Surveying the plant's world by magnetic resonance imaging

Modern phenomics to empower holistic crop science, agronomy, and breeding research

Crop phenomics enables the collection of diverse plant traits for a large number of samples along different time scales, representing a greater data collection throughput compared with traditional measurements. Most modern crop phenomics use different sensors to collect reflective, emitted, and fluorescence signals, etc., from plant organs at different spatial and temporal resolutions. Such multi-modal, high-dimensional data not only accelerates basic research on crop physiology, genetics, and whole plant systems modeling, but also supports the optimization of field agronomic practices, internal environments of plant factories, and ultimately crop breeding. Major challenges and opportunities facing the current crop phenomics research community include developing community consensus or standards for data collection, management, sharing, and processing, developing capabilities to measure physiological parameters, and enabling farmers and breeders to effectively use phenomics in the field to directly support agricultural production.

Plant microphenotype: from innovative imaging to computational analysis

The microphenotype plays a key role in bridging the gap between the genotype and the complex macro phenotype. In this article, we review the advances in data acquisition and the intelligent analysis of plant microphenotyping and present applications of microphenotyping in plant science over the past two decades. We then point out several challenges in this field and suggest that cross-scale image acquisition strategies, powerful artificial intelligence algorithms, advanced genetic analysis, and computational phenotyping need to be established and performed to better understand interactions among genotype, environment, and management. Microphenotyping has entered the era of Microphenotyping 3.0 and will largely advance functional genomics and plant science.

In Situ Root Dataset Expansion Strategy Based on an Improved CycleGAN Generator

The root system plays a vital role in plants' ability to absorb water and nutrients. In situ root research offers an intuitive approach to exploring root phenotypes and their dynamics. Deep-learning-based root segmentation methods have gained popularity, but they require large labeled datasets for training. This paper presents an expansion method for in situ root datasets using an improved CycleGAN generator. In addition, spatial-coordinate-based target background separation method is proposed, which solves the issue of background pixel variations caused by generator errors. Compared to traditional threshold segmentation methods, this approach demonstrates superior speed, accuracy, and stability. Moreover, through time-division soil image acquisition, diverse culture medium can be replaced in in situ root images, thereby enhancing dataset versatility. After validating the performance of the Improved_UNet network on the augmented dataset, the optimal results show a 0.63% increase in mean intersection over union, 0.41% in F1, and 0.04% in accuracy. In terms of generalization performance, the optimal results show a 33.6% increase in mean intersection over union, 28.11% in F1, and 2.62% in accuracy. The experimental results confirm the feasibility and practicality of the proposed dataset augmentation strategy. In the future, we plan to combine normal mapping with rendering software to achieve more accurate shading simulations of in situ roots. In addition, we aim to create a broader range of images that encompass various crop varieties and soil types.

Non-invasive assessment and visualization of Phytophthora cactorum infection in strawberry crowns using quantitative magnetic resonance imaging

Phytophthora cactorum is an oomycete species that causes enormous losses on horticultural crops, including strawberries. The purpose of this work was to investigate the alterations caused by P. cactorum inoculation in hydroponically grown strawberry plantlets (Fragaria × ananassa Duch.) using quantitative magnetic resonance imaging (qMRI). It was observed that with MRI, spatial and temporal progression of the infection could be observed in the crown using quantitative MR parameters, namely relaxation time maps. Relaxation times are numeric subject-specific properties that describe the MR signal behavior in an examined anatomical region. Elevated [Formula: see text] relaxation time values were observed inside the infected plant crowns with respect to the healthy references. The [Formula: see text] and [Formula: see text] values of healthy plants were small in the crown region and further diminished during the development of the plant. Furthermore, elevated [Formula: see text] relaxation time values were seen in regions where P. cactorum progression was observed in corresponding plant dissection photographs. Quantitative susceptibility maps (QSM) were calculated to estimate the local magnetic field inhomogeneities. The QSM suggests magnetic susceptibility differences near the center of the pith. This study provides novel non-invasive information on the structure and development of strawberry plants and the effects caused by the P. cactorum infection.

Leaf relative water content at 50% stomatal conductance measured by noninvasive NMR is linked to climate of origin in nine species of eucalypt

Stomata are the gatekeepers of plant water use and must quickly respond to changes in plant water status to ensure plant survival under fluctuating environmental conditions. The mechanism for their closure is highly sensitive to disturbances in leaf water status, which makes isolating their response to declining water content difficult to characterise and to compare responses among species. Using a small-scale non-destructive nuclear magnetic resonance spectrometer as a leaf water content sensor, we measure the stomatal response to rapid induction of water deficit in the leaves of nine species of eucalypt from contrasting climates. We found a strong linear correlation between relative water content at 50% stomatal conductance (RWCgs50 ) and mean annual temperature at the climate of origin of each species. We also show evidence for stomata to maintain control over water loss well below turgor loss point in species adapted to warmer climates and secondary increases in stomatal conductance despite declining water content. We propose that RWCgs50 is a promising trait to guide future investigations comparing stomatal responses to water deficit. It may provide a useful phenotyping trait to delineate tolerance and adaption to hot temperatures and high leaf-to-air vapour pressure deficits.

Thermal imaging: The digital eye facilitates high-throughput phenotyping traits of plant growth and stress responses

Plant phenotyping is important for plants to cope with environmental changes and ensure plant health. Imaging techniques are perceived as the most critical and reliable tools for studying plant phenotypes. Thermal imaging has opened up new opportunities for nondestructive imaging of plant phenotyping. However, a comprehensive summary of thermal imaging in plant phenotyping is still lacking. Here we discuss the progress and future prospects of thermal imaging for assessing plant growth and stress responses. First, we classify thermal imaging into ground-based and aerial platforms based on their adaptability to different experimental environments (including laboratory, greenhouse, and field). It is convenient to collect phenotypic information of different dimensions. Second, in order to enhance the efficiency of thermal image processing, automatic algorithms based on deep learning are employed instead of traditional manual methods, greatly reducing the time cost of experiments. Considering its ease of implementation, handling and instant response, thermal imaging has been widely used in research on environmental stress, crop yield, and seed vigor. We have found that thermal imaging can detect thermal energy dissipation caused by living organisms (e.g., pests, viruses, bacteria, fungi, and oomycetes), enabling early disease diagnosis. It also recognizes changes leaf surface temperatures resulting from reduced transpiration rates caused by nutrient deficiency, drought, salinity, or freezing. Furthermore, thermal imaging predicts crop yield under different water states and forecasts the viability of dormant seeds after water absorption by monitoring temperature changes in the seeds. This work will assist biologists and agronomists in studying plant phenotypes and serve a guide for breeders to develop high-yielding, stress-tolerant, and superior crops.

