In Vivo Phenotyping for the Early Detection of Drought Stress in Tomato

Kiwi 4.0: In Vivo Real-Time Monitoring to Improve Water Use Efficiency in Yellow Flesh Actinidia chinensis

This manuscript reports the application of sensors for water use efficiency with a focus on the application of an in vivo OECT biosensor. In two distinct experimental trials, the in vivo sensor bioristor was applied in yellow kiwi plants to monitor, in real-time and continuously, the changes in the composition and concentration of the plant sap in an open field during plant growth and development. The bioristor response and physiological data, together with other fruit sensor monitoring data, were acquired and combined in both trials, giving a complete picture of the biosphere conditions. A high correlation was observed between the bioristor index (ΔIgs), the canopy cover expressed as the fraction of intercepted PAR (fi_PAR), and the soil water content (SWC). In addition, the bioristor was confirmed to be a good proxy for the occurrence of drought in kiwi plants; in fact, a period of drought stress was identified within the month of July. A novelty of the bioristor measurements was their ability to detect in advance the occurrence of defoliation, thereby reducing yield and quality losses. A plant-based irrigation protocol can be achieved and tailored based on real plant needs, increasing water use sustainability and preserving high-quality standards.

Plant responses to climate change, how global warming may impact on food security: a critical review

Global agricultural production must double by 2050 to meet the demands of an increasing world human population but this challenge is further exacerbated by climate change. Environmental stress, heat, and drought are key drivers in food security and strongly impacts on crop productivity. Moreover, global warming is threatening the survival of many species including those which we rely on for food production, forcing migration of cultivation areas with further impoverishing of the environment and of the genetic variability of crop species with fall out effects on food security. This review considers the relationship of climatic changes and their bearing on sustainability of natural and agricultural ecosystems, as well as the role of omics-technologies, genomics, proteomics, metabolomics, phenomics and ionomics. The use of resource saving technologies such as precision agriculture and new fertilization technologies are discussed with a focus on their use in breeding plants with higher tolerance and adaptability and as mitigation tools for global warming and climate changes. Nevertheless, plants are exposed to multiple stresses. This study lays the basis for the proposition of a novel research paradigm which is referred to a holistic approach and that went beyond the exclusive concept of crop yield, but that included sustainability, socio-economic impacts of production, commercialization, and agroecosystem management.

A Novel Correction Methodology to Improve the Performance of a Low-Cost Hyperspectral Portable Snapshot Camera

The development of spectral sensors (SSs) capable of retrieving spectral information have opened new opportunities to improve several environmental and agricultural practices, e.g., crop breeding, plant phenotyping, land use monitoring, and crop classification. The SSs are classified as multispectral and hyperspectral (HS) based on the number of the spectral bands resolved and sampled during data acquisition. Large-scale applications of the HS remain limited due to the cost of this type of technology and the technical difficulties in hyperspectral data processing. Low-cost portable hyperspectral cameras (PHCs) have been progressively developed; however, critical aspects associated with data acquisition and processing, such as the presence of spectral discontinuities, signal jumps, and a high level of background noise, were reported. The aim of this work was to analyze and improve the hyperspectral output of a PHC Senop HSC-2 device by developing a general use methodology. Several signal gaps were identified as falls and jumps across the spectral signatures near 513, 650, and 930 nm, while the dark current signal magnitude and variability associated with instrumental noise showed an increasing trend over time. A data correction pipeline was successfully developed and tested, leading to 99% and 74% reductions in radiance signal jumps identified at 650 and 830 nm, respectively, while the impact of noise on the acquired signal was assessed to be in the range of 10% to 15%. The developed methodology can be effectively applied to other low-cost hyperspectral cameras.

