Morphological Descriptors Research Articles

Prevalence of African Mosaic and Morphological Characterization of Cassava (Manihot esculenta Cranz) Varieties in Two Agroecological Zones of Cameroon

The objective of this work is to conduct an epidemiological study of African cassava mosaic and to characterize the diversity of local cultivars in circulation in the monomodal and bimodal rainforest zones of Cameroon. Disease-related parameters (incidence and severity index) were studied as well as morphological parameters (plant height, leaflet color, petiole color, lobe length, number of lobes, number of branches, petiole length). The results show that 96 cassava varieties were identified with 89 local varieties and 07 improved varieties. Diseased plants showed a symptom severity index of 1 to 5, which could reduce production by half in the areas considered. The leaf color was dark green, the number of branches was 3, the lobe and petiole lengths were 16.46 and 22 cm respectively, while the number of lobes was 5 the disease incidence for the two agro-ecological zones as a whole is 57.58% for a symptom severity index of 3. The epidemiological study reveals that the desease incidence of both agro-ecological zones was 57.58 % for a symptom severity index of 2 corresponding to 40 %. In the humid forest zone with monomodal spray the average incidence was 49.74% and a leaf attack rate was 29.03 % in the locality of Njombé (Cameroon's littoral region). At Ekona in southwestern Cameroon, the average incidence was 63% and leaf attack index was 1 corresponding to 20 %. In the bimodal rainforest zone (central Cameroon region), the average incidence was 60 % for a leaf attack rate was 37.11%. The expected results highlight a relatively worrying situation. Principal Component Analysis (PCA) confirms the convergence of tolerance towards the mosaic and grouped the different varieties into more or less homogeneous groups according to the morphological and epidemiological cassava descriptors. The results of the present work show that the introduction of cassava local varieties tolerant to mosaic disease in middling could be an alternative for the control of the cassava mosaic disease.

Morphology of nanoporous glass: Stochastic 3D modeling, stereology and the influence of pore width

Excursion sets of Gaussian random fields are used to model the three-dimensional (3D) morphology of differently manufactured porous glasses (PGs), which vary with respect to their mean pore widths measured by mercury intrusion porosimetry. The stochastic 3D model is calibrated by means of volume fractions and two-point coverage probability functions estimated from tomographic image data. Model validation is performed by comparing model realizations and image data in terms of morphological descriptors which are not used for model fitting. For this purpose, we consider mean geodesic tortuosity and constrictivity of the pore space, quantifying the length of the shortest transportation paths and the strength of bottleneck effects, respectively. Additionally, a stereological approach for parameter estimation is presented, i.e., the 3D model is calibrated using merely two-dimensional (2D) cross-sections of the 3D image data. Doing so, on average, a comparable goodness of fit is achieved as well. The variance of the calibrated model parameters is discussed, which is estimated on the basis of randomly chosen, individual 2D cross-sections. Moreover, interpolating between the model parameters calibrated to differently manufactured glasses enables the predictive simulation of virtual but realistic PGs with mean pore widths that have not yet been manufactured. The predictive power is demonstrated by means of cross-validation. Using the presented approach, relationships between parameters of the manufacturing process and descriptors of the resulting morphology of PGs are quantified, which opens possibilities for an efficient optimization of the underlying manufacturing process. Published by the American Physical Society 2024

Analysis of Fennel Breeding Populations Based on Distinctness, Uniformity, and Stability (DUS) Testing via Morphological Descriptors and DNA Molecular Markers

