Dijkhuizen, R. F. | Search bioRxiv

bioRxiv2024

From aerial drone to QTL: Leveraging next-generation phenotyping to reveal the genetics of color and height in field-grown Lactuca sativa

In recent years, the automation of genotyping has significantly enhanced the efficiency of genome-wide association studies. As a result, phenotyping rather than genotyping is now the rate-limiting step, especially in field experiments. For this reason, there is a strong need to further automate in-field phenotyping. Here we present a 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 an unmanned aerial vehicle. Our high throughput phenotyping approach integrates an RGB camera, a multispectral camera to measure the reflectance at 5 wavelengths (blue, green, red, red edge, near-infrared), and precise height estimation. We used the mean and other descriptives such as median, quantiles, minimum and maximum to quantify different aspects of color and height variation in lettuce from the drone images. Using this approach, we confirm several previously described QTLs, now in populations grown under field conditions, and identify several new QTLs for plant-height and color.

plant biology↗

bioRxiv2023

A low-cost and open-source imaging platform reveals spatiotemporal insight into Arabidopsis leaf elongation and movement

Plant organs move throughout the diurnal cycle, changing leaf and petiole positions to balance light capture, leaf temperature and water loss under dynamic environmental conditions. Upward movement of the petiole, called hyponasty, is one of several traits of the shade avoidance syndrome (SAS). SAS traits are elicited upon perception of vegetation shade signals such as far-red light (FR) and improve light capture in dense vegetation. Monitoring plant movement at a high temporal resolution allows studying functionality, as well as molecular regulation of hyponasty. However, high temporal resolution imaging solutions are often very expensive, making this unavailable to many researchers. Here, we present a modular and low-cost imaging set-up, based on small Raspberry Pi computers, that can track leaf movements and elongation growth with high temporal resolution. We also developed an open-source, semi-automated image analysis pipeline. Using this setup we followed responses to FR enrichment, light intensity and their interactions. Tracking both elongation and angle of petiole, lamina and entire leaf revealed insight into R:FR sensitivities of leaf growth and movement dynamics, and its interactions with background light intensity. We also identified spatial separation in hyponastic response regulation for the petiole and the lamina of the leaf, depending on the light conditions.

plant biology↗