Biplot

Principal component regression (PCR) based on principal component analysis (PCA) and partial least squares regression (PLSR) are well known projection methods for analysis of multivariate data. They result in scores and loadings that may be visualized in a scoreloading plot (biplot) and used for process monitoring. The difficulty with this is that often more than two principal or PLS components have to be used, resulting in a need to monitor more than one such plot. However, it has recently been shown that for a scalar response variable all PLSR/PCR models can be compressed into equivalent PLSR models with two components only. After a summary of the underlying theory, the present paper shows how such two-component PLS (2PLS) models can be utilized in informative score-loading biplots for process understanding and monitoring. The possible utilization of known projection model monitoring statistics and variable contribution plots is also discussed, and a new method for

India's success in economic reforms spurred high growth rates, nevertheless; poverty, malnutrition and nutritional security remain serious and persisting concern. The present study examined the dynamics in intake of calorie, protein and fat over years and across provinces and also inequality, determinants and regional prioritization of nutrients consumption. The data extracted from various consumption survey reports of the National Sample Survey Office since 1972-73 to 2011-12 indicated that calorie intake in a majority of the states has witnessed significant changes and reduction over time. While, the intake of protein remained consistent, per capita fat intake increased with rural Punjab and rural Odisha being the highest and lowest consumers, respectively. The per capita fat consumption is higher in urban vis-a-vis rural. Variation (CV) and inequality (Gini coefficient) in calorie, protein and fat intake showed a declining trend across rural and urban. Regional prioritization (biplot) indicated a strong linkage between rural and urban for nutrient consumption. Regression analysis using panel data indicated that the nutrient intake in rural India is influenced positively by per capita expenditure on food items, household size and literacy rate, and negatively by poverty rate. The nutrients consumption level is low in a majority of states by any norms which gets reflected in the nutritional outcomes. Reduction in inequality and variation accompanied by an increase in intake can be achieved by increased spending on nutri-rich food items and per capita consumption of cereals and pulses.

Fifty wheat genotypes were evaluated at nine diverse locations in India to identify high-yielding and stable genotypes. The analysis of variance based on additive main effects and multiplicative interaction (AMMI) indicated significant genotype, environment and genotype-environment (GE) interactions, with a total variation of 5.99, 20.23 and 73.77%, respectively. A biplot-AMMI analysis and yield stability index incorporating the AMMI stability value and yield in a single non-parametric index were used to discriminate the genotypes with highest and stable yield; the genotypes G135, G125, G104, G112 and G144 were found to be promising. Two mega environments (ME) were identified based on GGE (genotype and GE interaction) biplot analysis and the genotypes G119 and G120 and G107, G148 and G146 performed best in the mega-environments ME I and ME II, respectively. Both approaches allowed the identification of stable genotypes (G112 and G135), which can be included in the national testing program, with a view to release a new variety.

sezonunda yürütülen bu araştırmada, üstün makarnalık buğday hatlarının tespit edilmesi ve ıslah programlarında kullanılması amacıyla verim ve bazı kalite özellikleri incelenmiştir. Çalışmada materyal olarak 80 makarnalık buğday hattı ile beş adet tescilli çeşit (Artuklu, Eyyubi, Güneyyıldızı, Şahinbey, Zühre) kullanılmıştır. Araştırma, Augmented deneme desenine göre her birinde 25 parsel bulunan dört blokta yürütülmüştür. Tane verimi ile birlikte, hektolitre ağırlığı, bin tane ağırlığı, protein oranı, irmik rengi ve SDS sedimantasyon testi incelenmiştir. Özellikler arası ve genotip-özellik ilişkilerini değerlendirmek amacıyla Biplot analiz yöntemi uygulanmıştır. Analiz neticesinde birbiriyle ilişkili olan özellikler ile belirli özellikler yönünden öne çıkan genotipler görsel olarak gösterilmiştir. Oluşturulan Biplot grafiğinde hatların çoğu kalite özellikleri yönünde yer alarak protein oranı, SDS sedimantasyon ve irmik rengi yönünden üstünlük göstermişlerdir. Araştırma sonucunda, farklı özellikler bakımından üstünlük gösteren 40 adet hat verim denemelerine alınmak üzere seçilmiş, ayrıca üstün kalite özelliğine sahip olan hatlar da melez bahçesine alınmıştır.

