ArticleFrontiers in plant science2019
Image-Derived Traits Related to Mid-Season Growth Performance of Maize Under Nitrogen and Water Stress.
Article in Frontiers in plant science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Article
- Evaluation of barley genotypes for drought adaptability: based on stress indices and comprehensive evaluation as criteria.Frontiers in plant science · 2024Article
- Engaging Precision Phenotyping to Scrutinize Vegetative Drought Tolerance and Recovery in Chickpea Plant Genetic Resources.Plants (Basel, Switzerland) · 2023Article
- Multivariate Interaction Analysis ofPlants (Basel, Switzerland) · 2023Article
- Defining growth requirements of microgreens in space cultivation via biomass production, morpho-anatomical and nutritional traits analysis.Frontiers in plant science · 2023Article
- Phenotyping ofPlant phenomics (Washington, D.C.) · 2023Article
- Article
- Image-based phenotyping of cassava roots for diversity studies and carotenoids prediction.PloS one · 2022Article
- Dynamics of Maize Vegetative Growth and Drought Adaptability Using Image-Based Phenotyping Under Controlled Conditions.Frontiers in plant science · 2021Article
- High-Throughput Phenotyping for Revealing Key Morpho-Physiological Traits for Drought Tolerance in Pea (Pisum sativum and Wild Relatives).Physiologia plantarumArticle
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10 authors.
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Abstract
Phenotypic measurements under controlled cultivation conditions are essential to gain a mechanistic understanding of plant responses to environmental impacts and thus for knowledge-based improvement of their performance under natural field conditions. Twenty maize inbred lines (ILs) were phenotyped in response to two levels of water and nitrogen supply (control and stress) and combined nitrogen and water deficit. Over a course of 5 weeks (from about 4-leaf stage to the beginning of the reproductive stage), maize phenology and growth were monitored by using a high-throughput phenotyping platform for daily acquisition of images in different spectral ranges. The focus of the present study is on the measurements taken at the time of maximum water stress (for traits that reflect plant physiological properties) and at the end of the experiment (for traits that reflect plant architectural and biomass-related traits). Twenty-five phenotypic traits extracted from the digital image data that support biological interpretation of plant growth were selected for their predictive value for mid-season shoot biomass accumulation. Measured fresh and dry weights after harvest were used to calculate various indices (water-use efficiency, physiological nitrogen-use efficiency, specific plant weight) and to establish correlations with image-derived phenotypic features. Also, score indices based on dry weight were used to identify contrasting ILs in terms of productivity and tolerance to stress, and their means for image-derived and manually measured traits were compared. Color-related traits appear to be indicative of plant performance and photosystem II operating efficiency might be an importance physiological parameter of biomass accumulation, particularly under severe stress conditions. Also, genotypes showing greater leaf area may be better adapted to abiotic stress conditions.
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