Establishment of integrated protocols for automated high throughput kinetic chlorophyll fluorescence analyses

Implementation of theoretical non-photochemical quenching (NPQ(T)) to investigate NPQ of chickpea under drought stress with High-throughput Phenotyping

Non-photochemical quenching (NPQ) is a protective mechanism for dissipating excess energy generated during photosynthesis in the form of heat. The accelerated relaxation of the NPQ in fluctuating light can lead to an increase in the yield and dry matter productivity of crops. Since the measurement of NPQ is time-consuming and requires specific light conditions, theoretical NPQ (NPQ(T)) was introduced for rapid estimation, which could be suitable for High-throughput Phenotyping. We investigated the potential of NPQ(T) to be used for testing plant genetic resources of chickpea under drought stress with non-invasive High-throughput Phenotyping complemented with yield traits. Besides a high correlation between the hundred-seed-weight and the Estimated Biovolume, significant differences were observed between the two types of chickpea desi and kabuli for Estimated Biovolume and NPQ(T). Desi was able to maintain the Estimated Biovolume significantly better under drought stress. One reason could be the effective dissipation of excess excitation energy in photosystem II, which can be efficiently measured as NPQ(T). Screening of plant genetic resources for photosynthetic performance could take pre-breeding to a higher level and can be implemented in a variety of studies, such as here with drought stress or under fluctuating light in a High-throughput Phenotyping manner using NPQ(T).

Water for agriculture: more crop per drop

Global crop production in agriculture depends on water availability. Future scenarios predict increasing occurrence of flash floods and rapidly developing droughts accompanied by heatwaves in humid regions that rely on rain-fed agriculture. It is challenging to maintain high crop yields, even in arid and drought-prone regions that depend on irrigation. The average water demand of crops varies significantly, depending on plant species, development stage, and climate. Most crops, such as maize and wheat, require relatively more water during the vegetative phase compared to the ripening phase. In this review, we explain WUE and options to improve water use and thus crop yield. Nutrient management might represent another possibility to manipulate water uptake and use by plants. An emerging topic involves agroforest co-cultivation, where trees in the system facilitate water transfer through hydraulic lift, benefiting neighbouring crops. Other options to enhance crop yield per water use are discussed.

Current status of community resources and priorities for weed genomics research

Weeds are attractive models for basic and applied research due to their impacts on agricultural systems and capacity to swiftly adapt in response to anthropogenic selection pressures. Currently, a lack of genomic information precludes research to elucidate the genetic basis of rapid adaptation for important traits like herbicide resistance and stress tolerance and the effect of evolutionary mechanisms on wild populations. The International Weed Genomics Consortium is a collaborative group of scientists focused on developing genomic resources to impact research into sustainable, effective weed control methods and to provide insights about stress tolerance and adaptation to assist crop breeding.

Strong prevalence of light regime-specific QTL in Arabidopsis detected using automated high-throughput phenotyping in fluctuating or constant light

Plants have evolved and adapted under dynamic environmental conditions, particularly to fluctuating light, but plant research has often focused on constant growth conditions. To quantitatively asses the adaptation to fluctuating light, a panel of 384 natural Arabidopsis thaliana accessions was analyzed in two parallel independent experiments under fluctuating and constant light conditions in an automated high-throughput phenotyping system upgraded with supplemental LEDs. While the integrated daily photosynthetically active radiation was the same under both light regimes, plants in fluctuating light conditions accumulated significantly less biomass and had lower leaf area during their measured vegetative growth than plants in constant light. A total of 282 image-derived architectural and/or color-related traits at six common time points, and 77 photosynthesis-related traits from one common time point were used to assess their associations with genome-wide natural variation for both light regimes. Out of the 3000 significant marker-trait associations (MTAs) detected, only 183 (6.1%) were common for fluctuating and constant light conditions. The prevalence of light regime-specific QTL indicates a complex adaptation. Genes in linkage disequilibrium with fluctuating light-specific MTAs with an adjusted repeatability value >0.5 were filtered for gene ontology terms containing "photo" or "light", yielding 15 selected candidates. The candidate genes are involved in photoprotection, PSII maintenance and repair, maintenance of linear electron flow, photorespiration, phytochrome signaling, and cell wall expansion, providing a promising starting point for further investigations into the response of Arabidopsis thaliana to fluctuating light conditions.

Cryopreservation of Duckweed Genetic Diversity as Model for Long-Term Preservation of Aquatic Flowering Plants

Vegetatively propagating aquatic angiosperms, the Lemnaceae family (duckweeds) represents valuable genetic resources for circular bioeconomics and other sustainable applications. Due to extremely fast growth and laborious cultivation of in vitro collections, duckweeds are an urgent subject for cryopreservation. We developed a robust and fast DMSO-free protocol for duckweed cryopreservation by vitrification. A single-use device was designed for sampling of duckweed fronds from donor culture, further spin-drying, and subsequent transferring to cryo-tubes with plant vitrification solution 3 (PVS3). Following cultivation in darkness and applying elevated temperatures during early regrowth stage, a specific pulsed illumination instead of a diurnal regime enabled successful regrowth after the cryopreservation of 21 accessions of Spirodela, Landoltia, Lemna, and Wolffia genera, including interspecific hybrids, auto- and allopolyploids. Genome size measurements revealed no quantitative genomic changes potentially caused by cryopreservation. The expression of CBF/DREB1 genes, considered as key factors in the development of freezing tolerance, was studied prior to cooling but was not linked with duckweed regrowth after rewarming. Despite preserving chlorophyll fluorescence after rewarming, the rewarmed fronds demonstrated nearly zero photosynthetic activity, which did not recover. The novel protocol provides the basis for future routine application of cryostorage to duckweed germplasm collections, saving labor for in vitro cultivation and maintaining characterized reference and mutant samples.

Dynamic growth QTL action in diverse light environments: characterization of light regime-specific and stable QTL in Arabidopsis

Plant growth is a complex process affected by a multitude of genetic and environmental factors and their interactions. To identify genetic factors influencing plant performance under different environmental conditions, vegetative growth was assessed in Arabidopsis thaliana cultivated under constant or fluctuating light intensities, using high-throughput phenotyping and genome-wide association studies. Daily automated non-invasive phenotyping of a collection of 382 Arabidopsis accessions provided growth data during developmental progression under different light regimes at high temporal resolution. Quantitative trait loci (QTL) for projected leaf area, relative growth rate, and PSII operating efficiency detected under the two light regimes were predominantly condition-specific and displayed distinct temporal activity patterns, with active phases ranging from 2 d to 9 d. Eighteen protein-coding genes and one miRNA gene were identified as potential candidate genes at 10 QTL regions consistently found under both light regimes. Expression patterns of three candidate genes affecting projected leaf area were analysed in time-series experiments in accessions with contrasting vegetative leaf growth. These observations highlight the importance of considering both environmental and temporal patterns of QTL/allele actions and emphasize the need for detailed time-resolved analyses under diverse well-defined environmental conditions to effectively unravel the complex and stage-specific contributions of genes affecting plant growth processes.

