ArticleJournal of experimental botany2015
Utilization of a high-throughput shoot imaging system to examine the dynamic phenotypic responses of a C4 cereal crop plant to nitrogen and water deficiency over time.
Article in Journal of experimental botany, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers.
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79 citing papers in PubMed.
- Mulberry Drought Diagnosis: Integrating Proximal Sensing and Metabolomics for Remote Monitoring.Plants (Basel, Switzerland) · 2026Article
- Crop growth model-enabled genetic mapping of biomass accumulation dynamics in photoperiod-sensitive sorghum.The plant genome · 2025Article
- Advancing radiation-induced mutant screening through high-throughput technology: a preliminary evaluation of mutant screening in Arabidopsis thaliana.Plant methods · 2025Article
- Saline irrigation improves survival of forage sorghum but limits growth and increases toxicity.Plant biology (Stuttgart, Germany) · 2025Article
- Automatic optimization of regions of interest in hyperspectral images for detecting vegetative indices in soybeans.Frontiers in plant science · 2025Article
- Dhurrin in Sorghum: Biosynthesis, Regulation, Biological Function and Challenges for Animal Production.Plants (Basel, Switzerland) · 2024Review
- Improved Transformer for Time Series Senescence Root Recognition.Plant phenomics (Washington, D.C.) · 2024Article
- Enhancing the cultivation ofFrontiers in plant science · 2024Article
- Monitoring of drought stress and transpiration rate using proximal thermal and hyperspectral imaging in an indoor automated plant phenotyping platform.Plant methods · 2023Article
- Deciphering the Genetic Mechanisms of Salt Tolerance inPlants (Basel, Switzerland) · 2023Article
- High-throughput shoot phenotyping reveals temporal growth responses to nitrogen and inorganic and organic phosphorus sources in tomato.AoB PLANTS · 2023Article
- Field phenotyping for African crops: overview and perspectives.Frontiers in plant science · 2023Review
- Phenomics based prediction of plant biomass and leaf area in wheat using machine learning approaches.Frontiers in plant science · 2023Article
- Improved Salinity Tolerance-Associated Variables Observed in EMS Mutagenized Wheat Lines.International journal of molecular sciences · 2022Article
- Capturing crop adaptation to abiotic stress using image-based technologies.Open biology · 2022Review
- Seedling growth and fall armyworm feeding preference influenced by dhurrin production in sorghum.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022Article
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- Morphological and Physiological Traits Associated with Yield under Reduced Irrigation in Chilean Coastal Lowland Quinoa.Plants (Basel, Switzerland) · 2022Article
- Co-cultivation Approach to Decipher the Influence of Nitrogen-Fixing Cyanobacterium on Growth and N Uptake in Rice Crop.Current microbiology · 2022Article
19 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors.
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No grant is acknowledged in the PubMed record.
Abstract
The use of high-throughput phenotyping systems and non-destructive imaging is widely regarded as a key technology allowing scientists and breeders to develop crops with the ability to perform well under diverse environmental conditions. However, many of these phenotyping studies have been optimized using the model plant Arabidopsis thaliana. In this study, The Plant Accelerator(®) at The University of Adelaide, Australia, was used to investigate the growth and phenotypic response of the important cereal crop, Sorghum bicolor L. Moench and related hybrids to water-limited conditions and different levels of fertilizer. Imaging in different spectral ranges was used to monitor plant composition, chlorophyll, and moisture content. Phenotypic image analysis accurately measured plant biomass. The data set obtained enabled the responses of the different sorghum varieties to the experimental treatments to be differentiated and modelled. Plant architectural instead of architecture elements were determined using imaging and found to correlate with an improved tolerance to stress, for example diurnal leaf curling and leaf area index. Analysis of colour images revealed that leaf 'greenness' correlated with foliar nitrogen and chlorophyll, while near infrared reflectance (NIR) analysis was a good predictor of water content and leaf thickness, and correlated with plant moisture content. It is shown that imaging sorghum using a high-throughput system can accurately identify and differentiate between growth and specific phenotypic traits. R scripts for robust, parsimonious models are provided to allow other users of phenomic imaging systems to extract useful data readily, and thus relieve a bottleneck in phenotypic screening of multiple genotypes of key crop plants.
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