Multi-sensor plant imaging: Towards the development of a stress-catalogue

Noninvasive, Presymptomatic Detection of Potato Cyst Nematode Infection in Tomato Using Chlorophyll Fluorescence Analysis

Potato cyst nematodes (PCNs) are notorious pathogens in all major potato production areas worldwide. Mainly due to the low mobility of this soil pathogen, PCN infestations are mostly observed as patches ("foci") that only cover a fraction of the acreage. In-field presymptomatic localization of these pathogens is valuable, as it would allow for the localized application of control measures. Although the mapping of foci is technically feasible, it is unpractical, as it would require the analysis of numerous soil samples. We investigated whether chlorophyll fluorescence (Chl-F) could be suitable as a rapid, nondestructive method for early PCN detection. To this end, the impact of four Globodera pallida densities on the Chl-F of tomato was investigated in a phenotyping greenhouse for 26 days. Furthermore, the classical plant performance indicators of biomass and root surface area were compared with Chl-F. Thermal dissipation (NPQ) and an estimate of the photosynthetic rate (ΦPSII) responded at 1 day postinoculation, and ΦPSII was most sensitive to low PCN infection levels. Chl-F parameters responded more readily to PCN infection than biomass and root surface area. The maximum quantum yield of photosystem II (Fv/Fm) and the potential activity of photosystem II (Fv/F0) initially increased at low PCN infection levels, whereas a sharp decrease was observed at higher infestation levels. Hence, our data suggest that low PCN levels promoted plant performance before becoming detrimental at higher levels. Although Chl-F allowed for early and sensitive PCN detection, it remains to be investigated whether these signals can be distinguished from those produced by other belowground stressors in the field. [Formula: see text] Copyright © 2025 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

From Detection to Protection: The Role of Optical Sensors, Robots, and Artificial Intelligence in Modern Plant Disease Management

In the past decade, there has been a recognized need for innovative methods to monitor and manage plant diseases, aiming to meet the precision demands of modern agriculture. Over the last 15 years, significant advances in the detection, monitoring, and management of plant diseases have been made, largely propelled by cutting-edge technologies. Recent advances in precision agriculture have been driven by sophisticated tools such as optical sensors, artificial intelligence, microsensor networks, and autonomous driving vehicles. These technologies have enabled the development of novel cropping systems, allowing for targeted management of crops, contrasting with the traditional, homogeneous treatment of large crop areas. The research in this field is usually a highly collaborative and interdisciplinary endeavor. It brings together experts from diverse fields such as plant pathology, computer science, statistics, engineering, and agronomy to forge comprehensive solutions. Despite the progress, translating the advancements in the precision of decision-making or automation into agricultural practice remains a challenge. The knowledge transfer to agricultural practice and extension has been particularly challenging. Enhancing the accuracy and timeliness of disease detection continues to be a priority, with data-driven artificial intelligence systems poised to play a pivotal role. This perspective article addresses critical questions and challenges faced in the implementation of digital technologies for plant disease management. It underscores the urgency of integrating innovative technological advances with traditional integrated pest management. It highlights unresolved issues regarding the establishment of control thresholds for site-specific treatments and the necessary alignment of digital technology use with regulatory frameworks. Importantly, the paper calls for intensified research efforts, widespread knowledge dissemination, and education to optimize the application of digital tools for plant disease management, recognizing the intersection of technology's potential with its current practical limitations.

ChloroSpec: A new in vivo chlorophyll fluorescence spectrometer for simultaneous wavelength- and time-resolved detection

Chlorophyll fluorescence is a ubiquitous tool in basic and applied plant science research. Various standard commercial instruments are available for characterization of photosynthetic material like leaves or microalgae, most of which integrate the overall fluorescence signals above a certain cut-off wavelength. However, wavelength-resolved (fluorescence signals appearing at different wavelengths having different time dependent decay) signals contain vast information required to decompose complex signals and processes into their underlying components that can untangle the photo-physiological process of photosynthesis. Hence, to address this we describe an advanced chlorophyll fluorescence spectrometer - ChloroSpec - allowing three-dimensional simultaneous detection of fluorescence intensities at different wavelengths in a time-resolved manner. We demonstrate for a variety of typical examples that most of the generally used fluorescence parameters are strongly wavelength dependent. This indicates a pronounced heterogeneity and a highly dynamic nature of the thylakoid and the photosynthetic apparatus under actinic illumination. Furthermore, we provide examples of advanced global analysis procedures integrating this three-dimensional signal and relevant information extracted from them that relate to the physiological properties of the organism. This conveniently obtained broad range of data can make ChloroSpec a new standard tool in photosynthesis research.

Screening of Ginkgo Individuals with Superior Growth Structural Characteristics in Different Genetic Groups Using Terrestrial Laser Scanning (TLS) Data

With the concept of sustainable management of plantations, individual trees with excellent characteristics in plantations have received attention from breeders. To improve and maintain long-term productivity, accurate and high-throughput access to phenotypic characteristics is essential when establishing breeding strategies. Meanwhile, genetic diversity is also an important issue that must be considered, especially for plantations without seed source information. This study was carried out in a ginkgo timber plantation. We used simple sequence repeat (SSR) markers for genetic background analysis and high-density terrestrial laser scanning for growth structural characteristic extraction, aiming to provide a possibility of applying remote sensing approaches for forest breeding. First, we analyzed the genetic diversity and population structure, and grouped individual trees according to the genetic distance. Then, the growth structural characteristics (height, diameter at breast height, crown width, crown area, crown volume, height to living crown, trunk volume, biomass of all components) were extracted. Finally, individual trees in each group were comprehensively evaluated and the best-performing ones were selected. Results illustrate that terrestrial laser scanning (TLS) point cloud data can provide nondestructive estimates of the growth structural characteristics at fine scale. From the ginkgo plantation containing high genetic diversity (average polymorphism information content index was 0.719) and high variation in growth structural characteristics (coefficient of variation ranged from 21.822% to 85.477%), 11 excellent individual trees with superior growth were determined. Our study guides the scientific management of plantations and also provides a potential for applying remote sensing technologies to accelerate forest breeding.

