Morphological Descriptors Research Articles

Morpho–Molecular Characterization of Brazilian Common Bean Landraces Varieties and Commercial Cultivars

This study aimed to characterize forty genotypes (31 landrace varieties and nine commercial cultivars) of common bean (Phaseolus vulgaris L.) morphologically and molecularly. Morphological descriptors were evaluated during seedling, flowering, physiological maturation and post-harvest stages. Ten microsatellite markers were used for molecular screening. The markers were analyzed according to the number of alleles per locus, the allele frequency per locus and the polymorphism in content (PIC). Genetic distances and cluster analysis were performed using Bayesian inference and the UPGMA method. All black beans evaluated have anthocyanin in the cotyledons, hypocotyls and stems, and their flowers are purple. For the growth habit, 50% of the evaluated genotypes belong to type III, and at the physiological maturation stage, yellow color is predominant in the pods (85%). Through the genetic dissimilarity, three groups were observed for the likelihood reason, and five groups were observed through the UPGMA method, a strong indication of the wide genetic diversity among the evaluated genotypes. All genotypes from the Andean center of origin were grouped into the same cluster.

Multi-level feature fusion network for neuronal morphology classification.

Neuronal morphology can be represented using various feature representations, such as hand-crafted morphometrics and deep features. These features are complementary to each other, contributing to improving performance. However, existing classification methods only utilize a single feature representation or simply concatenate different features without fully considering their complementarity. Therefore, their performance is limited and can be further improved. In this paper, we propose a multi-level feature fusion network that fully utilizes diverse feature representations and their complementarity to effectively describe neuronal morphology and improve performance. Specifically, we devise a Multi-Level Fusion Module (MLFM) and incorporate it into each feature extraction block. It can facilitate the interaction between different features and achieve effective feature fusion at multiple levels. The MLFM comprises a channel attention-based Feature Enhancement Module (FEM) and a cross-attention-based Feature Interaction Module (FIM). The FEM is used to enhance robust morphological feature presentations, while the FIM mines and propagates complementary information across different feature presentations. In this way, our feature fusion network ultimately yields a more distinctive neuronal morphology descriptor that can effectively characterize neurons than any singular morphological representation. Experimental results show that our method effectively depicts neuronal morphology and correctly classifies 10-type neurons on the NeuronMorpho-10 dataset with an accuracy of 95.18%, outperforming other approaches. Moreover, our method performs well on the NeuronMorpho-12 and NeuronMorpho-17 datasets and possesses good generalization.

Morphological characterization of the hippocampus: a first database in Ecuador.

The hippocampal volume is a well-known biomarker to detect and diagnose neurological, psychiatric, and psychological diseases. However, other morphological descriptors are not analyzed. Furthermore, not available databases, or studies, were found with information related to the hippocampal morphology from Latin-American patients living in the Andean highlands. The hippocampus is manually segmented by two medical imaging specialists on normal brain magnetic resonance images. Then, its morphological qualitative and quantitative descriptors (volume, sphericity, roundness, diameter, volume-surface ratio, and aspect ratio) are computed via 3D digital level-set-based mathematical representation. Furthermore, other morphological descriptors and their possible correlation with the hippocampal volume is analyzed. We introduce a first database with the hippocampus' morphological characterization of 63 patients from Quito, Ecuador, male and female, aged between 18 and 95 years old. This study provides new research opportunities to neurologists, psychologists, and psychiatrists, to further understand the hippocampal morphology of Andean and Latin American patients.

Deep Learning-Based Reconstruction of 3D Morphology of Geomaterial Particles from Single-View 2D Images.

The morphology of particles formed in different environments contains critical information. Thus, the rapid and effective reconstruction of their three-dimensional (3D) morphology is crucial. This study reconstructs the 3D morphology from two-dimensional (2D) images of particles using artificial intelligence (AI). More than 100,000 particles were sampled from three sources: naturally formed particles (desert sand), manufactured particles (lunar soil simulant), and numerically generated digital particles. A deep learning approach based on a voxel representation of the morphology and multi-dimensional convolutional neural networks was proposed to rapidly upscale and reconstruct particle morphology. The trained model was tested using the three particle types and evaluated using different multi-scale morphological descriptors. The results demonstrated that the statistical properties of the morphological descriptors were consistent for the real 3D particles and those derived from the 2D images and the model. This finding confirms the model's validity and generalizability in upscaling and reconstructing diverse particle samples. This study provides a method for generating 3D numerical representations of geological particles, facilitating in-depth analysis of properties, such as mechanical behavior and transport characteristics, from 2D images.

