Global research on keratomycosis: New insights from latent Dirichlet allocation and HJ-Biplot-driven knowledge mapping study.

BACKGROUND: Keratomycosis is a form of infectious keratitis, an infection of the cornea, which is caused by fungi. This disease is a leading cause of ocular morbidity globally with at least 60 % of the affected individuals becoming monocularly blind. OBJECTIVE: This bibliometric analysis aimed to comprehensively assess the existing body of literature, providing insights of the evolution of keratomycosis research by identifying key themes and research gaps. METHODS: This work used the modeling method Latent Dirichlet Allocation (LDA) to identify and interpret scientific information on topics concerning existing categories in a set of documents. The HJ-Biplot method was also used to determine the relationship between the analyzed topics, taking into consideration the years under study. RESULTS: This bibliometric analysis was performed on a total of 2,599 scientific articles published between 1992 and 2022. The five leading countries with more scientific production and citations on keratomycosis were The United States of America, followed by India, China, United Kingdom and Australia. The top five topics studied were Case Reports and Corneal Infections, which exhibited a decreasing trend; followed by Penetrating Keratoplasty and Corneal Surgery, Ocular Effects of Antifungal Drugs, Gene Expression and Inflammatory Response in the Cornea and Patient Data which have been increasing throughout the years. However Filamentous Fungi and Specific Pathogens, and Antifungal Therapies research has been decreasing in trend. CONCLUSION: Additional investigation into innovative antifungal drug therapies is crucial for proactively tackling the potential future resistance to antifungal agents in scientific writing.

Evaluation of adaptability and stability for iron, zinc and protein content in cowpea genotypes using GGE biplot approach.

Cowpea is a widely cultivated crop in the world. Biofortification strategies aim to reduce mineral and protein deficiencies, especially among the poorest people. The aim of this study was to estimate adaptability and stability of cowpea genotypes for iron, zinc and protein contents, through GGE biplot analysis. Twenty cowpea genotypes were evaluated in the municipalities of Piauí Monsenhor Hipólito, Pio IX and São Miguel do Tapuio, under rainfed conditions. The experimental design was a randomized block design with four replications. The traits evaluated were grain yield, iron, zinc and protein contents in dry grains. Iron (Fe) and zinc (Zn) were determined by flame atomic absorption spectrophotometer, and protein contents by Kjeldahl methods. Adaptability and stability were evaluated by GGE biplot analyses. The means of the experiments were 1,209.1 kg ha-1, 51.1 mg kg-1, 46.8 mg kg-1 and 24.3% for grain yield, Fe, Zn and protein contents, respectively. The joint analysis of variance showed significant difference (p < 0.05) for the effect of interaction genotypes by environments for Fe, Zn and protein contents. The lines G6 and G8 were the most promising for grain yield, mineral and protein content through adaptability and stability by GGE biplot approach.

Neuroendocrine Tumors: An Analysis of Prevalence, Incidence, and Survival in a Hospital-Based Study in Ecuador.

Neuroendocrine tumors (NETs) represent a heterogeneous malignancy group of neoplasms, with a limited amount of data from Latin America. Thus, this observational study aimed to provide data about the prevalence, incidence, and survival rates for NET in Ecuadorian hospitals. The study was conducted using data from the Society for the Fight Against Cancer (SOLCA). We evaluated patients with NETs (2000−2020) using the HJ-Biplot method and Cox proportional hazards. Annual age-adjusted incidence and limited-duration prevalence in multivariable analyses as well as hazard ratios (HRs) for mortality and survival were obtained. In the years 2000−2020, the age-adjusted incidence rate increased by 9-fold in the stomach and by 7-fold in the breast. The incidence rates were 1.38 per 100,000 persons in the lung and at 1.79 per 100,000 persons in gastroenteropancreatic sites (rectum, stomach, and pancreas). The prevalence increased from 0.0027% in 2000 to 0.0736% in 2019 and 0.0245% in 2020. Overall survival was worse for metastatic NETs (HR, 4.061; 95% CI, 1.932−8.540; p < 0.001) and advanced local NETs (HR, 2.348; 95% CI, 1.007−5.475 p < 0.048) than for localized NETs. In conclusion, the NET incidence increased in the last 20 years and survival decreased over time, especially for metastatic tumors in the pancreas and the nostril.

Association of Dietary Intake of Polyphenols with an Adequate Nutritional Profile in Postpartum Women from Argentina.

