Bioactive compounds and antioxidant activity from 44 fruit were evaluated. The data were statistically evaluated by analysis of common components and specific weights (CCSWA). Panã, acerola, açaí, and jabuticaba showed higher values of total phenolic compounds (TPCs) and antioxidant activity. The analysis of CCSWA was able to explain almost 100% of the variance of the data and established the correlation between TPC and antioxidant capacity, being the most influential variables in the classification of samples. This statistical method is ideal for quickly analyzing a large amount of data, as obtained in this research, which facilitates routines of industrial analysis.

No abstract

Summary The aim of this study was to assess the quality of different vegetable oils by applying common components and specific weights analysis as a tool for the evaluation and discrimination of chromatography, spectral and physicochemical data. This multiblock method of data analysis divided the data into three common components, corresponding to 56.44%, 34.74% and 8.77% of variance, and it was influenced mostly by chromatography, physicochemical and spectral data, respectively. Gas chromatography, which was used for discrimination of the botanical origin of oil and the groups of saturated, monounsaturated and polyunsaturated fatty acids, was situated in the first common dimension; physicochemical analysis, which was applied to evaluate quality parameters such as acid and saponification value and determine the stability of the product, was situated in the second common dimension. FTIR analysis, by exerting a minor influence on the common dimensions, was considered dispensable in evaluating the quality of vegetable oils by common components and specific weights analysis. Therefore, multiblock analysis could efficiently discriminate vegetable oils.

The common dimension (ComDim) chemometric method for multi‐block analysis and hierarchical cluster analysis (HCA) were used to evaluate the data obtained from the physico‐chemical and rheological characterization of 42 commercial fruit pulps. The physico‐chemical characteristics and the rheological behavior of the pulps were found to be considerably different. The Herschel–Bulkley equation was fit to the steady‐state flow curves of the fruit pulps, and it was found to appropriately describe the materials, which showed a wide range of yield stresses. The soluble solids content and the yield stress were the main factors responsible for the sample discrimination in the multivariate statistical analysis. The ComDim model indicates that these parameters may have a direct correlation. Namely, the soluble solids amount can influence the viscosity, as demonstrated by the similar scores of the samples in both common components, and this corroborated with the HCA analysis. Practical applications Fruit pulps can be used as raw materials in the food industry to obtain several products, such as nectars, jellies, ice creams, and juices, which can also be sold directly to consumers. To evaluate the technical and economic feasibility of those industrial processes, it is important to know the physico‐chemical properties of the products. Therefore, in this study we attempt to correlate the physical–chemical and rheological data using a new statistical approach.