Técnicas Multivariadas Exploratórias: Teorias e Aplicações no Software Statistica

Vicini, Lorena; Souza, Adriano Mendonça; Morales, Fidel Ernesto Castro; Souza, Francisca Mendonça

doi:10.32379/9788573913231

Cited by 13 publications

(11 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…It was carried by Principal Component Analyses (PCA) to explain the data variation and determine which soil attributes interfere in root growth. The radicial growth variables were considered supplementary variables to verify their behavior in relation to the others, without these being part of the initial analysis of PCA (Graffelman and Aluja-Banet, 2003;Vicini et al, 2018). Their supplementary use posterior to the analysis can, however, be highly informative.…”

Section: Discussionmentioning

confidence: 99%

Soybean Root Growth in Response to Chemical, Physical, and Biological Soil Variations

et al. 2021

View full text Add to dashboard Cite

Environmental conditions affect crop yield, and water deficit has been highlighted by the negative impact on soybean grain production. Radicial growth in greater volume and depth can be an alternative to minimize losses caused by a lack of water. Therefore, knowledge of how soybean roots behave before the chemical, physical, and biological attributes of the soil can help establish managements that benefit in-depth root growth. The objective was to evaluate the growth of soybean roots in response to chemical, physical, and biological variations in the soil, in different soil locations and depths. Six experiments were conducted in different locations. Soil samples were collected every 5 cm of soil up to 60 cm of soil depth for chemical, physical, and biological analysis. The roots were collected every 5 cm deep up to 45 cm deep from the ground. The six sites presented unsatisfactory values of pH and organic matter, and presented phosphorus, potassium, and calcium at high concentrations in the first centimeters of soil depth. The total porosity of the soil was above 0.50 m3 m−3, but the proportion of the volume of macropores, micropores, and cryptopores resulted in soils with resistance to penetration to the roots. Microbial biomass was higher on the soil surface when compared to deeper soil layers, however, the metabolic quotient was higher in soil depth, showing that microorganisms in depth have low ability to incorporate carbon into microbial biomass. Root growth occurred in a greater proportion in the first centimeters of soil-depth, possibly because the soil attributes that favor the root growth is concentrated on the soil surface.

show abstract

Section: Discussionmentioning

confidence: 99%

Soybean Root Growth in Response to Chemical, Physical, and Biological Soil Variations

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Additionally, cluster analysis was performed to determine the differences and similarities between agroecoregions, fields, and their YEs, using Ward's method for amalgamation (linkage) rule and square Euclidean distances as a measure of similarity. In order to group variables and cases in dendrograms and correlate them with the scatter plot of variables produced in the factorial analysis [32,33], Statistica 12 ® software was used. The relationships of enzyme activity with soil attributes and biota diversity (number of species identified in the samples) were investigated by linear and quadratic adjustments.…”

Section: Discussionmentioning

confidence: 99%

Soil Health Check-Up of Conservation Agriculture Farming Systems in Brazil

et al. 2021

View full text Add to dashboard Cite

Conservation agriculture has been promoted as the main strategy to regenerate soil life but its effect on soil enzyme activity remains little documented. This study investigated the β-glucosidase and arylsulfatase enzymes as tools to evaluate soil health at the field level. Croplands in four main grain-producing states in Brazil were selected for this study. In each cropland, three environments (high yield (HYE), medium yield (MYE), and low yield (LYE)) were delineated for soil sampling to determine soil chemical attributes and enzyme activity. In one of these fields with a large temporal database, soil DNA characterization was also undertaken. The two soil enzymes investigated were affected by a range of soil attributes and the most important of these were identified. Around 40% of the data points sampled had low soil organic matter content; these were associated with low enzyme activity. Furthermore, in HYE there was more biodiversity and a higher presence of plant-growth promoters, while in LYE there were more plant pathogenic organisms.

show abstract

“…Initially, the data were subjected to principal component analysis, an exploratory technique that aims to reduce the number of variables that need to be considered to a smaller number of indices (principal components), which are linear combinations of the original variables (MANLY; ALBERTO, 2019). One of the main uses of this technique is when the variables originate from Table 3 -Amounts of nitrogen (N), phosphorus (P), potassium (K), calcium (Ca) and magnesium (Mg) from tree legume residues added to the soil Tree legumes with fertilizer potential: a multivariate approach processes in which several characteristics must be observed simultaneously and there is a link between them, determined by correlation (VICINI et al, 2018), as occurs in the present study. Thus, with this analysis, it was sought to characterize the influence of treatments through the linear combinations that most explain the total variance of the original data.…”

Section: Methodsmentioning

confidence: 99%

“…Next, the data were subjected to cluster analysis, a numerical exploratory technique that aims to identify similar objects, individuals or treatments, and the groups formed show homogeneity within groups and heterogeneity between groups (VICINI et al, 2018). Thus, it was sought to identify which residues show the greatest dissimilarity with the control treatment (without residue application), thus suggesting greater fertilizer potential.…”

Section: Methodsmentioning

confidence: 99%

“…Finally, the canonical discriminant function analysis was performed using the data set with repetitions. This technique offers the possibility of separating different groups based on the available measures (MANLY; ALBERTO, 2019), making it possible to verify if there are significant differences between the groups, in addition to identifying the variables that discriminate treatments in different groups (VICINI et al, 2018). Thus, it was sought to show the greatest separation between treatments (groups), with the two best dimensions being analyzed by canonical variables 1 and 2 (CAN1 and CAN2).…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Tree legumes with fertilizer potential: a multivariate approach

Oliveira

Dias

Souza

et al. 2021

RCA

View full text Add to dashboard Cite

The objective of this study was to evaluate, through multivariate data analysis, which tree legume residues have the best fertilizer potential for agricultural crops in the semi-arid region of northeastern Brazil. The experiment was conducted in pots, in a randomized block design, with seven treatments and four replicates. Treatments consisted of residues of Sabiá, Jurema Preta and Gliricidia, besides two parts of the plant: leaves and leaves + branches. The pots were filled with 8.0 dm 3 of soil and the residues were added in the form of green mass, corresponding to 73.0 g of dry mass per pot. Maize seeds were sown and, at 65 days after addition of the residues, soil chemical attributes, growth and nutrient contents in the plants were evaluated. The data were studied through principal component analysis, clustering analysis, canonical discriminant function analysis and means comparison test from canonical variable 1. Gliricidia residues positively influenced soil K and Mg contents, as well as height, stem diameter, number of leaves and leaf contents of P, N and Mg in maize plants. These residues showed greater dissimilarity and separation compared to the control treatment and led to statistically higher means compared to the other treatments. Jurema Preta leaves positively influenced soil Ca, N and TOC, as well as leaf contents of K and Ca and total dry mass of maize. Multivariate statistical analysis made it possible to identify distinct potentials among legume residues for use as fertilizer in maize crop, and Gliricidia is the species with highest potential.

show abstract

Técnicas Multivariadas Exploratórias: Teorias e Aplicações no Software Statistica

Cited by 13 publications

References 0 publications

Soybean Root Growth in Response to Chemical, Physical, and Biological Soil Variations

Soybean Root Growth in Response to Chemical, Physical, and Biological Soil Variations

Soil Health Check-Up of Conservation Agriculture Farming Systems in Brazil

Tree legumes with fertilizer potential: a multivariate approach

Contact Info

Product

Resources

About