Species-independent analytical tools for next-generation agriculture

Applications of optical sensing and imaging spectroscopy in indoor farming: A systematic review

As demand for food continues to rise, innovative methods are needed to sustainably and efficiently meet the growing pressure on agriculture. Indoor farming and controlled environment agriculture have emerged as promising approaches to address this challenge. However, optimizing fertilizer usage, ensuring homogeneous production, and reducing agro-waste remain substantial challenges in these production systems. One potential solution is the use of optical sensing technology, which can provide real-time data to help growers make informed decisions and enhance their operations. optical sensing can be used to analyze plant tissues, evaluate crop quality and yield, measure nutrients, and assess plant responses to stress. This paper presents a systematic literature review of the current state of using spectral-optical sensors and hyperspectral imaging for indoor farming, following the PRISMA 2020 guidelines. The study surveyed existing studies from 2017 to 2023 to identify gaps in knowledge, provide researchers and farmers with current trends, and offer recommendations and inspirations for possible new research directions. The results of this review will contribute to the development of sustainable and efficient methods of food production.

Nanoparticle-specific transformations dictate nanoparticle effects associated with plants and implications for nanotechnology use in agriculture

Nanotechnology shows potential to promote sustainable and productive agriculture and address the growing population and food demand worldwide. However, the applications of nanotechnology are hindered by the lack of knowledge on nanoparticle (NP) transformations and the interactions between NPs and macromolecules within crops. In this Review, we discuss the beneficial and toxicity-relieving transformation products of NPs that provide agricultural benefits and the toxic and physiology-disturbing transformations that induce phytotoxicities. Based on knowledge related to the management of NP transformations and their long-term effects, we propose feasible design suggestions to attain nano-enabled efficient and sustainable agricultural applications.

Raman spectroscopy - a visit to the literature on plant, food, and agricultural studies

Raman spectroscopy, a fast, non-invasive, and label-free optical technique, has significantly advanced plant and food studies and precision agriculture by providing detailed molecular insights into biological tissues. Utilizing the Raman scattering effect generates unique spectral fingerprints that comprehensively analyze tissue composition, concentration, and molecular structure. These fingerprints are obtained without chemical additives or extensive sample preparation, making Raman spectroscopy particularly suitable for in-field applications. Technological enhancements such as surface-enhanced Raman scattering, Fourier-transform-Raman spectroscopy, and chemometrics have increased Raman spectroscopy sensitivity and precision. These and other advancements enable real-time monitoring of compound translocation within plants and improve the detection of chemical and biological contaminants, essential for food safety and crop optimization. Integrating Raman spectroscopy into agronomic practices is transformative and marks a shift toward more sustainable farming activities. It assesses crop quality - as well as the quality of the food that originated from crop production - early plant stress detection and supports targeted breeding programs. Advanced data processing techniques and machine learning integration efficiently handle complex spectral data, providing a dynamic and detailed view of food conditions and plant health under varying environmental and biological stresses. As global agriculture faces the dual challenges of increasing productivity and sustainability, Raman spectroscopy stands out as an indispensable tool, enhancing farming practices' precision, food safety, and environmental compatibility. This review is intended to select and briefly comment on outstanding literature to give researchers, students, and consultants a reference for works of literature in Raman spectroscopy mainly focused on plant, food, and agronomic sciences. © 2024 Society of Chemical Industry.

Light-emitting probes for in situ sensing of plant information

Monitoring plant physiological information for gaining a comprehensive understanding of plant growth and stress responses contributes to safeguarding plant health. Light-emitting probes - in terms of small-molecule, nanomaterials-based, and genetically protein-based probes - can be introduced into plants through foliar and root treatment or genetic transformation. These probes offer exciting opportunities for sensitive and in situ monitoring of dynamic plant chemical information - for example, reactive oxygen species (ROS), calcium ions, phytohormones - with spatiotemporal resolution. In this review we explore the sensing mechanisms of these light-emitting probes and their applications in monitoring various chemical information in plants in situ. These probes can be used as part of a sentinel plant approach to provide stress warning in the field or to explore plant signaling pathways.

Charge generation by passive plant leaf motion at low wind speeds: design and collective behavior of plant-hybrid energy harvesters

Energy harvesting techniques can exploit even subtle passive motion like that of plant leaves in wind as a consequence of contact electrification of the leaf surface. The effect is strongly enhanced by artificial materials installed as 'artificial leaves' on the natural leaves creating a recurring mechanical contact and separation. However, this requires a controlled mechanical interaction between the biological and the artificial component during the complex wind motion. Here, we build and test four artificial leaf designs with varying flexibility and degrees of freedom across the blade operating onNerium oleanderplants. We evaluate the apparent contact area (up to 10 cm2per leaf), the leaves' motion, together with the generated voltage, current and charge in low wind speeds of up to 3.3 m s-1and less. Single artificial leaves produced over 75 V and 1µA current peaks. Softer artificial leaves increase the contact area accessible for energy conversion, but a balance between softer and stiffer elements in the artificial blade is optimal to increase the frequency of contact-separation motion (here up to 10 Hz) for energy conversion also below 3.3 m s-1. Moreover, we tested how multiple leaves operating collectively during continuous wind energy harvesting over several days achieve a root mean square power of ∼6µW and are capable to transfer ∼80µC every 30-40 min to power a wireless temperature and humidity sensor autonomously and recurrently. The results experimentally reveal design strategies for energy harvesters providing autonomous micro power sources in plant ecosystems for example for sensing in precision agriculture and remote environmental monitoring.

