X-ray computed tomography for 3D plant imaging

The hidden diversity of vascular patterns in flower heads

Vascular systems are intimately related to the shape and spatial arrangement of the plant organs they support. We investigate the largely unexplored association between spiral phyllotaxis and the vascular system in Asteraceae flower heads. We imaged heads of eight species using synchrotron-based X-ray micro-computed tomography and applied original virtual reality and haptic software to explore head vasculature in three dimensions. We then constructed a computational model to infer a plausible patterning mechanism. The vascular system in the head of the model plant Gerbera hybrida is qualitatively different from those of Bellis perennis and Helianthus annuus, characterized previously. Cirsium vulgare, Craspedia globosa, Echinacea purpurea, Echinops bannaticus, and Tanacetum vulgare represent variants of the Bellis and Helianthus systems. In each species, the layout of the main strands is stereotypical, but details vary. The observed vascular patterns can be generated by a common computational model with different parameter values. In spite of the observed differences of vascular systems in heads, they may be produced by a conserved mechanism. The diversity and irregularities of vasculature stand in contrast with the relative uniformity and regularity of phyllotactic patterns, confirming that phyllotaxis in heads is not driven by the vasculature.

Unravelling the internal connections of plants

This article is a Commentary on Owens et al. (2024), 243: 423–439.

Hypoxia in tomato (Solanum lycopersicum) fruit during ripening: Biophysical elucidation by a 3D reaction-diffusion model

Respiration provides energy, substrates, and precursors to support physiological changes of the fruit during climacteric ripening. A key substrate of respiration is oxygen that needs to be supplied to the fruit in a passive way by gas transfer from the environment. Oxygen gradients may develop within the fruit due to its bulky size and the dense fruit tissues, potentially creating hypoxia that may have a role in the spatial development of ripening. This study presents a 3D reaction-diffusion model using tomato (Solanum lycopersicum) fruit as a test subject, combining the multiscale fruit geometry generated from magnetic resonance imaging and microcomputed tomography with varying respiration kinetics and contrasting boundary resistances obtained through independent experiments. The model predicted low oxygen levels in locular tissue under atmospheric conditions, and the oxygen level was markedly lower upon scar occlusion, aligning with microsensor profiling results. The locular region was in a hypoxic state, leading to its low aerobic respiration with high CO2 accumulation by fermentative respiration, while the rest of the tissues remained well oxygenated. The model further revealed that the hypoxia is caused by a combination of diffusion resistances and respiration rates of the tissue. Collectively, this study reveals the existence of the respiratory gas gradients and its biophysical causes during tomato fruit ripening, providing richer information for future studies on localized endogenous ethylene biosynthesis and fruit ripening.

Noninvasive Abiotic Stress Phenotyping of Vascular Plant in Each Vegetative Organ View

The last decades have witnessed a rapid development of noninvasive plant phenotyping, capable of detecting plant stress scale levels from the subcellular to the whole population scale. However, even with such a broad range, most phenotyping objects are often just concerned with leaves. This review offers a unique perspective of noninvasive plant stress phenotyping from a multi-organ view. First, plant sensing and responding to abiotic stress from the diverse vegetative organs (leaves, stems, and roots) and the interplays between these vital components are analyzed. Then, the corresponding noninvasive optical phenotyping techniques are also provided, which can prompt the practical implementation of appropriate noninvasive phenotyping techniques for each organ. Furthermore, we explore methods for analyzing compound stress situations, as field conditions frequently encompass multiple abiotic stressors. Thus, our work goes beyond the conventional approach of focusing solely on individual plant organs. The novel insights of the multi-organ, noninvasive phenotyping study provide a reference for testing hypotheses concerning the intricate dynamics of plant stress responses, as well as the potential interactive effects among various stressors.

Modeling lignin biosynthesis: a pathway to renewable chemicals

Plant biomass contains lignin that can be converted into high-value-added chemicals, fuels, and materials. The precise genetic manipulation of lignin content and composition in plant cells offers substantial environmental and economic benefits. However, the intricate regulatory mechanisms governing lignin formation challenge the development of crops with specific lignin profiles. Mathematical models and computational simulations have recently been employed to gain fundamental understanding of the metabolism of lignin and related phenolic compounds. This review article discusses the strategies used for modeling plant metabolic networks, focusing on the application of mathematical modeling for flux network analysis in monolignol biosynthesis. Furthermore, we highlight how current challenges might be overcome to optimize the use of metabolic modeling approaches for developing lignin-engineered plants.