Early-Stage Detection of Biotic and Abiotic Stress on Plants by Chlorophyll Fluorescence Imaging Analysis

Most agricultural land, as a result of climate change, experiences severe stress that significantly reduces agricultural yields. Crop sensing by imaging techniques allows early-stage detection of biotic or abiotic stress to avoid damage and significant yield losses. Among the top certified imaging techniques for plant stress detection is chlorophyll a fluorescence imaging, which can evaluate spatiotemporal leaf changes, permitting the pre-symptomatic monitoring of plant physiological status long before any visible symptoms develop, allowing for high-throughput assessment. Here, we review different examples of how chlorophyll a fluorescence imaging analysis can be used to evaluate biotic and abiotic stress. Chlorophyll a is able to detect biotic stress as early as 15 min after Spodoptera exigua feeding, or 30 min after Botrytis cinerea application on tomato plants, or on the onset of water-deficit stress, and thus has potential for early stress detection. Chlorophyll fluorescence (ChlF) analysis is a rapid, non-invasive, easy to perform, low-cost, and highly sensitive method that can estimate photosynthetic performance and detect the influence of diverse stresses on plants. In terms of ChlF parameters, the fraction of open photosystem II (PSII) reaction centers (qp) can be used for early stress detection, since it has been found in many recent studies to be the most accurate and appropriate indicator for ChlF-based screening of the impact of environmental stress on plants.

Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review

Remote detection and monitoring of the vegetation responses to stress became relevant for sustainable agriculture. Ongoing developments in optical remote sensing technologies have provided tools to increase our understanding of stress-related physiological processes. Therefore, this study aimed to provide an overview of the main spectral technologies and retrieval approaches for detecting crop stress in agriculture. Firstly, we present integrated views on: i) biotic and abiotic stress factors, the phases of stress, and respective plant responses, and ii) the affected traits, appropriate spectral domains and corresponding methods for measuring traits remotely. Secondly, representative results of a systematic literature analysis are highlighted, identifying the current status and possible future trends in stress detection and monitoring. Distinct plant responses occurring under shortterm, medium-term or severe chronic stress exposure can be captured with remote sensing due to specific light interaction processes, such as absorption and scattering manifested in the reflected radiance, i.e. visible (VIS), near infrared (NIR), shortwave infrared, and emitted radiance, i.e. solar-induced fluorescence and thermal infrared (TIR). From the analysis of 96 research papers, the following trends can be observed: increasing usage of satellite and unmanned aerial vehicle data in parallel with a shift in methods from simpler parametric approaches towards more advanced physically-based and hybrid models. Most study designs were largely driven by sensor availability and practical economic reasons, leading to the common usage of VIS-NIR-TIR sensor combinations. The majority of reviewed studies compared stress proxies calculated from single-source sensor domains rather than using data in a synergistic way. We identified new ways forward as guidance for improved synergistic usage of spectral domains for stress detection: (1) combined acquisition of data from multiple sensors for analysing multiple stress responses simultaneously (holistic view); (2) simultaneous retrieval of plant traits combining multi-domain radiative transfer models and machine learning methods; (3) assimilation of estimated plant traits from distinct spectral domains into integrated crop growth models. As a future outlook, we recommend combining multiple remote sensing data streams into crop model assimilation schemes to build up Digital Twins of agroecosystems, which may provide the most efficient way to detect the diversity of environmental and biotic stresses and thus enable respective management decisions.

Predicting Water Stress in Wild Blueberry Fields Using Airborne Visible and Near Infrared Imaging Spectroscopy

Water management and irrigation practices are persistent challenges for many agricultural systems, exacerbated by changing seasonal and weather patterns. The wild blueberry industry is at heightened susceptibility due to its unique growing conditions and uncultivated nature. Stress detection in agricultural fields can prompt management responses to mitigate detrimental conditions, including drought and disease. We assessed airborne spectral data accompanied by ground sampled water potential over three developmental stages of wild blueberries collected throughout the 2019 summer on two adjacent fields, one irrigated and one non-irrigated. Ground sampled leaves were collected in tandem to the hyperspectral image collection with an unoccupied aerial vehicle (UAV) and then measured for leaf water potential. Using methods in machine learning and statistical analysis, we developed models to determine irrigation status and water potential. Seven models were assessed in this study, with four used to process six hyperspectral cube images for analysis. These images were classified as irrigated or non-irrigated and estimated for water potential levels, resulting in an R2 of 0.62 and verified with a validation dataset. Further investigation relating imaging spectroscopy and water potential will be beneficial in understanding the dynamics between the two for future studies.

