Belgium

Traditional plant phenotyping for physiology, morphology, chemical composition and plant or seed biomass is labor-intensive and difficult to scale up. Like other scientific fields, it has benefited from automation, both in controlled environments and in the field. For practical reasons – particularly the need to handle the large numbers of plants required for genetic analysis - choices generally have been to measure plants fast and non-destructively. As a result, the traits being measured have shifted from ‘hard-core variables’ such as CO2  uptake rates or total plant biomass, to proxies like fluorescence or digital biomass. In this talk, I will discuss some of the implications of this shift for interpretating experimental results.
Another challenge is the gap that often exists between results obtained in controlled conditions and those observed in the field. This issue becomes even more pressing when using expensive high-throughput phenotyping equipment.  Addressing this discrepancy requires greater attention from the phenotyping community. We will also explore strategies to bridge this gap.

SEB Conference 2025

Exploring avenues to increase the relevance of high-throughput plant phenotyping

high-throughput plant phenotyping

growth conditions

We are pleased to announce the Fortieth AAAI Conference on Artificial Intelligence (AAAI-26), which will be held in Singapore EXPO from January 20 to January 27, 2026.

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AAAI 2026

We are pleased to announce the Fortieth AAAI Conference on Artificial Intelligence (AAAI-26), which will be held in Singapore EXPO from January 20 to January 27, 2026.

technical paper

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Latitudinal patterns in fitness-related traits within species are getting increased attention as these inform how high-latitude populations may evolve in response to global warming. The underlying mechanisms for these latitudinal trait patterns remain poorly understood, and recently the gut microbiome has been suggested to be a potentially important proximate driver of these patterns. We investigated the novel idea whether the gut microbiome drives differences in immune function and pathogen load between slow-paced, Southern Swedish, high-latitude and fast-paced, Southern French, low-latitude populations of Ischnura elegans damselflies. A reciprocal gut microbiome transplant was performed between high- and low-latitude larvae, at both a colder and warmer thermal regime, whereafter larvae were exposed to Escherichia coli , a pathogen naturally found in aquatic ecosystems. During the experiment, larval mortality, growth rate, phenoloxidase level (a measure of immune function), E. coli burden (a measure of pathogen load), and the gut microbiome diversity (α-diversity) and community compositions (β-diversity) were analysed. Exposure to the pathogen increased mortality, especially under warming. Our results confirmed latitude-associated thermal adaptation and a faster pace-of-life of the low-latitude larvae, and revealed this to be associated with a lower immune function and higher pathogen load. Moreover, our results provided the first experimental evidence that the gut microbiome causally contributed to latitudinal differences in the host’s immune function and pathogen load. Taking into account how the gut microbiome shapes latitudinal patterns in fitness-related traits will deepen our understanding of the evolution of host populations under warming.

The gut microbiome shapes latitudinal differences in host immunity and pathogen load, and buffers against immunosuppression under future warming

The pace-of-life hypothesis predicts that intrinsic traits such as rates of metabolism and growth influence behaviour, with high-metabolism individuals expected to be bolder, more aggressive, and more exploratory. These behavioural tendencies may increase predation risk by driving individuals to forage in riskier habitats. We tested this hypothesis in a freshwater fish community by integrating metabolic assays, growth analysis, stable isotope analysis, and acoustic telemetry. Using lakeside intermittent flow respirometry, we measured routine metabolic rate (RMR) as a proxy for baseline energy expenditure. Using biopsy, we back-calculated individual rates of growth and quantified stable isotope ratios (δ13 C and δ15 N) to infer diet composition and trophic position. Fish were then implanted with predation-sensing acoustic transmitters to track movement, habitat use, and predation events in a whole-lake acoustic positioning system (Ontario, Canada). The lake was divided into habitat zones (e.g., open water, vegetated shallows, nearshore areas) to assess how individuals used risky versus safe habitats. We studied prey species (bluegill Lepomis macrochirus, pumpkinseed Lepomis gibbosus) and a predator (largemouth bass Micropterus salmoides) to characterize metabolic-behavioural syndromes and their links to diet, growth, movement, and survival. This research rigorously tests the pace-of-life hypothesis and may inform conservation efforts by identifying traits that increase vulnerability to predation and environmental change.

