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1.
Science ; 372(6540)2021 04 23.
Artigo em Inglês | MEDLINE | ID: mdl-33888615

RESUMO

Plants constantly experience fluctuating internal and external mechanical cues, ranging from nanoscale deformation of wall components, cell growth variability, nutating stems, and fluttering leaves to stem flexion under tree weight and wind drag. Developing plants use such fluctuations to monitor and channel their own shape and growth through a form of proprioception. Fluctuations in mechanical cues may also be actively enhanced, producing oscillating behaviors in tissues. For example, proprioception through leaf nastic movements may promote organ flattening. We propose that fluctuation-enhanced proprioception allows plant organs to sense their own shapes and behave like active materials with adaptable outputs to face variable environments, whether internal or external. Because certain shapes are more amenable to fluctuations, proprioception may also help plant shapes to reach self-organized criticality to support such adaptability.


Assuntos
Desenvolvimento Vegetal , Fenômenos Fisiológicos Vegetais , Plantas/anatomia & histologia , Arabidopsis/anatomia & histologia , Arabidopsis/crescimento & desenvolvimento , Arabidopsis/fisiologia , Sinais (Psicologia) , Citoesqueleto/ultraestrutura , Morfogênese , Movimento , Epiderme Vegetal/citologia , Epiderme Vegetal/ultraestrutura , Folhas de Planta/anatomia & histologia , Folhas de Planta/crescimento & desenvolvimento , Folhas de Planta/fisiologia , Caules de Planta/anatomia & histologia , Caules de Planta/crescimento & desenvolvimento , Caules de Planta/fisiologia , Estresse Mecânico , Tropismo
2.
Methods Mol Biol ; 2222: 1-38, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33301085

RESUMO

Taxonomy is the science that explores, describes, names, and classifies all organisms. In this introductory chapter, we highlight the major historical steps in the elaboration of this science, which provides baseline data for all fields of biology and plays a vital role for society but is also an independent, complex, and sound hypothesis-driven scientific discipline.In a first part, we underline that plant taxonomy is one of the earliest scientific disciplines that emerged thousands of years ago, even before the important contributions of the Greeks and Romans (e.g., Theophrastus, Pliny the Elder, and Dioscorides). In the fifteenth-sixteenth centuries, plant taxonomy benefited from the Great Navigations, the invention of the printing press, the creation of botanic gardens, and the use of the drying technique to preserve plant specimens. In parallel with the growing body of morpho-anatomical data, subsequent major steps in the history of plant taxonomy include the emergence of the concept of natural classification , the adoption of the binomial naming system (with the major role of Linnaeus) and other universal rules for the naming of plants, the formulation of the principle of subordination of characters, and the advent of the evolutionary thought. More recently, the cladistic theory (initiated by Hennig) and the rapid advances in DNA technologies allowed to infer phylogenies and to propose true natural, genealogy-based classifications.In a second part, we put the emphasis on the challenges that plant taxonomy faces nowadays. The still very incomplete taxonomic knowledge of the worldwide flora (the so-called taxonomic impediment) is seriously hampering conservation efforts that are especially crucial as biodiversity has entered its sixth extinction crisis. It appears mainly due to insufficient funding, lack of taxonomic expertise, and lack of communication and coordination. We then review recent initiatives to overcome these limitations and to anticipate how taxonomy should and could evolve. In particular, the use of molecular data has been era-splitting for taxonomy and may allow an accelerated pace of species discovery. We examine both strengths and limitations of such techniques in comparison to morphology-based investigations, we give broad recommendations on the use of molecular tools for plant taxonomy, and we highlight the need for an integrative taxonomy based on evidence from multiple sources.