The fertility tracks of pollen tube in the ovary of Solanum nigrum by three-dimensional reconstruction

In this paper, we present an enhanced method for automatically capturing a large number of consecutive paraffin sections using a microscope. Leveraging these microstructural images, we employed three-dimensional visualisation and reconstruction techniques to investigate the dispersal growth process of pollen tube bundles upon entering the ovary of Solanum nigrum. Additionally, we explored their behaviour within different ovules and examined the relationship between the germination rate of seeds and the fertilisation process. Our findings reveal that despite the abundance of Solanum nigrum seeds, only a fraction of them is capable of successful germination. The germination rate of seeds is closely related to whether fertilisation of the ovules and pollen tubes is completed. Due to the limited number of pollen tubes entering the ovary, only a portion of the ovules can be fertilised. The proportion of fertilised ovules positively correlates with the germination rate of the seeds. Through three-dimensional reconstruction, we observed a phenomenon of proximity during the pollination process, wherein ovules closer to the pollen tube bundles are more likely to be fertilised. Furthermore, fertilised ovules exhibited significant changes in morphology and embryo sac structure. The number of fertilised ovules directly impacts the germination rate of wild Solanum nigrum seeds. Although all Solanum nigrum ovules have the potential to develop into seeds, most seeds originating from unfertilised ovules are unable to germinate normally, resulting in an incomplete germination rate of seeds and preventing it from reaching 100%.

Automatic 3D cell segmentation of fruit parenchyma tissue from X-ray micro CT images using deep learning

BACKGROUND

High quality 3D information of the microscopic plant tissue morphology-the spatial organization of cells and intercellular spaces in tissues-helps in understanding physiological processes in a wide variety of plants and tissues. X-ray micro-CT is a valuable tool that is becoming increasingly available in plant research to obtain 3D microstructural information of the intercellular pore space and individual pore sizes and shapes of tissues. However, individual cell morphology is difficult to retrieve from micro-CT as cells cannot be segmented properly due to negligible density differences at cell-to-cell interfaces. To address this, deep learning-based models were trained and tested to segment individual cells using X-ray micro-CT images of parenchyma tissue samples from apple and pear fruit with different cell and porosity characteristics.

RESULTS

The best segmentation model achieved an Aggregated Jaccard Index (AJI) of 0.86 and 0.73 for apple and pear tissue, respectively, which is an improvement over the current benchmark method that achieved AJIs of 0.73 and 0.67. Furthermore, the neural network was able to detect other plant tissue structures such as vascular bundles and stone cell clusters (brachysclereids), of which the latter were shown to strongly influence the spatial organization of pear cells. Based on the AJIs, apple tissue was found to be easier to segment, as the porosity and specific surface area of the pore space are higher and lower, respectively, compared to pear tissue. Moreover, samples with lower pore network connectivity, proved very difficult to segment.

CONCLUSIONS

The proposed method can be used to automatically quantify 3D cell morphology of plant tissue from micro-CT instead of opting for laborious manual annotations or less accurate segmentation approaches. In case fruit tissue porosity or pore network connectivity is too low or the specific surface area of the pore space too high, native X-ray micro-CT is unable to provide proper marker points of cell outlines, and one should rely on more elaborate contrast-enhancing scan protocols.

OPIA: an open archive of plant images and related phenotypic traits

High-throughput plant phenotype acquisition technologies have been extensively utilized in plant phenomics studies, leading to vast quantities of images and image-based phenotypic traits (i-traits) that are critically essential for accelerating germplasm screening, plant diseases identification and biotic & abiotic stress classification. Here, we present the Open Plant Image Archive (OPIA, https://ngdc.cncb.ac.cn/opia/), an open archive of plant images and i-traits derived from high-throughput phenotyping platforms. Currently, OPIA houses 56 datasets across 11 plants, comprising a total of 566 225 images with 2 417 186 labeled instances. Notably, it incorporates 56 i-traits of 93 rice and 105 wheat cultivars based on 18 644 individual RGB images, and these i-traits are further annotated based on the Plant Phenotype and Trait Ontology (PPTO) and cross-linked with GWAS Atlas. Additionally, each dataset in OPIA is assigned an evaluation score that takes account of image data volume, image resolution, and the number of labeled instances. More importantly, OPIA is equipped with useful tools for online image pre-processing and intelligent prediction. Collectively, OPIA provides open access to valuable datasets, pre-trained models, and phenotypic traits across diverse plants and thus bears great potential to play a crucial role in facilitating artificial intelligence-assisted breeding research.

