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(a) Construction of a Fibonacci spiral. The Fibonacci spiral is observed in sea shells of the species Argonauta argo (b) as well as in the growth of some species of ferns (c).
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Modern methods of image analysis are based on the coordinates of the points making the silhouette of an image and allow the comparison between seed shape in different species and varieties. Nevertheless, these methods miss an important reference point because they do not take into consideration the similarity of seeds with geometrical figures. We p...
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... Morphological variation in seed shape can be due to either genetic or environmental factors [38]. As the grapevine is normally propagated by vegetative propagation using stem cuttings, among the genetic factors, both the genetic composition of the parental cultivars in the initial crosses and those that were the male parents for the current generation may have an influence on the final phenotype [12]. ...
Resolving the genetic relationships between cultivars is one of the objectives of research in viticulture. To this end, both DNA markers and morphological analysis help to identify synonyms and homonyms and to determine the degree of relatedness between cultivars. Results of genetic analysis using single sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs) point to Hebén as the female progenitor of many of the cultivars currently used in viticulture. Here, seed shape is compared between Hebén and genetically related cultivars. An average silhouette derived from seeds of Hebén was used as a model, and the comparisons were made visually and quantitatively by calculation of J-index values (percent similarity of the seeds and the model). Quantification of seed shape by J-index confirms the data of DNA markers supporting different levels of conservation of maternal seed shape in the varieties. Other seed morphological measurements help to explain the basis of the differences in shape between Hebén, genetically related groups and the external group of unrelated cultivars. Curvature analysis in seeds silhouettes confirms the relationship between Hebén and other cultivars and supports the utility of this technique in the analysis of parental relationships.
... It is presumably because shape variations were not too diverse. Cervantes and Gomez [40] stated that shape is the result of a plant growth process. In one individual plant, sometimes there are differences in the fruits or seeds shape caused by many factors. ...
Seed morphological characters assessed through morphometry, include both qualitative and quantitative parameters. These are crucial for supporting taxonomic identification and classification processes, as well as predicting traits related to seed dispersal strategies. This study aimed to identify the most influential morphometric characters for classifying seed types and their dispersal strategies. Seeds from 12 selected species, collected during a plant exploration at Bromo Tengger Semeru National Park (BTSNP), were analyzed. Measurements include seed length, width, thickness, weight, volume, and hilum size, along with observations of seed color, texture, and shape to calculate the Eccentricity Index (EI) and Flatness Index (FI). Data were analyzed using Principal Component Analysis (PCA) and cluster analysis in PAST ver.4.04. The results revealed two seed groupings of species associated with M. acuminata from BTSNP based on morphometric influences: Group I, influenced by weight, color, hilum size, shape, texture, and EI value; and Group II: influenced by length, width, thickness, volume, and FI value. Overall, quantitative characters were more influential than qualitative ones in identifying the seeds of the 12 species studied. Thus, numerical characters serve as valuable supporting features for species grouping. Additionally, most seeds from the 12 species are likely dispersed by animals.
... Digital morphometry of plants has recently been actively developed and used to solve the problems of studying the biological diversity, classification and taxonomy of plants and the search for genes controlling the size and shape of various plant organs [38][39][40][41][42]. To characterize the complex shapes of objects, methods based on landmarks [43], quantitative indices [44], numerical description of contour curves parametrically [45] and nonparametrically [46] and elliptic Fourier descriptors [47] are used. ...
The spike shape and morphometric characteristics are among the key characteristics of cultivated cereals, being associated with their productivity. These traits are often used for the plant taxonomy and authenticity of hexaploid wheat species. Manual measurement of spike characteristics is tedious and not precise. Recently, the authors of this study developed a method for wheat spike morphometry utilizing 2D image analysis. Here, this method is applied to study variations in spike size and shape for 190 plants of seven hexaploid (2n = 6x = 42) species and one artificial amphidiploid of wheat. Five manually estimated spike traits and 26 traits obtained from digital image analysis were analyzed. Image-based traits describe the characteristics of the base, center and apex of the spike and common parameters (circularity, roundness, perimeter, etc.). Estimates of similar traits by manual measurement and image analysis were shown to be highly correlated, suggesting the practical importance of digital spike phenotyping. The utility of spike traits for classification into types (spelt, normal and compact) and species or amphidiploid is shown. It is also demonstrated that the estimates obtained made it possible to identify the spike characteristics differing significantly between species or between accessions within the same species. The present work suggests the usefulness of wheat spike shape analysis using an approach based on characteristics obtained by digital image analysis.
