Unverified paper record
Low-Cost Imaging to Quantify Germination Rate and Seedling Vigor across Lettuce Cultivars.
Sensors (Basel, Switzerland) · 29 Jun 2024 · 10.3390/s24134225
Abstract
The survival and growth of young plants hinge on various factors, such as seed quality and environmental conditions. Assessing seedling potential/vigor for a robust crop yield is crucial but often resource-intensive. This study explores cost-effective imaging techniques for rapid evaluation of seedling vigor, offering a practical solution to a common problem in agricultural research. In the first phase, nine lettuce ( Lactuca sativa ) cultivars were sown in trays and monitored using chlorophyll fluorescence imaging thrice weekly for two weeks. The second phase involved integrating embedded computers equipped with cameras for phenotyping. These systems captured and analyzed images four times daily, covering the entire growth cycle from seeding to harvest for four specific cultivars. All resulting data were promptly uploaded to the cloud, allowing for remote access and providing real-time information on plant performance. Results consistently showed the 'Muir' cultivar to have a larger canopy size and better germination, though 'Sparx' and 'Crispino' surpassed it in final dry weight. A non-linear model accurately predicted lettuce plant weight using seedling canopy size in the first study. The second study improved prediction accuracy with a sigmoidal growth curve from multiple harvests ( R 2 = 0.88, RMSE = 0.27, p < 0.001). Utilizing embedded computers in controlled environments offers efficient plant monitoring, provided there is a uniform canopy structure and minimal plant overlap.
Plant phenotyping relevance
低コスト画像・蛍光画像・組込みカメラを用いた生育モニタリングとキャノピー形状からの植物重量予測が研究の中心で、フェノタイピング手法とその予測性能を評価している。
abstractThis study explores cost-effective imaging techniques for rapid evaluation of seedling vigor
abstractThe second phase involved integrating embedded computers equipped with cameras for phenotyping.
abstractA non-linear model accurately predicted lettuce plant weight using seedling canopy size in the first study.
abstractThe second study improved prediction accuracy with a sigmoidal growth curve from multiple harvests ( R 2 = 0.88, RMSE = 0.27, p < 0.001).
Code and data availability
The paper's image-analysis scripts are only referenced as supplemental materials of the first author's Master's Thesis (ref [24]) with no public URL, and the data availability statement says the dataset is available only on request from the authors. No public, paper-specific phenotype dataset, images, or code deposit满足
No evidence-backed public reproduction asset is currently recorded.
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