Assuntos
Plantas/classificação , Biodiversidade , Evolução Biológica , Código de Barras de DNA Taxonômico , Fenótipo , Plantas/anatomia & histologia
3.
Plant Physiol Biochem ; 159: 100-112, 2021 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-33359959

RESUMO

At the dawn of the industrial revolution, the exorbitant use of heavy metals and toxic elements by mankind unfurls a powerful and complex web of hazard all around the world that significantly contributed to unprecedented trends in environmental degradation. Plants as sessile organisms, that cannot escape from the stress directly, have adapted to this environment via concurrent configurations of several traits. Among them the anatomy has been identified as much more advanced field of research that brought the explosion of interest among the expertise and its prodigious importance in stress physiology is unavoidable. In conjunction with various other disciplines, like physiology, biochemistry, genomics and metabolomics, the plant anatomy provides a large data sets that are paving the way towards a comprehensive and holistic understanding of plant growth, development, defense and productivity under heavy metal and toxic element stress. Present paper advances our recent knowledge about structural alterations of plant tissues induced by metals and metalloids, like antimony (Sb), arsenic (As), aluminium (Al), copper (Cu), cadmium (Cd), chromium (Cr), lead (Pb), manganese (Mn), mercury (Hg), nickel (Ni) and zinc (Zn) and points on essential role of plant anatomy and its understanding for plant growth and development in changing environment. Understanding of anatomical adaptations of various plant organs and tissues to heavy metals and metalloids could greatly contribute to integral and modern approach for investigation of plants in changing environmental conditions. These findings are necessary for understanding of the whole spectra of physiological and biochemical reactions in plants and to maintain the crop productivity worldwide. Moreover, our holistic perception regarding the processes underlying the plant responses to metal(loids) at anatomical level are needed for improving crop management and breeding techniques.


Assuntos
Exposição Ambiental , Metaloides , Metais Pesados , Plantas , Metaloides/toxicidade , Metais Pesados/toxicidade , Organogênese Vegetal/efeitos dos fármacos , Plantas/anatomia & histologia , Plantas/efeitos dos fármacos
4.
BMC Bioinformatics ; 21(1): 576, 2020 Dec 14.
Artigo em Inglês | MEDLINE | ID: mdl-33317442

RESUMO

BACKGROUND: Digital plant images are becoming increasingly important. First, given a large number of images deep learning algorithms can be trained to automatically identify plants. Second, structured image-based observations provide information about plant morphological characteristics. Finally in the course of digitalization, digital plant collections receive more and more interest in schools and universities. RESULTS: We developed a freely available mobile application called Flora Capture allowing users to collect series of plant images from predefined perspectives. These images, together with accompanying metadata, are transferred to a central project server where each observation is reviewed and validated by a team of botanical experts. Currently, more than 4800 plant species, naturally occurring in the Central European region, are covered by the application. More than 200,000 images, depicting more than 1700 plant species, have been collected by thousands of users since the initial app release in 2016. CONCLUSION: Flora Capture allows experts, laymen and citizen scientists to collect a digital herbarium and share structured multi-modal observations of plants. Collected images contribute, e.g., to the training of plant identification algorithms, but also suit educational purposes. Additionally, presence records collected with each observation allow contribute to verifiable records of plant occurrences across the world.


Assuntos
Plantas/anatomia & histologia , Software , Flores/anatomia & histologia , Processamento de Imagem Assistida por Computador , Redes Neurais de Computação
5.
PLoS One ; 15(12): e0243923, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33332382