... Shape-related phenotypes are dimensionless and insensitive to the seed size, which is important in seed species recognition and classification. The traditional manual measurement of seed geometric parameters is no longer suitable for the needs of smart agriculture [14,15]. Therefore, it is meaningful to explore a novel method of seed geometric parameters automatic measurement. ...
Seed geometric parameters are important in yielding trait scorers, quantitative trait loci, and species recognition and classification. A novel method for automatic measurement of three-dimensional seed phenotypes is proposed. First, a handheld three-dimensional (3D) laser scanner is employed to obtain the seed point cloud data in batches. Second, a novel point cloud-based phenotyping method is proposed to obtain a single-seed 3D model and extract 33 phenotypes. It is connected by an automatic pipeline, including single-seed segmentation, pose normalization, point cloud completion by an ellipse fitting method, Poisson surface reconstruction, and automatic trait estimation. Finally, two statistical models (one using 11 size-related phenotypes and the other using 22 shape-related phenotypes) based on the principal component analysis method are built. A total of 3400 samples of eight kinds of seeds with different geometrical shapes are tested. Experiments show: (1) a single-seed 3D model can be automatically obtained with 0.017 mm point cloud completion error; (2) 33 phenotypes can be automatically extracted with high correlation compared with manual measurements (correlation coefficient (R2) above 0.9981 for size-related phenotypes and R2 above 0.8421 for shape-related phenotypes); and (3) two statistical models are successfully built to achieve seed shape description and quantification.
... Legume seeds exhibit a diverse range of forms and sizes. The typical shapes of these obj ects are roughly spherical or ellipsoidal (Cervantes and Martín Gómez, 2019). Soybeans and peas exemplify legume seeds characterized by spherical and ellipso idal shapes. ...
Background: The advancements achieved in artificial intelligence (AI) technology in recent decades have not yet been equaled by agricultural phenotyping approaches that are both rapid and precise. Efficient crop phenotyping technologies are necessary to enhance crop improvement endeavors in order to fulfill the projected demand for food in future. Methods: This work demonstrates a method for non-destructive physiological state phenotyping of plants using cutting-edge image processing methods in conjunction with chlorophyll fluorescence imaging. Key fluorescence metrics, such as fv/fm and NPQ, were extracted from images taken at different phases of development via processing. In addition, this research explores the transformative role of automated image analysis in high-throughput phenotyping of legume traits. A comprehensive examination of recent studies reveals the diverse applications of machine learning and deep learning algorithms in capturing morphological traits, assessing physiological parameters, detecting stress and diseases in various legume species. The comparative analysis underscores the superiority of automated systems over traditional methods, emphasizing scalability and efficiency. Challenges, including algorithm sensitivity and environmental variability, are identified, urging further refinement. Recommendations advocate for standardized metrics, interdisciplinary collaborations and user-friendly platforms to enhance accessibility. As the field evolves, the integration of automated image analysis holds promise for revolutionizing legume phenotyping, accelerating crop improvement and contributing to global food security in sustainable agriculture. Result: The findings demonstrate that the proposed method is effective in illuminating how plants respond to their environment, hence promoting advancements in plant phenotyping and agricultural research
... In simpler terms, the mean represents the average color intensity, the standard deviation gauges the range of color intensities, and the skewness measures the tilt of the color distribution. Shape (10 features): This category includes geometric properties [58,59] of the seed such as its area, perimeter, convexity, solidity, minor and major axis lengths, orientation, eccentricity, circularity, and aspect ratio. The area measures the seed size, while the perimeter defines its boundary length. ...