Gelatin Nanoparticles can Improve Pesticide Delivery Performance to Plants

Nanomaterials associated with plant growth and crop cultivation revolutionize traditional concepts of agriculture. However, the poor reiterability of these materials in agricultural applications necessitates the development of environmentally-friendly approaches. To address this, biocompatible gelatin nanoparticles (GNPs) as nanofertilizers with a small size (≈150 nm) and a positively charged surface (≈30 mV) that serve as a versatile tool in agricultural practices is designed. GNPs load agrochemical agents to improve maintenance and delivery. The biocompatible nature and small size of GNPs ensure unrestricted nutrient absorption on root surfaces. Furthermore, when combined with pesticides, GNPs demonstrate remarkable enhancements in insecticidal (≈15%) and weed-killing effects (≈20%) while preserving the efficacy of the pesticide. That GNPs have great potential for use in sustainable agriculture, particularly in inducing plant growth, specifically plant root growth, without fertilization and in enhancing the functions of agrochemical agents is proposed. It is suggested conceptual applications of GNPs in real-world agricultural practices.

Attenuated total reflection Fourier-transform infrared spectroscopy for the prediction of hormone concentrations in plants

Plant hormones are important in the control of physiological and developmental processes including seed germination, senescence, flowering, stomatal aperture, and ultimately the overall growth and yield of plants. Many currently available methods to quantify such growth regulators quickly and accurately require extensive sample purification using complex analytic techniques. Herein we used ultra-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) to create and validate the prediction of hormone concentrations made using attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectral profiles of both freeze-dried ground leaf tissue and extracted xylem sap of Japanese knotweed (Reynoutria japonica) plants grown under different environmental conditions. In addition to these predictions made with partial least squares regression, further analysis of spectral data was performed using chemometric techniques, including principal component analysis, linear discriminant analysis, and support vector machines (SVM). Plants grown in different environments had sufficiently different biochemical profiles, including plant hormonal compounds, to allow successful differentiation by ATR-FTIR spectroscopy coupled with SVM. ATR-FTIR spectral biomarkers highlighted a range of biomolecules responsible for the differing spectral signatures between growth environments, such as triacylglycerol, proteins and amino acids, tannins, pectin, polysaccharides such as starch and cellulose, DNA and RNA. Using partial least squares regression, we show the potential for accurate prediction of plant hormone concentrations from ATR-FTIR spectral profiles, calibrated with hormonal data quantified by UHPLC-HRMS. The application of ATR-FTIR spectroscopy and chemometrics offers accurate prediction of hormone concentrations in plant samples, with advantages over existing approaches.

Harnessing Raman spectroscopy for the analysis of plant diversity

Here, we explore the application of Raman spectroscopy for the assessment of plant biodiversity. Raman spectra from 11 vascular plant species commonly found in forest ecosystems, specifically angiosperms (both monocots and eudicots) and pteridophytes (ferns), were acquired in vivo and in situ using a Raman leaf-clip. We achieved an overall accuracy of 91% for correct classification of a species within a plant group and identified lignin Raman spectral features as a useful discriminator for classification. The results demonstrate the potential of Raman spectroscopy in contributing to plant biodiversity assessment.

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.

Second near-infrared fluorescent Metal-Organic framework sensors for in vivo extracellular adenosine triphosphate monitoring

Plant nanobionic sensors enable real-time monitoring of signaling molecules in plants by interfacing them with specifically designed nanoprobes, which have been acknowledged as species-independent analytical tools. In this study, we developed a plant nanobionic sensor for in vivo detection of extracellular adenosine triphosphate (eATP) in living plants by designing a novel second near-infrared (NIR-II) fluorescent metal-organic framework (MOF) nanoprobe. The NIR-II fluorescent nanoprobe (IR-1061 micelle@ZIF-90) with a sandwich structure was synthesized by successive encapsulation of the hydrophobic NIR-II dye IR-1061 with the amphipathic polymer DSPE-mPEG 2000 and MOF ZIF-90. Interestingly, coating ZIF-90 around IR-1061 micelles increased the NIR-II fluorescence 16.6-fold. Utilizing the ultrahigh NIR-II fluorescent emission of the designed nanoprobes and specific recognition of ZIF-90 to ATP, the nanoprobes were applied to spatial and temporal monitoring eATP in model and non-model plants under environmental stress.

Regulatory networks in plant responses to drought and cold stress

Drought and cold represent distinct types of abiotic stress, each initiating unique primary signaling pathways in response to dehydration and temperature changes, respectively. However, a convergence at the gene regulatory level is observed where a common set of stress-responsive genes is activated to mitigate the impacts of both stresses. In this review, we explore these intricate regulatory networks, illustrating how plants coordinate distinct stress signals into a collective transcriptional strategy. We delve into the molecular mechanisms of stress perception, stress signaling, and the activation of gene regulatory pathways, with a focus on insights gained from model species. By elucidating both the shared and distinct aspects of plant responses to drought and cold, we provide insight into the adaptive strategies of plants, paving the way for the engineering of stress-resilient crop varieties that can withstand a changing climate.

Decoding early stress signaling waves in living plants using nanosensor multiplexing

Increased exposure to environmental stresses due to climate change have adversely affected plant growth and productivity. Upon stress, plants activate a signaling cascade, involving multiple molecules like H2O2, and plant hormones such as salicylic acid (SA) leading to resistance or stress adaptation. However, the temporal ordering and composition of the resulting cascade remains largely unknown. In this study we developed a nanosensor for SA and multiplexed it with H2O2 nanosensor for simultaneous monitoring of stress-induced H2O2 and SA signals when Brassica rapa subsp. Chinensis (Pak choi) plants were subjected to distinct stress treatments, namely light, heat, pathogen stress and mechanical wounding. Nanosensors reported distinct dynamics and temporal wave characteristics of H2O2 and SA generation for each stress. Based on these temporal insights, we have formulated a biochemical kinetic model that suggests the early H2O2 waveform encodes information specific to each stress type. These results demonstrate that sensor multiplexing can reveal stress signaling mechanisms in plants, aiding in developing climate-resilient crops and pre-symptomatic stress diagnoses.

