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The aim of this study was to select traditional accessions, compose a core collection of common bean, and assess the representativeness of the collection in relation to the base collection accommodated in the BAG of Embrapausing analysis strategies for multivariate models. We useddata characterizing 2903 accessions fromcollections representing all geographic areas of Brazil regarding three morphologic descriptors (seed color, growthhabittype, and seed size) and four ecogeographicdescriptors (geographical areas, states, altitudes, and soil classes). A set of400 accessions were selected using multivariate models applied to the data transformed in multibinary values. The accessions sampled had maximum similarity (100%) tothe traditional collection, phenotypic diversity, and representative heterogeneity in relation to the traditional collection. In the core collection, the accessions represented 9.5% of the traditional accessions and were equivalent to 3% of the accessions of the base collection. Thus, it is possible to form a core collection that is representative of the base collection regarding genetic diversity and the conservation of rare alleles. Made available in DSpace on 2022-09-14T21:05:18Z (GMT). No. of bitstreams: 1 ca-2022.pdf: 1195160 bytes, checksum: 84fdf069a44094ccf2bf97ea19da4085 (MD5) Previous issue date: 2022

Funding Acknowledgements Type of funding sources: None. Background Artificial Intelligence is an emergent tool in clinical practice for post processing of medical images. Machine Learning (ML) pipelines are created for data of interest extraction and algorithm application. A common issue in data extraction is represented by noisy datasets, like those of CMR studies, characterized by multiple images, acquired by different techniques, axis orientation and contrast timing. Purpose A ML pipeline for extraction of LGE images from raw DICOM data is presented. Additionally, steps for normalization of image number and automatically heart localization are outlined. Methods and Results 642 consecutive CMR studies were analyzed. Pipeline, Part 1. By looking at the metadata in raw files, ‘SequenceName’ tag was used to discard cine images, ‘ScanningSequence’ tag to select Gradient Recall and Inversion Recovery techniques (Inversion Time > 100 ms), ‘SequenceVariant’ tag to discard Steady State images (See Fig. 1). Orientation of the major axis was computed and ‘Axial’ or ‘Coronal’ images removed. Scans were grouped together by image orientation (requesting a min and max number of elements per group) and only the group with the largest number of files was selected. Finally, DICOMs were grouped by image shape (demanding a min number of elements), and only the series with the highest resolution was retained. Then, for each subject, the extracted series consists of a 3D-array (N,H,W), with N number of slices, and (H,W) image resolution. The attributes were not homogeneous between subjects. Pipeline, Part 2. Given a desired final number of slices and resolution, the 3D-array was reshaped through a spline interpolation. In order to have a focus on the heart, a Region of Interest (ROI) extractor was implemented, based on a YOLO network for object detection. The network was applied on all the slices (Fig. 2); then the images were cropped by keeping the largest bounding box. This step allowed us to remove the background by only selecting the relevant ROIs. To manage the data more easily, images were saved as a NumPy Array, while other useful Dicom metadata (e.g. weight, age, …) were stored using the json standard. At the end of the ML pipeline, images can be reduced to a common resolution and forwarded to ML algorithms. By using this pipeline, a great amount of information not needed for LGE analysis can be discarded, granting a significant reduction in terms of data storage. In our series, the original dataset extended for about 200 GB; by requesting 10 slices per subject with a resolution of 128 by 128 pixels (also extracting heart ROI) the final dimension was reduced to 108 MB. Conclusions In this work, we presented a post-processing pipeline for CRM images and LGE analysis. Given in input raw CRM the pipeline is able to (i) remove unuseful data, (ii) extract heart ROIs storing also Dicom metadata, (iii) normalize slices and image resolution, and (iv) store the processed CRM into ready-format for ML techniques. Fig.1:Pipeline Schematic RepresentationFig.2:YOLO Heart Extraction

Il volume offre un quadro organico della struttura giuridica della sicurezza sociale italiana e dei singoli istituti che la compongono, tenendo conto del formante giurisprudenziale e di quello dottrinale. A tal fine, ad una prima parte d'impostazione sistematica, che tiene conto delle due dimensioni dell'assistenza sociale e della previdenza sociale, con un apposito focus dedicato alla dimensione internazionale ed eurounitaria, segue l'esposizione dei fondamentali istituti della materia. La stesura del volume è frutto del lavoro di una pluralità di studiosi accomunati dall’interesse scientifico per il diritto della previdenza sociale: ferma restando la sinergica opera comune, ciascuno è autore di uno o più capitoli che tengono conto dei rispettivi percorsi di ricerca.

