ABSTRACT. To consider the different characteristics of soybean seeds for designing and regulating the post-harvest equipment, we evaluated the similarities in the physical properties of soybean cultivars in this study. Two-hundred soybean seeds from 40 genetically modified cultivars were collected in packages to measure the physical properties of the seeds. First, principal component analysis was performed to verify the interrelationships between the variables and soybean cultivars. Next, a boxplot was constructed for each variable, considering the groups obtained after analyzing the main components. Finally, a scatterplot containing the Pearson's correlations between the variables was constructed. We identified two clusters of cultivars: C1 and C2. The unit-specific mass was the physical property that contributed the most to the formation of C1, whereas the other physical properties contributed to the formation of C2. Soybean cultivars comprising C1 were similar to each other only in unit specific mass, and the cultivars allocated to group C2 were similar according to all the other properties evaluated. These results can serve as a guideline for genotype selection for soybean genetic improvement to minimize variations in the physical characteristics of the seeds and obtain greater efficiency in the processing stages. Thus, the equipment manufacturing industry and seed processing units can implement projects and equipment adjustments to manage the post-harvest and seeding processes of soybean seeds efficiently. ABSTRACT postharvest post harvest study Twohundred Two hundred 4 First Next variable components Finally Pearsons Pearson s C unitspecific stages Thus efficiently

Abstract Species of the genus Cynodon are among the most cultivated forage crops in the world due to their high yield and nutritional quality, and its use in cattle feeding has been associated with gains in animal weight and increased milk production. The objective of this study was to model covariance structures in Cynodon spp. clones and study the changes in ranking of the selected genotypes, since it is believed that affects the ranking of genotypes. A total of 202 genotypes were evaluated in an experiment conducted in an augmented block design with four replications and four harvests. The genotypes were assessed for plant height, green weight, percentage of dry matter, and plant vigor. Nineteen repeated measures models with different covariance structures were tested. The best-fitted model adopts the CORH covariance structure for the genetic effects. Correct modeling of the covariance structure affected the ranking of genotypes in all variables evaluated. quality production spp 20 harvests height matter vigor tested bestfitted best fitted effects 2

RESUMO Num cenário de mudanças climáticas, um produtor que decidisse investir em um sistema de integração Lavoura-Floresta, ao invés de investir na produção convencional, se beneficiaria. O presente trabalho, que é um modelo de agricultura de baixa emissão de carbono, teve como objetivo avaliar o efeito do sombreamento e a dependência espacial dos índices da cultura da soja em integração com floresta de eucalipto. O delineamento adotado foi o de blocos ao acaso com seis repetições e tratamentos compostos por diferentes distâncias horizontais sobre eucalipto (30, 34, 38, 42 e 46 m), em duas áreas distintas, uma com presença de eucalipto nas regiões norte e oeste e outra sem a presença do eucalipto na parte norte da área de cultivo da soja. Avaliaram-se os fótons fotossinteticamente ativos em quatro épocas diferentes, o estande de plantas, a altura de plantas e o índice de vegetação após 30 e 60 dias de germinação e por fim a massa de mil grãos e a produtividade. Como resultados, todos atributos apresentaram dependência espacial, exceto produtividade da soja. Como considerações finais, o espaçamento de 34 m entre os eucaliptos promove menor sombreamento. A maior produção média de grãos na área foi encontrada na presença de eucalipto nas laterais oeste e norte da área de cultivo. climáticas LavouraFloresta, LavouraFloresta Lavoura Floresta, Floresta Lavoura-Floresta convencional beneficiaria trabalho carbono 30, (30 38 4 m, , m) distintas Avaliaramse Avaliaram 3 6 resultados finais (3 (

