Correlations among behavior, performance and environment in broiler breeders using multivariate analysis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Multivariate analysis of fresh-cut carambola slices stored under different temperatures

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Discrimination of geomorphic surfaces with multivariate analysis of soil attributes in sandstone - basalt lithosequence

O conceito de superfície geomórfica permite uma interligação entre os diferentes ramos da ciência do solo, tais como geologia, geomorfologia e pedologia. Esta associação favorece a compreensão da distribuição espacial dos solos na paisagem, e torna possível compreender o comportamento dos atributos do solo, que estão principalmente relacionadas com a estratigrafia e formas do relevo. Assim, este estudo visa à aplicação da estatística multivariada para categorizar superfícies geomórficas em uma litossequência arenito-basalto, de modo a fornecer uma base para a avaliação do solo em áreas afins. A área de estudo está localizada no município de Pereira Barreto, São Paulo, Brasil. A área escolhida possui 530 hectares, onde foram localizadas e mapeadas três superfícies geomórficas (I, II e III). Na área, 134 amostras foram coletadas nas profundidades de 0,0-0,2 m e 0,8-1,0 m, foram determinados os conteúdos de areia, silte e argila, pH em CaCl2, conteúdo de MO, P, Ca, Mg, K, Al e H+Al. Com base nos resultados, foram realizadas a análise univariada e multivariada de variância, clusters e principal componente, a fim de comparar as três superfícies geomórficas. A análise estatística univariada dos atributos do solo não foi eficiente na identificação das três superfícies geomórficas. Utilizando-se os atributos físicos e químicos do solo, as técnicas estatísticas multivariada permitiram à separação dos três grupos de corpos naturais do solo que foram equivalentes as três superfícies geomórficas mapeadas. Estes resultados são interessantes, pois demonstram a viabilidade da utilização de classificação numérica das superfícies geomórficas para ajudar no mapeamento de solo.

Evaluation of development traits of beef buffalo in Brazil using multivariate analysis

The buffalo population in Brazil increased about 12.9% between 1998 and 2003, to 2.8 million head, evidencing the importance of this species for the country. The objective this work was evaluation of animal growth using multivariate analysis. The data were from 2,944 water buffalo from 10 herds raised in pasture conditions in Brazil. Principal components and genetic distances were estimated using proc PRINCOMP and proc CANDISC in SAS (SAS Inst. Inc. Cary, NC, USA). Variables analyzed were birth weight (BW), age at weaning (AW), weaning weight (WT), weight adjusted to 205 d (W205), total gain between BW and WT (TG), daily gain between BW and WT (DG), weight adjusted to 365 d (W365), total gain between WT and W365 (TG3), daily gain between WT and W365 (TGD3), weight adjusted to 550 d (W550) and weight adjusted to 730 d (W730). Means and standard deviations for each variable were 39.4 +/- 3.2 kg, 225.6 +/- 38.8 d, 209.4 +/- 39.4 kg, 195.4 +/- 30.2 kg, 157.4 +/- 32.0 kg, 0.77 +/- 0.16 kg/d, 282.0 +/- 43.5 kg, 73.9 +/- 33.9 kg, 0.53 +/- 0.21 kg/d, 406.8 +/- 67.9 kg, and 468.2 +/- 70.6 kg, respectively. The eigenvalues to four first principal components were 5.29, 2.54, 1.66, 1.01, and justify 48%, 23%, 15% and 9%, respectively, with a total cumulative 95%. We created an index using the first principal component which is Y. 0.0552 BW + 0.0438 AW + 0.3142 WT + 0.3549 W205 + 0.3426 TG + 0.3426 DG + 0.4070 W365- 0.1531 TG3 - 0.2059 TGD3 - 0.3833 W550 - 0.3966 W730. This index accounted for 48% the variation in the correlation matrix. This principal component emphasizes early growth of the animal. Estimates the pair-wise squared distances between herds, D2(i vertical bar j)= ((x) over bar (i)-(x) over bar (j))' cov(-1)((x) over bar (i)-(x) over bar (j)), using with basis the average of weight of animals, showed the largest distance between herds eight (Murrah: DF) and seven (Murrah: Amazon) and the closest distance between herds one (Mediterranean - RS) and five (Jafarabadi - SP).

GC Fingerprints Coupled to Pattern-Recognition Multivariate SIMCA Chemometric Analysis for Brazilian Gasoline Quality Studies

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Screening Brazilian Commercial Gasoline Quality by ASTM D6733 GC and Pattern-Recognition Multivariate SIMCA Chemometric Analysis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Evaluation of the influences of solution path length and additives concentrations on the solar photo-Fenton degradation of 4-chlorophenol using multivariate analysis

This study reports the photodegradation of 4-chlorophenol (4-CP) in aqueous solution by the photo-Fenton process using solar irradiation. The influence of solution path length, and Fe(NO3)(3) and H2O2 concentrations on the degradation of 4-CP is evaluated by response surface methodology. The degradation process was monitored by the removal of total organic carbon (TOC) and the release of chloride ion. The results showed a very important role of iron concentration either for TOC removal or dechlorination. on the other hand, a negative effect of increasing solution path length on mineralization was observed, which can be compensated by increasing the iron concentration. This permits an adjustment of the iron concentration according to the irradiation exposure area and path length (depth of a tank reactor). Under optimum conditions of 1.5 mM Fe(NO3)(3), 20.0 mM H2O2 and 4.5 cm solution path length, 17 min irradiation under solar light were sufficient to reduce a 72 mg C L-1 solution of 4-CP by 91 (c) 2006 Elsevier B.V. All rights reserved.