Latent class models (LCMs) can be used to assess diagnostic test performance when no reference test (a gold standard) is available, considering two latent classes representing disease or non-disease status. One of the basic assumptions in such models is that of local or conditional independence: all indicator variables (tests) are statistically independent within each latent class. However, in practice this assumption is often violated; hence, the two-LCM fits the data poorly. In this paper, we propose the use of Biplot methods to identify the conditional dependence between pairs of manifest variables within each latent class. Additionally, we propose incorporating such dependence in the corresponding latent class using the log-linear formulation of the model. The LCM is also used to evaluate the reasons for agreement/disagreement between clinical diagnoses or opinions provided by different raters/observers . The model, constructed under the assumption of conditional independence, assumes that within each latent class the evaluation provided by each of the specialists is statistically independent from the evaluations provided by the others.

Perceptual maps are often used in marketing to visually study relations between two or more attributes. However, in many perceptual maps published in the recent literature it remains unclear what is being shown and how the relations between the points in the map can be interpreted or even what a point represents. The term perceptual map refers to plots obtained by a series of different techniques, such as principal component analysis, (multiple) correspondence analysis, and multidimensional scaling, each needing specific requirements for producing the map and interpreting it. Some of the major flaws of published perceptual maps are omission of reference to the techniques that produced the map, non-unit shape parameters for the map, and unclear labelling of the points. The aim of this paper is to provide clear guidelines for producing these maps so that they are indeed useful and simple aids for the reader. To facilitate this, we suggest a small set of simple icons that indicate the rules for correctly interpreting the map.

In this paper, we focus on a Multidimensional Data Analysis approach to the Lee-Carter (LC) model of mortality trends. In particular, we extend the bilinear LC model and specify a new model based on a three-way structure, which incorporates a further component in the decomposition of the log-mortality rates. A multi-way component analysis is performed using the Tucker 3 model. The suggested methodology allows us to obtain combined estimates for the three modes: i) time, ii) agegroups and iii) different populations. From the results obtained by the Tucker 3 decomposition, we can jointly compare, in both a numerical and graphical way, the relationships among all three modes and obtain a time series component as a leading indicator of the mortality trend for a group of populations. Further, we carry out a correlation analysis of the estimated trends in order to assess the reliability of the results of the three-way decomposition. The model's goodness of fit is assessed using an analysis of the residuals. Finally, we discuss how the synthesised mortality index can be used to build concise projected life tables for a group of populations. An application which compares ten European countries is used to illustrate the approach and provide a deeper insight into the model and its implementation.

Lentil (Lens culinaris Medik. culinaris) is a cool season food legume contains the high quality of proteins and minerals. Selecting genotypes for high mean yield and yield stability has been a challenge for lentil breeders. The complexities of genotype × environment interaction (GEI) make selection difficult to identify the best performing and most stable genotypes. Therefore, this study was carried out to apply a GGE biplot and AMMI analysis model to evaluate the magnitude of the effect of GE interaction on grain yield of 25 lentil accessions at three environments during the year of 2016 and 2017 seasons in alpha-lattice design (5x5) with three locations and to evaluate relationships between test environments for identification of favorable genotypes for lentil production areas. Combined pooled mean analysis of variance for grain yield tested at three environments over the two subsequent years 2016 and 2017 showed that highly significant differences in genotypes, environment and G x E interaction effect indicating the possibility of selection for stable accessions. The stability of the assessed genotypes using some stability statistics derived from three types of statistical concepts (variance and regression analyses), AMMI (additive main effect and multiplicative interaction) analysis and GGE biplot (genotype main effects and genotype-by-environment interaction effects) models were applied to obtain good understanding of the interrelationship and overlapping among the used stability statistics. Research results showed that lentil accession WBL-77 (1451 kg ha-1) , RL-79(1446 kg ha-1) and PL-4(1429 kg ha-1) were the best performer and well adopted across the environments and over the years. AMMI analysis of variance for lentil grain yield (tha-1) of lentil accessions tested at three environments over the years showed that 80.71% of the total sum of squares was attributed to environmental effects, only 8.38 % to genotypic effects and 10.90% to genotype × environment interaction effects. The partitioning of GGE sum of squares through the GGE biplot analysis showed that PC1and PC2 accounted 74.75%, and 25.24% of GGE sum of squares respectively over the years. Accessions ILL8006, RL-6, Shital, ILL3490 and simal were more close to the center point and indicated that stable across the environments. In another words, the genotypes which have low stability value (ASV) is said to be stable and the breeder chose the stable genotypes along with grain yield above the mean grand yield. In this experiment accessions RL-6(G-2) ranked 1st stability (ASV-0.53) followed by Simal (ASV-2.05), ILL-3490 (ASV-2.42) and Shital (ASV-2.72) and suitable for all environment.