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

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

Integrated phenotyping of root and shoot growth dynamics in maize reveals specific interaction patterns in inbreds and hybrids and in response to drought

In recent years, various automated methods for plant phenotyping addressing roots or shoots have been developed and corresponding platforms have been established to meet the diverse requirements of plant research and breeding. However, most platforms are only either able to phenotype shoots or roots of plants but not both simultaneously. This substantially limits the opportunities offered by a joint assessment of the growth and development dynamics of both organ systems, which are highly interdependent. In order to overcome these limitations, a root phenotyping installation was integrated into an existing automated non-invasive high-throughput shoot phenotyping platform. Thus, the amended platform is now capable of conducting high-throughput phenotyping at the whole-plant level, and it was used to assess the vegetative root and shoot growth dynamics of five maize inbred lines and four hybrids thereof, as well as the responses of five inbred lines to progressive drought stress. The results showed that hybrid vigour (heterosis) occurred simultaneously in roots and shoots and was detectable as early as 4 days after transplanting (4 DAT; i.e., 8 days after seed imbibition) for estimated plant height (EPH), total root length (TRL), and total root volume (TRV). On the other hand, growth dynamics responses to progressive drought were different in roots and shoots. While TRV was significantly reduced 10 days after the onset of the water deficit treatment, the estimated shoot biovolume was significantly reduced about 6 days later, and EPH showed a significant decrease even 2 days later (8 days later than TRV) compared with the control treatment. In contrast to TRV, TRL initially increased in the water deficit period and decreased much later (not earlier than 16 days after the start of the water deficit treatment) compared with the well-watered plants. This may indicate an initial response of the plants to water deficit by forming longer but thinner roots before growth was inhibited by the overall water deficit. The magnitude and the dynamics of the responses were genotype-dependent, as well as under the influence of the water consumption, which was related to plant size.

Pitfalls and potential of high-throughput plant phenotyping platforms

Automated high-throughput plant phenotyping (HTPP) enables non-invasive, fast and standardized evaluations of a large number of plants for size, development, and certain physiological variables. Many research groups recognize the potential of HTPP and have made significant investments in HTPP infrastructure, or are considering doing so. To make optimal use of limited resources, it is important to plan and use these facilities prudently and to interpret the results carefully. Here we present a number of points that users should consider before purchasing, building or utilizing such equipment. They relate to (1) the financial and time investment for acquisition, operation, and maintenance, (2) the constraints associated with such machines in terms of flexibility and growth conditions, (3) the pros and cons of frequent non-destructive measurements, (4) the level of information provided by proxy traits, and (5) the utilization of calibration curves. Using data from an Arabidopsis experiment, we demonstrate how diurnal changes in leaf angle can impact plant size estimates from top-view cameras, causing deviations of more than 20% over the day. Growth analysis data from another rosette species showed that there was a curvilinear relationship between total and projected leaf area. Neglecting this curvilinearity resulted in linear calibration curves that, although having a high r2 (> 0.92), also exhibited large relative errors. Another important consideration we discussed is the frequency at which calibration curves need to be generated and whether different treatments, seasons, or genotypes require distinct calibration curves. In conclusion, HTPP systems have become a valuable addition to the toolbox of plant biologists, provided that these systems are tailored to the research questions of interest, and users are aware of both the possible pitfalls and potential involved.

A Lycopene ε-Cyclase TILLING Allele Enhances Lycopene and Carotenoid Content in Fruit and Improves Drought Stress Tolerance in Tomato Plants

In the scenario of climate change, the availability of genetic resources for tomato cultivation that combine improved nutritional properties and more tolerance to water deficiency is highly desirable. Within this context, the molecular screenings of the Red Setter cultivar-based TILLING platform led to the isolation of a novel lycopene ε-cyclase gene (SlLCY-E) variant (G/3378/T) that produces modifications in the carotenoid content of tomato leaves and fruits. In leaf tissue, the novel G/3378/T SlLCY-E allele enhances β,β-xanthophyll content at the expense of lutein, which decreases, while in ripe tomato fruit the TILLING mutation induces a significant increase in lycopene and total carotenoid content. Under drought stress conditions, the G/3378/T SlLCY-E plants produce more abscisic acid (ABA) and still conserve their leaf carotenoid profile (reduction of lutein and increase in β,β-xanthophyll content). Furthermore, under said conditions, the mutant plants grow much better and are more tolerant to drought stress, as revealed by digital-based image analysis and in vivo monitoring of the OECT (Organic Electrochemical Transistor) sensor. Altogether, our data indicate that the novel TILLING SlLCY-E allelic variant is a valuable genetic resource that can be used for developing new tomato varieties, improved in drought stress tolerance and enriched in fruit lycopene and carotenoid content.