Engaging Precision Phenotyping to Scrutinize Vegetative Drought Tolerance and Recovery in Chickpea Plant Genetic Resources

Precise and high-throughput phenotyping (HTP) of vegetative drought tolerance in chickpea plant genetic resources (PGR) would enable improved screening for genotypes with low relative loss of biomass formation and reliable physiological performance. It could also provide a basis to further decipher the quantitative trait drought tolerance and recovery and gain a better understanding of the underlying mechanisms. In the context of climate change and novel nutritional trends, legumes and chickpea in particular are becoming increasingly important because of their high protein content and adaptation to low-input conditions. The PGR of legumes represent a valuable source of genetic diversity that can be used for breeding. However, the limited use of germplasm is partly due to a lack of available characterization data. The development of HTP systems offers a perspective for the analysis of dynamic plant traits such as abiotic stress tolerance and can support the identification of suitable genetic resources with a potential breeding value. Sixty chickpea accessions were evaluated on an HTP system under contrasting water regimes to precisely evaluate growth, physiological traits, and recovery under optimal conditions in comparison to drought stress at the vegetative stage. In addition to traits such as Estimated Biovolume (EB), Plant Height (PH), and several color-related traits over more than forty days, photosynthesis was examined by chlorophyll fluorescence measurements on relevant days prior to, during, and after drought stress. With high data quality, a wide phenotypic diversity for adaptation, tolerance, and recovery to drought was recorded in the chickpea PGR panel. In addition to a loss of EB between 72% and 82% after 21 days of drought, photosynthetic capacity decreased by 16-28%. Color-related traits can be used as indicators of different drought stress stages, as they show the progression of stress.

Image-based time series analysis to establish differential disease progression for two Fusarium head blight pathogens in oat spikelets with variable resistance

Oat-based value-added products have increased their value as healthy foodstuff. Fusarium head blight (FHB) infections and the mycotoxins accumulated to the oat seeds, however, pose a challenge to oat production. The FHB infections are predicted to become more prevalent in the future changing climates and under more limited use of fungicides. Both these factors increase the pressure for breeding new resistant cultivars. Until now, however, genetic links in oats against FHB infection have been difficult to identify. Therefore, there is a great need for more effective breeding efforts, including improved phenotyping methods allowing time series analysis and the identification of molecular markers during disease progression. To these ends, dissected spikelets of several oat genotypes with different resistance profiles were studied by image-based methods during disease progression by Fusarium culmorum or F. langsethiae species. The chlorophyll fluorescence of each pixel in the spikelets was recorded after inoculation by the two Fusarium spp., and the progression of the infections was analyzed by calculating the mean maximum quantum yield of PSII (Fv/Fm) values for each spikelet. The recorded values were (i) the change in the photosynthetically active area of the spikelet as percentage of its initial size, and (ii) the mean of Fv/Fm values of all fluorescent pixels per spikelet post inoculation, both indicative of the progression of the FHB disease. The disease progression was successfully monitored, and different stages of the infection could be defined along the time series. The data also confirmed the differential rate of disease progression by the two FHB causal agents. In addition, oat varieties with variable responses to the infections were indicated.

Effects of Poty-Potexvirus Synergism on Growth, Photosynthesis and Metabolite Status of Nicotiana benthamiana

Mixed virus infections threaten crop production because interactions between the host and the pathogen mix may lead to viral synergism. While individual infections by potato virus A (PVA), a potyvirus, and potato virus X (PVX), a potexvirus, can be mild, co-infection leads to synergistic enhancement of PVX and severe symptoms. We combined image-based phenotyping with metabolite analysis of single and mixed PVA and PVX infections and compared their effects on growth, photosynthesis, and metabolites in Nicotiana benthamiana. Viral synergism was evident in symptom severity and impaired growth in the plants. Indicative of stress, the co-infection increased leaf temperature and decreased photosynthetic parameters. In contrast, singly infected plants sustained photosynthetic activity. The host's metabolic response differed significantly between single and mixed infections. Over 200 metabolites were differentially regulated in the mixed infection: especially defense-related metabolites and aromatic and branched-chain amino acids increased compared to the control. Changes in the levels of methionine cycle intermediates and a low S-adenosylmethionine/S-adenosylhomocysteine ratio suggested a decline in the methylation potential in co-infected plants. The decreased ratio between reduced glutathione, an important scavenger of reactive oxygen species, and its oxidized form, indicated that severe oxidative stress developed during co-infection. Based on the results, infection-associated oxidative stress is successfully controlled in the single infections but not in the synergistic infection, where activated defense pathways are not sufficient to counter the impact of the infections on plant growth.

High-throughput screening paradigms in ecotoxicity testing: Emerging prospects and ongoing challenges

The rapidly increasing number of new production chemicals coupled with stringent implementation of global chemical management programs necessities a paradigm shift towards boarder uses of low-cost and high-throughput ecotoxicity testing strategies as well as deeper understanding of cellular and sub-cellular mechanisms of ecotoxicity that can be used in effective risk assessment. The latter will require automated acquisition of biological data, new capabilities for big data analysis as well as computational simulations capable of translating new data into in vivo relevance. However, very few efforts have been so far devoted into the development of automated bioanalytical systems in ecotoxicology. This is in stark contrast to standardized and high-throughput chemical screening and prioritization routines found in modern drug discovery pipelines. As a result, the high-throughput and high-content data acquisition in ecotoxicology is still in its infancy with limited examples focused on cell-free and cell-based assays. In this work we outline recent developments and emerging prospects of high-throughput bioanalytical approaches in ecotoxicology that reach beyond in vitro biotests. We discuss future importance of automated quantitative data acquisition for cell-free, cell-based as well as developments in phytotoxicity and in vivo biotests utilizing small aquatic model organisms. We also discuss recent innovations such as organs-on-a-chip technologies and existing challenges for emerging high-throughput ecotoxicity testing strategies. Lastly, we provide seminal examples of the small number of successful high-throughput implementations that have been employed in prioritization of chemicals and accelerated environmental risk assessment.

