RESUMEN

Tropical forage grasses, particularly those belonging to the Urochloa genus, play a crucial role in cattle production and serve as the main food source for animals in tropical and subtropical regions. The majority of these species are apomictic and tetraploid, highlighting the significance of U. ruziziensis, a sexual diploid species that can be tetraploidized for use in interspecific crosses with apomictic species. As a means to support breeding programs, our study investigates the feasibility of genome-wide family prediction in U. ruziziensis families to predict agronomic traits. Fifty half-sibling families were assessed for green matter yield, dry matter yield, regrowth capacity, leaf dry matter, and stem dry matter across different clippings established in contrasting seasons with varying available water capacity. Genotyping was performed using a genotyping-by-sequencing approach based on DNA samples from family pools. In addition to conventional genomic prediction methods, machine learning and feature selection algorithms were employed to reduce the necessary number of markers for prediction and enhance predictive accuracy across phenotypes. To explore the regulation of agronomic traits, our study evaluated the significance of selected markers for prediction using a tree-based approach, potentially linking these regions to quantitative trait loci (QTLs). In a multiomic approach, genes from the species transcriptome were mapped and correlated to those markers. A gene coexpression network was modeled with gene expression estimates from a diverse set of U. ruziziensis genotypes, enabling a comprehensive investigation of molecular mechanisms associated with these regions. The heritabilities of the evaluated traits ranged from 0.44 to 0.92. A total of 28,106 filtered SNPs were used to predict phenotypic measurements, achieving a mean predictive ability of 0.762. By employing feature selection techniques, we could reduce the dimensionality of SNP datasets, revealing potential genotype-phenotype associations. The functional annotation of genes near these markers revealed associations with auxin transport and biosynthesis of lignin, flavonol, and folic acid. Further exploration with the gene coexpression network uncovered associations with DNA metabolism, stress response, and circadian rhythm. These genes and regions represent important targets for expanding our understanding of the metabolic regulation of agronomic traits and offer valuable insights applicable to species breeding. Our work represents an innovative contribution to molecular breeding techniques for tropical forages, presenting a viable marker-assisted breeding approach and identifying target regions for future molecular studies on these agronomic traits.

RESUMEN

Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) is a polyphagous pest species capable of feeding on almost all forage and grain crops, although the food quality for the larvae likely varies among plant species and cultivars. The cultivation of grass forage species with grains has increasingly been adopted in Brazil, within both no-tillage and crop-livestock integration systems. In this study, we evaluated the performance of S. frugiperda larvae on 14 forage cultivars of Brachiaria, Panicum, and Cynodon, which are widely used in integrated cropping systems in Brazil. The biological performance of S. frugiperda varied among the cultivars. The larval survival rates were lower on Panicum maximum 'Massai' and P. maximum 'Tamani' cultivars. The insects had the highest performance indexes on Brachiaria brizantha 'Paiaguás', B. brizantha 'Marandu', and B. brizantha 'Xaraés' cultivars, followed by Brachiaria ruziziensis, previously proposed as a standard grass forage for comparisons with other species. On P. maximum, the insect had the lowest performance indexes, with values equal to zero when feeding on the P. maximum 'Massai' and 'Tamani' cultivars. These results will help make management decisions when cultivating grass forage plants in crop production systems in which S. frugiperda infestation is of concern.

RESUMEN

Pastures based on perennial monocotyledonous plants are the principal source of nutrition for ruminant livestock in tropical and subtropical areas across the globe. The Urochloa genus comprises important species used in pastures, and these mainly include Urochloa brizantha, Urochloa decumbens, Urochloa humidicola, and Urochloa ruziziensis. Despite their economic relevance, there is an absence of genomic-level information for these species, and this lack is mainly due to genomic complexity, including polyploidy, high heterozygosity, and genomes with a high repeat content, which hinders advances in molecular approaches to genetic improvement. Next-generation sequencing techniques have enabled the recent release of reference genomes, genetic linkage maps, and transcriptome sequences, and this information helps improve our understanding of the genetic architecture and molecular mechanisms involved in relevant traits, such as the apomictic reproductive mode. However, more concerted research efforts are still needed to characterize germplasm resources and identify molecular markers and genes associated with target traits. In addition, the implementation of genomic selection and gene editing is needed to reduce the breeding time and expenditure. In this review, we highlight the importance and characteristics of the four main species of Urochloa used in pastures and discuss the current findings from genetic and genomic studies and research gaps that should be addressed in future research.