Among the different environmental stresses, drought is the constraint that induces a highly negative effect on crop production. In order to identify drought tolerant genotypes in safflower, an experiment was conducted in a randomized complete block design with three replications under rainfed and irrigated conditions during 2011-2012 cropping season at Agricultural and Natural Resources Research Center of West Azerbaijan, Iran. Seven drought resistance indices including Stress Tolerance Index (STI), Tolerance Index (TOL), Stress Susceptibility index (SSI), Mean Productivity (MP), Geometric Mean Productivity (GMP), Yield Index (YI) and Yield Stability Index (YSI) were calculated for each genotype based on grain yield under stress and normal conditions. Analysis of variance showed significant difference among genotypes in the terms of grain yield under rainfed and irrigated conditions. Result of correlation analysis between grain yield in both conditions and calculated drought resistance indices revealed that STI, MP, GMP and YI were the best indices for identifying high yielding genotypes in both conditions (drought tolerant genotypes). Gabriel Biplot Multivariate chart showed that 'Syrian', 'PI-537530' and 'PI-537636-S' genotypes relatively identified as drought tolerant and 'Hartman', 'Gila', 'PI-537636', 'PI-537598', 'LRV-51-51' and 'Yenice' genotypes identified as susceptible genotypes. Cluster analysis based on grain yield and drought tolerance indices classified the genotypes into four clusters, therefore this result was consistence with results of biplot analysis.

The purpose of this study was to find out whether a set of habitat characteristics, derived from the National Corine Land Cover (CLC) database of habitat types, could indicate the occurrence of white stork nests in a settlement. The analyses were performed for the settlements closer than 35 km from the Drava River (northern Croatia). Sixteen habitat characteristics were determined around 257 settlements occupied with white stork nests and 152 control sites without white stork nests within the same geographic region. We performed multivariate inspection of the data and a non-metric multidimensional preference analysis. The best variables for stork habitat selection were: distance to the nearest grassland habitat (P < 0.0001), distance to three nearest grassland habitats (P < 0.0001), altitude of the settlements above the sea level (P < 0.001), sum of distances to the three nearest agricultural mosaic habitats (P < 0.005) and standardized area proportion of forests (P < 0.05). The explanatory capacity of the model was 81.1%. We conclude that it is possible to define a small number of habitat characteristics derived from CLC database which can indicate the occurrence of white stork nests.

Este artículo presenta el análisis de sentimiento de la discusión de partidos políticos en Twitter, en el contexto de la Moción de Censura al gobierno español de 2018. En particular, extrajimos y analizamos 2824 tweets de las cuentas oficiales de las 13 formaciones políticas representadas en el Congreso de los Diputados. En su desarrollo metodológico aplicamos el análisis composicional de datos y su visualización a través del biplot (una herramienta de visualización que permite contrastar la importancia relativa de los elementos en estudio). A diferencia de los enfoques tradicionales, nuestro estudio enfatiza la importancia relativa de los temas dentro de la agenda, a la vez que incorpora un tercer componente, el análisis de sentimiento. La investigación concluye sobre la fiabilidad del método para representar composicionalmente la agenda y los agenda-setters, así como el análisis de sentimiento, constatando que los temas que se asocian de forma más notable con determinados partidos, también lo hacen con su proyección sobre los sentimientos. El análisis arroja luz sobre la representación de los sentimientos en los agenda-setters (agenda de atributos), especialmente en el campo de la comunicación política.

