Which potential for Near Infrared Spectroscopy-based phenomic selection of grapevine rootstocks?
Abstract
Developing rootstocks adapted to environmental constraints constitutes a key lever for grapevine adaptation to climate change. In this context, Near Infrared Spectroscopy (NIRS) could be used as a high-throughput phenotyping technique to simplify the selection of rootstocks and predict their performance in grafted situations. This study is an exploratory analysis that aimed at evaluating the potential of NIRS spectra acquired ex- and in-situ in different tissues and stages of the vegetative cycle on ungrafted and grafted plants to reveal rootstock effects and their plasticity in response to scion/rootstock combination of to better characterize these interactions, and to predict phenotypes of grafted plants from data acquired on ungrafted material.
Through the study of 25 combinations (5 scions × 5 rootstocks), performed in 2023 in a dedicated experimental vineyard, we showed that NIRS obtained from ex-situ and in-situ measurements on scion tissues of grafted captured some rootstock and scion/rootstock interaction signals (up to 20% of the total variance at specific wavelengths). Yet, the scion effect on the spectra remains dominant over the rootstock effect, which is also the case for agronomic traits measured in the same experimental vineyard. Using NIRS data collected ex-situ on dried leaves, spectral wavelengths specific to the rootstock effect could be identified.
Predictions at the plant level were carried out on twenty-eight phenotypic traits recorded over several seasons (2019-2022), showed variable predictive abilities (0.2 to 0.8) between traits, those related to all phenological stages recorded in 2023 and pruning weight in 2021 and 2022, being the best predicted. For NIRS data collected on dried leaves, three spectral regions were consistently identified as contributing to predictions and to differences between scion/rootstock combinations. No significant difference was detected in the prediction ability between the whole spectrum and these specific regions for their predictive ability. Considering these promising findings, NIRS data have been collected similarly on leaves of a non-grafted and grafted progeny (as rootstocks). Their predictive ability will be tested, and preliminary results will be presented during the conference.
Issue: GBG 2026
Type: Oral
Authors
1 INRAE
2 Bordeaux Sciences Agro
3 IFV
4 Hennessy