ABSTRACT In a climate change scenario, a producer who decides to invest in a Crop-Forest integration system, instead of investing in conventional production, benefits. The objective the present work, which is a low carbon emission agriculture model, aimed to evaluate the effect of shading and the spatial dependence of soybean crop indices in integration with eucalyptus forest. The design adopted was that of randomized blocks with six replications and treatments composed of different horizontal distances about eucalyptus (30, 34, 38, 42 and 46 m), in two distinct areas, one with the presence of eucalyptus forest in the north and west phase and another one without the presence of eucalyptus in the northern part of the soybean cultivation area. Evaluated the photosynthetically active photons at four different times, the plant stand, plant height, and the vegetation index after 30 and 60 days of germination and finally the mass of a thousand grains and productivity. As a result, all attributes showed spatial dependence, except soybean productivity. As final considerations, the spacing of 34 m between the eucalyptus trees promote less shading. The highest average grain production in the area was found in the presence of eucalyptus on the west and north sides of the cultivation area. scenario CropForest Crop Forest system benefits work model 30, (30 38 4 m, , m) areas times stand height 3 6 productivity result considerations (3 (

ABSTRACT Genetic diversity is important for conservation and genetic improvement of common beans. This study aimed to estimate the genetic diversity among common bean genotypes from the Embrapa germplasm collection using univariate and multivariate analyses. The experiment was conducted in the region of Aquidauana-MS, at the State University of Mato Grosso do Sul, in a randomized block design with three replications and twenty-three genotypes, in 2021. The agronomic traits considered in the study were plant height, height to first pod, number of branches, number of pods per plant, number of grains per pod, hundred-grain mass, and grain yield. Descriptive analysis, univariate and multivariate variance analyses, mean clustering, phenotypic correlation network, UPGMA analysis (Unweighted Pair Group Method with Arithmetic Mean), and canonical variables were used to examine the data. The genotypes showed significant differences for plant height, height to first pod, number of branches per plant, number of pods per plant and yield, with potential for the selection of these traits. CNFC17278, CNFC17305, CNFC19133 and CNFC19198 showed superior yield potential compared to the other lines. The combined use of statistical methodologies can provide more information about the genotypes studied. beans analyses AquidauanaMS, AquidauanaMS Aquidauana MS, MS Aquidauana-MS Sul twentythree twenty 2021 pod hundredgrain hundred mass clustering network Unweighted Mean, Mean , Mean) data CNFC17278 CNFC CNFC17305 CNFC1913 CNFC1919 lines studied 202 CNFC1727 CNFC1730 CNFC191 20 CNFC172 CNFC173 CNFC19 2 CNFC17 CNFC1

Resumo O objetivo deste trabalho foi avaliar como a herdabilidade e o número de locos de características quantitativas (QTL) que controla a característica podem influenciar na predição do valor genético por meio de métodos de seleção genômica. Uma equação de predição foi estabelecida para estimar a correlação genética baseada na correlação fenotípica, tendo-se utilizado uma população F2 com 1.000 indivíduos, simulados em diferentes cenários. A herdabilidade (5, 20, 40, 60, 80 e 99%) e o número de QTL (60, 120, 180 e 240) variaram em cada cenário. Os quatro seguintes métodos de seleção genômica foram utilizados nas análises: ridge-regression best linear unbiased prediction (RR-BLUP), BLUP genômico (GBLUP), método bayesiano de estimação B (Bayes B) e reproducing kernel Hilbert spaces regression (RKHS). As habilidades preditivas fenotípicas e genotípicas foram calculadas para cada método, e o teste de Tukey foi utilizado para comparação de médias. O efeito da herdabilidade e do número de QTL que controla a característica foi avaliado por análise de regressão. O teste de Tukey revelou diferenças entre os métodos, sendo que Bayes B e RR-BLUP foram superiores aos demais em quase todos os cenários. A herdabilidade apresenta relação linear positiva com a capacidade preditiva fenotípica e relação quadrática positiva com a capacidade preditiva genotípica. O número de QTL controlando a característica não tem relação com a capacidade preditiva fenotípica e genotípica. (QTL tendose tendo se F 1000 1 000 1.00 indivíduos cenários 5, 5 (5 20 40 60 8 99% 99 (60 120 18 240 cenário análises ridgeregression ridge RRBLUP, RRBLUP RR , (RR-BLUP) GBLUP, GBLUP (GBLUP) RKHS. RKHS . (RKHS) médias regressão genotípica 100 00 1.0 ( 2 4 6 9 (6 12 24 (RR-BLUP (GBLUP (RKHS 10 0 1.

