Monitoring drought responses of barley genotypes with semi-robotic phenotyping platform and association analysis between recorded traits and allelic variants of some stress genes

Genetic improvement of complex traits such as drought adaptation can be advanced by the combination of genomic and phenomic approaches. Semi-robotic phenotyping platform was used for computer-controlled watering, digital and thermal imaging of barley plants grown in greenhouse. The tested barley variants showed 0–76% reduction in green pixel-based shoot surface area in soil with 20% water content, compared to well-watered plants grown in soil with 60% water content. The barley HvA1 gene encoding the group 3 LEA (Late Embryogenesis Abundant) protein exhibited four (A–D) haplotypes as identified by the EcoTILLING and subsequent DNA sequencing. The green pixel mean value of genotypes with haplotype D was higher than the mean value of the remaining haplotypes, indicating a pivotal role of haplotype D in optimizing the green biomass production under drought condition. In water limitation, the canopy temperature of a highly sensitive genotype was 18.0°C, as opposed to 16.9°C of leaves from a tolerant genotype as measured by thermal imaging. Drought-induced changes in leaf temperature showed moderate correlation with the water use efficiency (r2 = 0.431). The haplotype/trait association analysis based on the t-test has revealed a positive effect of a haplotype B (SNPs:GCCCCTGC) in a gene encoding the barley fungal pathogen induced mRNA for pathogen-related protein (HvPPRPX), on harvest index, thousand grain weight, water use efficiency and grain yield. The presented pilot study established a basic methodology for the integrated use of phenotyping and haplotyping data in characterization of genotype-dependent drought responses in barley

Potential phenotyping methodologies to assess inter- and intravarietal variability and to select grapevine genotypes tolerant to abiotic stress

ReviewPlant phenotyping is an emerging science that combines multiple methodologies and protocols to measure plant traits (e.g., growth, morphology, architecture, function, and composition) at multiple scales of organization. Manual phenotyping remains as a major bottleneck to the advance of plant and crop breeding. Such constraint fostered the development of high throughput plant phenotyping (HTPP), which is largely based on imaging approaches and automatized data retrieval and processing. Field phenotyping still poses major challenges and the progress of HTPP for field conditions can be relevant to support selection and breeding of grapevine. The aim of this review is to discuss potential and current methods to improve field phenotyping of grapevine to support characterization of inter- and intravarietal diversity. Vitis vinifera has a large genetic diversity that needs characterization, and the availability of methods to support selection of plant material (polyclonal or clonal) able to withstand abiotic stress is paramount. Besides being time consuming, complex and expensive, field experiments are also affected by heterogeneous and uncontrolled climate and soil conditions, mostly due to the large areas of the trials and to the high number of traits to be observed in a number of individuals ranging from hundreds to thousands. Therefore, adequate field experimental design and data gathering methodologies are crucial to obtain reliable data. Some of the major challenges posed to grapevine selection programs for tolerance to water and heat stress are described herein. Useful traits for selection and related field phenotyping methodologies are described and their adequacy for large scale screening is discussedinfo:eu-repo/semantics/publishedVersio

