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Estimation of Cold Stress, Plant Age, and Number of Leaves in Watermelon Plants Using Image Analysis

Authors :
Shona Nabwire
Collins Wakholi
Mohammad Akbar Faqeerzada
Muhammad Akbar Andi Arief
Moon S. Kim
Insuck Baek
Byoung-Kwan Cho
Source :
Frontiers in Plant Science, Vol 13 (2022)
Publication Year :
2022
Publisher :
Frontiers Media S.A., 2022.

Abstract

Watermelon (Citrullus lanatus) is a widely consumed, nutritious fruit, rich in water and sugars. In most crops, abiotic stresses caused by changes in temperature, moisture, etc., are a significant challenge during production. Due to the temperature sensitivity of watermelon plants, temperatures must be closely monitored and controlled when the crop is cultivated in controlled environments. Studies have found direct responses to these stresses include reductions in leaf size, number of leaves, and plant size. Stress diagnosis based on plant morphological features (e.g., shape, color, and texture) is important for phenomics studies. The purpose of this study is to classify watermelon plants exposed to low-temperature stress conditions from the normal ones using features extracted using image analysis. In addition, an attempt was made to develop a model for estimating the number of leaves and plant age (in weeks) using the extracted features. A model was developed that can classify normal and low-temperature stress watermelon plants with 100% accuracy. The R2, RMSE, and mean absolute difference (MAD) of the predictive model for the number of leaves were 0.94, 0.87, and 0.88, respectively, and the R2 and RMSE of the model for estimating the plant age were 0.92 and 0.29 weeks, respectively. The models developed in this study can be utilized in high-throughput phenotyping systems for growth monitoring and analysis of phenotypic traits during watermelon cultivation.

Details

Language :
English
ISSN :
1664462X
Volume :
13
Database :
Directory of Open Access Journals
Journal :
Frontiers in Plant Science
Publication Type :
Academic Journal
Accession number :
edsdoj.7d8b52eca9784b3ba79f2d9fca9c2ca8
Document Type :
article
Full Text :
https://doi.org/10.3389/fpls.2022.847225