Predicting the behaviour of wild fish using metabolism, growth, and diet

A prominent feature of biodiverse habitats is the acoustic landscape. Yet very little is known about the acoustic landscapes of extinct environments, for example of a Jurassic Forest. One problem is that recovering the real acoustic features of extinct tetrapods is challenging, as their vocal organs do not readily fossilize. Conversely, the stridulating organs present in the sclerotised cuticle of some arthropods do fossilise well. For example, the stridulatory structures (a file, plectrum, and sound radiating membranes) in the forewings of male crickets and katydids are preserved in fossils, offering a unique opportunity to investigate species diversification and the acoustic landscapes of the past. Integrating experimental and numerical procedures, several katydid fossils (of nine species) were studied to recreate the acoustic landscape of the mid Jurassic (Inner Mongolia, China). Wing vibration and calling songs of these fossils were recovered and validated. Jurassic katydids used sharp pure-tones (musical) calls, which made localization by eavesdropping predators difficult. While 60% of these species communicate in the low audio range 5-7 kHz, one species exploited ultrasounds (>20kHz). Results imply that ultrasonic communication in insects was established long before the emergence of bats. The results extend current understanding of the Jurassic soundscape, revealing insect song and hearing diversity, but also highlighting the co-evolutionary pressures and constraints exerted by ultrasound sensitive eavesdropping insectivorous predators other than bats. Such arm race is proposed as one of the main pressures that boosted the evolution of the mammalian cochlea and the sophisticated ‘insect cochlea’ shown by living katydids.

The reconstruction of an extinct Jurassic soundscape

Jumping represent one of the most widely used modes of locomotion in the animal kingdom. However, this does not mean that the characteristics of jumps are universal; there are many different ways in which jumps are powered (actuated). In orthopterans there are two main methods of actuation; direct muscle actuation and latch mediated spring actuation. It has previously been suggested that spring actuated systems provide propulsive power to an animal, which in turn generates incredibly fast jumps. Clown hoppers (Eumastacidae) are a group of south American grasshopper which use their spring actuated laterally projected legs to achieve jump speeds of up to 3.1 m/s. Similar to the muscle actuated group of arboreal orthopterans (Phlugidini), the clown hopper will perform targeted jumps, although the level of control which they employ is less fine tuned. When clown hoppers are presented with 3 different overhead target heights (50 mm, 75 mm and 100 mm), there was a significant difference between the linear velocity (m/s) at take-off with jump speed increasing as target height increases. However, whilst there was a generalised decrease in angular velocity (rad/s), this was not significant suggesting that whilst the hoppers can control the extent to which the spring in their legs powers the jumps (represented by the proportionate change in speed of the jumps), the ability to control jump rotation at different heights remains obscure.

Introducing the Monkey Grasshopper, a spring-powered jumper with the ability to control its linear velocity

The clade of boxfish (Ostraciidae and Aracanidae) are reef-dwelling fish that share a unique feature, the carapace. The body of Ostraciidae is completely covered by a bony shell of fused hexagonal plates. In Aracanidae, the carapace also covers the body, but is not completely closed at the caudal peduncle for some of the species. The carapace provides protection against predators, but its shape also defines their hydrodynamic characteristics. Among the many extant species, shapes vary between boxes with major lateral keels, over wedges with dorsal and ventrolateral keels, to more disc-like shapes with major dorsoventral keels. Here, we studied how hydrodynamic performance differs among twenty-nine species of boxfish. Drag forces and pitch and yaw moments were calculated using computational fluid dynamics simulations based on 3D laser-scans of museum specimens, which were all digitally rescaled to the same carapace volume. Up to 40% difference was observed between boxfish species with the lowest drag force and those with the highest drag force. We determined that Aracanidae have a significantly higher drag force than Ostraciidae. Additionally, we found a strong positive correlation between drag force and frontal-projected area and a negative correlation between drag force and carapace length. The strong variability in drag force related to the degree of axial compression of boxfish shapes, together with the relatively high coefficients of drag in boxfish in general, suggests that weak selection pressures on drag-reduction are common in this group.