EthoWatcher OS: improving the reproducibility and quality of categorical and morphologic/kinematic data from behavioral recordings in laboratory animals.

Behavioral recordings annotated by human observers (HOs) from video recordings are a fundamental component of preclinical animal behavioral models of neurobiological diseases. These models are often criticized for their vulnerability to reproducibility issues. Here, we present the EthoWatcher-Open Source (EW-OS), with tools and procedures for the use of blind-to-condition categorical transcriptions that are simultaneous with tracking, for the assessment of HOs intra- and interobserver reliability during training and data collection, for producing video clips of samples of behavioral categories that are useful for observer training. The use of these tools can inform and optimize the performance of observers, thus favoring the reproducibility of the data obtained. Categorical and machine vision-derived outputs are presented in an open data format for increased interoperability with other applications, where behavioral categories are associated frame-by-frame with tracking, morphological and kinematic attributes of an animal's image. The center of mass (X and Y pixel coordinates), the animal's area in square millimeters, the length and width in millimeters, and the angle in degrees were recorded. It also assesses the variation in each morphological descriptor to produce kinematic descriptors. While the initial measurements are in pixels, they are later converted to millimeters using the scale calibrated by the user via the graphical user interfaces. This process enables the creation of databases suitable for machine learning processing and behavioral pharmacology studies. EW-OS is constructed for continued collaborative development, available through an open-source platform, to support initiatives toward the adoption of good scientific practices in behavioral analysis, including tools for evaluating the quality of the data that can alleviate problems associated with low reproducibility in the behavioral sciences.

Morphological and molecular diversity analysis vis-a-vis phylogenetic correlation among pomegranate (Punica granatum L.) varieties

Abstract Identification of different pomegranate (Punica granatum L.) genotypes using morphological descriptors and further substantiated through molecular means is essential for a breeding program. Characterization using molecular markers has an advantage over its morphological counterpart due to its low expense, quick and reliable results, and the requirement of less sophisticated equipment. In this study, eight different pomegranate cultivars were characterized based on their morphological and molecular characters in sub-tropical regions between 2018 and 2019. Morphological experiments were conducted in a randomized block design replicated thrice for each cultivar, whereas RAPD markers were employed for molecular studies. Principal component analysis revealed significant morphological variation (79.61%) among the cultivars. A high level of polymorphism, similar to PCA, was observed with RAPD analysis (80.49%). Some discrepancies between morphological and molecular results were noted in UPGMA cluster analysis. However, eight primers (total = 41) distinctively separated the Bhagwa variety from others, with the maximum similarity coefficient value (ca. 0.54) and superior fruit quality distinguished in PCA analysis with the maximum mean Euclidean distance (ca. 16). Hence, RAPD markers could be used along with morphological markers for a quick screening of germplasms in further crop improvement programs.

Quantitative assessment of the 3D pore space and microglobule clustering network to understand chromatographic transport phenomena in polymeric monolithic columns

The 3D pore space and microglobule clustering network of polymer monolithic columns, which exhibited similar external porosity but significantly different chromatographic dispersion and permeability characteristics, were subjected to tomographic imaging followed by stereological analyses. The morphologies of the monolithic support structures were examined using serial-block-face scanning electron microscopy. The statistically computed characteristic chord-length, hydraulic radius and tortuosity of the pore are strongly associated to chromatographic transport processes, in particular, eddy dispersion and mass-transfer resistance contributing to chromatographic dispersion, and permeability of monolithic columns. Moreover, Giddings’ trans-column velocity bias has been quantified in monoliths for the first time. With demonstrated method robustness, the proposed morphological descriptors and the streamlined analysis workflow provide novel insights bridging the structure-performance relationship for future chromatography column design.

Genetic Diversity of Common Bean (Phaseolus vulgaris L.) Landraces Based on Morphological Traits and Molecular Markers.

