2020
DOI: 10.1590/fst.04919
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Quality pattern evaluation of frozen soursop pulps: an assessment based on chemical composition and chemometric analysis

Abstract: On the present study, the physicochemical properties and mineral composition of commercially-frozen soursop pulps from the southern region of the state of Bahia, Brazil, were evaluated. The physicochemical parameters such as soluble solids (°Brix), acidity and pH were determined according to reference methodologies. For mineral composition evaluation, samples were digested in a closed microwave system and the elements K, P, S, Ca, Mg, Fe, Cu, Zn, and Mn were quantified through inductively coupled plasma optica… Show more

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Cited by 4 publications
(4 citation statements)
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“…The principal component analysis (PCA) showed that the cumulative variance contribution rate of the first three principal components reached 88.97% (see Table 4), which indicated that these three principal components could accurately and objectively reflect the similarity between samples, so a total of three principal components were extracted (Nascimento et al 2020;Fernandes et al. 2019).…”
Section: Principal Component Analysismentioning
confidence: 99%
“…The principal component analysis (PCA) showed that the cumulative variance contribution rate of the first three principal components reached 88.97% (see Table 4), which indicated that these three principal components could accurately and objectively reflect the similarity between samples, so a total of three principal components were extracted (Nascimento et al 2020;Fernandes et al. 2019).…”
Section: Principal Component Analysismentioning
confidence: 99%
“…Food quality is related to its content and type of minerals that contribute to taste, appearance, texture and stability, as well as its nutritional value (Fernandes et al, 2019;Nascimento et al, 2020). However, minerals in fruit are affected by environmental factors (Hernández Suárez et al, 2007;Watanabe et al, 2015).…”
Section: Physical and Chemical Properties Of Samplesmentioning
confidence: 99%
“…Principal component analysis is a statistical technique for the reduction of input data dimension and is largely used for feature extraction. It captures the relevant information in a set of input data providing a lower dimension (Fernandes et al, 2019;Nascimento et al, 2020). For improved visualization of the data, PCA was performed to distinguish aroma attributes of 10 shrimp during the hot-air-drying process (Figure 3b).…”
Section: Classification Of Aroma Attributes Of Shrimp During the Hot-airdrying Process Using Pcamentioning
confidence: 99%