Abstract The objective of this work was to evaluate how heritability and the number of quantitative trait loci (QTL) controlling the trait can influence the prediction of genetic value by genomic selection methods. A prediction equation was established to estimate genetic correlation based on phenotypic correlation, using an F2 population with 1,000 individuals, simulated in different scenarios. Heritability (5, 20, 40, 60, 80, and 99%) and QTL number (60, 120, 180, and 240) varied in each scenario. The following four genomic selection methods were used in the analyses: ridge-regression best linear unbiased prediction (RR-BLUP), genomic BLUP (GBLUP), Bayesian estimation method B (Bayes B), and reproducing kernel Hilbert spaces regression (RKHS). The phenotypic and genotypic predictive abilities were calculated for each method, and Tukey’s test was used to compare means. The effect of heritability and of the number of QTL controlling the trait was evaluated by the regression analysis. Tukey’s test revealed differences between the methods, with Bayes B and RR-BLUP being superior to the others in almost all scenarios. Heritability presents a positive linear relationship with phenotypic predictive ability and a positive quadratic relationship with genotypic predictive ability. The number of QTL controlling the trait has no relationship with the phenotypic and genotypic predictive abilities. (QTL F 1000 1 000 1,00 individuals scenarios 5, 5 (5 20 40 60 80 99% 99 (60 120 180 240 scenario analyses ridgeregression ridge RRBLUP, RRBLUP RR , (RR-BLUP) GBLUP, GBLUP (GBLUP) B, B) RKHS. RKHS . (RKHS) Tukeys Tukey s means analysis 100 00 1,0 ( 2 4 6 8 9 (6 12 18 24 (RR-BLUP (GBLUP (RKHS 10 0 1,

Resumo O objetivo deste trabalho foi avaliar modelos que utilizam os nucleotídeos de polimorfismo único significativos (SNPs), encontrados por seleção assistida por marcadores e associação genômica, como um efeito fixo em modelos comumente utilizados na seleção genômica ampla para a população F2, em comparação com o modelo que utiliza todos os SNPs. Utilizou-se para todos modelos o método bayesiano de regressão de crista. Para as comparações entre os modelos, avaliaram-se a capacidade de predição fenotípica e genotípica, a acurácia fenotípica, o ganho de seleção, o índice de coincidência e o tempo de processamento. Ambos os métodos não conseguiram identificar com precisão os verdadeiros loci de características quantitativas (QTL). A seleção baseada apenas nos QTL identificados pelos métodos avaliados elegeu indivíduos de baixo valor genético. O uso de um modelo de seleção genômica ampla -com os SNPs significativos encontrados pela associação genômica como um efeito fixo, e os SNPs restantes como um efeito aleatório – foi a estratégia adequada para selecionar indivíduos superiores com alta precisão. A introdução de QTL já descritos para uma dada característica no modelo de seleção genômica ampla permite a seleção de indivíduos superiores com maior precisão. SNPs, , (SNPs) F2 F Utilizouse Utilizou se crista avaliaramse avaliaram genotípica processamento QTL. . (QTL) genético (SNPs (QTL

