Using artificial neural networks to select upright cowpea (Vigna unguiculata) genotypes with high productivity and phenotypic stability.

Cowpea (Vigna unguiculata) is grown in three Brazilian regions: the Midwest, North, and Northeast, and is consumed by people on low incomes. It is important to investigate the genotype x environment (GE) interaction to provide accurate recommendations for farmers. The aim of this study was to identify cowpea genotypes with high adaptability and phenotypic stability for growing in the Brazilian Cerrado, and to compare the use of artificial neural networks with the Eberhart and Russell (1966) method. Six trials with upright cowpea genotypes were conducted in 2005 and 2006 in the States of Mato Grosso do Sul and Mato Grosso. The data were subjected to adaptability and stability analysis by the Eberhart and Russell (1966) method and artificial neural networks. The genotypes MNC99-537F-4 and EVX91-2E-2 provided grain yields above the overall environment means, and exhibited high stability according to both methods. Genotype IT93K-93-10 was the most suitable for unfavorable environments. There was a high correlation between the results of both methods in terms of classifying the genotypes by their adaptability and stability. Therefore, this new approach would be effective in quantifying the GE interaction in upright cowpea breeding programs.

Clustering of soybean genotypes via Ward-MLM and ANNs associated with mixed models.

The objectives of this study were to use mixed models to confirm the presence of genetic variability in 16 soybean genotypes, to compare clusters generated by artificial neural networks (ANNs) with those created by the Ward modified location model (MLM) technique, and to indicate parental combinations that hold promise for obtaining superior segregating populations of soybean. A field trial was conducted between November 2014 and February 2015 at Universidade Estadual de Mato Grosso do Sul, Aquidauana, MS. The experimental design consisted of four replications of randomized blocks, each containing 16 treatments. We assessed the following agronomic traits: plant height, first pod height, number of branches per plant, number of pods per plant, number of grains per pod, hundred-grain weight, and grain yield. Mixed models were used to estimate variance components and genetic parameters, and obtain genotypic values for each trait. After verifying the presence of genetic variability for all traits, genotypic values were submitted to both a Ward-MLM procedure and ANNs to estimate genetic divergence among genotypes. The number of groups formed by both methods was the same, but there were differences in group constitutions. ANN analysis improved soybean genotypes clustering patterns compared to Ward-MLM procedure. Based on these methods, divergent crosses may be made between genotype 97R73 with genotypes AS3797 and SYN9070, whereas convergent crosses may be made between genotypes AS3797 and SYN9070.

Selection of common bean (Phaseolus vulgaris L.) genotypes using a genotype plus genotype x environment interaction biplot.

Recently, the genotype plus genotype x environment interaction (GGE) biplot methodology has been used to investigate genotype x environment interactions in several crop species, but has not been applied to the common bean (Phaseolus vulgaris L.) crop in Brazil. The aim of this study was to identify common bean genotypes that exhibit high grain yield and stability in the State of Mato Grosso do Sul, Brazil. We conducted 12 trials from 2000 to 2006 in the municipalities of Aquidauana and Dourados, and evaluated 13 genotypes in a randomized block design with three replications. Grain yield data were subjected to individual and joint analyses of variance. After analyzing the GE interaction, the adaptability and phenotypic stability of the common bean genotypes were analyzed using GGE biplot methodology. The genotypes EMGOPA-201, Xamego, and Aporé are recommended for growing in Mato Grosso do Sul, because they exhibited high grain yield and phenotypic stability.

Identification of sorghum hybrids with high phenotypic stability using GGE biplot methodology.

The aim of this study was to identify sorghum hybrids that have both high yield and phenotypic stability in Brazilian environments. Seven trials were conducted between February and March 2011. The experimental design was a randomized complete block with 25 treatments and three replicates. The treatments consisted of 20 simple pre-commercial hybrids and five witnesses of grain sorghum. Sorghum genotypes were analyzed by the genotype main effects + genotype environment interaction (GGE) biplot method if significant genotype x environment interaction, adaptability, and phenotypic stability were detected. GGE biplot methodology identified two groups of environments, the first composed of Água Comprida-MG, Montividiu-GO, and Vilhena- RO and the second of Guaíra-SP and Sete Lagoas-MG. The BRS 308 and 1G282 genotypes were found to have high grain yield, adaptability, and phenotypic stability and are thus indicated for cultivation in the first and second groups of environments, respectively.

Adaptability and phenotypic stability of common bean genotypes through Bayesian inference.