RESUMO

A lack of sufficient training data, both in terms of variety and quantity, is often the bottleneck in the development of machine learning (ML) applications in any domain. For agricultural applications, ML-based models designed to perform tasks such as autonomous plant classification will typically be coupled to just one or perhaps a few plant species. As a consequence, each crop-specific task is very likely to require its own specialized training data, and the question of how to serve this need for data now often overshadows the more routine exercise of actually training such models. To tackle this problem, we have developed an embedded robotic system to automatically generate and label large datasets of plant images for ML applications in agriculture. The system can image plants from virtually any angle, thereby ensuring a wide variety of data; and with an imaging rate of up to one image per second, it can produce lableled datasets on the scale of thousands to tens of thousands of images per day. As such, this system offers an important alternative to time- and cost-intensive methods of manual generation and labeling. Furthermore, the use of a uniform background made of blue keying fabric enables additional image processing techniques such as background replacement and image segementation. It also helps in the training process, essentially forcing the model to focus on the plant features and eliminating random correlations. To demonstrate the capabilities of our system, we generated a dataset of over 34,000 labeled images, with which we trained an ML-model to distinguish grasses from non-grasses in test data from a variety of sources. We now plan to generate much larger datasets of Canadian crop plants and weeds that will be made publicly available in the hope of further enabling ML applications in the agriculture sector.


Assuntos
Agricultura/classificação , Aprendizado Profundo , Processamento de Imagem Assistida por Computador , Plantas/classificação , Algoritmos , Canadá , Humanos , Aprendizado de Máquina , Desenvolvimento Vegetal , Plantas/anatomia & histologia
6.
Nat Commun ; 11(1): 4519, 2020 09 09.
Artigo em Inglês | MEDLINE | ID: mdl-32908150

RESUMO

The leaf economics spectrum (LES) describes consistent correlations among a variety of leaf traits that reflect a gradient from conservative to acquisitive plant strategies. So far, whether the LES holds in wetland plants at a global scale has been unclear. Using data on 365 wetland species from 151 studies, we find that wetland plants in general show a shift within trait space along the same common slope as observed in non-wetland plants, with lower leaf mass per area, higher leaf nitrogen and phosphorus, faster photosynthetic rates, and shorter leaf life span compared to non-wetland plants. We conclude that wetland plants tend to cluster at the acquisitive end of the LES. The presented global quantifications of the LES in wetland plants enhance our understanding of wetland plant strategies in terms of resources acquisition and allocation, and provide a stepping-stone to developing trait-based approaches for wetland ecology.


Assuntos
Fotossíntese/genética , Folhas de Planta/genética , Plantas/genética , Áreas Alagadas , Nitrogênio/análise , Fósforo/análise , Folhas de Planta/anatomia & histologia , Folhas de Planta/química , Plantas/anatomia & histologia , Plantas/metabolismo
7.
PLoS One ; 15(9): e0239588, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32966345

RESUMO

Despite a growing body of evidence concerning accelerated organic degradation at archaeological sites, there have been few follow-up investigations to examine the status of the remaining archaeological materials in the ground. To address the question of archaeo-organic preservation, we revisited the Swedish, Mesolithic key-site Ageröd and could show that the bone material had been subjected to an accelerated deterioration during the last 75 years, which had destroyed the bones in the areas where they had previously been best preserved. To understand why this has happened and to quantify and qualify the extent of the organic degradation, we here analyse the soil chemistry, bone histology, collagen preservation and palaeobotany at the site. Our results show that the soil at Ageröd is losing, or has already lost, its preservative and buffering qualities, and that pH-values in the still wet areas of the site have dropped to levels where no bone preservation is possible. Our results suggest that this acidification process is enhanced by the release of sulphuric acid as pyrite in the bones oxidizes. While we are still able to find well-preserved palaeobotanical remains, they are also starting to corrode through re-introduced oxygen into the archaeological layers. While some areas of the site have been more protected through redeposited soil on top of the archaeological layers, all areas of Ageröd are rapidly deteriorating. Lastly, while it is still possible to perform molecular analyses on the best-preserved bones from the most protected areas, this opportunity will likely be lost within a few decades. In conclusion, we find that if we, as a society, wish to keep this valuable climatic, environmental and cultural archive, both at Ageröd and elsewhere, the time to act is now and if we wait we will soon be in a situation where this record will be irretrievably lost forever.


