Nondestructive detection of saline-alkali stress in wheat (Triticum aestivum L.) seedlings via fusion technology.

ABSTRACT:

Background

Wheat (Triticum aestivum L.) is an important grain crops in the world, and its growth and development in different stages is seriously affected by saline-alkali stress, especially in seedling stage. Therefore, nondestructive detection of wheat seedlings under saline-alkali stress can provide more comprehensive technical support for wheat breeding, cultivation and management.

Results

This research focused on moisture signal prediction and classification of saline-alkali stress in wheat seedlings using fusion techniques. After collecting and analyzing transverse relaxation time and Multispectral imaging (MSI) information of wheat seedlings, four regression models were used to predict the moisture signal. K-Nearest Neighbor (KNN) and Gaussian-Naïve Bayes (GNB) models

SUBMITTER: Gu Y 

PROVIDER: S-EPMC11375829 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature