Biology subjects

Kronenberg, L.

Publications and source records attributed to Kronenberg, L..

10 recordsLinked to original sources

bioRxiv2026

From smartphone to gene: Automated image-based phenotyping captures flowering diversity of common buckwheat

Common buckwheat (Fagopyrum esculentum Moench) exhibits an indeterminate flowering habit, resulting in the simultaneous occurrence of flowering, seed development and seed ripening. This contributes to yield losses and complicates mechanized harvesting. Therefore, the development of varieties with a desirable flowering pattern is a breeding priority in buckwheat. However, phenotyping of buckwheat flowering under field conditions remains challenging because manual assessments are time consuming and expertise dependent. Here, we show that imaging devices such as smartphones or cameras can be used for phenotyping of flowering traits in a buckwheat collection encompassing 169 accessions. Flowering traits describing flowering time (n=10), flowering intensity (n=6) and abscission (n=6) were extracted from 37,078 images captured over five growing seasons using a Mask R-CNN segmentation model combined with statistical modelling of flowering dynamics. The 22 extracted traits were highly heritable (0.5 < h2 < 0.93) and correlated well (0.84 <r< 0.94) with manually assessed flowering stages while providing additional information on flowering intensity. Genome-wide association studies revealed 171 genomic regions associated with flowering traits, including marker-trait associations for agronomically important breeding targets. Candidate genes had functional annotations including "Auxin response factor" and "Ethylene-insensitive protein", gene families involved in hormone signalling and developmental regulation, controlling flowering in other species. These results demonstrate how digital imaging combined with automated feature extraction can be leveraged to gain insight on buckwheat flowering patterns in large scale field trials across different phenotyping platforms. This paves the way to breed for desired flowering patterns using molecular tools in a targeted manner.

plant biology↗

bioRxiv2026

Agronomic characterisation of a common buckwheat germplasm collection unlocks resources for genomics-assisted ideotype breeding

The mechanisation of agriculture has achieved major increases in labour productivity but has also led to an erosion of agrobiodiversity. Neglected and underutilized crops such as common buckwheat (Fagopyrum esculentum Moench) offer the potential to diversify food production systems but require major genetic improvement to compete with established crops. Although target traits for breeding such as more homogeneous ripening, reduced height, larger seeds and higher and more stable yields are well known, large-scale and field-based phenotyping data of diverse common buckwheat accessions across multiple environments are still scarce. Here, we tested the agronomic performance of a common buckwheat germplasm collection consisting of 170 accessions of diverse origin. The collection was tested at seven year-sites, and 19 agronomic traits related to phenology, growth habit and yield were assessed. Most traits showed high repeatability (0.31 < R2 < 0.98) and heritability (0.45 < H2 < 0.97), indicating genetic control of these traits. Coefficients of variation ranged between 6.19% and 46.15%, showing the high phenotypic diversity within the collection. By combining multiple traits, distinct ideotypes for different roles in the crop rotation were investigated, and accessions with promising agronomic profiles identified. Genome-wide association studies revealed marker-trait associations for 18 traits, allowing the identification of putative candidate genes influencing these traits such as a putative GRF-INTERACTING FACTOR associated with flowering time and biomass production. Our results show that the collection offers vast phenotypic diversity that can be exploited for the development of improved varieties tailored to meet specific agronomic purposes. The efficient utilization of these genetic resources should be supported by the application of genomics-based breeding approaches. The development of genetic markers and search for putative candidate genes mark important steps towards the establishment of efficient breeding schemes. Thus, these genomic resources provide a foundation for accelerating the genetic improvement of common buckwheat and developing agronomically competitive varieties.

plant biology↗

bioRxiv2025

Buying time - increasing yield potential in wheat by extending stem elongation duration

Extending the duration of the stem elongation (SE) phase between terminal spikelet (TS) and anthesis has often been proposed as an avenue to increase wheat yield. However, accurate determination of TS is labour intensive, and existing evidence is often based on a limited number of genotypes observed under controlled conditions. Here, a Buster x Charger population comprising 108 doubled haploid lines was grown across four year-sites under UK field conditions. TS was recorded through meristem dissection and SE duration was measured as the time between TS and ear emergence (EE). Mixed model analysis across year-sites revealed high heritabilities (H2yield = 0.66, H2TS = 0.93, H2SE = 0.89, H2EE = 0.95) and strong genetic correlations between yield and the phenology traits SE and EE (rg = 0.56 and rg = 0.6, respectively). While SE duration was mainly driven by EE, independent QTL for TS suggest that SE could be modified without affecting EE. The positive effect of SE duration on yield was attributed to increased grain number per area as well as increased grain weight, through independent QTL. Although validation in broader genetic backgrounds is needed, these QTL may offer opportunities for further yield increase in a physiological breeding framework. HighlightsO_LILonger stem elongation duration increases grain number. C_LIO_LILonger stem elongation duration increases grain weight. C_LIO_LIIndependent QTL suggest the timing of stem elongation as well as its effect on yield components may be independently selectable. C_LI

genetics↗

bioRxiv2024

The FIP 1.0 Data Set: Highly Resolved Annotated Image Time Series of 4,000 Wheat Plots Grown in Six Years