An overview of image-based phenotyping as an adaptive 4.0 technology for studying plant abiotic stress: A bibliometric and literature review

Improving the tolerance of crop species to abiotic stresses that limit plant growth and productivity is essential for mitigating the emerging problems of global warming. In this context, imaged data analysis represents an effective method in the 4.0 technology era, where this method has the non-destructive and recursive characterization of plant phenotypic traits as selection criteria. So, the plant breeders are helped in the development of adapted and climate-resilient crop varieties. Although image-based phenotyping has recently resulted in remarkable improvements for identifying the crop status under a range of growing conditions, the topic of its application for assessing the plant behavioral responses to abiotic stressors has not yet been extensively reviewed. For such a purpose, bibliometric analysis is an ideal analytical concept to analyze the evolution and interplay of image-based phenotyping to abiotic stresses by objectively reviewing the literature in light of existing database. Bibliometricy, a bibliometric analysis was applied using a systematic methodology which involved data mining, mining data improvement and analysis, and manuscript construction. The obtained results indicate that there are 554 documents related to image-based phenotyping to abiotic stress until 5 January 2023. All document showed the future development trends of image-based phenotyping will be mainly centered in the United States, European continent and China. The keywords analysis major focus to the application of 4.0 technology and machine learning in plant breeding, especially to create the tolerant variety under abiotic stresses. Drought and saline become an abiotic stress often using image-based phenotyping. Besides that, the rice, wheat and maize as the main commodities in this topic. In conclusion, the present work provides information on resolutive interactions in developing image-based phenotyping to abiotic stress, especially optimizing high-throughput sensors in image-based phenotyping for the future development.

Size measurement and filled/unfilled detection of rice grains using backlight image processing

Measurements of rice physical traits, such as length, width, and percentage of filled/unfilled grains, are essential steps of rice breeding. A new approach for measuring the physical traits of rice grains for breeding purposes was presented in this study, utilizing image processing techniques. Backlight photography was used to capture a grayscale image of a group of rice grains, which was then analyzed using a clustering algorithm to differentiate between filled and unfilled grains based on their grayscale values. The impact of backlight intensity on the accuracy of the method was also investigated. The results show that the proposed method has excellent accuracy and high efficiency. The mean absolute percentage error of the method was 0.24% and 1.36% in calculating the total number of grain particles and distinguishing the number of filled grains, respectively. The grain size was also measured with a little margin of error. The mean absolute percentage error of grain length measurement was 1.11%, while the measurement error of grain width was 4.03%. The method was found to be highly accurate, non-destructive, and cost-effective when compared to conventional methods, making it a promising approach for characterizing physical traits for crop breeding.

Synchrotron micro-computed tomography unveils the three-dimensional structure and origin of staminodes in the Plains Prickly Pear Cactus Opuntia polyacantha Haw. (Cactaceae)

Floral appendages display an array of shapes and sizes. Among these organs, staminodes are morphologically diverse structures that have lost the ability to produce pollen, but in some instances, they produce fertile pollen grains. In the family Cactaceae staminodes are uncommon and range from simple linear to flat to spatulate structures, but studies describing their structural attributes are scanty. This study highlights the advantages of synchrotron radiation for sample preparation and as a research tool for plant biology. It describes the internal morphology of floral parts, particularly stamen, tepal, and staminode in the Plains Prickly Pear Cactus, Opuntia polyacantha, using synchrotron radiation micro-computed tomography (SR-μCT). It also shows the different anatomical features in reconstructed three-dimensional imaging of reproductive parts and discuss the advantages of the segmentation method to detect and characterize the configuration and intricate patterns of vascular networks and associated structures of tepal and androecial parts applying SR-μCT. This powerful technology led to substantial improvements in terms of resolution allowing a more comprehensive understanding of the anatomical organization underlying the vasculature of floral parts and inception of staminodes in O. polyacantha. Tepal and androecial parts have uniseriate epidermis enclosing loose mesophyll with mucilage secretory ducts, lumen, and scattered vascular bundles. Cryptic underlying structural attributes provide evidence of a vascularized pseudo-anther conjoint with tepals. The undefined contours of staminodial appendages (pseudo-anther) amalgamated to the tepals' blurred boundaries suggest that staminodes originate from tepals, a developmental pattern supporting the fading border model of floral organ identity for angiosperms.

Application of Improved UNet and EnglightenGAN for Segmentation and Reconstruction of In Situ Roots

The root is an important organ for crops to absorb water and nutrients. Complete and accurate acquisition of root phenotype information is important in root phenomics research. The in situ root research method can obtain root images without destroying the roots. In the image, some of the roots are vulnerable to soil shading, which severely fractures the root system and diminishes its structural integrity. The methods of ensuring the integrity of in situ root identification and establishing in situ root image phenotypic restoration remain to be explored. Therefore, based on the in situ root image of cotton, this study proposes a root segmentation and reconstruction strategy, improves the UNet model, and achieves precise segmentation. It also adjusts the weight parameters of EnlightenGAN to achieve complete reconstruction and employs transfer learning to implement enhanced segmentation using the results of the former two. The research results show that the improved UNet model has an accuracy of 99.2%, mIOU of 87.03%, and F1 of 92.63%. The root reconstructed by EnlightenGAN after direct segmentation has an effective reconstruction ratio of 92.46%. This study enables a transition from supervised to unsupervised training of root system reconstruction by designing a combination strategy of segmentation and reconstruction network. It achieves the integrity restoration of in situ root system pictures and offers a fresh approach to studying the phenotypic of in situ root systems, also realizes the restoration of the integrity of the in situ root image, and provides a new method for in situ root phenotype study.

Seeing plants as never before

Imaging has long supported our ability to understand the inner life of plants, their development, and response to a dynamic environment. While optical microscopy remains the core tool for imaging, a suite of novel technologies is now beginning to make a significant contribution to visualize plant metabolism. The purpose of this review was to provide the scientific community with an overview of current imaging methods, which rely variously on either nuclear magnetic resonance (NMR), mass spectrometry (MS) or infrared (IR) spectroscopy, and to present some examples of their application in order to illustrate their utility. In addition to providing a description of the basic principles underlying these technologies, the review discusses their various advantages and limitations, reveals the current state of the art, and suggests their potential application to experimental practice. Finally, a view is presented as to how the technologies will likely develop, how these developments may encourage the formulation of novel experimental strategies, and how the enormous potential of these technologies can contribute to progress in plant science.

New insight into the genetic basis of oil content based on noninvasive three-dimensional phenotyping and tissue-specific transcriptome in Brassica napus

BACKGROUND

Increasing seed oil content is the most important breeding goal in Brassica napus, and phenotyping is crucial to dissect its genetic basis in crops. To date, QTL mapping for oil content has been based on whole seeds, and the lipid distribution is far from uniform in different tissues of seeds in B. napus. In this case, the phenotype based on whole seeds was unable to sufficiently reveal the complex genetic characteristics of seed oil content.

RESULTS

Here, the three-dimensional (3D) distribution of lipid was determined for B. napus seeds by magnetic resonance imaging (MRI) and 3D quantitative analysis, and ten novel oil content-related traits were obtained by subdividing the seeds. Based on a high-density genetic linkage map, 35 QTLs were identified for 4 tissues, the outer cotyledon (OC), inner cotyledon (IC), radicle (R) and seed coat (SC), which explained up to 13.76% of the phenotypic variation. Notably, 14 tissue-specific QTLs were reported for the first time, 7 of which were novel. Moreover, haplotype analysis showed that the favorable alleles for different seed tissues exhibited cumulative effects on oil content. Furthermore, tissue-specific transcriptomes revealed that more active energy and pyruvate metabolism influenced carbon flow in the IC, OC and R than in the SC at the early and middle seed development stages, thus affecting the distribution difference in oil content. Combining tissue-specific QTL mapping and transcriptomics, 86 important candidate genes associated with lipid metabolism were identified that underlie 19 unique QTLs, including the fatty acid synthesis rate-limiting enzyme-related gene CAC2, in the QTLs for OC and IC.