HJ-Biplot analysis is a multivariate graphic representation that collects data covariation structure between variables and individuals to represent them in a low-dimensional space with the highest quality in the same reference system. Consequently, it is a promising technique for evaluating dietary exposure to polyphenols and accurately characterizing female nutrition. Herein, we hypothesized that polyphenol intake defines specific clusters with dietary impacts, which can be assessed using HJ-Biplot, based on a cross-sectional study in Argentina. The study included 275 healthy postpartum women who provided information about their food frequency intake and other conditions, which were then used to evaluate polyphenolic intake using the Phenol-Explorer database. Outcomes were established using HJ-Biplot for clustering and ANOVA to compare their impact on diet quality indicators. Two HJ-Biplot models were run (for intakes >20 mg/d and 5∼20 mg/d, respectively) to identify three clusters per model with excellent statistical fitness to explain the data. Thus, specific polyphenolic clusters with potentially bioactive and safe compounds were defined despite significant interindividual variability. In fact, women with the lowest polyphenolic intake exhibited worse dietary quality, body fat, and physical activity. As a result, HJ-Biplot proved to be an effective technique for clustering women based on their dietary intake of these compounds. Furthermore, cluster membership improved the intake of antioxidants, water, fiber, and healthy fats. Additionally, women with formal jobs and a higher educational level showed a better diet. Dietary polyphenols are critical during postpartum because they exert beneficial effects on women and breastfed infants.

Clinical related factors to neuroendocrine tumors in Ecuadorian patients: a logistic biplot approach / Factores clínicos asociados a tumores neuroendocrinos en pacientes ecuatorianos: un análisis biplot logístico

Abstract Neuroendocrine tumors (NETs) are relative rare, affecting neuroendocrine cells throughout the body. Most tumors are diagnosed at advanced stages. NETs prevalence has increased in the last years but there is little data available in developing countries. The aim of this study was to describe symptoms associated with NETs in patients of the Society for the Fight Against Cancer (SOLCA) in Ecuador from 2005 to 2020; using logistic biplots, in a hospital database, generating binary responses (presence/absence) relevant to this study. The results showed that the mean age was 59 and the study showed no difference in prevalence between genders. NETs were mainly found in lungs (19%), followed by stomach (18%) and skin (9%). Most patients had pathological diagnosis G2 and G3 (30% and 70%, respectively). Symptoms as cough, dyspnea, weight loss, diarrhea, constipation, abdominal pain, dyspepsia, hypertensive crisis, distended abdomen and intestinal obstruction had p values <0.05. Additionally, the statistical analysis showed that cough and intestinal obstruction were also common, bearing in mind that patients had most frequent NETs in the lungs and skin. In summary, our results indicate that symptoms of NETs patients were positively associated with lung and skin. Further investigation is needed focusing on the type of NETs and their symptoms in order to establish an early marker for diagnosis.

Resumen Los tumores neuroendocrinos (TNE) son relativamente raros y afectan a las células neuroendocrinas de todo el cuerpo. La mayoría de los tumores se diagnostican en etapas avanzadas. La prevalencia de los TNE ha aumentado en los últimos años, pero hay pocos datos en los países en desarrollo. El objetivo de este estudio fue determinar los síntomas asociados a los TNE en pacientes de la Sociedad de Lucha contra el Cáncer (SOLCA) en Ecuador entre 2005 y 2020, utilizando biplots logísticos en una base de datos hospitalaria, generando respuestas binarias (presencia / ausencia) relevantes para este estudio. Los resultados mostraron que la edad promedio era de 59 años y el estudio no encontró diferencias en la prevalencia entre géneros. Los TNE se encontraron con mayor frecuencia en los pulmones (19%), seguidos del estómago (18%) y piel (9%). La mayoría de los pacientes tenían diagnóstico patológico G2 y G3 (30% y 70% respectivamente). Los síntomas como tos, disnea, pérdida de peso, diarrea, estreñimiento, dolor abdominal, dispepsia, crisis hipertensiva, abdomen distendido y obstrucción intestinal tuvieron valores de p <0,05. Además, el análisis estadístico mostró que la tos y la obstrucción intestinal también eran comunes, teniendo en cuenta que los pacientes tenían TNE más frecuentes en los pulmones y la piel. En resumen, nuestros resultados indican que los síntomas de los pacientes con TNE se asociaron positivamente con los pulmones y la piel. Se necesitan más investigaciones que se centren en el tipo de TNE y sus síntomas a fin de establecer un marcador más temprano para el diagnóstico.

Phenotyping Latin American Open-Pollinated Varieties of Popcorn for Environments with Low Water Availability.