RESUMEN

Artificial hybridization plays a fundamental role in plant breeding programs since it generates new genotypic combinations that can result in desirable phenotypes. Depending on the species and mode of reproduction, controlled crosses may be challenging, and contaminating individuals can be introduced accidentally. In this context, the identification of such contaminants is important to avoid compromising further selection cycles, as well as genetic and genomic studies. The main objective of this work was to propose an automated multivariate methodology for the detection and classification of putative contaminants, including apomictic clones (ACs), self-fertilized individuals, half-siblings (HSs), and full contaminants (FCs), in biparental polyploid progenies of tropical forage grasses. We established a pipeline to identify contaminants in genotyping-by-sequencing (GBS) data encoded as allele dosages of single nucleotide polymorphism (SNP) markers by integrating principal component analysis (PCA), genotypic analysis (GA) measures based on Mendelian segregation, and clustering analysis (CA). The combination of these methods allowed for the correct identification of all contaminants in all simulated progenies and the detection of putative contaminants in three real progenies of tropical forage grasses, providing an easy and promising methodology for the identification of contaminants in biparental progenies of tetraploid and hexaploid species. The proposed pipeline was made available through the polyCID Shiny app and can be easily coupled with traditional genetic approaches, such as linkage map construction, thereby increasing the efficiency of breeding programs.

RESUMEN

Forage dry matter is the main source of nutrients in the diet of ruminant animals. Thus, this trait is evaluated in most forage breeding programs with the objective of increasing the yield. Novel solutions combining unmanned aerial vehicles (UAVs) and computer vision are crucial to increase the efficiency of forage breeding programs, to support high-throughput phenotyping (HTP), aiming to estimate parameters correlated to important traits. The main goal of this study was to propose a convolutional neural network (CNN) approach using UAV-RGB imagery to estimate dry matter yield traits in a guineagrass breeding program. For this, an experiment composed of 330 plots of full-sib families and checks conducted at Embrapa Beef Cattle, Brazil, was used. The image dataset was composed of images obtained with an RGB sensor embedded in a Phantom 4 PRO. The traits leaf dry matter yield (LDMY) and total dry matter yield (TDMY) were obtained by conventional agronomic methodology and considered as the ground-truth data. Different CNN architectures were analyzed, such as AlexNet, ResNeXt50, DarkNet53, and two networks proposed recently for related tasks named MaCNN and LF-CNN. Pretrained AlexNet and ResNeXt50 architectures were also studied. Ten-fold cross-validation was used for training and testing the model. Estimates of DMY traits by each CNN architecture were considered as new HTP traits to compare with real traits. Pearson correlation coefficient r between real and HTP traits ranged from 0.62 to 0.79 for LDMY and from 0.60 to 0.76 for TDMY; root square mean error (RSME) ranged from 286.24 to 366.93 kg·ha-1 for LDMY and from 413.07 to 506.56 kg·ha-1 for TDMY. All the CNNs generated heritable HTP traits, except LF-CNN for LDMY and AlexNet for TDMY. Genetic correlations between real and HTP traits were high but varied according to the CNN architecture. HTP trait from ResNeXt50 pretrained achieved the best results for indirect selection regardless of the dry matter trait. This demonstrates that CNNs with remote sensing data are highly promising for HTP for dry matter yield traits in forage breeding programs.