Tomato Biodiversity and Drought Tolerance: A Multilevel Review

Ongoing global climate change suggests that crops will be exposed to environmental stresses that may affect their productivity, leading to possible global food shortages. Among these stresses, drought is the most important contributor to yield loss in global agriculture. Drought stress negatively affects various physiological, genetic, biochemical, and morphological characteristics of plants. Drought also causes pollen sterility and affects flower development, resulting in reduced seed production and fruit quality. Tomato (Solanum lycopersicum L.) is one of the most economically important crops in different parts of the world, including the Mediterranean region, and it is known that drought limits crop productivity, with economic consequences. Many different tomato cultivars are currently cultivated, and they differ in terms of genetic, biochemical, and physiological traits; as such, they represent a reservoir of potential candidates for coping with drought stress. This review aims to summarize the contribution of specific physio-molecular traits to drought tolerance and how they vary among tomato cultivars. At the genetic and proteomic level, genes encoding osmotins, dehydrins, aquaporins, and MAP kinases seem to improve the drought tolerance of tomato varieties. Genes encoding ROS-scavenging enzymes and chaperone proteins are also critical. In addition, proteins involved in sucrose and CO₂ metabolism may increase tolerance. At the physiological level, plants improve drought tolerance by adjusting photosynthesis, modulating ABA, and pigment levels, and altering sugar metabolism. As a result, we underline that drought tolerance depends on the interaction of several mechanisms operating at different levels. Therefore, the selection of drought-tolerant cultivars must consider all these characteristics. In addition, we underline that cultivars may exhibit distinct, albeit overlapping, multilevel responses that allow differentiation of individual cultivars. Consequently, this review highlights the importance of tomato biodiversity for an efficient response to drought and for preserving fruit quality levels.

Low-Cost Hyperspectral Imaging to Detect Drought Stress in High-Throughput Phenotyping

Recent developments in low-cost imaging hyperspectral cameras have opened up new possibilities for high-throughput phenotyping (HTP), allowing for high-resolution spectral data to be obtained in the visible and near-infrared spectral range. This study presents, for the first time, the integration of a low-cost hyperspectral camera Senop HSC-2 into an HTP platform to evaluate the drought stress resistance and physiological response of four tomato genotypes (770P, 990P, Red Setter and Torremaggiore) during two cycles of well-watered and deficit irrigation. Over 120 gigabytes of hyperspectral data were collected, and an innovative segmentation method able to reduce the hyperspectral dataset by 85.5% was developed and applied. A hyperspectral index (H-index) based on the red-edge slope was selected, and its ability to discriminate stress conditions was compared with three optical indices (OIs) obtained by the HTP platform. The analysis of variance (ANOVA) applied to the OIs and H-index revealed the better capacity of the H-index to describe the dynamic of drought stress trend compared to OIs, especially in the first stress and recovery phases. Selected OIs were instead capable of describing structural changes during plant growth. Finally, the OIs and H-index results have revealed a higher susceptibility to drought stress in 770P and 990P than Red Setter and Torremaggiore genotypes.