The main goal of the present work was to elucidate the genetic inheritance of the CPMMV resistance present in BRS Sublime, an Embrapa cultivar with carioca seed type identified as the most promising CPMMV resistance source in Brazil so far. Made available in DSpace on 2021-07-01T18:01:21Z (GMT). No. of bitstreams: 1 BIC-2021-p15-16.pdf: 233028 bytes, checksum: 496e0fbb242bc455445ba1821d32095e (MD5) Previous issue date: 2021

Anthracnose, caused by the fungus Colletotrichum lindemuthianum (Sacc. and Magn.), is one of the most important diseases affecting the common bean (Phaseolus vulgaris L.) in Brazil. Based on the level of susceptibility shown by the cultivars, the occurrence of environmental conditions favorable to the development of the disease, and the amount of initial inoculum present, losses in the seed yield and quality can range from 80 to 100%. The main goal of the present work was to identify the inheritance of anthracnose resistance in the Andean cultivar BRSMG Realce. Made available in DSpace on 2021-07-01T18:01:08Z (GMT). No. of bitstreams: 1 BIC-2021-p7-8.pdf: 273082 bytes, checksum: 96e210483712162c7a1415b85ee8040f (MD5) Previous issue date: 2021

The availability of high-density molecular markers in common bean has allowed to explore the genetic basis of important complex agronomic traits with increased resolution. Genome-Wide Association Studies (GWAS) and Regional Heritability Mapping (RHM) are two analytical approaches for the detection of genetic variants. We carried out GWAS and RHM for plant architecture, lodging and productivity across two important growing environments in Brazil in a germplasm of 188 common bean varieties using DArTseq genotyping strategies. The coefficient of determination of G · E interaction (c2 int) was equal to 17, 21 and 41%, respectively for the traits architecture, lodging, and productivity. Trait heritabilities were estimated at 0.81 (architecture), 0.79 (lodging) and 0.43 (productivity), and total genomic heritability accounted for large proportions (72% to 100%) of trait heritability. At the same probability threshold, three marker?trait associations were detected using GWAS, while RHM detected eight QTL encompassing 145 markers along five chromosomes. The proportion of genomic heritability explained by RHM was considerably higher (35.48 to 58.02) than that explained by GWAS (28.39 to 30.37). In general, RHM accounted for larger fractions of the additive genetic variance being captured by markers effects inside the defined regions. Nevertheless, a considerable proportion of the heritability is still missing (42% to 64%), probably due to LD between markers and genes and/or rare allele variants not sampled. RHM in autogamous species had the potential to identify larger-effect QTL combining allelic variants that could be effectively incorporated into whole-genome prediction models and tracked through breeding generations using marker-assisted selection. Made available in DSpace on 2018-09-18T00:41:40Z (GMT). No. of bitstreams: 1 2018M.DeonG3Genomewide.pdf: 1476838 bytes, checksum: ad2596aa80cc16027d13266642284b81 (MD5) Previous issue date: 2018-09-17

The identification and validation of candidate genes related to traits of interest is a time consuming and expensive process and the homology among genes from different species can facilitate the identification of genes of the target species from the genomic information of a model species. This study aimed to quantify the expression of homologous rice genes previously related to drought tolerance in Arabidopsis. Five genes (CPK6, PLDa, GluR2, CesA8, and EIN2) were identified in rice by the homology of the amino acid sequence between rice and Arabidopsis. The genotypes Douradão (drought tolerant) and Primavera (drought susceptible) were subjected to a water deficit experiment, and subsequently evaluated for gene expression by qPCR for the five homologous and Lsi1 genes. The qPCR analysis clearly showed that the five homologous genes were expressed in rice, which is an indication that these genes could preserve their function in rice as a response to drought. In Douradão, of the five homologous genes, all but OsGluR2 displayed an increase in the average expression in drought treatment when compared to the control, while in Primavera, the average expression of the five genes did not differ between the control and drought treatment. In Douradão, the OsPLDa1, which showed the higher expression level in drought in relation to the control (10.82), significantly increased the gene expression in the leaf and root tissues as a response to drought, in both vegetative and reproductive stages, whereas in Primavera, this gene was suppressed in both tissues and stages under drought. Therefore, the OsPLDa1 gene was the most important in relation to drought response and is an interesting candidate for further studies in developing rice cultivars that are more tolerant to this stress.

The establishment of a specific Marker-Assisted Selection Facility at the Embrapa Rice and Beans Biotechnology Laboratory, in 2014, has better supported the routine analysis with molecular markers demanded by the Embrapa Common Bean Breeding Program. In addition, it has also supported other Embrapa plant breeding programs, such as rice and cotton.

The main goal of this work was to characterize the genetic variability of genomic regions flanking the anthracnose resistance locus Co-4 aiming to develop SNP markers for specific identification of the different alleles presented by this locus, mainly of the Co-42.