Asunto(s)

RESUMEN

The world population is expected to be larger and wealthier over the next few decades and will require more animal products, such as milk and beef. Tropical regions have great potential to meet this growing global demand, where pasturelands play a major role in supporting increased animal production. Better forage is required in consonance with improved sustainability as the planted area should not increase and larger areas cultivated with one or a few forage species should be avoided. Although, conventional tropical forage breeding has successfully released well-adapted and high-yielding cultivars over the last few decades, genetic gains from these programs have been low in view of the growing food demand worldwide. To guarantee their future impact on livestock production, breeding programs should leverage genotyping, phenotyping, and envirotyping strategies to increase genetic gains. Genomic selection (GS) and genome-wide association studies play a primary role in this process, with the advantage of increasing genetic gain due to greater selection accuracy, reduced cycle time, and increased number of individuals that can be evaluated. This strategy provides solutions to bottlenecks faced by conventional breeding methods, including long breeding cycles and difficulties to evaluate complex traits. Initial results from implementing GS in tropical forage grasses (TFGs) are promising with notable improvements over phenotypic selection alone. However, the practical impact of GS in TFG breeding programs remains unclear. The development of appropriately sized training populations is essential for the evaluation and validation of selection markers based on estimated breeding values. Large panels of single-nucleotide polymorphism markers in different tropical forage species are required for multiple application targets at a reduced cost. In this context, this review highlights the current challenges, achievements, availability, and development of genomic resources and statistical methods for the implementation of GS in TFGs. Additionally, the prediction accuracies from recent experiments and the potential to harness diversity from genebanks are discussed. Although, GS in TFGs is still incipient, the advances in genomic tools and statistical models will speed up its implementation in the foreseeable future. All TFG breeding programs should be prepared for these changes.

RESUMEN

Monitoring biomass of forages in experimental plots and livestock farms is a time-consuming, expensive, and biased task. Thus, non-destructive, accurate, precise, and quick phenotyping strategies for biomass yield are needed. To promote high-throughput phenotyping in forages, we propose and evaluate the use of deep learning-based methods and UAV (Unmanned Aerial Vehicle)-based RGB images to estimate the value of biomass yield by different genotypes of the forage grass species Panicum maximum Jacq. Experiments were conducted in the Brazilian Cerrado with 110 genotypes with three replications, totaling 330 plots. Two regression models based on Convolutional Neural Networks (CNNs) named AlexNet and ResNet18 were evaluated, and compared to VGGNet-adopted in previous work in the same thematic for other grass species. The predictions returned by the models reached a correlation of 0.88 and a mean absolute error of 12.98% using AlexNet considering pre-training and data augmentation. This proposal may contribute to forage biomass estimation in breeding populations and livestock areas, as well as to reduce the labor in the field.

Asunto(s)

RESUMEN

Taxonomicamente, Stylosanthes guianensis está dividida em quatro variedades botânicas: var. guianensis, var. pauciflora, var. canescens e var. microcephala. A cultivar 'BRS Bela' é uma das duas cultivares dessa leguminosa forrageira registradas no Brasil e é composta por uma mistura física de sementes de quatro acessos pertencentes a variedades botânicas ainda desconhecidas. O objetivo deste trabalho foi caracterizar a variabilidade genética entre os quatro acessos que compõem esta cultivar e determinar suas inter-relações com acessos de variedades botânicas conhecidas, usando a técnica de polimorfismos de DNA amplificados ao acaso (RAPD). Foram analisados 10 primers decâmeros em 36 acessos, do banco de germoplasma da Embrapa gado de Corte, de S. guianensis: 14 da variedade botânica pauciflora, 11 da var. guianensis, quatro da var. canescens, três da var. microcephala e os quatro acessos da cultivar 'BRS Bela'. As bandas amplificadas foram analisadas como dados binários e uma matriz de similaridade genética foi gerada, usando coeficiente de Jaccard. Com base na dissimilaridade genética, os acessos foram agrupados pelos métodos de ligação média entre grupos (UPGMA) e Tocher. A média de similaridade genética dentro das variedades botânicas foi de 0,72 para var. pauciflora, 0,63 para var. microcephala, 0,62 para var. canescens e 0,46 para var. guianensis. Entre os quatro acessos da cultivar 'BRS Bela', esta média foi de 0,62. Ambos os métodos de agrupamento geraram resultados similares e tenderam a agrupar os acessos da mesma variedade botânica. Os acessos da cultivar 'BRS Bela' foram agrupados com acessos var. guianensis. Os resultados mostram que há variabilidade genética dentro das variedades botânicas de S. guianensis e entre os acessos da cultivar 'BRS Bela' e que existe uma tendência ao agrupamento por variedade botânica.