Estimating Crop Stomatal Conductance Through High-Throughput Plant Phenotyping

During photosynthesis and transpiration, crops exchange carbon dioxide and water with the atmosphere through stomata. When a crop experiences water stress, stomata are closed to reducing water loss. However, the closing of stomata also negatively affects the photosynthetic efficiency of the crop and leads to lower yields. Stomatal conductance (gs) quantifies the degree of stomatal opening and closing by using the rate of gas exchange between the crop and the atmosphere, which helps to understand the water status of the crop for better irrigation management. Unfortunately, gs measurement typically requires contact measuring instruments and manual collection in the field, which is time-consuming and labor-intensive. Thus, this study estimates gs in two ways. Firstly, plant phenotypic data and weather information were used to estimate gs for various types of crops. The plant phenotypic data were extracted from images captured by a thermal infrared camera, a multispectral camera, and a visible and near-infrared spectrometer integrated on field phenotyping platform. Weather information was obtained from a field weather station. The random forest regression (RFR) model performed the best with R2 of 0.69 and RMSE of 0.135 mol*m-2 *s-1 , while the model using weather parameters alone had R2 of 0.58 and RMSE of 0.161, and the model using phenotypic data alone had R2 values of 0.59 and RMSE of 0.158 mol*m-2 *s-1 . The results indicated that there was a complementary relationship between plant phenotypic data and weather information in estimating gs. The second aspect of the study was to estimate maize and soybean gs directly from near-infrared, thermal-infrared and RGB (Red Green Blue) images collected by the same platform. The results showed that the convolutional neural network (CNN) model outperformed the other models with an R2 of 0.52. In addition, adding soil moisture as a variable to the model improved its accuracy, which decreased the RMSE from 0.147 to 0.137 mol*m-2 *s-1 . This study highlights the potential of estimating gs from remote sensing and field phenotyping platforms to help growers obtain information about the water status of crops and plan irrigation more efficiently. Advisor: Yufeng G

Study of Root System Architectural Traits of Oat and Response to Endophyte Inoculation and Drought Stress

Oat is an important cereal crop grown worldwide. Oats have the potential to contribute to human health due to their unique nutritional attributes. Developing oat cultivars with efficient root systems able to extract heterogeneously distributed soil resources can help maintain yield under drought conditions and in nutrient poor soil. Various root traits determine the soil volume that is explored by the root system for resource acquisition. Knowledge about the genetic control of oat root traits and response to biotic and abiotic environmental factors is lacking. Identifying quantitative trait loci associated with root traits and understanding the response of roots to abiotic and biotic environmental factors such as drought and endophytic bacteria may enable plant breeders to develop oat cultivars with efficient roots that can maintain yield under unstable climates. To understand the genetic basis of various root traits in oats and how the oat root and shoot development is impacted by drought and by plant growth-promoting endophytic bacteria, we conducted three different experiments. First, we studied the response of oat root and shoot development to endophytic bacterial inoculation by conducting a root vigor assay and a greenhouse experiment. Several endophytic bacteria significantly increased the root length, root area and root volume for one of the two oat cultivars evaluated in the root xiii vigor assay. The greenhouse study revealed that the response of oat cultivars to endophytic bacterial inoculation varied depending on the growth parameters evaluated, the nitrogen fertilization level, the oat genotype, and their interactions. Thus, identifying a specific strain of bacteria for overall growth promotion in oats might be difficult. To gain a better understanding of the extent of phenotypic differences in roots among oat genotypes and how those variations are controlled genetically, a genome-wide association study of root system architectural traits was conducted. Root traits were phenotyped at the seedling stage using a germination paper-based growth platform and a high-throughput image analysis system. Significant variability in root traits among the 285 genotypes evaluated was observed and broad-sense heritability ranged from 0.17 to 0.59 depending on the trait. We identified 82 significant marker-trait associations using a mixed linear model approach. Markers significantly associated with root traits explained from 7.6 to 19.9 % of the phenotypic variation. We identified multiple candidate genes located close to the significant markers that are known to have a role in root development. Finally, we evaluated the morphological and physiological responses of root and shoot development of ten oat genotypes under drought stress. After withholding watering for two weeks on 21 days old seedlings, we measured chlorophyll content, relative water content, stomatal conductance, stomata number, shoot dry weight, root dry weight, root length, root area, and root volume. Seed yield per plant was also collected by continuing the drying and rewatering cycle until physiological maturity. All traits measured were significantly impacted by the water regime. Oat cultivar Hayden showed the smallest reduction in vigor assay. The greenhouse study revealed that the response of oat cultivars to endophytic bacterial inoculation varied depending on the growth parameters evaluated, the nitrogen fertilization level, the oat genotype, and their interactions. Thus, identifying a specific strain of bacteria for overall growth promotion in oats might be difficult. To gain a better understanding of the extent of phenotypic differences in roots among oat genotypes and how those variations are controlled genetically, a genome-wide association study of root system architectural traits was conducted. Root traits were phenotyped at the seedling stage using a germination paper-based growth platform and a high-throughput image analysis system. Significant variability in root traits among the 285 genotypes evaluated was observed and broad-sense heritability ranged from 0.17 to 0.59 depending on the trait. We identified 82 significant marker-trait associations using a mixed linear model approach. Markers significantly associated with root traits explained from 7.6 to 19.9 % of the phenotypic variation. We identified multiple candidate genes located close to the significant markers that are known to have a role in root development. Finally, we evaluated the morphological and physiological responses of root and shoot development of ten oat genotypes under drought stress. After withholding watering for two weeks on 21 days old seedlings, we measured chlorophyll content, relative water content, stomatal conductance, stomata number, shoot dry weight, root dry weight, root length, root area, and root volume. Seed yield per plant was also collected by continuing the drying and rewatering cycle until physiological maturity. All traits measured were significantly impacted by the water regime. Oat cultivar Hayden showed the smallest reduction in yield in response to drought treatment. Hayden also showed a smaller reduction in relative water content, chlorophyll content, and a strong reduction in stomata number. Results indicated that the larger root system may not necessarily provide a yield advantage under drought conditions in oats. The importance of root mass distribution into lower and upper soil layers should be investigated to improve our understanding of mechanisms involved in coping with drought