Assuntos
Arqueologia/métodos , Fósseis/história , Animais , Osso e Ossos/anatomia & histologia , Osso e Ossos/química , Botânica , Colágeno/análise , Conservação dos Recursos Naturais/métodos , Características Culturais/história , Fósseis/anatomia & histologia , História Antiga , Paleontologia , Plantas/anatomia & histologia , Preservação Biológica/história , Datação Radiométrica , Solo/química , Suécia , Áreas Alagadas
8.
PLoS Biol ; 18(8): e3000843, 2020 08.
Artigo em Inglês | MEDLINE | ID: mdl-32866143

RESUMO

Interactions between species generate the functions on which ecosystems and humans depend. However, we lack an understanding of the risk that interaction loss poses to ecological communities. Here, we quantify the risk of interaction loss for 4,330 species interactions from 41 empirical pollination and seed dispersal networks across 6 continents. We estimate risk as a function of interaction vulnerability to extinction (likelihood of loss) and contribution to network feasibility, a measure of how much an interaction helps a community tolerate environmental perturbations. Remarkably, we find that more vulnerable interactions have higher contributions to network feasibility. Furthermore, interactions tend to have more similar vulnerability and contribution to feasibility across networks than expected by chance, suggesting that vulnerability and feasibility contribution may be intrinsic properties of interactions, rather than only a function of ecological context. These results may provide a starting point for prioritising interactions for conservation in species interaction networks in the future.


Assuntos
Biota , Simbiose , Animais , Estudos de Viabilidade , Plantas/anatomia & histologia , Risco , Especificidade da Espécie
9.
PLoS One ; 15(8): e0237645, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32814345

RESUMO

In this research, an efficient scheme to identify leaf types is proposed. In that scheme, the leaf boundary points are fitted in a continuous contour using Radial Basis Function Neural Networks (RBFNN) to calculate the centroid of the leaf shape. Afterwards, the distances between predetermined points and the centroid were computed and normalized. In addition, the time complexity of the features' extraction algorithm was calculated. The merit of this scheme is objects' independence to translation, rotation and scaling. Moreover, different classification techniques were evaluated against the leaf shape features. Those techniques included two of the most commonly used classification methods; RBFNN and SVM that were evaluated and compared with other researches that used complex features extraction algorithms with much higher dimensionality. Furthermore, a third classification method with an optimization technique for the SVM using Salp Swarm Algorithm (SSA) was utilized showing a significant improvement over RBFNN and SVM.


Assuntos
Algoritmos , Redes Neurais de Computação , Folhas de Planta/anatomia & histologia , Plantas/anatomia & histologia , Plantas/classificação , Máquina de Vetores de Suporte
10.
Neurology ; 95(12): 532-536, 2020 09 22.
Artigo em Inglês | MEDLINE | ID: mdl-32759198

RESUMO

Medicine and botany are 2 distinct disciplines of "natural science," one focusing on humans, the other on plants. However, among the life sciences, both were quite close in earlier times. Moreover, the history of neuropathology, especially in the field of the peripheral nervous system, has been marked by many examples of "botanical images" used to describe certain histopathologic structures. We propose to better understand the reasons why neuropathologists used these botanical terms from a number of interesting anecdotes.


Assuntos
Botânica , Microscopia/história , Patologia/história , Sistema Nervoso Periférico/anatomia & histologia , História do Século XVI , História do Século XVII , História do Século XVIII , História do Século XIX , História do Século XX , História do Século XXI , Humanos , Plantas/anatomia & histologia
11.
Nat Commun ; 11(1): 2999, 2020 06 12.
Artigo em Inglês | MEDLINE | ID: mdl-32532992

RESUMO

Recent studies show coordinated relationships between plant leaf traits and their capacity to predict ecosystem functions. However, how leaf traits will change within species and whether interspecific trait relationships will shift under future environmental changes both remain unclear. Here, we examine the bivariate correlations between leaf economic traits of 515 species in 210 experiments which mimic climate warming, drought, elevated CO2, and nitrogen deposition. We find divergent directions of changes in trait-pairs between species, and the directions mostly do not follow the interspecific trait relationships. However, the slopes in the logarithmic transformed interspecific trait relationships hold stable under environmental changes, while only their elevations vary. The elevation changes of trait relationship are mainly driven by asymmetrically interspecific responses contrary to the direction of the leaf economic spectrum. These findings suggest robust interspecific trait relationships under global changes, and call for linking within-species responses to interspecific coordination of plant traits.