Precision phenotyping across the life cycle to validate and decipher drought-adaptive QTLs of wild emmer wheat (Triticum turgidum ssp. dicoccoides) introduced into elite wheat varieties

Drought events or the combination of drought and heat conditions are expected to become more frequent due to global warming, and wheat yields may fall below their long-term average. One way to increase climate-resilience of modern high-yielding varieties is by their genetic improvement with beneficial alleles from crop wild relatives. In the present study, the effect of two beneficial QTLs introgressed from wild emmer wheat and incorporated in the three wheat varieties BarNir, Zahir and Uzan was studied under well-watered conditions and under drought stress using non-destructive High-throughput Phenotyping (HTP) throughout the life cycle in a single pot-experiment. Plants were daily imaged with RGB top and side view cameras and watered automatically. Further, at two time points, the quantum yield of photosystem II was measured with a top view FluorCam. The QTL carrying near isogenic lines (NILs) were compared with their corresponding parents by t-test for all non-invasively obtained traits and for the manually determined agronomic and yield parameters. Data quality of phenotypic traits (repeatability) in the controlled HTP experiment was above 85% throughout the life cycle and at maturity. Drought stress had a strong effect on growth in all wheat genotypes causing biomass reduction from 2% up to 70% at early and late points in the drought period, respectively. At maturity, the drought caused 47-55% decreases in yield-related traits grain weight, straw weight and total biomass and reduced TKW by 10%, while water use efficiency (WUE) increased under drought by 29%. The yield-enhancing effect of the introgressed QTLs under drought conditions that were previously demonstrated under field/screenhouse conditions in Israel, could be mostly confirmed in a greenhouse pot experiment using HTP. Daily precision phenotyping enabled to decipher the mode of action of the QTLs in the different genetic backgrounds throughout the entire wheat life cycle. Daily phenotyping allowed a precise determination of the timing and size of the QTLs effect (s) and further yielded information about which image-derived traits are informative at which developmental stage of wheat during the entire life cycle. Maximum height and estimated biovolume were reached about a week after heading, so experiments that only aim at exploring these traits would not need a longer observation period. To obtain information on different onset and progress of senescence, the CVa curves represented best the ongoing senescence of plants. The QTL on 7A in the BarNir background was found to improve yield under drought by increased biomass growth, a higher photosynthetic performance, a higher WUE and a "stay green effect."

Integration of high-throughput phenotyping with anatomical traits of leaves to help understanding lettuce acclimation to a changing environment

MAIN CONCLUSION

The combination of image-based phenotyping with in-depth anatomical analysis allows for a thorough investigation of plant physiological plasticity in acclimation, which is driven by environmental conditions and mediated by anatomical traits. Understanding the ability of plants to respond to fluctuations in environmental conditions is critical to addressing climate change and unlocking the agricultural potential of crops both indoor and in the field. Recent studies have revealed that the degree of eco-physiological acclimation depends on leaf anatomical traits, which show stress-induced alterations during organogenesis. Indeed, it is still a matter of debate whether plant anatomy is the bottleneck for optimal plant physiology or vice versa. Here, we cultivated 'Salanova' lettuces in a phenotyping chamber under two different vapor pressure deficits (VPDs; low, high) and watering levels (well-watered, low-watered); then, plants underwent short-term changes in VPD. We aimed to combine high-throughput phenotyping with leaf anatomical analysis to evaluate their capability in detecting the early stress signals in lettuces and to highlight the different degrees of plants' eco-physiological acclimation to the change in VPD, as influenced by anatomical traits. The results demonstrate that well-watered plants under low VPD developed a morpho-anatomical structure in terms of mesophyll organization, stomatal and vein density, which more efficiently guided the acclimation to sudden changes in environmental conditions and which was not detected by image-based phenotyping alone. Therefore, we emphasized the need to complement high-throughput phenotyping with anatomical trait analysis to unveil crop acclimation mechanisms and predict possible physiological behaviors after sudden environmental fluctuations due to climate changes.

Opportunities and limits of controlled-environment plant phenotyping for climate response traits

Rising temperatures and changing precipitation patterns will affect agricultural production substantially, exposing crops to extended and more intense periods of stress. Therefore, breeding of varieties adapted to the constantly changing conditions is pivotal to enable a quantitatively and qualitatively adequate crop production despite the negative effects of climate change. As it is not yet possible to select for adaptation to future climate scenarios in the field, simulations of future conditions in controlled-environment (CE) phenotyping facilities contribute to the understanding of the plant response to special stress conditions and help breeders to select ideal genotypes which cope with future conditions. CE phenotyping facilities enable the collection of traits that are not easy to measure under field conditions and the assessment of a plant's phenotype under repeatable, clearly defined environmental conditions using automated, non-invasive, high-throughput methods. However, extrapolation and translation of results obtained under controlled environments to field environments is ambiguous. This review outlines the opportunities and challenges of phenotyping approaches under controlled environments complementary to conventional field trials. It gives an overview on general principles and introduces existing phenotyping facilities that take up the challenge of obtaining reliable and robust phenotypic data on climate response traits to support breeding of climate-adapted crops.

Harnessing Chlorophyll Fluorescence for Phenotyping Analysis of Wild and Cultivated Tomato for High Photochemical Efficiency under Water Deficit for Climate Change Resilience

Fluctuations of the weather conditions, due to global climate change, greatly influence plant growth and development, eventually affecting crop yield and quality, but also plant survival. Since water shortage is one of the key risks for the future of agriculture, exploring the capability of crop species to grow with limited water is therefore fundamental. By using chlorophyll fluorescence analysis, we evaluated the responses of wild tomato accession Solanum pennellii LA0716, Solanum lycopersicum cv. Μ82, the introgression line IL12-4 (from cv. M82 Χ LA0716), and the Greek tomato cultivars cv. Santorini and cv. Zakinthos, to moderate drought stress (MoDS) and severe drought stress (SDS), in order to identify the minimum irrigation level for efficient photosynthetic performance. Agronomic traits (plant height, number of leaves and root/shoot biomass), relative water content (RWC), and lipid peroxidation, were also measured. Under almost 50% deficit irrigation, S. pennellii exhibited an enhanced photosynthetic function by displaying a hormetic response of electron transport rate (ETR), due to an increased fraction of open reaction centers, it is suggested to be activated by the low increase of reactive oxygen species (ROS). A low increase of ROS is regarded to be beneficial by stimulating defense responses and also triggering a more oxidized redox state of quinone A (QA), corresponding in S. pennellii under 50% deficit irrigation, to the lowest stomatal opening, resulting in reduction of water loss. Solanumpennellii was the most tolerant to drought, as it was expected, and could manage to have an adequate photochemical function with almost 30% water regime of well-watered plants. With 50% deficit irrigation, cv. Μ82 and cv. Santorini did not show any difference in photochemical efficiency to control plants and are recommended to be cultivated under deficit irrigation as an effective strategy to enhance agricultural sustainability under a global climate change. We conclude that instead of the previously used Fv/Fm ratio, the redox state of QA, as it can be estimated by the chlorophyll fluorescence parameter 1 - qL, is a better indicator to evaluate photosynthetic efficiency and select drought tolerant cultivars under deficit irrigation.