Alternating Current Electroluminescence for Human-Interactive Sensing Displays

The development of stimuli-interactive displays based on alternating current (AC)-driven electroluminescence (EL) is of great interest, owing to their simple device architectures suitable for wearable applications requiring resilient mechanical flexibility and stretchability. AC-EL displays can serve as emerging platforms for various human-interactive sensing displays (HISDs) where human information is electrically detected and directly visualized using EL, promoting the development of the interaction of human-machine technologies. This review provides a holistic overview of the latest developments in AC-EL displays with an emphasis on their applications for HISDs. AC-EL displays based on exciton recombination or impact excitations of hot electrons are classified into four representative groups depending upon their device architecture: 1) displays without insulating layers, 2) displays with single insulating layers, 3) displays with double insulating layers, and 4) displays with EL materials embedded in an insulating matrix. State-of-the-art AC HISDs are discussed. Furthermore, emerging stimuli-interactive AC-EL displays are described, followed by a discussion of scientific and engineering challenges and perspectives for future stimuli-interactive AC-EL displays serving as photo-electronic human-machine interfaces.

Boosting Plant Photosynthesis with Carbon Dots: A Critical Review of Performance and Prospects

Artificially augmented photosynthesis in nano-bionic plants requires tunable nano-antenna structures with physiochemical and optoelectronic properties, as well as unique light conversion capabilities. The use of nanomaterials to promote light capture across photosystems, primarily by carbon dots, has shown promising results in enhancing photosynthesis through tunable uptake, translocation, and biocompatibility. Carbon dots possess the ability to perform both down and up-light conversions, making them effective light promoters for harnessing solar energy beyond visible light wavelengths.This review presents and discusses the recent progress in fabrication, chemistry, and morphology, as well as other properties such as photoluminescence and energy conversion efficiency of nano-antennas based on carbon dots. The performance of artificially boosted photosynthesis is discussed and then correlated with the conversion properties of carbon dots and how they are applied to plant models. The challenges related to the nanomaterial delivery and the performance evaluation practices in modified photosystems, consideration of the reliability of this approach, and the potential avenues for performance improvements through other types of nano-antennas based on alternative nanomaterials are also critically evaluated. It is anticipated that this review will stimulate more high-quality research in plant nano-bionics and provide avenues to enhance photosynthesis for future agricultural applications.

Soft Human-Machine Interface Sensing Displays: Materials and Devices

The development of human-interactive sensing displays (HISDs) that simultaneously detect and visualize stimuli is important for numerous cutting-edge human-machine interface technologies. Therefore, innovative device platforms with optimized architectures of HISDs combined with novel high-performance sensing and display materials are demonstrated. This study comprehensively reviews the recent advances in HISDs, particularly the device architectures that enable scaling-down and simplifying the HISD, as well as material designs capable of directly visualizing input information received by various sensors. Various HISD platforms for integrating sensors and displays are described. HISDs consist of a sensor and display connected through a microprocessor, and attempts to assemble the two devices by eliminating the microprocessor are detailed. Single-device HISD technologies are highlighted in which input stimuli acquired by sensory components are directly visualized with various optical components, such as electroluminescence, mechanoluminescence and structural color. The review forecasts future HISD technologies that demand the development of materials with molecular-level synthetic precision that enables simultaneous sensing and visualization. Furthermore, emerging HISDs combined with artificial intelligence technologies and those enabling simultaneous detection and visualization of extrasensory information are discussed.

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.

In Situ Fabricated Liquid Metal Capacitors for Plant Sensing

Capacitive sensors are essential to promoting modernization and intelligence in agriculture. With the continuous advancement of this sensor technology, the demand for materials with high conductivity and flexibility is rapidly increasing. Herein, we introduce liquid metal as a solution for the in-site fabrication of high-performance capacitive sensors for plant sensing. As a comparison, three pathways have been proposed for the preparation of flexible capacitors inside plants, as well as on their surfaces. Specifically, concealed capacitors can be constructed by directly injecting liquid metal into the plant cavity. Printable capacitors are prepared via printing Cu-doped liquid metal with better adhesion on plant surfaces. A composite liquid metal-based capacitive sensor is achieved by printing liquid metal on the plant surface and injecting it into the interior of the plant. While each method has limitations, the composite liquid metal-based capacitive sensor provides an optimal trade-off between signal capture capability and operability. As a result, this composite capacitor is chosen as a sensor for monitoring water changes within plants and demonstrates the desired sensing performance, making it a promising technology for monitoring plant physiology.