Past and Future of Plant Stress Detection: An Overview From Remote Sensing to Positron Emission Tomography

Plant stress detection is considered one of the most critical areas for the improvement of crop yield in the compelling worldwide scenario, dictated by both the climate change and the geopolitical consequences of the Covid-19 epidemics. A complicated interconnection of biotic and abiotic stressors affect plant growth, including water, salt, temperature, light exposure, nutrients availability, agrochemicals, air and soil pollutants, pests and diseases. In facing this extended panorama, the technology choice is manifold. On the one hand, quantitative methods, such as metabolomics, provide very sensitive indicators of most of the stressors, with the drawback of a disruptive approach, which prevents follow up and dynamical studies. On the other hand qualitative methods, such as fluorescence, thermography and VIS/NIR reflectance, provide a non-disruptive view of the action of the stressors in plants, even across large fields, with the drawback of a poor accuracy. When looking at the spatial scale, the effect of stress may imply modifications from DNA level (nanometers) up to cell (micrometers), full plant (millimeters to meters), and entire field (kilometers). While quantitative techniques are sensitive to the smallest scales, only qualitative approaches can be used for the larger ones. Emerging technologies from nuclear and medical physics, such as computed tomography, magnetic resonance imaging and positron emission tomography, are expected to bridge the gap of quantitative non-disruptive morphologic and functional measurements at larger scale. In this review we analyze the landscape of the different technologies nowadays available, showing the benefits of each approach in plant stress detection, with a particular focus on the gaps, which will be filled in the nearby future by the emerging nuclear physics approaches to agriculture.

Applications of Multi-Omics Technologies for Crop Improvement

Multiple "omics" approaches have emerged as successful technologies for plant systems over the last few decades. Advances in next-generation sequencing (NGS) have paved a way for a new generation of different omics, such as genomics, transcriptomics, and proteomics. However, metabolomics, ionomics, and phenomics have also been well-documented in crop science. Multi-omics approaches with high throughput techniques have played an important role in elucidating growth, senescence, yield, and the responses to biotic and abiotic stress in numerous crops. These omics approaches have been implemented in some important crops including wheat (Triticum aestivum L.), soybean (Glycine max), tomato (Solanum lycopersicum), barley (Hordeum vulgare L.), maize (Zea mays L.), millet (Setaria italica L.), cotton (Gossypium hirsutum L.), Medicago truncatula, and rice (Oryza sativa L.). The integration of functional genomics with other omics highlights the relationships between crop genomes and phenotypes under specific physiological and environmental conditions. The purpose of this review is to dissect the role and integration of multi-omics technologies for crop breeding science. We highlight the applications of various omics approaches, such as genomics, transcriptomics, proteomics, metabolomics, phenomics, and ionomics, and the implementation of robust methods to improve crop genetics and breeding science. Potential challenges that confront the integration of multi-omics with regard to the functional analysis of genes and their networks as well as the development of potential traits for crop improvement are discussed. The panomics platform allows for the integration of complex omics to construct models that can be used to predict complex traits. Systems biology integration with multi-omics datasets can enhance our understanding of molecular regulator networks for crop improvement. In this context, we suggest the integration of entire omics by employing the "phenotype to genotype" and "genotype to phenotype" concept. Hence, top-down (phenotype to genotype) and bottom-up (genotype to phenotype) model through integration of multi-omics with systems biology may be beneficial for crop breeding improvement under conditions of environmental stresses.

Imaging of Chlorophyll a Fluorescence in Natural Compound-Induced Stress Detection

Imaging of chlorophyll a fluorescence (CFI) represents an easy, precise, fast and non-invasive technique that can be successfully used for discriminating plant response to phytotoxic stress with reproducible results and without damaging the plants. The spatio-temporal analyses of the fluorescence images can give information about damage evolution, secondary effects and plant defense response. In the last years, some studies about plant natural compounds-induced phytotoxicity have introduced imaging techniques to measure fluorescence, although the analysis of the image as a whole is often missed. In this paper we, therefore, evaluated the advantages of monitoring fluorescence images, presenting the physiological interpretation of different possible combinations of the most relevant parameters linked to fluorescence emission and the images obtained.

Phenotyping in Arabidopsis and Crops-Are We Addressing the Same Traits? A Case Study in Tomato

The convenient model Arabidopsis thaliana has allowed tremendous advances in plant genetics and physiology, in spite of only being a weed. It has also unveiled the main molecular networks governing, among others, abiotic stress responses. Through the use of the latest genomic tools, Arabidopsis research is nowadays being translated to agronomically interesting crop models such as tomato, but at a lagging pace. Knowledge transfer has been hindered by invariable differences in plant architecture and behaviour, as well as the divergent direct objectives of research in Arabidopsis versus crops compromise transferability. In this sense, phenotype translation is still a very complex matter. Here, we point out the challenges of "translational phenotyping" in the case study of drought stress phenotyping in Arabidopsis and tomato. After briefly defining and describing drought stress and survival strategies, we compare drought stress protocols and phenotyping techniques most commonly used in the two species, and discuss their potential to gain insights, which are truly transferable between species. This review is intended to be a starting point for discussion about translational phenotyping approaches among plant scientists, and provides a useful compendium of methods and techniques used in modern phenotyping for this specific plant pair as a case study.