Orchid fruit and root movement analyzed using 2D photographs and a bioinformatics pipeline for processing sequential 3D scans

Premise

Most studies of the movement of orchid fruits and roots during plant development have focused on morphological observations; however, further genetic analysis is required to understand the molecular mechanisms underlying this phenomenon. A precise tool is required to observe these movements and harvest tissue at the correct position and time for transcriptomics research.

Methods

We utilized three-dimensional (3D) micro-computed tomography (CT) scans to capture the movement of fast-growing Erycina pusilla roots, and built an integrated bioinformatics pipeline to process 3D images into 3D time-lapse videos. To record the movement of slowly developing E. pusilla and Phalaenopsis equestris fruits, two-dimensional (2D) photographs were used.

Results

The E. pusilla roots twisted and resupinated multiple times from early development. The first period occurred in the early developmental stage (77-84 days after germination [DAG]) and the subsequent period occurred later in development (140-154 DAG). While E. pusilla fruits twisted 45° from 56-63 days after pollination (DAP), the fruits of P. equestris only began to resupinate a week before dehiscence (133 DAP) and ended a week after dehiscence (161 DAP).

Discussion

Our methods revealed that each orchid root and fruit had an independent direction and degree of torsion from the initial to the final position. Our innovative approaches produced detailed spatial and temporal information on the resupination of roots and fruits during orchid development.

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.

Spatio-temporal dynamics of the metabolome of climacteric fruit during ripening and post-harvest storage

Fruit quality traits are determined to a large extent by their metabolome. The metabolite content of climacteric fruit changes drastically during ripening and post-harvest storage, and has been investigated extensively. However, the spatial distribution of metabolites and how it changes in time has received much less attention as fruit are usually considered as homogenous plant organs. Yet, spatio-temporal changes of starch, which is hydrolyzed during ripening, has been used for a long time as a ripening index. As vascular transport of water, and hence convective transport of metabolites, slows down in mature fruit and even stalls after detachment, spatio-temporal changes in their concentration are probably affected by diffusive transport of gaseous molecules that act as substrate (O2), inhibitor (CO2), or regulator (ethylene and NO) of the metabolic pathways that are active during climacteric ripening. In this review, we discuss such spatio-temporal changes of the metabolome and how they are affected by transport of metabolic gases and gaseous hormones. As there are currently no techniques available to measure the metabolite distribution repeatedly by non-destructive means, we introduce reaction-diffusion models as an in silico tool to compute it. We show how the different components of such a model can be integrated and used to better understand the role of spatio-temporal changes of the metabolome in ripening and post-harvest storage of climacteric fruit that is detached from the plant, and discuss future research needs.

Cavity and entrance pore development in ant plant hypocotyls

Some genera of Rubiaceae in South-eastern Asia are known as typical ant plants. They have large domatia, which form in well-developed hypocotyls in which ants nest. Previously, cavity formation processes were described; however, these reports were dependent on tissue sections of different individuals of different ages. No continuous time-course analyses were done because cavity formation occurs inside the thick tissues of highly swollen domatia. Here we observed cavity formation processes in ant plants by using X-ray computed tomography (CT) imaging and revealed previously overlooked features of cavity formation. Firstly, the cavity pore occurs at the hypocotyl base in not only gravity-dependent but also basal position-dependent manner. Secondly, the cavity forms prior to the start of short tunnel formation between the cavity and the pore. The cavity axis is parallel to the longitudinal axis of the hypocotyl; however, the short tunnel axis between the pore and cavity depends on gravity. Non-invasive CT scanning is a very powerful method to analyze deeply hidden morphogenic processes in organs.

A maceration technique for soft plant tissue without hazardous chemicals

Premise

Current methods for maceration of plant tissue use hazardous chemicals. The new method described here improves the safety of dissection and maceration of soft plant tissues for microscopic imaging by using the harmless enzyme pectinase.