A Novel Method for Quantifying Spatial Patterns in Plants

Color patterns are found in a plethora of organisms, from vertebrates to flowering plants. While many studies have examined the mechanisms that produce these diverse patterns in animals, little research has investigated the mechanisms by which plants create color patterns. The conclusions drawn from animal studies may not accurately translate to plants due to early divergence in the evolution of life. Characterization of plant patterning mechanisms would have widespread impacts on developmental and evolutionary biology. To unravel the mystery behind pattern formation, we suggest an experimental framework to understand pattern evolution and development at a phenotypic, genotypic, and quantitative level, creating a holistic model for the evolution of complex traits and phenotypic diversity. Here, we provide a novel protocol for the quantification of pattern morphology, and demonstrate its efficacy in a segregating F2 population of the model organism Mimulus luteus . By co-opting ArcGIS and FragStats, two landscape ecology softwares, to map petal patterns, we developed a high throughput method for objective phenotype characterization. This protocol is useful for preliminary work in a bulk segregant analysis by separating a population in discrete groups based on morphology. We used this protocol to demonstrate that patterns are distinct between petals within the same flower depending on petal location, and that there is a genetic basis for pattern formation in flowers. Minor tweaks to the genes guiding pattern formation may be responsible for the rapid evolution of angiosperm flower diversity. Future work is required to identify the genes responsible for pattern formation, and to develop a method for modeling these genes to predict how minor mutations would impact phenotypic traits

Phenotyping to dissect the biostimulant action of a protein hydrolysate in tomato plants under combined abiotic stress

Drought and heat stresses are the main constrains to agricultural crop production worldwide. Precise and efficient phenotyping is essential to understand the complexity of plant responses to abiotic stresses and to identify the best management strategies to increase plant tolerance. In the present study, two phenotyping platforms were used to investigate the effects of a protein hydrolysate-based biostimulant on the physiological response of two tomato genotypes (‘E42’ and ‘LA3120’) subjected to heat, drought, or combined stress. The free amino acids in the biostimulant, or other molecules, stimulated growth in treated plants subjected to combined stress, probably promoting endogenous phytohormonal biosynthesis. Moreover, biostimulant application increased the net photosynthetic rate and maximal efficiency of PSII photochemistry under drought, possibly related to the presence of glycine betaine and aspartic acid in the protein hydrolysate. Increased antioxidant content and a decreased accumulation of hydrogen peroxide, proline, and soluble sugars in treated plants under drought and combined stress further demonstrated that the biostimulant application mitigated the negative effects of abiotic stresses. Generally, the response to biostimulant in plants had a genotype-dependent effect, with ‘E42’ showing a stronger response to protein hydrolysate application than ‘LA3120’. Altogether, in this study a fine and multilevel phenotyping revealed increased plant performances under water-limited conditions and elevated temperatures induced by a protein hydrolysate, thus highlighting the great potential biostimulants have in improving plant resilience to abiotic stresses

