From aerial drone to quantitative trait locus: leveraging next-generation phenotyping to reveal the genetics of color and height in field-grown Lactuca sativa.

Abstract

In recent years, accurate and low-cost variant calling has enabled the genotyping of large diversity panels for genome-wide association studies. As a result, phenotyping rather than genotyping is now the rate-limiting step, especially in field experiments. This has created a strong need for high-throughput, accurate, and low-cost in-field phenotyping. Here, we present a genome-wide association study (GWAS) study on 194 field-grown accessions of lettuce (Lactuca sativa). These accessions were non-destructively phenotyped at two time points 15 days apart using a drone equipped with an RGB and multispectral (MSP) camera. Our high-throughput phenotyping approach integrates an RGB- and MSP camera to measure the color and height of lettuce in this large-scale field experiment. We used the mean and other summary statistics, such as median, quantiles, skewness, kurtosis, minimum, and maximum to quantify different aspects of color and height variation in lettuce from the drone images. Using these summary statistics as traits for GWAS, we confirm several previously described genetic associations, now under field conditions, and identify additional novel associations for color and height traits in lettuce.

Code and data availability

The paper's authors publicly deposited their image processing, GWAS, and figure scripts on GitHub (SnoekLab/Dijkhuizen_etal_2025_Drone) and all raw/intermediate phenotyping data (including weather data) at a UU Yoda DOI (10.24416/UU01-S5FCM9). Both are paper-specific, public, and actionable.