Noninvasive determination of toxic stress biomarkers by high-throughput screening of photoautotrophic cell suspension cultures with multicolor fluorescence imaging

BACKGROUND

With increasing pollution, herbicide application and interest in plant phenotyping, sensors capturing early responses to toxic stress are demanded for screening susceptible or resistant plant varieties. Standard toxicity tests on plants are laborious, demanding in terms of space and material, and the measurement of growth-inhibition based endpoints takes relatively long time. The aim of this work was to explore the potential of photoautotrophic cell suspension cultures for high-throughput early toxicity screening based on imaging techniques. The investigation of the universal potential of fluorescence imaging methods involved testing of three toxicants with different modes of action (DCMU, glyphosate and chromium).

RESULTS

The increased pace of testing was achieved by using non-destructive imaging methods-multicolor fluorescence (MCF) and chlorophyll fluorescence (ChlF). These methods detected the negative effects of the toxicants earlier than it was reflected in plant growth inhibition (decrease in leaf area and final dry weight). Moreover, more subtle and transient effects not resulting in growth inhibition could be detected by fluorescence. The pace and sensitivity of stress detection was further enhanced by using photoautotrophic cell suspension cultures. These reacted sooner, more pronouncedly and to lower concentrations of the tested toxicants than the plants. Toxicant-specific stress signatures were observed as a combination of MCF and ChlF parameters and timing of the response. Principal component analysis was found to be useful for reduction of the collected multidimensional data sets to a few informative parameters allowing comparison of the toxicant signatures.

CONCLUSIONS

Photoautotrophic cell suspension cultures have proved to be useful for rapid high-throughput screening of toxic stress and display a potential for employment as an alternative to tests on whole plants. The MCF and ChlF methods are capable of distinguishing early stress signatures of at least three different modes of action.

Detection of Bacterial Infection in Melon Plants by Classification Methods Based on Imaging Data

The bacterium Dickeya dadantii is responsible of important economic losses in crop yield worldwide. In melon leaves, D. dadantii produced multiple necrotic spots surrounded by a chlorotic halo, followed by necrosis of the whole infiltrated area and chlorosis in the surrounding tissues. The extent of these symptoms, as well as the day of appearance, was dose-dependent. Several imaging techniques (variable chlorophyll fluorescence, multicolor fluorescence, and thermography) provided spatial and temporal information about alterations in the primary and secondary metabolism, as well as the stomatal activity in the infected leaves. Detection of diseased leaves was carried out by using machine learning on the numerical data provided by these imaging techniques. Mathematical algorithms based on data from infiltrated areas offered 96.5 to 99.1% accuracy when classifying them as mock vs. bacteria-infiltrated. These algorithms also showed a high performance of classification of whole leaves, providing accuracy values of up to 96%. Thus, the detection of disease on whole leaves by a model trained on infiltrated areas appears as a reliable method that could be scaled-up for use in plant breeding programs or precision agriculture.

Chlorophyll Fluorescence Video Imaging: A Versatile Tool for Identifying Factors Related to Photosynthesis

Measurements of chlorophyll fluorescence provide an elegant and non-invasive means of probing the dynamics of photosynthesis. Advances in video imaging of chlorophyll fluorescence have now made it possible to study photosynthesis at all levels from individual cells to entire crop populations. Since the technology delivers quantitative data, is easily scaled up and can be readily combined with other approaches, it has become a powerful phenotyping tool for the identification of factors relevant to photosynthesis. Here, we review genetic chlorophyll fluorescence-based screens of libraries of Arabidopsis and Chlamydomonas mutants, discuss its application to high-throughput phenotyping in quantitative genetics and highlight potential future developments.

From laboratory to field studies - The assessment of Biscutella laevigata suitability to biological reclamation of areas contaminated with lead and cadmium

The aim of the work was to evaluate the usefulness of the in vitro multiplication of Biscutella laevigata calamine ecotype for in situ reclamation of post-flotation wastes polluted with Pb and Cd. The experiment was conducted on three steps: (i) plant shoots' production under in vitro condition, (ii) establishment of the material in greenhouse experiment, and finally (iii) field cultivation directly on the mining-waste heap of Olkusz Ore-Bearing Region, Poland. This region is known to be one of the most chemically-degraded area in central Europe. The laboratory-set in vitro analysis enabled to obtain the high-quality plant shoots, which multiply the most effectively (with growth tolerance index 130-150%) on medium containing 5.0μM CdCl₂ and 0.5mM Pb(NO₃)₂. These plants were used for the next two ex vitro experiments. Several biometric and physiological analysis (i.e. of photosystem II activity F_v/F_m and PI, photosynthetic pigment contents) were done to indicate plant physiological status during these experiments. The main novelty of the work was to prove that in vitro-multiplied shoots of B. laevigata - the representative of native flora from Olkusz Ore-Bearing Region - can be successfully implemented in situ for the restoration of these degraded area. Moreover, the addition of sewage sludge as a source of organic compounds significantly improved plants' growth and development what is especially important due to the lack of other legal solutions for the management of the sewage sludge in some countries.