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

A Deep Learning Method for Fully Automatic Stomatal Morphometry and Maximal Conductance Estimation

Stomata are integral to plant performance, enabling the exchange of gases between the atmosphere and the plant. The anatomy of stomata influences conductance properties with the maximal conductance rate, gsmax, calculated from density and size. However, current calculations of stomatal dimensions are performed manually, which are time-consuming and error prone. Here, we show how automated morphometry from leaf impressions can predict a functional property: the anatomical gsmax. A deep learning network was derived to preserve stomatal morphometry via semantic segmentation. This forms part of an automated pipeline to measure stomata traits for the estimation of anatomical gsmax. The proposed pipeline achieves accuracy of 100% for the distinction (wheat vs. poplar) and detection of stomata in both datasets. The automated deep learning-based method gave estimates for gsmax within 3.8 and 1.9% of those values manually calculated from an expert for a wheat and poplar dataset, respectively. Semantic segmentation provides a rapid and repeatable method for the estimation of anatomical gsmax from microscopic images of leaf impressions. This advanced method provides a step toward reducing the bottleneck associated with plant phenotyping approaches and will provide a rapid method to assess gas fluxes in plants based on stomata morphometry

Characterization of plant water flows in Controlled environment -PLANT SMART SENSORS

The present thesis project "Characterization of water flows in Controlled Environment -PLANT SMART SENSORS" has a multidisciplinary core and aimed towards the creation of synergies between the world of scientific research and the industry. By applying research results to technological development, this research targeted at innovation in the Agrotechnology and Aerospace sectors. Indeed, the introduction of new technologies is pivotal for controlled environment production on Earth to feed a growing population as well as for human permanence in Space in longterm missions where plants are used to regenerate resources (e.g. oxygen, water) and as source of fresh high-nutritious food. The realization of these systems must be based on a precise knowledge of plant morpho-anatomical development and its physiological behavior in closed growth systems, which are strongly influenced by numerous environmental factors including the relative humidity or more specifically the Vapour Pressure Deficit (VPD). In a protected environment (e.g. in Space greenhouses, vertical farm, indoor growing-modules), the control of relative humidity represents a significant problem, which has often been neglected. For instance, in conditions of poor aeration, too high humidity can occur with consequent low values of VPD which reduces the plant transpiration, slowing or stopping the water flow through the SPAC (Soil-plant-atmosphere-continuum), and ultimately blocking the photosynthesis, yield and biomass production. Even though there have been many studies regarding the VPD control, alone and/or in combination with other environmental factors, certain points are still unclear or controversial, providing contrasting results in different or even in the same species. This happens mainly due to the complex interactions between many microclimatic factors and plant physiological behaviour at different phenological stages. In a context of climate change, the efficient regulation of VPD can be applied to greenhouse and indoor-module production in order to enhance crop productivity, improve WUE and reduce total water consumption to design irrigation strategies, considering the balance between the amount of water saved and the quantity used to regulate the VPD. The regulation of the VPD and related environmental parameters need to be designed according to the species and its adaptive plasticity at morphophysiological levels.  