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As wheat blast is one of the most damaging disease of wheat worldwide and extremely important in Brazil, in this work we are trying to summarize the scientific research direction and temporal trends about the disease. We summarized the evolution of scientific research from the Thomson Reuters Web of Science database, through bibliometrix analysis of the temporal trends of authors, organizations and journals. During 31 years, 521 publications approach wheat blast was published, with an annual growth rate of 3.86%. Different countries were identified, being the USA, Brazil and China the lead of publications. The main organizations are Brazilian federal institutions Empresa Brasileira de Pesquisa Agropecuária, followed by Kobe University, Kansas State University, Agriculture Research Service of United States Department of Agriculture. A total of 168 journals were identified in wheat blast publications in bibliometric analysis, being Phytopathology the journal with most publications about wheat blast, with 14.2% of publications (74 documents). Considering the 521 documents, the bibliometric analysis reported a total of 1941 authors, and thirteen authors are ranked as the main authors by h-index. Among the 20 most relevant terms, in keywords and keywords plus, in the documents related to wheat blast emphasize that three main ones are related to the fungus and the culture, being "Magnaporthe grisea", "Wheat" and "Pyricularia oryzae". These authors, organizations and journals have a great importance in plant disease research, and in addition they are recognized by worldwide researches. In this sense, the breeding programs should be encouraged in the search for blast. [ABSTRACT FROM AUTHOR]

Asian soybean rust (ASR) causes large reductions in soybean yield, affecting the entire grain market. With low fungicide efficiency, the use of resistant cultivars can be an economical, safe, efficient, and sustainable control alternative. However, the great variability and aggressiveness of ASR and the use of Rpp genes are limited. Thus, gene pyramiding is a promising strategy for the development of cultivars with high resistance to a greater number of isolates. Thus, the objective of this study was to evaluate sister lines, previously evaluated by Meira et al. (2022). https://doi.org/10.1007/s10681-020-02667-x), presenting different Rpp-pyramided genes for resistance to Phakopsora pachyrhizi to clarify the pyramiding effect of two originally developed Rpp-pyramided lines compared to two existing lines or lines possessing only a single Rpp of resistance under field conditions. Rpp-pyramided lines 52117-1 (Rpp2 + Rpp1-b), 52117-57 (Rpp2 + Rpp1-b), 52117-59 (Rpp2 + Rpp1-b) + 52117-60 (Rpp2 + Rpp4) showed high resistance levels compared to resistant sources and resistance control, carrying a single Rpp gene PI 200487 (Rpp5), PI 200492 (Rpp1), PI 230970 (Rpp2), PI 459025A (R pp4), and PI 506764 (Rpp3 + Rpp5) with significant reductions in sporulation levels (SL), number of uredinia per lesion (NoU), and frequency of lesions with uredinia (%LU). Only, the line 52117-54 (Rpp2 + Rpp1-b), and 52117-63 (Rpp2 + Rpp4) showed resistance level smaller than PI 594723 (Rpp1-b) and similar resistance levels than PI 230970 (Rpp2), respectively. Rpp-pyramided lines carrying Rpp2 + Rpp1-b (52116-54, 52116-74, 52117-21, 52117-59 and 52117-60), and Rpp2 + Rpp4 (52117-60), and single gene Rpp1-b were classified as "highly resistant" and "resistant". Furthermore, one sister line, 52117-57 (Rpp2 + Rpp1-b), showed immunity under field conditions. The Rpp-pyramided genes are an alternative for achieving high resistance levels against ASR. [ABSTRACT FROM AUTHOR]

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]

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]

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]

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]

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Brazil is one of the largest soybean ( Glycine max L. Merrill) producers in the world, as well as main exporter. Little information is available about both the composition of Brazilian genotypes in respect to soluble sugars contents such as sucrose, glucose, raffinose and stachyose, and the effect of genotype × environment interaction (GEI). This study evaluated the soluble sugar contents, the GEI and the genetic variability of highly cultivated cultivars and new soybean lines. A sample of 46 commercial Brazilian cultivars and 35 pre-commercial lines were evaluated at six locations during the 2014/15 crop season, in a randomized complete block design with three replications. Soluble sugars were evaluated using an infrared spectroscopy (NIR) method. The average contents of sucrose, glucose, raffinose and stachyose were 3.3, 1.62, 0.39 and 3.07% which were lower than the levels found in other countries. All field traits were highly influenced by the environment. The cultivar NS 6121 RR presented a reduced (and stable across the environments) raffinose and stachyose content and can be used as a source of novel genes in breeding programs. Brazilian soybean presents genotypic differences which can be exploited to reduce or increase soluble sugar contents in breeding programs. There is a strong GEI for sucrose, glucose, raffinose and stachyose contents for Brazilian environments. The evaluated genotypes presented reduced contents of raffinose and stachyose, which are considered antinutritional factors. The new soybean lines presented similar soluble sugar contents to the tested cultivars. [ABSTRACT FROM AUTHOR]