AbstractA bred plant variety is a valuable tool for enhancing crop production and total yield. Recently, our breeding team developed three high seed yielding synthetic cultivars of bitter fennel. To characterize these newly breeding populations and differentiate them from each other and their parental populations, we conducted a Distinctness, Uniformity, and Stability (DUS) assessment using morphological traits evaluated over two consecutive years, as well as 20 Start Codon Targeted (SCoT) markers. The evaluation of morphological traits revealed that, five of qualitative traits exhibited monomorphism, while two other qualitative traits displayed polymorphism. Additionally, the investigation of eight quantitative traits showcased significant diversity. The Combined Over Years Distinctiveness analysis at a 1% significance level, based on eight quantitative characteristics, indicated distinctiveness for two breeding populations, namely Early and Medium Maturity Synthetic cultivars, compared to other populations. The Combined Over Years Uniformity analysis identified that all of the breeding populations and their parental populations were uniform in terms of the measured traits. The differences between Phenotypic Coefficients of Variation and Genotypic Coefficients of Variation were not particularly noticeable in the experimental material used currently. The majority of the measured traits showed high heritability, highlighting their stability over time. PCA utilized for quantitative morphological features, the first two principal components collectively accounted for more than 86.8% of the phenotypic variation. Subsequently, a dendrogram was constructed, which clustered breeding and parental populations into three distinct groups. The 15 SCoT markers produced a total of 164 extended fragments, with 139 (85%) of them showed polymorphic.The genetic similarity between the populations exhibited a range of 0.08–0.81, and cluster analysis utilizing Jaccard similarity coefficients and the Unweighted Pair Group Method with Arithmetic Mean (UPGMA) technique revealed clear distinctions among the three breeding populations and their parental populations. Altogether, the findings indicate that morphological DUS descriptors effectively distinguish some the populations, while others with overlapping expressions cannot be discriminated. Notably, SCoT markers demonstrate a fine ability to detect distinctions among fennel populations, suggesting the possibility of utilizing them as a complement to morphological traits in the DUS test. As a conclusion, these three newly breeding populations of fennel are distinct from each other and from their parental populations, and they can advance for registration and seed purity testing.

Unsupervised deep representation learning enables phenotype discovery for genetic association studies of brain imaging

Understanding the genetic architecture of brain structure is challenging, partly due to difficulties in designing robust, non-biased descriptors of brain morphology. Until recently, brain measures for genome-wide association studies (GWAS) consisted of traditionally expert-defined or software-derived image-derived phenotypes (IDPs) that are often based on theoretical preconceptions or computed from limited amounts of data. Here, we present an approach to derive brain imaging phenotypes using unsupervised deep representation learning. We train a 3-D convolutional autoencoder model with reconstruction loss on 6130 UK Biobank (UKBB) participants’ T1 or T2-FLAIR (T2) brain MRIs to create a 128-dimensional representation known as Unsupervised Deep learning derived Imaging Phenotypes (UDIPs). GWAS of these UDIPs in held-out UKBB subjects (n = 22,880 discovery and n = 12,359/11,265 replication cohorts for T1/T2) identified 9457 significant SNPs organized into 97 independent genetic loci of which 60 loci were replicated. Twenty-six loci were not reported in earlier T1 and T2 IDP-based UK Biobank GWAS. We developed a perturbation-based decoder interpretation approach to show that these loci are associated with UDIPs mapped to multiple relevant brain regions. Our results established unsupervised deep learning can derive robust, unbiased, heritable, and interpretable brain imaging phenotypes.

Morphoagronomic descriptors of rice landraces varieties (Oryza sativa L.) from the state of Maranhão

Rice landrace varieties are adapted to the most diverse environmental conditions, which is clearly important in periods of great climatic and sanitary uncertainties. However, there is a gap in their description in the literature. Maranhão, Brazil, has wide diversity in landrace seeds, with rice varieties that can significantly contribute to the genetic breeding of the species. Based on this information, the objective of the present study was to characterize the landraces rice varieties, through the description of the morphological and agronomic profile. The study analyzed 23 qualitative heredity descriptors and three quantitative descriptors in 21 rice landrace varieties from different locations in the state of Maranhão, according to the methodological procedures recommended by the National Cultivar Protection Service. A randomized block e experimental design was used (DBC), with 21 treatments and four replications. Considering complementing To complement the study, a multicategorical analysis was carried out between the 21 accessions, based on qualitative data obtained from the 22 morphological descriptors, which generated a dendrogram. The results showed that there are differences between the qualitative descriptors. Quantitative descriptors are highly significant, with regard to the number of tillers, with emphasis on the Edinho variety. The Quechi variety was responsible for one of the factors that most influences the rice yield, with the highest number of grains per panicle. The varieties Codozinho, Edinho, Palha Murcha and Pé Roxo, are more productive in number of panicles. The dendrogram formed three clusters with evidence of dissimilarities between the varieties. The results show that the landrace varieties differ in their morphoagronomic characteristics and can be valuable materials in the construction of a new, more sustainable agriculture.