The objective of this study was to evaluate the genetic diversity among traditional common bean accessions through morphological descriptors and molecular markers. Sixty-seven common bean accessions from the Germplasm bank of the Instituto Federal of Espírito Santo-Campus de Alegre were evaluated. For this, 25 specific morphological descriptors were used, namely 12 quantitative and 13 qualitative ones. A diversity analysis based on morphological descriptors was carried out using the Gower algorithm. For molecular characterization, 23 ISSR primers were used to estimate dissimilarity using the Jaccard Index. Based on the dendrograms obtained by the UPGMA method, for morphological and molecular characterization, high genetic variability was observed between the common bean genotypes studied, evidenced by cophenetic correlation values in the order of 0.99, indicating an accurate representation of the dissimilarity matrix by the UPGMA clustering. In the morphological characterization, high phenotypic diversity was observed between the accessions, with grains of different shapes, colors, and sizes, and the accessions were grouped into nine distinct groups. Molecular characterization was efficient in separating the genotypes in the Andean and Mesoamerican groups, with the 23 ISSR primers studied generating an average of 6.35 polymorphic bands. The work identified divergent accessions that can serve different market niches, which can be indicated as parents to form breeding programs in order to obtain progenies with high genetic variability.

Enhancing genetic diversity in Pelargonium: insights from crossbreeding in the gene pool.

This study aimed to enrich the Pelargonium gene pool through crosses and assess genetic variation among 56 genotypes from five Pelargonium species. Seventeen morphological descriptors were used, and NTSYS-pc software was employed to define genetic relationships, and a UPGMA-generated dendrogram reflected these relationships. Moreover, principal component analysis (PCA) was performed to determine which parameter was more effective in explaining variation. Results showed wide variation in genetic similarity rates, with the most similar genotypes being P. zonale 'c1' and a hybrid of P. zonale 'c1' x P. zonale 'c2' (90% similarity). According to the dendrogram results, it was observed that the genotypes were distributed in six clusters. In contrast, the most distant genotypes were P. zonale 'c11' and a hybrid of P. zonale 'c10' x P.zonale 'c11' (0.04% similarity). Hybrids from the female parent P. x hortorum 'c1' exhibited unique placement in the dendrogram. In the crossing combinations with this genotype, the individuals obtained in terms of flower type, flower color, flower size, bud size, early flowering, and leaf size characters showed different characteristics from the parents. Surprising outcomes in flower types, colors, and shapes contributed to gene pool enrichment, promising increased breeding variation success. The study holds practical implications for commercial breeding and serves as a valuable guide for future research endeavors.

Exploring genetic diversity of yellow-berried night shade (Solanum virginianum L.) using genetic divergence and molecular markers

The rationale of this research was to explore the genetic divergence of 54 kantakari accessions (Solanum virginianum L. syn. S. surattense Burm. f.), to identify their significant traits, and unravel their genetic variations. Kantakari is a widely used medicinal plant in traditional medicine worldwide and is also known for its allopathic properties. The morphological descriptors and molecular markers (Random Amplified Polymorphic DNA) used to characterize these samples revealed significant within-accession heterogeneity, indicating the possibility of future selection. Twenty-three morphological and biochemical features were examined to assess taxonomic traits. Accessions were classified into six clusters based on Mahalanobis D2 statistics of 23 quantitative traits. Clusters V and VI had the largest intercluster distance (1183.81), whereas Cluster IV had the largest intracluster distance (D2 = 275.67) (Cluster V and VI). Random Amplified Polymorphic DNA marker amplification using 10 polymorphic primers revealed 79 alleles with an overall mean of 7.90 alleles per marker, with Polymorphism Information Content values varying from 0.11 to 0.37 (Mean = 0.30). Cluster assessment produced three distinct groups. In conclusion, the investigation underscores that substantial diversity was observed among the surveyed kantakari accessions. Using molecular markers in tandem with morphological characterization, presents a robust approach for elucidating the intricacies of species-specific genetic variation with greater accuracy and depth.