CONCLUSIONS

The present study provides further insight into the genetic basis of seed oil content at the tissue-specific level.

Image-Based High-Throughput Phenotyping in Horticultural Crops

Plant phenotyping is the primary task of any plant breeding program, and accurate measurement of plant traits is essential to select genotypes with better quality, high yield, and climate resilience. The majority of currently used phenotyping techniques are destructive and time-consuming. Recently, the development of various sensors and imaging platforms for rapid and efficient quantitative measurement of plant traits has become the mainstream approach in plant phenotyping studies. Here, we reviewed the trends of image-based high-throughput phenotyping methods applied to horticultural crops. High-throughput phenotyping is carried out using various types of imaging platforms developed for indoor or field conditions. We highlighted the applications of different imaging platforms in the horticulture sector with their advantages and limitations. Furthermore, the principles and applications of commonly used imaging techniques, visible light (RGB) imaging, thermal imaging, chlorophyll fluorescence, hyperspectral imaging, and tomographic imaging for high-throughput plant phenotyping, are discussed. High-throughput phenotyping has been widely used for phenotyping various horticultural traits, which can be morphological, physiological, biochemical, yield, biotic, and abiotic stress responses. Moreover, the ability of high-throughput phenotyping with the help of various optical sensors will lead to the discovery of new phenotypic traits which need to be explored in the future. We summarized the applications of image analysis for the quantitative evaluation of various traits with several examples of horticultural crops in the literature. Finally, we summarized the current trend of high-throughput phenotyping in horticultural crops and highlighted future perspectives.

A Synthetic Review of Various Dimensions of Non-Destructive Plant Stress Phenotyping

Non-destructive plant stress phenotyping begins with traditional one-dimensional (1D) spectroscopy, followed by two-dimensional (2D) imaging, three-dimensional (3D) or even temporal-three-dimensional (T-3D), spectral-three-dimensional (S-3D), and temporal-spectral-three-dimensional (TS-3D) phenotyping, all of which are aimed at observing subtle changes in plants under stress. However, a comprehensive review that covers all these dimensional types of phenotyping, ordered in a spatial arrangement from 1D to 3D, as well as temporal and spectral dimensions, is lacking. In this review, we look back to the development of data-acquiring techniques for various dimensions of plant stress phenotyping (1D spectroscopy, 2D imaging, 3D phenotyping), as well as their corresponding data-analyzing pipelines (mathematical analysis, machine learning, or deep learning), and look forward to the trends and challenges of high-performance multi-dimension (integrated spatial, temporal, and spectral) phenotyping demands. We hope this article can serve as a reference for implementing various dimensions of non-destructive plant stress phenotyping.

A method of cotton root segmentation based on edge devices

The root is an important organ for plants to absorb water and nutrients. In situ root research method is an intuitive method to explore root phenotype and its change dynamics. At present, in situ root research, roots can be accurately extracted from in situ root images, but there are still problems such as low analysis efficiency, high acquisition cost, and difficult deployment of image acquisition devices outdoors. Therefore, this study designed a precise extraction method of in situ roots based on semantic segmentation model and edge device deployment. It initially proposes two data expansion methods, pixel by pixel and equal proportion, expand 100 original images to 1600 and 53193 respectively. It then presents an improved DeeplabV3+ root segmentation model based on CBAM and ASPP in series is designed, and the segmentation accuracy is 93.01%. The root phenotype parameters were verified through the Rhizo Vision Explorers platform, and the root length error was 0.669%, and the root diameter error was 1.003%. It afterwards designs a time-saving Fast prediction strategy. Compared with the Normal prediction strategy, the time consumption is reduced by 22.71% on GPU and 36.85% in raspberry pie. It ultimately deploys the model to Raspberry Pie, realizing the low-cost and portable root image acquisition and segmentation, which is conducive to outdoor deployment. In addition, the cost accounting is only $247. It takes 8 hours to perform image acquisition and segmentation tasks, and the power consumption is as low as 0.051kWh. In conclusion, the method proposed in this study has good performance in model accuracy, economic cost, energy consumption, etc. This paper realizes low-cost and high-precision segmentation of in-situ root based on edge equipment, which provides new insights for high-throughput field research and application of in-situ root.

Phyllotaxis transition over the lifespan of a palm tree using Magnetic Resonance Imaging (MRI) and Terrestrial Laser Scanning (TLS): the case of Jubaea chilensis

BACKGROUND

Jubaea chilensis (Molina) Baillon, is a uniquely large palm species endemic to Chile. It is under threatened status despite its use as an ornamental species throughout the world. This research seeks to identify the phyllotaxis of the species based on an original combination of non-destructive data acquisition technologies, namely Magnetic Resonance Imaging (MRI) in saplings and young individuals and Terrestrial Laser Scanning (TLS) in standing specimens, and a novel analysis methodology.

RESULTS

Two phyllotaxis parameters, parastichy pairs and divergence angle, were determined by analyzing specimens at different developmental stages. Spiral phyllotaxis patterns of J. chilensis progressed in complexity from parastichy pairs (3,2) and (3,5) in juvenile specimens and (5,3), (8,5) and (8,13) for adult specimens. Divergence angle was invariable and averaged 136.9°, close to the golden angle. Phyllotactic pattern changes associated with establishment phase, the adult vegetative and the adult reproductive phases were observed. Both technologies, MRI and TLS proved to be adequate for the proposed analysis.

CONCLUSIONS

Understanding phyllotactic transitions may assist identification of developmental stages of wild J. chilensis specimens. The proposed methodology may also be useful for the study of other palm species.

Particle-Based Imaging Tools Revealing Water Flows in Maize Nodal Vascular Plexus

In plants, water flows are the major driving force behind growth and play a crucial role in the life cycle. To study hydrodynamics, methods based on tracking small particles inside water flows attend a special place. Thanks to these tools, it is possible to obtain information about the dynamics of the spatial distribution of the flux characteristics. In this paper, using contrast-enhanced magnetic resonance imaging (MRI), we show that gadolinium chelate, used as an MRI contrast agent, marks the structural characteristics of the xylem bundles of maize stem nodes and internodes. Supplementing MRI data, the high-precision visualization of xylem vessels by laser scanning microscopy was used to reveal the structural and dimensional characteristics of the stem vascular system. In addition, we propose the concept of using prototype “Y-type xylem vascular connection” as a model of the elementary connection of vessels within the vascular system. A Reynolds number could match the microchannel model with the real xylem vessels.