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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]

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]

Copyright of Acta Scientiarum: Agronomy is the property of Universidade Estadual de Maringa 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.)

Copyright of Acta Scientiarum: Agronomy is the property of Universidade Estadual de Maringa 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.)

Copyright of Acta Scientiarum: Agronomy is the property of Universidade Estadual de Maringa 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.)

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.)

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]

Yield increase in soybean [Glycine max (L.) Merr.] has occurred due to plant breeding, as well as the improvement in management practices. Genetic gain for important traits in soybean due to plant breeding in South Brazil has not been evaluated. The objective of this study was to measure the genetic progress of several soybean agronomic, phenological and physiological traits, in a historical set of cultivars released for cultivation in South Brazil from 1965 to 2011. Twenty-nine cultivars were evaluated in a three replicate randomized complete block design at two locations in the 2016/17 crop season. Mean genetic gain for yield was 40.06 kg ha−1 year−1 averaged across locations. The modern cultivars had higher biological yield (BY), harvest index (HI), number of pods per plant (NPP), and lower number of branches per plant, plant height, and lodging score compared to older releases. There was a reduction in the vegetative period, and increase in ratio between reproductive and vegetative periods (R/V). Photosynthetic rate (PN) and transpiration rate (Tr) also increased with year of release. The traits BY, NPP, HI, R/V, number of seeds per pod, PN, Tr, and chlorophyll content (Chl a and b) was highly associated with seed yield. Breeding strategies that maximize the R/V ratio, and prioritize indirect selection through HI, BY, NPP, PN, Tr, and Chl a and b, will likely contribute to improving soybean yield in the future. [ABSTRACT FROM AUTHOR]

Breeding companies release new high-yielding soybean genotypes every year. The main trait is grain yield (GY), and the performance need to be evaluated by statistical methods to identify superior genotypes. Biplot analysis are good tools for selecting superior genotypes and to increase efficiency in selection. This study aimed to: (a) identify genotypes with high GY and stability in edaphoclimatic regions (ECR) in southern of Brazil; (b) compare the year-by-year and across-years analyses to identify ideal genotype (IG) for each ECR; and (c) identify the association between genotypes and locations using the across-year approach. GY data from yield trials performed in the crop seasons of 2013, 2014, and 2015 were used. The analysis of IG was performed for each year independently and across the years. Moreover, environment-genotype relationship analysis was used to identify the association between genotypes and ECR. Genotypes with high GY and widely adapted for each ECR were identify. The across-year analysis was superior to the year-by-year analysis. However, only genotypes evaluated in more than 1 year and in sufficient locations provide accurate information about GY and stability; otherwise, the results should be adopted with caution. [ABSTRACT FROM AUTHOR]

Genomic selection (GS) can potentially accelerate genetic improvement of soybean [Glycine max L. (Merrill)] by reducing the time to complete breeding cycles. The objectives of this study were to (1) explore the accuracy of GS in soybean, (2) evaluate the contribution of intrapopulational structure to the accuracy of GS, and (3) compare the efficiencies of phenotypic selection and GS in soybean. For this, phenotypic and genotypic data were collected from 324 soybean genotypes (243 recombinant inbred lines and 81 cultivars) and GS was performed for five yield related traits. BayesB methodology with a 10-fold cross-validation was used to compute accuracies. The GS accuracies were evaluated for grain yield, plant height, insertion of first pod, days to maturity, and 1000-grain weight at eight locations. We found that GS can reduce the time required to complete a selection cycle in soybean, which can lead to increased production of this commercially important crop. Furthermore, genotypic accuracy was similar regardless of population structure correction. [ABSTRACT FROM AUTHOR]