Non-invasive identification of combined salinity stress and stalk rot disease caused by Colletotrichum graminicola in maize using Raman spectroscopy

Food security is an emerging problem that is faced by our civilization. There are millions of people around the world suffering from various kinds of malnutrition. The number of people that starve will only increase considering the continuous growth of the world's population. The problem of food security can be addressed by timely detection and identification biotic and abiotic stresses in plants that drastically reduce the crop yield. A growing body of evidence suggests that Raman spectroscopy (RS), an emerging analytical technique, can be used for the confirmatory and non-invasive diagnostics of plant stresses. However, it remains unclear whether RS can efficiently disentangle biotic and abiotic stresses, as well as detect both of them simultaneously in plants. In this work, we modeled a stalk rot disease in corn by inoculating the plant stalks with Colletotrichum graminicola. In parallel, we subjected plants to salt stress, as well as challenging plants with both stalk rot disease and salinity stress simultaneously. After the stresses were introduced, Raman spectra were collected from the stalks to reveal stress-specific changes in the plant biochemistry. We found that RS was able to differentiate between stalk rot disease and salinity stresses with 100% accuracy, as well as predict presence of both of those stresses in plants on early and late stages. These results demonstrate that RS is a robust and reliable approach that can be used for confirmatory, non-destructive and label-free diagnostics of biotic and abiotic stresses in plants.

Integrating biopolymer design with physical unclonable functions for anticounterfeiting and product traceability in agriculture

Smallholder farmers and manufacturers in the Agri-Food sector face substantial challenges because of increasing circulation of counterfeit products (e.g., seeds), for which current countermeasures are implemented mainly at the secondary packaging level, and are generally vulnerable because of limited security guarantees. Here, by integrating biopolymer design with physical unclonable functions (PUFs), we propose a cryptographic protocol for seed authentication using biodegradable and miniaturized PUF tags made of silk microparticles. By simply drop casting a mixture of variant silk microparticles on a seed surface, tamper-evident PUF tags can be seamlessly fabricated on a variety of seeds, where the unclonability comes from the stochastic assembly of spectrally and visually distinct silk microparticles in the tag. Unique, reproducible, and unpredictable PUF codes are generated from both Raman mapping and microscopy imaging of the silk tags. Together, the proposed technology offers a highly secure solution for anticounterfeiting and product traceability in agriculture.

Near-Infrared Fluorescent Carbon Nanotube Sensors for the Plant Hormone Family Gibberellins

Gibberellins (GAs) are a class of phytohormones, important for plant growth, and very difficult to distinguish because of their similarity in chemical structures. Herein, we develop the first nanosensors for GAs by designing and engineering polymer-wrapped single-walled carbon nanotubes (SWNTs) with unique corona phases that selectively bind to bioactive GAs, GA₃ and GA₄, triggering near-infrared (NIR) fluorescence intensity changes. Using a new coupled Raman/NIR fluorimeter that enables self-referencing of nanosensor NIR fluorescence with its Raman G-band, we demonstrated detection of cellular GA in Arabidopsis, lettuce, and basil roots. The nanosensors reported increased endogenous GA levels in transgenic Arabidopsis mutants that overexpress GA and in emerging lateral roots. Our approach allows rapid spatiotemporal detection of GA across species. The reversible sensor captured the decreasing GA levels in salt-treated lettuce roots, which correlated remarkably with fresh weight changes. This work demonstrates the potential for nanosensors to solve longstanding problems in plant biotechnology.

In vivo surface-enhanced Raman scattering nanosensor for the real-time monitoring of multiple stress signalling molecules in plants

When under stress, plants release molecules to activate their defense system. Detecting these stress-related molecules offers the possibility to address stress conditions and prevent the development of diseases. However, detecting endogenous signalling molecules in living plants remains challenging due to low concentrations of these analytes and interference with other compounds; additionally, many methods currently used are invasive and labour-intensive. Here we show a non-destructive surface-enhanced Raman scattering (SERS)-based nanoprobe for the real-time detection of multiple stress-related endogenous molecules in living plants. The nanoprobe, which is placed in the intercellular space, is optically active in the near-infrared region (785 nm) to avoid interferences from plant autofluorescence. It consists of a Si nanosphere surrounded by a corrugated Ag shell modified by a water-soluble cationic polymer poly(diallyldimethylammonium chloride), which can interact with multiple plant signalling molecules. We measure a SERS enhancement factor of 2.9 × 10⁷ and a signal-to-noise ratio of up to 64 with an acquisition time of ~100 ms. To show quantitative multiplex detection, we adopted a binding model to interpret the SERS intensities of two different analytes bound to the SERS hot spot of the nanoprobe. Under either abiotic or biotic stress, our optical nanosensors can successfully monitor salicylic acid, extracellular adenosine triphosphate, cruciferous phytoalexin and glutathione in Nasturtium officinale, Triticum aestivum L. and Hordeum vulgare L.-all stress-related molecules indicating the possible onset of a plant disease. We believe that plasmonic nanosensor platforms can enable the early diagnosis of stress, contributing to a timely disease management of plants.

Plant Hormonomics: A Key Tool for Deep Physiological Phenotyping to Improve Crop Productivity

Agriculture is particularly vulnerable to climate change. To cope with the risks posed by climate-related stressors to agricultural production, global population growth, and changes in food preferences, it is imperative to develop new climate-smart crop varieties with increased yield and environmental resilience. Molecular genetics and genomic analyses have revealed that allelic variations in genes involved in phytohormone-mediated growth regulation have greatly improved productivity in major crops. Plant science has remarkably advanced our understanding of the molecular basis of various phytohormone-mediated events in plant life. These findings provide essential information for improving the productivity of crops growing in changing climates. In this review, we highlight the recent advances in plant hormonomics (multiple phytohormone profiling) and discuss its application to crop improvement. We present plant hormonomics as a key tool for deep physiological phenotyping, focusing on representative plant growth regulators associated with the improvement of crop productivity. Specifically, we review advanced methodologies in plant hormonomics, highlighting mass spectrometry- and nanosensor-based plant hormone profiling techniques. We also discuss the applications of plant hormonomics in crop improvement through breeding and agricultural management practices.