High-throughput field phenotyping reveals genetic variation in photosynthetic traits in durum wheat under drought

Chlorophyll fluorescence (ChlF) is a powerful non-invasive technique for probing photosynthesis. Although proposed as a method for drought tolerance screening, ChlF has not yet been fully adopted in physiological breeding, mainly due to limitations in high-throughput field phenotyping capabilities. The light-induced fluorescence transient (LIFT) sensor has recently been shown to reliably provide active ChlF data for rapid and remote characterisation of plant photosynthetic performance. We used the LIFT sensor to quantify photosynthesis traits across time in a large panel of durum wheat genotypes subjected to a progressive drought in replicated field trials over two growing seasons. The photosynthetic performance was measured at the canopy level by means of the operating efficiency of Photosystem II ( Fq'/Fm' ) and the kinetics of electron transport measured by reoxidation rates ( Fr1' and Fr2' ). Short- and long-term changes in ChlF traits were found in response to soil water availability and due to interactions with weather fluctuations. In mild drought, Fq'/Fm' and Fr2' were little affected, while Fr1' was consistently accelerated in water-limited compared to well-watered plants, increasingly so with rising vapour pressure deficit. This high-throughput approach allowed assessment of the native genetic diversity in ChlF traits while considering the diurnal dynamics of photosynthesis.

High-Resolution Analysis of Growth and Transpiration of Quinoa Under Saline Conditions

The Plantarray 3.0 phenotyping platform^® was used to monitor the growth and water use of the quinoa varieties Pasto and selRiobamba under salinity (0-300 mM NaCl). Salinity reduced the cumulative transpiration of both varieties by 60% at 200 mM NaCl and by 75 and 82% at 300 mM NaCl for selRiobamba and Pasto, respectively. Stomatal conductance was reduced by salinity, but at 200 mM NaCl Pasto showed a lower reduction (15%) than selRiobamba (35%), along with decreased specific leaf area. Diurnal changes in water use parameters indicate that under salt stress, daily transpiration in quinoa is less responsive to changes in light irradiance, and stomatal conductance is modulated to maximize CO₂ uptake and minimize water loss following the changes in VPD (vapor pressure deficit). These changes might contribute to the enhanced water use efficiency of both varieties under salt stress. The mechanistic crop model LINTUL was used to integrate physiological responses into the radiation use efficiency of the plants (RUE), which was more reduced in Pasto than selRiobamba under salinity. By the end of the experiment (eleven weeks after sowing, six weeks after stress), the growth of Pasto was significantly lower than selRiobamba, fresh biomass was 50 and 35% reduced at 200 mM and 70 and 50% reduced at 300 mM NaCl for Pasto and selRiobamba, respectively. We argue that contrasting water management strategies can at least partly explain the differences in salt tolerance between Pasto and selRiobamba. Pasto adopted a "conservative-growth" strategy, saving water at the expense of growth, while selRiobamba used an "acquisitive-growth" strategy, maximizing growth in spite of the stress. The implementation of high-resolution phenotyping could help to dissect these complex growth traits that might be novel breeding targets for abiotic stress tolerance.

High-Throughput Phenotyping Methods for Breeding Drought-Tolerant Crops

Drought is a main factor limiting crop yields. Modern agricultural technologies such as irrigation systems, ground mulching, and rainwater storage can prevent drought, but these are only temporary solutions. Understanding the physiological, biochemical, and molecular reactions of plants to drought stress is therefore urgent. The recent rapid development of genomics tools has led to an increasing interest in phenomics, i.e., the study of phenotypic plant traits. Among phenomic strategies, high-throughput phenotyping (HTP) is attracting increasing attention as a way to address the bottlenecks of genomic and phenomic studies. HTP provides researchers a non-destructive and non-invasive method yet accurate in analyzing large-scale phenotypic data. This review describes plant responses to drought stress and introduces HTP methods that can detect changes in plant phenotypes in response to drought.

Seed Priming With Protein Hydrolysates Improves Arabidopsis Growth and Stress Tolerance to Abiotic Stresses

The use of plant biostimulants contributes to more sustainable and environmentally friendly farming techniques and offers a sustainable alternative to mitigate the adverse effects of stress. Protein hydrolysate-based biostimulants have been described to promote plant growth and reduce the negative effect of abiotic stresses in different crops. However, limited information is available about their mechanism of action, how plants perceive their application, and which metabolic pathways are activating. Here we used a multi-trait high-throughput screening approach based on simple RGB imaging and combined with untargeted metabolomics to screen and unravel the mode of action/mechanism of protein hydrolysates in Arabidopsis plants grown in optimal and in salt-stress conditions (0, 75, or 150 mM NaCl). Eleven protein hydrolysates from different protein sources were used as priming agents in Arabidopsis seeds in three different concentrations (0.001, 0.01, or 0.1 μl ml-1). Growth and development-related traits as early seedling establishment, growth response under stress and photosynthetic performance of the plants were dynamically scored throughout and at the end of the growth period. To effectively classify the functional properties of the 11 products a Plant Biostimulant Characterization (PBC) index was used, which helped to characterize the activity of a protein hydrolysate based on its ability to promote plant growth and mitigate stress, and to categorize the products as plant growth promoters, growth inhibitors and/or stress alleviator. Out of 11 products, two were identified as highly effective growth regulators and stress alleviators because they showed a PBC index always above 0.51. Using the untargeted metabolomics approach, we showed that plants primed with these best performing biostimulants had reduced contents of stress-related molecules (such as flavonoids and terpenoids, and some degradation/conjugation compounds of phytohormones such as cytokinins, auxins, gibberellins, etc.), which alleviated the salt stress response-related growth inhibition.

The Arabidopsis AAC Proteins CIL and CIA2 Are Sub-functionalized Paralogs Involved in Chloroplast Development

The Arabidopsis gene Chloroplast Import Apparatus 2 (CIA2) encodes a transcription factor that positively affects the activity of nuclear genes for chloroplast ribosomal proteins and chloroplast protein import machineries. CIA2-like (CIL) is the paralogous gene of CIA2. We generated a cil mutant by site-directed mutagenesis and compared it with cia2 and cia2cil double mutant. Phenotype of the cil mutant did not differ from the wild type under our growth conditions, except faster growth and earlier time to flowering. Compared to cia2, the cia2cil mutant showed more impaired chloroplast functions and reduced amounts of plastid ribosomal RNAs. In silico analyses predict for CIA2 and CIL a C-terminal CCT domain and an N-terminal chloroplast transit peptide (cTP). Chloroplast (and potentially nuclear) localization was previously shown for HvCMF3 and HvCMF7, the homologs of CIA2 and CIL in barley. We observed nuclear localization of CIL after transient expression in Arabidopsis protoplasts. Surprisingly, transformation of cia2 with HvCMF3, HvCMF7, or with a truncated CIA2 lacking the predicted cTP could partially rescue the pale-green phenotype of cia2. These data are discussed with respect to potentially overlapping functions between CIA2, CIL, and their barley homologs and to the function of the putative cTPs of CIA2 and CIL.