Thus, the characterization and modeling of water flows in model plants in different growth chamber scenarios (from small modules intended for the spatialization for Space applications, up to structures that can be used in protected cultivation on Earth), as well as the real-time monitoring of the water status of plants, become fundamental for the management of precision agriculture both in support of Space exploration and for the sustainability of urban agriculture. To date, most of the research has focused on either specific physiological/structural aspect at the single-plant level, or on cultivation management or even on technological aspects, with only a few interlinks of knowledge. The aim of this thesis is to develop knowledge to help filling this gap to improve the understanding of VPD effects on crop productivity, with the creation of synergies among different expertise (e.g., plant physiology, crop science, engineering). To do so, it is fundamental to study the complexity of plant morpho/physiological responses, since without a deep knowledge of mechanisms behind plant responses to the environment it is difficult to determine how and to which extent plants can adapt to any changes in the environmental conditions. The application of a multidisciplinary approach in research will allow crop production in a sustainable way, even in harsh environments, where a "climate smart-agriculture" becomes necessary to improve crop yield and quality. The present thesis is organized as follows: Chapter 1 is a review which presents the current state of knowledge on how VPD influences plant morpho-physiological traits in controlled environment agriculture. The study has been published as a review article in Annals of Applied Biology (Amitrano et al., 2019 https://doi.org/10.1111/aab.12544). It covers main important aspects of VPD influence on plant growth, morpho-anatomical development, and physiology, emphasizing the possible interaction between VPD and other microclimatic factors in protected cultivation. Furthermore, the rewiew identifies and discusses future research areas, which should be explored further, based on needed synergies among different expertise from biological and horticultural fields. Chapter 2 presents evidence that the modulation of relative humidity (RH) together with other important cultivation factors such as light (presence/absence), can influence morpho-anatomical development and improve antioxidant content, even at the early stages of plant life cycle (germination, seedling establishment). The combined effect of RH and light was studied during the germination and seedling development of Vigna radiata L. (mung bean), a species widespread throughout the world also due to the high nutritional value of its edible sprouts. A manuscript reporting these data has been published in Plants (Amitrano et al., 2020a https://doi.org/10.3390/plants9091093). In Chapter 3, the role of leaf anatomical traits (e.g. leaf mesophyll features, stomata and vein traits) in photosynthetic acclimation to short- and long-term changes in VPD was examined in Vigna radiata L. adult plants. In this study, we underlined the key role of leaf structure in photosynthetic acclimation to air VPD. The long-term exposure to different VPD levels determined a pre-acclimation at the leaf morpho-anatomical level which influenced the extent of leaf physiological plasticity, changing plant ability to acclimate to any changes in the surrounding microclimate. This different leaf anatomy-related capacity of pre-acclimating becomes therefore fundamental in the present climate-change scenario due to its key role in the adaptation process under changing environmental conditions. A manuscript reporting these data has been published in Environmental and Experimental Botany (Amitrano et al., 2021a https://doi.org/10.1016/j.envexpbot.2021.104453). In Chapter 4, the effect of VPD on morpho-physiological traits also incorporating the trade-off between transpiration and carbon gain was evaluated in two cultivars of Salanova lettuce (Lactuca sativa L.) with green and red leaves, in a growth-chamber experiment. Low-VPD turned out to significantly improve growth, stomata development and hydraulic-related traits which led to higher photosynthesis and a reduced water consumption compared to the high-VPD condition. A manuscript reporting these data was published in Agronomy (Amitrano et al., 2021b https://doi.org/10.3390/agronomy11071396).  