Visualizing changes of metabolites during iron deficiency chlorosis in field-grown pear leaves using micro-Raman spectral imaging

Owing to iron chlorosis, pear trees are some of the most severely impacted by iron deficiency, and they suffer significant losses every year. While it is possible to determine the iron content of leaves using laboratory-standard analytical techniques, the sampling and analysis process is time-consuming and labor-intensive, and it does not quickly and accurately identify the physiological state of iron-deficient leaves. Therefore, it is crucial to find a precise and quick visualization approach for metabolites linked to leaf iron to comprehend the mechanism of iron deficiency and create management strategies for pear-tree planting. In this paper, we propose a micro-Raman spectral imaging method for non-destructive, rapid, and precise visual characterization of iron-deficiency-related metabolites in pear leaves. According to our findings, iron deficiency significantly decreased the Raman peak intensities of chlorophylls and lipids in leaves. The spatial distributions of chlorophylls and lipids in the leaves changed significantly as the symptoms of iron insufficiency worsened. The technique offers a new, prospective tool for rapid recognition of iron deficiency in pear trees because it is capable of visual detection of plant physiological metabolites induced by iron deficiency.

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.

A perspective on plant robotics: from bioinspiration to hybrid systems

As miscellaneous as the Plant Kingdom is, correspondingly diverse are the opportunities for taking inspiration from plants for innovations in science and engineering. Especially in robotics, properties like growth, adaptation to environments, ingenious materials, sustainability, and energy-effectiveness of plants provide an extremely rich source of inspiration to develop new technologies-and many of them are still in the beginning of being discovered. In the last decade, researchers have begun to reproduce complex plant functions leading to functionality that goes far beyond conventional robotics and this includes sustainability, resource saving, and eco-friendliness. This perspective drawn by specialists in different related disciplines provides a snapshot from the last decade of research in the field and draws conclusions on the current challenges, unanswered questions on plant functions, plant-inspired robots, bioinspired materials, and plant-hybrid systems looking ahead to the future of these research fields.

Improving Plant Photosynthesis through Light-Harvesting Upconversion Nanoparticles

Nanotechnology is considered as an emerging effective means to augment plant photosynthesis. However, there is still a lot of work to be done in this field. Here, we applied the upconversion nanoparticles (UCNPs) on lettuce leaves and found that the UCNPs were able to transport into the lettuce body and colocalize with the chloroplasts. It was proved that UCNPs could harvest the near-infrared light of sunlight and increase the electron transfer rate in the photosynthesis process, thus increasing the photosynthesis rate. The gene expression analysis showed that more than 90% of gene expression in photosynthesis was upregulated. After spraying the UCNP solution on the leaves of lettuce and placing the lettuce under sunlight for 1 week, the wet/dry weight of the leaves increased by 53.33% and 45.71%, respectively. This nanoengineering of light-harvesting UCNPs may have great potential for applications in agriculture.

Wind dynamics and leaf motion: Approaching the design of high-tech devices for energy harvesting for operation on plant leaves

High-tech sensors, energy harvesters, and robots are increasingly being developed for operation on plant leaves. This introduces an extra load which the leaf must withstand, often under further dynamic forces like wind. Here, we took the example of mechanical energy harvesters that consist of flat artificial "leaves" fixed on the petioles of N. oleander, converting wind energy into electricity. We developed a combined experimental and computational approach to describe the static and dynamic mechanics of the natural and artificial leaves individually and join them together in the typical energy harvesting configuration. The model, in which the leaves are torsional springs with flexible petioles and rigid lamina deforming under the effect of gravity and wind, enables us to design the artificial device in terms of weight, flexibility, and dimensions based on the mechanical properties of the plant leaf. Moreover, it predicts the dynamic motions of the leaf-artificial leaf combination, causing the mechanical-to-electrical energy conversion at a given wind speed. The computational results were validated in dynamic experiments measuring the electrical output of the plant-hybrid energy harvester. Our approach enables us to design the artificial structure for damage-safe operation on leaves (avoiding overloading caused by the interaction between leaves and/or by the wind) and suggests how to improve the combined leaf oscillations affecting the energy harvesting performance. We furthermore discuss how the mathematical model could be extended in future works. In summary, this is a first approach to improve the adaptation of artificial devices to plants, advance their performance, and to counteract damage by mathematical modelling in the device design phase.

Plant biomacromolecule delivery methods in the 21st century

The 21st century witnessed a boom in plant genomics and gene characterization studies through RNA interference and site-directed mutagenesis. Specifically, the last 15 years marked a rapid increase in discovering and implementing different genome editing techniques. Methods to deliver gene editing reagents have also attempted to keep pace with the discovery and implementation of gene editing tools in plants. As a result, various transient/stable, quick/lengthy, expensive (requiring specialized equipment)/inexpensive, and versatile/specific (species, developmental stage, or tissue) methods were developed. A brief account of these methods with emphasis on recent developments is provided in this review article. Additionally, the strengths and limitations of each method are listed to allow the reader to select the most appropriate method for their specific studies. Finally, a perspective for future developments and needs in this research area is presented.

