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A seleção com base no fenótipo pode ser influenciada por fatores de ambiente, sendo necessário que o melhorista utilize métodos de seleção que separem efeitos genéticos dos de ambiente. O objetivo deste estudo foi testar a eficiência da seleção indireta para o incremento no rendimento de grãos de aveia (Avena sativa L). Oito populações segregantes de aveia foram submetidas à seleção para o caráter peso de panícula, sob três diferentes métodos de semeadura (em cova, em planta espaçada e em linha cheia), durante os anos de 2000 e 2001. Os resultados mostraram que o desenvolvimento de genótipos superiores requer avaliação principalmente em anos distintos para minimizar os efeitos de ambiente. O sistema de semeadura parece ter extrema importância para a seleção, pois o mecanismo de semeadura em cova proporcionou reduzida participação do ambiente na expressão do peso de panícula.

A dissimilaridade genética estimada por meio de marcadores moleculares, quando acompanhada de informações fenotípicas, é importante para a seleção de genótipos para o melhoramento e o mapeamento genético. Desta forma, os objetivos deste estudo foram: i) estimar a dissimilaridade genética entre 30 linhagens de milho contrastantes para a tolerância ao encharcamento; ii) selecionar genitores para mapeamento e melhoramento genético; iii) comparar diferentes métodos de visualização gráfica das distâncias. Foram utilizados 21 iniciadores de RAPD. A dissimilaridade genética foi estimada por meio do complemento do coeficiente de similaridade de Dice, posteriormente foi construído um dendrograma pelo método de agrupamento da distância média e calculado o coeficiente de correlação cofenética entre a matriz de dissimilaridade e o dendrograma gerado. O complemento da matriz de similaridade foi submetido também à análise de componentes principais e de escala multidimensional. Para ambas as análises, foi testada a eficiência das projeções, por meio da correlação entre as distâncias originais e as representadas nos gráficos. As técnicas de agrupamento não revelaram um bom ajuste entre as distâncias apresentadas graficamente e a matriz original de distâncias, com correlações de 0,70, 0,53 e 0,75 para o dendrograma, componentes principais e análise de escala multidimensional, respectivamente. Dentre as técnicas de agrupamento empregadas, a que atendeu de forma mais precisa aos objetivos do trabalho foi a análise multidimensional, uma vez que esta, além de apresentar a maior correlação com a matriz original de distâncias, preservou as distâncias entre todos os pares de genótipos. Além disso, esta técnica é a mais indicada quando o objetivo do trabalho é a definição de cruzamentos, pois ela permite uma observação mais fácil das distâncias entre todos os pares de genótipos.

A correlação genotípica permite avaliar a magnitude e a direção da associação entre caracteres, sendo de grande utilidade por permitir a viabilidade do emprego da seleção indireta, que em alguns casos, pode levar a progressos genéticos mais rápidos e altamente expressivos em programas de melhoramento de aveia (Avena sativa L.). O objetivo deste trabalho foi avaliar a viabilidade da implementação de uma modificação na fórmula de PETR & FREY (1966), para a obtenção de estimativas de correlação genotípica, fenotípica e de ambiente, através da análise de quatro populações segregantes F2 de aveia: OR 2 x UPF 18, UPF 7 x CTC 5, OR 2 x UPF 7, UPF 18 x CTC 5. As estimativas de correlação genotípica indicam que a seleção de plantas de alta produtividade de grãos pode ser realizada indiretamente através dos caracteres número de panículas por planta, peso de panícula, número de grãos por panícula e peso médio de grãos. Entretanto, as diferenças em magnitude e direção das estimativas de correlações, entre os vários pares de caracteres, nas quatro populações estudadas, não permitem a generalização de uma estratégia de seleção, isto devido as limitações impostas pelas diferenças entre as constituições genéticas dos genitores e populações. Desta forma, é de fundamental importância a avaliação da capacidade combinatória das principais constituições genéticas utilizadas em cruzamentos artificiais, a fim de se estabelecer critérios mais efetivos a serem empregados na seleção de genótipos superiores.