Predicting and Comparing Students’ Online and Offline Academic Performance Using Machine Learning Algorithms

Due to COVID-19, the researching of educational data and the improvement of related systems have become increasingly important in recent years. Educational institutions seek more information about their students to find ways to utilize their talents and address their weaknesses. With the emergence of e-learning, researchers and programmers aim to find ways to maintain students’ attention and improve their chances of achieving a higher grade point average (GPA) to gain admission to their desired colleges. In this paper, we predict, test, and provide reasons for declining student performance using various machine learning algorithms, including support vector machine with different kernels, decision tree, random forest, and k-nearest neighbors algorithms. Additionally, we compare two databases, one with data related to online learning and another with data on relevant offline learning properties, to compare predicted weaknesses with metrics such as F1 score and accuracy. However, before applying the algorithms, the databases need normalization to meet the prediction format. Ultimately, we find that success in school is related to habits such as sleep, study time, and screen time. More details regarding the results are provided in this paper.

Long-Term Stability in Electronic Properties of Textile Organic Electrochemical Transistors for Integrated Applications

Organic electrochemical transistors (OECTs) have demonstrated themselves to be an efficient interface between living environments and electronic devices in bioelectronic applications. The peculiar properties of conductive polymers allow new performances that overcome the limits of conventional inorganic biosensors, exploiting the high biocompatibility coupled to the ionic interaction. Moreover, the combination with biocompatible and flexible substrates, such as textile fibers, improves the interaction with living cells and allows specific new applications in the biological environment, including real-time analysis of plants' sap or human sweat monitoring. In these applications, a crucial issue is the lifetime of the sensor device. The durability, long-term stability, and sensitivity of OECTs were studied for two different textile functionalized fiber preparation processes: (i) adding ethylene glycol to the polymer solution, and (ii) using sulfuric acid as a post-treatment. Performance degradation was studied by analyzing the main electronic parameters of a significant number of sensors for a period of 30 days. RGB optical analysis were performed before and after the treatment of the devices. This study shows that device degradation occurs at voltages higher than 0.5 V. The sensors obtained with the sulfuric acid approach exhibit the most stable performances over time.

Current understanding, challenges and perspective on portable systems applied to plant monitoring and precision agriculture

The devastating effects of global climate change on crop production and exponential population growth pose a major challenge to agricultural yields. To cope with this problem, crop performance monitoring is becoming increasingly necessary. In this scenario, the use of sensors and biosensors capable of detecting changes in plant fitness and predicting the evolution of their morphology and physiology has proven to be a useful strategy to increase crop yields. Flexible sensors and nanomaterials have inspired the emerging fields of wearable and on-plant portable devices that provide continuous and accurate long-term sensing of morphological, physiological, biochemical, and environmental parameters. This review provides an overview of novel plant sensing technologies by discussing wearable and integrated devices proposed for engineering plant and monitoring its morphological traits and physiological processes, as well as plant-environment interactions. For each application scenario, the state-of-the-art sensing solutions are grouped according to the plant organ on which they have been installed highlighting their main technological advantages and features. Finally, future opportunities, challenges and perspectives are discussed. We anticipate that the application of this technology in agriculture will provide more accurate measurements for farmers and plant scientists with the ability to track crop performance in real time. All of this information will be essential to enable rapid optimization of plants development through tailored treatments that improve overall plant health even under stressful conditions, with the ultimate goal of increasing crop productivity in a more sustainable manner.

Simple Phenotypic Sensor for Visibly Tracking H2O2 Fluctuation to Detect Plant Health Status

Hydrogen peroxide (H₂O₂), as a main component of reactive oxygen species (ROS), serves as a key signaling molecule relevant to plant stress response and health status. Many strategies have been developed for detecting or quantifying H₂O₂ concentration. However, reports on simply, visibly tracking H₂O₂ fluctuation in vivo are limited. Here, for visibly tracking the plant H₂O₂ wave, a green fluorescent phenotypic probe was designed by merging a H₂O₂-sensitive tertiary amine moiety with the core fluorophore tetraphenylethene skeleton. The green fluorescence emission is quenched up to 52% by H₂O₂ with good sensitivity, selectivity, and reversibility within the plant physiological range of 10-100 μM H₂O₂. In response to various abiotic stresses, including mechanical damage, high salt, strong light and drought, fluorescence fluctuations, response to H₂O₂ concentration alterations in vivo was visible to the naked eye under irradiation of commercially available UV light (365 nm) after simple injection of this H₂O₂ probe solution into seedling leaves. This phenotypic fluorescent H₂O₂ probe illustrates great potential as early sensors of plant health under stress without the aid of skillful operation and specialized equipment.

