Advancements in Multispectral Imaging Enhance Genetic Understanding of Ornamental Plants for Urban Greening

by Anna

Ornamental plants, appreciated for their diverse morphological features, play an increasingly vital role in urban greening initiatives, notably in endeavors such as rooftop greening. However, the unique challenges posed by such environments, including limited soil depth and lack of irrigation, necessitate the selection of resilient species like those within the Phedimus genus.

Current research endeavors focus on unraveling the genetic and seasonal morphological intricacies of these plants, with a particular emphasis on understanding color variations and dormancy patterns. Despite notable strides in comprehending these aspects, genetic and breeding research faces a slow trajectory, and the evaluation methods for morphological traits remain in their nascent stages. While recent developments in multispectral image analysis show promise in non-destructively assessing plant traits, their application in evaluating ornamental plants remains constrained.

In a significant contribution to this field, Plant Phenomics featured a research article titled “Multispectral Phenotyping and Genetic Analyses of Spring Appearance in Greening Plant, Phedimus spp.”

The study employed multispectral image analysis to scrutinize the color attributes of Phedimus spp., a crucial consideration for ornamental plants aimed at advancing breeding techniques. By generating an F1 population through the crossbreeding of two Phedimus types, P1 (evergreen) and P2 (winter dormant), researchers unveiled a spectrum of traits leaning towards P2. This diversity encompassed variations in leaf color, size, shape, and plant height. Utilizing multispectral image capture and principal component analysis (PCA) of reflected wavelengths from the plant body, the study identified two major components, elucidating over 95% of the variations.

PC1 primarily denoted the contrast between green visible light and other colors, while PC2 represented the reflection of near-infrared (NIR) light. The F1 plants notably clustered closer to P2, indicating the distinguishability of P1 due to its higher reflection of green wavelengths. The study further delved into the correlation between plant color and covered area, revealing a negative correlation between PC1 values and plant cover area, signifying that lower PC1 values (indicative of green color) corresponded to larger covered areas.

Annual phenotypic correlations uncovered positive associations between green wavelengths and vegetation indices related to biomass and pigments. Conversely, non-green visible light and indices linked to anthocyanins exhibited a positive interrelation but a negative correlation with the green light set. RAD-seq and Quantitative Trait Loci (QTL) analysis identified significant QTLs on two linkage groups, LG-34.P2 and LG-7.P1, associated with various traits, including leaf color and dormancy.

The QTL on LG-34.P2 demonstrated a robust association with multiple traits, remaining consistent across two measurement years, underscoring its significant influence on leaf color.

In summary, the research showcased the efficacy of multispectral imaging in capturing not only leaf color variations but also genetic factors influencing dormancy. This method provides a more objective and comprehensive evaluation compared to traditional techniques, offering fresh insights into the genetic analysis of leaf color and dormancy in Phedimus spp. with potential implications for breeding programs targeting ornamental plants.

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