Seed traits, such as seed color and seed size, directly impact seed quality, affecting the marketability and value of dry peas [1]. Assessing seed quality is integral to a plant breeding programs to ensure optimal seed standards. This research introduced a phenotyping tool to assess seed quality traits specifically tailored for pulse crops, which integrates image processing with cutting-edge deep learning models. The proposed method is designed for automation, seamlessly processing a sequence of images while minimizing human intervention. The pipeline standardized red-green-blue (RGB) images captured from a color light box and used deep learning models to segment and detect seed features. Our method extracted up to 86 distinct seed characteristics, ranging from basic size metrics to intricate texture details and color nuances. Compared to traditional methods, our pipeline demonstrated a 95 percent similarity in seed quality assessment and increased time efficiency (from 2 weeks to 30 minutes for processing time). Specifically, we observed an improvement in the accuracy of seed trait identification by simply using an RGB value instead of a categorical, non-standard description, which allowed for an increase in the range of detectable seed quality characteristics. By integrating conventional image processing techniques with foundational deep learning models, this approach emerges as a pivotal instrument in pulse breeding programs, guaranteeing the maintenance of superior seed quality standards.
... A quantitative method based on the comparison with geometric models has been applied to describe, quantify and compare seed shape in diverse families and species [32][33][34][35]. The application of this method to the seeds of the Cucurbitaceae showed the similarity that many seeds have with ellipses and ovoids [35] and gave quantifications of shape for some species. ...
... Bilateral symmetry of a seed was calculated based on the protocol to obtain J index. J index is the percentage of similarity between a plane figure of a seed and the corresponding geometric model [32][33][34][35]. The model used to calculate bilateral symmetry is the specular image of the seed silhouette obtained with the command reflect horizontally in Corel PhotoPaint ( Figure 2). ...
Quantitative morphological methods have been applied here to seed morphology in species representative of the Cucurbitaceae: Curvature analysis, symmetry analysis and the comparison with geometric models. The three methods were applied to the comparison of three species and two varieties of Cucumis, and the results indicate that both symmetry analysis and the comparison with geometric models can be useful for the identification and classification of species and varieties in Cucumis. Curvature analysis reveals differences between species of the Cucurbitaceae, and, together with other quantitative morphological measurements, like circularity, aspect ratio and solidity, may provide valuable information and be an interesting tool for taxonomy in this family.
... Variability in seed traits has been reported in different species, populations or individuals (see, e.g., Susko and Lovett-Doust, 2000;Lopez et al., 2008;Cervantes and Martín Gómez, 2019). Differences in seed (germination) traits among populations (i.e., within species) have been considered an effective evolutionary strategy that influence on species resilience by increasing the chances of reproduction under heterogeneous environmental conditions, thus minimizing the extinction risk (Venable and Brown, 1988). ...
Interpopulation variability in seed traits may drive the regeneration capacity of a species to colonize different environments. In the present study, we evaluated the variation in seed physical traits (mass / size, water imbibition, shape index) and physiological traits (germination) of five Polygonaceae species. Seeds of Polygonum lapathifolium var. salicifolium, P. lapathifolium, Reynoutria japonica, Rumex trisetifer, and R. obtusifolius were collected from two or three populations in Jiujiang, China. Physical seed traits were measured before germination tests conducted under different combinations of light and temperatures. Most species had a significant variation in seed physical and physiological traits, although populations are geographically close. Interpopulation variation in seed traits appeared to be species-specific, with the highest variation for R. japonica and lowest for R. trisetifer seeds. Germination response to temperature and light conditions also varied among species and populations, being mostly inhibited in the dark treatments. The light dependence of germination can be related to the small seed size, except for the round-seeded Rumex, depending on the temperature regime. Optimal temperature ranges mainly varied from 10/20°C to 25/35°C, with significant decreases in germination percentage at both coolest and warmest extremes. Germination requirements seem to be related to altitudinal gradients in populations of P. lapathifolium and R. japonica seeds.
... However, this effect was entirely dependent on correcting for a strong phylogenetic signal in shape and can most likely be explained by the positive correlation of the shape variable with seed length. Effects of seed shape could be further explored by analysing simulation data combined with other (geometric) descriptions of seed shape based on image processing systems (Cervantes et al. 2016, Cervantes andGómez 2019), although based on our current results we expect a stronger influence of traits other than seed shape. Seed hardness did have a clear positive effect on seed survival, but this disappeared after correcting for phylogenetic relationships. ...