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

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

Combining Precision Viticulture Technologies and Economic Indices to Sustainable Water Use Management

The scarcity of water due to climate change is endangering worldwide the production, quality, and economic viability of growing wine grapes. One of the main mitigation measures to be adopted in the viticulture sector will be an adequate irrigation strategy. Irrigation involves an increasing demand for water, a natural limited resource with increasing availability problems for the foreseeable future. Therefore, the development of a precision irrigation system, which is able to manage the efficient use of water and to monitor the crop water stress, is an important research topic for viticulture. This paper, through the analysis of a case study, aims to describe the prototype of a software platform that integrates data coming from different innovative remote and proximal sensors to monitor the hydric stress status of the vineyard. In addition, by using a cost analysis of grape cultivation and implementing economic indices, this study examines the conditions by which irrigation strategies may be economically justified, helping the decision-making process. By combining different sensors, the platform makes it possible to assess the spatial and temporal variability of water in vineyards. In addition, the output data of the platforming, matched with the economic indices, support the decision-making process for winemakers to optimize and schedule water use under water-scarce conditions.

Plant Bioelectronics and Biohybrids: The Growing Contribution of Organic Electronic and Carbon-Based Materials

Life in our planet is highly dependent on plants as they are the primary source of food, regulators of the atmosphere, and providers of a variety of materials. In this work, we review the progress on bioelectronic devices for plants and biohybrid systems based on plants, therefore discussing advancements that view plants either from a biological or a technological perspective, respectively. We give an overview on wearable and implantable bioelectronic devices for monitoring and modulating plant physiology that can be used as tools in basic plant science or find application in agriculture. Furthermore, we discuss plant-wearable devices for monitoring a plant's microenvironment that will enable optimization of growth conditions. The review then covers plant biohybrid systems where plants are an integral part of devices or are converted to devices upon functionalization with smart materials, including self-organized electronics, plant nanobionics, and energy applications. The review focuses on advancements based on organic electronic and carbon-based materials and discusses opportunities, challenges, as well as future steps.

Exploiting High-Throughput Indoor Phenotyping to Characterize the Founders of a Structured B. napus Breeding Population

Phenotyping is considered a significant bottleneck impeding fast and efficient crop improvement. Similar to many crops, Brassica napus, an internationally important oilseed crop, suffers from low genetic diversity, and will require exploitation of diverse genetic resources to develop locally adapted, high yielding and stress resistant cultivars. A pilot study was completed to assess the feasibility of using indoor high-throughput phenotyping (HTP), semi-automated image processing, and machine learning to capture the phenotypic diversity of agronomically important traits in a diverse B. napus breeding population, SKBnNAM, introduced here for the first time. The experiment comprised 50 spring-type B. napus lines, grown and phenotyped in six replicates under two treatment conditions (control and drought) over 38 days in a LemnaTec Scanalyzer 3D facility. Growth traits including plant height, width, projected leaf area, and estimated biovolume were extracted and derived through processing of RGB and NIR images. Anthesis was automatically and accurately scored (97% accuracy) and the number of flowers per plant and day was approximated alongside relevant canopy traits (width, angle). Further, supervised machine learning was used to predict the total number of raceme branches from flower attributes with 91% accuracy (linear regression and Huber regression algorithms) and to identify mild drought stress, a complex trait which typically has to be empirically scored (0.85 area under the receiver operating characteristic curve, random forest classifier algorithm). The study demonstrates the potential of HTP, image processing and computer vision for effective characterization of agronomic trait diversity in B. napus, although limitations of the platform did create significant variation that limited the utility of the data. However, the results underscore the value of machine learning for phenotyping studies, particularly for complex traits such as drought stress resistance.

