Biology subjects

Atkin, O. K.

Publications and source records attributed to Atkin, O. K..

4 recordsLinked to original sources

bioRxiv2026

Combining 3D-multispectral and hyperspectral imaging to identify environmental stress treatments imposed during plant growth

Non-invasive, high-throughput phenotyping tools are needed that can identify environmental effects on plant structure and function to diagnose factors responsible for reduced growth in commercial and non-commercial settings. In this study, we explored whether the integration of 3D-multispectral (3D) and 2D-hyperspectral imaging (HSI), aided by machine learning (ML), could be used to identify environmental stress treatments imposed during plant growth. Controlled environment-grown Nicotiana Benthamiana plants were subjected to a range of abiotic treatments - including different growth irradiances, heat treatment and drought stress - with the treatments resulting in differences in shoot height, biomass, leaf area and spectral reflectance. ML models were trained to identify these treatments using morphological and spectral traits measured at 27, 29, 31, and 34 days after sowing (DAS). A 3D-multispectral scanner was used to obtain information on plant height, biomass, and leaf area. A visible and near-infrared (VNIR) HSI camera provided detailed spectral information for deriving spectral indices including the Normalised Difference Vegetation Index (NDVI), Photochemical Reflectance Index (PRI) and Normalized Difference Red Edge (NDRE). Manual measurements provided baseline comparative data. The 3D-multispectral scanner reliably estimated above-ground traits, with high correlations between manual and scanner-derived measurements. The ML models accurately differentiated among environmental stress treatments, with the fused 3D+HSI model achieving the best overall predictive performance across all evaluated metrics compared with models based on either imaging modality alone. Results demonstrated the effectiveness of combining 3D-multispectral and 2D-HSI data with ML analyses for non-destructive, high-throughput phenotyping. The integration of these techniques enabled non-destructive, high-throughput identification of environmental stress treatments imposed during plant growth.

plant biology↗

bioRxiv2025

Wheat leaf dark respiration acclimates more strongly at night than in the day when responding to nocturnal warming

Rising night temperatures pose a significant threat to wheat productivity, yet the physiological basis of wheat adaptation to nocturnal warming remains poorly understood. We evaluated leaf photosynthetic and respiratory traits in ten Australian wheat cultivars released between 1901 and 2012 to warm nights under temperature-controlled environments. When exposed to warmer nights, rates of leaf net CO2 assimilation measured at 25 {degrees}C (Anet25) remained stable across cultivar release date despite declines in photosynthetic capacity (Vcmax and J1500) in newer cultivars. In most cultivars leaf respiratory CO2 release in the dark (Rdark) exhibited divergent thermal responses: warm nights suppressed temperature-normalised night Rdark (Rnight) but stimulated or maintained Rdark in the daytime (Rday). The results suggest that century-long, yield-focused selection may have inadvertently maintained Anet25 under warmer nights in modern cultivars through selection for more night-temperature sensitive but efficient photosynthetic capacity (i.e. greater return per protein investment) and overall reduced respiratory demand for maintenance of processes such as Rubisco protein turnover and synthesis. Our findings highlight trait-based targets for enhancing energy efficiency and climate resilience in wheat and opportunities to improve the parameterization of Rdark to warm nights in crop and Earth system models.

plant biology↗

bioRxiv2021

Wheat photosystem II heat tolerance responds dynamically to short and long-term warming

Heat-induced inhibition of photosynthesis is a key factor in declining wheat performance and yield. Variation in wheat heat tolerance can be characterised using the critical temperature (Tcrit) above which incipient damage to the photosynthetic machinery occurs. We investigated intraspecies variation and plasticity of wheat Tcrit under elevated temperature in field and controlled environment experiments. We also assessed whether intraspecies variation in wheat Tcrit mirrors patterns of global interspecies variation in heat tolerance reported for mostly wild, woody plants. In the field, wheat Tcrit varied through the course of a day, peaking at noon and lowest at sunrise, and increased as plants developed from heading to anthesis and grain filling. Under controlled temperature conditions, heat stress (36{degrees}C) was associated with a rapid rise in wheat Tcrit (i.e. within two hours of heat stress) that peaked after 3-4 days. These peaks in Tcrit indicate a physiological limitation to photosystem II heat tolerance. Analysis of a global dataset (comprising 183 Triticum and wild wheat (Aegilops) species) generated from the current study and a systematic literature review showed that wheat leaf Tcrit varied by up to 20{degrees}C (about two-thirds of reported global plant interspecies variation). However, unlike global patterns of interspecies Tcrit variation which has been linked to latitude of genotype origin, intraspecific variation in wheat Tcrit was unrelated to that. Yet, the observed genotypic variation and plasticity of wheat Tcrit suggests that this trait could be a useful tool for high-throughput phenotyping of wheat photosynthetic heat tolerance.

plant biology↗

bioRxiv2021

AusTraits: a curated plant trait database for the Australian flora

We introduce the AusTraits database - a compilation of measurements of plant traits for taxa in the Australian flora (hereafter AusTraits). AusTraits synthesises data on 375 traits across 29230 taxa from field campaigns, published literature, taxonomic monographs, and individual taxa descriptions. Traits vary in scope from physiological measures of performance (e.g. photosynthetic gas exchange, water-use efficiency) to morphological parameters (e.g. leaf area, seed mass, plant height) which link to aspects of ecological variation. AusTraits contains curated and harmonised individual-, species- and genus-level observations coupled to, where available, contextual information on site properties. This data descriptor provides information on version 2.1.0 of AusTraits which contains data for 937243 trait-by-taxa combinations. We envision AusTraits as an ongoing collaborative initiative for easily archiving and sharing trait data to increase our collective understanding of the Australian flora.

ecology↗