In an attempt to develop a potential new core mapping population for common bean, the BIOAGRO/UFV and Embrapa bean research groups developed a RIL population with 500 lines from crosses between Rudá (Mesoamerican) and AND 277 (Andean).

O objetivo deste trabalho foi determinar o potencial produtivo e a interação entre genótipos e ambientes em 550 acessos da Coleção Nuclear de Arroz da Embrapa. O desempenho, a adaptação e a estabilidade produtiva de cada genótipo foram avaliados por meio da metodologia de análise dos efeitos principais aditivos e interações multiplicativas (AMMI), em nove experimentos de campo, realizados em seis Estados, em condição de sequeiro e irrigada, durante três anos agrícolas. Foi realizada a análise por meio de modelos lineares mistos, e as estimativas de componentes de variância foram obtidas pelo método de máxima verossimilhança residual (REML), com aplicação do procedimento de melhor predição linear não viesada (BLUP) para a predição dos valores genéticos dos efeitos aleatórios (EBLUP) associados a cada um dos acessos. O grupo de acessos com melhor desempenho foi o de linhagens e cultivares brasileiras (LCB), conforme o esperado. No entanto, foram identificadas variedades tradicionais (VT) entre os genótipos mais produtivos, o que mostra o potencial deste grupo de germoplasma em contribuir com novas fontes de variabilidade genética para programas de melhoramento. Foram identificados acessos superiores quanto à estabilidade, adaptabilidade e produtividade de grãos, entre os quais destacam-se CA880078, CA840182 e CNA00091.

We isolated and characterized 12 microsatellite loci for Tibouchina papyrus (Melastomataceae), an endangered species with narrow and disjunct range, endemics to a few localities in ?cerrado rupestre? from Central Brazil. These microsatellites were obtained by sequencing of a genomic shotgun library for primer design. Leaves from 96 individuals collected in the three known local populations were genotyped using the 12 primers designed to analyze the polymorphisms at each locus. The number of alleles per locus ranged from one to six; two loci were monomorphic. Among the polymorphic loci, expected heterozygosities ranged from 0.161 to 0.714. Combined paternity exclusion probability was 0.957 and combined genetic identity (0.051) was high for studies on parentage. Tibouchina papyrus is a rare and endemic tree species of outcrop quartzite and sandstone soils, with highly isolated populations, which may have lead to the low degree of polymorphism that we detected. Also, motifs of most loci are larger than dinucleotide, which typically display lower levels of polymorphism. Made available in DSpace on 2011-04-09T14:47:26Z (GMT). No. of bitstreams: 1 gmr.pdf: 283155 bytes, checksum: a4f24af854ccf7804dd2d5543280ff36 (MD5) Previous issue date: 2011-03-23

O presente trabalho apresenta uma nova metodologia de estimação de fasores na presença de decaimento DC exponencial e de harmônicos ímpares no sinal. As estimações são realizadas em meio ciclo mais três amostras da componente fundamental do sistema. O método é baseado na estimação dos parâmetros do decaimento DC exponencial presentes no sinal. Para tal, são utilizadas algumas técnicas de processamento de sinais tais como o janelamento, modulação, a DTFT (Discret Time Fourier Transform) e buscas em tabelas. O desempenho do novo método é avaliado frente a dois métodos de estimação tradicionais, o DFT e o Least Square Error, ambos de meio ciclo.

A qualidade do vinho é uma resultante direta da qualidade da uva. Por sua vez, nas diferentes regiões de produção de vinho do mundo, a qualidade da uva é fortemente influenciada pelo clima Vitícola . Alguns trabalhos já sinalizam para a possibilidade de produção de uvas para vinhos em Minas Gerais, especialmente considerando a produção na estação seca. Neste sentido, este estudo tem por objetivo caracterizar o potencial climático existente ao longo do ano em diferentes regiões do estado de Minas Gerais, buscando-se alternativas para a produção de vinhos finos. Não se pretende fazer uma abordagem climatológica ampla para todo o estado, mas tão-somente enfocar a questão sob o angulo de seu potencial vitivinicultor, uma alternativa promissora para a agroindústria do Estado. Made available in DSpace on 2016-08-05T07:27:33Z (GMT). No. of bitstreams: 1 toniettovianelloregina2006.pdf: 2875776 bytes, checksum: 2bf2b09f4a6a66ef8476624dc3293949 (MD5) Previous issue date: 2006-12-04

Made available in DSpace on 2018-05-18T00:38:46Z (GMT). No. of bitstreams: 1 ID21549.pdf: 211213 bytes, checksum: f2c604005d7dbad07051facb148b4317 (MD5) Previous issue date: 1999-09-03 Producao Cientifica/CENARGEN/97