Multivariate analysis of photo-Fenton degradation of the herbicides tebuthiuron, diuron and 2,4-D

The degradation of herbicides in aqueous solution by photo-Fenton process using ferrioxalate complex (FeOx) as source of Fe2+ was evaluated under blacklight irradiation. The commercial products of the herbicides tebuthiuron, diuron and 2,4-D were used. The multivariate analysis, more precisely, the response surface methodology was applied to evaluate the role of FeOx and hydrogen peroxide concentrations as variables in the degradation process, and in particular, to define the concentration ranges that result in the most efficient degradation of the herbicides. The degradation process was evaluated by the determination of the remaining total organic carbon content (TOC), by monitoring the decrease of the concentrations of the original compounds using HPLC and by the chloride ion release in the case of diuron and 2,4-D. Under optimized conditions, 20min were sufficient to mineralize 93% of TOC from 2,4-D and 90% of diuron, including oxalate. Complete dechlorination of these compounds was achieved after 10 min reaction. It was found that the most recalcitrant herbicide is tebuthiuron, while diuron shows the highest degradability. However, under optimized conditions the initial concentration of tebuthiuron was reduced to less than 15%, while diuron and 2,4-D were reduced to around 2% after only 1 min reaction. Furthermore, it was observed that the ferrioxalate complex plays a more important role than H2O2 in the photodegradation of these herbicides in the ranges of concentrations investigated. (C) 2004 Elsevier Ltd. All rights reserved.

Evaluation of the combined solar TiO2/photo-Fenton process using multivariate analysis

The effect of combining the photocatalytic processes using TiO 2 and the photo-Fenton reaction with Fe3+ or ferrioxalate as a source of Fe2+ was investigated in the degradation of 4-chlorophenol (4CP) and dichloroacetic acid (DCA) using solar irradiation. Multivariate analysis was used to evaluate the role of three variables: iron, H2O2 and TiO2 concentrations. The results show that TiO2 plays a minor role when compared to iron and H2O2 in the solar degradation of 4CP and DCA in the studied conditions. However, its presence can improve TOC removal when H2O2 is totally consumed. Iron and peroxide play major roles, especially when Fe(NO3)3 used in the degradation of 4CP. No significant synergistic effect was observed by the addition of TiO 2 in this process. On the other hand, synergistic effects were observed between FeOx and TiO2 and between H 2O2 and TiO2 in the degradation of DCA. © IWA Publishing 2004.

Multivariate curve resolution analysis applied to time-resolved synchrotron X-ray Absorption Spectroscopy monitoring of the activation of copper alumina catalyst

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Multivariate analysis of the temporal variability of sugarcane ripening in south-eastern Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Multivariate analysis for animal selection in experimental research

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Multivariate analysis for selecting animals for experimental research

Background Several researchers seek methods for the selection of homogeneous groups of animals in experimental studies, a fact justified because homogeneity is an indispensable prerequisite for casualization of treatments. The lack of robust methods that comply with statistical and biological principles is the reason why researchers use empirical or subjective methods, influencing their results. Objective To develop a multivariate statistical model for the selection of a homogeneous group of animals for experimental research and to elaborate a computational package to use it. Methods The set of echocardiographic data of 115 male Wistar rats with supravalvular aortic stenosis (AoS) was used as an example of model development. Initially, the data were standardized, and became dimensionless. Then, the variance matrix of the set was submitted to principal components analysis (PCA), aiming at reducing the parametric space and at retaining the relevant variability. That technique established a new Cartesian system into which the animals were allocated, and finally the confidence region (ellipsoid) was built for the profile of the animals’ homogeneous responses. The animals located inside the ellipsoid were considered as belonging to the homogeneous batch; those outside the ellipsoid were considered spurious. Results The PCA established eight descriptive axes that represented the accumulated variance of the data set in 88.71%. The allocation of the animals in the new system and the construction of the confidence region revealed six spurious animals as compared to the homogeneous batch of 109 animals. Conclusion The biometric criterion presented proved to be effective, because it considers the animal as a whole, analyzing jointly all parameters measured, in addition to having a small discard rate.

Linkage & Selective Mapping and QTL Analysis in a Harosoy x Clark population of 300 RILs

Four of the 12 major Glycine max ancestors of all modern elite U.S.A. soybean cultivars were the grandparents of Harosoy and Clark, so a Harosoy x Clark population would include some of that genetic diversity. A mating of eight Harosoy and eight Clark plants generated eight F1 plants. The eight F1:2 families were advanced via a plant-to-row selfing method to produce 300 F6-derived RILs that were genotyped with 266 SSR, 481 SNP, and 4 classical markers. SNPs were genotyped with the Illumina 1536-SNP assay. Three linkage maps, SSR, SNP, and SSR-SNP, were constructed with a genotyping error of < 1 %. Each map was compared with the published soybean consensus map. The best subset of 94 RILs for a high-resolution framework (joint) map was selected based on the expected bin length statistic computed with MapPop. The QTLs of seven traits measured in a 2-year replicated performance trial of the 300 RILs were identified using composite interval mapping (CIM) and multiple-interval mapping (MIM). QTL x Year effects in multiple trait analysis were compared with results of multiple-interval mapping. QTL x QTL effects were identified in MIM.