Drought is a common abiotic stress in tropical and subtropical regions that limits the growth and development of agricultural crops, mainly impacting grain yield. Acting through plant breeding is the most viable alternative for obtaining genotypes more tolerant of environments with stress. This work aims to select popcorn genotypes for environments with drought and to identify discriminating traits for the evaluation of drought tolerance in popcorn germplasm. Fifteen Latin American populations of popcorn were evaluated in water stress (WS) and well-watered (WW) conditions. The evaluated traits were based in morpho-agronomic, physiological and radicular descriptors. Data were submitted to individual and joint ANOVA and GT Biplot analysis. Variability was detected between populations for all traits in both conditions. The drought caused a reduction of 30.61% and 3.5% in grain yield and popping expansion, respectively. Based in GT biplot analysis, 880POP was the most stable in WS and WW, being indicated as a promising population for cultivation in environments with water limitation. This study is going to allow the establishment of a collection of great importance to maize germplasm and to provide information to facilitate the process of selection in breeding programs focused on drought tolerance.

Análisis multivariado HJ-Biplot de la ocurrencia de Helicobacter pylori como riesgo para cáncer gástrico, en la ciudadela el Cristo de Consuelo, Milagro Ecuador / HJ-Biplot multivariate analysis of the occurrence of Helicobacter pylori as a risk for gastric cancer, in the citadel of El Cristo de Consuelo, Milagro Ecuador

El Helicobacter pylori, es el causante del mayor número de úlceras y cáncer gástrico a nivel mundial. Población de 15 a 20 años, de escasos recursos y con mayor precariedad en el funcionamiento de los servicios públicos como es el agua potable son altamente vulnerables. Por lo que se planteó como objetivo, realizar un análisis multivariado HJ-Biplot de la ocurrencia de H. pylori como riesgo para cáncer gástrico, en la ciudadela el Cristo de Consuelo, Milagro Ecuador. Estudio epidemiológico transversal, descriptiva y de tipo observacional, contó con una población finita de 230 personas. Técnicas de recolección de datos: la encuesta, la observación directa y la detección de H. pylori en las muestras de heces. El análisis de las muestras biológicas se realizó mediante el método de Elisa en muestras de suero y heces. A los datos obtenidos se les aplicó el método de análisis multivariado bidireccional llamado HJ-Biplot, reflejándose en las variables las relaciones de las composiciones químicas, físicas y biológicas. Los resultados conforman dos grupos de puntos de muestra que coinciden satisfactoriamente con las estaciones de la región. Con este estudio se demuestra que los métodos estadísticos multivariantes son valiosos para interpretar conjuntos de datos complejos, concretamente, para la red de prevalencia de cáncer gástrico causado por el bacilo H. pylori, ha ido en aumento en los últimos años tanto en el Ecuador como en el resto del mundo. Es necesario que se establezcan los mecanismos de control de los agentes causantes de la propagación de este bacilo lo que incidirá en la disminución en la tasa de crecimiento del cáncer gástrico(AU)

Helicobacter pylori is the cause of the highest number of ulcers and gastric cancer worldwide. Population aged 15 to 20 years, with limited resources and with greater precariousness in the operation of public services such as drinking water, are highly vulnerable. Therefore, the objective was to carry out a multivariate HJ-Biplot analysis of the occurrence of H. pylori as a risk for gastric cancer, in the citadel of Cristo de Consuelo, Milagro Ecuador. Cross-sectional, descriptive and observational epidemiological study, had a finite population of 230 people. Data collection techniques: survey, direct observation and detection of H. pylori in stool samples. Analysis of biological samples was performed using the Elisa method in samples of serum and feces. The obtained data were applied the method of bi-directional multivariate analysis called HJ-Biplot, reflecting in the variables the relationships of the chemical, physical and biological compositions. The results form two groups of sample points that successfully coincide with the stations in the region. This study shows that multivariate statistical methods are valuable for interpreting complex data sets, specifically for the prevalence network of gastric cancer caused by the H. pylori bacillus, which has been increasing in recent years both in Ecuador and in the rest of the world. it is necessary to establish the control mechanisms of the agents that cause the spread of this bacillus, which will affect the decrease in the growth rate of gastric cáncer(AU)

Evaluation of drought tolerance indices for barley landraces under irrigated and dry conditions / Avaliação de índices de tolerância seca para terraços de cevada em condições irrigadas e secas