Inter-tissue and inter-organ signaling in drought stress response and phenotyping of drought tolerance

Plant response to drought stress includes systems for intracellular regulation of gene expression and signaling, as well as inter-tissue and inter-organ signaling, which helps entire plants acquire stress resistance. Plants sense water-deficit conditions both via the stomata of leaves and roots, and transfer water-deficit signals from roots to shoots via inter-organ signaling. Abscisic acid is an important phytohormone involved in the drought stress response and adaptation, and is synthesized mainly in vascular tissues and guard cells of leaves. In leaves, stress-induced abscisic acid is distributed to various tissues by transporters, which activates stomatal closure and expression of stress-related genes to acquire drought stress resistance. Moreover, the stepwise stress response at the whole-plant level is important for proper understanding of the physiological response to drought conditions. Drought stress is sensed by multiple types of sensors as molecular patterns of abiotic stress signals, which are transmitted via separate parallel signaling networks to induce downstream responses, including stomatal closure and synthesis of stress-related proteins and metabolites. Peptide molecules play important roles in the inter-organ signaling of dehydration from roots to shoots, as well as signaling of osmotic changes and reactive oxygen species/Ca²⁺ . In this review, we have summarized recent advances in research on complex plant drought stress responses, focusing on inter-tissue signaling in leaves and inter-organ signaling from roots to shoots. We have discussed the mechanisms via which drought stress adaptations and resistance are acquired at the whole-plant level, and have proposed the importance of quantitative phenotyping for measuring plant growth under drought conditions.

Recent Advances in Plant Nanoscience

Plants have complex internal signaling pathways to quickly adjust to environmental changes and harvest energy from the environment. Facing the growing population, there is an urgent need for plant transformation and precise monitoring of plant growth to improve crop yields. Nanotechnology, an interdisciplinary research field, has recently been boosting plant yields and meeting global energy needs. In this context, a new field, "plant nanoscience," which describes the interaction between plants and nanotechnology, emerges as the times require. Nanosensors, nanofertilizers, nanopesticides, and nano-plant genetic engineering are of great help in increasing crop yields. Nanogenerators are helping to develop the potential of plants in the field of energy harvesting. Furthermore, the uptake and internalization of nanomaterials in plants and the possible effects are also worthy of attention. In this review, a forward-looking perspective on the plant nanoscience is presented and feasible solutions for future food shortages and energy crises are provided.

New approaches to improve crop tolerance to biotic and abiotic stresses

During the last years, a great effort has been dedicated at the development and employment of diverse approaches for achieving more stress-tolerant and climate-flexible crops and sustainable yield increases to meet the food and energy demands of the future. The ongoing climate change is in fact leading to more frequent extreme events with a negative impact on food production, such as increased temperatures, drought, and soil salinization as well as invasive arthropod pests and diseases. In this review, diverse "green strategies" (e.g., chemical priming, root-associated microorganisms), and advanced technologies (e.g., genome editing, high-throughput phenotyping) are described on the basis of the most recent research evidence. Particularly, attention has been focused on the potential use in a context of sustainable and climate-smart agriculture (the so called "next agriculture generation") to improve plant tolerance and resilience to abiotic and biotic stresses. In addition, the gap between the results obtained in controlled experiments and those from application of these technologies in real field conditions (lab to field step) is also discussed.

Organic Electrochemical Transistors for In Vivo Bioelectronics

Organic electrochemical transistors (OECTs) are presently a focus of intense research and hold great potential in expanding the horizons of the bioelectronics industry. The notable characteristics of OECTs, including their electrolyte-gating, which offers intimate interfacing with biological environments, and aqueous stability, make them particularly suitable to be operated within a living organism (in vivo). Unlike the existing in vivo bioelectronic devices, mostly based on rigid metal electrodes, OECTs form a soft mechanical contact with the biological milieu and ensure a high signal-to-noise ratio because of their powerful amplification capability. Such features make OECTs particularly desirable for a wide range of in vivo applications, including electrophysiological recordings, neuron stimulation, and neurotransmitter detection, and regulation of plant processes in vivo. In this review, a systematic compilation of the in vivo applications is presented that are addressed by the OECT technology. First, the operating mechanisms, and the device design and materials design principles of OECTs are examined, and then multiple examples are provided from the literature while identifying the unique device properties that enable the application progress. Finally, one critically looks at the future of the OECT technology for in vivo bioelectronic applications.