Non-Invasive and Confirmatory Differentiation of Hermaphrodite from Both Male and Female Cannabis Plants Using a Hand-Held Raman Spectrometer

Cannabis (Cannabis sativa L.) is a dioecious plant that produces both male and female inflorescences. In nature, male and female plants can be found with nearly equal frequency, which determines species out-crossing. In cannabis farming, only female plants are preferred due to their high yield of cannabinoids. In addition to unfavorable male plants, commercial production of cannabis faces the appearance of hermaphroditic inflorescences, species displaying both pistillate flowers and anthers. Such plants can out-cross female plants, simultaneously producing undesired seeds. The problem of hermaphroditic cannabis triggered a search for analytical tools that can be used for their rapid detection and identification. In this study, we investigate the potential of Raman spectroscopy (RS), an emerging sensing technique that can be used to probe plant biochemistry. Our results show that the biochemistry of male, female and hermaphroditic cannabis plants is drastically different which allows for their confirmatory identification using a hand-held Raman spectrometer. Furthermore, the coupling of machine learning approaches enables the identification of hermaphrodites with 98.7% accuracy, whereas both male and female plants can be identified with 100% accuracy. Considering the label-free, non-invasive and non-destructive nature of RS, the developed optical sensing approach can transform cannabis farming in the U.S. and overseas.

Poly(allylamine)-copper(II) coordination complex grafted on core@shell upconversion nanoparticles for ultrafast and sensitive determination of the phytohormone salicylic acid in plant extracts

Salicylic acid (SA) is a phenolic phytohormone with critical roles in plant growth regulation and resistance to biotic and abiotic stress. Since low SA concentrations can modulate many plant biochemical responses, innovative analytical tools are required to deeply understand its activity and to control its exogenous application in modern agricultural systems. Herein, a NIR-activated composite based on NaYF₄:Yb,Er@NaYF₄ core@shell upconversion nanoparticles decorated with the poly(allylamine)-Cu(II) complex [UCNPs-PAAm-Cu(II)] was developed to sensitively determine the SA molecule in plant-derived samples. Accordingly, the PAAm-Cu(II) complex grafted on the UCNPs induces a strategic charge transfer band which triggers a quenching process through a resonance energy transfer (RET) mechanism. Such process is gradually deactivated upon the addition of SA and the consequent formation of the SA-Cu(II) complex, allowing a luminescence recovery in the 1-800 nM linear range. This mechanism is promoted by the strong stability of the SA-Cu(II) complex (log β_2-SA/Cu = 19.01) which is over twelve orders of magnitude stronger than the PAAm-Cu²⁺ counterpart. Furthermore, the equilibrium and kinetic studies on the involved mononuclear Cu²⁺ complexes formation permitted instantaneous analytical responses and excellent selectivity against other representative phytohormones and metallic cations. The reliability of this method was demonstrated by determining the SA content of some edible fruits and vegetables comprising apple, lemon, kiwi, tomato, and cucumber, whose concentrations ranged from 0.30 to 2.99 μg g^-1, with percent recoveries between 94.6 to 102.3%. Thereby, the reported nanocomplex can help to understand the SA activity in plants with significant applications in crop yield improvement and food quality assessment.

Raman Method in Identification of Species and Varieties, Assessment of Plant Maturity and Crop Quality—A Review

The present review covers reports discussing potential applications of the specificity of Raman techniques in the advancement of digital farming, in line with an assumption of yield maximisation with minimum environmental impact of agriculture. Raman is an optical spectroscopy method which can be used to perform immediate, label-free detection and quantification of key compounds without destroying the sample. The authors particularly focused on the reports discussing the use of Raman spectroscopy in monitoring the physiological status of plants, assessing crop maturity and quality, plant pathology and ripening, and identifying plant species and their varieties. In recent years, research reports have presented evidence confirming the effectiveness of Raman spectroscopy in identifying biotic and abiotic stresses in plants as well as in phenotyping and digital selection of plants in farming. Raman techniques used in precision agriculture can significantly improve capacities for farming management, crop quality assessment, as well as biological and chemical contaminant detection, thereby contributing to food safety as well as the productivity and profitability of agriculture. This review aims to increase the awareness of the growing potential of Raman spectroscopy in agriculture among plant breeders, geneticists, farmers and engineers.

Prospects of Fluorescent Single-Chirality Carbon Nanotube-Based Biosensors

Semiconducting single-wall carbon nanotubes (SWCNTs) fluoresce in the near-infrared (NIR), and the emission wavelength depends on their structure (chirality). Interactions with other molecules affect their fluorescence, which has successfully been used for SWCNT-based molecular sensors. So far, most such sensors are assembled from crude mixtures of different SWCNT chiralities, which causes polydisperse sensor responses as well as spectral congestion and limits their performance. The advent of chirality-pure SWCNTs is about to overcome this limitation and paves the way for the next generation of biosensors. Here, we discuss the first examples of chirality-pure SWCNT-based fluorescent biosensors. We introduce routes to such sensors via aqueous two-phase extraction-assisted purification of SWCNTs and highlight the critical interplay between purification and surface modification procedures. Applications include the NIR detection and imaging of neurotransmitters, reactive oxygen species, lipids, bacterial motives, and plant metabolites. Most importantly, we outline a path toward how such monodisperse (chirality-pure) sensors will enable advanced multiplexed sensing with enhanced bioanalytical performance.

Agricultural big data and methods and models for food security analysis-a mini-review

Background

Big data and data analysis methods and models are important tools in food security (FS) studies for gap analysis and preparation of appropriate analytical frameworks. These innovations necessitate the development of novel methods for collecting, storing, processing, and extracting data.

Methodology

The primary goal of this study was to conduct a critical review of agricultural big data and methods and models used for FS studies published in peer-reviewed journals since 2010. Approximately 130 articles were selected for full content review after the pre-screening process.