Use of Natural Diversity and Biotechnology to Increase the Quality and Nutritional Content of Tomato and Grape

Improving fruit quality has become a major goal in plant breeding. Direct approaches to tackling fruit quality traits specifically linked to consumer preferences and environmental friendliness, such as improved flavor, nutraceutical compounds, and sustainability, have slowly been added to a breeder priority list that already includes traits like productivity, efficiency, and, especially, pest and disease control. Breeders already use molecular genetic tools to improve fruit quality although most advances have been made in producer and industrial quality standards. Furthermore, progress has largely been limited to simple agronomic traits easy-to-observe, whereas the vast majority of quality attributes, specifically those relating to flavor and nutrition, are complex and have mostly been neglected. Fortunately, wild germplasm, which is used for resistance against/tolerance of environmental stresses (including pathogens), is still available and harbors significant genetic variation for taste and health-promoting traits. Similarly, heirloom/traditional varieties could be used to identify which genes contribute to flavor and health quality and, at the same time, serve as a good source of the best alleles for organoleptic quality improvement. Grape (Vitis vinifera L.) and tomato (Solanum lycopersicum L.) produce fleshy, berry-type fruits, among the most consumed in the world. Both have undergone important domestication and selection processes, that have dramatically reduced their genetic variability, and strongly standardized fruit traits. Moreover, more and more consumers are asking for sustainable production, incompatible with the wide range of chemical inputs. In the present paper, we review the genetic resources available to tomato/grape breeders, and the recent technological progresses that facilitate the identification of genes/alleles of interest within the natural or generated variability gene pool. These technologies include omics, high-throughput phenotyping/phenomics, and biotech approaches. Our review also covers a range of technologies used to transfer to tomato and grape those alleles considered of interest for fruit quality. These include traditional breeding, TILLING (Targeting Induced Local Lesions in Genomes), genetic engineering, or NPBT (New Plant Breeding Technologies). Altogether, the combined exploitation of genetic variability and innovative biotechnological tools may facilitate breeders to improve fruit quality tacking more into account the consumer standards and the needs to move forward into more sustainable farming practices.

A Rapid Laser Probing Method Facilitates the Non-invasive and Contact-free Determination of Leaf Thermal Properties

Plants can produce valuable substances such as secondary metabolites and recombinant proteins. The purification of the latter from plant biomass can be streamlined by heat treatment (blanching). A blanching apparatus can be designed more precisely if the thermal properties of the leaves are known in detail, i.e., the specific heat capacity and thermal conductivity. The measurement of these properties is time consuming and labor intensive, and usually requires invasive methods that contact the sample directly. This can reduce the product yield and may be incompatible with containment requirements, e.g., in the context of good manufacturing practice. To address these issues, a non-invasive, contact-free method was developed that determines the specific heat capacity and thermal conductivity of an intact plant leaf in about one minute. The method involves the application of a short laser pulse of defined length and intensity to a small area of the leaf sample, causing a temperature increase that is measured using a near infrared sensor. The temperature increase is combined with known leaf properties (thickness and density) to determine the specific heat capacity. The thermal conductivity is then calculated based on the profile of the subsequent temperature decline, taking thermal radiation and convective heat transfer into account. The associated calculations and critical aspects of sample handling are discussed.

Determination of the thermal properties of leaves by non-invasive contact‑free laser probing

The thermal properties of materials provide valuable data for quality monitoring and the rational design of process steps where heating is required. Here we report a rapid, simple and reliable technique that determines the most important thermal properties of leaves, i.e. the specific heat capacity (cp) and thermal conductivity (λ). Such data are useful when leaves are heated during processing, e.g. for the precipitation of host cell proteins during the extraction of high-value products such as recombinant proteins produced by molecular farming. The cp of tobacco (Nicotiana tabacum) and Nicotiana benthamiana leaves was determined by infrared measurement of the temperature increase caused by a near-infrared laser pulse of defined length and intensity. We used the sample temperature profiles to calculate λ based on exponential fits of the temperature decline, taking convective heat transfer and thermal radiation into account. We found that the average cp was 3661 ± 323 J kg(-1) K(-1) (n=19) for tobacco and 2253 ± 285 J kg(-1) K(-1) (n=25) for N. benthamiana, whereas the average λ was 0.49 ± 0.13 (n=19) for tobacco and 0.41 ± 0.20 (n=25) Jm(-1) s(-1)K(-1) for N. benthamiana. These values are similar to those established for other plant species by photothermal imaging and other methods. The cp and λ values of leaves can be determined easily using our non-invasive method, which is therefore suitable for the in-line or at-line monitoring of plants, e.g. during the highly regulated production of biopharmaceutical proteins.

Tracking transience: a method for dynamic monitoring of biological events in Arabidopsis thaliana biosensors

The activation and level of expression of an endogenous, stress-responsive biosensor (bioreporter) can be visualized in real-time and non-destructively using highly accessible equipment (fluorometer). Biosensor output can be linked to computer-controlled systems to enable feedback-based control of a greenhouse environment. Today's agriculture requires an ability to precisely and rapidly assess the physiological stress status of plants in order to optimize crop yield. Here we describe the implementation and utility of a detection system based on a simple fluorometer design for real-time, continuous, and non-destructive monitoring of a genetically engineered biosensor plant. We report the responses to heat stress of Arabidopsis thaliana plants expressing a Yellow Fluorescent Protein bioreporter under the control of the DREB2A temperature-sensing promoter. Use of this bioreporter provides the ability to identify transient and steady-state behavior of gene activation in response to stress, and serves as an interface for novel experimental protocols. Models identified through such experiments inform the development of computer-based feedback control systems for the greenhouse environment, based on in situ monitoring of mature plants. More broadly, the work here provides a basis for informing biologists and engineers about the kinetics of bioreporter constructs, and also about ways in which other fluorescent protein constructs could be integrated into automated control systems.

