Starch adulteration in turmeric samples through multivariate analysis with infrared spectroscopy

Macêdo, Isaac Yves Lopes de; Machado, Fábio Bahls; Ramos, Gabrielle Santos; Costa, André Gabriel do Carmo; Batista, Rayssa Dias; Filho, Arlindo Rodrigues Galvão; Asquieri, Eduardo Ramirez; Souza, Aparecido Ribeiro de; Oliveira, Anselmo E. de; Gil, Eric de Souza

doi:10.1016/j.foodchem.2020.127899

Cited by 14 publications

(5 citation statements)

References 27 publications

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“…Raman specters were treated with a first-derivative Savitzky-Golay filter with a 2nddegree polynomial and 21-point window. The dataset was further treated with the standard normal variate filter [9].…”

Section: Methodsmentioning

confidence: 99%

“…Among the promising techniques, Raman Spectroscopy allows the chemical identification of minor compounds and also the macro structural characterization of different polymorphs. Chemometric approaches, such as principal component analysis and K-means clustering, can explore and assist in the observation correlated patterns with specific samples within a group [9].…”

Section: Introductionmentioning

confidence: 99%

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Arrowroot and Cassava Mixed Starch Products Identification by Raman Analysis with Chemometrics

et al. 2021

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Food frauds present a major problem in the foodstuff industry. Arrowroot and cassava may be targeted in adulteration and falsification processes. Raman analysis combined with chemometric techniques was proposed to identify the mixing and adulteration of these foodstuffs in commercial products. 67 cassava and 5 arrowroot samples were prepared in laboratory. 21 cassava and 5 arrowroot commercial samples were purchased in local stores. Raman assays were performed in the range of 400 to 2300 cm−1. Principal component analysis with K-means clustering was used to identify the adulteration of these products. It was possible to observe the separation of three different groups in the data, these groups labelled group 1, 2 and 3 were correspondent to cassava-like samples, mixed samples, and arrowroot-like samples, respectively. Despite the visual analysis related to sensory characteristics and the visual analysis of each Raman spectrum of cassava and arrowroot not being able to differentiate these foodstuffs, the chemometric approaches with the Raman specters data were able to identify which samples were pure arrowroot, pure cassava and which were mixed products. The proposed approach showed to be an effective tool in the investigation of fraud for arrowroot and cassava.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Arrowroot and Cassava Mixed Starch Products Identification by Raman Analysis with Chemometrics

et al. 2021

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“…One hypothesis is that the treatment with lactic acid alone is not relevant for the modification but is relevant if the lactic acid is present during the treatment with UV-C from the sun or artificial sources, with a known oxidizing effect. The graft of the lactide formatted to the starch structure as an ether [13] would draw acids radicals from starch, which could explain the increase and stability of pH values in samples subjected to the joint action of the addition of lactic acid and UV-C treatment [19].…”

Section: Mirmentioning

confidence: 99%

“…The methods used for starch analysis are time-consuming, but mid-infrared spectroscopy allows for the analysis of a small sample, identifying most modifications quickly and accurately, as proven in many food and starch products, including starches with expansion properties [15,[19][20][21]. However, the presence of excess glucose in these polymers makes the analysis difficult.…”

Section: Introductionmentioning

confidence: 99%

“…Despite its economic importance in South America, sour cassava starch is still produced by natural fermentation followed by sun exposition [18]. Not yet classified as modified starch, it can only be identified by the expansion property evaluated by the specific volume in baking [12,19] and the carboxyl content [12]. Its characterization as reported in the literature points to an oxidation reaction [12] linked to the action ultraviolet radiation [20].…”

Section: Introductionmentioning

confidence: 99%

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Modified Cassava Starches’ Identification through Mid-Infrared Spectroscopy and Exploratory Analysis

et al. 2023

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Different starch properties may cause alterations in the foodstuff’s external appearance. However, modification processes in starches are usually secretive. The use of chemically modified starches is regulated by international standards, which makes it important to identify its presence and type. Mid-infrared spectroscopy (MIR)-modified starches’ identification can be hindered by the presence of excess glucose. This research investigates types of modification in commercial starches and in approaches that circumvent MIR’s limitations with exploratory analysis. It also considers that enzymatic hydrolysis (α-amylase and amyloglucosidase) can highlight the points of modification in the structure, which can be detected with infrared assays. To determine if sour cassava starch (FCS) is modified and check its type, six samples were selected: a native one, three of the most common cassava modified starches (etherified, esterified, and FCS), and two laboratory processed samples (Acid, Oxidized). The results showed that the sour cassava starch showed similarities with a commercial ester and an oxidized cassava starch, which may be due to the formation of a graft, corresponding to what the literature has already reported for corn starch treated with lactic acid and gamma radiation.

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Detection of Starch in Turmeric Using Machine Learning Methods

Lanjewar

Parate²,

Wakodikar³

et al. 2023

Lecture Notes in Networks and Systems

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Starch adulteration in turmeric samples through multivariate analysis with infrared spectroscopy

Cited by 14 publications

References 27 publications

Arrowroot and Cassava Mixed Starch Products Identification by Raman Analysis with Chemometrics

Arrowroot and Cassava Mixed Starch Products Identification by Raman Analysis with Chemometrics

Modified Cassava Starches’ Identification through Mid-Infrared Spectroscopy and Exploratory Analysis

Detection of Starch in Turmeric Using Machine Learning Methods

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