Dynamics of Maize Vegetative Growth and Drought Adaptability Using Image-Based Phenotyping Under Controlled Conditions

Changes in climate are likely to have a negative impact on water availability and soil fertility in many maize-growing agricultural areas. The development of high-throughput phenotyping platforms provides a new prospect for dissecting the dynamic complex plant traits such as abiotic stress tolerance into simple components. The growth phenotypes of 20 maize (Zea mays L.) inbred lines were monitored in a non-invasive way under control, nitrogen, and water limitation as well as under combined nitrogen and water stress using an automated phenotyping system in greenhouse conditions. Thirteen biomass-related and morphophysiological traits were extracted from RGB images acquired at 33 time points covering developmental stages from leaf count 5 at the first imaging date to leaf count 10-13 at the final harvest. For these traits, genetic differences were identified and dynamic developmental trends during different maize growth stages were analyzed. The difference between control and water stress was detectable 3-10 days after the beginning of stress depending on the genotype, while the effect of limited nitrogen supply only induced subtle phenotypic effects. Phenotypic traits showed different response dynamics as well as multiple and changing interaction patterns with stress progression. The estimated biovolume, leaf area index, and color ratios were found to be stress-responsive at different stages of drought stress progression and thereby represent valuable reference indicators in the selection of drought-adaptive genotypes. Furthermore, genotypes could be grouped according to two typical growth dynamic patterns in water stress treatments by c-means clustering analysis. Inbred lines with high drought adaptability across time and development were identified and could serve as a basis for designing novel genotypes with desired, stage-specific growth phenotypes under water stress through pyramiding. Drought recovery potential may play an equal role as drought tolerance in plant drought adaptation.

Image-Based Methods to Score Fungal Pathogen Symptom Progression and Severity in Excised Arabidopsis Leaves

Image-based symptom scoring of plant diseases is a powerful tool for associating disease resistance with plant genotypes. Advancements in technology have enabled new imaging and image processing strategies for statistical analysis of time-course experiments. There are several tools available for analyzing symptoms on leaves and fruits of crop plants, but only a few are available for the model plant Arabidopsis thaliana (Arabidopsis). Arabidopsis and the model fungus Botrytis cinerea (Botrytis) comprise a potent model pathosystem for the identification of signaling pathways conferring immunity against this broad host-range necrotrophic fungus. Here, we present two strategies to assess severity and symptom progression of Botrytis infection over time in Arabidopsis leaves. Thus, a pixel classification strategy using color hue values from red-green-blue (RGB) images and a random forest algorithm was used to establish necrotic, chlorotic, and healthy leaf areas. Secondly, using chlorophyll fluorescence (ChlFl) imaging, the maximum quantum yield of photosystem II (F_v/F_m) was determined to define diseased areas and their proportion per total leaf area. Both RGB and ChlFl imaging strategies were employed to track disease progression over time. This has provided a robust and sensitive method for detecting sensitive or resistant genetic backgrounds. A full methodological workflow, from plant culture to data analysis, is described.

Transcriptional and Physiological Analyses to Assess the Effects of a Novel Biostimulant in Tomato

This work aimed to study the effects in tomato (Solanum lycopersicum L.) of foliar applications of a novel calcium-based biostimulant (SOB01) using an omics approach involving transcriptomics and physiological profiling. A calcium-chloride fertilizer (SOB02) was used as a product reference standard. Plants were grown under well-watered (WW) and water stress (WS) conditions in a growth chamber. We firstly compared the transcriptome profile of treated and untreated tomato plants using the software RStudio. Totally, 968 and 1,657 differentially expressed genes (DEGs) (adj-p-value < 0.1 and |log2(fold change)| ≥ 1) were identified after SOB01 and SOB02 leaf treatments, respectively. Expression patterns of 9 DEGs involved in nutrient metabolism and osmotic stress tolerance were validated by real-time quantitative reverse transcription PCR (RT-qPCR) analysis. Principal component analysis (PCA) on RT-qPCR results highlighted that the gene expression profiles after SOB01 treatment in different water regimes were clustering together, suggesting that the expression pattern of the analyzed genes in well water and water stress plants was similar in the presence of SOB01 treatment. Physiological analyses demonstrated that the biostimulant application increased the photosynthetic rate and the chlorophyll content under water deficiency compared to the standard fertilizer and led to a higher yield in terms of fruit dry matter and a reduction in the number of cracked fruits. In conclusion, transcriptome and physiological profiling provided comprehensive information on the biostimulant effects highlighting that SOB01 applications improved the ability of the tomato plants to mitigate the negative effects of water stress.

Mutation of the ALBOSTRIANS Ohnologous Gene HvCMF3 Impairs Chloroplast Development and Thylakoid Architecture in Barley

Gene pairs resulting from whole genome duplication (WGD), so-called ohnologous genes, are retained if at least one member of the pair undergoes neo- or sub-functionalization. Phylogenetic analyses of the ohnologous genes ALBOSTRIANS (HvAST/HvCMF7) and ALBOSTRIANS-LIKE (HvASL/HvCMF3) of barley (Hordeum vulgare) revealed them as members of a subfamily of genes coding for CCT motif (CONSTANS, CONSTANS-LIKE and TIMING OF CAB1) proteins characterized by a single CCT domain and a putative N-terminal chloroplast transit peptide. Recently, we showed that HvCMF7 is needed for chloroplast ribosome biogenesis. Here we demonstrate that mutations in HvCMF3 lead to seedlings delayed in development. They exhibit a yellowish/light green - xantha - phenotype and successively develop pale green leaves. Compared to wild type, plastids of mutant seedlings show a decreased PSII efficiency, impaired processing and reduced amounts of ribosomal RNAs; they contain less thylakoids and grana with a higher number of more loosely stacked thylakoid membranes. Site-directed mutagenesis of HvCMF3 identified a previously unknown functional domain, which is highly conserved within this subfamily of CCT domain containing proteins. HvCMF3:GFP fusion constructs were localized to plastids and nucleus. Hvcmf3Hvcmf7 double mutants exhibited a xantha-albino or albino phenotype depending on the strength of molecular lesion of the HvCMF7 allele. The chloroplast ribosome deficiency is discussed as the primary observed defect of the Hvcmf3 mutants. Based on our observations, the genes HvCMF3 and HvCMF7 have similar but not identical functions in chloroplast development of barley supporting our hypothesis of neo-/sub-functionalization between both ohnologous genes.