Waterbirds disperse plant species via ingestion and egestion of seeds (endozoochory). However, our understanding about the regulating effects of seed traits, underlying mechanisms and possible (co)evolutionary processes is limited by our traditional reliance on data from feeding experiments with living waterbirds. Here, we overcome these limitations by developing and applying a new bioassay that realistically simulates digestive processes for Anseriformes waterbirds. We test three hypotheses: 1) seed survival and germination are most affected by mechanical digestion in the waterbird gizzard; 2) seed size, hardness, imbibition and shape regulate seed survival; and 3) plants growing in aquatic habitats benefit most from endozoochory by waterbirds. Experiments with 28 200 seeds of 48 plant species demonstrated species‐specific seed survival that was entirely determined by digestion in the avian gizzard. Intestinal digestion did not affect seed survival but affected seed establishment (germinability and germination time) for 21% of the species. Large, hard seeds survived the simulations the best, in contrast to generally higher seed survival for smaller seeds during in vivo experiments. This mechanistically explains that small seeds escape digestive processes rather than being inherently more resistant (the ‘escape mechanism'), while large seeds are retained until fully digested or regurgitated (the ‘resistance and regurgitation mechanism'). Plants growing in wetter habitats had similar seed survival, but digestive processes stimulated their germinability and accelerated their germination more than for terrestrial plants. This indicates a relative advantage of endozoochory for plant species growing in wet habitats, possibly reflecting a co‐evolutionary response related to dormancy breaking by gut passage. Simulating seed gut passage using a bioassay allowed establishing mechanisms and identifying relevant seed traits involved in seed dispersal by waterbirds. This information enhances our understanding of how animal species shape plant species distributions, which is extremely relevant now that current anthropogenic pressures already severely impact plant dispersal capacities.
... While seed shape usually remains relatively constant for each species, it can vary notably in some families. In certain plant families, like the Arecaceae and the Vitaceae [11,12], seeds resemble multiple types of geometric figures, while in others, a reduced number of morphological types are predominant, such as ellipses in the Campanulaceae [13] and Oleaceae [14], ovals in the Cucurbitaceae [15], Euphorbiaceae [16,17], and Rutaceae [13]. Seeds of the Caryophyllaceae present interesting features, with ovules hemianatropous to campylotropous [18][19][20], and the embryo corresponds to a peripheral type [21]. ...
... While seed shape usually remains relatively constant for each species, it can vary notably in some families. In certain plant families, like the Arecaceae and the Vitaceae [11,12], seeds resemble multiple types of geometric figures, while in others, a reduced number of morphological types are predominant, such as ellipses in the Campanulaceae [13] and Oleaceae [14], ovals in the Cucurbitaceae [15], Euphorbiaceae [16,17], and Rutaceae [13]. Seeds of the Caryophyllaceae present interesting features, with ovules hemianatropous to campylotropous [18][19][20], and the embryo corresponds to a peripheral type [21]. ...
... Seed shape quantification can be done by estimating the percentage surface shared between the seed image and a given model [13,25]. The resulting measurement has been termed the J index. ...
Historically, little attention has been paid to the resemblance between seed silhouettes to geometric figures. Cardioid and derivatives, ellipses, heart curves, lemniscates, lenses, lunes, ovals, superellipses, waterdrops, and other figures can be used to describe seed shape, as well as models for quantification. Algebraic expressions representing the average silhouettes for a group of seeds are available, and their shape can be described and quantified by comparison with geometric models. Bidimensional closed-plane figures resulting from the representation of Fourier equations can be used as models for shape analysis. Elliptic Fourier Transform equations reproduce the seed silhouettes for any closed-plane curve corresponding to the contour of the image of a seed. We review the geometric properties of the silhouettes from seed images and discuss them in the context of seed development, plant taxonomy, and environmental adaptation. Silene is proposed as a model for the study of seed morphology. Three groups have been recently defined among Silene species based on the structure of their seed silhouettes, and their geometric properties are discussed. Using models based on Fourier Transform equations is useful in Silene species where the seeds are homogenous in shape but don’t adjust to described figures.
