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Classification of Vase Life Day Based on Petal Colorimetric Data in Cut Lisianthus Using AutoML

Authors :
Hye Sook Kwon
Seong Heo
Source :
Horticulturae, Vol 10, Iss 10, p 1033 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

This study investigated the potential of petal colorimetric data to classify vase life stages in cut lisianthus flowers (Eustoma grandiflorum). We analyzed the changes in the petal color space over time, focusing on the b* value as an indicator of senescence due to increasing yellowing caused by copigmentation. A comparative analysis was conducted between two cultivation methods: soil (S) and hydroponic (H) cultivation. The objective was to evaluate the performance of machine learning models trained to classify vase life stages based on petal color data. Automated machine learning models exhibited better performance in H-cultivated cut flowers, effectively distinguishing days within the vase life stages from Days 1 to 14 for H cultivation. Cut flowers cultivated under S conditions showed less variation in the color space from Days 1 to 9, maintaining a relatively uniform color range. This made it more difficult to distinguish the vase life stages compared to H cultivation. These findings demonstrate that petal color metrics can serve as reliable indicators of cut flower senescence and potentially facilitate nondestructive methods for classifying vase life stages. This technology holds promise for wider applications in the floriculture industry, improving quality control, and extending the vase life of various cut-flower crops.

Details

Language :
English
ISSN :
23117524
Volume :
10
Issue :
10
Database :
Directory of Open Access Journals
Journal :
Horticulturae
Publication Type :
Academic Journal
Accession number :
edsdoj.fca947a13f5e4379ae04fb6af98dcb27
Document Type :
article
Full Text :
https://doi.org/10.3390/horticulturae10101033