This study used Bayesian inference to investigate the genotype x environment interaction in common bean grown in Mato Grosso do Sul State, and it also evaluated the efficiency of using informative and minimally informative a priori distributions. Six trials were conducted in randomized blocks, and the grain yield of 13 common bean genotypes was assessed. To represent the minimally informative a priori distributions, a probability distribution with high variance was used, and a meta-analysis concept was adopted to represent the informative a priori distributions. Bayes factors were used to conduct comparisons between the a priori distributions. The Bayesian inference was effective for the selection of upright common bean genotypes with high adaptability and phenotypic stability using the Eberhart and Russell method. Bayes factors indicated that the use of informative a priori distributions provided more accurate results than minimally informative a priori distributions. According to Bayesian inference, the EMGOPA-201, BAMBUÍ, CNF 4999, CNF 4129 A 54, and CNFv 8025 genotypes had specific adaptability to favorable environments, while the IAPAR 14 and IAC CARIOCA ETE genotypes had specific adaptability to unfavorable environments.

Simultaneous selection for cowpea (Vigna unguiculata L.) genotypes with adaptability and yield stability using mixed models.

The aim of this study was to select erect cowpea (Vigna unguiculata L.) genotypes simultaneously for high adaptability, stability, and yield grain in Mato Grosso do Sul, Brazil using mixed models. We conducted six trials of different cowpea genotypes in 2005 and 2006 in Aquidauana, Chapadão do Sul, Dourados, and Primavera do Leste. The experimental design was randomized complete blocks with four replications and 20 genotypes. Genetic parameters were estimated by restricted maximum likelihood/best linear unbiased prediction, and selection was based on the harmonic mean of the relative performance of genetic values method using three strategies: selection based on the predicted breeding value, having considered the performance mean of the genotypes in all environments (no interaction effect); the performance in each environment (with an interaction effect); and the simultaneous selection for grain yield, stability, and adaptability. The MNC99542F-5 and MNC99-537F-4 genotypes could be grown in various environments, as they exhibited high grain yield, adaptability, and stability. The average heritability of the genotypes was moderate to high and the selective accuracy was 82%, indicating an excellent potential for selection.

Artificial intelligence in the selection of common bean genotypes with high phenotypic stability.

Artificial neural networks have been used for various purposes in plant breeding, including use in the investigation of genotype x environment interactions. The aim of this study was to use artificial neural networks in the selection of common bean genotypes with high phenotypic adaptability and stability, and to verify their consistency with the Eberhart and Russell method. Six trials were conducted using 13 genotypes of common bean between 2002 and 2006 in the municipalities of Aquidauana and Dourados. The experimental design was a randomized block with three replicates. Grain yield data were submitted to individual and joint variance analyses. The data were then submitted to analysis of adaptability and stability through the Eberhart and Russell and artificial neural network methods. There was high concordance between the methodologies evaluated for discrimination of phenotypic adaptability of common bean genotypes, indicating that artificial neural networks can be used in breeding programs. Based on both approaches, the genotypes Aporé, Rudá, and CNFv 8025 are recommended for use in unfavorable, general and favorable environments, respectively by the grain yield above the overall average of environments and high phenotypic stability.

Measurements of experimental precision for trials with cowpea (Vigna unguiculata L. Walp.) genotypes.

The aim of this study was to evaluate the suitability of statistics as experimental precision degree measures for trials with cowpea (Vigna unguiculata L. Walp.) genotypes. Cowpea genotype yields were evaluated in 29 trials conducted in Brazil between 2005 and 2012. The genotypes were evaluated with a randomized block design with four replications. Ten statistics that were estimated for each trial were compared using descriptive statistics, Pearson correlations, and path analysis. According to the class limits established, selective accuracy and F-test values for genotype, heritability, and the coefficient of determination adequately estimated the degree of experimental precision. Using these statistics, 86.21% of the trials had adequate experimental precision. Selective accuracy and the F-test values for genotype, heritability, and the coefficient of determination were directly related to each other, and were more suitable than the coefficient of variation and the least significant difference (by the Tukey test) to evaluate experimental precision in trials with cowpea genotypes.

Bayesian approach increases accuracy when selecting cowpea genotypes with high adaptability and phenotypic stability.