Autophagy Plays Prominent Roles in Amino Acid, Nucleotide, and Carbohydrate Metabolism during Fixed-Carbon Starvation in Maize

Autophagic recycling of proteins, lipids, nucleic acids, carbohydrates, and organelles is essential for cellular homeostasis and optimal health, especially under nutrient-limiting conditions. To better understand how this turnover affects plant growth, development, and survival upon nutrient stress, we applied an integrated multiomics approach to study maize (Zea mays) autophagy mutants subjected to fixed-carbon starvation induced by darkness. Broad metabolic alterations were evident in leaves missing the core autophagy component ATG12 under normal growth conditions (e.g., lipids and secondary metabolism), while changes in amino acid-, carbohydrate-, and nucleotide-related metabolites selectively emerged during fixed-carbon starvation. Through combined proteomic and transcriptomic analyses, we identified numerous autophagy-responsive proteins, which revealed processes underpinning the various metabolic changes seen during carbon stress as well as potential autophagic cargo. Strikingly, a strong upregulation of various catabolic processes was observed in the absence of autophagy, including increases in simple carbohydrate levels with a commensurate drop in starch levels, elevated free amino acid levels with a corresponding reduction in intact protein levels, and a strong increase in the abundance of several nitrogen-rich nucleotide catabolites. Altogether, this analysis showed that fixed-carbon starvation in the absence of autophagy adjusts the choice of respiratory substrates, promotes the transition of peroxisomes to glyoxysomes, and enhances the retention of assimilated nitrogen.

Crop Photosynthetic Performance Monitoring Based on a Combined System of Measured and Modelled Chloroplast Electron Transport Rate in Greenhouse Tomato

Combining information of plant physiological processes with climate control systems can improve control accuracy in controlled environments as greenhouses and plant factories. Through that, resource optimization can be achieved. To predict the plant physiological processes and implement them in control actions of interest, a reliable monitoring system and a capable control system are needed. In this paper, we focused on the option to use real-time crop monitoring for precision climate control in greenhouses. For that, we studied the processes and external factors influencing leaf net CO₂ assimilation rate (A_L , µmol CO₂ m^-2 s^-1) as possible variables of a plant performance indicator. While measured greenhouse environmental variables such as light, temperature, or humidity showed a direct relation between A_L and light-quantum yield of photosystem II (Φ₂), we defined three objectives: (1) to explore the relationship between climate variables and A_L , as well as Φ₂; (2) create a simple and reliable method for real-time prediction of A_L with continuously Φ₂ measurements; and (3) calibrate parameters to predict chloroplast electron transport rate as input in A_L modelling. Due to practical obstacles in measuring CO₂ gas-exchange in commercial production, we explored a method to predict A_L by measuring Φ₂ of leaves in a commercial hydroponic greenhouse tomato crop ("Pureza"). We calculated A_L with two different approaches based on either the negative exponential response model with simplified biochemical equations (marked as Model I) or the non-rectangular hyperbola full biochemical photosynthetic models (marked as Model II). Using Model I can only be used to predict A_L with large uncertainty (R² 0.64; RMSE 2.21), while using Φ₂ as input to Model II could be used to improve the prediction accuracy of A_L (R² 0.71; RMSE 1.98). Our results suggests that (1) Φ₂ light signals can be used to predict net photosynthesis rate with high accuracy; (2) a parameterized photosynthetic electron transport rate model is suitable predicting measured electron transport rate (J) and A_L . The system can be used as decision support system (DSS) for plant and crop performance monitoring when leaf-dynamics are up-scaled to the plant or crop level.

NH4+ Toxicity, Which Is Mainly Determined by the High NH4+/K+ Ratio, Is Alleviated by CIPK23 in Arabidopsis

Ammonium (NH₄⁺) toxicity is always accompanied by ion imbalances, and NH₄⁺ and potassium (K⁺) exhibit a competitive correlation in their uptake and transport processes. In Arabidopsis thaliana, the typical leaf chlorosis phenotype in the knockout mutant of calcineurin B-like interacting protein kinase 23 (CIPK23) is high-NH₄⁺-dependent under low-K⁺ condition. However, the correlation of K⁺ and NH₄⁺ in the occurrence of leaf chlorosis in the cipk23 mutant has not been deeply elucidated. Here, a modified hydroponic experimental system with different gradients of NH₄⁺ and K⁺ was applied. Comparative treatments showed that NH₄⁺ toxicity, which is triggered mainly by the high ratio of NH₄⁺ to K⁺ (NH₄⁺/K⁺ ≥ 10:1 for cipk23) but not by the absolute concentrations of the ions, results in leaf chlorosis. Under high NH₄⁺/K⁺ ratios, CIPK23 is upregulated abundantly in leaves and roots, which efficiently reduces the leaf chlorosis by regulating the contents of NH₄⁺ and K⁺ in plant shoots, while promoting the elongation of primary and lateral roots. Physiological data were obtained to further confirm the role CIPK23 in alleviating NH₄⁺ toxicity. Taken all together, CIPK23 might function in different tissues to reduce stress-induced NH₄⁺ toxicity associated with high NH₄⁺/K⁺ ratios by regulating the NH₄⁺-K⁺ balance in Arabidopsis.

Strong temporal dynamics of QTL action on plant growth progression revealed through high-throughput phenotyping in canola

A major challenge of plant biology is to unravel the genetic basis of complex traits. We took advantage of recent technical advances in high-throughput phenotyping in conjunction with genome-wide association studies to elucidate genotype-phenotype relationships at high temporal resolution. A diverse Brassica napus population from a commercial breeding programme was analysed by automated non-invasive phenotyping. Time-resolved data for early growth-related traits, including estimated biovolume, projected leaf area, early plant height and colour uniformity, were established and complemented by fresh and dry weight biomass. Genome-wide SNP array data provided the framework for genome-wide association analyses. Using time point data and relative growth rates, multiple robust main effect marker-trait associations for biomass and related traits were detected. Candidate genes involved in meristem development, cell wall modification and transcriptional regulation were detected. Our results demonstrate that early plant growth is a highly complex trait governed by several medium and many small effect loci, most of which act only during short phases. These observations highlight the importance of taking the temporal patterns of QTL/allele actions into account and emphasize the need for detailed time-resolved analyses to effectively unravel the complex and stage-specific contributions of genes affecting growth processes that operate at different developmental phases.