Methods and Results

Leaf material from a variety of land plants was obtained from living plants and dried herbarium specimens. Concentrations of aqueous pectinase and soaking schedules were optimized, and tissues were manually dissected while submerged in fresh solution following a soaking period. Most leaves required 2-4 h of soaking; however, delicate leaves could be macerated after 30 min while tougher leaves required 12 h to 3 days of soaking. Staining techniques can also be used with this method, and permanent or semi-permanent slides can be prepared. The epidermis, vascular tissue, and individual cells were imaged at magnifications of 10× to 400×. Only basic safety precautions were needed.

Conclusions

This pectinase method is a cost-effective and safe way to obtain images of epidermal peels, separated tissues, or isolated cells from a wide range of plant taxa.

Terahertz Constant Velocity Flying Spot for 3D Tomographic Imaging

This work reports on a terahertz tomography technique using constant velocity flying spot scanning as illumination. This technique is essentially based on the combination of a hyperspectral thermoconverter and an infrared camera used as a sensor, a source of terahertz radiation held on a translation scanner, and a vial of hydroalcoholic gel used as a sample and mounted on a rotating stage for the measurement of its absorbance at several angular positions. From the projections made in 2.5 h and expressed in terms of sinograms, the 3D volume of the absorption coefficient of the vial is reconstructed by a back-projection method based on the inverse Radon transform. This result confirms that this technique is usable on samples of complex and nonaxisymmetric shapes; moreover, it allows 3D qualitative chemical information with a possible phase separation in the terahertz spectral range to be obtained in heterogeneous and complex semitransparent media.

Applications of Microct Imaging to Archaeobotanical Research

The potential applications of microCT scanning in the field of archaeobotany are only just beginning to be explored. The imaging technique can extract new archaeobotanical information from existing archaeobotanical collections as well as create new archaeobotanical assemblages within ancient ceramics and other artefact types. The technique could aid in answering archaeobotanical questions about the early histories of some of the world's most important food crops from geographical regions with amongst the poorest rates of archaeobotanical preservation and where ancient plant exploitation remains poorly understood. This paper reviews current uses of microCT imaging in the investigation of archaeobotanical questions, as well as in cognate fields of geosciences, geoarchaeology, botany and palaeobotany. The technique has to date been used in a small number of novel methodological studies to extract internal anatomical morphologies and three-dimensional quantitative data from a range of food crops, which includes sexually-propagated cereals and legumes, and asexually-propagated underground storage organs (USOs). The large three-dimensional, digital datasets produced by microCT scanning have been shown to aid in taxonomic identification of archaeobotanical specimens, as well as robustly assess domestication status. In the future, as scanning technology, computer processing power and data storage capacities continue to improve, the possible applications of microCT scanning to archaeobotanical studies will only increase with the development of machine and deep learning networks enabling the automation of analyses of large archaeobotanical assemblages.

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.

Generating 3D Multispectral Point Clouds of Plants with Fusion of Snapshot Spectral and RGB-D Images

Accurate and high-throughput plant phenotyping is important for accelerating crop breeding. Spectral imaging that can acquire both spectral and spatial information of plants related to structural, biochemical, and physiological traits becomes one of the popular phenotyping techniques. However, close-range spectral imaging of plants could be highly affected by the complex plant structure and illumination conditions, which becomes one of the main challenges for close-range plant phenotyping. In this study, we proposed a new method for generating high-quality plant 3-dimensional multispectral point clouds. Speeded-Up Robust Features and Demons was used for fusing depth and snapshot spectral images acquired at close range. A reflectance correction method for plant spectral images based on hemisphere references combined with artificial neural network was developed for eliminating the illumination effects. The proposed Speeded-Up Robust Features and Demons achieved an average structural similarity index measure of 0.931, outperforming the classic approaches with an average structural similarity index measure of 0.889 in RGB and snapshot spectral image registration. The distribution of digital number values of the references at different positions and orientations was simulated using artificial neural network with the determination coefficient (R ²) of 0.962 and root mean squared error of 0.036. Compared with the ground truth measured by ASD spectrometer, the average root mean squared error of the reflectance spectra before and after reflectance correction at different leaf positions decreased by 78.0%. For the same leaf position, the average Euclidean distances between the multiview reflectance spectra decreased by 60.7%. Our results indicate that the proposed method achieves a good performance in generating plant 3-dimensional multispectral point clouds, which is promising for close-range plant phenotyping.