Chapter 5 represents a clear interlink of knowledge between plant scientists, engineers, mathematician and modelists. In this study, published in Sensors (Amitrano et al., 2020b https://doi.org/10.3390/s20113110), we used experimental data, based on morpho-anatomical analyses of lettuce plants, to run the Energy Cascade Model (MEC), a model already used to predict biomass production and photosynthetic efficiency in advanced life support systems studies (Space-oriented research). Here, the modification of the model is discussed together with possible improvements and applications. Chapter 6 focuses on how to modulate the micro-environment, and in particular the VPD levels, in protected cultivation to improve plant antioxidant content in crops. More specifically, the exposure of the same lettuce cultivars mentioned in previous chapters to high VPD determined an improved phytochemical content in lettuce leaves, especially in the red cultivar. Here we discussed a further possibility to use short-term high VPD treatments as a mild stress to boost the phytochemical production in lettuce plants. A Manuscript reporting these data has been published in Horticulturae (Amitrano et al., 2021c http://doi.org/10.3390/horticulturae7020032). Chapter 7 is a deep focus on how the VPD drives the coordination among morpho-anatomical traits in leaves of the above-mentioned lettuce cultivars, also exploring the variability of traits along the leaf lamina. More specifically, the attention is focused on how stomata and vein develop within lettuce leaves and how these traits are coordinated with leaf size under different VPDs. Results from this study suggest that VPD triggers a different response in lettuce plants in terms of balance of leaf 4 traits and highlight the possibility of further exploring the microenvironment (combined influence of light and VPD) to adjust the development of stomata and vein densities, thus providing optimal water and gas fluxes through the leaves. In Chapter 8, the experiments conducted during the period spent at the Controlled Environment Agriculture Center of the University of Arizona (UA-CEAC) are reported. The experiments reported here were conducted on the same species of the previous chapters (Salanvoa lettuce with green and red leaves) in a multi-layer vertical farm to test the interaction between VPD and other microclimatic factors on plant morpho-physiological development. More specifically two experimental trials are reported (E1 and E2). In E1, the interaction between VPD levels (low and high) and increasing DLI (Daily Light Integral - 8.6, 12.9, 15.5) was tested to study morpho-physiological changes and to determine the optimal combination of DLI and VPD for lettuce growth. In E2, a sudden salt stress was applied to the cultivation and then CO2 enrichment was provided, based on the hypothesis that the CO2 enrichment would mitigate the salt stress, modifying the plant carbon gain/water balance. We evaluated whether the mechanisms of salt stress mitigation due to CO2 enrichment were different under high and low VPD conditions, depending on the different morphoanatomical leaf structure.   Chapter 9 reports on experiments conducted at the IPK-Leibniz institute of plant genetics and crop plant research (Gatersleeben, Germany) in the framework of the EPPN2020 transnational access (https://eppn2020.plant-phenotyping.eu/EPPN_Transnational_Access). A report with obtained results is showed in this chapter. These experiments concern the application of high-throughput phenotyping combined with morpho-anatomical analyses on Salanova green and red plants acclimated to a VPD level and then subjected to short-term changes in the VPD. The project submitted to the EPPN transnational access and winner of the grant is presented in Appendix 1. Chapter 10 and 11 report on the possible industrial applications after the collaboration with the partner company "Kayser Italia srl" (http://www.kayser.it/). Chapter 10 is a study for the definition of scientific and technical requirements for the realization of a miniaturized phenotyping growth chamber to grow microgreens or small crops in Space. The structure of the chamber is based on the "Kubik" incubator, an incubator facility of the European Space Agency with the shape of a cube of about 40 cm that has been operating aboard the International Space Station for more than 12 years, carrying different life science experiments. In the chapter, technical and scientific requirements are listed and a preliminary schedule for the project realization is provided. At the end of the chapter, open issues are also discussed. In Chapter 11, the set-up of a prototype miniaturized cultivation chamber for use in Space is described and the results of validation tests, carried out at Kayser Italia with brassica microgreens (Brassica rapa subsp. sylvestris var. esculenta) under different air relative humidities (VPD), are reported. In Appendix 1, the project submitted to the EPPN transnational access (PHEW- Automated phenotyping platform to improve lettuce water use efficiency under different VPD and watering regimens) and winner of the grant is presented. In Appendix 2, a brief recap on the activities conducted during the Ph.D. program is presented