Correspondence analysis has found extensive use in ecology, archeology, linguistics and the social sciences as a method for visualizing the patterns of association in a table of frequencies or nonnegative ratio-scale data. Inherent to the method is the expression of the data in each row or each column relative to their respective totals, and it is these sets of relative values (called profiles) that are visualized. This 'relativization' of the data makes perfect sense when the margins of the table represent samples from sub-populations of inherently different sizes. But in some ecological applications sampling is performed on equal areas or equal volumes so that the absolute levels of the observed occurrences may be of relevance, in which case relativization may not be required. In this paper we define the correspondence analysis of the raw 'unrelativized' data and discuss its properties, comparing this new method to regular correspondence analysis and to a related variant of non-symmetric correspondence analysis.

A biplot is a graphical representation of multivariate data, where the elements of a data matrix are represented according to dots and vectors associated with the rows and columns of the matrix. Biplot is based on the same principle as other factorial techniques used for dimensionality reduction, the only difference is it represent variables also along with the data and give dual dimensional representation between principal components and the main coordinates. Geometric concepts are used to interpret the biplot, which facilitate the understandings. PCA based biplot explation given in this paper.

ISBN: 978-93-5300-510-8
DOI: 10.13140/RG.2.2.28187.57125

Principal component analysis (PCA) has been successfully applied to gait data; however, interpretation of the components is challenging. An alternative is to use a graphical display called biplot that gives insights into relationships and trends of data sets. Our goal was to demonstrate the sensitivity of gait variables to aging in elderly women with PCA-biplot. One hundred fifty-one elderly females (71.6±5.0 yrs), 152 adults (44.7±5.4 yrs) and 150 young (21.7±4.1 yrs) participated in the study. Gait spatial and temporal parameters were collected using a computerized carpet. PCA-biplot, discriminant analysis and MANOVA were used in the analysis. PCA-biplot revealed that elderly females walked with lower velocity, shorter step length, reduced swing time, higher cadence, and increased double support time compared to the other two groups. The greatest distances between the groups were along the variable step length with the elderly group showing a decrease of 8.4 cm in relation to the younger group. The discriminant function confirmed the importance of principal component 2 for group separation. Because principal component 2 was heavily weighted by step length and swing time, it represents a measure of stability. As women age they seek a more stable gait by decreasing step length, swing time, and velocity. PCA-biplot highlighted the importance of the variable step length in distinguishing between women of different age groups. It is well-known that as we age we seek a more stable gait. The PCA-biplot emphasized that premise and gave further important insights into relationships and trends of this complex data set.

Resumo -O objetivo deste trabalho foi avaliar a influência da interação de genótipos com ambientes (GxA) na produtividade de grãos de um conjunto de linhagens de soja (Glycine max L.). Foram utilizados dados de 11 experimentos (ambientes) realizados no Estado de Goiás. Em cada experimento foram avaliados 18 genótipos, sendo quatro cultivares comerciais como testemunhas. O método de análise da interação foi o procedimento AMMI (modelo de efeitos principais aditivos e interação multiplicativa). O padrão significativo das interações GxA foi captado apenas pelo primeiro eixo principal AMMI, o qual explicou 36% da soma de quadrados GxA original, sugerindo contaminação da matriz de interações clássica por ruídos que prejudicam a qualidade das predições de respostas fenotípicas obtidas pelos métodos tradicionais. Quanto à estabilidade de comportamento, a maioria das linhagens experimentais destacou-se (com menores interações com ambientes) em relação às cultivares testemunhas. Estas, no entanto, foram relativamente mais produtivas, sobretudo a cultivar Conquista. Entre as novas linhagens, os genótipos L-16, L-13 e L-14 mostraram ser os mais promissores para fins de recomendação como cultivares.

This paper establishes a general framework for metric scaling of any distance measure between individuals based on a rectangular individuals-by-variables data matrix. The method allows visualization of both individuals and variables as well as preserving all the good properties of principal axis methods such as principal components and correspondence analysis, based on the singular-value decomposition, including the decomposition of variance into components along principal axes which provide the numerical diagnostics known as contributions. The idea is inspired from the chi-square distance in correspondence analysis which weights each coordinate by an amount calculated from the margins of the data table. In weighted metric multidimensional scaling (WMDS) we allow these weights to be unknown parameters which are estimated from the data to maximize the fit to the original distances. Once this extra weight-estimation step is accomplished, the procedure follows the classical path in decomposing a matrix and displaying its rows and columns in biplots.

