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Home
Grain Quality In Maize.

Home
Grain Quality In Maize.

Related Experiment Video

High-throughput, Microscale Protocol for the Analysis of Processing Parameters and Nutritional Qualities in Maize Zea mays L.

High-throughput, Microscale Protocol for the Analysis of Processing Parameters and Nutritional Qualities in Maize Zea mays L.

Published on: June 16, 2018

Grain Quality in Maize.

Anthony Assibi Mahama¹, Adrienne N Moran Lauter¹, M Paul Scott²

¹Corn Insects and Crop Genetics Research Unit, United States Department of Agriculture-Agricultural Research Service, Ames, Iowa 50011, USA.

Cold Spring Harbor Protocols

|December 29, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

Measuring grain quality is crucial for breeding and market classes. This review covers official and unofficial methods for analyzing maize composition, including near-infrared spectroscopy (NIRS), to assess grain suitability.

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Area of Science:

Agricultural Science
Analytical Chemistry
Biochemistry

Background:

Grain quality determines its suitability for specific uses, defined by chemical composition and physical properties.
Accurate measurement of grain quality is vital for identity preservation, breeding improved varieties, and understanding genetic controls.
Key compositional traits include protein, starch, oil, amino acids, phytate, and phosphorus, impacting nutritional value and bioavailability.

Purpose of the Study:

To review official and non-official methods for measuring maize grain quality traits.
To discuss the application of near-infrared spectroscopy (NIRS) for rapid compositional analysis.
To highlight factors influencing assay selection and analytical outcome optimization.

Main Methods:

Review of established analytical methods for maize compositional analysis (protein, starch, oil, etc.).

Discussion of non-official methods for phytate, available phosphorus, and amino acid balance.

Description of near-infrared spectroscopy (NIRS) principles and application in grain analysis.

Main Results:

Official methods provide standardized measurements for key maize components.
Near-infrared spectroscopy (NIRS) offers a rapid, non-destructive method for predicting multiple compositional traits.
Sensitivity, accuracy, precision, throughput, and cost are critical considerations in method selection.

Conclusions:

Accurate assessment of grain quality relies on appropriate analytical methods and experimental design.
NIRS is a powerful tool for high-throughput grain quality analysis, complementing traditional methods.
Optimized analytical strategies ensure reliable data for breeding, commerce, and research.