Automated extraction of pod phenotype data from micro-computed tomography

INTRODUCTION

Plant image datasets have the potential to greatly improve our understanding of the phenotypic response of plants to environmental and genetic factors. However, manual data extraction from such datasets are known to be time-consuming and resource intensive. Therefore, the development of efficient and reliable machine learning methods for extracting phenotype data from plant imagery is crucial.

METHODS

In this paper, a current gold standard computed vision method for detecting and segmenting objects in three-dimensional imagery (StartDist-3D) is applied to X-ray micro-computed tomography scans of oilseed rape (Brassica napus) mature pods.

RESULTS

With a relatively minimal training effort, this fine-tuned StarDist-3D model accurately detected (Validation F1-score = 96.3%,Testing F1-score = 99.3%) and predicted the shape (mean matched score = 90%) of seeds.

DISCUSSION

This method then allowed rapid extraction of data on the number, size, shape, seed spacing and seed location in specific valves that can be integrated into models of plant development or crop yield. Additionally, the fine-tuned StarDist-3D provides an efficient way to create a dataset of segmented images of individual seeds that could be used to further explore the factors affecting seed development, abortion and maturation synchrony within the pod. There is also potential for the fine-tuned Stardist-3D method to be applied to imagery of seeds from other plant species, as well as imagery of similarly shaped plant structures such as beans or wheat grains, provided the structures targeted for detection and segmentation can be described as star-convex polygons.

Genetic improvement toward nitrogen-use efficiency in rice: Lessons and perspectives

The indispensable role of nitrogen fertilizer in ensuring world food security together with the severe threats it poses to the ecosystem makes the usage of nitrogen fertilizer a major challenge for sustainable agriculture. Genetic improvement of crops with high nitrogen-use efficiency (NUE) is one of the most feasible solutions for tackling this challenge. In the last two decades, extensive efforts toward dissecting the variation of NUE-related traits and the underlying genetic basis in different germplasms have been made, and a series of achievements have been obtained in crops, especially in rice. Here, we summarize the approaches used for genetic dissection of NUE and the functions of the causal genes in modulating NUE as well as their applications in NUE improvement in rice. Strategies for exploring the variants controlling NUE and breeding future crops with "less-input-more-output" for sustainable agriculture are also proposed.

Imaging tools for plant nanobiotechnology

The successful application of nanobiotechnology in biomedicine has greatly changed the traditional way of diagnosis and treating of disease, and is promising for revolutionizing the traditional plant nanobiotechnology. Over the past few years, nanobiotechnology has increasingly expanded into plant research area. Nanomaterials can be designed as vectors for targeted delivery and controlled release of fertilizers, pesticides, herbicides, nucleotides, proteins, etc. Interestingly, nanomaterials with unique physical and chemical properties can directly affect plant growth and development; improve plant resistance to disease and stress; design as sensors in plant biology; and even be used for plant genetic engineering. Similarly, there have been concerns about the potential biological toxicity of nanomaterials. Selecting appropriate characterization methods will help understand how nanomaterials interact with plants and promote advances in plant nanobiotechnology. However, there are relatively few reviews of tools for characterizing nanomaterials in plant nanobiotechnology. In this review, we present relevant imaging tools that have been used in plant nanobiotechnology to monitor nanomaterial migration, interaction with and internalization into plants at three-dimensional lengths. Including: 1) Migration of nanomaterial into plant organs 2) Penetration of nanomaterial into plant tissues (iii)Internalization of nanomaterials by plant cells and interactions with plant subcellular structures. We compare the advantages and disadvantages of current characterization tools and propose future optimal characterization methods for plant nanobiotechnology.

A non-destructive coconut fruit and seed traits extraction method based on Micro-CT and deeplabV3+ model

With the completion of the coconut gene map and the gradual improvement of related molecular biology tools, molecular marker-assisted breeding of coconut has become the next focus of coconut breeding, and accurate coconut phenotypic traits measurement will provide technical support for screening and identifying the correspondence between genotype and phenotype. A Micro-CT system was developed to measure coconut fruits and seeds automatically and nondestructively to acquire the 3D model and phenotyping traits. A deeplabv3+ model with an Xception backbone was used to segment the sectional image of coconut fruits and seeds automatically. Compared with the structural-light system measurement, the mean absolute percentage error of the fruit volume and surface area measurements by the Micro-CT system was 1.87% and 2.24%, respectively, and the squares of the correlation coefficients were 0.977 and 0.964, respectively. In addition, compared with the manual measurements, the mean absolute percentage error of the automatic copra weight and total biomass measurements was 8.85% and 25.19%, respectively, and the adjusted squares of the correlation coefficients were 0.922 and 0.721, respectively. The Micro-CT system can nondestructively obtain up to 21 agronomic traits and 57 digital traits precisely.