Phenotypic and Molecular Diversity of Wild Populations of Acca sellowiana (Berg.) Burret in the Southern Area of Natural Distribution

Acca sellowiana is a subtropical tree in the myrtle family (Myrtaceae) native to southern Brazil and northeastern Uruguay. It is recognized for its value as a fruit-bearing, ornamental, and medicinal species. Based on distinctive characteristics of fruits, seeds, and leaves, as well as its geographical distribution pattern, two variants of the species are distinguished: the “Brazilian type” and the “Uruguayan type”. The objective of this study was to characterize, for the first time, the diversity of 202 individuals from four wild populations in Uruguay, representative of the species’ most southern natural distribution. Twenty-three morphological descriptors (leaf, flower, and fruit) and 204 RAPD (Random Amplified Polymorphic DNA) markers were used. The morphological data collected validated the main criteria that distinguish “Uruguayan type” populations from “Brazilian type” populations, such as lower seed weight and fruit size, thin and slightly rough skin, high pulp percentage, and hairy white abaxial leaf surfaces. Analyses of both morphological and molecular data indicated wide diversity and strong population structuring, which is relevant information for designing conservation plans, sustainable utilization, and genetic improvement of the plant genetic resources of this species.

Analysis of genetic divergence in Psidium cattleyanum Sabine accessions based on morphological fruit descriptors

Analysis of genetic divergence in Psidium cattleyanum Sabine accessions based on morphological fruit descriptors

Leaf-based characterization of intermediate forms between Cuban and Honduran mahogany

The genus Swietenia includes two mahogany species, Swietenia macrophylla (King.), commonly known as Honduran mahogany, and Swietenia mahagoni (L.) Jacq, commonly known as Cuban mahogany. There are reports of morphologically intermediate forms between Cuban and Honduran mahogany that have been localized in some Caribbean islands. The main objective of this research is to distinguish morphologically intermediate forms between the parental species S. mahagoni and S. macrophylla based on leaf morphological characters. Phenotypic data from a total of 357 mahogany trees were collected in the province of Sancti Spiritus, Cuba. Rachis length, petiole length, leaflet length, leaflet width, number of leaflets and number of nerves were evaluated. Morphological descriptor analysis revealed significant differences in the morphometric variables of the evaluated leaves, with rachis length, number of leaflets, leaflet length, petiole length, leaflet width, and number of nerves being significantly higher in S. macrophylla than in S. mahagoni. ANOVA reflected the variance between all leaf morphological parameters evaluated between the two pure species with statistically significant difference. Using the function obtained in the first DC of the two species, the individuals in the mixed stands were classified into 71 morphologically intermediate forms, 45 S. macrophylla and 64 S. mahagoni. In the second DC with the two species and the morphologically intermediate forms, Wilks’ partial lambda indicates that the variable "leaflet length" with 0.67 contributed most to the overall discrimination.

Breast masses with rim enhancement on contrast-enhanced mammography: morphological and enhancement features for diagnosis and differentiation of benign and malignant.