Assuntos
Mudança Climática , Ecossistema , Aquecimento Global , Folhas de Planta/metabolismo , Plantas/metabolismo , Algoritmos , Dióxido de Carbono/metabolismo , Secas , Modelos Biológicos , Nitrogênio/metabolismo , Fenótipo , Folhas de Planta/anatomia & histologia , Plantas/anatomia & histologia , Plantas/classificação , Especificidade da Espécie
12.
Sensors (Basel) ; 20(4)2020 Feb 19.
Artigo em Inglês | MEDLINE | ID: mdl-32093006

RESUMO

Hyperspectral imaging techniques have been expanding considerably in recent years. The cost of current solutions is decreasing, but these high-end technologies are not yet available for moderate to low-cost outdoor and indoor applications. We have used some of the latest compressive sensing methods with a single-pixel imaging setup. Projected patterns were generated on Fourier basis, which is well-known for its properties and reduction of acquisition and calculation times. A low-cost, moderate-flow prototype was developed and studied in the laboratory, which has made it possible to obtain metrologically validated reflectance measurements using a minimal computational workload. From these measurements, it was possible to discriminate plant species from the rest of a scene and to identify biologically contrasted areas within a leaf. This prototype gives access to easy-to-use phenotyping and teaching tools at very low-cost.


Assuntos
Custos e Análise de Custo , Imageamento Tridimensional , Plantas/anatomia & histologia , Análise Espectral , Hydrangea/anatomia & histologia , Fenótipo , Folhas de Planta/anatomia & histologia
13.
Sensors (Basel) ; 20(3)2020 Feb 10.
Artigo em Inglês | MEDLINE | ID: mdl-32050619

RESUMO

Comprehensive and accurate vegetation monitoring is required in forestry and agricultural applications. The optical remote sensing method could be a solution. However, the traditional light detection and ranging (LiDAR) scans a surface to create point clouds and provide only 3D-state information. Active laser-induced fluorescence (LIF) only measures the photosynthesis and biochemical status of vegetation and lacks information about spatial structures. In this work, we present a new Multi-Wavelength Fluorescence LiDAR (MWFL) system. The system extended the multi-channel fluorescence detection of LIF on the basis of the LiDAR scanning and ranging mechanism. Based on the principle prototype of the MWFL system, we carried out vegetation-monitoring experiments in the laboratory. The results showed that MWFL simultaneously acquires the 3D spatial structure and physiological states for precision vegetation monitoring. Laboratory experiments on interior scenes verified the system's performance. Fluorescence point cloud classification results were evaluated at four wavelengths and by comparing them with normal vectors, to assess the MWFL system capabilities. The overall classification accuracy and Kappa coefficient increased from 70.7% and 0.17 at the single wavelength to 88.9% and 0.75 at four wavelengths. The overall classification accuracy and Kappa coefficient improved from 76.2% and 0.29 at the normal vectors to 92.5% and 0.84 at the normal vectors with four wavelengths. The study demonstrated that active 3D fluorescence imaging of vegetation based on the MWFL system has a great application potential in the field of remote sensing detection and vegetation monitoring.