Capturing crop adaptation to abiotic stress using image-based technologies

Farmers and breeders aim to improve crop responses to abiotic stresses and secure yield under adverse environmental conditions. To achieve this goal and select the most resilient genotypes, plant breeders and researchers rely on phenotyping to quantify crop responses to abiotic stress. Recent advances in imaging technologies allow researchers to collect physiological data non-destructively and throughout time, making it possible to dissect complex plant responses into quantifiable traits. The use of image-based technologies enables the quantification of crop responses to stress in both controlled environmental conditions and field trials. This paper summarizes phenotyping imaging technologies (RGB, multispectral and hyperspectral sensors, among others) that have been used to assess different abiotic stresses including salinity, drought and nitrogen deficiency, while discussing their advantages and drawbacks. We present a detailed review of traits involved in abiotic tolerance, which have been quantified by a range of imaging sensors under high-throughput phenotyping facilities or using unmanned aerial vehicles in the field. We also provide an up-to-date compilation of spectral tolerance indices and discuss the progress and challenges in machine learning, including supervised and unsupervised models as well as deep learning.

Quantitative monitoring of paramagnetic contrast agents and their allocation in plant tissues via DCE-MRI

BACKGROUND

Studying dynamic processes in living organisms with MRI is one of the most promising research areas. The use of paramagnetic compounds as contrast agents (CA), has proven key to such studies, but so far, the lack of appropriate techniques limits the application of CA-technologies in experimental plant biology. The presented proof-of-principle aims to support method and knowledge transfer from medical research to plant science.

RESULTS

In this study, we designed and tested a new approach for plant Dynamic Contrast Enhanced Magnetic Resonance Imaging (pDCE-MRI). The new approach has been applied in situ to a cereal crop (Hordeum vulgare). The pDCE-MRI allows non-invasive investigation of CA allocation within plant tissues. In our experiments, gadolinium-DTPA, the most commonly used contrast agent in medical MRI, was employed. By acquiring dynamic T₁-maps, a new approach visualizes an alteration of a tissue-specific MRI parameter T₁ (longitudinal relaxation time) in response to the CA. Both, the measurement of local CA concentration and the monitoring of translocation in low velocity ranges (cm/h) was possible using this CA-enhanced method.

CONCLUSIONS

A novel pDCE-MRI method is presented for non-invasive investigation of paramagnetic CA allocation in living plants. The temporal resolution of the T₁-mapping has been significantly improved to enable the dynamic in vivo analysis of transport processes at low-velocity ranges, which are common in plants. The newly developed procedure allows to identify vascular regions and to estimate their involvement in CA allocation. Therefore, the presented technique opens a perspective for further development of CA-aided MRI experiments in plant biology.

Synchrotron Based X-ray Microtomography Reveals Cellular Morphological Features of Developing Wheat Grain

Wheat is one of the most important crops in the world, mainly used for human consumption and animal feed. To overcome the increasing demand in wheat production, it is necessary to better understand the mechanisms involved in the growth of the wheat grain. X-ray computed tomography is an efficient method for the non-destructive investigation of the 3D architecture of biological specimens, which does not require staining, sectioning, or inclusion. In particular, phase-contrast tomography results in images with better contrast and an increased resolution compared to that obtained with laboratory tomography devices. The aim of this study was to investigate the potential of phase-contrast tomography for the study of the anatomy of the wheat grain at early stages of development. We provided 3D images of entire grains at various development stages. The image analysis allowed identifying a large number of tissues, and to visualize individual cells. Using a high-resolution setup, finer details were obtained, making it possible to identify additional tissues. Three-dimensional rendering of the grain also revealed the pattern resulting from the epidermis cells. X-ray phase-contrast tomography appears as a promising imaging method for the study of the 3D anatomy of plant organs and tissues.

Mechanical Forces in Floral Development

Mechanical forces acting within the plant body that can mold flower shape throughout development received little attention. The palette of action of these forces ranges from mechanical pressures on organ primordia at the microscopic level up to the twisting of a peduncle that promotes resupination of a flower at the macroscopic level. Here, we argue that without these forces acting during the ontogenetic process, the actual flower phenotype would not be achieved as it is. In this review, we concentrate on mechanical forces that occur at the microscopic level and determine the fate of the flower shape by the physical constraints on meristems at an early stage of development. We thus highlight the generative role of mechanical forces over the floral phenotype and underline our general view of flower development as the sum of interactions of known physiological and genetic processes, together with physical aspects and mechanical events that are entangled towards the shaping of the mature flower.

The metabolic environment of the developing embryo: A multidisciplinary approach on oilseed rapeseed

Brassicaceae seeds consist of three genetically distinct structures: the embryo, endosperm and seed coat, all of which are involved in assimilate allocation during seed development. The complexity of their metabolic interrelations remains unresolved to date. In the present study, we apply state-of-the-art imaging and analytical approaches to assess the metabolic environment of the Brassica napus embryo. Nuclear magnetic resonance imaging (MRI) provided volumetric data on the living embryo and endosperm, revealing how the endosperm envelops the embryo, determining endosperm's priority in assimilate uptake from the seed coat during early development. MRI analysis showed higher levels of sugars in the peripheral endosperm facing the seed coat, but a lower sugar content within the central vacuole and the region surrounding the embryo. Feeding intact siliques with ¹³C-labeled sucrose allowed tracing of the post-phloem route of sucrose transfer within the seed at the heart stage of embryogenesis, by means of mass spectrometry imaging. Quantification of over 70 organic and inorganic compounds in the endosperm revealed shifts in their abundance over different stages of development, while sugars and potassium were the main determinants of osmolality throughout these stages. Our multidisciplinary approach allows access to the hidden aspects of endosperm metabolism, a task which remains unattainable for the small-seeded model plant Arabidopsis thaliana.

Microstructure investigation of plant architecture with X-ray microscopy

In recent years, the plant morphology has been well studied by multiple approaches at cellular and subcellular levels. Two-dimensional (2D) microscopy techniques offer imaging of plant structures on a wide range of magnifications for researchers. However, subcellular imaging is still challenging in plant tissues like roots and seeds. Here we use a three-dimensional (3D) imaging technology based on the X-ray microscope (XRM) and analyze several plant tissues from different plant species. The XRM provides new insights into plant structures using non-destructive imaging at high-resolution and high contrast. We also utilized a workflow aiming to acquire accurate and high-quality images in the context of the whole specimen. Multiple plant samples including rice, tobacco, Arabidopsis and maize were used to display the differences of phenotypes. Our work indicates that the XRM is a powerful tool to investigate plant microstructure in high-resolution scale. Our work also provides evidence that evaluate and quantify tissue specific differences for a range of plant species. We also characterize novel plant tissue phenotypes by the XRM, such as seeds in Arabidopsis, and utilize them for novel observation measurement. Our work represents an evaluated spatial and temporal resolution solution on seed observation and screening.

Non-invasive hydrodynamic imaging in plant roots at cellular resolution

A key impediment to studying water-related mechanisms in plants is the inability to non-invasively image water fluxes in cells at high temporal and spatial resolution. Here, we report that Raman microspectroscopy, complemented by hydrodynamic modelling, can achieve this goal - monitoring hydrodynamics within living root tissues at cell- and sub-second-scale resolutions. Raman imaging of water-transporting xylem vessels in Arabidopsis thaliana mutant roots reveals faster xylem water transport in endodermal diffusion barrier mutants. Furthermore, transverse line scans across the root suggest water transported via the root xylem does not re-enter outer root tissues nor the surrounding soil when en-route to shoot tissues if endodermal diffusion barriers are intact, thereby separating 'two water worlds'.