To investigate the imaging characteristics and clinicopathological features of rim enhancement of breast masses demonstrated on contrast-enhanced mammography (CEM). 67 cases of breast lesions confirmed by pathology and showing rim enhancement on CEM examinations were analyzed. The lesions were divided into benign and malignant groups, and the morphological and enhanced features were described. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated separately for each morphology descriptor to evaluate the diagnostic ability of each indicator. There were 35 (52.2%) malignant and 32 (47.8%) benign lesions. There are significant differences in the morphological and enhanced features between benign and malignant lesions. 29/35 (82.9%) malignant lesions exhibited irregular shapes, and 31/35 (88.6%) showed indistinct margins. 28/35 (80%) malignant lesions displayed strong enhancement on CEM, while 12/32 (37.5%) benign lesions exhibited weak enhancement (P = 0.001). Malignant lesions showed a higher incidence of unsmooth inner walls than benign lesions (28/35 vs 7/32; P <.001). Lesion margins showed high sensitivity of 88.57% and NPV of 81.8%. The presence of suspicious calcifications had the highest specificity of 100% and PPV of 100%. The diagnostic sensitivity, specificity, PPV, and NPV of the combined parameters were 97.14%, 93.15%, 94.44%, and 96.77%, respectively. The assessment of morphological and enhanced features of breast lesions exhibiting rim enhancement on CEM can improve the differentiation between benign and malignant breast lesions. This article provides a reference for the differential diagnosis of ring enhanced lesions on CEM.

Establishment of morphological markers to differentiate male and female plants in Ailanthus excelsa Roxb. using multiple logistic regression

Ailanthus excelsa Roxb., belongs to the family Simaroubaceae, is a fast-growing multipurpose tree, and used mainly as a source of fodder and shade. It bears male, female, and hermaphrodite flowers on separate plants. It has been observed that male plant has more leaf biomass during April-May in semi-arid regions of India (Jaipur). In its vegetative state, the sex of the tree cannot be identified. The present study has therefore been designed to investigate if there is any difference in male and female plants based on morphological descriptors namely stomata number, stomata length, stomata diameter, trichome number, trichome length, and trichome diameter. 20 plants with male flowers and 20 plants with female flowers have been studied. The data revealed that male plants have lower trichome diameter (11.91 µm) than female (14.18 µm) plants. Other parameters do not show any statistically significant difference (P > 0.05). The Omnibus Tests of the Model Coefficient obtained for trichome diameter (0.042) is reliable in improving the model, implying that the model is the best fit. To test the validity of this model, the Hosmer and Lemeshow test was performed, and the p-value of chi-square (0.405 > 0.05) indicates that the logistic model obtained above is the best-fit model. Further studies of trichome diameter at the seedling stage and then confirmation of plant sex at maturity level will help in establishing morphological markers in A. excelsa for identification of sex.

Stochastic 3D Modeling of Nanostructured NVP/C Active Material Particles for Sodium‐Ion Batteries

AbstractA data‐driven modeling approach is presented to quantify the influence of morphology on effective properties in nanostructured sodium vanadium phosphate / carbon composites (NVP/C), which are used as cathode material in sodium‐ion batteries. This approach is based on the combination of advanced imaging techniques, experimental nanostructure characterization and stochastic modeling of the 3D nanostructure consisting of NVP, carbon and pores. By 3D imaging and subsequent post‐processing involving image segmentation, the spatial distribution of NVP is resolved in 3D, and the spatial distribution of carbon and pores is resolved in 2D. Based on this information, a parametric stochastic model, specifically a Pluri‐Gaussian model, is calibrated to the 3D morphology of the nanostructured NVP/C particles. Model validation is performed by comparing the nanostructure of simulated NVP/C composites with image data in terms of morphological descriptors which have not been used for model calibration. Finally, the stochastic model is used for predictive simulation to quantify the effect of varying the amount of carbon while keeping the amount of NVP constant. The presented methodology opens new possibilities for a ressource‐efficient optimization of the morphology of NVP/C particles by modeling and simulation.

Morphological characterization of Cereus trigonodendron K.Schum. ex Vaupel (Cactácea), in a native population of the South-Western Amazon

The Cereus trigonodendron is a species of cactus native to the state of Rondônia (RO), occurring on rocky outcrops and with potential use in the gastronomic market. However, the lack of knowledge about the species becomes a hindrance to its commercial insertion. In the present study, the first characterization of the main morphological descriptors of flowers, fruits, spines, and cladodes or stem in a native population located in the Union Bandeirantes District (RO) is presented. Ten clumps were observed containing an average of 13.1 primary branches, ranging from 25-440cm, with an average of 200.75cm. The flowers, white, exceed an average of 20 cm in length and the mature fruits observed were reddish in color. Additional studies are necessary to explain the probable phenotypic plasticity of the fruits of this species.