Current and Prospective Methods for Plant Disease Detection

Food losses due to crop infections from pathogens such as bacteria, viruses and fungi are persistent issues in agriculture for centuries across the globe. In order to minimize the disease induced damage in crops during growth, harvest and postharvest processing, as well as to maximize productivity and ensure agricultural sustainability, advanced disease detection and prevention in crops are imperative. This paper reviews the direct and indirect disease identification methods currently used in agriculture. Laboratory-based techniques such as polymerase chain reaction (PCR), immunofluorescence (IF), fluorescence in-situ hybridization (FISH), enzyme-linked immunosorbent assay (ELISA), flow cytometry (FCM) and gas chromatography-mass spectrometry (GC-MS) are some of the direct detection methods. Indirect methods include thermography, fluorescence imaging and hyperspectral techniques. Finally, the review also provides a comprehensive overview of biosensors based on highly selective bio-recognition elements such as enzyme, antibody, DNA/RNA and bacteriophage as a new tool for the early identification of crop diseases.

Coping with drought: stress and adaptive responses in potato and perspectives for improvement

Potato (Solanum tuberosum L.) is often considered as a drought sensitive crop and its sustainable production is threatened due to frequent drought episodes. There has been much research aiming to understand the physiological, biochemical, and genetic basis of drought tolerance in potato as a basis for improving production under drought conditions. The complex phenotypic response of potato plants to drought is conditioned by the interactive effects of the plant's genotypic potential, developmental stage, and environment. Effective crop improvement for drought tolerance will require the pyramiding of many disparate characters, with different combinations being appropriate for different growing environments. An understanding of the interaction between below ground water uptake by the roots and above ground water loss from the shoot system is essential. The development of high throughput precision phenotyping platforms is providing an exciting new tool for precision screening, which, with the incorporation of innovative screening strategies, can aid the selection and pyramiding of drought-related genes appropriate for specific environments. Outcomes from genomics, proteomics, metabolomics, and bioengineering advances will undoubtedly compliment conventional breeding strategies and presents an alternative route toward development of drought tolerant potatoes. This review presents an overview of past research activity, highlighting recent advances with examples from other crops and suggesting future research directions.

A review of imaging techniques for plant phenotyping

Given the rapid development of plant genomic technologies, a lack of access to plant phenotyping capabilities limits our ability to dissect the genetics of quantitative traits. Effective, high-throughput phenotyping platforms have recently been developed to solve this problem. In high-throughput phenotyping platforms, a variety of imaging methodologies are being used to collect data for quantitative studies of complex traits related to the growth, yield and adaptation to biotic or abiotic stress (disease, insects, drought and salinity). These imaging techniques include visible imaging (machine vision), imaging spectroscopy (multispectral and hyperspectral remote sensing), thermal infrared imaging, fluorescence imaging, 3D imaging and tomographic imaging (MRT, PET and CT). This paper presents a brief review on these imaging techniques and their applications in plant phenotyping. The features used to apply these imaging techniques to plant phenotyping are described and discussed in this review.

A novel system for spatial and temporal imaging of intrinsic plant water use efficiency

Instrumentation and methods for rapid screening and selection of plants with improved water use efficiency are essential to address current issues of global food and fuel security. A new imaging system that combines chlorophyll fluorescence and thermal imaging has been developed to generate images of assimilation rate (A), stomatal conductance (gs), and intrinsic water use efficiency (WUEi) from whole plants or leaves under controlled environmental conditions. This is the first demonstration of the production of images of WUEi and the first to determine images of g s from themography at the whole-plant scale. Data are presented illustrating the use of this system for rapidly and non-destructively screening plants for alterations in WUEi by comparing Arabidopsis thaliana mutants (OST1-1) that have altered WUEi driven by open stomata, with wild-type plants. This novel instrument not only provides the potential to monitor multiple plants simultaneously, but enables intra- and interspecies variation to be taken into account both spatially and temporally. The ability to measure A, gs, and WUEi progressively was developed to facilitate and encourage the development of new dynamic protocols. Images illustrating the instrument's dynamic capabilities are demonstrated by analysing plant responses to changing photosynthetic photon flux density (PPFD). Applications of this system will augment the research community's need for novel screening methods to identify rapidly novel lines, cultivars, or species with improved A and WUEi in order to meet the current demands on modern agriculture and food production.

Thermography to explore plant-environment interactions

Stomatal regulation is a key determinant of plant photosynthesis and water relations, influencing plant survival, adaptation, and growth. Stomata sense the surrounding environment and respond rapidly to abiotic and biotic stresses. Stomatal conductance to water vapour (g s) and/or transpiration (E) are therefore valuable physiological parameters to be monitored in plant and agricultural sciences. However, leaf gas exchange measurements involve contact with leaves and often interfere with leaf functioning. Besides, they are time consuming and are limited by the sampling characteristics (e.g. sample size and/or the high number of samples required). Remote and rapid means to assess g s or E are thus particularly valuable for physiologists, agronomists, and ecologists. Transpiration influences the leaf energy balance and, consequently, leaf temperature (T leaf). As a result, thermal imaging makes it possible to estimate or quantify g s and E. Thermal imaging has been successfully used in a wide range of conditions and with diverse plant species. The technique can be applied at different scales (e.g. from single seedlings/leaves through whole trees or field crops to regions), providing great potential to study plant-environment interactions and specific phenomena such as abnormal stomatal closure, genotypic variation in stress tolerance, and the impact of different management strategies on crop water status. Nevertheless, environmental variability (e.g. in light intensity, temperature, relative humidity, wind speed) affects the accuracy of thermal imaging measurements. This review presents and discusses the advantages of thermal imaging applications to plant science, agriculture, and ecology, as well as its limitations and possible approaches to minimize them, by highlighting examples from previous and ongoing research.