BackgroundUnderstanding genotype-environment interactions of plants is crucial for crop improvement, yet limited by the scarcity of quality phenotyping data. This data note presents the Field Phenotyping Platform 1.0 data set, a comprehensive resource for winter wheat research that combines imaging, trait, environmental, and genetic data. FindingsWe provide time series data for more than 4,000 wheat plots, including aligned high-resolution image sequences totaling more than 153,000 aligned images across six years. Measurement data for eight key wheat traits is included, namely canopy cover values, plant heights, wheat head counts, senescence ratings, heading date, final plant height, grain yield, and protein content. Genetic marker information and environmental data complement the time series. Data quality is demonstrated through heritability analyses and genomic prediction models, achieving accuracies aligned with previous research. ConclusionsThis extensive data set offers opportunities for advancing crop modeling and phenotyping techniques, enabling researchers to develop novel approaches for understanding genotype-environment interactions, analyzing growth dynamics, and predicting crop performance. By making this resource publicly available, we aim to accelerate research in climate-adaptive agriculture and foster collaboration between plant science and machine learning communities.

plant biology↗

bioRxiv2024

Velamins: the first green-light emitting class of wild-type Ca2+-regulated photoproteins isolated from the ctenophore Velamen parallelum

Ca2+-regulated photoproteins (CaPhs) consist of single-chain globular proteins to which coelenterazine, a widely distributed marine luminogenic substrate (the luciferin), binds along with molecular oxygen, producing a stable peroxide. Upon Ca2+ addition, CaPhs undergo conformational changes leading to the cyclization of the peroxide and the formation of a high-energy intermediate. Subsequently, its decomposition yields coelenteramide in an excited state and results in the emission of a flash of light. To date, all CaPhs reported produce blue light ({lambda}max 465-495 nm). Here, we report the cloning and functional characterization of a novel class of wild-type CaPhs capable of emitting green light: velamins, isolated from the bioluminescent ctenophore Velamen parallelum. Ten unique photoprotein-like sequences were recovered and grouped in three main clusters. Representative sequences were cloned, expressed, purified, and regenerated into the active His-tagged -, {beta}-, and {gamma}-velamins. Upon injection of a calcium-containing buffer into the velamin, a flash of green light ({lambda}max 500-508 nm) was observed across pH values ranging from 7 to 9. Whilst -velamin isoforms exhibited the highest light emission activity, {beta}- and {gamma}-velamins were found to be more thermostable at higher temperatures. Velamins are the only known wild-type Ca2+-regulated photoproteins that exhibit the longest wavelength in light emission, making them a promising model for studying spectral modulation. As a result, velamins hold potential for enhancing the sensitivity of signal detection in analytical systems, particularly when dealing with complex biological matrices.

biochemistry↗

bioRxiv2024

A genome-wide association study identifies markers and candidate genes affecting tolerance to the wheat pathogen Zymoseptoria tritici

Plants defend themselves against pathogens using either resistance, measured as the hosts ability to limit pathogen multiplication, or tolerance, measured as the hosts ability to reduce the negative effects of infection. Tolerance is a promising trait for crop breeding, but its genetic basis has rarely been studied and remains poorly understood. Here, we reveal the genetic basis of leaf tolerance to the fungal pathogen Zymoseptoria tritici that causes the globally important septoria tritici blotch disease on wheat. Leaf tolerance to Z. tritici is a quantitative trait that was recently discovered in wheat by using automated image analyses that quantified the symptomatic leaf area and counted the number of pycnidia found on the same leaf. A genome-wide association study identified four chromosome intervals associated with tolerance and a separate chromosome interval associated with resistance. Within these intervals, we identified candidate genes, including wall-associated kinases similar to Stb6, the first cloned STB resistance gene. Our analysis revealed a strong negative genetic correlation between tolerance and resistance to STB, indicative of a trade-off. Such a trade-off between tolerance and resistance would hinder breeding simultaneously for both traits, but our findings suggest a way forward using marker-assisted breeding. We expect that the methods described here can be used to characterize tolerance to other fungal diseases that produce visible fruiting bodies, such as speckled leaf blotch on barley, potentially unveiling conserved tolerance mechanisms shared among plant species.

plant biology↗

bioRxiv2023

Field phenotyping reveals the importance of including cultivar-specific per se temperature response in phenology modeling