Generative adversarial network (GAN) enabled Statistically equivalent virtual microstructures (SEVM) for modeling cold spray formed bimodal polycrystals

Image-based micromechanical models, necessary for the development of structure-property-response relations, are far from mature for complex microstructures with multi-modal distributions of morphological and crystallographic features, such as those occurring with cold spray-formed (CSF) aluminum alloys. These materials have a bimodal polycrystalline microstructure composed of recrystallized ultra-fine grains (UFGs) and deformed coarse grains (CGs) within prior particles. A prime reason is the lack of robust approaches for generating statistically equivalent virtual microstructures (SEVM) capturing the statistics of characteristic morphological and crystallographic features, such as grain size, crystallographic orientations, and misorientations. This paper introduces an approach, strategically integrating Generative Adversarial Network-based approaches for producing bimodal CSF AA7050 alloy microstructures, with the synthetic microstructure builder Dream3D for packing prior particles with CGs having statistically equivalent morphological and crystallographic descriptors to electron backscatter diffraction (EBSD) maps. An efficient finite element (FE) simulation approach is developed for the SEVMs to generate local and overall response functions through the creation of sub-volume elements (SVEs).

The trajectory of contemporary cryoplanation literature: A bibliometric assessment

AbstractThe origin of cryoplanation landforms has long been a subject of controversy in the literature on periglacial geomorphology. Multiple hypotheses have been advanced over the past century, but by the early 1970s only two had survived: geological structure and climate‐driven nivation processes. To determine whether some publications may be playing a “gate‐keeping” role through selective citation, we conducted a co‐citation analysis of the cryoplanation literature for the 1971–2018 period preceding a resurgence of publications by the authors of the present paper. The results indicate that there has been no overt attempt to influence the trajectory of the cryoplanation literature. Although consensus now exists that cryoplanation landforms are erosional phenomena, the roles of structure and nivation and their relative importance are still contested. We suggest that terminological complexity and ambiguity can be reduced by treating “nivation” as a process term and “cryoplanation terrace” as a morphological descriptor.

A mathematical model to estimate tissue level oxygenation during OSA events- beyond morphological descriptors and back to physiology

A mathematical model to estimate tissue level oxygenation during OSA events- beyond morphological descriptors and back to physiology

Redes neurais artificiais para descritores morfológicos em germoplasma de alface biofortificada

ABSTRACT The classification based on morphological descriptors in lettuce is considered a complex activity and proves to be efficient for studying phenotypic characteristics. Therefore, the objective of this study was to analyze the biofortified lettuce germplasm bank at the Universidade Federal de Uberlândia using both conventional morphological descriptors and artificial neural networks. The experiment was conducted in the field. The experimental design employed was a randomized complete block design, consisting of 14 treatments (11 genotypes of mini lettuce, and the cultivars Purpurita, UDI 10.000, and Pira 72) with four replications. Nine morphological descriptors were evaluated. Following the data acquisition, dissimilarity matrix analyses, principal component analysis, dendrogram construction, and artificial neural network (ANN) analyses were performed. The genotypes exhibited phenotypic variability when compared to the parental strains UDI 10.000 and Pira 72. The purple color of the leaves and anthocyanin presence across the entire leaf surface were predominant among the genotypes. Descriptors such as leaf intensity and color, as well as anthocyanin intensity, coloration, and distribution, were the most influential in assessing genetic variability. The Self-Organizing Map (SOM) demonstrated greater sensitivity in discriminating between genotypes compared to the Unweighted Pair Group Method with Arithmetic Mean (UPGMA). While the UPGMA clustering method grouped genotypes into three clusters, the SOM method grouped into five clusters. The use of genetic distance analyses and SOM dendrogram proved to be effective in selecting individuals UFU 215#1, UFU 215#2, UFU 215#6, UFU 215#10, and UFU 215#13, which are clustered with the cultivar UFU Mini Biofort.