Biosensors for phytohormone quantification: challenges, solutions, and opportunities

Fluorescent reporters are valuable tools for plant science research, particularly as sensors to monitor biological signals and developmental processes. Such biosensors are particularly useful to monitor the spatial and temporal distribution of small signalling molecules such as phytohormones. Knowledge of perception and signalling pathways can be exploited to design biosensors for estimating intracellular abundance of hormones. However, the nonlinear relationship between target molecule and reporter necessitates the development of parameterised mathematical models to quantitatively relate sensor fluorescence to hormone abundance. In this opinion article, we will discuss the use of transcriptional reporters, sensor design strategy, and the importance of mathematical modelling approaches and technological advances in the development of new techniques to allow truly quantitative analyses of hormone regulated processes.

Integration of the 1,2,3-triazole "click" motif as a potent signalling element in metal ion responsive fluorescent probes

In a systematic approach we synthesized a new series of fluorescent probes incorporating donor-acceptor (D-A) substituted 1,2,3-triazoles as conjugative π-linkers between the alkali metal ion receptor N-phenylaza-[18]crown-6 and different fluorophoric groups with different electron-acceptor properties (4-naphthalimide, meso-phenyl-BODIPY and 9-anthracene) and investigated their performance in organic and aqueous environments (physiological conditions). In the charge-transfer (CT) type probes 1, 2 and 7, the fluorescence is almost completely quenched by intramolecular CT (ICT) processes involving charge-separated states. In the presence of Na(+) and K(+) ICT is interrupted, which resulted in a lighting-up of the fluorescence in acetonitrile. Among the investigated fluoroionophores, compound 7, which contains a 9-anthracenyl moiety as the electron-accepting fluorophore, is the only probe which retains light-up features in water and works as a highly K(+)/Na(+)-selective probe under simulated physiological conditions. Virtually decoupled BODIPY-based 6 and photoinduced electron transfer (PET) type probes 3-5, where the 10-substituted anthracen-9-yl fluorophores are connected to the 1,2,3-triazole through a methylene spacer, show strong ion-induced fluorescence enhancement in acetonitrile, but not under physiological conditions. Electrochemical studies and theoretical calculations were used to assess and support the underlying mechanisms for the new ICT and PET 1,2,3-triazole fluoroionophores.

Future scenarios for plant phenotyping

With increasing demand to support and accelerate progress in breeding for novel traits, the plant research community faces the need to accurately measure increasingly large numbers of plants and plant parameters. The goal is to provide quantitative analyses of plant structure and function relevant for traits that help plants better adapt to low-input agriculture and resource-limited environments. We provide an overview of the inherently multidisciplinary research in plant phenotyping, focusing on traits that will assist in selecting genotypes with increased resource use efficiency. We highlight opportunities and challenges for integrating noninvasive or minimally invasive technologies into screening protocols to characterize plant responses to environmental challenges for both controlled and field experimentation. Although technology evolves rapidly, parallel efforts are still required because large-scale phenotyping demands accurate reporting of at least a minimum set of information concerning experimental protocols, data management schemas, and integration with modeling. The journey toward systematic plant phenotyping has only just begun.

Phytoalexin transgenics in crop protection--fairy tale with a happy end?

Phytoalexins are pathogen induced low molecular weight compounds with antimicrobial activities derived from secondary metabolism. Following their identification, phytoalexins were directly incorporated into the network of plant defense responses. Due to their heterogeneity, the metabolic pathways involved in phytoalexin formation and in particular the regulatory mechanisms remained elusive. Consequently, research focus shifted to the characterization of other components of plant immunity such as defense signaling and resistance mechanisms, including components of systemic acquired and induced systemic resistance, effector and pathogen-associated molecular pattern triggered immunity as well as R-gene resistance. Despite the obtained knowledge on these immunity mechanisms, genetic engineering employing these mechanisms and classical breeding reached too low improvements in crop protection, probably because classical breeding focused on yield performance and taste, rather than pathogen resistance. The increasing demand for disease resistant crop species and the aim to reduce pesticide application therefore requires alternative approaches. Recent advances in the understanding of phytoalexin function, biosynthesis and regulation, in combination with novel methods of molecular engineering and advances in instrumental analysis, returned attention to phytoalexins as a potent target for improving crop protection. Based on this, the advantages as well as potential bottlenecks for molecular approaches of modulating inducible phytoalexins to improve crop protection are discussed.