Unraveling the roles of plant specialized metabolites: using synthetic biology to design molecular biosensors

Plants are a rich source of specialized metabolites with a broad range of bioactivities and many applications in human daily life. Over the past decades significant progress has been made in identifying many such metabolites in different plant species and in elucidating their biosynthetic pathways. However, the biological roles of plant specialized metabolites remain elusive and proposed functions lack an identified underlying molecular mechanism. Understanding the roles of specialized metabolites frequently is hampered by their dynamic production and their specific spatiotemporal accumulation within plant tissues and organs throughout a plant's life cycle. In this review, we propose the employment of strategies from the field of Synthetic Biology to construct and optimize genetically encoded biosensors that can detect individual specialized metabolites in a standardized and high-throughput manner. This will help determine the precise localization of specialized metabolites at the tissue and single-cell levels. Such information will be useful in developing complete system-level models of specialized plant metabolism, which ultimately will demonstrate how the biosynthesis of specialized metabolites is integrated with the core processes of plant growth and development.

Automated In Situ Seed Variety Identification via Deep Learning: A Case Study in Chickpea

On-time seed variety recognition is critical to limit qualitative and quantitative yield loss and asynchronous crop production. The conventional method is a subjective and error-prone process, since it relies on human experts and usually requires accredited seed material. This paper presents a convolutional neural network (CNN) framework for automatic identification of chickpea varieties by using seed images in the visible spectrum (400–700 nm). Two low-cost devices were employed for image acquisition. Lighting and imaging (background, focus, angle, and camera-to-sample distance) conditions were variable. The VGG16 architecture was modified by a global average pooling layer, dense layers, a batch normalization layer, and a dropout layer. Distinguishing the intricate visual features of the diverse chickpea varieties and recognizing them according to these features was conceivable by the obtained model. A five-fold cross-validation was performed to evaluate the uncertainty and predictive efficiency of the CNN model. The modified deep learning model was able to recognize different chickpea seed varieties with an average classification accuracy of over 94%. In addition, the proposed vision-based model was very robust in seed variety identification, and independent of image acquisition device, light environment, and imaging settings. This opens the avenue for the extension into novel applications using mobile phones to acquire and process information in situ. The proposed procedure derives possibilities for deployment in the seed industry and mobile applications for fast and robust automated seed identification practices.

In through the out door: Biochemical mechanisms affecting flavonoid glycoside catabolism in plants

Plants are the sole source of flavonoids, a chemical category that includes flavonols. For the most part, flavonols occur as glycosides with numerous postulated biological roles in plants, including photoprotection, modulation of hormone translocation, and sequestration of reactive oxygen species. Flavonol glycosides are often considered as dead-end metabolites because related flavonoids (i.e., anthocyanins) occur in terminal tissues such as flowers and fruit, but recent evidence points to their turnover in planta, including developing photosynthetic tissues. Although microbial degradation pathways for flavonol glycosides of plant origin are well described, plant catabolic pathways are little studied by comparison. This review will address our current understanding of biochemical processes leading to the loss of flavonol glycosides in plants, with a specific emphasis on the evidence for flavonol-specific β-glucosidases. Complete elucidation of these catabolic pathways is dependent on the identification of regiospecific modifying steps, including enzymes associated with the hydrolysis of rhamnosylated flavonols, as well as flavonol peroxidation and their encoding genes. Herein, we highlight challenges for the identification of hypothetical plant α-rhamnosidases and peroxidases involved in flavonol glycoside degradation, and the potential biological role of this catabolism in mitigating oxidative stress in developing and postharvest plant tissues.

Identification of the initial water-site and movement in Gleditsia sinensis seeds and its relation to seed coat structure

BACKGROUND

Water uptake is essential for seed germination. However, Gleditsia sinensis seeds have a water-impermeable seed coat, which is beneficial for its adaption to the environment, but prohibits its germination without treatment. This feature may be associated with the structure of the seed coat. Thus, the aim of this research was to identify and describe the initial water uptake site and water movement and to determine the relationship between seed coat structure and water absorption.

RESULTS

A water temperature of 80 °C was optimal to break the hardseededness of G. sinensis seeds. Scanning electron microscopy (SEM) images revealed that the seed coat consisted of a palisade layer and light line that can hinder water entry into the seed. Also, a structure of vascular bundles existed in the hilar region. Hot water treatment caused the tightly closed micropyle to open and the cavity beneath it expanded; the layer of palisade cells in the lens was raised. The embryo dye-tracking tests showed that the radicle tip was the initial region to be stained red. After staining for 24 h, the red-stained area on the vascular bundle side of cotyledon was more extensive than that on the other side. Further studies by MRI maps indicated that the micropyle was the initial site for water imbibition. Some water then migrated along the space between the seed coat and the endosperm to the chalazal; simultaneously, the rest of the water reached the embryonic axis and spread into cotyledons. The maps of 20-24 h showed that water was unevenly distributed within the cotyledons in a way that the edge parts were more hydrated than the center. Blocking tests showed that the hilar region was the initial and an important region during seed imbibition. The medial region and chalazal portion were capable of imbibing water when the hilar region was blocked, but water absorption was later and slower than that through the hilar region.

CONCLUSION

MRI technology provides a promising and non-invasive technique to identify the water gap and the path of water movement in the seed. Combined with the results of SEM, the relation between seed coat and its imbibition can be inferred.

Recent developments and potential of robotics in plant eco-phenotyping

Automated acquisition of plant eco-phenotypic information can serve as a decision-making basis for precision agricultural management and can also provide detailed insights into plant growth status, pest management, water and fertilizer management for plant breeders and plant physiologists. Because the microscopic components and macroscopic morphology of plants will be affected by the ecological environment, research on plant eco-phenotyping is more meaningful than the study of single-plant phenotyping. To achieve high-throughput acquisition of phenotyping information, the combination of high-precision sensors and intelligent robotic platforms have become an emerging research focus. Robotic platforms and automated systems are the important carriers of phenotyping monitoring sensors that enable large-scale screening. Through the diverse design and flexible systems, an efficient operation can be achieved across a range of experimental and field platforms. The combination of robot technology and plant phenotyping monitoring tools provides the data to inform novel artificial intelligence (AI) approaches that will provide steppingstones for new research breakthroughs. Therefore, this article introduces robotics and eco-phenotyping and examines research significant to this novel domain of plant eco-phenotyping. Given the monitoring scenarios of phenotyping information at different scales, the used intelligent robot technology, efficient automation platform, and advanced sensor equipment are summarized in detail. We further discuss the challenges posed to current research as well as the future developmental trends in the application of robot technology and plant eco-phenotyping. These include the use of collected data for AI applications and high-bandwidth data transfer, and large well-structured (meta) data storage approaches in plant sciences and agriculture.

A device for the controlled cooling and freezing of excised plant specimens during magnetic resonance imaging

BACKGROUND

Investigating plant mechanisms to tolerate freezing temperatures is critical to developing crops with superior cold hardiness. However, the lack of imaging methods that allow the visualization of freezing events in complex plant tissues remains a key limitation. Magnetic resonance imaging (MRI) has been successfully used to study many different plant models, including the study of in vivo changes during freezing. However, despite its benefits and past successes, the use of MRI in plant sciences remains low, likely due to limited access, high costs, and associated engineering challenges, such as keeping samples frozen for cold hardiness studies. To address this latter need, a novel device for keeping plant specimens at freezing temperatures during MRI is described.