Abstract The objective of this work was to evaluate models using the significant single nucleotide polymorphisms (SNPs) detected by marker-assisted selection and genome-wide association, as a fixed effect in the models commonly used in genome-wide selection for F2 population, in comparison with models using all SNPs. For all models, the Bayesian ridge regression method was used. Comparisons between the models were carried out to evaluate the phenotypic and genotypic prediction ability, phenotypic accuracy, selection gain, coincidence index, and processing time. Both methods failed to accurately identify true quantitative trait loci (QTL). The selection based only in the QTL identified by the studied methods elected individuals of low genetic value. The use of a genome-wide selection model – with the significant SNPs found by the genome-wide association as a fixed effect, and the remaining SNPs as a random effect – was the suitable strategy to select superior individuals with high accuracy. The introduction of QTL already described for a given trait into the genome-wide selection model allows of the selection of superior individuals with greater precision. (SNPs markerassisted marker assisted genomewide genome wide F population ability accuracy gain index time QTL. . (QTL) value precision (QTL

ABSTRACT The objective of this research was to identify the most effective method to estimate the repeatability coefficients in species of eucalyptus and to predict the minimum number of measurements necessary for growth traits. The experimental design was randomized blocks, with five species, with four repetitions. Data were collected from five measurements during the period from 2014 to 2016, evaluated according to the diameter, chest height and total height. The repeatability coefficient (r) was estimated using different strategies: analysis of variance (ANOVA), principal component analysis based on the correlation matrix (PCCOR), principal components based on the phenotypic variance and covariance matrix (PCCOV), and structural analysis based on the correlation matrix (SACOR). The PCCOR and PCCOV provide accurate estimates of the repeatability coefficient and the number of measurements required. At least five measurements are necessary to predict the real value, with a minimum accuracy of 80%. traits blocks repetitions 201 2016 diameter r (r strategies ANOVA, ANOVA , (ANOVA) PCCOR, (PCCOR) PCCOV, (PCCOV) SACOR. SACOR . (SACOR) required value 80 80% 20 (ANOVA (PCCOR (PCCOV (SACOR 8 2

ABSTRACT High-throughput phenotyping (HTP) using vegetation indices (VIs) is an important data source for managing plant breeding programs and can be a promising tool in indirect selection. This study hypothesized that VIs are correlated with agronomic traits in corn, and therefore, HTP can be an auxiliary tool for selecting superior genotypes. The objectives were: i) to analyze the association between agronomic traits and VIs, and ii) to identify superior corn hybrids for the evaluated traits using multivariate techniques. Ten corn hybrids (AGRI 330, AGRI 340, FS575PWU, KTZ006VP3, MG545AW, MG580PW, MG711PW, MZ1780, MZ1952, and TROPI 102) were evaluated for plant height (PH), stem diameter (SD), and grain yield (GY). The VIs studied were NDVI, NDRE, EVI, GNDVI, SAVI, and MSAVI. Pearson’s correlation network was constructed to analyze the relationship between the variables, and a canonical analysis was performed to verify the inter-relationship between the variables and hybrids. The VIs evaluated are strongly positively correlated with each other and with PH. The most productive hybrids are MG545AW, FS575PWU and KTZ006VP3. Hybrid MZ1952 has higher correlations with VIs and PH. The findings reveal that VIs can be excellent auxiliary variables for selecting agronomically superior genotypes, being a promising alternative to increase corn breeding efficiency. Highthroughput High throughput (HTP (VIs selection therefore genotypes i ii techniques 330 340 FSPWU FS PWU KTZ006VP3 KTZVP KTZ VP MG545AW MGAW MG AW MG580PW MGPW PW MG711PW MZ1780 MZ 102 PH, PH , (PH) SD, SD (SD) GY. GY . (GY) NDVI NDRE EVI GNDVI SAVI MSAVI Pearsons Pearson s interrelationship inter MZ195 efficiency 33 34 KTZ006VP MZ178 10 (PH (SD (GY MZ19 3 MZ17 1 MZ1

RESUMO As pimentas precisam ser caracterizadas para a conservação in situ da espécie que possam ser importantes para fins de reprodução. Neste estudo, caracterizamos a diversidade de 23 genótipos de pimenta por meio de oito descritores qualitativos e 12 quantitativos. As amostras de pimenta foram coletadas na cidade de Manaus e nos municípios de Rio Preto da Eva e Iranduba no estado do Amazonas. Realizamos análise descritiva, análise de variância, análise de correlação de Pearson e análise de componentes principais (ACP) e usamos o método de grupo de pares não ponderados com média aritmética (UPGMA) para analisar os dados. As diferenças entre os genótipos para todos os descritores avaliados foram significativas. Dentre os genótipos coletados, foram identificadas quatro espécies de pimenta, sendo elas Capsicum chinense (14 genótipos), Capsicum frutescens (dois genótipos), Capsicum baccatum (um genótipo) e Capsicum annuum (quatro genótipos), e outros dois genótipos foram obtidos com espécies não identificadas. Os métodos de agrupamento ACP e UPGMA podem ser usados para diferenciar eficientemente os genótipos por meio da aplicação de descritores quantitativos e qualitativos de frutos e sementes. Esses métodos ajudaram a identificar diferentes genótipos (G1 e G15) e separá-los em grupos distintos associados à distribuição das espécies com base apenas em dados quantitativos. No geral, nossos achados sugerem que a variabilidade genética em Capsicum disponível no Estado do Amazonas pode ser útil em programas de melhoramento. reprodução estudo 2 1 descritiva variância (ACP (UPGMA significativas coletados 14 (1 genótipos, , genótipos) um genótipo sementes G1 G (G G15 separálos separá los geral melhoramento (

ABSTRACT Peppers need to be characterized for the in situ conservation of species that might be important for breeding purposes. In this study, we characterized the diversity of 23 pepper genotypes through eight qualitative and 12 quantitative descriptors. The pepper samples were collected from the city of Manaus and in the municipalities of Rio Preto da Eva and Iranduba in the state of Amazonas. We performed descriptive analysis, analysis of variance, Pearson’s correlation analysis, and principal component analysis (PCA) and used the unweighted pair group method with arithmetic mean (UPGMA) to analyze the data. The differences between the genotypes for all descriptors evaluated were significant. Among the genotypes collected, four pepper species were identified, including Capsicum chinense (14 genotypes), Capsicum frutescens (two genotypes), Capsicum baccatum (one genotype), and Capsicum annuum (four genotypes), and two other genotypes were obtained with unidentified species. The PCA and UPGMA clustering methods could be used to efficiently differentiate between the genotypes by applying quantitative and qualitative descriptors of fruits and seeds. These methods helped to identify different genotypes (G1 and G15) and separate them into distinct groups associated with the distribution of species based on quantitative data only. Overall, our findings suggested that the genetic variability in Capsicum available in the State of Amazonas might be useful in breeding programs. purposes study 2 1 variance Pearsons Pearson s (PCA (UPGMA significant identified 14 (1 genotypes, , genotypes) one genotype, genotype genotype) seeds G1 G (G G15 only Overall programs (

RESUMO: Compreender a diversidade genética e contornar os problemas causados pela interação genótipos por ambientes é uma etapa importante em programas de melhoramento. Este estudo teve como objetivo estimar a diversidade genética e aplicar a metodologia de biplot genótipo + genótipo por ambiente (GGE biplot) em doze genótipos de algodão avaliados quanto ao rendimento da fibra, comprimento da fibra, resistência da fibra e micronaire. A estimativa dos componentes de variância e dos parâmetros genéticos foi feita através do método da máxima verossimilhança restrita e a predição dos valores genotípicos por meio da melhor predição linear não enviesada. Os métodos de Tocher modificado e análise de componentes principais (PCA) foram utilizados para quantificar a diversidade genética entre os genótipos. O método GGE biplot foi conduzido para encontrar os melhores genótipos em relação à adaptabilidade e estabilidade. As técnicas de Tocher e PCA permitiram a formação de clusters de genótipos semelhantes com base em uma estrutura multivariada. O GGE biplot indicou que os genótipos IMACV 690 e IMA08 WS foram altamente adaptáveis e estáveis para as principais características do algodão. O cruzamento dentre os genótipos IMACV 690 e IMA08 WS é o mais recomendado para aumentar o desempenho das principais características na cultura do algodão.

