Comparative Analysis of Polyphenolic Acids from Various Zea mays Parts in Ultrasound-Assisted Extraction

In this study, we compared different parameters in the ultrasound-assisted extraction of polyphenolic acids from seven parts of <i>Zea mays</i> (kernels, leaves, stems, corn silks, roots, the whole plant, and the whole fermented plant) to identify its richest natural sources. Additionally, the correlation between extraction parameters and polyphenol yield was investigated. The extraction was performed using ultrasound at varying powers (480 or 240 W) and frequencies (80 or 37 kHz). Total phenolic content (TPC) was determined using the Folin-Ciocalteu assay, while radical scavenging activity (RSA) was assessed via the DPPH assay. The TPC values ranged from 0.69 ± 0.00008 mg GAE/g to 4.07 ± 0.0004 mg GAE/g in corn. RSA analysis revealed the highest scavenging activity in corn silk (80.06% ± 1.01) and the lowest in kernels (2.77% ± 0.90). High-performance liquid chromatography identified up to 22 different phenolic acids per sample, with the 5 most abundant being chlorogenic acid, protocatechuic acid ethyl ester, quercetin, sinapic acid, and <i>trans</i>-cinnamic acid. The study found small effects of power and frequency on the extraction efficiency. This suggests a practical advantage for industrial-scale applications, as using 240 W instead of 480 W under the same conditions can reduce energy consumption without compromising yield.

Authors

Institutions

Publication Details

Journal
Foods
Published
2025-04-23
DOI
https://doi.org/10.3390/foods14091458
Primary Topic
Phytochemicals and Antioxidant Activities
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comparative Analysis of Polyphenolic Acids from Various Zea mays Parts in Ultrasound-Assisted Extraction

David Řepka, Lubomir Lapčí­k
Foods
Phytochemicals and Antioxidant Activities
article

Comparative Analysis of Polyphenolic Acids from Various Zea mays Parts in Ultrasound-Assisted Extraction

David Řepka, Lubomir Lapčí­k
article en

Abstract

In this study, we compared different parameters in the ultrasound-assisted extraction of polyphenolic acids from seven parts of <i>Zea mays</i> (kernels, leaves, stems, corn silks, roots, the whole plant, and the whole fermented plant) to identify its richest natural sources. Additionally, the correlation between extraction parameters and polyphenol yield was investigated. The extraction was performed using ultrasound at varying powers (480 or 240 W) and frequencies (80 or 37 kHz). Total phenolic content (TPC) was determined using the Folin-Ciocalteu assay, while radical scavenging activity (RSA) was assessed via the DPPH assay. The TPC values ranged from 0.69 ± 0.00008 mg GAE/g to 4.07 ± 0.0004 mg GAE/g in corn. RSA analysis revealed the highest scavenging activity in corn silk (80.06% ± 1.01) and the lowest in kernels (2.77% ± 0.90). High-performance liquid chromatography identified up to 22 different phenolic acids per sample, with the 5 most abundant being chlorogenic acid, protocatechuic acid ethyl ester, quercetin, sinapic acid, and <i>trans</i>-cinnamic acid. The study found small effects of power and frequency on the extraction efficiency. This suggests a practical advantage for industrial-scale applications, as using 240 W instead of 480 W under the same conditions can reduce energy consumption without compromising yield.

FoodsVol. 14(9)
Tomas Bata University in Zlín (CZ), Palacký University Olomouc (CZ)
Affordable and clean energy
Openalex Percentile: Top 92%
Phytochemicals and Antioxidant Activities
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.