Combining next-generation sequencing and progeny testing for rapid identification of induced recessive and dominant mutations in maize M2 individuals

Molecular identification of mutant alleles responsible for certain phenotypic alterations is a central goal of genetic analyses. In this study we describe a rapid procedure suitable for the identification of induced recessive and dominant mutations applied to two Zea mays mutants expressing a dwarf and a pale green phenotype, respectively, which were obtained through pollen ethyl methanesulfonate (EMS) mutagenesis. First, without prior backcrossing, induced mutations (single nucleotide polymorphisms, SNPs) segregating in a (M₂ ) family derived from a heterozygous (M₁ ) parent were identified using whole-genome shotgun (WGS) sequencing of a small number of (M₂ ) individuals with mutant and wild-type phenotypes. Second, the state of zygosity of the mutation causing the phenotype was determined for each sequenced individual by phenotypic segregation analysis of the self-pollinated (M₃ ) offspring. Finally, we filtered for segregating EMS-induced SNPs whose state of zygosity matched the determined state of zygosity of the mutant locus in each sequenced (M₂ ) individuals. Through this procedure, combining sequencing of individuals and Mendelian inheritance, three and four SNPs in linkage passed our zygosity filter for the homozygous dwarf and heterozygous pale green mutation, respectively. The dwarf mutation was found to be allelic to the an1 locus and caused by an insertion in the largest exon of the AN1 gene. The pale green mutation affected the nuclear W2 gene and was caused by a non-synonymous amino acid exchange in encoded chloroplast DNA polymerase with a predicted deleterious effect. This coincided with lower cpDNA levels in pale green plants.

Phenotyping viral infection in sweetpotato using a high-throughput chlorophyll fluorescence and thermal imaging platform

BACKGROUND

Virus diseases caused by co-infection with Sweet potato feathery mottle virus (SPFMV) and Sweetpotato chlorotic stunt virus (SPCSV) are a severe problem in the production of sweetpotato (Ipomoea batatas L.). Traditional molecular virus detection methods include nucleic acid-based and serological tests. In this study, we aimed to validate the use of a non-destructive imaging-based plant phenotype platform to study plant-virus synergism in sweetpotato by comparing four virus treatments with two healthy controls.

RESULTS

By monitoring physiological and morphological effects of viral infection in sweetpotato over 29 days, we quantified photosynthetic performance from chlorophyll fluorescence (ChlF) imaging and leaf thermography from thermal infrared (TIR) imaging among sweetpotatoes. Moreover, the differences among different treatments observed from ChlF and TIR imaging were related to virus accumulation and distribution in sweetpotato. These findings were further validated at the molecular level by related gene expression in both photosynthesis and carbon fixation pathways.

CONCLUSION

Our study validated for the first time the use of ChlF- and TIR-based imaging systems to distinguish the severity of virus diseases related to SPFMV and SPCSV in sweetpotato. In addition, we demonstrated that the operating efficiency of PSII and photochemical quenching were the most sensitive parameters for the quantification of virus effects compared with maximum quantum efficiency, non-photochemical quenching, and leaf temperature.

Phenotyping Plant Responses to Biotic Stress by Chlorophyll Fluorescence Imaging

Photosynthesis is a pivotal process in plant physiology, and its regulation plays an important role in plant defense against biotic stress. Interactions with pathogens and pests often cause alterations in the metabolism of sugars and sink/source relationships. These changes can be part of the plant defense mechanisms to limit nutrient availability to the pathogens. In other cases, these alterations can be the result of pests manipulating the plant metabolism for their own benefit. The effects of biotic stress on plant physiology are typically heterogeneous, both spatially and temporarily. Chlorophyll fluorescence imaging is a powerful tool to mine the activity of photosynthesis at cellular, leaf, and whole-plant scale, allowing the phenotyping of plants. This review will recapitulate the responses of the photosynthetic machinery to biotic stress factors, from pathogens (viruses, bacteria, and fungi) to pests (herbivory) analyzed by chlorophyll fluorescence imaging both at the lab and field scale. Moreover, chlorophyll fluorescence imagers and alternative techniques to indirectly evaluate photosynthetic traits used at field scale are also revised.

Converging phenomics and genomics to study natural variation in plant photosynthetic efficiency

In recent years developments in plant phenomic approaches and facilities have gradually caught up with genomic approaches. An opportunity lies ahead to dissect complex, quantitative traits when both genotype and phenotype can be assessed at a high level of detail. This is especially true for the study of natural variation in photosynthetic efficiency, for which forward genetics studies have yielded only a little progress in our understanding of the genetic layout of the trait. High-throughput phenotyping, primarily from chlorophyll fluorescence imaging, should help to dissect the genetics of photosynthesis at the different levels of both plant physiology and development. Specific emphasis should be directed towards understanding the acclimation of the photosynthetic machinery in fluctuating environments, which may be crucial for the identification of genetic variation for relevant traits in food crops. Facilities should preferably be designed to accommodate phenotyping of photosynthesis-related traits in such environments. The use of forward genetics to study the genetic architecture of photosynthesis is likely to lead to the discovery of novel traits and/or genes that may be targeted in breeding or bio-engineering approaches to improve crop photosynthetic efficiency. In the near future, big data approaches will play a pivotal role in data processing and streamlining the phenotype-to-gene identification pipeline.

Salt stress under the scalpel - dissecting the genetics of salt tolerance

Salt stress limits the productivity of crops grown under saline conditions, leading to substantial losses of yield in saline soils and under brackish and saline irrigation. Salt tolerant crops could alleviate these losses while both increasing irrigation opportunities and reducing agricultural demands on dwindling freshwater resources. However, despite significant efforts, progress towards this goal has been limited, largely because of the genetic complexity of salt tolerance for agronomically important yield-related traits. Consequently, the focus is shifting to the study of traits that contribute to overall tolerance, thus breaking down salt tolerance into components that are more genetically tractable. Greater consideration of the plasticity of salt tolerance mechanisms throughout development and across environmental conditions furthers this dissection. The demand for more sophisticated and comprehensive methodologies is being met by parallel advances in high-throughput phenotyping and sequencing technologies that are enabling the multivariate characterisation of vast germplasm resources. Alongside steady improvements in statistical genetics models, forward genetics approaches for elucidating salt tolerance mechanisms are gaining momentum. Subsequent quantitative trait locus and gene validation has also become more accessible, most recently through advanced techniques in molecular biology and genomic analysis, facilitating the translation of findings to the field. Besides fuelling the improvement of established crop species, this progress also facilitates the domestication of naturally salt tolerant orphan crops. Taken together, these advances herald a promising era of discovery for research into the genetics of salt tolerance in plants.