Results

There are different sources of data collection, including but not limited to online databases, the internet, omics, Internet of Things, social media, survey rounds, remote sensing, and the Food and Agriculture Organization Corporate Statistical Database. The collected data require analysis (i.e., mining, neural networks, Bayesian networks, and other ML algorithms) before data visualization using Python, R, Circos, Gephi, Tableau, or Cytoscape. Approximately 122 models, all of which were used in FS studies worldwide, were selected from 130 articles. However, most of these models addressed only one or two dimensions of FS (i.e., availability and access) and ignored the other dimensions (i.e., stability and utilization), creating a gap in the global context.

Conclusions

There are certain FS gaps both worldwide and in the United Arab Emirates that need to be addressed by scientists and policymakers. Following the identification of the drivers, policies, and indicators, the findings of this review could be used to develop an appropriate analytical framework for FS and nutrition.

Novel Materials for Urban Farming

Scarcity of natural resources, shifting demographics, climate change, and increasing waste are four major challenges in the quest to feed the exploding world population. These challenges serve as the impetus to harness novel technologies to improve agriculture, productivity, and sustainability. Urban farming has several advantages over conventional farming: higher productivity, improved sustainability, and the ability to provide fresh food all year round. Novel materials are key to accelerating the evolution of urban farming - with their ability to facilitate controlled release of nutrients and pesticides, improved seed health, substrates with better water retention capability, more efficient recycling of agricultural waste, and precise plant health monitoring. Materials science enables environmental sustainability and higher harvest yields in urban farms. Here, Singapore is used as an example of a land-scarce city where urban farming may be the solution for future food production. Potential research directions and challenges in urban farming are highlighted, and how material optimization and innovation drive the development of urban farming to meet national and global food demands is briefly discussed. This review serves as a guide for researchers and a reference for stakeholders of urban farms, policy makers, and other interested parties.

A fluorescent nanosensor paint detects dopamine release at axonal varicosities with high spatiotemporal resolution

SignificanceThe neurotransmitter dopamine controls normal behavior and dopaminergic dysfunction is prevalent in multiple brain diseases. To reach a detailed understanding of how dopamine release and signaling are regulated at the subcellular level, we developed a near infrared fluorescent dopamine nanosensor 'paint' (AndromeDA) to directly image dopamine release and its spatiotemporal characteristics. With AndromeDA, we can ascribe discrete DA release events to defined axonal varicosities, directly assess the heterogeneity of DA release events across such release sites, and determine the molecular components of the DA release machinery. AndromeDA thus provides a new method for gaining fundamental insights into the core mechanisms of dopamine release, which with greatly benefit our knowledge of dopamine biology and pathobiology.

Non-destructive Technologies for Plant Health Diagnosis

As global population grows rapidly, global food supply is increasingly under strain. This is exacerbated by climate change and declining soil quality due to years of excessive fertilizer, pesticide and agrichemical usage. Sustainable agricultural practices need to be put in place to minimize destruction to the environment while at the same time, optimize crop growth and productivity. To do so, farmers will need to embrace precision agriculture, using novel sensors and analytical tools to guide their farm management decisions. In recent years, non-destructive or minimally invasive sensors for plant metabolites have emerged as important analytical tools for monitoring of plant signaling pathways and plant response to external conditions that are indicative of overall plant health in real-time. This will allow precise application of fertilizers and synthetic plant growth regulators to maximize growth, as well as timely intervention to minimize yield loss from plant stress. In this mini-review, we highlight in vivo electrochemical sensors and optical nanosensors capable of detecting important endogenous metabolites within the plant, together with sensors that detect surface metabolites by probing the plant surface electrophysiology changes and air-borne volatile metabolites. The advantages and limitations of each kind of sensing tool are discussed with respect to their potential for application in high-tech future farms.

Raman Spectroscopy Enables Non-invasive and Confirmatory Diagnostics of Aluminum and Iron Toxicities in Rice

Metal toxicities can be detrimental to a plant health, as well as to the health of animals and humans that consume such plants. Metal content of plants can be analyzed using colorimetric, atomic absorption- or mass spectroscopy-based methods. However, these techniques are destructive, costly and laborious. In the current study, we investigate the potential of Raman spectroscopy (RS), a modern spectroscopic technique, for detection and identification of metal toxicities in rice. We modeled medium and high levels of iron and aluminum toxicities in hydroponically grown plants. Spectroscopic analyses of their leaves showed that both iron and aluminum toxicities can be detected and identified with ∼100% accuracy as early as day 2 after the stress initiation. We also showed that diagnostics accuracy was very high not only on early, but also on middle (day 4-day 8) and late (day 10-day 14) stages of the stress development. Importantly this approach only requires an acquisition time of 1 s; it is non-invasive and non-destructive to plants. Our findings suggest that if implemented in farming, RS can enable pre-symptomatic detection and identification of metallic toxins that would lead to faster recovery of crops and prevent further damage.

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.

Principles of Nanoparticle Design for Genome Editing in Plants

Precise plant genome editing technologies have provided new opportunities to accelerate crop improvement and develop more sustainable agricultural systems. In particular, the prokaryote-derived CRISPR platforms allow precise manipulation of the crop genome, enabling the generation of high-yielding and stress-tolerant crop varieties. Nanotechnology has the potential to catalyze the development of a novel molecular toolbox even further by introducing the possibility of a rapid, universal delivery method to edit the plant genome in a species-independent manner. In this Perspective, we highlight how nanoparticles can help unlock the full potential of CRISPR/Cas technology in targeted manipulation of the plant genome to improve agricultural output. We discuss current challenges hampering progress in nanoparticle-enabled plant gene-editing research and application in the field, and highlight how rational nanoparticle design can overcome them. Finally, we examine the implications of the regulatory frameworks and social acceptance for the future of nano-enabled precision breeding in the developing world.