Proximal and remote sensing in plant phenomics: 20 years of progress, challenges, and perspectives

Plant phenomics (PP) has been recognized as a bottleneck in studying the interactions of genomics and environment on plants, limiting the progress of smart breeding and precise cultivation. High-throughput plant phenotyping is challenging owing to the spatio-temporal dynamics of traits. Proximal and remote sensing (PRS) techniques are increasingly used for plant phenotyping because of their advantages in multi-dimensional data acquisition and analysis. Substantial progress of PRS applications in PP has been observed over the last two decades and is analyzed here from an interdisciplinary perspective based on 2972 publications. This progress covers most aspects of PRS application in PP, including patterns of global spatial distribution and temporal dynamics, specific PRS technologies, phenotypic research fields, working environments, species, and traits. Subsequently, we demonstrate how to link PRS to multi-omics studies, including how to achieve multi-dimensional PRS data acquisition and processing, how to systematically integrate all kinds of phenotypic information and derive phenotypic knowledge with biological significance, and how to link PP to multi-omics association analysis. Finally, we identify three future perspectives for PRS-based PP: (1) strengthening the spatial and temporal consistency of PRS data, (2) exploring novel phenotypic traits, and (3) facilitating multi-omics communication.

Computer-aided food engineering

Computer-aided food engineering (CAFE) can reduce resource use in product, process and equipment development, improve time-to-market performance, and drive high-level innovation in food safety and quality. Yet, CAFE is challenged by the complexity and variability of food composition and structure, by the transformations food undergoes during processing and the limited availability of comprehensive mechanistic frameworks describing those transformations. Here we introduce frameworks to model food processes and predict physiochemical properties that will accelerate CAFE. We review how investments in open access, such as code sharing, and capacity-building through specialized courses could facilitate the use of CAFE in the transformation already underway in digital food systems.

Risk factors associated with radiolucent foreign body inhalation in adults: a 10-year retrospective cohort study

BACKGROUND

Foreign body aspiration (FBA) is a serious condition with high morbidity and mortality rates. Although chest radiography is generally the first radiologic modality used in diagnosis, a substantial percentage of foreign bodies are radiolucent in adults with diagnosis challenging.

METHODS

Retrospective review of adult patients with FBA diagnosed by flexible electronic bronchoscopy from 2012 to 2022 collecting demographics, history, hospital presentation, radiographic, and operative details. Risk factors associated with radiolucent foreign body inhalation in adults were explored using appropriate statistical methods.

RESULTS

Between 1 January 2012 and 1 January 2022, 114 adult patients diagnosed with FBA were enrolled. The median age of participants was 65 years (IQR 52-74). Multidetector computed tomography (MDCT) examinations identified 28 cases (25%) showing direct visualization of the foreign body (defined as the radiopaque group) and 86 cases (75%) in the radiolucent group. Multivariable stepwise linear regression analysis showed increased odds of radiolucent foreign body inhalation in adults associated with pneumonic patches in MDCT (OR 6.99; 95% CI 1.80-27.22; P = 0.005) and plants/meat foreign bodies (OR 6.17; 95% CI 1.12-33.96; P = 0.04). A witnessed choking history (OR 0.02; 95% CI 0-0.14; P < 0.001) was a protective factor of radiolucent foreign body inhalation in adults.

CONCLUSIONS

Unlike radiopaque FBA, in those presenting with a suspected radiolucent foreign body aspiration, the diagnosis is far more challenging. Risk factors such as lacking a choking history, non-resolving pneumonia (pneumonic patches) in MDCT findings, and plants/meat foreign bodies may help in the early diagnosis of radiolucent foreign body inhalation in adults. Further prospective multicenter studies should be conducted to validate the findings.