Real-time monitoring of Arundo donax response to saline stress through the application of in vivo sensing technology

One of the main impacts of climate change on agriculture production is the dramatic increase of saline (Na⁺) content in substrate, that will impair crop performance and productivity. Here we demonstrate how the application of smart technologies such as an in vivo sensor, termed bioristor, allows to continuously monitor in real-time the dynamic changes of ion concentration in the sap of Arundo donax L. (common name giant reed or giant cane), when exposed to a progressive salinity stress. Data collected in vivo by bioristor sensors inserted at two different heights into A. donax stems enabled us to detect the early phases of stress response upon increasing salinity. Indeed, the continuous time-series of data recorded by the bioristor returned a specific signal which correlated with Na⁺ content in leaves of Na-stressed plants, opening a new perspective for its application as a tool for in vivo plant phenotyping and selection of genotypes more suitable for the exploitation of saline soils.

High-throughput phenotyping to dissect genotypic differences in safflower for drought tolerance

Drought is one of the most severe and unpredictable abiotic stresses, occurring at any growth stage and affecting crop yields worldwide. Therefore, it is essential to develop drought tolerant varieties to ensure sustainable crop production in an ever-changing climate. High-throughput digital phenotyping technologies in tandem with robust screening methods enable precise and faster selection of genotypes for breeding. To investigate the use of digital imaging to reliably phenotype for drought tolerance, a genetically diverse safflower population was screened under different drought stresses at Agriculture Victoria’s high-throughput, automated phenotyping platform, Plant Phenomics Victoria, Horsham. In the first experiment, four treatments, control (90% field capacity; FC), 40% FC at initial branching, 40% FC at flowering and 50% FC at initial branching and flowering, were applied to assess the performance of four safflower genotypes. Based on these results, drought stress using 50% FC at initial branching and flowering stages was chosen to further screen 200 diverse safflower genotypes. Measured plant traits and dry biomass showed high correlations with derived digital traits including estimated shoot biomass, convex hull area, caliper length and minimum area rectangle, indicating the viability of using digital traits as proxy measures for plant growth. Estimated shoot biomass showed close association having moderately high correlation with drought indices yield index, stress tolerance index, geometric mean productivity, and mean productivity. Diverse genotypes were classified into four clusters of drought tolerance based on their performance (seed yield and digitally estimated shoot biomass) under stress. Overall, results show that rapid and precise image-based, high-throughput phenotyping in controlled environments can be used to effectively differentiate response to drought stress in a large numbers of safflower genotypes.

Towards In Vivo Monitoring of Ions Accumulation in Trees: Response of an in Planta Organic Electrochemical Transistor Based Sensor to Water Flux Density, Light and Vapor Pressure Deficit Variation

Research on organic electrochemical transistor (OECT) based sensors to monitor in vivo plant traits such as xylem sap concentration is attracting attention for their potential application in precision agriculture. Fabrication and electronic aspects of OECT have been the subject of extensive research while its characterization within the plant water relation context deserves further efforts. This study tested the hypothesis that the response (R) of an OECT (bioristor) implanted in the trunk of olive trees is inversely proportional to the water flux density flowing through the plant (Jw). This study also examined the influence on R of vapor pressure deficit (VPD) as coupled/uncoupled with light. R was hourly recorded in potted olive trees for a 10-day period concomitantly with Jw (weight loss method). A subgroup of trees was bagged in order to reduce VPD and in turn Jw, and other trees were located in a walk-in chamber where VPD and light were independently managed. R was tightly sensitive to diurnal oscillation of Jw and at negligible values of Jw (late afternoon and night) R increased. The bioristor was not sensitive to the VPD per se unless a light source was coupled to trigger Jw. This study preliminarily examined the suitability of bioristor to estimate the mean daily nutrients accumulation rate (Ca, K) in leaves comparing chemical and sensor-based procedures showing a good agreement between them opening new perspective towards the application of OECT sensor in precision agricultural cropping systems.