Genetic diversity and DNA fingerprinting of rice varieties of Manipur using microsatellite markers

Rice variety differentiation was based on morphological descriptors (DUS) before the advent of genomic and proteomic technology. DNA fingerprinting is becoming an important molecular marker approach because of its wide application in varietal protection, classification, and conflict settlement. In the present study, genetic diversity and variability among the 11 rice varieties of Manipur at the molecular level was studied using 42 SSR markers. The genotypic data of the SSR markers revealed four sub-populations. Cluster analysis indicated the close similarity between RC Maniphou 12 and RC Maniphou 15. To create a DNA fingerprinting database for 11 rice varieties, three separate multiplex PCR systems using different combinations of 11 polymorphic SSR markers based on amplicon size were successfully developed . These were able to distinguish the distinctness of all the eleven released rice varieties.

Assessment of the genetic diversity and population structure in Moringa oleifera accessions using DNA markers and phenotypic descriptors

Moringa (Moringa oleifera Lam.) is one of the multipurpose trees with significant promise as a high-value crop of industrial importance, having nutritional, therapeutic, and prophylactic properties. Genetic diversity is a cornerstone of any crop improvement program and plays a key role in the selection of promising parental lines for hybrid breeding. Morphological and molecular markers have been proven to be potential tools for the evaluation of genetic diversity, crop genetic improvement, and conservation of plant genetic resources. In the current study, morphological descriptors, RAPD, and SCoT markers were used to determine genetic diversity among 28 M. oleifera accessions. Significant morphological variations were noted for several economic traits across the accessions studied. Four primary clusters were visible on the dendrogram based on phenotypic markers, indicating clustering of accession from a shared geographical habitat. No correlation was estimated between morphological traits, indicating an environmental influence. Three RAPD and seven SCoT primer sets produced 37 and 46 markers, with 53.2 and 71.3% polymorphisms, respectively. Based on genotypic data and the UPGMA approach, all 28 accessions were separated into two major clusters in the phylogenetic tree, irrespective of any geographical areas. The clustering pattern indicates widespread plant species and rapid gene flow through cross-pollination in Moringa populations. Three subpopulations of the involved accessions were identified by population structure analysis; however, there was only a weak link with the location of plant cultivation. The expected heterozygosity for the three subpopulations varied from 0.23 to 0.32, as per R-based structural analysis. AMOVA's attribution of 86% and 19% of all variations to within- and between-populations, respectively, indicates that there has been gene flow across geographic regions. The PCA showed a wide distribution of genotypes in the scatterplot, also suggesting huge genetic variation among the M. oleifera population. The study revealed a significant level of genetic diversity among M. oleifera accessions, which can be harnessed to conserve plant genetic resources and develop high-yielding, nutrient-dense Moringa cultivars.

The Effect of Irrigation on the Vineyard Canopy and Individual Leaf Morphology Evaluated with Proximal Sensing, Colorimetry, and Traditional Morphometry

The high number of grapevine (Vitis vinifera L.) cultivars grown world-wide are described and identified according to detailed morphological and morphometric descriptor lists. The grapevine leaf is of utmost importance in characterization, despite its traits being very sensitive to environmental factors. In this study, the effect of irrigation/drought stress on the individual leaf morphology and morphometry of the ‘Hárslevelű’ grapevine (Vitis vinifera L.) cultivar was examined. To verify the effect of the applied irrigation methods (drip and subsoil irrigation) on the plant’s water status, water potential measurements were carried out during the 2022 season. The effect of the applied treatments on the vegetative growth was evaluated according to point quadrat and a multichannel LiDAR analysis in order to describe the width of the canopy area, row volume, and area coverage index. The individual leaf morphology was assessed via traditional morphometry and colorimetry. Our results showed that rainfed plants had a significantly lower stem ψ compared to the drip- and subsoil-irrigated plants at all examined dates. The point quadrat results indicate that the leaf layer number was significantly (p < 0.05) influenced by the position, while the treatment showed no effect on the leaf layer number. The leaf colorimetry showed a difference among the samples, as significant alterations were found in 28 out of the 32 examined color properties. Within the traditional morphometric analysis, 54 traits were evaluated, and 14 of the traits were significantly altered due to the different water management systems.

