RESUMO
The usefulness of genomic prediction (GP) for many animal and plant breeding programs has been highlighted for many studies in the last 20 years. In maize breeding programs, mostly dedicated to delivering more highly adapted and productive hybrids, this approach has been proved successful for both large- and small-scale breeding programs worldwide. Here, we present some of the strategies developed to improve the accuracy of GP in tropical maize, focusing on its use under low budget and small-scale conditions achieved for most of the hybrid breeding programs in developing countries. We highlight the most important outcomes obtained by the University of São Paulo (USP, Brazil) and how they can improve the accuracy of prediction in tropical maize hybrids. Our roadmap starts with the efforts for germplasm characterization, moving on to the practices for mating design, and the selection of the genotypes that are used to compose the training population in field phenotyping trials. Factors including population structure and the importance of non-additive effects (dominance and epistasis) controlling the desired trait are also outlined. Finally, we explain how the source of the molecular markers, environmental, and the modeling of genotype-environment interaction can affect the accuracy of GP. Results of 7 years of research in a public maize hybrid breeding program under tropical conditions are discussed, and with the great advances that have been made, we find that what is yet to come is exciting. The use of open-source software for the quality control of molecular markers, implementing GP, and envirotyping pipelines may reduce costs in an efficient computational manner. We conclude that exploring new models/tools using high-throughput phenotyping data along with large-scale envirotyping may bring more resolution and realism when predicting genotype performances. Despite the initial costs, mostly for genotyping, the GP platforms in combination with these other data sources can be a cost-effective approach for predicting the performance of maize hybrids for a large set of growing conditions.
RESUMO
ABSTRACT: Glyphosate is a broad-spectrum herbicide capable of controlling a wide range of weed. It uses could cause the occurrence of residues in conventional or genetically modified crops. For this purpose, grains (soybean and corn) and cotton seeds were sampled from commercial areas in 2012/2013 to 2017/2018 seasons in different Brazilian agricultural regions to monitor glyphosate residues levels and its metabolite (aminomethylphosphonic acid - AMPA) after different managements. The glyphosate residues levels in genetically modified corn (GM) ranged from no detected (ND) to 0.15 mg kg-1, in GM soybean values ranged from ND to 2.81 mg kg-1 and in GM cotton ranged from ND to 1.78 mg kg-1. AMPA residues levels indicated a correlation with the glyphosate residues. Glyphosate residues levels in soybean and corn grains and cotton seeds were within the Maximum Residue Limits (MRLs) established by ANVISA and Codex Alimentarius.
RESUMO: O glifosato é um herbicida de amplo espectro capaz de controlar uma grande diversidade de ervas daninhas e seu uso pode acarretar na ocorrência de resíduos, seja em culturas convencionais ou geneticamente modificadas. Sendo assim, amostragens de grãos de soja e milho e de sementes de algodão foram realizadas em áreas comerciais nas safras de 2012/2013 a 2017/2018 em diferentes regiões agrícolas brasileiras com o objetivo de monitorar os níveis de resíduos de glifosato e seu metabólito (ácido aminometilfosfônico - AMPA) após diferentes manejos. Os níveis de resíduos de glifosato em milho geneticamente modificados (GM) tolerante ao glifosato variaram desde não detectados (ND) a até 0,15 mg kg-1, em soja GM tolerante ao glifosato os valores variaram de ND a 2,81 mg kg-1 e em algodão GM tolerante ao glifosato os resultados se estabeleceram entre ND a 1,78 mg kg-1. Os valores de resíduos de AMPA indicaram correlação com os resíduos de glifosato. Os níveis de resíduos de glifosato em grãos de soja e milho e sementes de algodão ficaram dentro dos Limites Máximos de Resíduos (LMRs) preconizados pela ANVISA e Codex Alimentarius.
