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bioRxiv · 10.1101/2023.08.15.553356

Intra-leaf modeling of Cannabis leaflet shape produces synthetic leaves that predict genetic and developmental identities

Balant, M.·Garnatje, T.·Vitales, D.·Hidalgo, O.·Chitwood, D. H.
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Abstract

O_LIThe iconic, palmately compound leaves of Cannabis have attracted significant attention in the past. However, investigations into the genetic basis of leaf shape or its connections to phytochemical composition have yielded inconclusive results. This is partly due to prominent changes in leaflet number within a single plant during development, which has so far prevented the proper use of common morphometric techniques. C_LIO_LIHere we present a new method that overcomes the challenge of nonhomologous landmarks in palmate, pinnate and lobed leaves, using Cannabis as an example. We model corresponding pseudo-landmarks for each leaflet as angle-radius coordinates and model them as a function of leaflet to create continuous polynomial models, bypassing the problems associated with variable number of leaflets between leaves. C_LIO_LIWe analyze 341 leaves from 24 individuals from nine Cannabis accessions. Using 3,591 pseudo-landmarks in modeled leaves, we accurately predict accession identity, leaflet number, and relative node number. C_LIO_LIIntra-leaf modeling offers a rapid, cost-effective means of identifying Cannabis accessions, making it a valuable tool for future taxonomic studies, cultivar recognition, and possibly chemical content analysis and sex identification, in addition to permitting the morphometric analysis of leaves in any species with variable numbers of leaflets or lobes. C_LI

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Balant, M., Garnatje, T., Vitales, D., Hidalgo, O., Chitwood, D. H.. 2023-08-16. Intra-leaf modeling of Cannabis leaflet shape produces synthetic leaves that predict genetic and developmental identities. https://doi.org/10.1101/2023.08.15.553356

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