Effects of Steaming on Fresh Edible Kernels of Waxy and Normal Maize Determined by Metabolomic Analysis

The understanding of the characteristics and metabolite changes in waxy and normal maize kernels after cooking is rather limited. This study was designed to meticulously analyze the differences in characteristics and metabolites of these kernels before and after steaming. To cut environmental impacts, samples were obtained by pollinating one ear with mixed pollen. Non-targeted metabolomics was used to analyze metabolites comprehensively. The results demonstrated that a total of 4043 annotated metabolites were identified. Principal component analysis (PCA) indicated distinct variances between kernels before and after steaming and between the two maize types. Steaming led to an increase in differential metabolites (DEMs) for both maize varieties, noticeably in waxy maize. In waxy maize, the down-regulated DEMs were associated with lipid metabolism, while the up-regulated ones were related to amino acid, phenylpropanoid, and flavone metabolism. Compared to steamed normal maize kernels, waxy maize had more DEMs in purine and steroid pathways, fewer in fatty acid, α-linolenic acid, and phenylpropanoid ones, with marked differences in secondary metabolites like those in amino acid metabolism. This study offers a vital foundation and direction for future research on metabolic pathways regarding maize quality improvement and flavor regulation.

Authors

Institutions

Publication Details

Journal
Foods
Published
2024-12-22
DOI
https://doi.org/10.3390/foods13244157
Citations
3
Primary Topic
Meat and Animal Product Quality
Type
article
Field-Weighted Citation Impact
1.02

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Effects of Steaming on Fresh Edible Kernels of Waxy and Normal Maize Determined by Metabolomic Analysis

Gening Jiang, Xuecai Zhang, Yonghui He, Zhitong Yin et al.
3 citations
Foods
Meat and Animal Product Quality
1.02
article

Effects of Steaming on Fresh Edible Kernels of Waxy and Normal Maize Determined by Metabolomic Analysis

Gening Jiang, Xuecai Zhang, Yonghui He, Zhitong Yin, Huanhuan Liu, Yingjie Zhu, Mingjun Xu
article en
3 citations

Abstract

The understanding of the characteristics and metabolite changes in waxy and normal maize kernels after cooking is rather limited. This study was designed to meticulously analyze the differences in characteristics and metabolites of these kernels before and after steaming. To cut environmental impacts, samples were obtained by pollinating one ear with mixed pollen. Non-targeted metabolomics was used to analyze metabolites comprehensively. The results demonstrated that a total of 4043 annotated metabolites were identified. Principal component analysis (PCA) indicated distinct variances between kernels before and after steaming and between the two maize types. Steaming led to an increase in differential metabolites (DEMs) for both maize varieties, noticeably in waxy maize. In waxy maize, the down-regulated DEMs were associated with lipid metabolism, while the up-regulated ones were related to amino acid, phenylpropanoid, and flavone metabolism. Compared to steamed normal maize kernels, waxy maize had more DEMs in purine and steroid pathways, fewer in fatty acid, α-linolenic acid, and phenylpropanoid ones, with marked differences in secondary metabolites like those in amino acid metabolism. This study offers a vital foundation and direction for future research on metabolic pathways regarding maize quality improvement and flavor regulation.

FoodsVol. 13(24)
Centro Internacional de Mejoramiento de Maíz Y Trigo (MX), Yangzhou University (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Priority Academic Program Development of Jiangsu Higher Education Institutions, National Key Research and Development Program of China
Openalex Percentile: Top 24%
Meat and Animal Product Quality
1.02
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.