Non-symmetric Correspondence analysis is a method increasingly used in place of classical correspondence analysis to portray the asymmetric association of two categorical variables. In this paper we investigate the reliability of graphical displays illustrating variable prediction, by looking at inferential aspects of the sampling variation of the configuration of points, using a bootstrap approach.

This study aimed to investigate the influence of different sites of cacao (Theobroma cacao L.) cultivartion, represented by different soils and cropping systems, on biometrics attributes of pods and beans. The 12 study sites are in the cacao region of Bahia, Brazil, in the humid zone. The variation and the statistical differences between the means of these attributes clearly indicate the influence of genotype and environment interaction. Attributes pod wet biomass, beans with mucilage wet biomass and number of beans were positively correlated with the cultivation sites represented by Argisol Red-Yellow Eutrophic cambisolic and Argisol Red-Yellow Dystrophic Cohesive abrupt soils. The highest values of length and dry weight of dry cacao beans correspond to Argisol Red-Yellow Eutrophic cambisolic. The dystrophic soils are related to lower dry weight values of cacao beans. The selection of cacao cropping sites by biometric attributes also highlighted the Argisol Red-Yellow Eutrophic cambisolic and Argisol Red-Yellow Dystrophic Cohesive abrupt soils. Understanding the variability of cacao biometric attributes emphasizes the importance of using technologies for achieving sustainable production of cacao with quality.

This study aimed to investigate the influence of different sites of cacao (Theobroma cacao L.) cultivartion, represented by different soils and cropping systems, on biometrics attributes of pods and beans. The 12 study sites are in the cacao region of Bahia, Brazil, in the humid zone. The variation and the statistical differences between the means of these attributes clearly indicate the influence of genotype and environment interaction. Attributes pod wet biomass, beans with mucilage wet biomass and number of beans were positively correlated with the cultivation sites represented by Argisol Red-Yellow Eutrophic cambisolic and Argisol Red-Yellow Dystrophic Cohesive abrupt soils. The highest values of length and dry weight of dry cacao beans correspond to Argisol Red-Yellow Eutrophic cambisolic. The dystrophic soils are related to lower dry weight values of cacao beans. The selection of cacao cropping sites by biometric attributes also highlighted the Argisol Red-Yellow Eutrophic cambisolic and Argisol Red-Yellow Dystrophic Cohesive abrupt soils. Understanding the variability of cacao biometric attributes emphasizes the importance of using technologies for achieving sustainable production of cacao with quality.

Bean grain size, along with grain color and shape, is a constituent of bean?s market quality. In order to be able to satisfy the broad market demand, cultivars with grain of all classes (from the smallest to largest) and top agronomic qualities must be developed. This paper analyzed 24 bean genotypes. They had different grain size in terms of their specific responses to growing conditions over three growing seasons. The two-way ANOVA was used to separate the main effects responsible for the formation of grain of a particular size. The genotype effects were 89.9%, the year effects 2.2%, and those of genotype x year interaction 7.9%. A large portion of interaction variability was attributable to two (AMMI) or tree (SREG) highly significant (by the Gollob F-test) principal components. Most of the genotypes exhibited high stability. The various types of interactions between individual genotypes and growing conditions in a given year are shown in two types of biplot graphs (GE and GGE).t...

Correspondence analysis, when used to visualize relationships in a table of counts (for example, abundance data in ecology), has been frequently criticized as being too sensitive to objects (for example, species) that occur with very low frequency or in very few samples. In this statistical report we show that this criticism is generally unfounded. We demonstrate this in several data sets by calculating the actual contributions of rare objects to the results of correspondence analysis and canonical correspondence analysis, both to the determination of the principal axes and to the chi-square distance. It is a fact that rare objects are often positioned as outliers in correspondence analysis maps, which gives the impression that they are highly influential, but their low weight offsets their distant positions and reduces their effect on the results. An alternative scaling of the correspondence analysis solution, the contribution biplot, is proposed as a way of mapping the results in order to avoid the problem of outlying and low contributing rare objects.

