Image analysis using smartphones: relationship between leaf color and fresh weight of lettuce under different nutritional treatments

Image analysis can be useful for assessing crop health and predicting yield. Instead of expensive equipment, smartphones are considered an accessible and low-cost alternative. The objectives of this study were to evaluate whether fresh weight in green and red lettuce could be predicted by leaf color (intensity of green color measured by RGB) under different fertilizer treatments using RGB imaging from two widely used smartphone models (Samsung Galaxy and Apple iPhone). The two smartphones showed similar longitudinal patterns of RGB data (the intensity and dark green proportion), but the absolute difference in the RGB data was significantly different. Therefore, the averaged results were used for the analyses. Color intensity and dark green proportion were associated with the fresh lettuce weight (p = 0.005, 0.003, 0.014 and p < 0.001, respectively). This study suggests that farmers and practitioners can use these economic devices as a non-destructive method to diagnose and monitor the nutritional status and predict lettuce yield.

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Publication Details

Journal
Frontiers in Plant Science
Published
2025-05-05
DOI
https://doi.org/10.3389/fpls.2025.1589825
Citations
3
Primary Topic
Leaf Properties and Growth Measurement
Type
article
Field-Weighted Citation Impact
5.25

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article

Image analysis using smartphones: relationship between leaf color and fresh weight of lettuce under different nutritional treatments

Y. G. Cho, Jung-Chang Nam, Steven Kim, Ji-Won Jung et al.
3 citations
Frontiers in Plant Science
Leaf Properties and Growth Measurement
5.25
article

Image analysis using smartphones: relationship between leaf color and fresh weight of lettuce under different nutritional treatments

Y. G. Cho, Jung-Chang Nam, Steven Kim, Ji-Won Jung, Sang Hee Lee, Ho-Yeon Won, Eun-Ji Lee, Dong Sub Kim, Thomas Evert, Noah Kan
article en
3 citations

Abstract

Image analysis can be useful for assessing crop health and predicting yield. Instead of expensive equipment, smartphones are considered an accessible and low-cost alternative. The objectives of this study were to evaluate whether fresh weight in green and red lettuce could be predicted by leaf color (intensity of green color measured by RGB) under different fertilizer treatments using RGB imaging from two widely used smartphone models (Samsung Galaxy and Apple iPhone). The two smartphones showed similar longitudinal patterns of RGB data (the intensity and dark green proportion), but the absolute difference in the RGB data was significantly different. Therefore, the averaged results were used for the analyses. Color intensity and dark green proportion were associated with the fresh lettuce weight (p = 0.005, 0.003, 0.014 and p < 0.001, respectively). This study suggests that farmers and practitioners can use these economic devices as a non-destructive method to diagnose and monitor the nutritional status and predict lettuce yield.

Frontiers in Plant ScienceVol. 16
California State University, Monterey Bay (US), Kongju National University (KR)
U.S. Department of Agriculture, California State University, National Institute of Food and Agriculture
Openalex Percentile: Top 6%
Leaf Properties and Growth Measurement
5.25
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Image analysis using smartphones: relationship between leaf color and fresh weight of lettuce under different nutritional treatments — Y. G. Cho, Jung-Chang Nam, et al. · Frontiers in Plant Science (2025) | TGRS Research Map | TGRS