Taxonomically Stylosanthes guianensis is divided in four botanical varieties: var. guianensis, var. pauciflora, var. canescens and var. microcephala. The 'BRS Bela' cultivar is one of the two cultivars of this forage legume registered on Brazil, it is made up of a physical mixture of seeds of four accessions of unknown botanical varieties. The objective in this research was to characterize the genetic variability among four accessions of the cultivar 'BRS Bela' and to determine its genetic relationship with others accessions of known botanical varieties, using the random amplified polymorphic DNA (RAPD) technique. Ten decamer primers were evaluated in 36 accessions, from the germoplasm bank of Embrapa Beef Cattle, of S. guianensis: 14 of the botanical variety pauciflora, 11 of var. guianensis, four of var. canescens, three of var. microcephala and the four accessions of cultivar 'BRS Bela'. The amplified bands were analyzed as binary data and a matrix of genetic similarity was generated using the coefficient of Jaccard. Genetic dissimilarity data were utilized for clustering the accessions by not weighted pair-group method with arithmetical average (UPGMA) and Tocher methods. The mean genetic similarity within of the botanic varieties was of 0.72 for var. pauciflora, 0.63 for var. microcephala, 0.62 for var. canescens and 0.46 for var. guianensis. Among the four accessions of cultivar 'BRS Bela' this mean was 0.62. Both methods of clustering generated similar results and showed a tendency to cluster the accessions of the same botanical variety. The accessions of cultivar 'BRS Bela' were grouped with accessions of botanical variety guianensis. The results show that there is genetic variability within of the botanical varieties of S. guianensis and among the accessions of the cultivar 'BRS Bela' and that there is a tendency to the clustering by botanical variety.

RESUMEN

Taxonomically Stylosanthes guianensis is divided in four botanical varieties: var. guianensis, var. pauciflora, var. canescens and var. microcephala. The 'BRS Bela' cultivar is one of the two cultivars of this forage legume registered on Brazil, it is made up of a physical mixture of seeds of four accessions of unknown botanical varieties. The objective in this research was to characterize the genetic variability among four accessions of the cultivar 'BRS Bela' and to determine its genetic relationship with others accessions of known botanical varieties, using the random amplified polymorphic DNA (RAPD) technique. Ten decamer primers were evaluated in 36 accessions, from the germoplasm bank of Embrapa Beef Cattle, of S. guianensis: 14 of the botanical variety pauciflora, 11 of var. guianensis, four of var. canescens, three of var. microcephala and the four accessions of cultivar 'BRS Bela'. The amplified bands were analyzed as binary data and a matrix of genetic similarity was generated using the coefficient of Jaccard. Genetic dissimilarity data were utilized for clustering the accessions by not weighted pair-group method with arithmetical average (UPGMA) and Tocher methods. The mean genetic similarity within of the botanic varieties was of 0.72 for var. pauciflora, 0.63 for var. microcephala, 0.62 for var. canescens and 0.46 for var. guianensis. Among the four accessions of cultivar 'BRS Bela' this mean was 0.62. Both methods of clustering generated similar results and showed a tendency to cluster the accessions of the same botanical variety. The accessions of cultivar 'BRS Bela' were grouped with accessions of botanical variety guianensis. The results show that there is genetic variability within of the botanical varieties of S. guianensis and among the accessions of the cultivar 'BRS Bela' and that there is a tendency to the clustering by botanical variety.