Phenotypic analysis of mezcal agaves from the Central Valleys of Oaxaca

Objective: Mezcal agaves in the state of Oaxaca have a high economic value due to the demand for mezcal production; therefore, the purpose of this work was to assess and highlight the importance of morphological diversity within and among cultivated Agave species. Design/Methodology/Approach: A completely randomized experimental design with 25 treatments (populations) and 11 replicates (individuals) was implemented. The plant (individual) was the experimental unit and 19 morphological descriptors proposed by the National Seed Inspection and Certification Service (SNICS) were assessed. A total of 275 individuals of the Agave angustifolia, Agave karwinskii, Agave marmorata, Agave rhodacantha, Agave potatorum, Agave seemanniana, and Agave nussaviorum species were assessed using a multivariate analysis to determine their phenotypic variability and existing relationships. Results: The dendrograms for the Q-mode and R-mode were obtained by means of a cluster analysis, forming 4 groups based on the average linkage generated from the standardized BDM of the sampled species of the genus Agave. Four groups were formed using the k-means clustering method, in accordance with field observations and a review of the taxonomic bibliography. The first two principal components (PC) accounted for 66.4% of the total variation, according to the principal component analysis (PCA). For PC1 and PC2, the variables with the highest contribution were those related to leaf shape (Fh), size of the lateral spine (FEL), number of leaves (Nh), plant height (H), uniformity in the size of the lateral spines (UTE), and terminal spine shape (FET). Study Limitations/Implications: A comprehensive study requires taxonomic keys to identify species, subspecies, and even varieties of Agave. Additionally, molecular characterization is essential to understand the variability and phylogenetic relationships of these populations, subject to a phylogenetic analysis. Findings/Conclusions: Multivariate analysis techniques revealed that three species showed high phenotypic variability in the maturation stage under cultivation conditions. The A. potatorum and A. karwinskii species had a greater intra-population phenotypic variability, with significant differences within the same species. Agave marmorata showed no intra- or inter-population variability. Leaf texture (Txh) was the only variable that explained the variation within its group. This is a tall species whose diameter is larger than in the other species. The variables of the Mexican (Agave rhodacantha) group showed low correlation, as their behavior was highly dispersed. The variables obtained in the field from this group of populations must be meticulously assessed to identify the degree of correlation between the variables and to confirm the behavior of this group.

Usefulness of Transbronchial Lung Cryobiopsy When Starting Antifibrotic Treatment and Predicting Progressive Fibrosing Interstitial Lung Disease: Descriptive Research.

Although transbronchial lung cryobiopsy (TBLC) is widely used in diagnostic algorithms for various interstitial lung diseases (ILDs), its real-world utility in the therapeutic decision-making strategy for ILD patients remains unclear, in particular, when judging the time to start antifibrotic agents. We analyzed medical records of 40 consecutive patients with idiopathic or fibrotic hypersensitivity pneumonitis who underwent TBLC. A TBLC-based usual interstitial pneumonia (UIP) score was used to assess three morphologic descriptors: patchy fibrosis, fibroblastic foci, and honeycombing. In our 40 patients with ILD, the most frequent radiological feature was indeterminate for UIP (45.0%). Final diagnosis included idiopathic pulmonary fibrosis (22.5%), fibrotic nonspecific interstitial pneumonia (5.0%), fibrotic hypersensitivity pneumonitis (35.0%), and unclassifiable ILD (37.5%). Linear mixed-effects analysis showed that declines in the slopes of %FVC and %DLCO in patients with TBLC-based UIP "Score ≥ 2" were significantly steeper than those of patients with "Score ≤ 1." During follow-up of patients with Score ≥ 2 (n = 24), more than half of them (n = 17) received an antifibrotic agent, with most patients (n = 13) receiving early administration of the antifibrotic agent within 6 months after the TBLC procedure. TBLC-based UIP Score ≥ 2 indicated the increased possibility of a progressive fibrosis course that may prove helpful in predicting progressive pulmonary fibrosis/progressive fibrosing ILD even if disease is temporarily stabilized due to anti-inflammatory agents. Patients may benefit from early introduction of antifibrotic agents by treating clinicians.

Morphological descriptors of young plants in Acmella spp.

Morphological descriptors of young plants in Acmella spp.

Which North American spine society disc herniation morphology descriptors are most associated with improvements in clinical outcomes after microdiscectomy?