Barley cultivation for drought areas requires a reliable assessment of drought tolerance variability among the breeding germplasms. Hence, 121 barley landraces, advanced breeding lines, and varieties were evaluated under both moisture non-stress and stress field conditions using a lattice square (11×11) design with two replications for each set of the trials. Twelve drought tolerance indices (SSI, TOL, MP, GMP, STI, YI, YSI, HM, SDI, DI, RDI, and SSPI) were used based on grain yield under normal (Yp) and drought (Ys) conditions. Analysis of variance showed a significant genetic variation among genotypes for all indices except for TOL and SSPI indices. Yp had a very strong association with Ys (r = 0.92**) that indicates high yield potential under non-stress can predict better yield under stress conditions. Yp and Ys were positively and significantly correlated with MP, GMP, STI, YI, HM, and DI indices, whereas they were negatively correlated with SSI and SDI. In principal component analysis (PCA), the first PC explained 64% of total variation with Yp, Ys, MP, GMP, STI, YI, HM, and DI. The second PC explained 35.6% of the total variation and had a positive correlation with SSI, TOL, SDI, and SSPI. It can be concluded that MP, GMP, STI, YI, HM and DI indices with the most positive and significant correlation with the yield at both non-stress and stress environments would be better indices to screen barley genotypes, although none of the indices could undoubtedly identify high yield genotypes under both conditions.

O cultivo de cevada para áreas secas exige uma avaliação confiável da variabilidade da tolerância à seca entre os germoplasmas reprodutores. Assim, 121 linhagens crioulas de cevada (linhas de reprodução avançada e variedades) foram avaliadas em campo sob condições sem estresse e com estresse de umidade do solo, utilizando-se para isso um arranjo experimental de malha quadrada (11×11), com duas repetições para cada conjunto de ensaios. Foram utilizados 12 índices de tolerância à seca (SSI, TOL, MP, GMP, STI, YI, YSI, HM, SDI, DI, RDI e SSPI), com base no rendimento de grãos sob condições normais sem estresse (Yp) e com estresse de seca (Ys). A análise de variância mostrou uma variação genética significativa entre os genótipos para todos os índices, com exceção dos índices TOL e SSPI. Yp teve uma associação muito forte com Ys (r = 0,92**), o que indica que o potencial de alto rendimento sob condições sem estresse pode prever melhor rendimento sob condições de estresse. Yp e Ys foram positivamente e significativamente correlacionados com os índices MP, GMP, STI, YI, HM e DI, enquanto, foram correlacionados negativamente com os índices SSI e SDI. Na análise de componentes principais (PCA), o primeiro PC explicou 64% da variação total com Yp, Ys, MP, GMP, STI, YI, HM e DI. O segundo PC explicou 35,6% da variação total e apresentou correlação positiva com SSI, TOL, SDI e SSPI. Pode-se concluir que, os índices MP, GMP, STI, YI, HM e DI com a correlação mais positiva e significativa com a produção nos ambientes sem estresse e com estresse seriam melhores índices para a seleção de genótipos de cevada, embora nenhum dos índices pudesse concretamente identificar genótipos de alto rendimento sob ambas as condições.

Análisis clúster para big data: una aplicación con variables demográficas en provincias del Ecuador / Cluster analysis for big data: an application with demographic variables in provinces of Ecuador

Los métodos de clasificación permiten explorar y analizar grandes conjuntos de datos visualmente, lo cual es de gran utilidad para tomar decisiones rápidas. El objetivo fue comparar dos métodos de análisis de clúster para big data en variables demográficas de las provincias del Ecuador. Se hizo uso de un estudio observacional de tipo comparativo mediante la representación simultanea del HJ-Biplot y el método Two Step (clúster bietápico), a través del software MultBiplot y SPSS. Los datos corresponden a variables demográficas de interés sociosanitarias tasa de mortalidad general, tasa de mortalidad infantil, tasa de natalidad, densidad poblacional, porcentaje urbano y esperanza de vida, medidas en las provincias del Ecuador. Se utilizaron datos provenientes del Instituto de Estadísticas y Censos INEC. Se analizó la asociación entre variables y se identificaron clústeres de las provincias del Ecuador según estas variables demográficas. Según la representación simultánea del HJ-Biplot se identificaron 3 clústeres, el clúster 1 son provincias con mayor densidad poblacional y tasas de mortalidad general, pero valores bajos de tasas de natalidad, el clúster 2 agrupa provincias con mayor esperanza de vida y tasas de mortalidad infantil pero bajos valores de tasa de natalidad y el clúster 3 están las provincias con valores altos de tasas de natalidad y valores bajos de densidad poblacional, esperanza de vida, tasas de mortalidad general y mortalidad infantil, distintos resultados se obtuvieron con el método Two Step. Se pudo concluir que estos métodos son de utilidad para explorar las similitudes entre las provincias según variables demográficas.

The classification methods allow to explore and analyze big data sets visually, which is very useful for making quick decisions. This work aimed to compare of two methods of cluster analysis for big data in demographic variables of the provinces of Ecuador. An observational study of comparative type was carried out through the simultaneous representation of the HJ/Biplot and the Two Step method (two-stage cluster), through the MultBiplot and SPSS software. The data correspond to demographic variables of socio-health interest, general mortality rate, infant mortality rate, birth rate, population density, urban percentage and life expectancy, measured in the provinces of Ecuador. Data from Statistics and Census Institute were used. The association between variables was analyzed and clusters of the provinces of Ecuador were identified according to these demographic variables. According to the simultaneous representation of the HJBiplot, 3 clusters were identified, cluster 1 are provinces with higher population density and general mortality rates, but low birth rates values, cluster 2 are provinces with higher life expectancy and mortality rates infantile but low birth rate values and cluster 3 are the provinces with high birth rates values and low population density, life expectancy, general mortality and infant mortality rates, different results were obtained with the Two Step method. It was concluded that these methods are useful for exploring the similarities between provinces according to demographic variables.

Clustering Disjoint HJ-Biplot: A new tool for identifying pollution patterns in geochemical studies.

This paper introduces a new mathematical algorithm termed Clustering Disjoint HJ-Biplot (CDBiplot), which searches for the underlying data structure in order to find the best classification of the object groups in a reduced space. To this end, disjoint factorial axes are generated, in which each variable only contributes to the formation of one factorial axis. A graphical representation of the individuals and variables is performed using the HJ-Biplot method. In order to facilitate the use of this new method within any practical context, a function in the language R has been developed. This work applies the CDBiplot to study an environmental geochemistry case involving environmental pollution in river surface sediments. The study focuses on an area close to an important mining and metallurgical site, where sediments share a similar geological origin and chemical composition. The algorithm permitted a detailed study of the geochemical interactions and performed an excellent separation of the samples. Thus, the groups obtained were formed according to a similar geological origin, location, and nature of the anthropogenic inputs based only on chemical composition data. These results allowed clear identification of the sources of pollution and the delimitation of the polluted zones. All things considered, we conclude that the proposed algorithm is a powerful tool for studying environmental geochemistry data sets, and suggest that the application of this methodology be extended to other research fields.

Spatiotemporal and variability gait data in community-dwelling elderly women from Brazil

ABSTRACT Background Gait is an extremely complex motor task; therefore, gait data should encompass as many gait parameters as possible. Objective To provide reference values for gait measurements obtained from a Brazilian group of community-dwelling elderly females between the ages of 65 and 89 years and to apply the PCA-biplot to yield insight into different walking strategies that might occur during the aging process. Method 305 elderly community-dwelling females living in Brazil were stratified into four age groups: 65-69 years (N=103); 70-74 years (N=95); 75-79 years (N=77); and ≥80 years (N=30). Age, height, and BMI were assessed to describe the characteristics of the groups. Gait spatiotemporal and variability data were obtained using the GAITRite® system. Principal component analysis, followed by MANOVA and the PCA-biplot approach were used to analyze the data. Results 95% CI showed that only three components – rhythm, variability, and support - together explained 74.2% of the total variance in gait that were different among the groups. The older groups (75-79 and ≥80 years) walked with lower than average velocity, cadence, and step length and were above average for the variables stance, step, swing, and double support time and the ≥80 year old group presented the highest gait variability compared to the other groups. Conclusion Aging is associated with decreased gait velocity and cadence and increased stance, step time, and variability, but not associated with changes in base of support. In addition, the PCA-biplot indicates a decline towards decreased rhythm and increased variability with aging.

Spatiotemporal gait parameters and recurrent falls in community-dwelling elderly women: a prospective study

BACKGROUND: Falling is a common but devastating and costly problem of aging. There is no consensus in the literature on whether the spatial and temporal gait parameters could identify elderly people at risk of recurrent falls. OBJECTIVE: To determine whether spatiotemporal gait parameters could predict recurrent falls in elderly women. METHOD: One hundred and forty-eight elderly women (65-85 years) participated in this study. Seven spatiotemporal gait parameters were collected with the GAITRite(r) system. Falls were recorded prospectively during 12 months through biweekly phone contacts. Elderly women who reported two or more falls throughout the follow-up period were considered as recurrent fallers. Principal component analysis (PCA) and discriminant analysis followed by biplot graph interpretation were applied to the gait parameters. RESULTS: After 12 months, 23 elderly women fell twice or more and comprised the recurrent fallers group and 110 with one or no falls comprised the non-recurrent fallers group. PCA resulted in three components that explained 88.3% of data variance. Discriminant analysis showed that none of the components could significantly discriminate the groups. However, visual inspection of the biplot showed a trend towards group separation in relation to gait velocity and stance time. PC1 represented gait rhythm and showed that recurrent fallers tend to walk with lower velocity and cadence and increased stance time in relation to non-recurrent fallers. CONCLUSIONS: The analyzed spatiotemporal gait parameters failed to predict recurrent falls in this sample. The PCA-biplot technique highlighted important trends or red flags that should be considered when evaluating recurrent falls in elderly females. .