RESULTS

The device consists of commercial and custom parts. All custom parts were 3D printed and made available as open source to increase accessibility to research groups who wish to reproduce or iterate on this work. Calibration tests documented that, upon temperature equilibration for a given experimental temperature, conditions between the circulating coolant bath and inside the device seated within the bore of the magnet varied by less than 0.1 °C. The device was tested on plant material by imaging buds from Vaccinium macrocarpon in a small animal MRI system, at four temperatures, 20 °C, - 7 °C, - 14 °C, and -  21 °C. Results were compared to those obtained by independent controlled freezing test (CFT) evaluations. Non-damaging freezing events in inner bud structures were detected from the imaging data collected using this device, phenomena that are undetectable using CFT.

CONCLUSIONS

The use of this novel cooling and freezing device in conjunction with MRI facilitated the detection of freezing events in intact plant tissues through the observation of the presence and absence of water in liquid state. The device represents an important addition to plant imaging tools currently available to researchers. Furthermore, its open-source and customizable design ensures that it will be accessible to a wide range of researchers and applications.

A Mobile NMR Sensor and Relaxometric Method to Non-destructively Monitor Water and Dry Matter Content in Plants

Water content (WC) and dry matter content (DMC) are some of the most basic parameters to describe plant growth and yield, but are exceptionally difficult to measure non-invasively. Nuclear Magnetic Resonance (NMR) relaxometry may fill this methodological gap. It allows non-invasive detection of protons in liquids and solids, and on the basis of these measures, can be used to quantify liquid and dry matter contents of seeds and plants. Unfortunately, most existing NMR relaxometers are large, unwieldy and not suitable to measure intact plants or to be used under field conditions. In addition, currently the appropriate NMR relaxometric methods are poorly suited for non-expert use. We here present a novel approach to overcome these drawbacks. We demonstrate that a basic NMR relaxometer with the capability to accept intact plants, in combination with straightforward NMR and data processing methods, can be used as an NMR plant sensor to continuously, quantitatively and non-invasively monitor changes in WC and DMC. This can be done in vivo, in situ, and with high temporal resolution. The method is validated by showing that measured liquid and solid proton densities accurately reflect WC and DMC of reference samples. The NMR plant sensor is demonstrated in an experimental context by monitoring WC of rice leaves under osmotic stress, and by measuring the dynamics of water and dry matter accumulation during seed filling in a developing wheat ear. It is further demonstrated how the method can be used to estimate leaf water potential on the basis of changes in leaf water content.

Trehalose 6-phosphate promotes seed filling by activating auxin biosynthesis

Plants undergo several developmental transitions during their life cycle. One of these, the differentiation of the young embryo from a meristem-like structure into a highly specialized storage organ, is believed to be controlled by local connections between sugars and hormonal response systems. However, we know little about the regulatory networks underpinning the sugar-hormone interactions in developing seeds. By modulating the trehalose 6-phosphate (T6P) content in growing embryos of garden pea (Pisum sativum), we investigate here the role of this signaling sugar during the seed-filling process. Seeds deficient in T6P are compromised in size and starch production, resembling the wrinkled seeds studied by Gregor Mendel. We show also that T6P exerts these effects by stimulating the biosynthesis of the pivotal plant hormone, auxin. We found that T6P promotes the expression of the auxin biosynthesis gene TRYPTOPHAN AMINOTRANSFERASE RELATED2 (TAR2), and the resulting effect on auxin concentrations is required to mediate the T6P-induced activation of storage processes. Our results suggest that auxin acts downstream of T6P to facilitate seed filling, thereby providing a salient example of how a metabolic signal governs the hormonal control of an integral phase transition in a crop plant.

MRSI vs CEST MRI to understand tomato metabolism in ripening fruit: is there a better contrast?

Besides structural information, magnetic resonance imaging (MRI) is crucial to reveal the presence and gradients of metabolites in organs constituted of several tissues. In plant science, such knowledge is key to better understand fruit development and metabolism. Routine methods based on fixation for cytological studies or dissection for metabolite measurements induce biases and plant sample destruction. Magnetic resonance spectroscopy imaging (MSRI) leads to one NMR spectrum per pixel while chemical exchange saturation transfer (CEST) MRI allows mapping metabolites having exchangeable protons. As both methods present different advantages and drawbacks, we compared them to map metabolites in ripe tomato fruits. We demonstrated that MRSI was difficult to interpret due to large spatial chemical shift variations while CEST MRI produced promising image mapping of the main carbohydrates and amino acids. It showed that glucose/fructose was mostly located in the locular tissue, whereas glutamate/glutamine/GABA was found inside the columella.Graphical abstract.

High-Throughput Phenotyping of Morphological Seed and Fruit Characteristics Using X-Ray Computed Tomography

Traditional seed and fruit phenotyping are mainly accomplished by manual measurement or extraction of morphological properties from two-dimensional images. These methods are not only in low-throughput but also unable to collect their three-dimensional (3D) characteristics and internal morphology. X-ray computed tomography (CT) scanning, which provides a convenient means of non-destructively recording the external and internal 3D structures of seeds and fruits, offers a potential to overcome these limitations. However, the current CT equipment cannot be adopted to scan seeds and fruits with high throughput. And there is no specialized software for automatic extraction of phenotypes from CT images. Here, we introduced a high-throughput image acquisition approach by mounting a specially designed seed-fruit container onto the scanning bed. The corresponding 3D image analysis software, 3DPheno-Seed&Fruit, was created for automatic segmentation and rapid quantification of eight morphological phenotypes of internal and external compartments of seeds and fruits. 3DPheno-Seed&Fruit is a graphical user interface design and user-friendly software with an excellent phenotype result visualization function. We described the software in detail and benchmarked it based upon CT image analyses in seeds of soybean, wheat, peanut, pine nut, pistachio nut and dwarf Russian almond fruit. R 2 values between the extracted and manual measurements of seed length, width, thickness, and radius ranged from 0.80 to 0.96 for soybean and wheat. High correlations were found between the 2D (length, width, thickness, and radius) and 3D (volume and surface area) phenotypes for soybean. Overall, our methods provide robust and novel tools for phenotyping the morphological seed and fruit traits of various plant species, which could benefit crop breeding and functional genomics.

Phylogenetic Diversity and Physiological Roles of Plant Monovalent Cation/H+ Antiporters

The processes of plant nutrition, stress tolerance, plant growth, and development are strongly dependent on transport of mineral nutrients across cellular membranes. Plant membrane transporters are key components of these processes. Among various membrane transport proteins, the monovalent cation proton antiporter (CPA) superfamily mediates a broad range of physiological and developmental processes such as ion and pH homeostasis, development of reproductive organs, chloroplast operation, and plant adaptation to drought and salt stresses. CPA family includes plasma membrane-bound Na⁺/H⁺ exchanger (NhaP) and intracellular Na⁺/H⁺ exchanger NHE (NHX), K⁺ efflux antiporter (KEA), and cation/H⁺ exchanger (CHX) family proteins. In this review, we have completed the phylogenetic inventory of CPA transporters and undertaken a comprehensive evolutionary analysis of their development. Compared with previous studies, we have significantly extended the range of plant species, including green and red algae and Acrogymnospermae into phylogenetic analysis. Our data suggest that the multiplication and complexation of CPA isoforms during evolution is related to land colonisation by higher plants and associated with an increase of different tissue types and development of reproductive organs. The new data extended the number of clades for all groups of CPAs, including those for NhaP/SOS, NHE/NHX, KEA, and CHX. We also critically evaluate the latest findings on the biological role, physiological functions and regulation of CPA transporters in relation to their structure and phylogenetic position. In addition, the role of CPA members in plant tolerance to various abiotic stresses is summarized, and the future priority directions for CPA studies in plants are discussed.

