Intraspecific Leaf Trait Variation Across and Within Wine Grape Varieties

Macklin, Samantha C.; Mariani, Rachel O.; Young, Emily N.; Kish, Rosalyn; Cathline, Kimberley A.; Robertson, Gavin P.; Martin, Adam R.

doi:10.20944/preprints202208.0547.v1

Cited by 2 publications

(1 citation statement)

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“…We collected LES and related trait and spectral reflectance data for six of the most common wine grape varieties-Cabernet Franc, Cabernet Sauvignon, Merlot, Pinot Noir, Sauvignon Blanc, Viognier-at the Niagara College Teaching Vineyard, Niagara-on-the-Lake, Ontario. The site is an operational vineyard characterized as non-irrigated, with imperfectly drained silty clays overlaying clay loam till mixed with poorly drained lacustrine heavy clay, and uniformly tilled and sprayed [48,49]. All trait and reflectance data were collected during the fruit setting stage (at our site, from June 6-17, 2022) between 6:00-12:00.…”

Section: Study Sitementioning

confidence: 99%

High throughput screening of Leaf Economics traits in six wine grape varieties

Cui,

Mariani,

Cathline

et al. 2023

Preprint

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Reflectance spectroscopy has become a powerful tool for non-destructive and high- throughput phenotyping in crops. Emerging evidence indicates that this technique allows for estimation of multiple leaf traits across large numbers of samples, while alleviating the constraints associated with traditional field- or lab-based approaches. While the ability of reflectance spectroscopy to predict leaf traits across species and ecosystems has received considerable attention, whether or not this technique can be applied to quantify within species trait variation have not been extensively explored. Employing reflectance spectroscopy to quantify intraspecific variation in functional traits is especially appealing in the field of agroecology, where it may present an approach for better understanding crop performance, fitness, and trait-based responses to managed and unmanaged environmental conditions. We tested if reflectance spectroscopy coupled with Partial Least Square Regression (PLSR) predicts rates of photosynthetic carbon assimilation (Amax), Rubisco carboxylation (Vcmax), electron transport (Jmax), leaf mass per area (LMA), and leaf nitrogen (N), across six wine grape (Vitis vinifera) varieties (Cabernet Franc, Cabernet Sauvignon, Merlot, Pinot Noir, Viognier, Sauvignon Blanc). Our PLSR models showed strong capability in predicting intraspecific trait variation, explaining 55%, 58%, 62%, and 64% of the variation in observedJmax,Vcmax, leaf N, and LMA values, respectively. However, predictions ofAmaxwere less strong, with reflectance spectra explaining only 29% of the variation in this trait. Our results indicate that trait variation within species and crops is less well-predicted by reflectance spectroscopy, than trait variation that exists among species. However, our results indicate that reflectance spectroscopy still presents a viable technique for quantifying trait variation and plant responses to environmental change in agroecosystems.

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Section: Study Sitementioning

confidence: 99%

High throughput screening of Leaf Economics traits in six wine grape varieties

Cui,

Mariani,

Cathline

et al. 2023

Preprint

Self Cite

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De Novo Transcriptome Assembly of Anoectochilus roxburghii for Morphological Diversity Assessment and Potential Marker Development

Zhang,

Chen,

Mei

et al. 2024

Plants

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Anoectochilus roxburghii is a rare and precious medicinal and ornamental plant of Orchidaceae. Abundant morphological characteristics have been observed among cultivated accessions. Our understanding of the genetic basis of morphological diversity is limited due to a lack of sequence data and candidate genes. In this study, a high-quality de novo transcriptome assembly of A.roxburghii was generated. A total of 138,385 unigenes were obtained, and a BUSCO (Benchmarking Universal Single-Copy Orthologs) analysis showed an assembly completeness of 98.8%. Multiple databases were used to obtain a comprehensive annotation, and the unigenes were functionally categorized using the GO (Gene Ontology), KOG (Eukaryotic Orthologous Groups), KEGG (Kyoto Encyclopedia of Genes and Genomes), and Nr databases. After comparing the phenotypic characteristics of five representative cultivars, a set of cultivar-specific, highly expressed unigenes was identified based on a comparative transcriptome analysis. Then, a WGCNA (Weighted Gene Co-expression Network Analysis) was performed to generate gene regulatory modules related to chlorophyll content (red) and sucrose synthase activity (black). In addition, the expression of six and four GO enrichment genes in the red and black modules, respectively, was analyzed using qRT-PCR to determine their putative functional roles in the leaves of the five cultivars. Finally, in silico SSR (Simple Sequence Repeat) mining of the assembled transcriptome identified 44,045 SSRs. Mononucleotide was the most dominant class of SSRs, followed by complex SSRs. In summary, this study reports on the phenomic and genomic resources of A. roxburghii, combining SSR marker development and validation. This report aids in morphological diversity assessments of Anoectochilus roxburghii.

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Intraspecific Leaf Trait Variation Across and Within Wine Grape Varieties

Cited by 2 publications

References 33 publications

High throughput screening of Leaf Economics traits in six wine grape varieties

High throughput screening of Leaf Economics traits in six wine grape varieties

De Novo Transcriptome Assembly of Anoectochilus roxburghii for Morphological Diversity Assessment and Potential Marker Development

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