Análises Biplot: conceitos, interpretações e aplicações / Biplot analysis: concepts, interpretations and uses

A seleção e recomendação de genótipos superiores são dificultadas devido à ocorrência da interação genótipo e ambiente. Nesse contexto, as análises biplot têm sido cada vez mais utilizadas na análise de dados agronômicos, com interações de natureza complexa. Entretanto, as particularidades existentes no gráfico biplot dificultam sua interpretação, podendo induzir o pesquisador a erros. Assim, este artigo de revisão discute a aplicabilidade e a interpretação gráfica dos modelos AMMI (Additive Main effects and Multiplicative Interaction) e GGE biplot (genotype main effects + genotype environment interaction) destas análises no gráfico biplot. Também, visa a desmistificar a necessidade de comparação entre ambas as metodologias. Discute-se quanto à escolha da metodologia mais adequada, levando em consideração a informação requerida e os objetivos do pesquisador.

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 biplot (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.

Análises Biplot: conceitos, interpretações e aplicações

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 biplot (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.

A seleção e recomendação de genótipos superiores são dificultadas devido à ocorrência da interação genótipo e ambiente. Nesse contexto, as análises biplot têm sido cada vez mais utilizadas na análise de dados agronômicos, com interações de natureza complexa. Entretanto, as particularidades existentes no gráfico biplot dificultam sua interpretação, podendo induzir o pesquisador a erros. Assim, este artigo de revisão discute a aplicabilidade e a interpretação gráfica dos modelos AMMI (Additive Main effects and Multiplicative Interaction) e GGE biplot (genotype main effects + genotype environment interaction) destas análises no gráfico biplot. Também, visa a desmistificar a necessidade de comparação entre ambas as metodologias. Discute-se quanto à escolha da metodologia mais adequada, levando em consideração a informação requerida e os objetivos do pesquisador.

Análises Biplot: conceitos, interpretações e aplicações

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 biplot (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.

A seleção e recomendação de genótipos superiores são dificultadas devido à ocorrência da interação genótipo e ambiente. Nesse contexto, as análises biplot têm sido cada vez mais utilizadas na análise de dados agronômicos, com interações de natureza complexa. Entretanto, as particularidades existentes no gráfico biplot dificultam sua interpretação, podendo induzir o pesquisador a erros. Assim, este artigo de revisão discute a aplicabilidade e a interpretação gráfica dos modelos AMMI (Additive Main effects and Multiplicative Interaction) e GGE biplot (genotype main effects + genotype environment interaction) destas análises no gráfico biplot. Também, visa a desmistificar a necessidade de comparação entre ambas as metodologias. Discute-se quanto à escolha da metodologia mais adequada, levando em consideração a informação requerida e os objetivos do pesquisador.

Morphogenetic responses of embryo culture of wheat related to environment culture conditions of the explant donor plant

Availability of immature embryos as explants to establish wheat (Triticum aestivum L.) by tissue culture can be limited by climatic factors and the lack of high quality embryos frequently hampers experimentation. This study evaluates the effects of rainfall, various temperature-based variables and sunshine duration on tissue culture response (TCR) traits including callus formation (CF), regenerating calli (RC), and number of plants per embryo (PPE) for 96 wheat genotypes of worldwide origin. The objectives of this study were to evaluate the significance of a particular climatic factor on TCR traits and to determine the period of wheat growth during which these factors were the most effective. The genotypes were grown in an experimental field during three seasons differing in meteorological conditions. The relationships between TCR traits and climatic factors within three time periods of wheat growth: 2, 6 and 10 weeks prior to embryo sampling were analysed by biplot analysis. The tissue culture traits were influenced at very different degrees by climatic factors: from 16.8% (RC) to 69.8% (CF). Donor plant environment with high temperatures and low rainfalls reduced (p 0.05) the tissue culture performance of wheat genotypes. Callus formation was most sensitive to the temperature based factors. The environmental conditions between flowering and the medium milk stage were the most important for CF, while RC and PPE were not particularly related to any period.