RESUMO
Glyphosate is a broad-spectrum herbicide capable of controlling a wide range of weed. It uses could cause the occurrence of residues in conventional or genetically modified crops. For this purpose, grains (soybean and corn) and cotton seeds were sampled from commercial areas in 2012/2013 to 2017/2018 seasons in different Brazilian agricultural regions to monitor glyphosate residues levels and its metabolite (aminomethylphosphonic acid - AMPA) after different managements. The glyphosate residues levels in genetically modified corn (GM) ranged from no detected (ND) to 0.15 mg kg-1, in GM soybean values ranged from ND to 2.81 mg kg-1 and in GM cotton ranged from ND to 1.78 mg kg-1. AMPA residues levels indicated a correlation with the glyphosate residues. Glyphosate residues levels in soybean and corn grains and cotton seeds were within the Maximum Residue Limits (MRLs) established by ANVISA and Codex Alimentarius.(AU)
O glifosato é um herbicida de amplo espectro capaz de controlar uma grande diversidade de ervas daninhas e seu uso pode acarretar na ocorrência de resíduos, seja em culturas convencionais ou geneticamente modificadas. Sendo assim, amostragens de grãos de soja e milho e de sementes de algodão foram realizadas em áreas comerciais nas safras de 2012/2013 a 2017/2018 em diferentes regiões agrícolas brasileiras com o objetivo de monitorar os níveis de resíduos de glifosato e seu metabólito (ácido aminometilfosfônico - AMPA) após diferentes manejos. Os níveis de resíduos de glifosato em milho geneticamente modificados (GM) tolerante ao glifosato variaram desde não detectados (ND) a até 0,15 mg kg-1, em soja GM tolerante ao glifosato os valores variaram de ND a 2,81 mg kg-1 e em algodão GM tolerante ao glifosato os resultados se estabeleceram entre ND a 1,78 mg kg-1. Os valores de resíduos de AMPA indicaram correlação com os resíduos de glifosato. Os níveis de resíduos de glifosato em grãos de soja e milho e sementes de algodão ficaram dentro dos Limites Máximos de Resíduos (LMRs) preconizados pela ANVISA e Codex Alimentarius.(AU)
Assuntos
Produtos Agrícolas/genética , Glycine max , Zea maysRESUMO
Maize plants can be N-use efficient or N-stress tolerant. The first have high yields in favorable environments but is drastically affected under stress conditions; whereas the second show satisfactory yields in stressful environments but only moderate ones under optimal conditions. In this context, our aim was to assess the possibility of selecting tropical maize lines that are simultaneously N-stress tolerant and N-use efficient and check for differences between simultaneous selection statistical methods. Sixty-four tropical maize lines were evaluated for Nitrogen Agronomic Efficiency (NAE) and Low Nitrogen Tolerance (LNTI) response indices and two per se selection indices, Low Nitrogen Agronomic Efficiency (LNAE) and Harmonic Mean of Relative Performance (HMRP). We performed eight selection scenarios: LNAE; HMRP; Additive index; Mulamba-Mock index; and Independent culling levels. The last three was predicted by REML/BLUP single-trait and multi-trait using genotypic values of NAE and LNTI. The REML/BLUP multi-trait analysis was superior to the single-trait analysis due to high unfavorable correlation between NAE and LNTI. However, the accuracy and genotypic determination coefficient of NAE and LNTI were too low. Thus, neither single- nor multi-trait analysis achieved a good result for simultaneous selection nor N-use efficiency nor N-stress tolerance. LNAE obtained satisfactorily accurate values and genotypic determination coefficient, but its performance in selection gain was worse than HMRP, particularly in terms of N-use efficiency. Therefore, because of the superior performance in accuracy, genotypic determination coefficient and selection, HMRP was considered the best simultaneous selection methodology of the scenarios tested for N-use efficiency and N-stress tolerance.
Assuntos
Fatores Abióticos/análise , Zea mays/crescimento & desenvolvimento , Zea mays/efeitos adversos , Zea mays/químicaRESUMO
Maize plants can be N-use efficient or N-stress tolerant. The first have high yields in favorable environments but is drastically affected under stress conditions; whereas the second show satisfactory yields in stressful environments but only moderate ones under optimal conditions. In this context, our aim was to assess the possibility of selecting tropical maize lines that are simultaneously N-stress tolerant and N-use efficient and check for differences between simultaneous selection statistical methods. Sixty-four tropical maize lines were evaluated for Nitrogen Agronomic Efficiency (NAE) and Low Nitrogen Tolerance (LNTI) response indices and two per se selection indices, Low Nitrogen Agronomic Efficiency (LNAE) and Harmonic Mean of Relative Performance (HMRP). We performed eight selection scenarios: LNAE; HMRP; Additive index; Mulamba-Mock index; and Independent culling levels. The last three was predicted by REML/BLUP single-trait and multi-trait using genotypic values of NAE and LNTI. The REML/BLUP multi-trait analysis was superior to the single-trait analysis due to high unfavorable correlation between NAE and LNTI. However, the accuracy and genotypic determination coefficient of NAE and LNTI were too low. Thus, neither single- nor multi-trait analysis achieved a good result for simultaneous selection nor N-use efficiency nor N-stress tolerance. LNAE obtained satisfactorily accurate values and genotypic determination coefficient, but its performance in selection gain was worse than HMRP, particularly in terms of N-use efficiency. Therefore, because of the superior performance in accuracy, genotypic determination coefficient and selection, HMRP was considered the best simultaneous selection methodology of the scenarios tested for N-use efficiency and N-stress tolerance.(AU)