Cohabiting Plant-Wearable Sensor In Situ Monitors Water Transport in Plant

The boom of plant phenotype highlights the need to measure the physiological characteristics of an individual plant. However, continuous real-time monitoring of a plant's internal physiological status remains challenging using traditional silicon-based sensor technology, due to the fundamental mismatch between rigid sensors and soft and curved plant surfaces. Here, the first flexible electronic sensing device is reported that can harmlessly cohabitate with the plant and continuously monitor its stem sap flow, a critical plant physiological characteristic for analyzing plant health, water consumption, and nutrient distribution. Due to a special design and the materials chosen, the realized plant-wearable sensor is thin, soft, lightweight, air/water/light-permeable, and shows excellent biocompatibility, therefore enabling the sap flow detection in a continuous and non-destructive manner. The sensor can serve as a noninvasive, high-throughput, low-cost toolbox, and holds excellent potentials in phenotyping. Furthermore, the real-time investigation on stem flow insides watermelon reveals a previously unknown day/night shift pattern of water allocation between fruit and its adjacent branch, which has not been reported before.

A needle-type micro-sampling device for collecting nanoliter sap sample from plants

In plant research, measuring the physiological parameters of plants is vital for understanding the behavior and response of plants to changes in the external environment. Plant sap analysis provides an approach for elucidating the physiological condition of plants. However, to facilitate accurate sap analysis, a sampling device capable of collecting sap samples from plants is required. In this paper, a minimally invasive, needle-type micro-sampling device capable of collecting nanoliter (~ 91 nL) quantities of sap from plants is described. The developed micro-sampling system showed great reproducibility (3%) in experiments designed to assess sampling performance. As a proof of concept, sap samples were collected continuously from target plants with the micro-sampling system, and the dynamic changes in potassium ions, plant hormones and sugar levels inside plants were analyzed. The results demonstrated the feasibility of the micro-sampling device and its potential for developing a measurement system for plant research in the future.

Emerging Technologies for Monitoring Plant Health in Vivo

In the coming decades, increasing agricultural productivity is all-important. As the global population is growing rapidly and putting increased demand on food supply, poor soil quality, drought, flooding, increasing temperatures, and novel plant diseases are negatively impacting yields worldwide. One method to increase yields is plant health monitoring and rapid detection of disease, nutrient deficiencies, or drought. Monitoring plant health will allow for precise application of agrichemicals, fertilizers, and water in order to maximize yields. In vivo plant sensors are an emerging technology with the potential to increase agricultural productivity. In this mini-review, we discuss three major approaches of in vivo sensors for plant health monitoring, including genetic engineering, imaging and spectroscopy, and electrical.

Diurnal in vivo xylem sap glucose and sucrose monitoring using implantable organic electrochemical transistor sensors

Bioelectronic devices that convert biochemical signals to electronic readout enable biosensing with high spatiotemporal resolution. These technologies have been primarily applied in biomedicine while in plants sensing is mainly based on invasive methods that require tissue sampling, hindering in-vivo detection and having poor spatiotemporal resolution. Here, we developed enzymatic biosensors based on organic electrochemical transistors (OECTs) for in-vivo and real-time monitoring of sugar fluctuations in the vascular tissue of trees. The glucose and sucrose OECT-biosensors were implanted into the vascular tissue of trees and were operated through a low-cost portable unit for 48hr. Our work consists a proof-of-concept study where implantable OECT-biosensors not only allow real-time monitoring of metabolites in plants but also reveal new insights into diurnal sugar homeostasis. We anticipate that this work will contribute to establishing bioelectronic technologies as powerful minimally invasive tools in plant science, agriculture and forestry.