing mechanism through rationally designed experiments. The organohydrogel oxygen sensor is used to monitor human respiration in real-time, verifying the feasibility of its practical application. This work provides ideas for fabricating more stretchable, self-healable, self-adhesive, and high-performance gas sensors using ion-conducting organohydrogels.

Toward the Next Generation of Digitalization in Agriculture Based on Digital Twin Paradigm

Digitalization has impacted agricultural and food production systems, and makes application of technologies and advanced data processing techniques in agricultural field possible. Digital farming aims to use available information from agricultural assets to solve several existing challenges for addressing food security, climate protection, and resource management. However, the agricultural sector is complex, dynamic, and requires sophisticated management systems. The digital approaches are expected to provide more optimization and further decision-making supports. Digital twin in agriculture is a virtual representation of a farm with great potential for enhancing productivity and efficiency while declining energy usage and losses. This review describes the state-of-the-art of digital twin concepts along with different digital technologies and techniques in agricultural contexts. It presents a general framework of digital twins in soil, irrigation, robotics, farm machineries, and food post-harvest processing in agricultural field. Data recording, modeling including artificial intelligence, big data, simulation, analysis, prediction, and communication aspects (e.g., Internet of Things, wireless technologies) of digital twin in agriculture are discussed. Digital twin systems can support farmers as a next generation of digitalization paradigm by continuous and real-time monitoring of physical world (farm) and updating the state of virtual world.

Self-Powered Sensing for Smart Agriculture by Electromagnetic-Triboelectric Hybrid Generator

The lack of efficient, low-cost, distributed energy collection methods is a vital factor restricting the application of the Internet of Things (IoT) in smart agriculture. This paper proposes a method based on triboelectric nanogenerator and electromagnetic generator to realize self-powered IoT nodes and self-powered sensors at the same time. An energy harvesting and sensing device based on electromagnetic-triboelectric hybrid generator (ES-ETHG) is designed. The peak power of ES-ETHG is 32.4 mW, which can supply power to IoT nodes for a long time with power management circuits. In addition, ES-ETHG can critically measure wind speed and wind level within the range of 3-15 m/s, and accurately detect wind direction within 2 s. Furthermore, the self-powered distributed weather sensing system based on ES-ETHG is developed to realize the remote collection of wind speed, wind direction, temperature, and humidity. This work proposes a solution for developing self-powered IoT and sensor in the field of smart agriculture.

Digitalization in Food Supply Chains: A Bibliometric Review and Key-Route Main Path Analysis

Technological advances such as blockchain, artificial intelligence, big data, social media, and geographic information systems represent a building block of the digital transformation that supports the resilience of the food supply chain (FSC) and increases its efficiency. This paper reviews the literature surrounding digitalization in FSCs. A bibliometric and key-route main path analysis was carried out to objectively and analytically uncover the knowledge development in digitalization within the context of sustainable FSCs. The research began with the selection of 2140 articles published over nearly five decades. Then, the articles were examined according to several bibliometric metrics such as year of publication, countries, institutions, sources, authors, and keywords frequency. A keyword co-occurrence network was generated to cluster the relevant literature. Findings of the review and bibliometric analysis indicate that research at the intersection of technology and the FSC has gained substantial interest from scholars. On the basis of keyword co-occurrence network, the literature is focused on the role of information communication technology for agriculture and food security, food waste and circular economy, and the merge of the Internet of Things and blockchain in the FSC. The analysis of the key-route main path uncovers three critical periods marking the development of technology-enabled FSCs. The study offers scholars a better understanding of digitalization within the agri-food industry and the current knowledge gaps for future research. Practitioners may find the review useful to remain ahead of the latest discussions of technology-enabled FSCs. To the authors’ best knowledge, the current study is one of the few endeavors to explore technology-enabled FSCs using a comprehensive sample of journal articles published during the past five decades.

Flexible Wearables for Plants

The excellent stretchability and biocompatibility of flexible sensors have inspired an emerging field of plant wearables, which enable intimate contact with the plants to continuously monitor the growth status and localized microclimate in real-time. Plant flexible wearables provide a promising platform for the development of plant phenotype and the construction of intelligent agriculture via monitoring and regulating the critical physiological parameters and microclimate of plants. Here, the emerging applications of plant flexible wearables together with their pros and cons from four aspects, including physiological indicators, surrounding environment, crop quality, and active control of growth, are highlighted. Self-powered energy supply systems and signal transmission mechanisms are also elucidated. Furthermore, the future opportunities and challenges of plant wearables are discussed in detail.

Wireless Sensor Networks in Agriculture: Insights from Bibliometric Analysis

This study investigates how wireless sensor network (WSN) applications in agriculture are discussed in the current academic literature. On the basis of bibliometric techniques, 2444 publications were extracted from the Scopus database and analyzed to identify the temporal distribution of WSN research, the most productive journals, the most cited authors, the most influential studies, and the most relevant keywords. The computer program VOSviewer was used to generate the keyword co-occurrence network and partition the pertinent literature. Findings show the remarkable growth of WSN research in recent years. The most relevant journals, cited countries, and influential studies were also identified. The main results from the keyword co-occurrence clustering and the detailed analysis illustrate that WSN is a key enabler for precision agriculture. WSN research also focuses on the role of other technologies such as the Internet of Things, cloud computing, artificial intelligence, and unmanned aerial vehicles in supporting several agriculture activities, including smart irrigation and soil management. This study illuminates researchers’ and practitioners’ views of what has been researched and identifies possible opportunities for future studies. To the authors’ best knowledge, this bibliometric study represents the first attempt to map global WSN research using a comprehensive sample of documents published over nearly three decades.