Drought is a wide-spread problem seriously influencing canola (Brassica napus L.) production and quality, but development of tolerance cultivars is hampered by the lack of effective selection criteria. The objective of this study was to evaluate the ability of several selection indices to identify drought tolerance cultivars under two environments (normal and drought stress), at dezful, Province in the agricultural year in 2013–2014. A randomized complete block design with four replications was used. Results of the variance analysis showed that differences among the genotypes, in terms of all indices and yield in normal and drought stress conditions were significant. Results of correlation between defferente drought tolerance indices with grain yield in both conditions(normal and water stress) showed that MP, GMP and STI were a successful index to select high yield and tolerante genotypes. Based on this indices and the results of the biplot diagram the genotypes Hyola401, Sarigol, RGS003 and Hyola308 had the best drought tolerance. and the genotypes Kimberley, Hysun110 and pF were high sensitivity to drought and can be identified as the most sensitive lines to drought. Get more articles at: http://www.innspub.net/volume-6-number-5-march-2015-ijb/

India&#39;s success in economic reforms spurred high growth rates, nevertheless; poverty, malnutrition and nutritional security remain serious and persisting concern. The present study examined the dynamics in intake of calorie, protein and fat over years and across provinces and also inequality, determinants and regional prioritization of nutrients consumption. The data extracted from various consumption survey reports of the National Sample Survey Office since 1972-73 to 2011-12 indicated that calorie intake in a majority of the states has witnessed significant changes and reduction over time. While, the intake of protein remained consistent, per capita fat intake increased with rural Punjab and rural Odisha being the highest and lowest consumers, respectively. The per capita fat consumption is higher in urban vis-a-vis rural. Variation (CV) and inequality (Gini coefficient) in calorie, protein and fat intake showed a declining trend across rural and urban. Regional prioritization...

This study aimed to investigate the influence of different sites of cacao (Theobroma cacao L.) cultivartion, represented by different soils and cropping systems, on biometrics attributes of pods and beans. The 12 study sites are in the cacao region of Bahia, Brazil, in the humid zone. The variation and the statistical differences between the means of these attributes clearly indicate the influence of genotype and environment interaction. Attributes pod wet biomass, beans with mucilage wet biomass and number of beans were positively correlated with the cultivation sites represented by Argisol Red-Yellow Eutrophic cambisolic and Argisol Red-Yellow Dystrophic Cohesive abrupt soils. The highest values of length and dry weight of dry cacao beans correspond to Argisol Red-Yellow Eutrophic cambisolic. The dystrophic soils are related to lower dry weight values of cacao beans. The selection of cacao cropping sites by biometric attributes also highlighted the Argisol Red-Yellow Eutrophic cambisolic and Argisol Red-Yellow Dystrophic Cohesive abrupt soils. Understanding the variability of cacao biometric attributes emphasizes the importance of using technologies for achieving sustainable production of cacao with quality.

No information is available on the efficacy of various nonparametric stability parameters when compared with GGE biplot methodology in assessing the stability of dry matter yield in bermudagrass (Cynodon dactylon L. Pers.) when a small number of genotypes is assayed. This study was conducted to compare the results of four nonparametric stability parameters developed by Huehn and Nassar (S

In this paper Non-Symmetric Correspondence Analysis (NSCA, Lauro and D’Ambra, 1984; D’Ambra and Lauro, 1989, 1992) is proposed as a useful technique for evaluating contingency table with a dependence structure, in particular within the context of comparing market share differences. Technical aspects of the method are discussed with a view towards application, giving special attention to the biplot representation ofNSCA as compared to the symmetric graphical display. Two examples dealing with canned food and the car market, respectively, are used to illustrate the usefulness of the technique and its kind of representation.

The Bajío-Mexico&#39;s central lowlands-is a region of economic importance because of its agricultural industry. Over time, agricultural practices have led to soil deterioration, loss of fertility, and abandonment. In this study, six agricultural soils were analyzed: AGQ, CTH, CTJ, JRM, CRC, and CYI, and used to develop a soil quality index (SQI) that includes the use of physicochemical, biological, and ecophysiological indicators to differentiate soil quality. Principal component analysis (PCA) was used, reducing the indicators from 46 to 4, which represents 80.4% of data variability. It was implemented the equation of additive weights using the variance of the principal components as a weight factor for the SQI. The developed SQI was according to the indicators WHC, SLT, N-NO 3 − , and qCO 2 , differentiating the quality of soils from the agricultural management in low quality (JRM &lt; CYI &lt; AGQ) and moderate quality (CTJ &lt; CRC &lt; CTH). The use of biological and ecophysio...