ABSTRACT: Understanding the genetic diversity and overcoming genotype-by-environment interaction issues is an essential step in breeding programs that aims to improve the performance of desirable traits. This study estimated genetic diversity and applied genotype + genotype-by-environment (GGE) biplot analyses in cotton genotypes. Twelve genotypes were evaluated for fiber yield, fiber length, fiber strength, and micronaire. Estimation of variance components and genetic parameters was made through restricted maximum likelihood and the prediction of genotypic values was made through best linear unbiased prediction. The modified Tocher and principal component analysis (PCA) methods, were used to quantify genetic diversity among genotypes. GGE biplot was performed to find the best genotypes regarding adaptability and stability. The Tocher technique and PCA allowed for the formation of clusters of similar genotypes based on a multivariate framework. The GGE biplot indicated that the genotypes IMACV 690 and IMA08 WS were highly adaptable and stable for the main traits in cotton. The cross between the genotype IMACV 690 and IMA08 WS is the most recommended to increase the performance of the main traits in cotton crops.

ABSTRACT. In cotton crops, the cotton seed yield significantly contributes with the success of any cultivar. However, other traits are considered when an ideotype is pointed out in the selection, such as the fiber quality traits. The aim of this study was to applied genotype by yield*trait (GYT) biplot to a multi-environment trial data of cotton genotypes and selected the best genotypes. For this end, thirteen genotypes from nineteen trials were assessed. Seven traits were evaluated [cotton seed yield (SY), fiber percentage (FP), fiber length (FL), fiber uniformity (FU), short fiber index (SFI), fiber strength (FS), and elongation (EL)] and residual error variances structures [identity variance (IDV) and diagonal (Diag)] were tested by bayesian information criterion. After, the REML/BLUP approach was applied to predict the genetic values of each trait and the selective accuracy were measured from the prediction. Then, the GYT-biplot were applied to the data. For SP and SFI traits, the model with Diag residual variance was indicated, whereas for SY FL, FU, FS, and EL traits the model with IDV residual variance demonstrated the best fit to the data. Values of accuracy were higher than 0.9 for all traits analyzed. In the GYT-biplot acute angles were find for all traits relations, which means high correlation between the yield*traits combination. Besides that, the correlation still can be seen in the GYT-biplot, as shown by the magnitudes of the angles between the pairs Yield*FU-Yield*FS and Yield*FS-Yield*EL. Also, the GYT-biplot indicates the genotype G4 with the best performance for Yield*FS, Yield*SFI, Yield*FU, Yield*FL, and Yield*FP combined. The genotypes G4, G1, G13, G8, and G9 represent those genotypes with yield advantage over the other cultivars. Then, the genotype G4 combines all desirable characteristics and demonstrate have large potential in the cotton breeding. The GYT approach were valuable and were highly recommended in cotton breeding programs for selection purpose in a multivariate scenario.

Resumo O objetivo deste trabalho foi selecionar, simultaneamente, híbridos pré-comerciais de sorgo granífero com alta adaptabilidade e estabilidade da produção de grãos, por meio de modelagem mista, em 20 ambientes, por seis anos. O material vegetal avaliado consistia de 57 híbridos comerciais de sorgo granífero. Em todos os experimentos, os híbridos foram arranjados em delineamento fatorial triplo; alguns experimentos utilizaram um fatorial 6x6, e outros, um fatorial 5x5. Os parâmetros de adaptabilidade e estabilidade foram obtidos com base na predição por média harmônica da performance relativa dos valores genéticos (MHPRVG). Os modelos mistos mostraram-se adequados para analisar a interação genótipo x ambiente (GxE) e os estudos de adaptabilidade e estabilidade genotípica do sorgo granífero. Os híbridos que se destacam, considerando-se todos os ambientes, são 1G282, A9904, 50A50, A9902 e XB6022. O híbrido A9904 destaca-se em ambientes favoráveis, com rendimento de grãos acima da média. Apenas 1G282 está entre os cinco melhores híbridos para cada grupo de ambientes e é o melhor híbrido de sorgo granífero quanto ao rendimento, à adaptabilidade e à estabilidade. Os valores genotípicos preditos com base em médias genotípicas podem ser usados em relação aos ambientes com o mesmo padrão de interação GxE por estarem livres da interação GxE.