Mechanical damages and packaging methods along the fresh fruit supply chain: A review

Mechanical damage of fresh fruit occurs throughout the postharvest supply chain leading to poor consumer acceptance and marketability. In this review, the mechanisms of damage development are discussed first. Mathematical modeling provides advanced ways to describe and predict the deformation of fruit with arbitrary geometry, which is important to understand their mechanical responses to external forces. Also, the effects of damage at the cellular and molecular levels are discussed as this provides insight into fruit physiological responses to damage. Next, direct measurement methods for damage including manual evaluation, optical detection, magnetic resonance imaging, and X-ray computed tomography are examined, as well as indirect methods based on physiochemical indexes. Also, methods to measure fruit susceptibility to mechanical damage based on the bruise threshold and the amount of damage per unit of impact energy are reviewed. Further, commonly used external and interior packaging and their applications in reducing damage are summarized, and a recent biomimetic approach for designing novel lightweight packaging inspired by the fruit pericarp. Finally, future research directions are provided.HIGHLIGHTSMathematical modeling has been increasingly used to calculate damage to fruit.Cell and molecular mechanisms response to fruit damage is an under-explored area.Susceptibility measurement of different mechanical forces has received attention.Customized design of reusable and biodegradable packaging is a hot topic of research.

Leaf microscopy applications in photosynthesis research: identifying the gaps

Leaf imaging via microscopy has provided critical insights into research on photosynthesis at multiple junctures, from the early understanding of the role of stomata, through elucidating C4 photosynthesis via Kranz anatomy and chloroplast arrangement in single cells, to detailed explorations of diffusion pathways and light utilization gradients within leaves. In recent decades, the original two-dimensional (2D) explorations have begun to be visualized in three-dimensional (3D) space, revising our understanding of structure-function relationships between internal leaf anatomy and photosynthesis. In particular, advancing new technologies and analyses are providing fresh insight into the relationship between leaf cellular components and improving the ability to model net carbon fixation, water use efficiency, and metabolite turnover rate in leaves. While ground-breaking developments in imaging tools and techniques have expanded our knowledge of leaf 3D structure via high-resolution 3D and time-series images, there is a growing need for more in vivo imaging as well as metabolite imaging. However, these advances necessitate further improvement in microscopy sciences to overcome the unique challenges a green leaf poses. In this review, we discuss the available tools, techniques, challenges, and gaps for efficient in vivo leaf 3D imaging, as well as innovations to overcome these difficulties.

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.

Applications of hyperspectral imaging in plant phenotyping

Our ability to interrogate and manipulate the genome far exceeds our capacity to measure the effects of genetic changes on plant traits. Much effort has been made recently by the plant science research community to address this imbalance. The responses of plants to environmental conditions can now be defined using a variety of imaging approaches. Hyperspectral imaging (HSI) has emerged as a promising approach to measure traits using a wide range of wavebands simultaneously in 3D to capture information in lab, glasshouse, or field settings. HSI has been applied to define abiotic, biotic, and quality traits for optimisation of crop management.

Preparation of a gold@europium-based coordination polymer nanocomposite with excellent photothermal properties and its potential for four-mode imaging

A nanocomposite was synthesized by replacing the toxic CTAB on the surface of GNRs with a europium-based hyaluronic acid coordination polymer. The nanocomposite exhibits excellent photothermal performance and also has potential for four-mode imaging.

Microstructural changes enhance oxygen transport in tomato (Solanum lycopersicum) fruit during maturation and ripening

Climacteric ripening of tomato fruit is initiated by a characteristic surge of the production rate of ethylene, accompanied by an increase in respiration rate. As both activities consume O₂ and produce CO₂ , gas concentration gradients develop in the fruit that cause diffusive transport. This may, in turn, affect respiration and ethylene biosynthesis. Gas diffusion in fruit depends on the amount and connectivity of cells and intercellular spaces in 3D. We investigated micromorphological changes in different tomato tissues during development and ripening by visualizing cells and pores based on high-resolution micro-computed tomography, and computed effective O₂ diffusivity coefficients based on microstructural features of the tissues. We demonstrated that mesocarp and septa tissues have larger cells but small and more disconnected pores than the placenta and columella, resulting in relatively lower effective O₂ diffusivity coefficients. Cell disintegration occurred in the mesocarp and septa during ripening, indicating lysigenous air pore formation and resulting in a gradual increase of the effective O₂ diffusivity. The results suggest that hypoxic conditions caused by the increasing size and, hence, diffusion resistance of the growing fruit may induce an increase of tissue porosity that results in a greatly enhanced O₂ diffusivity and, thus, helps to alleviate them.