Federico Dicenta

In plant breeding and genetics, recent advances in high-throughput phenotyping are beginning to meet the growing demand for large-scale, high-quality phenotypic data that emerged after the development of next-generation sequencing technologies. Recent developments in phenomics have been incorporated into almond breeding programs, facilitating the large-scale acquisition of quantitative phenotypes and the dissection of the genetic architecture underlying morphological and quality-related traits. The implementation of a high-throughput phenotyping platform integrating RGB and hyperspectral imaging with genotyping using the 60K almond SNP array enabled the large-scale characterization of almond populations and the identification of 567 robust marker–trait associations across 66 traits. These analyses revealed two major genomic hotspots on chromosomes 2 and 5 associated with morphological and quality-related traits. These regions harbored biologically relevant candidate genes, including genes associated with OVATE family proteins, brassinosteroid signaling, protein ubiquitination, and acyl-CoA metabolism, as well as other regulators of organ growth, cell proliferation, hormone signaling, and seed development. Furthermore, a novel candidate gene encoding a COMT-like O-methyltransferase involved in lignin biosynthesis was identified and proposed to contribute to shell hardness, a major genetically controlled trait in almond. Together, these findings demonstrate the potential of integrating high-throughput phenomics and genomics to dissect complex traits, identify candidate genes, and accelerate genomics-informed breeding in almond.

Almond ( Prunus dulcis ) is a major nut crop with high genetic complexity due to its heterozygosity and self-incompatibility. In this study, genetic parameters for flowering and maturity time—two key complex traits in almond breeding—were estimated using classical methods (midparent-offspring regression and between/within family variance components) as well as a Bayesian linear mixed model. A comprehensive dataset from the CEBAS-CSIC Almond Breeding Program (CC-ABP), comprising over 17,500 individuals and more than 30 years of historical phenotypic records, was used to generate the first complete pedigree and evaluate trait inheritance. Narrow-sense and broad-sense heritability estimates were obtained, showing substantial variation across traits and methods, with the highest values derived from classical approaches. Bayesian mixed models, implemented via the MCMCglmm R package, allowed for the estimation of breeding values (EBVs), repeatability, and variance components under unbalanced data conditions. Repeatability estimates ranged from 0.15 to 0.56. EBVs were calculated for all individuals, including those without phenotypic records, enabling the construction of trait-specific rankings for early or late flowering and maturity. Reliability values were used to refine these rankings, improving the accuracy of parental selection. Genetic trends based on EBVs revealed changes in breeding objectives over time and highlighted the limited genetic progress achieved through phenotypic selection alone. The integration of the complete pedigree, EBVs, and trait rankings offers a robust framework to optimize crossing strategies. This work lays the groundwork for incorporating genomic selection into future almond breeding efforts, improving selection efficiency for traits of agronomic importance.

High-throughput phenotyping is addressing the current bottleneck in phenotyping within breeding programs. Imaging tools are becoming the primary resource for improving the efficiency of phenotyping processes and providing large datasets for genomic selection approaches. The advent of AI brings new advantages by enhancing phenotyping methods using imaging, making them more accessible to breeding programs. In this context, we have developed an open Python workflow for analyzing morphology and heritable morphometric traits using AI, which can be applied to fruits and other plant organs. This workflow has been implemented in almond (Prunus dulcis ), a species where efficiency is critical due to its long breeding cycle. Over 25,000 kernels, more than 20,000 nuts, and over 600 individuals have been phenotyped, making this the largest morphological study conducted in almond. As result, new heritable morphometric traits of interest have been identified. These findings pave the way for more efficient breeding strategies, ultimately facilitating the development of improved cultivars with desirable traits.

ISHS I International Symposium on Reproductive Biology of Fruit Tree Species Non-targeted metabolomics unveil ABA and ascorbic acid as two key molecules for endodormancy release in almond

The objective of this research was to quantify the concentration levels of the cyanogenic compounds, amygdalin and prunasin present in some varieties of almonds, considering their conversion to hydrocyanic acid, and their possible consumption in addition to other industrial uses, seeds of 29 commercial varieties were used of almond (Prunus dulcis Miller), evaluating its concentration and toxicity levels, taking into account the minimum degree of theoretical intake both for human consumption and for animals, through feed, this in terms of by-products. In addition, thermophysical properties thermophysical properties (thermal conductivity, thermal diffusivity, specific heat and density) and industrial uses were determined. The concentration was determined by chromatographic techniques (HPLC) and colorimetry (microdiffusion). The results obtained showed low levels of amygdalin from "not detected" to 375.40 mg/100 g of sample, depending on the sweet, slightly bitter and bitter varieties. The results indicate its possibility of commercialization, uses and applications in the food and pharmaceutical industry.

ISHS XI International Symposium on Apricot Culture PLUM POX VIRUS SITUATION IN MURCIA (SPAIN).

2483 almond seedlings developed from 42 crosses between 12 parents were studied for three years (1989, 1990 and 1991). General and specific combining ability was determined for six traits (all years) and eight traits (1989 only). Additive factors are largely responsible for the genetic control of all traits, non‐additive factors being of importance for the density of flowering and particularly for the density of production, time and duration of maturation and double kernels. The results permit the correct choice of parents and crosses for future breeding programmes and provide a better insight into the genetic control of the traits studied.