Taxonomicamente, Stylosanthes guianensis está dividida em quatro variedades botânicas: var. guianensis, var. pauciflora, var. canescens e var. microcephala. A cultivar 'BRS Bela' é uma das duas cultivares dessa leguminosa forrageira registradas no Brasil e é composta por uma mistura física de sementes de quatro acessos pertencentes a variedades botânicas ainda desconhecidas. O objetivo deste trabalho foi caracterizar a variabilidade genética entre os quatro acessos que compõem esta cultivar e determinar suas inter-relações com acessos de variedades botânicas conhecidas, usando a técnica de polimorfismos de DNA amplificados ao acaso (RAPD). Foram analisados 10 primers decâmeros em 36 acessos, do banco de germoplasma da Embrapa gado de Corte, de S. guianensis: 14 da variedade botânica pauciflora, 11 da var. guianensis, quatro da var. canescens, três da var. microcephala e os quatro acessos da cultivar 'BRS Bela'. As bandas amplificadas foram analisadas como dados binários e uma matriz de similaridade genética foi gerada, usando coeficiente de Jaccard. Com base na dissimilaridade genética, os acessos foram agrupados pelos métodos de ligação média entre grupos (UPGMA) e Tocher. A média de similaridade genética dentro das variedades botânicas foi de 0,72 para var. pauciflora, 0,63 para var. microcephala, 0,62 para var. canescens e 0,46 para var. guianensis. Entre os quatro acessos da cultivar 'BRS Bela', esta média foi de 0,62. Ambos os métodos de agrupamento geraram resultados similares e tenderam a agrupar os acessos da mesma variedade botânica. Os acessos da cultivar 'BRS Bela' foram agrupados com acessos var. guianensis. Os resultados mostram que há variabilidade genética dentro das variedades botânicas de S. guianensis e entre os acessos da cultivar 'BRS Bela' e que existe uma tendência ao agrupamento por variedade botânica.

RESUMEN

Taxonomically Stylosanthes guianensis is divided in four botanical varieties: var. guianensis, var. pauciflora, var. canescens and var. microcephala. The 'BRS Bela' cultivar is one of the two cultivars of this forage legume registered on Brazil, it is made up of a physical mixture of seeds of four accessions of unknown botanical varieties. The objective in this research was to characterize the genetic variability among four accessions of the cultivar 'BRS Bela' and to determine its genetic relationship with others accessions of known botanical varieties, using the random amplified polymorphic DNA (RAPD) technique. Ten decamer primers were evaluated in 36 accessions, from the germoplasm bank of Embrapa Beef Cattle, of S. guianensis: 14 of the botanical variety pauciflora, 11 of var. guianensis, four of var. canescens, three of var. microcephala and the four accessions of cultivar 'BRS Bela'. The amplified bands were analyzed as binary data and a matrix of genetic similarity was generated using the coefficient of Jaccard. Genetic dissimilarity data were utilized for clustering the accessions by not weighted pair-group method with arithmetical average (UPGMA) and Tocher methods. The mean genetic similarity within of the botanic varieties was of 0.72 for var. pauciflora, 0.63 for var. microcephala, 0.62 for var. canescens and 0.46 for var. guianensis. Among the four accessions of cultivar 'BRS Bela' this mean was 0.62. Both methods of clustering generated similar results and showed a tendency to cluster the accessions of the same botanical variety. The accessions of cultivar 'BRS Bela' were grouped with accessions of botanical variety guianensis. The results show that there is genetic variability within of the botanical varieties of S. guianensis and among the accessions of the cultivar 'BRS Bela' and that there is a tendency to the clustering by botanical variety.

Taxonomicamente, Stylosanthes guianensis está dividida em quatro variedades botânicas: var. guianensis, var. pauciflora, var. canescens e var. microcephala. A cultivar 'BRS Bela' é uma das duas cultivares dessa leguminosa forrageira registradas no Brasil e é composta por uma mistura física de sementes de quatro acessos pertencentes a variedades botânicas ainda desconhecidas. O objetivo deste trabalho foi caracterizar a variabilidade genética entre os quatro acessos que compõem esta cultivar e determinar suas inter-relações com acessos de variedades botânicas conhecidas, usando a técnica de polimorfismos de DNA amplificados ao acaso (RAPD). Foram analisados 10 primers decâmeros em 36 acessos, do banco de germoplasma da Embrapa gado de Corte, de S. guianensis: 14 da variedade botânica pauciflora, 11 da var. guianensis, quatro da var. canescens, três da var. microcephala e os quatro acessos da cultivar 'BRS Bela'. As bandas amplificadas foram analisadas como dados binários e uma matriz de similaridade genética foi gerada, usando coeficiente de Jaccard. Com base na dissimilaridade genética, os acessos foram agrupados pelos métodos de ligação média entre grupos (UPGMA) e Tocher. A média de similaridade genética dentro das variedades botânicas foi de 0,72 para var. pauciflora, 0,63 para var. microcephala, 0,62 para var. canescens e 0,46 para var. guianensis. Entre os quatro acessos da cultivar 'BRS Bela', esta média foi de 0,62. Ambos os métodos de agrupamento geraram resultados similares e tenderam a agrupar os acessos da mesma variedade botânica. Os acessos da cultivar 'BRS Bela' foram agrupados com acessos var. guianensis. Os resultados mostram que há variabilidade genética dentro das variedades botânicas de S. guianensis e entre os acessos da cultivar 'BRS Bela' e que existe uma tendência ao agrupamento por variedade botânica.