Vinte cultivares de aveia (Avena sativa L.) foram avaliados para rendimento de grãos nas safras agrícolas de 2001 e 2002 em nove locais dos estados do Paraná, Rio Grande do Sul e São Paulo, com o objetivo de avaliar as estimativas dos componentes de adaptabilidade e estabilidade do rendimento de grãos em ambientes favoráveis e desfavoráveis em presença e ausência de aplicação de fungicida. Foi empregada a metodologia de EBERHART & RUSSELL (1966). A presença de significância para anos, genótipos, fungicidas e locais, indicou comportamento diferencial de genótipos frente às variações de ambiente e a aplicação de fungicida, nas condições de ambientes favoráveis e desfavoráveis. A aplicação de fungicida e o favorecimento do ambiente de cultivo afetaram intensamente os parâmetros de adaptabilidade (b1) e estabilidade (s²d i), indicando que estas estimativas devam ser realizadas em ambientes estratificados, apesar de nenhuma constituição genética ter evidenciado o biótipo ideal, conforme preconizado pelo modelo adotado.

Em aveia (Avena sativa L.), a utilização de técnicas que minimizem os efeitos de ambiente na expressão do fenótipo e que facilitem a identificação de genótipos de superior rendimento de grãos, baixa estatura e tolerantes ao alumínio tóxico são aspectos de fundamental importância para o desenvolvimento de cultivares mais promissores e com adaptabilidade a áreas consideradas marginais. Desta forma, genótipos selecionados pelo método colméia de condução de populações segregantes, em três diferentes cruzamentos, foram submetidos a testes simultâneos para tolerância ao alumínio tóxico (Al+3) e insensibilidade ao ácido giberélico (AG3), objetivando a identificação de constituições genéticas superiores. A técnica utilizada possibilitou a seleção de plantas de alto potencial produtivo, menor estatura (insensíveis ao AG3) e mais tolerantes ao Al+3, podendo ser aplicada com sucesso em programas de melhoramento genético com a cultura da aveia hexaplóide cultivada.

Medidas de dissimilaridade são artifícios que os melhoristas de plantas dispõem para identificarem genótipos distantes na obtenção de populações segregantes desejadas. Assim, o presente trabalho foi realizado para estabelecer relação entre as diferentes técnicas multivariadas utilizadas em estimativas de divergência genética. O experimento foi desenvolvido no ano agrícola de 2001, quando doze cultivares de aveia foram testados para sete caracteres agronômicos, utilizando-se o delineamento experimental de blocos casualizados com quatro repetições. As distâncias Euclidiana e de Mahalanobis evidenciaram baixa correlação (0,529) e, quando utilizadas na confecção de dendrogramas, não possibilitaram a formação de agrupamentos similares. As análises gráficas por componentes principais e variáveis canônicas também apresentaram dispersões distintas. Entretanto, apesar das discrepâncias observadas entre as metodologias analisadas, foi possível a identificação de genótipos dissimilares e com média elevada, que poderão ser utilizados com grande probabilidade de sucesso em hibridações dirigidas em aveia.

Pyramiding Rpp genes is a promising strategy to achieve a more durable resistance against Asian soybean rust (ASR). The objective of this study was to develop Rpp‐pyramided populations and evaluate their resistance and yield in field conditions. Fifteen pyramided populations carrying different combinations of Rpp genes were developed, and the F3 lines were evaluated to phenotypic resistance and yield performance. Our results suggest that the Rpp1‐b of different resistant sources (PI 587880A, PI 594723, PI 4538A) have higher resistance and yield performance compared with other Rpp genes. Rpp‐pyramided populations carrying two and three genes showed an increase in resistance compared with populations carrying a single Rpp gene. The best gene combinations were Rpp1‐b + Rpp5, showing neither uredinia formation nor sporulation (immunity + RB1 phenotype reaction) in more than 70% of the F3 population. Rpp‐pyramided lines developed in this study have the potential to be used in backcross programs for improving ASR resistance. Core Ideas: Rpp‐pyramided populations carrying two and three Rpp genes show higher resistance to ASR.Rpp1‐b + Rpp5 could be an interesting option to achieve resistance.Rpp‐pyramided lines have potential to be used in backcross programs for improving ASR. [ABSTRACT FROM AUTHOR]