Parâmetros genéticos e dissimilaridade genética de Gower em aveia preta

ABSTRACT: This research evaluated the agronomic performance through mixed models, and determined the genetic divergence between black oat genotypes. The experiment was carried out at Federal University of Santa Maria, Frederico Westphalen/RS. Fourteen black oat genotypes were evaluated, being 11 lines developed by Breeding Program of University, and three commercial cultivars (IAPAR 61, UPFA 21 - Moreninha and, IPR Cabocla). We evaluated quantitative traits associated to plant height, cycle, dry mass yield and seeds yield; and 19 qualitative traits, being these morphological descriptors. The results showed that lines UFSMFW 2-05 and UFSMFW 2-07 stand out with characteristics such as early cycle, higher dry mass and grain yield. Divergence analysis revealed the formation of three distinct groups, indicating the presence of variability. These results suggested the potential for the development of new cultivars of black oat, presenting early cycle and good grain yield.

Characterization of Indian garlic accessions through IPGRI morphological descriptors

Characterization of Indian garlic accessions through IPGRI morphological descriptors

Foliar Morphological and Micromorphological Variation of Dioscorea Species in Terengganu, Malaysia

Dioscorea species are recognised for their production of tuberous roots and are referred to as "ubi" by the local population in Malaysia. The tubers of Dioscorea are commonly consumed by individuals residing in the East Coast region of Peninsular Malaysia as their primary food source. These tuberous roots are particularly abundant during the monsoon season, typically observed in local markets from October to December. Due to the availability and potential of this Dioscorea species, a study about the variation in morphological and micromorphological study of the leaves of three species of Dioscorea in Terengganu was conducted in order to identify the variation in their morphological and micromorphological characteristics. The selected species are D. esculenta (ubi itik), D. alata (ubi besar), and D. hispida (ubi gadong). The collection has been done in the Kuala Berang Terengganu area. The leaves morphological characteristics such as leaf colour, leaf type, leaf shape, leaf size, leaf margin and hairiness of adaxial and abaxial surface and shape of leaves and petiole were recorded. The morphological descriptors were suggested by the International Plant Genetic Resources Institute (IPGRI) / International Institute of Tropical Agriculture (IITA). The foliar anatomical studies of selected Dioscorea were followed by the standard tissue sectioning procedures and the observation was done by using light microscopy. The morphological study shows the variations in leaf shape, leaf base, and leaf size but they have the similarity in term of leaf margin shape and leaf attachment which is all species are petiolate. The micromorphological study shows the presence of non-glandular and uniseriate trichomes which is only obtained in the D. esculenta and D. hispida. Hence, this study contributes to the information on these species, especially for classification and identification of Dioscorea species.Keywords: Dioscorea, morphology, foliar anatomy

Amelioration of economically important traits through mutagenesis in spine gourd (Momordica dioica)

Mutation breeding can sometimes be endeavored along with conventional breeding efforts, resulting in the discovery of some economically useful genetic changes. Evaluation of 96 first-generation mutant germplasm lines of spine gourd (Momordica dioica Roxb.) was done through morphological descriptors and molecular makers. Correlation coefficient analysis, path analysis and cluster analysis supplemented by molecular marker-based population structure analysis helped in understanding the population behavior and identification of high-yielding lines. The yield was found to be highly positively correlated with days to first flowering, leaf width, single fruit weight and number of fruits per plant. Also, the maximum positive direct effect on yield was shown by single fruit weight followed by the number of fruits per plant and leaf width. The population structure analysis revealed 4 clusters of population. Few high-yielding lines were identified which approximately yielded 1.5 times more than the checks. Further refinement in these mutant lines through breeding programs coupled with in-depth molecular analysis can lay the foundation of the release of some excellent spine gourd varieties in the future.