Understanding the Biostimulant Action of Vegetal-Derived Protein Hydrolysates by High-Throughput Plant Phenotyping and Metabolomics: A Case Study on Tomato

Designing and developing new biostimulants is a crucial process which requires an accurate testing of the product effects on the morpho-physiological traits of plants and a deep understanding of the mechanism of action of selected products. Product screening approaches using omics technologies have been found to be more efficient and cost effective in finding new biostimulant substances. A screening protocol based on the use of high-throughput phenotyping platform for screening new vegetal-derived protein hydrolysates (PHs) for biostimulant activity followed by a metabolomic analysis to elucidate the mechanism of the most active PHs has been applied on tomato crop. Eight PHs (A-G, I) derived from enzymatic hydrolysis of seed proteins of Leguminosae and Brassicaceae species were foliarly sprayed twice during the trial. A non-ionic surfactant Triton X-100 at 0.1% was also added to the solutions before spraying. A control treatment foliarly sprayed with distilled water containing 0.1% Triton X-100 was also included. Untreated and PH-treated tomato plants were monitored regularly using high-throughput non-invasive imaging technologies. The phenotyping approach we used is based on automated integrative analysis of photosynthetic performance, growth analysis, and color index analysis. The digital biomass of the plants sprayed with PH was generally increased. In particular, the relative growth rate and the growth performance were significantly improved by PHs A and I, respectively, compared to the untreated control plants. Kinetic chlorophyll fluorescence imaging did not allow to differentiate the photosynthetic performance of treated and untreated plants. Finally, MS-based untargeted metabolomics analysis was performed in order to characterize the functional mechanisms of selected PHs. The treatment modulated the multi-layer regulation process that involved the ethylene precursor and polyamines and affected the ROS-mediated signaling pathways. Although further investigation is needed to strengthen our findings, metabolomic data suggest that treated plants experienced a metabolic reprogramming following the application of the tested biostimulants. Nonetheless, our experimental data highlight the potential for combined use of high-throughput phenotyping and metabolomics to facilitate the screening of new substances with biostimulant properties and to provide a morpho-physiological and metabolomic gateway to the mechanisms underlying PHs action on plants.

Systems models, phenomics and genomics: three pillars for developing high-yielding photosynthetically efficient crops

Recent years witnessed a stagnation in yield enhancement in major staple crops, which leads plant biologists and breeders to focus on an urgent challenge to dramatically increase crop yield to meet the growing food demand. Systems models have started to show their capacity in guiding crops improvement for greater biomass and grain yield production. Here we argue that systems models, phenomics and genomics combined are three pillars for the future breeding for high-yielding photosynthetically efficient crops (HYPEC). Briefly, systems models can be used to guide identification of breeding targets for a particular cultivar and define optimal physiological and architectural parameters for a particular crop to achieve high yield under defined environments. Phenomics can support collection of architectural, physiological, biochemical and molecular parameters in a high-throughput manner, which can be used to support both model validation and model parameterization. Genomic techniques can be used to accelerate crop breeding by enabling more efficient mapping between genotypic and phenotypic variation, and guide genome engineering or editing for model-designed traits. In this paper, we elaborate on these roles and how they can work synergistically to support future HYPEC breeding.

A Combined Phenotypic and Metabolomic Approach for Elucidating the Biostimulant Action of a Plant-Derived Protein Hydrolysate on Tomato Grown Under Limited Water Availability

Plant-derived protein hydrolysates (PHs) are an important category of biostimulants able to increase plant growth and crop yield especially under environmental stress conditions. PHs can be applied as foliar spray or soil drench. Foliar spray is generally applied to achieve a relatively short-term response, whereas soil drench is used when a long-term effect is desired. The aim of the study was to elucidate the biostimulant action of PH application method (foliar spray or substrate drench) on morpho-physiological traits and metabolic profile of tomato grown under limited water availability. An untreated control was also included. A high-throughput image-based phenotyping (HTP) approach was used to non-destructively monitor the crop response under limited water availability (40% of container capacity) in a controlled environment. Moreover, metabolic profile of leaves was determined at the end of the trial. Dry biomass of shoots at the end of the trial was significantly correlated with number of green pixels (R ² = 0.90) and projected shoot area, respectively. Both drench and foliar treatments had a positive impact on the digital biomass compared to control while the photosynthetic performance of the plants was slightly influenced by treatments. Overall drench application under limited water availability more positively influenced biomass accumulation and metabolic profile than foliar application. Significantly higher transpiration use efficiency was observed with PH-drench applications indicating better stomatal conductance. The mass-spectrometry based metabolomic analysis allowed the identification of distinct biochemical signatures in PH-treated plants. Metabolomic changes involved a wide and organized range of biochemical processes that included, among others, phytohormones (notably a decrease in cytokinins and an accumulation of salicylates) and lipids (including membrane lipids, sterols, and terpenes). From a general perspective, treated tomato plants exhibited an improved tolerance to reactive oxygen species (ROS)-mediated oxidative imbalance. Such capability to cope with oxidative stress might have resulted from a coordinated action of signaling compounds (salicylic acid and hydroxycinnamic amides), radical scavengers such as carotenoids and prenyl quinones, as well as a reduced biosynthesis of tetrapyrrole coproporphyrins.

Transcriptome sequencing dissection of the mechanisms underlying differential cold sensitivity in young and mature leaves of the tea plant (Camellia sinensis)

The tea plant originated in tropical and subtropical regions and experiences considerable challenges during cold winters and late spring frosts. After short-term chilling stress, young leaves of tea plants exhibit browning, a significant increase in electrolyte leakage and a marked decrease in the maximal photochemical efficiency of photosystem II (F_v/F_m) compared with mature leaves. To identify the mechanisms underlying the different chilling tolerance between young and mature leaves of the tea plant, we used Illumina RNA-Seq technology to analyse the transcript expression profiles of young and mature leaves exposed to temperatures of 20 °C, 4 °C, and 0 °C for 4 h. A total of 45.70-72.93 million RNA-Seq raw reads were obtained and then de novo assembled into 228,864 unigenes with an average length of 601 bp and an N50 of 867 bp. In addition, the differentially expressed unigenes were identified via Venn diagram analyses for paired comparisons of young and mature leaves. Functional classifications based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed that the up-regulated differentially expressed genes were predominantly related to the cellular component terms of chloroplasts and cell membranes, the biological process term of oxidation-reduction process as well as the pathway terms of glutathione metabolism and photosynthesis, suggesting that these components and pathways may contribute to the cold hardiness of mature leaves. Conversely, the inhibited expression of genes related to cell membranes, carotenoid metabolism, photosynthesis, and ROS detoxification in young leaves under cold conditions might lead to the disintegration of cell membranes and oxidative damage to the photosynthetic apparatus. Further quantitative real-time PCR testing validated the reliability of our RNA-Seq results. This work provides valuable information for understanding the mechanisms underlying the cold susceptibility of young tea plant leaves and for breeding tea cultivars with superior frost resistance via the genetic manipulation of antioxidant enzymes.