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. 2025 Jun;18(2):e70018.
doi: 10.1002/tpg2.70018.

Genetic analysis of predicted vegetative biomass and biomass-related traits from digital phenotyping of strawberry

Cheryl Dalid  1 , Caiwang Zheng  2 , Luis Osorio  1 , Sujeet Verma  3 , Amr Abd-Elrahman  2 , Xu Wang  4 , Vance M Whitaker  1
Affiliations

Genetic analysis of predicted vegetative biomass and biomass-related traits from digital phenotyping of strawberry

Cheryl Dalid et al. Plant Genome. 2025 Jun.

Abstract

High-throughput digital phenotyping (DP) has been widely explored in plant breeding to assess large numbers of genotypes with minimal manual labor and reduced cost and time. DP platforms using high-resolution images captured by drones and tractor-based platforms have recently allowed the University of Florida strawberry (Fragaria × ananassa) breeding program to assess vegetative biomass at scale. Biomass has not previously been explored in a strawberry breeding context due to the labor required and the need to destroy the plant. This study aims to understand the genetic basis of predicted vegetative biomass and biomass-related traits and to chart a path for the combined use of DP and genomics in strawberry breeding. Aboveground dry vegetative biomass was estimated by adapting a previously published model using ground-truth data on a subset of breeding germplasm. High-resolution images were collected on clonally replicated trials at different time points during the fruiting season. There was moderate to high heritability (h2 = 0.26-0.56) for predicted vegetative biomass, and genetic correlations between vegetative biomass and marketable yield were mostly positive (rG = -0.13-0.47). Fruit yield traits scaled on a vegetative biomass basis also had moderate to high heritability (h2 = 0.25-0.64). This suggests that vegetative biomass can be decreased or increased through selection, and that marketable fruit yield can be improved without simultaneously increasing plant size. No consistent marker-trait associations were discovered via genome-wide association studies. On the other hand, predictive abilities from genomic selection ranged from 0.15 to 0.46 across traits and years, suggesting that genomic prediction will be an effective breeding tool for vegetative biomass in strawberry.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

FIGURE 1
FIGURE 1
Location of the phenomics trial used to develop the model to predict vegetative biomass in relation to the advanced selection trial where vegetative biomass was predicted and used in this study.
FIGURE 2
FIGURE 2
An example of strawberry plant growth curve where the solid red line is the fitted logistic curve, and the discrete blue points are the biomass estimated using machine learning methods. The green shaded area represents the accumulated biomass during the strawberry winter growing season, spanning from the initial to the final days of data collection.
FIGURE 3
FIGURE 3
Genetic correlations of predicted biomass and biomass‐related traits (BIO, predicted vegetative biomass; ACCB, accumulated predicted vegetative biomass; AWTB, average fruit weight on a predicted biomass basis; MYB, marketable fruit yield on a predicted biomass basis; AWTAC, average fruit weight on an accumulated predicted vegetative biomass basis; TMYAC, total marketable fruit yield on an accumulated predicted vegetative biomass basis) with yield and fruit traits (AWT, average weight; TMY, total marketable yield) during (a) the total season 2017–2018, (b) total season 2018–2019, (c) total season 2020–2021, and (e) total season 2021–2022. Early season showed similar trend as the total season. TMYB, total marketable yield on a predicted biomass basis.
FIGURE 4
FIGURE 4
Genome‐wide association studies (GWAS) analysis of predicted biomass during (a) the early season 2017–2018, (b) total season 2017–2018, (c) early season 2018–2019, and (d) total season 2018–2019 showing no consistent peaks across years.
FIGURE 5
FIGURE 5
Genome‐wide association studies (GWAS) analysis of accumulated biomass during (a) the total season 2020–2021 and (b) total season 2021–2022 showing no consistent peaks across years.
See this image and copyright information in PMC

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