A small-scale MRI scanner and complementary imaging method to visualize and quantify xylem embolism formation

Magnetic resonance imaging (MRI) is a useful tool to image xylem embolism formation in plants. MRI scanners configured to accept intact plants are rare and expensive. Here, we investigate if affordable small-scale, custom-built low-field MRI scanners would suffice for the purpose. A small-scale, C-shaped permanent magnet was paired with open, plane parallel imaging gradients. The setup was small enough to fit between leaves or branches and offered open access for plant stems of arbitrary length. To counter the two main drawbacks of the system, low signal to noise and reduced magnetic field homogeneity, a multi-spin echo (MSE) pulse sequence was implemented, allowing efficient signal acquisition and quantitative imaging of water content and T₂ signal relaxation. The system was tested visualizing embolism formation in Fagus sylvatica during bench dehydration. High-quality images of water content and T₂ were readily obtained, which could be utilized to detect the cavitation of vessels smaller than could be spatially resolved. A multiplication of both map types yielded images in which filled xylem appeared with even greater contrast. T₂ imaging with small-scale MRI devices allows straightforward visualization of the spatial and temporal dynamics of embolism formation and the derivation of vulnerability curves.

Precise Volumetric Measurements of Any Shaped Objects with a Novel Acoustic Volumeter

We introduce a novel technique to measure volumes of any shaped objects based on acoustic components. The focus is on small objects with rough surfaces, such as plant seeds. The method allows measurement of object volumes more than 1000 times smaller than the volume of the sensor chamber with both high precision and high accuracy. The method is fast, noninvasive, and easy to produce and use. The measurement principle is supported by theory, describing the behavior of the measured data for objects of known volumes in a range of 1 to 800 µL. In addition to single-frequency, we present frequency-dependent measurements that provide supplementary information about pores on the surface of a measured object, such as the total volume of pores and, in the case of cylindrical pores, their average radius-to-length ratio. We demonstrate the usefulness of the method for seed phenotyping by measuring the volume of irregularly shaped seeds and showing the ability to "look" under the husk and inside pores, which allows us to assess the true density of seeds.

Elucidating the ionic liquid distribution in monolithic SILP hydroformylation catalysts by magnetic resonance imaging

Monolithic silicon carbide supported ionic liquid-phase (SILP) Rh-catalysts have very recently been introduced for gas-phase hydroformylation as an important step toward industrial upscaling. This study investigates the monolithic catalyst system in combination with different impregnation procedures with non-invasive magnetic resonance imaging (MRI). The findings were supported by X-ray microtomography (micro-CT) data of the monolithic pore structure and a catalytic performance test of the catalyst system for 1-butene gas-phase hydroformylation. MRI confirmed a homogeneous impregnation of the liquid phase throughout the full cross-section of the cylindrical monoliths. Consistent impregnations from one side to the other of the monoliths were achieved with a stabilizer in the system that helped preventing inhomogeneous rim formation. External influences relevant for industrial application, such as long-term storage and temperature exposure, did not affect the homogeneous liquid-phase distribution of the catalyst. The work elucidates important parameters to improve liquid-phase catalyst impregnation to obtain efficient monolithic catalysts for industrial exploitation in gas-phase hydroformylation as well as other important industrial processes.

The action of the liquid catalyst phase in monolithic silicon carbide supported ionic liquid-phase (SILP) Rh-catalysts provide important insight toward industrial upscaling for gas-phase hydroformylation.

A Statistical Growth Property of Plant Root Architectures

Numerous types of biological branching networks, with varying shapes and sizes, are used to acquire and distribute resources. Here, we show that plant root and shoot architectures share a fundamental design property. We studied the spatial density function of plant architectures, which specifies the probability of finding a branch at each location in the 3-dimensional volume occupied by the plant. We analyzed 1645 root architectures from four species and discovered that the spatial density functions of all architectures are population-similar. This means that despite their apparent visual diversity, all of the roots studied share the same basic shape, aside from stretching and compression along orthogonal directions. Moreover, the spatial density of all architectures can be described as variations on a single underlying function: a Gaussian density truncated at a boundary of roughly three standard deviations. Thus, the root density of any architecture requires only four parameters to specify: the total mass of the architecture and the standard deviations of the Gaussian in the three (x, y, z) growth directions. Plant shoot architectures also follow this design form, suggesting that two basic plant transport systems may use similar growth strategies.

Applications of magnetic resonance imaging in chemical engineering

While there are many techniques to study phenomena that occur in chemical engineering applications, magnetic resonance imaging (MRI) receives increasing scientific interest. Its non-invasive nature and wealth of parameters with the ability to generate functional images and contrast favors the use of MRI for many purposes, in particular investigations of dynamic phenomena, since it is very sensitive to motion. Recent progress in flow-MRI has led to shorter acquisition times and enabled studies of transient phenomena. Reactive systems can easily be imaged if NMR parameters such as relaxation change along the reaction coordinate. Moreover, materials and devices can be examined, such as batteries by mapping the magnetic field around them.

Three-Dimensional Time-Lapse Analysis Reveals Multiscale Relationships in Maize Root Systems with Contrasting Architectures

Understanding how an organism's phenotypic traits are conditioned by genetic and environmental variation is a central goal of biology. Root systems are one of the most important but poorly understood aspects of plants, largely due to the three-dimensional (3D), dynamic, and multiscale phenotyping challenge they pose. A critical gap in our knowledge is how root systems build in complexity from a single primary root to a network of thousands of roots that collectively compete for ephemeral, heterogeneous soil resources. We used time-lapse 3D imaging and mathematical modeling to assess root system architectures (RSAs) of two maize (Zea mays) inbred genotypes and their hybrid as they grew in complexity from a few to many roots. Genetically driven differences in root branching zone size and lateral branching densities along a single root, combined with differences in peak growth rate and the relative allocation of carbon resources to new versus existing roots, manifest as sharply distinct global RSAs over time. The 3D imaging of mature field-grown root crowns showed that several genetic differences in seedling architectures could persist throughout development and across environments. This approach connects individual and system-wide scales of root growth dynamics, which could eventually be used to predict genetic variation for complex RSAs and their functions.