Assuntos
Imageamento Tridimensional , Luz , Plantas/anatomia & histologia , Fluorescência , Lasers , Folhas de Planta/anatomia & histologia , Folhas de Planta/fisiologia , Folhas de Planta/efeitos da radiação
14.
BMC Evol Biol ; 20(1): 19, 2020 02 04.
Artigo em Inglês | MEDLINE | ID: mdl-32019502

RESUMO

BACKGROUND: The evolution of the Jehol Biota of western Liaoning in China includes three phases, initiation in the Dabeigou phase, radiation in the Yixian phase, and decline in the Jiufotang phase. Numerous ephedroid macrofossils were reported from the Lower Cretaceous Yixian Formation. However, so far none has been found in the younger Jiufotang Formation (ca. 120.3 Ma) of western Liaoning. RESULTS: Here we report a new species Jianchangia verticillata gen. et sp. nov. with unusual morphology from the Lower Cretaceous of the Jiufotang Formation, Lamadong Village, Jianchang County, Liaoning. This species is the first record of gnetophytes from the Jiufotang Formation. It is similar to other ephedroid species from the Yixian Formation in possessing linear leaves with parallel veins, jointed shoots with swollen nodes and longitudinally furrowed internodes, and ovulate cones possessing two whorls of bracts enclosing two chlamydosperms, but differs from all known species by the ovulate cone having multiple fine linear verticillate bracts. CONCLUSIONS: This study expands our knowledge about the diversity of early gnetophytes in the Lower Cretaceous, and demonstrates the lineage continuity of gnetophytes from the Yixian Formation to the younger Jiufotang Formation.


Assuntos
Flores/anatomia & histologia , Fósseis , Plantas/anatomia & histologia , Animais , China , Ecossistema , Filogenia , Fatores de Tempo
15.
Biochem Soc Trans ; 48(1): 71-82, 2020 02 28.
Artigo em Inglês | MEDLINE | ID: mdl-31922184

RESUMO

Chloroplasts are photosynthetic plant organelles descended from a bacterial ancestor. The vast majority of chloroplast proteins are synthesized in the cytosol and then imported into the chloroplast post-translationally. Translocation complexes exist in the organelle's outer and inner envelope membranes (termed TOC and TIC, respectively) to facilitate protein import. These systems recognize chloroplast precursor proteins and mediate their import in an energy-dependent manner. However, many unanswered questions remain regarding mechanistic details of the import process and the participation and functions of individual components; for example, the cytosolic events that mediate protein delivery to chloroplasts, the composition of the TIC apparatus, and the nature of the protein import motor all require resolution. The flux of proteins through TOC and TIC varies greatly throughout development and in response to specific environmental cues. The import process is, therefore, tightly regulated, and it has emerged that the ubiquitin-proteasome system (UPS) plays a key role in this regard, acting at several different steps in the process. The UPS is involved in: the selective degradation of transcription factors that co-ordinate the expression of chloroplast precursor proteins; the removal of unimported chloroplast precursor proteins in the cytosol; the inhibition of chloroplast biogenesis pre-germination; and the reconfiguration of the TOC apparatus in response to developmental and environmental signals in a process termed chloroplast-associated protein degradation. In this review, we highlight recent advances in our understanding of protein import into chloroplasts and how this process is regulated by the UPS.


Assuntos
Cloroplastos/metabolismo , Complexo de Endopeptidases do Proteassoma/metabolismo , Transporte Proteico/fisiologia , Ubiquitina/metabolismo , Proteínas de Cloroplastos/metabolismo , Citosol/metabolismo , Organelas/metabolismo , Fotossíntese , Proteínas de Plantas/metabolismo , Plantas/anatomia & histologia , Plantas/metabolismo , Precursores de Proteínas/metabolismo , Proteólise
16.
Microsc Res Tech ; 83(4): 345-353, 2020 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-31789485

RESUMO

Recent field exploration and collections has led to the findings of several new species in Pakistan. Here we reported two new species Ajuga reptance L and Sphagneticola trilobata (L.) Prusk for the first time in Pakistan flora as these species were neither listed in any other literature nor identified before in Pakistan. These species were found as a result of taxonomic studies performed in the year 2019 in District Rawalpindi and Islamabad, Pakistan. Microscopic techniques were used for the confirmation of foliar epidermal and pollen micromorphological features. Detailed study (morphological, palynological, and foliar epidermal) was provided for the correct identification and delimitation of the species using both light and scanning electron microscopy. Morphological results were compared with the flora of Taiwan and China.


