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Veins are a critical component of the plant growth and development system, playing an integral role in supporting and protecting leaves, as well as transporting water, nutrients, and photosynthetic products. A comprehensive understanding of the form and function of veins requires a dual approach that combines plant physiology with cutting-edge image recognition technology. The latest advancements in computer vision and machine learning have facilitated the creation of algorithms that can identify vein networks and explore their developmental progression. Here, we review the functional, environmental, and genetic factors associated with vein networks, along with the current status of research on image analysis. In addition, we discuss the methods of venous phenotype extraction and multi-omics association analysis using machine learning technology, which could provide a theoretical basis for improving crop productivity by optimizing the vein network architecture. [ABSTRACT FROM AUTHOR]

The leaf economic spectrum (LES) has been repeatedly verified with regional and global datasets. However, the LES of desert plants and its drivers has not been fully explored at the species level. In this study, we sampled three desert perennial plant species (Alhagi sparsifolia, Karelinia caspia, and Apocynum venetum) at three different geographical areas of distribution in Xinjiang, China, and measured 10 leaf economic traits to determine their strategy of resource utilization. The scores of the first axis from the principal component analysis of 10 leaf economic traits as a continuous variable define the LES. This study showed that the LES did exist in desert plants in this region. The leaf economic spectrum shifted from a more conservative strategy to a more acquisitive strategy with increasing contents of soil potassium (K) and the ratio of K to phosphorus. Except for the vein density of A. venetum, which quadratically correlated with LES, the vein density, distance between veins, and vein loopiness significantly positively correlated with the LES (p < 0.05), indicating a covariation and tradeoff relationship. The annual mean temperature was significantly negatively correlated with LES, while the annual mean precipitation (MAP) and the aridity index (AI), which was calculated by the ratio of MAP to potential evapotranspiration, significantly positively correlated with the LES. Of these, vein loopiness and AI were more effective at predicting the change in LES from anatomical and climatic perspectives owing to their high regression coefficients (R2). The findings of this study will substantially improve the understanding of the strategies of desert plants to utilize resources and predict the structure and function of ecosystems. [ABSTRACT FROM AUTHOR]

The leaf economic spectrum (LES) has been repeatedly verified with regional and global datasets. However, the LES of desert plants and its drivers has not been fully explored at the species level. In this study, we sampled three desert perennial plant species (Alhagi sparsifolia, Karelinia caspia, and Apocynum venetum) at three different geographical areas of distribution in Xinjiang, China, and measured 10 leaf economic traits to determine their strategy of resource utilization. The scores of the first axis from the principal component analysis of 10 leaf economic traits as a continuous variable define the LES. This study showed that the LES did exist in desert plants in this region. The leaf economic spectrum shifted from a more conservative strategy to a more acquisitive strategy with increasing contents of soil potassium (K) and the ratio of K to phosphorus. Except for the vein density of A. venetum, which quadratically correlated with LES, the vein density, distance between veins, and vein loopiness significantly positively correlated with the LES (p < 0.05), indicating a covariation and tradeoff relationship. The annual mean temperature was significantly negatively correlated with LES, while the annual mean precipitation (MAP) and the aridity index (AI), which was calculated by the ratio of MAP to potential evapotranspiration, significantly positively correlated with the LES. Of these, vein loopiness and AI were more effective at predicting the change in LES from anatomical and climatic perspectives owing to their high regression coefficients (R2). The findings of this study will substantially improve the understanding of the strategies of desert plants to utilize resources and predict the structure and function of ecosystems.

• Leaves of vascular plants use specific tissues to irrigate the lamina (veins) and to regulate water loss (stomata), to approach homeostasis in leaf hydration during photosynthesis. As both tissues come with attendant costs, it would be expected that the synthesis and spacing of leaf veins and stomata should be coordinated in a way that maximizes benefit to the plant. • We propose an innovative geoprocessing method based on image editing and a geographic information system to study the quantitative relationships between vein and stomatal spatial patterns on leaves collected from 31 angiosperm species from different biomes. • The number of stomata within each areole was linearly related to the length of the looping vein contour. As a consequence of the presence of free-ending veinlets, the minimum mean distance of stomata from the nearest veins was invariant with areole size in most of the species, and species with smaller distances carried a higher density of stomata. • Uniformity of spatial patterning was consistent within leaves and species. Our results demonstrate the existence of an optimal spatial organization of veins and stomata, and suggest their interplay as a key feature for achieving a constant mesophyll hydraulic resistance throughout the leaf. [ABSTRACT FROM AUTHOR]

The earliest considerations of the venous circulation of the leg and calf belong to DENTU. Then, BOURDERET and LEJARS described more detailed the morphology veins of the foot and impressed venous network of the leg, they called it "venous sandal". Much later, ANDER and VAN LIMBORGH fully presented their considerations on leg venous network, while trying to clarify issues on the communicating veins. In this paper the authors present their considerations on leg venous network, comparing them with the literature data and, particularly, making observations on the communicating veins and causal factors that facilitate the flow of blood return. [ABSTRACT FROM AUTHOR]

The growth and development of biological tissues and organs strongly depend on the requirements of their multiple functions. Plant veins yield efficient nutrient transport and withstand various external loads. Victoria cruziana , a tropical species of the Nymphaeaceae family of water lilies, has evolved a network of three-dimensional and rugged veins, which yields a superior load-bearing capacity. However, it remains elusive how biological and mechanical factors affect their unique vein layout. In this paper, we propose a multi-functional and large-scale topology optimization method to investigate the morphomechanics of Victoria cruziana veins, which optimizes both the structural stiffness and nutrient transport efficiency. Our results suggest that increasing the branching order of radial veins improves the efficiency of nutrient delivery, and the gradient variation of circumferential vein sizes significantly contributes to the stiffness of the leaf. In the present method, we also consider the optimization of the wall thickness and the maximum layout distance of circumferential veins. Furthermore, biomimetic leaves are fabricated by using the three-dimensional printing technique to verify our theoretical findings. This work not only gains insights into the morphomechanics of Victoria cruziana veins, but also helps the design of, for example, rib-reinforced shells, slabs and dome skeletons.

The data set contains images of leaf venation networks obtained from tree species in Malaysian Borneo. The data set contains 726 leaves from 295 species comprising 50 families, sampled from eight forest plots in Sabah. Image extents are approximately 1 × 1 cm, or 50 megapixels. All images contain a region of interest in which all veins have been hand traced. The complete data set includes over 30 billion pixels, of which more than 600 million have been validated by hand tracing. These images are suitable for morphological characterization of these species, as well as for training of machine‐learning algorithms that segment biological networks from images. Data are made available under the Open Data Commons Attribution License. You are free to copy, distribute, and use the database; to produce works from the database; and to modify, transform, and build upon the database. You must attribute any public use of the database, or works produced from the database, in the manner specified in the license. For any use or redistribution of the database, or works produced from it, you must make clear to others the license of the database and keep intact any notices on the original database. [ABSTRACT FROM AUTHOR]