Abstract The objective of this work was to simultaneously select pre-commercial grain sorghum hybrids with high adaptability and yield stability, through mixed modeling, in 20 environments, during six years. The evaluated plant material consisted of 57 commercial grain sorghum hybrids. In all experiments, hybrids were arranged in a triple lattice design; some experiments used a 6x6 lattice, and others, a 5x5 lattice. Adaptability and stability parameters were obtained based on the prediction by harmonic mean of the relative performance of genotypic values (HMRPGV). The mixed models proved to be adequate to analyze the genotype x environment (GxE) interaction and the genotypic adaptability and stability studies on grain sorghum. The hybrids that stand out, considering all environments are 1G282, A9904, 50A50, A9902, and XB6022. The A9904 hybrid stands out in favorable environments, with a grain yield above average. Only 1G282 is among the five best hybrids for each group of environments, and it is the best grain sorghum hybrid for yield performance, adaptability, and stability. The predicted genotypic values based on genotypic means can be used in the environments with the same GxE interaction pattern because they are free of the GxE interaction.

ABSTRACT Grain yield is a constant concern in soybean breeding programs for being highly influenced by the environment. This trait can be significantly affected by the sowing times. Thus, for the correct cultivar recommendation, methods of stability and adaptability analysis are used to verify the genotype x environment interaction at different sowing times. In this study, ten soybean cultivars were evaluated in 2016/2017 and 2017/2018 seasons, at different sowing times. Each experiment was carried out in a randomized block design with three replications. The methods of Eberhart & Russel and Lin & Binns were used for cultivars recommendation for general, favorable, and unfavorable environments. Cultivars CS2728, BONUS, and BRS1074 show high yield and predictability and therefore are the most suitable for the region of Chapadão do Sul.

Abstract Multiple-trait best linear unbiased prediction (BLUP) is generally the most appropriate method to predict genetic values because it considers the genetic and residual correlations among traits and leads to higher selective accuracy. Thus, the aim of the present study was to analyze the interrelationships among traits related to cotton fiber length through path analysis under multiple-trait BLUP. To that end, 36 elite lines were evaluated in three envi ronments and phenotyped for fiber quality and agronomic traits. Variance components were estimated via residual maximum likelihood (REML). The genetic correlation coefficients among traits were obtained through the mixed model output, and a correlation network was constructed to graphically express these results. Subsequently, path analysis was performed considering fiber length as the main dependent variable. Genetic parameters indicate that the phenotypic variance for most traits is mainly composed of residual effects, which reinforces the need for more accurate statistical methods, such as multiple-trait BLUP. The results for genetic correlations and path analysis reveal the difficulty of selection based on important fiber quality traits, especially fiber length, since most traits show a low cause-and-effect relationship, while other important traits have an undesirable cause-and-effect relationship. Path analysis under multiple-trait BLUP proved to be suitable and useful for studying interrelationships among traits related to cotton fiber length.