Assuntos
Ajuga/anatomia & histologia , Microscopia/métodos , Estômatos de Plantas/ultraestrutura , Plantas/anatomia & histologia , Pólen/ultraestrutura , Tricomas/ultraestrutura , China , Microscopia Eletrônica de Varredura , Paquistão , Plantas/classificação , Taiwan
17.
Comput Intell Neurosci ; 2019: 2015017, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31871441

RESUMO

Plant identification is a fine-grained classification task which aims to identify the family, genus, and species according to plant appearance features. Inspired by the hierarchical structure of taxonomic tree, the taxonomic loss was proposed, which could encode the hierarchical relationships among multilevel labels into the deep learning objective function by simple group and sum operation. By training various neural networks on PlantCLEF 2015 and PlantCLEF 2017 datasets, the experimental results demonstrated that the proposed loss function was easy to implement and outperformed the most commonly adopted cross-entropy loss. Eight neural networks were trained, respectively, by two different loss functions on PlantCLEF 2015 dataset, and the models trained by taxonomic loss led to significant performance improvements. On PlantCLEF 2017 dataset with 10,000 species, the SENet-154 model trained by taxonomic loss achieved the accuracies of 84.07%, 79.97%, and 73.61% at family, genus and species levels, which improved those of model trained by cross-entropy loss by 2.23%, 1.34%, and 1.08%, respectively. The taxonomic loss could further facilitate the fine-grained classification task with hierarchical labels.


Assuntos
Aprendizado Profundo , Plantas/classificação , Processamento de Imagem Assistida por Computador/métodos , Reconhecimento Automatizado de Padrão/métodos , Plantas/anatomia & histologia
18.
Biophys J ; 117(10): 1995-2004, 2019 11 19.
Artigo em Inglês | MEDLINE | ID: mdl-31727319

RESUMO

Plant organ outgrowth superficially appears like the continuous mechanical deformation of a sheet of cells. Yet, how precisely cells as individual mechanical entities can act to morph a tissue reliably and efficiently into three dimensions during outgrowth is still puzzling, especially when cells are tightly connected as in plant tissue. In plants, the mechanics of cells within a tissue is particularly well-defined because individual cell growth is essentially the mechanical yielding of the cell wall in response to internal turgor pressure. Cell-wall stiffness is controlled by biological signaling, which is impacted by stresses, and hence, cell growth is observed to respond to mechanical stresses building up within a tissue. What is the role of the mechanical feedback during morphing of tissue in three dimensions? Here, we develop a three-dimensional vertex model to investigate tissue mechanics at the onset of organ outgrowth at the tip of a plant shoot. We find that organ height is primarily governed by the ratio of growth rates of faster-growing cells initiating the organ versus slower-growing cells surrounding them. Remarkably, the outgrowth rate is higher when cell growth responds to the tissue-wide mechanical stresses. Our quantitative analysis of simulation data shows that tissue mechanical feedback on cell growth can act via a twofold mechanism. First, the feedback guides patterns of cellular growth. Second, the feedback modifies the stress patterns on the cells, consequently amplifying and propagating growth anisotropies. This mechanism may allow plants to grow organs efficiently out of the meristem by reorganizing the cellular growth rather than inflating growth rates.