A disponibilidade de embriões imaturos para estabelecer plantas de trigo (Triticum aestivum L.) por cultura de tecido pode ser limitada por fatores climáticos, e a falta de embriões de alta qualidade frequentemente dificulta a experimentação. Avaliou-se o efeito da chuva, de variáveis baseadas em temperatura e duração do brilho solar na resposta da cultura de tecido (RCT), incluindo a formação de calos (FC), regeneração dos calos (RC) e número de plantas por embrião (NPPE), para 96 genótipos de trigo. Os objetivos foram a procura de algum fator climatico específico em alguma característica da RCT e a determinação do período do desenvolvimento do trigo no qual estes fatores são mais eficazes. Os genótipos foram obtidos num campo experimental durante três estações climáticas. As relações entre as características da RTC e os fatores de clima dentro de três períodos de desenvolvimento do trigo (2, 6 e 10 semanas) antes da amostragem dos embriões foram analisadas pela técnica "biplot". As características das culturas de tecido foram influenciadas em diferentes graus pelos fatores climáticos: de 16.8% (RC) para 69.8% (FC). Ambientes da planta doadora com alta temperatura e pouca chuva reduziram (p 0.05) o desempenho dos genótipos de trigo. A FC foi mais sensível aos fatores baseados em temperatura. As condições ambientais entre o florescimento e o estágio médio de leite dos frutos foram os mais importantes para FC, enquanto RC e NPPE não estavam relacionados a qualquer período.

Morphogenetic responses of embryo culture of wheat related to environment culture conditions of the explant donor plant

Availability of immature embryos as explants to establish wheat (Triticum aestivum L.) by tissue culture can be limited by climatic factors and the lack of high quality embryos frequently hampers experimentation. This study evaluates the effects of rainfall, various temperature-based variables and sunshine duration on tissue culture response (TCR) traits including callus formation (CF), regenerating calli (RC), and number of plants per embryo (PPE) for 96 wheat genotypes of worldwide origin. The objectives of this study were to evaluate the significance of a particular climatic factor on TCR traits and to determine the period of wheat growth during which these factors were the most effective. The genotypes were grown in an experimental field during three seasons differing in meteorological conditions. The relationships between TCR traits and climatic factors within three time periods of wheat growth: 2, 6 and 10 weeks prior to embryo sampling were analysed by biplot analysis. The tissue culture traits were influenced at very different degrees by climatic factors: from 16.8% (RC) to 69.8% (CF). Donor plant environment with high temperatures and low rainfalls reduced (p 0.05) the tissue culture performance of wheat genotypes. Callus formation was most sensitive to the temperature based factors. The environmental conditions between flowering and the medium milk stage were the most important for CF, while RC and PPE were not particularly related to any period.

A disponibilidade de embriões imaturos para estabelecer plantas de trigo (Triticum aestivum L.) por cultura de tecido pode ser limitada por fatores climáticos, e a falta de embriões de alta qualidade frequentemente dificulta a experimentação. Avaliou-se o efeito da chuva, de variáveis baseadas em temperatura e duração do brilho solar na resposta da cultura de tecido (RCT), incluindo a formação de calos (FC), regeneração dos calos (RC) e número de plantas por embrião (NPPE), para 96 genótipos de trigo. Os objetivos foram a procura de algum fator climatico específico em alguma característica da RCT e a determinação do período do desenvolvimento do trigo no qual estes fatores são mais eficazes. Os genótipos foram obtidos num campo experimental durante três estações climáticas. As relações entre as características da RTC e os fatores de clima dentro de três períodos de desenvolvimento do trigo (2, 6 e 10 semanas) antes da amostragem dos embriões foram analisadas pela técnica "biplot". As características das culturas de tecido foram influenciadas em diferentes graus pelos fatores climáticos: de 16.8% (RC) para 69.8% (FC). Ambientes da planta doadora com alta temperatura e pouca chuva reduziram (p 0.05) o desempenho dos genótipos de trigo. A FC foi mais sensível aos fatores baseados em temperatura. As condições ambientais entre o florescimento e o estágio médio de leite dos frutos foram os mais importantes para FC, enquanto RC e NPPE não estavam relacionados a qualquer período.