This study aimed to verify that a Bayesian approach could be used for the selection of upright cowpea genotypes with high adaptability and phenotypic stability, and the study also evaluated the efficiency of using informative and minimally informative a priori distributions. Six trials were conducted in randomized blocks, and the grain yield of 17 upright cowpea genotypes was assessed. To represent the minimally informative a priori distributions, a probability distribution with high variance was used, and a meta-analysis concept was adopted to represent the informative a priori distributions. Bayes factors were used to conduct comparisons between the a priori distributions. The Bayesian approach was effective for selection of upright cowpea genotypes with high adaptability and phenotypic stability using the Eberhart and Russell method. Bayes factors indicated that the use of informative a priori distributions provided more accurate results than minimally informative a priori distributions.

Carcinoma neuroendocrino de vejiga en mujer con infección por VIH: presentación del primer caso mundial / Neuroendocrine carcinome of the bladder in a female with HIV infection: presentation of the first case worldwide

El carcinoma neuroendocrino primario de vejiga es una neoplasia infrecuente que representa el 0,5por ciento de todos los tumores vesicales. La asociación de carcinoma neuroendocrino de vejiga en un paciente con infección por VIH nunca hasta hoy había sido descrita. Presentamos el primer caso clínico español y mundial de esta desconocida y nunca descrita asociación. MATERIAL Y MÉTODOS: Se presenta el caso clínico de una paciente de 46 años con infección por VIH que desarrolló un carcinoma neuroendocrino de vejiga urinaria de evolución fatal. Se describe su clínica de presentación, métodos de diagnóstico utilizados y su tratamiento. La paciente debutó con retención urinaria aguda que rápidamente progresó a la instauración de una uropatía obstructiva alta con deterioro de la función renal. El diagnóstico se efectuó mediante TAC, resección transuretral y estudio histopatológico donde la clave del diagnóstico fue el estudio inmunohistoquímico intensamente positivo para la cromogranina A. El tratamiento adyuvante con quimioterapia le ocasionó una aplasia medular severa, falleciendo por fallo multiórganico a los 26 días de su diagnóstico. A propósito de este caso, se revisa la literatura inglesa en PubMed sobre carcinoma neuroendocrino de vejiga y sobre tumores vesicales en pacientes con infección VIH, no existiendo ningún caso publicado de carcinoma neuroendocrino de vejiga en un paciente con infección por VIH. CONCLUSIONES: El carcinoma neuroendocrino de vejiga es un tumor infrecuente y muy agresivo. Es un tumor que suele presentarse clínicamente en estadios avanzados o metastásicos donde ninguna terapia es eficaz. El tratamiento incluye resección trans-uretral (RTU), cistectomía parcial, cistectomía radical y quimioterapia. El estudio inmunohistoquímico (IHQ) y la tinción con cromogranina A dan la clave para su diagnóstico. Su presentación en pacientes VIH implica muy mal pronóstico. Éste caso es el primer caso mundial publicado de carcinoma neuroendocrino...

The primary neuroendocrine carcinome of the bladder is an infrequent neoplasm which represents 0.5 percent of all vesical tumors. The association of neuroendocrine carcinome of the bladder in a patient with HIV infection has never been described before today. We present the first clinical case in the Spanish-speaking world and worldwide, of this unknown and never written about association. MATERIAL AND METHODS: The clinical case of a 46-yearoldpatient with HIV infection who developed a neuroendocrine carcinoma of the urinary bladder with a fatal evolution, its clinical presentation, the diagnosis methods used and its treatment, are described. The patient started with a severe urinary retention which rapidly progressed to the establishment of a high obstructive uropathy with deterioration in the renal function. The diagnosis was done using TAC, transurethral resection and histopathological study where the key to diagnosis was the intensely positive immunohistochemical study for the chromogranin A. The adjuvant treatment with chemotherapy led to a severe medular aplasia, with the patient dying due to a multi-organ failure, 26 days after her diagnosis. As a result of this case, English literature on the matter in PubMed about neuroendocrine carcinome of the bladder and about vesical tumors in patients with HIV infection was revised, with no published case existing about neuroendocrine carcinome in a patient with HIV. CONCLUSIONS: The neuroendocrine carcinome of the bladder is an infrequent and very aggressive tumor. It is a tumor that tends to be clinically present in advanced or metastasic states, where no therapy is efficient. The treatment includes transurethral resection (TUR), partial cystectomy, radical cystectomy and chemotherapy. The immunohistochemical study (IHC), and the stain with chromogranin A are key for its diagnosis. Its presentation in HIV patients implies a very bad prognosis. This case is the first published case worldwide of neuroendocrine...