The North American Spine Society (NASS) assembled the first ever comprehensive naming system for describing lumbar disc disease, including lumbar disc herniation. The objectives of this study were (1) to determine which NASS descriptors are most predictive of independent patient-reported outcomes after microdiscectomy and (2) to identify the inter-rater reliability of each NASS descriptor. Adult patients (≥18 years) who underwent a lumbar microdiscectomy from 2014-2021 were retrospectively identified. Patient-reported outcome measures (PROMs) were collected at preoperative, 3-month, and 1-year postoperative time points. Lumbar disc herniations were evaluated and classified on preoperative MRI using the NASS lumbar disc nomenclature specific to disc herniation. About 213 microdiscectomy patients were included in the final analysis. Herniation descriptors exhibiting the greatest reliability included sequestration status (κ=0.83), axial disc herniation area (κ=0.83), and laterality (κ=0.83). The descriptor with the lowest inter-rater reliability was direction of migration (κ=0.53). At 3 months, a sequestered herniation was associated with lower odds of achieving the minimal clinically important difference (MCID) for ODI (p=.004) and MCS (p=.032). At 12 months, a similar trend was observed for Oswestry Disability Index (ODI) MCID achievement (p=.001). At 3 months, a herniation with larger axial area was a predictor of MCID achievement in ODI (p=.004) and the mental component summary (MCS) (p=.009). Neither association persisted at 12 months; however, larger axial disc herniation area was able to predict MCID achievement in the Visual Analogue Scale (VAS) leg (p=.031) at 12 months. The utility of the NASS nomenclature system in predicting postoperative outcomes after microdiscectomy has yet to be studied. We showed that sequestration status and disc area are both reliable and able to predict the odds of achieving MCID in certain clinical outcomes at 3 months and 12 months after surgery. Hence, preoperative imaging analysis of lumbar disc herniations may be useful in accurately setting patient expectations.

An Image‐Based Approach to Automated Recognition of Asbestos‐Containing Components in Wall Demolition Waste

AbstractThe feasibility to discriminate potentially asbestos‐containing components from asbestos‐free concrete based on camera images using the example of wall demolition waste is investigated. For this, three types of asbestos substitute materials and two types of concrete are crushed and photographed. The classification of the fragment images is carried out with a) morphological and texture features and b) with features automatically extracted by the pretrained MobileNetV3 network. Feret diameters, circularity, and others served as morphological descriptors. The texture was described by measures of grey‐level intensity, as obtained from the grey‐level co‐occurrence matrix. Support vector machines are found to achieve classification accuracies above 99 % based on the automatically extracted features. The presented identification approach is promising to automate the treatment process of asbestos‐containing materials from construction and demolition waste, which is effortful and requires expert knowledge to this day.

EVALUACIÓN DEL CICLO FENOLÓGICO Y CARACTERIZACIÓN MORFOLÓGICA DE GENOTIPOS DE QUINUA (Chenopodium quinua Willd.)

<p><strong>Background:</strong> Background: Morphological characterization studies and determination of the phenological cycle of quinoa in Colombia are scarce, which are necessary for the identification of new planting materials. <strong>Objective:</strong> The aim of this study was to evaluate the phenological cycle of quinoa materials to identify early and late genotypes; study the morphological characteristics to identify discriminatory descriptors for the genetic improvement of this species in the Department of Cauca. <strong>Methodology:</strong> Fourteen families and three commercial controls (Blanca de Jericó, Aurora, and Tunkahuan) were evaluated in two locations in the department of Cauca under a completely randomized block design with four replications. Twelve phenological stages and 20 morphological descriptors were evaluated. The data were analyzed using an Analysis of Variance and Duncan's Multiple Range Test (p<0.05), in addition, a Multiple Correspondence Analysis was performed. The information was analyzed with the statistical package “R” version 4.3. <strong>Results:</strong> It was found that the Flia27 family was the earliest in Silvia and Totoró. The clustering analysis based on the 20 morphological descriptors grouped the 17 genotypes into five groups, differentiating the controls from the rest of the 14 evaluated families. The families were grouped to present an architecture with low stature and easy management, compact panicle form, and simple growth habit, in contrast to what was found in the controls which exhibited high stature, lax panicle, and branching up to the lower third. <strong>Implications:</strong> It is necessary to study with more homogeneous materials to determine which characteristics exactly are variable depending on the genotype and which show genotypic stability. <strong>Conclusions:</strong> Flia27 was the earliest, making it interesting to be included in a quinoa genetic improvement program. The most discriminatory descriptors were leaf shape, leaf margin, and panicle color.</p>

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.