R-based workflow to estimate chilling requirements in multiple fruit tree genotypes using Partial Least Squares...

Area of Science:

• Horticulture and Plant Breeding
• Computational Biology
• Agroclimatology

Background:

• Accurate estimation of chilling requirements (CR) is crucial for breeding temperate fruit trees adapted to diverse agroclimatic conditions, especially with global warming.
• Partial Least Squares (PLS) regression, utilizing phenological and temperature data, is a suitable method for determining effective chill accumulation.
• Genotype-specific CR data is essential for selecting and breeding fruit trees for specific environments.

Purpose of the Study:

• To develop and present an R-based workflow for estimating genotype-specific chilling requirements (CR) in apricot (Prunus armeniaca L.) seedlings.
• To utilize the 'chillR' package and PLS regression for accurate CR assessment.
• To generate standardized datasets for downstream applications like QTL mapping and genotype selection.

Main Methods:

• An R-based workflow was developed using the 'chillR' package for R.
• Long-term phenological observations and temperature records were used.
• Partial Least Squares (PLS) regression was integrated to estimate genotype-specific CR for 282 apricot seedlings from two progenies.

Main Results:

• The workflow successfully determined genotype-specific CR for apricot seedlings.
• Standardized CR datasets were generated, suitable for QTL mapping and breeding.
• The R-based workflow streamlines CR estimation, reducing time and expertise needed.

Conclusions:

• The developed R-based workflow provides an efficient and accessible tool for estimating genotype-specific chilling requirements.
• This method supports informed breeding decisions and accelerates genetic research in temperate fruit trees.
• The workflow and data are publicly available, promoting wider application across temperate fruit species.