RESUMEN

Taxonomically Stylosanthes guianensis is divided in four botanical varieties: var. guianensis, var. pauciflora, var. canescens and var. microcephala. The 'BRS Bela' cultivar is one of the two cultivars of this forage legume registered on Brazil, it is made up of a physical mixture of seeds of four accessions of unknown botanical varieties. The objective in this research was to characterize the genetic variability among four accessions of the cultivar 'BRS Bela' and to determine its genetic relationship with others accessions of known botanical varieties, using the random amplified polymorphic DNA (RAPD) technique. Ten decamer primers were evaluated in 36 accessions, from the germoplasm bank of Embrapa Beef Cattle, of S. guianensis: 14 of the botanical variety pauciflora, 11 of var. guianensis, four of var. canescens, three of var. microcephala and the four accessions of cultivar 'BRS Bela'. The amplified bands were analyzed as binary data and a matrix of genetic similarity was generated using the coefficient of Jaccard. Genetic dissimilarity data were utilized for clustering the accessions by not weighted pair-group method with arithmetical average (UPGMA) and Tocher methods. The mean genetic similarity within of the botanic varieties was of 0.72 for var. pauciflora, 0.63 for var. microcephala, 0.62 for var. canescens and 0.46 for var. guianensis. Among the four accessions of cultivar 'BRS Bela' this mean was 0.62. Both methods of clustering generated similar results and showed a tendency to cluster the accessions of the same botanical variety. The accessions of cultivar 'BRS Bela' were grouped with accessions of botanical variety guianensis. The results show that there is genetic variability within of the botanical varieties of S. guianensis and among the accessions of the cultivar 'BRS Bela' and that there is a tendency to the clustering by botanical variety.

Taxonomicamente, Stylosanthes guianensis está dividida em quatro variedades botânicas: var. guianensis, var. pauciflora, var. canescens e var. microcephala. A cultivar 'BRS Bela' é uma das duas cultivares dessa leguminosa forrageira registradas no Brasil e é composta por uma mistura física de sementes de quatro acessos pertencentes a variedades botânicas ainda desconhecidas. O objetivo deste trabalho foi caracterizar a variabilidade genética entre os quatro acessos que compõem esta cultivar e determinar suas inter-relações com acessos de variedades botânicas conhecidas, usando a técnica de polimorfismos de DNA amplificados ao acaso (RAPD). Foram analisados 10 primers decâmeros em 36 acessos, do banco de germoplasma da Embrapa gado de Corte, de S. guianensis: 14 da variedade botânica pauciflora, 11 da var. guianensis, quatro da var. canescens, três da var. microcephala e os quatro acessos da cultivar 'BRS Bela'. As bandas amplificadas foram analisadas como dados binários e uma matriz de similaridade genética foi gerada, usando coeficiente de Jaccard. Com base na dissimilaridade genética, os acessos foram agrupados pelos métodos de ligação média entre grupos (UPGMA) e Tocher. A média de similaridade genética dentro das variedades botânicas foi de 0,72 para var. pauciflora, 0,63 para var. microcephala, 0,62 para var. canescens e 0,46 para var. guianensis. Entre os quatro acessos da cultivar 'BRS Bela', esta média foi de 0,62. Ambos os métodos de agrupamento geraram resultados similares e tenderam a agrupar os acessos da mesma variedade botânica. Os acessos da cultivar 'BRS Bela' foram agrupados com acessos var. guianensis. Os resultados mostram que há variabilidade genética dentro das variedades botânicas de S. guianensis e entre os acessos da cultivar 'BRS Bela' e que existe uma tendência ao agrupamento por variedade botânica.