Assuntos
Zea mays/efeitos adversos , Zea mays/química , Zea mays/crescimento & desenvolvimento , Fatores Abióticos/análiseRESUMO
A few breeding companies dominate the maize (Zea mays L.) hybrid market in Brazil: Monsanto® (35%), DuPont Pioneer® (30%), Dow Agrosciences® (15%), Syngenta® (10%) and Helix Sementes (4%). Therefore, it is important to monitor the genetic diversity in commercial germplasms as breeding practices, registration and marketing of new cultivars can lead to a significant reduction of the genetic diversity. Reduced genetic variation may lead to crop vulnerabilities, food insecurity and limited genetic gains following selection. The aim of this study was to evaluate the genetic vulnerability risk by examining the relationship between the commercial Brazilian maize germplasms and the Nested Association Mapping (NAM) Parents. For this purpose, we used the commercial hybrids with the largest market share in Brazil and the NAM parents. The hybrids were genotyped for 768 single nucleotide polymorphisms (SNPs), using the Illumina Goldengate® platform. The NAM parent genomic data, comprising 1,536 SNPs for each line, were obtained from the Panzea data bank. The population structure, genetic diversity and the correlation between allele frequencies were analyzed. Based on the estimated effective population size and genetic variability, it was found that there is a low risk of genetic vulnerability in the commercial Brazilian maize germplasms. However, the genetic diversity is lower than those found in the NAM parents. Furthermore, the Brazilian germplasms presented no close relations with most NAM parents, except B73. This indicates that B73, or its heterotic group (Iowa Stiff Stalk Synthetic), contributed to the development of the commercial Brazilian germplasms.
Assuntos
Técnicas de Genotipagem/métodos , Polimorfismo de Nucleotídeo Único , Sementes/genética , Zea mays/genética , Brasil , Mapeamento Cromossômico , Frequência do Gene , Filogenia , Melhoramento VegetalRESUMO
O objetivo deste trabalho foi identificar qual é o componente principal do rendimento de grãos de feijão comum que apresenta menor sensibilidade ao efeito do ambiente, e que propicia maior consistência na expressão dos resultados, quando avaliados em diferentes locais. Os dados experimentais utilizados nas análises são provenientes de Ensaio de Valor cultivo e Uso (VCU) conduzidos nos municípios de Lages e de Chapecó. Os caracteres observados foram estande final de plantas; número de legumes por planta; número de grãos por legume; massa de 1.000 grãos e rendimento total de grãos em kg ha-1. O delineamento experimental utilizado foi o de blocos ao acaso, com quatro repetições. As estimativas das correlações fenotípicas foram obtidas pelo método proposto por STEEL e TORRIE e particionadas em efeitos diretos e indiretos mediante a análise de trilha. Correlação inversa foi obtida para os caracteres massa de 1.000 grãos e número de grão por legume, revelando que os mesmos devem ser selecionados conjuntamente para obter ganho no caráter rendimento de grãos. Quando a seleção tem por objetivo aumentar o rendimento de grãos, para as condições ambientais de Chapecó a característica massa de 1.000 grãos pode ser utilizada, enquanto que em Lages o mais apropriado é utilizar o caractere número de legume por planta, pois apresentam consistência e estabilidade no desdobramento dos coeficientes de trilha.
This study aimed to identify which is the main component of grain yield of bean that that shows less sensitivity effect of the environment, and provides greater consistency in the expression of results when evaluated in different environments. Experimental data used in the analysis are derived from test of Cultivate and Use Value (VCU) conducted in Lages SC and Chapecó SC, South of Brazil. The characters observed were the final stand of plants, number of pods per plant; number of grains per pod, seed mass (g 1000 seed-1) and grain yield (kg ha-1). The experiment was conducted in a randomized block design, with four replications. Estimates of phenotypic correlations were obtained by the method proposed by STEEL and TORRIE and partitioned into direct and indirect effects through path analysis.The inverse correlation was obtained for the characters of seed mass and grain number per pod, revealing that they should be selected together to obtain gains in the yield character. When the selection is aimed at grain production, for Chapecó-SC the characteristic of seed mass can be used, where as in Lages-SC the character number of grains per pod is more appropriate. Characters seed mass and number of vegetable per pod showed high stability during the unfolding of the path coefficients, showing that they can be used in selecting genotypes with higher grain yield in different environments.