Dissecting foliar physiology and chemical properties with integrated highthroughput phenotyping and molecular markers in grape improvement

Authors

  • Ugochukwu Ikeogu Cornell University, Cornell AgriTech, Horticulture Section, Geneva, NY, USA
  • Kaitlin M. Gold Cornell University, Cornell AgriTech, Plant Pathology & Plant-Microbe Biology Section, Geneva, NY, USA
  • John Couture Purdue University, Depts of Entomology and Forestry and Natural Resources, West Lafayette, IN, USA
  • Nikita Gambhir Cornell University, Cornell AgriTech, Plant Pathology & Plant-Microbe Biology Section, Geneva, NY, USA
  • Robetauli Simangunsong Cornell University, Cornell AgriTech, Plant Pathology & Plant-Microbe Biology Section, Geneva, NY, USA
  • Surya Sapkota Cornell University, Cornell AgriTech, Plant Pathology & Plant-Microbe Biology Section, Geneva, NY, USA
  • Michael Colizzi Cornell University, Cornell AgriTech, Horticulture Section, Geneva, NY, USA
  • Lance Cadle-Davidson Cornell University, Cornell AgriTech, Plant Pathology & Plant-Microbe Biology Section, Geneva, NY, USA; USDA-ARS, Grape Genetics Research Unit, Geneva, NY, USA
  • Bruce I. Reisch Cornell University, Cornell AgriTech, Horticulture Section, Geneva, NY, USA

DOI:

https://doi.org/10.5073/vitis.2023.62.special-issue.37-40

Keywords:

Grapes, foliar, chemical composition, breeding, high-throughput phenotyping, hyperspectral, QTL

Abstract

An advanced phenotyping protocol using a hyperspectral spectrometer to better understand foliar chemical composition and physiological processes in relation to grapevine yield, quality, biotic and abiotic resistance was initiated with in-house and public spectral resources. The initial result for foliar pigments calibration was promising for classification and measurements to support breeding. We demonstrated the potential of adapting public spectral resources in supporting modern phenotyping in programs with limited resources and when combined with our current effort in deploying marker-assisted selection, the dual innovations provide new information to fast-tracking grapevine research and trait improvement.

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Published

2023-10-31

Issue

Vol. 62 (2023): Vitis (Special Issue)

Section

Article

License

Copyright (c) 2023 The Author(s)

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