Rapid identification of boron-tolerant grapevine rootstocks via leaf spectroscopy

Authors: LUPO, YANIV - University Of California, Davis; SHARMA, SADIKSHYA - University Of California, Davis; MUNOZ, JOSE - University Of California, Davis; NUNEZ, VERONICA - University Of California, Davis; GASPAR, ANA - University Of California, Davis; McElrone, Andrew; DIAZ-GARCIA, LUIS - University Of California, Davis

Submitted to: OENO One
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/12/2025
Publication Date: 10/6/2025
Citation: Lupo, Y., Sharma, S., Munoz, J.R., Nunez, V., Gaspar, A., McElrone, A.J., Diaz-Garcia, L. 2025. Rapid identification of boron-tolerant grapevine rootstocks via leaf spectroscopy. OENO One. Volume 59, No. 4 (2025). https://doi.org/10.20870/oeno-one.2025.59.4.9336.
DOI: https://doi.org/10.20870/oeno-one.2025.59.4.9336

Interpretive Summary: Boron (B) toxicity is a problem in some California growing regions, and decreases grapevine performance, yields and fruit quality. We screened a range of commercial grapevine rootstocks and wild Vitis germplasm under of range of B soil treatments. We measured B levels, water loss, photosynthesis and reflectance in leaves to identify B-tolerant plant rootstocks. Our results revealed substantial variation in B exclusion, with some genotypes maintaining low leaf B content despite high applied concentrations. Vegetation indices from hyperspectral reflectance data indicated that B stress reduces chlorophyll levels and may induce carotenoid accumulation, which would protect photosynthetic machinery in tolerant genotypes. This work demonstrates the value of hyperspectral measurements for high-throughput screening, allowing breeders to rapidly identify B-tolerant rootstocks.

Technical Abstract: Boron is an essential micronutrient for grapevine growth, yet excessive levels can impair photosynthesis, reduce yields, and diminish fruit quality. This study evaluated the potential of leaf spectroscopy combined with machine learning to identify boron-tolerant rootstocks rapidly and cost-effectively. We screened both commercial grapevine rootstocks and wild Vitis germplasm under boron treatments ranging from 0.5 to 8 ppm, measuring leaf boron accumulation, stomatal conductance, photosystem II efficiency, and leaf reflectance. The results revealed substantial genotypic variation in boron exclusion, with some genotypes maintaining low leaf boron concentration despite high substrate concentrations. Classification models (partial least squares discriminant analysis and random forest classification) outperformed regression models (partial least squares regression and random forest regression) in distinguishing boron-excluding genotypes, achieving 68 % to 79 % accuracy within just eight days after stress initiation. Reflectance-based vegetation indices such as the Normalized Difference Vegetation Index, Photochemical Reflectance Index, Structure Insensitive Pigment Index, and Chlorophyll Index indicated that boron stress reduces chlorophyll levels and may induce carotenoid accumulation, suggesting a photosynthetic tolerance mechanism. Although quantitative prediction of leaf boron concentration proved more challenging, simulations showed that even modest prediction accuracies (~60 %) can substantially boost genetic gains if larger populations are screened and selection intensities are increased. These findings underscore the value of leaf spectroscopy for high-throughput phenotyping, allowing breeders to rapidly identify and advance boron-tolerant rootstocks.