Predicting plant development, a longstanding goal in plant physiology, involves two interwoven components: continuous growth and the progression of growth stages (phenology). Current models, like thermal time, assume species-level growth responses to temperature. We challenge this assumption, suggesting that cultivar-specific temperature responses significantly affect phenology. To investigate, we collected field-based growth and phenology data in winter wheat and soybean over multiple years. We used diverse models, from linear to neural networks, to assess growth responses to temperature at various trait and covariate levels. Cultivar-specific non-linear models best explained phenology-related cultivar-environment interactions. With cultivar-specific models, additional relations to other stressors than temperature were found. The availability of the presented field phenotyping tools allows incorporating cultivar-specific temperature response functions in future plant physiology studies, which will deepen our understanding of key factors that influence plant development. Consequently, this work has implications for crop breeding and cultivation under adverse climatic conditions.

physiology↗

bioRxiv2022

High-throughput field phenotyping reveals that selection in breeding has affected the phenology and temperature response of wheat in the stem elongation phase

Crop breeders increasingly need to mitigate the effects of climate change. Ideally, their selection strategies are based on an understanding of crop responses to environmental covariates such as temperature. In this study, the height of 352 varieties (European and Swiss) was repeatedly measured in multiple years. P-splines were used to model plant height as a function of time, from which the phenology parameters jointing (start) and end of stem elongation were derived. An asymptotic model was used to estimate the base-temperature of growth (Tmin), the steepness of the response (lrc), and the growth at optimum temperature (rmax). Parameter rmax had the largest effect on final height, whereas the temperature-response parameters in the narrow sense (Tmin, lrc) were closely connected to phenology. Final height and rmax decreased from the more continental, eastern European countries towards the more maritime, western countries. For genotypes registered in Great Bitain, Tmin was distinctly lower compared to most other regions. Integrating such analysis of in-season responsiveness to fluctuating environmental conditions in breeding will help to improve the genetic gain for climate adaptation. It can only be achieved based on high-throughput assessment of phenotypes in the field throughout the season. HighlightWheat phenology and environmental responses have been affected by breeders selections since 1970. High throughput field phenotyping methods reveal these developments, allowing to better adapt future varieties to climate change.

physiology↗

bioRxiv2021

A two-stage approach for the spatio-temporal analysis of high-throughput phenotyping data

High throughput phenotyping (HTP) platforms and devices are increasingly used for the characterization of growth and developmental processes for large sets of plant genotypes. Such HTP data require challenging statistical analyses in which longitudinal genetic signals need to be estimated against a background of spatio-temporal noise processes. We propose a two-stage approach for the analysis of such longitudinal HTP data. In a first stage, we correct for design features and spatial trends per time point. In a second stage, we focus on the longitudinal modelling of the spatially corrected data, thereby taking advantage of shared longitudinal features between genotypes and plants within genotypes. We propose a flexible hierarchical three-level P-spline growth curve model, with plants/plots nested in genotypes, and genotypes nested in populations. For selection of genotypes in a plant breeding context, we show how to extract new phenotypes, like growth rates, from the estimated genotypic growth curves and their first-order derivatives. We illustrate our approach on HTP data from the PhenoArch greenhouse platform at INRAE Montpellier and the outdoor Field Phenotyping platform at ETH Zurich.

genetics↗

bioRxiv2019

Temperature response of wheat affects final height and the timing of key developmental stages under field conditions

In wheat, temperature affects the timing and intensity of stem elongation (SE). Genetic variation for this process is therefore important for adaptation. This study investigates the genetic response to temperature fluctuations during SE and its relationship to phenology and height. Canopy height of 315 wheat genotypes (GABI wheat panel) was scanned twice weekly in the field phenotyping platform (FIP) of ETH Zurich using a LIDAR. Temperature response was modelled using linear regressions between SE and mean temperature in each measurement interval. This led to a temperature-responsive (slope) and a temperature-irresponsive (intercept) component. The temperature response was highly heritable (H2 = 0.81) and positively related to a later start and end of SE as well as final height. Genome-wide association mapping revealed three temperature-responsive and four temperature-irresponsive quantitative trait loci (QTL). Furthermore, putative candidate genes for temperature-response QTL were frequently related to the flowering pathway in A. thaliana, whereas temperature-irresponsive QTLs corresponded with growth and reduced height genes. In combination with Rht and Ppd alleles, these loci, together with the loci for the timing of SE accounted for 71% of the variability in height. This demonstrates how high-throughput field phenotyping combined with environmental covariates can contribute to a smarter selection of climate-resilient crops. HighlightWe measured ambient temperature response of stem elongation in wheat grown under field conditions. The results indicate that temperature response is highly heritable and linked to the flowering pathway.

plant biology↗