Variation in hydrodynamic performance among boxfish carapace shapes

In aquatic ecosystems, the growth and physiology of species are profoundly influenced by trophic interactions and environmental conditions, especially light and food sources. Daphnids, commonly known as water fleas, have a central role in freshwater ecosystems due to their wide distribution, crucial position in food webs, and sensitivity to environmental changes. In this study, we focused on the impact of food quality and light conditions on lifespan, growth, reproduction, and metabolic responses of daphnids. Frozen algae food is a less nutritious source that led to slower growth, reduced reproduction, and induced metabolic restrictions, while deprivation of light induced distinct metabolic changes, suggesting disruptions in circadian rhythms. These changes point to potential impacts on broader ecological interactions and metabolic efficiency.
Our research highlights the importance of food quality and light in shaping aquatic organisms’ physiology, providing insights into the ecological and metabolic processes that govern freshwater species. The study’s results could inform broader ecological models and risk assessments, emphasising the interconnectedness of environmental factors on aquatic species' health and ecosystem dynamics.

Molecular approaches unravel the impact of food quality and light on the physiology of daphnids 

Per- and polyfluoroalkyl substances (PFAS), widely used in industries and consumer products, often contaminate marine environments, posing potential risks to wildlife and humans. Their bioaccumulation and toxicity have led to global concern, particularly with the emergence of short-chain PFAS as alternatives to restricted legacy compounds. However, limited information exists on their environmental fate and toxicity, necessitating further research on their effects on marine organisms, particularly bivalves.
This study investigates the toxicity of six PFAS (short-chain: PFHxA, 6:2 FTA; long-chain: PFUnDA, PFDoA, PFTriDA, PFTeDA) in the digestive gland (DG) and gills (G) of Mytilus galloprovincialis, a key bioindicator, through in vitro exposure. To understand early toxicity mechanisms, biochemical responses related to oxidative stress and neurotransmission were assessed.
The results indicated organ-specific effects, with the DG demonstrating heightened sensitivity to PFHxA, evidenced by a reduction in total antioxidant capacity. Conversely, PFTriDA exhibited a propensity to induce cellular damage at elevated concentrations. Gills exhibited a heightened response to PFDoA and PFTeDA, manifesting as the inhibition of antioxidant enzymes resulting in oxidative stress. Additionally, PFHxA and PFTriDA were observed to exert neurotoxic effects through the inhibition of acetylcholinesterase. Among all compounds, 6:2 FTA was the least toxic, while PFHxA was the most toxic.
These findings highlight the complexity of PFAS toxicity and the need to assess short- and long-chain compounds to establish safe environmental thresholds. M. galloprovincialis proves to be a valuable bioindicator, reinforcing the need for regulatory measures to mitigate PFAS pollution while providing insights into organ-specific toxicity and environmental exposure pathways.

Revealing Hidden Risks: In Vitro Analysis of PFAS Hazards in Mytilus galloprovincialisGills and Digestive Gland

Arbuscular mycorrhizal fungi (AM fungi) may facilitate plants during increasingly prevalent extreme stress events such as heatwaves and drought. Heatwaves are commonly characterised by the presence of extreme temperatures and frequently co-occur with droughts or water deficits. The combination of these stressors is deleterious for plants and the role of AM fungi in ameliorating this compound stress event is not fully understood, particularly within threatened communities such as grasslands. This study has investigated the role of field-collected AM fungi in facilitating plant responses to heat and water stress using a simulated heatwave event in a factorial greenhouse experiment to test how native grassland species respond. We found that the impact of heat stress combined with water stress on plant performance was shown to be greater than the additive effects of heat and water stress in isolation. AM fungi was shown to have variable influences on plant growth, fitness, and physiological responses but these influences were commonly at odds with previous publications on AM fungi with agricultural species. Most notably, AM fungi increased the germination success of seeds of one species grown following exposure to climate stress. The results of this study highlight the dynamic role of AM fungi and help us understand grassland responses to heatwave events in the face of increasing extreme climate events. Furthermore, this study emphasises the importance of building ecologically relevant ex-situ experiments to study and understand current global pressures facing natural ecological communities.