Assuntos
Retroalimentação , Organogênese , Desenvolvimento Vegetal , Fenômenos Biomecânicos , Ácidos Indolacéticos/metabolismo , Meristema/crescimento & desenvolvimento , Plantas/anatomia & histologia , Estresse Fisiológico
19.
PLoS One ; 14(9): e0221203, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31568494

RESUMO

With the introduction of multi-camera systems in modern plant phenotyping new opportunities for combined multimodal image analysis emerge. Visible light (VIS), fluorescence (FLU) and near-infrared images enable scientists to study different plant traits based on optical appearance, biochemical composition and nutrition status. A straightforward analysis of high-throughput image data is hampered by a number of natural and technical factors including large variability of plant appearance, inhomogeneous illumination, shadows and reflections in the background regions. Consequently, automated segmentation of plant images represents a big challenge and often requires an extensive human-machine interaction. Combined analysis of different image modalities may enable automatisation of plant segmentation in "difficult" image modalities such as VIS images by utilising the results of segmentation of image modalities that exhibit higher contrast between plant and background, i.e. FLU images. For efficient segmentation and detection of diverse plant structures (i.e. leaf tips, flowers), image registration techniques based on feature point (FP) matching are of particular interest. However, finding reliable feature points and point pairs for differently structured plant species in multimodal images can be challenging. To address this task in a general manner, different feature point detectors should be considered. Here, a comparison of seven different feature point detectors for automated registration of VIS and FLU plant images is performed. Our experimental results show that straightforward image registration using FP detectors is prone to errors due to too large structural difference between FLU and VIS modalities. We show that structural image enhancement such as background filtering and edge image transformation significantly improves performance of FP algorithms. To overcome the limitations of single FP detectors, combination of different FP methods is suggested. We demonstrate application of our enhanced FP approach for automated registration of a large amount of FLU/VIS images of developing plant species acquired from high-throughput phenotyping experiments.


Assuntos
Processamento de Imagem Assistida por Computador/métodos , Plantas/anatomia & histologia , Algoritmos , Clorofila/metabolismo , Fluorescência , Humanos , Processamento de Imagem Assistida por Computador/estatística & dados numéricos , Iluminação , Fenótipo , Fotografação/métodos , Desenvolvimento Vegetal , Folhas de Planta/anatomia & histologia , Folhas de Planta/metabolismo , Plantas/metabolismo
20.
Plant Physiol ; 181(4): 1425-1440, 2019 12.
Artigo em Inglês | MEDLINE | ID: mdl-31591152

RESUMO

Developing automated methods to efficiently process large volumes of point cloud data remains a challenge for three-dimensional (3D) plant phenotyping applications. Here, we describe the development of machine learning methods to tackle three primary challenges in plant phenotyping: lamina/stem classification, lamina counting, and stem skeletonization. For classification, we assessed and validated the accuracy of our methods on a dataset of 54 3D shoot architectures, representing multiple growth conditions and developmental time points for two Solanaceous species, tomato (Solanum lycopersicum cv 75 m82D) and Nicotiana benthamiana Using deep learning, we classified lamina versus stems with 97.8% accuracy. Critically, we also demonstrated the robustness of our method to growth conditions and species that have not been trained on, which is important in practical applications but is often untested. For lamina counting, we developed an enhanced region-growing algorithm to reduce oversegmentation; this method achieved 86.6% accuracy, outperforming prior methods developed for this problem. Finally, for stem skeletonization, we developed an enhanced tip detection technique, which ran an order of magnitude faster and generated more precise skeleton architectures than prior methods. Overall, our improvements enable higher throughput and accurate extraction of phenotypic properties from 3D point cloud data.


Assuntos
Imageamento Tridimensional , Aprendizado de Máquina , Plantas/anatomia & histologia , Algoritmos , Meio Ambiente , Lycopersicon esculentum/anatomia & histologia , Fenótipo , Folhas de Planta/anatomia & histologia , Raízes de Plantas/anatomia & histologia , Brotos de Planta/anatomia & histologia , Caules de Planta/anatomia & histologia , Reprodutibilidade dos Testes , Tabaco/anatomia & histologia
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