Se evaluaron 15 variables morfologicas y culturales, con mezcla de variables cuantitativas y cualitativas, a 58 aislamientos de Colletotrichum spp. con cuatro repeticiones. Se genero una agrupacion guiada por el Analisis de Coordenadas Principales (ACOP), basado en el coeficiente de similitud de Gower. Las dos primeras dimensiones del ACOP permitieron la perfecta discriminacion de tres grandes grupos: la primera dimension separaba a Colletotrichum gloeosporioides y su teleomorfo Glomerella cingulata de C. dematium; la segunda dimension permitia separar a C. gloeosporioides de su teleomorfo G. cingulata. Mediante el analisis simultaneo de los tres primeros ejes factoriales, se detectaron 21 grupos menores. Para la caracterizacion de los grupos se uso la representacion Biplot de la tabla de contingencia de los grupos y las variables. Se trabajo con las frecuencias relativas al tamano de los grupos para evitar la alta influencia que de otra forma tendrian los grupos mas numerosos sobre...

The cajuí Anacardium spp., which is similar to the caju Anacardium Ocidentale L., is a species adapted to edaphic-climatic conditions of the biome Cerratinga (Cerrado e Caatinga). Its fruit is composed of one swollen stalk (pedicel) which is formed by nutritional reserves rich in vitamin C and drupe (cashew nut). It is also rich in protein and lipids, but with smaller size. This paper focuses on investigating the applicability of the biplot graphical analysis in the process of selective breeding of cajuí population. The cajuí working

En este trabajo se presentan los resultados de un estudio, el primero de estas características a nivel de la Comunidad de Castilla y León, cuyo objetivo es identificar los perfiles socioeconómicos de las mujeres salmantinas, en situación de irregularidad laboral, en comparación con las características de las mujeres que desarrollan su actividad en un marco laboral regular.&lt;br /&gt;&lt;br /&gt;The objective of this work is identifying the socio-economic profiles of women holding undeclared jobs as opposed to the profites of those holding declared jobs. This study is the first of its kind in the Castilla y León Community.

We propose here some refinements of the ecological-niche factor analysis (ENFA) to describe precisely one organism's habitat selection. The ENFA is based on the concept of the ecological niche, and provides a measure of the realised niche within the available space from the computation of two parameters, the marginality and the specialization. By measuring the departure of the ecological niche from the average available habitat, the marginality identifies the preference of the individual, population, or species for specific conditions of the environment among the whole set of possibilities. The specialization appears as a consequence of the narrowness of the niche on some environmental variables. The ENFA is a factorial analysis that extracts one axis of marginality and several axes of specialization. We present here the use of biplots (i.e., the projection of both the pixels of the map and the environmental variables in the subspace extracted by the ENFA) as a way to identify the key-variables for management, assessing which habitat features are of prime importance and should be preserved or reinforced. With the help of this tool, we are now able to describe much more precisely the habitat selection of the organism under focus. In our application to the lynx in the Vosges mountains, based on sightings as well as other indices of lynx presence, we thus underlined a strong avoidance of agricultural areas by the lynx. We also highlighted the relative indifference of the lynx to the proximity of artificial areas and at the opposite, the sensitivity to the proximity of highways. The ENFA provides a suitable way to measure habitat use/selection under a large range of ecological contexts and should be used to define precisely the ecological niche and therefore identify the characteristics searched for by the organism under study.

Although correspondence analysis is now widely available in statistical software packages and applied in a variety of contexts, notably the social and environmental sciences, there are still some misconceptions about this method as well as unresolved issues which remain controversial to this day. In this paper we hope to settle these matters, namely (i) the way CA measures variance in a two-way table and how to compare variances between tables of different sizes, (ii) the influence, or rather lack of influence, of outliers in the usual CA maps, (iii) the scaling issue and the biplot interpretation of maps, (iv) whether or not to rotate a solution, and (v) statistical significance of results.