Resumen La mejor predicción lineal insesgada de rasgos múltiples (BLUP) es, en general, el método más apropiado para predecir valores genéticos porque considera las correlaciones genéticas y residuales entre rasgos y conducta con mayor precisión selectiva. Por lo tanto, el presente estudio tuvo como objetivo estudiar las interrelaciones entre los rasgos relacio nados con la longitud de la fibra de algodón a través del análisis de ruta en BLUP de rasgos múltiples. Con este fin, se evaluaron treinta y seis líneas élite en tres ambientes y se fenotipificaron para muchos rasgos relacionados con la calidad de la fibra y los rasgos agronómicos. Los componentes de la varianza se estimaron mediante la máxima verosimilitud residual (REML). Los coeficientes de correlación genética entre rasgos se obtuvieron a través de la salida del modelo mixto, y para expresar gráficamente estos resultados se construyó una red de correlación. Posteriormente, realizamos el análisis de ruta considerando la longitud de la fibra como variable dependiente principal. Los parámetros genéticos indican que la variación fenotípica para la mayoría de los rasgos se compone principalmente de efectos residuales, lo que refuerza la necesidad de utilizar métodos estadísticos más precisos, como BLUP de rasgos múltiples. Los resultados encontrados para las correlaciones genéticas y el análisis de ruta revelan la dificultad de la selección basada en rasgos importantes de la calidad de la fibra, especialmente la longitud de la fibra, ya que la mayoría de los rasgos muestran una relación de causa y efecto muy baja, y otros rasgos importantes presentan una relación de causa y efecto no deseada. El análisis de ruta en BLUP de rasgos múltiples resultó ser adecuado y útil para el estudio de las interrelaciones entre los rasgos relacio nados con la longitud de la fibra de algodón.

Abstract Grain sorghum production has expanded during the off-season when rainfall oscillates and becomes insufficient. Aiming to obtain better adapted cultivars, breeding programs have sought new combinations of hybrids with earliness, high grain yield, and ideal plant height for harvesting. This study aimed to estimate de combining ability of grain sorghum lines, proposing a breeding strategy, to identify hybrids gathering high yield, earliness, and desired plant height. Thirty-six hybrids from crosses of 12 lines were evaluated at two sites in the Brazilian region known as Cerrado biome. The evaluated traits were: days to flowering, plant height, and grain yield. For the diallel analysis, Method 4 of Griffing adapted to partial diallel was adopted. By combining ability analysis, we identified promising lines to be used as parents to obtain more yielding, early, and ideal height hybrids. The findings allowed us to propose a breeding strategy, in which complex crosses should be performed to gather favorable alleles in new restorer and male-sterile lines. The hybrids 7, 9, 19, and 22 are the most suitable for growing in the evaluated sites.

Resumen El cultivo de sorgo granífero se ha expandido durante la temporada baja, cuando la lluvia es oscilante e insuficiente. Para obtener cultivares mejor adaptados a estas condiciones, los programas de mejoramiento han buscado nuevas combinaciones de híbridos con preco cidad, alto rendimiento de grano y altura ideal de la planta para la cosecha. Este estudio tuvo como objetivo estimar la capacidad de combinación de líneas de sorgo granífero, con el objetivo de proponer una estrategia de mejoramiento e identificar híbridos con alto rendimiento, precocidad y altura de plantas adecuadas para la cosecha. Treinta y seis híbridos obtenidos del cruzamiento entre 12 líneas fueron evaluados en dos sitios en la región brasilera denominada Bioma Cerrado. Los caracteres evaluados fueron: días hasta la floración, altura de la planta y el rendimiento de grano. Para el análisis del dialelo, se adoptó el Método 4 de Griffing adaptado al dialelo parcial. Por medio del análisis de capacidad de combinación, identificamos líneas promisorias para ser usadas como parentales con el fin de obtener híbridos de mayor rendimiento, precocidad y altura ideal. Los resultados nos permitieron proponer una estrategia de mejoramiento, donde cruzamientos complejos deben ser realizados para reunir alelos favorables para los caracteres en nuevas líneas restauradoras y macho estériles. Los híbridos 7, 9, 19 y 22 son los más adecuados para el cultivo en los sitios evaluados.