ArticleJournal of Zhejiang University. Science. B2025
Optimized substrate selection for enhanced orchid growth based on high-throughput lysimetric arrays.
Article in Journal of Zhejiang University. Science. B, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Enhancing rapeseed biomass and yield estimation with ensemble learning and synergistic multidimensional features.Journal of Zhejiang University. Science. B · 2026Article
- Advancing multi-scale plant phenotyping for precision agriculture and sustainable crop production.Journal of Zhejiang University. Science. B · 2026Review
- Embedding of ripening topology into one-stage detection for tomato cluster phenotyping.Journal of Zhejiang University. Science. B · 2026Article
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Authors and funding
8 authors.
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Abstract
Orchids are highly valued ornamental plants whose growth conditions directly impact the economic returns of the horticultural industry. The substrate, acting both as a physical support and a nutrient reservoir, is critical for orchid development. Therefore, the careful selection of an appropriate growth substrate is of paramount importance. However, existing research on the relationship between orchid growth and substrate properties relies mainly on manual measurements of physiological indicators, with limited application of high-throughput phenotyping (HTP) platforms. In this study, we evaluated three distinct substrate types, peat soil mixed with perlite, pine bark, and river sand, which were applied to two orchid species,
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