The objective of this work was to assess the breeding influences in different agronomic and physiological traits in Brazilian soybean cultivars, released between 1965 and 2011, to identify traits associated with modern cultivars. A total of 29 cultivars were evaluated in two locations in the 2016/17 crop season. Genotype selection based on agronomic and physiological traits was determined using GYT (Grain Yield*Trait) methodology, which uses the Superiority Index to rank genotypes by mean of all traits. Grain Yield is combined with other target traits and shows the strengths and weaknesses of each genotype. Soybean breeding improved desirable traits during the 46 years of evaluation. Superiority index can be a powerful tool for breeders to obtain high genetic gains in the future. The cultivars DMario 58i, TMG 7161RR and TMG 7262 RR stand out as the best cultivars but present different sets of desirable traits. The traits grain yield, harvest index, number of pods per plant, reproductive-vegetative ratio, photosynthetic rate and transpiration rate are core traits which can be evaluated in soybean breeding programs. [ABSTRACT FROM AUTHOR]

The wheat cultivar UTF 25 is recommended for wheat-growing regions 1 and 2 of Paraná and Santa Catarina states. It has a good disease resistance, early cycle, and high grain yield potential, with an average yield of 3.511 kg ha-1. It is classified as bread wheat with white flour. [ABSTRACT FROM AUTHOR]

Recently developed selection indexes provide solutions for plant breeding, using linear‐bilinear models that consider factors as fixed or random. This work aimed to compare the multitrait selection indexes based on factor analysis and ideotype‐design (FAI‐BLUP), GGE biplot, and grain yield × trait index (GYT), and proposes the use of predicted genetic values together with the GYT index (best linear unbiased prediction used in grain yield*trait index, GYT‐BLUP). In addition, this work indicates the best index to select superior soybean [Glycine max (L.) Merr.] genotypes, closer to the ideotype. Data from 35 homozygous soybean lines and four checks, were obtained from trials conducted in six locations in the southern region of Brazil in the 2014/2015 crop season. The grain yield, yield components, morphological and grain composition were evaluated. Phenotypic data were used for GGE biplot and GYT analysis, using the software GGE biplot. Genetic values were predicted with mixed models considering genotype and location as random and fixed effects, respectively. Thus, genetic values were used in GYT‐BLUP and FAI‐BLUP indexes. These methods were compared by Spearman's rank correlation. Genetic gains obtained by indexes and traits were estimated. Soybean lines L1 and L22, and cultivars C3 and C4 were selected based on their performance for multiple traits, for indexes used. Thus, we suggest to combined FAI‐BLUP and GYT‐BLUP indexes. The GYT‐BLUP has a high importance for grain yield, which was related to all other traits. FAI‐BLUP gave similar weights for all traits. So, combining different approaches can provide better answers to breeders. [ABSTRACT FROM AUTHOR]

An optimal number of test locations and replications in yield trials allows improvements in the efficiency of a breeding program and selection reliability. The objectives of this study were to verify the optimal number of test locations and replications per test location in edaphoclimatic regions (ECR) and macroregions (MRs) of soybean adaptation in Brazil. Grain yield data from 184 soybean trials in 57 locations was evaluated in crop seasons 2012–2013 to 2015–2016. The number of replications currently used (3) is sufficient to achieve selection reliability and reduce costs in all MRs. However, the optimal number of replications needs to be determined for each location. Locations that require a high number of replicates to achieve H = 0.75 must be removed and/or replaced to improve selective accuracy. The optimal mean number of test locations in macroregions MR1 and MR2 is seven locations per ECR, and in MR3 and MR4, it is five locations per ECR. Thus, analyses of the optimal number of locations and replications may be applied to other regions to improve the yield trial efficiency of soybean cultivars. [ABSTRACT FROM AUTHOR]

Wheat (Triticum aestivum L.) is one of the most important crops in the world. Brazil is one of the largest importers of this cereal, and wheat breeding programs are attempting to increase productivity and reduce external dependence. The objectives of this study were to quantify the spring wheat genetic gain in Brazil between 1984 and 2014 using data from multienvironment trials, and to verify if the genetic gain stagnated after the 2000s. This study used a highly unbalanced dataset containing grain yield (GY) data from 187 spring wheat trials that were performed at 25 locations between 2002 and 2015. In total, 126 cultivars, released between 1985 and 2014, were evaluated over 14 crop seasons. The cultivar evaluation indicated that there was a genetic gain in GY of 33.9 kg ha−1 yr−1 (r2 = 0.53, P < 0.01), which represents an increase of 1.28% yr−1. The dataset showed a linear regression for the genetic gain and indicates that wheat genetic gain has not stagnated in Brazil after the 2000s. [ABSTRACT FROM AUTHOR]