Interactions of Arbuscular Mycorrhizal Fungi with Native Grassland Species Under Combined Heat and Water Stress

Optimizing radiation use efficiency (RUE) is essential for increasing wheat crop yields. Conventional RUE measurements rely on the dynamics of above-ground biomass (AGB) and intercepted photosynthetic active radiation (IPAR). It therefore suffers from low throughput, hindering large-scale phenotyping of RUE for crop improvement. In this study, we propose a high-throughput phenotyping method utilizing multi-view RGB cameras to estimate RUE in wheat crops in the field. Initially, a deep semantic segmentation model assesses the green fraction (GF) from zenith angle 0° and 45° RGB images, denoted as GF(0°) and GF(45°). Subsequently, employing the digital plant phenotyping platform from our prior work, we generate a synthetic dataset with 10,000 simulations, including GF(0°) and GF(45°), along with the corresponding green area index (GAI) and fraction of intercepted PAR (FIPAR). This synthetic dataset facilitates training a Gaussian Process Regression model to estimate GAI and FIPAR based on GF(0°) and GF(45°). Consequently, the accumulation of intercepted PAR is computed from FIPAR dynamics, and AGB is estimated from GAI using the allometric growth law developed in our previous work. Finally, RUE is estimated by fitting a linear regression between biomass dynamics and accumulated IPAR. Our high-throughput phenotyping method for RUE was implemented on a wheat population exceeding 500 genotypes across three sites. This approach successfully identified key genes strongly associated with the photosynthetic process, validating the reliability of our algorithm. In summary, our algorithm, requiring observations from only two RGB cameras, significantly enhances feasibility and throughput for application in wheat breeding programs.

High-Throughput Phenotyping the Radiation Use Efficiency of Wheat Crops in the Field

Tomato (Solanum lycopersicum) is among the world’s most important crops, yet its cultivation is increasingly threatened by climate change. Traditional destructive analyses can accurately classify stress symptoms, but novel Artificial Intelligence driven approaches offer promising solutions for early abiotic stress detection through computer vision. This study integrates image-derived traits with laboratory-based physiological parameters within a machine learning framework to classify, identify, and quantify the responses of two dwarf tomato cultivars (Microtom and Tiny Tim) under long-term drought and salinity conditions, at increasing intensities. RGB and PAM chlorophyll fluorescence imaging were combined with biochemical assays, including pigment content (chlorophylls and carotenoids), malondialdehyde (MDA) content, relative water content (RWC), and electrolyte leakage (EL). Notably, color indices exhibited significant shifts in pixel distribution peaks across treatments, highlighting their sensitivity to stress-induced physiological changes. Moreover, cultivar-specific differences at 7 and 14 Days After Stress (DAS) suggested genetic variability in stress responses. Based on these multi-source features, various decision tree-based models were trained, tested, and evaluated. The binary presence/absence classifier achieved the highest accuracy (precision=0.87, recall=0.97, F-measure=0.92), outperforming more complex models designed to differentiate and quantify stressors. As classification complexity increased, image-derived features—particularly geometrical (e.g., area, perimeter), colorimetric (e.g., chroma indices), and fluorescence-based traits (e.g., NPQ)—became more influential, while laboratory-derived attributes (e.g., RWC) had reduced importance. These findings underscore the potential of digital traits as reliable, non-destructive indicators for early stress monitoring in tomato plants. Future research will refine and generalize this AI-based framework to enhance its robustness, scalability, and applicability in field studies.

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