O objetivo deste trabalho foi avaliar a influência da interação de genótipos com ambientes (GxA) na produtividade de grãos de um conjunto de linhagens de soja (Glycine max L.). Foram utilizados dados de 11 experimentos (ambientes) realizados no Estado de Goiás. Em cada experimento foram avaliados 18 genótipos, sendo quatro cultivares comerciais como testemunhas. O método de análise da interação foi o procedimento AMMI (modelo de efeitos principais aditivos e interação multiplicativa). O padrão significativo das interações GxA foi captado apenas pelo primeiro eixo principal AMMI, o qual explicou 36% da soma de quadrados GxA original, sugerindo contaminação da matriz de interações clássica por ruídos que prejudicam a qualidade das predições de respostas fenotípicas obtidas pelos métodos tradicionais. Quanto à estabilidade de comportamento, a maioria das linhagens experimentais destacou-se (com menores interações com ambientes) em relação às cultivares testemunhas. Estas, no entanto, foram relativamente mais produtivas, sobretudo a cultivar Conquista. Entre as novas linhagens, os genótipos L-16, L-13 e L-14 mostraram ser os mais promissores para fins de recomendação como cultivares.

Hungary was one of the main countries in the world as regards the yields reached in maize production. The research was conducted to appraise the effect of NPK fertilizer on traits of different hybrid maize (Fao410, Fao340) at the University of Debrecen and our experiment was carried out in Centre for Agricultural Sciences, Institute of Crop Sciences at Látókép in 2018. NPK fertilizer was applied in six different combinations (0-0-0 control, 30-23-27 first dose, 60-46-54 second dose, 90-69-81 third dose, 120-92-108 fourth dose and 150-115-135 fifth dose kg · ha−1). The result of compound variance showed the level of fertilizer and interaction between fertilizer and genotypes were significant in one percent. Effect of genotypes was a variable level of fertilizer and providing a different yield in the level of fertilizer. The weight of seeds in ear and weight of ear were important traits in the average yield on Fao410 hybrid. Also, the fourth of the fertilizer level was the best level ...

Abstract Fusarium wilt, caused by Fusarium oxysporum f. sp. ciceris, is a major constraint to chickpea (Cicer arietinum L.) production and breeding for resistant cultivars is one of the most practical and economical strategies for managing this disease. The present study assesses elite chickpea breeding lines for Fusarium wilt resistance through multi-location evaluation in field sick plots over two years in India. The effects of genotype, environment and GE interaction for wilt incidence were highly significant with maximum variation caused by GE effect (82.09%) followed by genotype (11.16%) and environment effect (6.38%). GGE biplot analysis revealed that Rahuri and Indore locations were most discriminating locations and could differentiate the wilt resistant and susceptible chickpea genotypes while Dholi and Kanpur locations were least discriminating. Durgapura location was the most representative of average environment followed by Sehore while Rahuri and Indore locations were least representative. The genotypes GJG 0904, GJG 0906, GJG 1010, GJG 0814, GJG 0922, JAKI 9218 and GJG 1001 possessed high level of multiple race resistance against Fusarium wilt pathogen and can be exploited for disease resistance breeding in chickpea.

M aize (Zea mays L.) is a major staple food crop in West and Central Africa (WCA), providing about 15% of the total caloric intake of rural and urban consumers. Recurrent drought is the cause of frequent food shortages in the subregion and is also the most important factor limiting maize production. Production worth several billion U.S. dollars is lost annually when the rains fail or the rainfall is insuffi cient. The annual maize yield loss from drought stress in the savannas of WCA is estimated at 15% of total production and localized losses may be much higher in the marginal areas where the annual rainfall is below 500 mm and soils are sandy or shallow (Edmeades et al., 1995). Grain yield losses can even be greater if the drought stress occurs at the most droughtsensitive stages of crop growth, such as the fl owering and grain fi lling periods. For example, drought stress can reduce yield by 21% when it occurs at the grain fi lling period, by 50% when it happens at fl owering (Denmead and Shaw, 1960), and by as much as 90% (NeSmith and Ritchie, 1992) when it strikes from a few days before