Mega‐environment (ME) identification is the first step for evaluating, selecting and recommending genotypes within a target region (TR). The present study aimed to (a) identify MEs, using GGE biplot methods, in Brazilian edaphoclimatic region (ECR) 402 of soybean cultivation, located in the Mato Grosso State (the TR) and (b) compare the performance of genotypes within the TR and in each ME using fixed and mixed models. Data from three years of soybean yield trials, 19 genotypes and 22 environments were used. The biplots GGE, GGL + GGE and GGS + GGE were implemented to identify the MEs. Two MEs were identified in the TR. ME1 presents a higher altitude, farms which use a higher level of fertilizer inputs and a higher occurrence of the soybean cyst nematode (SCN) than ME2. When selection and recommendation are made based on MEs, genotypes with both broadly and specific adaptation can be selected. This action can improve grain yield in the entire target region. [ABSTRACT FROM AUTHOR]

Soybean [Glycine max (L.) Merr.] maturity group (MG) is an important concept used to determine the most suitable macroregion and edaphoclimatic region (ECR) in which soybean can best use the available resources. This classification is based on the number of days between sowing and maturation in the soybean life cycle. The MG is related to photoperiod; thus, the longer the photoperiod, the shorter the MG of cultivars must be to have an adequate life cycle. However, there is no consensus on which MGs are the most suitable for each region to improve grain yield. The objective of this study was to identify suitable soybean MGs for cultivation in the macroregions and ECRs in Brazil. During 4 yr of evaluation, grain yield data from 247 yield trials over 83 locations, encompassing four macroregions and 14 ECRs in Brazil, were used. Cultivars were grouped according to their MG for statistical analyses. Using these groups, the ideal genotypes and performance according to local analyses were determined. The best adapted and most productive cultivars were those with an intermediate MG in their predefined adaptation region (both macroregions and ECR). The maturities that performed the best in each macroregion were as follows: M1 (cultivars in MGs 5.3-5.9) M2 (cultivars in MGs 6.0-7.0), M3 (cultivars in MGs 7.1-7.9), and M4 (cultivars in MGs 7.7-8.4). A lower productivity was observed in cultivars in extreme MGs for each macroregion. Breeding program efforts should target the MGs identified as ideal for each ECR to develop cultivars with a greater chance of achieving high yields and with greater adaptability to the specific region. [ABSTRACT FROM AUTHOR]

Several studies have shown a significant increase in wheat (Triticum aestivum L.) grain yield (GY) worldwide during the 20th century as a result of genetic and environmental improvement. The objective of this study was to measure the genetic gains achieved in a wheat breeding program maintained by the Central Cooperative of Agricultural Research (COO DETEC) in Brazil through the annual evaluation of lines in multienvironment trials. The dataset was composed of 836 advanced trials and was evaluated in 40 representative locations to assess the value for cultivation and use (VCU) regions in the south, southeast, and central-west areas of the country from 2004 to 2013. Each trial consisted of 25 treatments (lines + checks) in a randomized complete block design with three replicates. A linear mixed model was fitted to predict the genetic values of each genotype per year and a restricted maximum likelihood algorithm to estimate the variance components. These genetic values were used to compute the genetic gain over the years. The overall estimated genetic gain of the breeding program was 61.59 kg ha-1 yr-1 (1.68% yr-1) for GY, although it was partially counterbalanced by the estimated negative environmental effects. The genetic gain per VCU region ranged from 31.38 (VCU 4) to 115.33 kg ha-1 yr-1 (VCU 1). After accounting for the environmental changes over years, the yield gain was 39.40 kg ha-1 yr-1 (1.10% yr-1), ranging from -0.82 (VCU 3) to 3.35% yr-1 (VCU 1). The assessment of Brazilian cultivars released between 1998 and 2014 showed genetic gains in GY of 34.8 kg ha-1 yr-1 (1% yr-1), demonstrating that the efforts of Brazilian research institutions to develop cultivars have produced additive results. The implications of genetic gain estimates on breeding programs are discussed. [ABSTRACT FROM AUTHOR]