Structural and functional imaging of large and opaque plant specimens

Three- and four-dimensional imaging techniques are a prerequisite for spatially resolving the form-structure-function relationships in plants. However, choosing the right imaging method is a difficult and time-consuming process as the imaging principles, advantages and limitations, as well as the appropriate fields of application first need to be compared. The present study aims to provide an overview of three imaging methods that allow for imaging opaque, large and thick (>5 mm, up to several centimeters), hierarchically organized plant samples that can have complex geometries. We compare light microscopy of serial thin sections followed by 3D reconstruction (LMTS3D) as an optical imaging technique, micro-computed tomography (µ-CT) based on ionizing radiation, and magnetic resonance imaging (MRI) which uses the natural magnetic properties of a sample for image acquisition. We discuss the most important imaging principles, advantages, and limitations, and suggest fields of application for each imaging technique (LMTS, µ-CT, and MRI) with regard to static (at a given time; 3D) and dynamic (at different time points; quasi 4D) structural and functional plant imaging.

Magnetic resonance imaging suggests functional role of previous year vessels and fibres in ring-porous sap flow resumption

Reactivation of axial water flow in ring-porous species is a complex process related to stem water content and developmental stage of both earlywood-vessel and leaf formation. Yet empirical evidence with non-destructive methods on the dynamics of water flow resumption in relation to these mechanisms is lacking. Here we combined in vivo magnetic resonance imaging and wood-anatomical observations to monitor the dynamic changes in stem water content and flow during spring reactivation in 4-year-old pedunculate oaks (Quercus robur L.) saplings. We found that previous year latewood vessels and current year developing earlywood vessels form a functional unit for water flow during growth resumption. During spring reactivation, water flow shifted from latewood towards the new earlywood, paralleling the formation of earlywood vessels and leaves. At leaves' full expansion, volumetric water content of previous rings drastically decreased due to the near-absence of water in fibre tissue. We conclude (i) that in ring-porous oak, latewood vessels play an important hydraulic role for bridging the transition between old and new water-conducting vessels and (ii) that fibre and parenchyma provides a place for water storage.

Resolving Form–Structure–Function Relationships in Plants with MRI for Biomimetic Transfer

In many biomimetic approaches, a deep understanding of the form–structure–function relationships in living and functionally intact organisms, which act as biological role models, is essential. This knowledge is a prerequisite for the identification of parameters that are relevant for the desired technical transfer of working principles. Hence, non-invasive and non-destructive techniques for static (3D) and dynamic (4D) high-resolution plant imaging and analysis on multiple hierarchical levels become increasingly important. In this study we demonstrate that magnetic resonance imaging (MRI) can be used to resolve the plants inner tissue structuring and functioning on the example of four plant concept generators with sizes larger than 5 mm used in current biomimetic research projects: Dragon tree (Dracaena reflexa var. angustifolia), Venus flytrap (Dionaea muscipula), Sugar pine (Pinus lambertiana) and Chinese witch hazel (Hamamelis mollis). Two different MRI sequences were applied for high-resolution 3D imaging of the differing material composition (amount, distribution, and density of various tissues) and condition (hydrated, desiccated, and mechanically stressed) of the four model organisms. Main aim is to better understand their biomechanics, development, and kinematics. The results are used as inspiration for developing novel design and fabrication concepts for bio-inspired technical fiber-reinforced branchings and smart biomimetic actuators.

3D Morphological Processing for Wheat Spike Phenotypes Using Computed Tomography Images

Wheat is the main food crop today world-wide. In order to improve its yields, researchers are committed to understand the relationships between wheat genotypes and phenotypes. Compared to progressive technology of wheat gene section identification, wheat trait measurement is mostly done manually in a destructive, labor-intensive and time-consuming way. Therefore, this study will be greatly accelerated and promoted if we can automatically discover wheat phenotype in a nondestructive and fast manner. In this paper, we propose a novel pipeline based on 3D morphological processing to detect wheat spike grains and stem nodes from 3D X-ray micro computed tomography (CT) images. We also introduce a set of newly defined 3D phenotypes, including grain aspect ratio, porosity, Grain-to-Grain distance, and grain angle, which are very difficult to be manually measured. The analysis of the associations among these traits would be very helpful for wheat breeding. Experimental results show that our method is able to count grains more accurately than normal human performance. By analyzing the relationships between traits and environment conditions, we find that the Grain-to-Grain distance, aspect ratio and porosity are more likely affected by the genome than environment (only tested temperature and water conditions). We also find that close grains will inhibit grain volume growth and that the aspect ratio 3.5 may be the best for higher yield in wheat breeding.

Using Plant Phenomics to Exploit the Gains of Genomics

Agricultural scientists face the dual challenge of breeding input-responsive, widely adoptable and climate-resilient varieties of crop plants and developing such varieties at a faster pace. Integrating the gains of genomics with modern-day phenomics will lead to increased breeding efficiency which in turn offers great promise to develop such varieties rapidly. Plant phenotyping techniques have impressively evolved during the last two decades. The low-cost, automated and semi-automated methods for data acquisition, storage and analysis are now available which allow precise quantitative analysis of plant structure and function; and genetic dissection of complex traits. Appropriate plant types can now be quickly developed that respond favorably to low input and resource-limited environments and address the challenges of subsistence agriculture. The present review focuses on the need of systematic, rapid, minimal invasive and low-cost plant phenotyping. It also discusses its evolution to modern day high throughput phenotyping (HTP), traits amenable to HTP, integration of HTP with genomics and the scope of utilizing these tools for crop improvement.

A qualitative analysis of the bud ontogeny of Dracaena marginata using high-resolution magnetic resonance imaging

The development of the branch-stem-attachment of Dracaena marginata was analyzed to clarify how a load-adapted arrangement of mechanically relevant tissues, i.e. the vascular bundles with fiber caps, is established during ontogeny. For this purpose, 3D images of four intact and developing buds of D. marginata were repetitively acquired in vivo within the time span of 180 days using high-resolution magnetic resonance imaging, as this method allows for non-invasive and non-destructive image acquisition. This methodical approach enabled the classification of distinct ontogenetic stages revealing the complex ontogeny of the branch-stem-attachment in D. marginata and the establishment of a load-adapted tissue arrangement within the junction between branch and main stem. This further allows for a first biomimetic abstraction and the transfer into a technical implementation of the form-structure-function principles found in branchings in D. marginata.

Ice Nucleation Activity in Plants: The Distribution, Characterization, and Their Roles in Cold Hardiness Mechanisms

Control of freezing in plant tissues is a key issue in cold hardiness mechanisms. Yet freeze-regulation mechanisms remain mostly unexplored. Among them, ice nucleation activity (INA) is a primary factor involved in the initiation and regulation of freezing events in plant tissues, yet the details remain poorly understood. To address this, we developed a highly reproducible assay for determining plant tissue INA and noninvasive freeze visualization tools using MRI and infrared thermography. The results of visualization studies on plant freezing behaviors and INA survey of over 600 species tissues show that (1) freezing-sensitive plants tend to have low INA in their tissues (thus tend to transiently supercool), while wintering cold-hardy species have high INA in some specialized tissues; and (2) the high INA in cold-hardy tissues likely functions as a freezing sensor to initiate freezing at warm subzero temperatures at appropriate locations and timing, resulting in the induction of tissue-/species-specific freezing behaviors (e.g., extracellular freezing, extraorgan freezing) and the freezing order among tissues: from the primary freeze to the last tissue remaining unfrozen (likely INA level dependent). The spatiotemporal distributions of tissue INA, their characterization, and functional roles are detailed. INA assay principles, anti-nucleation activity (ANA), and freeze visualization tools are also described.