Testes multiambientais na seleção de genótipos de arroz utilizando o modelo de regressão nos sítios ou locais / Multi-environment tests in the selection of rice genotypes using sites regression model

A análise da interação genótipo x ambiente utilizda no melhoramento de plantas tem sofrido mudanças na última década, melhorando a sua eficiência quanto à seleção dos genótipos sob diferentes condições ambientais. O objetivo deste trabalho foi analisar a produtividade e estabilidade de 12 genótipos de arroz em oito ambientes, durante os anos 2005 e 2006, na Colômbia. O delineamento utilizado foi o de blocos ao acaso com quatro repetições. Os parâmetros de estabilidade fenotípica e o agrupamento dos ambientes foram estimados pelo estudo da interação genótipo x ambiente, segundo o método SREG (Regressão nos sítios ou locais) e seu gráfico biplot (GGE). As análises estatísticas indicaram diferenças significativas (com 5 por cento de probabilidade de erro) entre genótipos e entre ambientes e significância (com 5 por cento de probabilidade de erro) da interação genótipo x ambiente, sugerindo uma resposta diferente dos genótipos nos vários ambientes. No método SREG, os dois primeiros componentes principais da interação explicaram 75,29 por cento da interação. Os genótipos 400094, 350361 e a variedade Fedearroz 50 foram considerados os de maior produtividade. Segundo o gráfico biplot GGE, os ambientes La Libertad e Escobal foram os mais favoráveis para o cultivo do arroz.(AU)

The analysis of genotype x environment interaction in plant breeding have been enlarged with new methodologies in the last decade, improving its efficiency on the selection of genotypes under different environmental conditions. The objective of this research was to analyze the yield and stability of twelve genotypes of rice, in eight environments, during the years 2005 and 2006 in Colombia. Completely randomized block designs with four replications were used. The phenotypic stability parameters and grouping of environments were estimated by the genotype-environment interaction study according to SREG (Sites Regression) method and its biplot graphic (GGE). The statistical analysis indicated significant differences (with 5 percent probability error) among genotypes and among environments. Also, it pointed out the significance (with 5 percent probability error) of the genotype-environment interaction, indicating different responses of genotypes confronted with different environments. In SREG method, the two first principal components of interactions explained 75.29 percent of the interaction. The genotypes 400094, 350361 and the variety Fedearroz were found as the highest yields. According to the biplot GGE graphic the environments La Libertad and Escobal were the ones with small variations during the years of study.(AU)

Testes multiambientais na seleção de genótipos de arroz utilizando o modelo de regressão nos sítios ou locais / Multi-environment tests in the selection of rice genotypes using sites regression model

A análise da interação genótipo x ambiente utilizda no melhoramento de plantas tem sofrido mudanças na última década, melhorando a sua eficiência quanto à seleção dos genótipos sob diferentes condições ambientais. O objetivo deste trabalho foi analisar a produtividade e estabilidade de 12 genótipos de arroz em oito ambientes, durante os anos 2005 e 2006, na Colômbia. O delineamento utilizado foi o de blocos ao acaso com quatro repetições. Os parâmetros de estabilidade fenotípica e o agrupamento dos ambientes foram estimados pelo estudo da interação genótipo x ambiente, segundo o método SREG (Regressão nos sítios ou locais) e seu gráfico biplot (GGE). As análises estatísticas indicaram diferenças significativas (com 5 por cento de probabilidade de erro) entre genótipos e entre ambientes e significância (com 5 por cento de probabilidade de erro) da interação genótipo x ambiente, sugerindo uma resposta diferente dos genótipos nos vários ambientes. No método SREG, os dois primeiros componentes principais da interação explicaram 75,29 por cento da interação. Os genótipos 400094, 350361 e a variedade Fedearroz 50 foram considerados os de maior produtividade. Segundo o gráfico biplot GGE, os ambientes La Libertad e Escobal foram os mais favoráveis para o cultivo do arroz.

The analysis of genotype x environment interaction in plant breeding have been enlarged with new methodologies in the last decade, improving its efficiency on the selection of genotypes under different environmental conditions. The objective of this research was to analyze the yield and stability of twelve genotypes of rice, in eight environments, during the years 2005 and 2006 in Colombia. Completely randomized block designs with four replications were used. The phenotypic stability parameters and grouping of environments were estimated by the genotype-environment interaction study according to SREG (Sites Regression) method and its biplot graphic (GGE). The statistical analysis indicated significant differences (with 5 percent probability error) among genotypes and among environments. Also, it pointed out the significance (with 5 percent probability error) of the genotype-environment interaction, indicating different responses of genotypes confronted with different environments. In SREG method, the two first principal components of interactions explained 75.29 percent of the interaction. The genotypes 400094, 350361 and the variety Fedearroz were found as the highest yields. According to the biplot GGE graphic the environments La Libertad and Escobal were the ones with small variations during the years of study.