Related Experiment Video
Updated: Feb 12, 2026

Basics of Multivariate Analysis in Neuroimaging Data
Published on: July 24, 2010
Single-Kernel FT-NIR Spectroscopy for Detecting Supersweet Corn (Zea mays L. Saccharata Sturt) Seed Viability with
Guangjun Qiu1, Enli Lü2, Huazhong Lu3
1College of Engineering, South China Agricultural University, Guangzhou 510640, China. qiuq16@scau.edu.cn.
Abstract:
The viability and vigor of crop seeds are crucial indicators for evaluating seed quality, and high-quality seeds can increase agricultural yield. The conventional methods for assessing seed viability are time consuming, destructive, and labor intensive. Therefore, a rapid and nondestructive technique for testing seed viability has great potential benefits for agriculture. In this study, single-kernel Fourier transform near-infrared (FT-NIR) spectroscopy with a wavelength range of 1000-2500 nm was used to distinguish viable and nonviable supersweet corn seeds. Various preprocessing algorithms coupled with partial least squares discriminant analysis (PLS-DA) were implemented to test the performance of classification models. The FT-NIR spectroscopy technique successfully differentiated viable seeds from seeds that were nonviable due to overheating or artificial aging. Correct classification rates for both heat-damaged kernels and artificially aged kernels reached 98.0%. The comprehensive model could also attain an accuracy of 98.7% when combining heat-damaged samples and artificially aged samples into one category. Overall, the FT-NIR technique with multivariate data analysis methods showed great potential capacity in rapidly and nondestructively detecting seed viability in supersweet corn.
More Related Videos
10:50Detection and Quantification of Plasmodium falciparum in Aqueous Red Blood Cells by Attenuated Total Reflection Infrared Spectroscopy and Multivariate Data Analysis
Published on: November 2, 2018
08:28Mycorrhizal Maps as a Tool to Explore Colonization Patterns and Fungal Strategies in the Roots of Festuca rubra and Zea mays
Published on: August 26, 2022
Related Concept Videos
Seed Structure and Early Development of the Sporophyte
Analysis of Population Pharmacokinetic Data
Overview of Microsoft Excel as a Data Analysis Tool
Introduction to Seed Plants
Performing a Simple Data Analysis using MS-Excel Function
SUM: This function calculates the total sum of a range of values. It's the foundation for aggregating data, essential for determining overall trends and totals in datasets.
AVERAGE: It computes the mean value of a given set of numbers, providing a quick insight into the central...
Statistical Software for Data Analysis and Clinical Trials