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A classification method of stress in plants using unsupervised learning algorithm and chlorophyll fluorescence

Miao Lu¹, Pan Gao¹, Jin Hu^1,2,3

¹College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, Shaanxi, China.

Frontiers in Plant Science

|November 8, 2023

Summary

Detecting cucumber chilling injury using chlorophyll fluorescence (ChlF) technology is possible. This study developed a classification model to accurately assess chilling injury in cucumber seedlings, aiding in minimizing crop loss.

Keywords:

Fuzzy C-means clustering algorithm PSI chlorophyll fluorescence parameters low temperature uniform manifold approximation and projection

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Area of Science:

Plant physiology
Agricultural meteorology
Biophysics

Background:

Chilling injury significantly impacts cucumber production, necessitating rapid and accurate assessment methods.
Early detection of chilling injury is crucial for implementing timely remedial measures and minimizing crop losses.

Purpose of the Study:

To evaluate the efficacy of chlorophyll fluorescence (ChlF) technology for detecting chilling injury in cucumber seedlings.
To establish criteria for evaluating chilling injury using ChlF parameters.
To develop a classification model for identifying different degrees of chilling injury.

Main Methods:

Collected ChlF induction curves from cucumber seedlings under various low-temperature conditions.
Utilized Principal Component Analysis (PCA) to identify key ChlF parameters (Fv/Fm, Y(NO), qP, Fo) characterizing chilling injury.
Employed Uniform Manifold Approximation and Projection (UMAP) to extract new features for classification.
Constructed a Fuzzy C-means clustering algorithm model using extracted features to classify chilling injury.

Main Results:

Key ChlF parameters (Fv/Fm, Y(NO), qP, Fo) effectively characterized chilling injury.
The developed classification model accurately identified different classes of cucumber chilling injury.
Variations in indicators supported the model's validity, correlating with malondialdehyde content and ChlF images.

Conclusions:

Chlorophyll fluorescence technology offers a viable method for assessing chilling injury in cucumber seedlings.
The developed classification model provides a novel approach for evaluating plant stress responses to low temperatures.
This research contributes to a better understanding of plant damage under environmental stress.