Copyright of Cientifica is the property of Fundacao de Apoio a Pesquisa e Extensao and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The aim of this study was to evaluate the experimental precision of different methods of statistical analysis for trials with large numbers of soybean genotypes, and their relationship with the number of replicates. Soybean yield data (nine trials; 324 genotypes; 46 cultivars; 278 lines; agricultural harvest of 2014/15) were used. Two of these trials were performed at the same location, side by side, forming a trial with six replicates. Each trial was analyzed by the randomized complete block, triple lattice design, and use of the Papadakis method. The selective accuracy, least significant difference, and Fasoulas differentiation index were estimated, and model assumptions were tested. The resampling method was used to study the influence of the number of replicates, by varying the number of blocks and estimating the precision measurements. The experimental precision indicators of the Papadakis method are more favorable as compared to the randomized complete block design and triple lattice. To obtain selective accuracy above the high experimental precision range in trials with 324 soybean genotypes, two repetitions can be used, and data can be analyzed using the randomized complete block design or Papadakis method [ABSTRACT FROM AUTHOR]

Copyright of Revista Ceres is the property of Revista Ceres and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Multi-environment trials often yield unbalanced datasets, thus necessitating the estimation of missing values. It is unknown whether this estimation affects the graphic characteristics of genotype plus genotype-by-environment interaction (GGE) biplots. Therefore, our objectives were to investigate the effects of different percentages of missing values on the number of significant principal components (PCs) and on mega environments, “winner” (highest-performing) genotypes, and the amount of variation explained by the PCs. Two complete sets of two-way data from wheat (Triticum aestivum L.) were used. The first set consisted of the original data (Data1, from which we created scenarios with 0, 30, and 60% missing data. For the second dataset (Data2), we removed 50% data from the original dataset, estimated missing values to make it a new complete dataset, and created scenarios like those for Data1. Missing values were estimated via expectation-maximization–GGE (EM–GGE) and EM–additive main effects and multiplicative interaction (EM–AMMI) methods. The percentage of variation explained by the PCs was affected by the percentage of missing data; a large percentage of missing values considerably increased the amount of variation explained by PC 1 and PC 2 and reduced the complexity of the genotype-by-environment interaction because two PCs accounted for more than 80% of the variation, instead of the three PCs that were required to explain the variation in the original dataset. The EM–GGE estimation method was able to maintain the original conformation of the ‘which-won-where’ biplot when ≤30% of estimated data were used. The EM–GGE was superior to the EM–AMMI method for estimating missing data. The estimation of more than 30% of the data should be avoided because it can lead to significant changes in mega environment conformation and the identification of “winner” genotypes. [ABSTRACT FROM AUTHOR]

In wheat (Triticum aestivum L.) several studies have reported genetic gain for grain yield over the years. However, studies on wheat bread-making quality are scarce. Our objective was to estimate the progress due to genetic and environmental components in wheat breadmaking quality parameters. In addition, we aimed to examine trends in historical cultivars and associate traits performance with geographical parameters. We used data from multi-environment trials (MET) represented by eight years (2005-2012) and 458 genotypes, including lines and commercial cultivars (controls). We determined the genetic progress by the contrasts between genotypes assessed in each biennium, excluding the year effect. This effect is previously estimated by existing variation among common genotypes. Genotype replacement rate was 52% and reflects the dynamism of the breeding program to develop better genotypes in terms of bread-making quality. The genetic progress estimated for gluten strength (W) was 1.30% yr-1. The progress in W demonstrated to be partly counterbalanced by the environmental effect (-0.78% yr-1). We observed disequilibrium tendency in relationship between tenacity and extensibility (P/L ratio) as a consequence of searching for lines with high W. Analysis showed that P/L ratio can be reduced in responses to the increase in latitude of the location. Environmental and genetic effects on the traits variation were discussed. [ABSTRACT FROM AUTHOR]

Deoxynivalenol (DON) is a mycotoxin produced by Fusarium graminearum and its intake represents a severe risk to human and animal health. The objective of this study was to evaluate levels of DON in wheat (Triticum aestivum L.) flour from two representative locations of south Brazil. Experiments were carried out in Pato Branco (Paraná) and Coxilha (Rio Grande do Sul) in a randomized complete block design with three replicates. Levels of DON were measured by high-performance liquid chromatography coupled with mass spectrometry (HPLC-MS/MS). This mycotoxin was detected in 97% of samples, ranging from 200 to 4140 µ g kg-1. Only 17% of samples presented DON beyond of the maximum allowed by the Brazilian Health Surveillance Agency up to the year 2012; even though, Fusarium head blight (FHB) epidemics were slight low in the growing season that the study was performed. According to our knowledge, this is the first report showing genetic variability of Brazilian cultivars to DON contamination and some genotypes have potential to be exploited as a source of low accumulation of this toxin. [ABSTRACT FROM AUTHOR]

Copyright of Agricultural Research in the Tropics / Pesquisa Agropecuária Tropical is the property of Pesquisa Agropecuaria Tropical and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The objectives of this study were to investigate the pattern of genotype environment interaction and identify megaenvironments (ME), essential test locations, and suitable genotypes for each ME. The genotype plus genotype by environment interaction (GGE) biplot and additive main effects and multiplicative interaction analysis (AMMI) were used to demonstrate the potential of using a graphical biplot to analyze the genotype by environment interaction (GEI) in data of multienvironment trials (MET). These trials of the Central Cooperative Agricultural Research (COODETEC) evaluated 36 advanced breeding lines and 27 check cultivars for 3 years (2008- 2010) at 12 test locations. Yield data were analyzed using the genotype plus GGE and AMMI biplot methods. The test environments were classified into two ME (i.e. ME1: Castro, Guarapuava, Não-Me-Toque, Abelardo Luz, and Cachoeira do Sul; and ME2: Campo Mourão, Dourados, Palmital, Palotina, Ponta Porã, and Rolândia. In ME1, the locations Guarapuava, Cachoeira do Sul, and Abelardo Luz were classified as ideal, while in ME2, Ponta Porã, Dourados and Palotina were close to ideal. Guarapuava was the essential test location in ME1; however the identification of an essential test location in ME2 was unclear. Superior cultivars and advanced lines were identified in both ME that could be valuable for spring wheat (Triticum aestivum L.) improvement or cultivars released. [ABSTRACT FROM AUTHOR]

Choosing the right sowing dates can maximize the outcomes of the interaction between genotype and environment, thus increasing grain yield and baking quality of wheat (Triticum aestivum L.). The present study aimed at determining the most appropriate sowing dates that maximize grain yield and baking quality of wheat cultivars. Seven wheat cultivars (BRS 179, BRS Guamirim, BRS Guabiju, BRS Umbu, Safira, CD 105 and CD 115) were evaluated at four sowing dates (the 1st and the 15th of June and July) in two harvesting seasons (2007 and 2008). The study was setup in a completely randomized block design with four repetitions. The effects of the year and sowing date when combined explained 93% of the grain yield variance. In 2007, the CD 105 and Safira cultivars had the highest grain yield (GY) for all sowing dates. Only the BRS Guabiju and Safira cultivars possessed high baking quality for all sowing dates assessed. In 2008, the environmental conditions were favorable for superior GY, but the baking quality was inferior. Considering adapted cultivars and sowing dates, it is possible to maximize grain yield and baking quality of wheat. [ABSTRACT FROM AUTHOR]

The objective of this study was to determine the optimal number of tests required to predict the performance of grain yield of wheat genotypes in different regions of Value for Cultivation and Use (VCU), with a view to selecting and recommending cultivars. Grain yield data from 285 field trials at 31 locations in the VCU Regions 1, 2, 3 and 4 in 2007-2011 were used. There are differences among VCU regions with reference to the repeatability coefficient and the number of tests required for a predetermined accuracy. It was noted the need to raise the number of tests VCU regions 2 and 4 and reduce the number of trials in the regions of VCU 1 and 3. In regions VCU 1, 2, 3 and 4, to a level of 80% accuracy, are required 8, 14, 10 and 12 tests, respectively. [ABSTRACT FROM AUTHOR]