Interaction of proline, sugars, and anthocyanins during photosynthetic acclimation of Arabidopsis thaliana to drought stress

The relationships among photosynthetic acclimation, proline (Pro), soluble sugar (SS), and anthocyanin (An) accumulation in Arabidopsis thaliana leaves to the onset of drought stress (OnDS), mild (MiDS) and moderate drought stress (MoDS), were evaluated. As leaf water content (LWC) decreased, metabolic concentrations (Pro, SS, and An) increased and were negatively and significantly correlated with LWC. Thus, these metabolites may have an important role in the acclimation process to drought stress (DS). No correlations among Pro, SS and An accumulation with the quantum efficiency of PSII photochemistry (Φ(PSII)) and the excitation pressure (1-q(P)) were observed under DS. This implies that, while metabolites increased in a drought-dependent way, PSII activity did not decrease in the same pattern. Our results indicated that, under MoDS, A. thaliana leaves were able to maintain oxidative compounds such as malondialdeyde, an end product of lipid peroxidation, within the range of control leaves, and to cope with oxidative damage, as was evident by the decreased excitation pressure (1-q(P)) and similar (ns difference) Φ(PSII) to that of control leaves. In addition, a statistically significant increased accumulation of Pro, SS and An was recorded only under MoDS compared to controls. The better PSII functioning of MoDS Arabidopsis leaves may reflect the greater capacity of these leaves to undertake key metabolic adjustments, including increased Pro, SS and An accumulation, to maintain a higher antioxidant protection and a better balance between light capture and energy use.

Spatio-temporal heterogeneity in Arabidopsis thaliana leaves under drought stress

Using chlorophyll (chl) fluorescence imaging, we studied the effect of mild (MiDS), moderate (MoDS) and severe (SDS) drought stress on photosystem II (PSII) photochemistry of 4-week-old Arabidopsis thaliana. Spatio-temporal heterogeneity in all chl fluorescence parameters was maintained throughout water stress. After exposure to drought stress, maximum quantum yield of PSII photochemistry (F(v)/F(m)) and quantum efficiency of PSII photochemistry (Φ(PSΙΙ)) decreased less in the proximal (base) than in the distal (tip) leaf. The chl fluorescence parameter F(v) /F(m) decreased less after MoDS than MiDS. Under MoDS, the antioxidant mechanism of A. thaliana leaves seemed to be sufficient in scavenging reactive oxygen species, as evident by the decreased lipid peroxidation, the more excitation energy dissipated by non-photochemical quenching (NPQ) and decreased excitation pressure (1-q(p)). Arabidopsis leaves appear to function normally under MoDS, but do not seem to have particular metabolic tolerance mechanisms under MiDS and SDS, as revealed by the level of lipid peroxidation and decreased quantum yield for dissipation after down-regulation in PSII (Φ(NPQ)), indicating that energy dissipation by down-regulation did not function and electron transport (ETR) was depressed. The simultaneous increased quantum yield of non-regulated energy dissipation (Φ(NO)) indicated that both the photochemical energy conversion and protective regulatory mechanism were insufficient. The non-uniform photosynthetic pattern under drought stress may reflect different zones of leaf anatomy and mesophyll development. The data demonstrate that the effect of different degrees of drought stress on A. thaliana leaves show spatio-temporal heterogeneity, implying that common single time point or single point leaf analyses are inadequate.

Phenomics--technologies to relieve the phenotyping bottleneck

Global agriculture is facing major challenges to ensure global food security, such as the need to breed high-yielding crops adapted to future climates and the identification of dedicated feedstock crops for biofuel production (biofuel feedstocks). Plant phenomics offers a suite of new technologies to accelerate progress in understanding gene function and environmental responses. This will enable breeders to develop new agricultural germplasm to support future agricultural production. In this review we present plant physiology in an 'omics' perspective, review some of the new high-throughput and high-resolution phenotyping tools and discuss their application to plant biology, functional genomics and crop breeding.

Tracking viral movement in plants by means of chlorophyll fluorescence imaging

Many techniques have been applied to understand viral cell-to-cell movement in host plants, but little progress has been made in understanding viral vascular transport mechanisms. We propose the use of chlorophyll fluorescence imaging techniques, not only to diagnose the viral infection, but also to follow the movement of the virus through the vascular system and its subsequent spread into the leaves. In Nicotiana benthamiana plants, imaging of chlorophyll fluorescence parameters such as Ф(PSII) and NPQ proved useful to follow infections with Pepper mild mottle virus. The results demonstrate a correlation between changes in the chlorophyll fluorescence parameters and the viral distribution analyzed by tissue printing.

New phenotyping methods for screening wheat and barley for beneficial responses to water deficit

This review considers stomatal conductance as an indicator of genotypic differences in the growth response to water stress. The benefits of using stomatal conductance are compared with photosynthetic rate and other indicators of genetic variation in water stress tolerance, along with the use of modern phenomics technologies. Various treatments for screening for genetic diversity in response to water deficit in controlled environments are considered. There is no perfect medium: there are pitfalls in using soil in pots, and in using hydroponics with ionic and non-ionic osmotica. Use of mixed salts or NaCl is recommended over non-ionic osmotica. Developments in infrared thermography provide new and feasible screening methods for detecting genetic variation in the stomatal response to water deficit in controlled environments and in the field.

High-throughput shoot imaging to study drought responses

Drought is a complex stress which elicits a wide variety of plant responses. As such, genetic studies of drought are particularly difficult. Elucidation of the genetic basis of components contributing to drought tolerance is likely to be more tractable than that of overall drought tolerance. Certain of the traits which contribute to drought tolerance in plants and the high-throughput phenotyping techniques available to measure those traits are described in this paper. On the basis of the dynamic nature of drought, plant development, and the resulting stress response, the focus is on non-destructive imaging techniques which allow a temporal resolution and monitoring of the same plants throughout the experiment. Information on the physiological changes in response to drought over time is vital in order to identify and characterize different drought-tolerance mechanisms. High-throughput imaging provides a valuable new tool which allows the dissection of plant responses to drought into a series of component traits.