Advances in optical phenotyping of cereal crops

Optical sensors and sensing-based phenotyping techniques have become mainstream approaches in high-throughput phenotyping for improving trait selection and genetic gains in crops. We review recent progress and contemporary applications of optical sensing-based phenotyping (OSP) techniques in cereal crops and highlight optical sensing principles for spectral response and sensor specifications. Further, we group phenotypic traits determined by OSP into four categories - morphological, biochemical, physiological, and performance traits - and illustrate appropriate sensors for each extraction. In addition to the current status, we discuss the challenges of OSP and provide possible solutions. We propose that optical sensing-based traits need to be explored further, and that standardization of the language of phenotyping and worldwide collaboration between phenotyping researchers and other fields need to be established.

Making Sense of Light: The Use of Optical Spectroscopy Techniques in Plant Sciences and Agriculture

As a result of the development of non-invasive optical spectroscopy, the number of prospective technologies of plant monitoring is growing. Being implemented in devices with different functions and hardware, these technologies are increasingly using the most advanced data processing algorithms, including machine learning and more available computing power each time. Optical spectroscopy is widely used to evaluate plant tissues, diagnose crops, and study the response of plants to biotic and abiotic stress. Spectral methods can also assist in remote and non-invasive assessment of the physiology of photosynthetic biofilms and the impact of plant species on biodiversity and ecosystem stability. The emergence of high-throughput technologies for plant phenotyping and the accompanying need for methods for rapid and non-contact assessment of plant productivity has generated renewed interest in the application of optical spectroscopy in fundamental plant sciences and agriculture. In this perspective paper, starting with a brief overview of the scientific and technological backgrounds of optical spectroscopy and current mainstream techniques and applications, we foresee the future development of this family of optical spectroscopic methodologies.

Illuminating the hidden world of calcium ions in plants with a universe of indicators

The tools available to carry out in vivo analysis of Ca²⁺ dynamics in plants are powerful and mature technologies that still require the proper controls.

Nanosensor Detection of Synthetic Auxins In Planta using Corona Phase Molecular Recognition

Synthetic auxins such as 1-naphthalene acetic acid (NAA) and 2,4-dichlorophenoxyacetic acid (2,4-D) have been extensively used in plant tissue cultures and as herbicides because they are chemically more stable and potent than most endogenous auxins. A tool for rapid in planta detection of these compounds will enhance our knowledge about hormone distribution and signaling and facilitate more efficient usage of synthetic auxins in agriculture. In this work, we show the development of real-time and nondestructive in planta NAA and 2,4-D nanosensors based on the concept of corona phase molecular recognition (CoPhMoRe), to replace the current state-of-the-art sensing methods that are destructive and laborious. By designing a library of cationic polymers wrapped around single-walled carbon nanotubes with general affinity for chemical moieties displayed on auxins and its derivatives, we developed selective sensors for these synthetic auxins, with a particularly large quenching response to NAA (46%) and a turn-on response to 2,4-D (51%). The NAA and 2,4-D nanosensors are demonstrated in planta across several plant species including spinach, Arabidopsis thaliana (A. thaliana), Brassica rapa subsp. chinensis (pak choi), and Oryza sativa (rice) grown in various media, including soil, hydroponic, and plant tissue culture media. After 5 h of 2,4-D supplementation to the hydroponic medium, 2,4-D is seen to accumulate in susceptible dicotyledon pak choi leaves, while no uptake is observed in tolerant monocotyledon rice leaves. As such, the 2,4-D nanosensor had demonstrated its capability for rapid testing of herbicide susceptibility and could help elucidate the mechanisms of 2,4-D transport and the basis for herbicide resistance in crops. The success of the CoPhMoRe technique for measuring these challenging plant hormones holds tremendous potential to advance the plant biology study.

Agriculture 4.0: Is Sub-Saharan Africa Ready?

A fourth agricultural revolution, termed agriculture 4.0, is gradually gaining ground around the globe. It encompasses the application of smart technologies such as artificial intelligence, biotechnology, the internet of things (IoT), big data, and robotics to improve agriculture and the sustainability of food production. To date, narratives around agriculture 4.0 associated technologies have generally focused on their application in the context of higher-income countries (HICs). In contrast, in this perspective, we critically assess the place of sub-Saharan Africa (SSA) in this new technology trajectory, a region that has received less attention with respect to the application of such technologies. We examine the continent’s readiness based on a number of dimensions such as scale, finance, technology leapfrogging, institutions and governance, education and skills. We critically reviewed the challenges, opportunities, and prospects of adopting agriculture 4.0 technologies in SSA, particularly with regards to how smallholder farmers in the region can be involved through a robust strategy. We find that whilst potential exist for agriculture 4.0 adoption in SSA, there are gaps in knowledge, skills, finance, and infrastructure to ensure successful adoption.

Non-Invasive Identification of Nutrient Components in Grain

Digital farming is a modern agricultural concept that aims to maximize the crop yield while simultaneously minimizing the environmental impact of farming. Successful implementation of digital farming requires development of sensors to detect and identify diseases and abiotic stresses in plants, as well as to probe the nutrient content of seeds and identify plant varieties. Experimental evidence of the suitability of Raman spectroscopy (RS) for confirmatory diagnostics of plant diseases was previously provided by our team and other research groups. In this study, we investigate the potential use of RS as a label-free, non-invasive and non-destructive analytical technique for the fast and accurate identification of nutrient components in the grains from 15 different rice genotypes. We demonstrate that spectroscopic analysis of intact rice seeds provides the accurate rice variety identification in ~86% of samples. These results suggest that RS can be used for fully automated, fast and accurate identification of seeds nutrient components.