The potential yield of wheat is mainly determined by temperature, solar radiation and the photothermal quotient. The objective of this study was to determine the temporal and spatial variability of the photothermal quotient and the frost risk to identify suitable sowing dates for wheat in Parana State, Brazil. The results showed that the photothermal quotient has greater spatial variability than temporal variability. The sowing date affects crop conditions that can in turn affect yield. However, the photothermal quotient and frost risk fluctuate differently in different Value for Cultivation and Use (VCU) regions. The regions VCU 1 and VCU 2 showed greater temporal variability of the photothermal quotient. The photothermal quotient ranged from 1.5 to 2.0 MJ m-2 day ºC in VCU 1, from 1.1 to 1.5 MJ m-2 day ºC in VCU 2 and from 1.0 to 1.2 MJ m-2 day ºC in VCU 3. Sowing performed in June provided the greatest photothermal quotient in all VCU regions. However, June sowing increased the frost risk in VCU 1. Thus, the sowing date can be used as a management tool for the attainment of higher yield in wheat. [ABSTRACT FROM AUTHOR]

The genotype environment interaction (GE) influences on the selection and recommendation of cultivars. Biplot analysis has been increasingly used in data analysis of complex traits in agriculture. However the peculiarities of biplot graphic could induce the researcher to errors on interpretation. Thus, this review argues the applicability and graphic interpretation of models AMMI (Additive Main Effects and Multiplicative Interaction) and GGE biplof (genotype main effects + genotype environment interaction). Moreover, also aims to explain that it is not adequate to compare both statistical methods. It is discussed the best methodology considering the information required and the research objectives. [ABSTRACT FROM AUTHOR]

The release of wheat cultivars with different nutritional demands and yield potential hinders generalized recommendations for nitrogen fertilization. This study was designed to evaluate the effects of different nitrogen fertilization levels (0, 60, 120 and 180 kg ha-1 of N) on the agronomic performance of six wheat cultivars (Triticum aestivum L.) in two harvests. A randomized block factorial design with three replications was used. The response to fertilization levels was evaluated through AMMI (Additive Main effects and Multiplicative Interaction) and GGE (Genotype main effects and Genotype x Environment interaction) biplot graphic methodologies and polynomial regression. There was genetic variability in response to nitrogen fertilization in the cultivars studied. The biggest increases in yield were observed under a more suitable water regime. The higher performance of yield components was associated with higher nitrogen fertilization levels. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Ciências Agrárias is the property of Sociedade de Ciencias Agrarias de Portugal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Technological performance represents an opportunity to add market value to wheat, especially considering international market and industrial sector which seek to achieve distinctive quality of their products. Genetic, metereological, and management factors are crucial to obtain the desired quality. With respect to the selection of an adequate cultivar, knowledge about the climatic limitations of the wheat-growing region and soil fertility, and accomplishing the management practices recommended by research can substantially contribute toward obtaining the physical, chemical, and biological characteristics that lend quality to flour and flour-based products, as discussed in this review. [ABSTRACT FROM AUTHOR]

In this study, we summarized the evolution of scientific research about fungus Phakopsora pachyrhizi Sydow & Sydow affecting soybean [Glycine max (L.) Merrill]. We retrieved research articles from the Thomson Reuters Web of Science database that reported studies of the Asian soybean rust (ASR) from 1945 to 2018. We applied the scientometric analysis of the temporal trends of authors, journals, research partnerships, and resistance genes to ASR. Several studies aiming to understand fungal etiology, testing, or improve strategies to control the pathogen were developed. The temporal trends in publications showed an increase in the number of publications between 2005 and 2013. This is directly related to the dissemination of ASR in South and later North America, which facilitates field research and an increase in grant opportunities. The USA had the highest number of published articles (42%), followed by Brazil, Germany, Japan, and Argentina. The leading organizations associated with these publications are from Brazil and the USA. 19% of articles pertaining to ASR were published in the journal Plant Disease. Our results also showed that among the seven dominant genes identified for resistance to ASR, Rpp1, and Rpp2 are the most studied. Several countries, institutions, and plant scientists are deeply involved in ASR research and have been making efforts to control this disease and ensure food security worldwide. [ABSTRACT FROM AUTHOR]