ArticlePlant methods2015
HyperART: non-invasive quantification of leaf traits using hyperspectral absorption-reflectance-transmittance imaging.
Article in Plant methods, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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20 citing papers in PubMed, 210 citations in OpenAlex.
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- Light scattering in stacked mesophyll cells results in similarity characteristic of solar spectral reflectance and transmittance of natural leaves.Scientific reports · 2023Article
- Scientific and technological advances in the development of sustainable disease management tools: a case study on kiwifruit bacterial canker.Frontiers in plant science · 2023Review
- Growth, photosynthetic function, and stomatal characteristics of Persian walnut explantsFrontiers in plant science · 2023Article
- Classification of rice leaf blast severity using hyperspectral imaging.Scientific reports · 2022Article
- A Comprehensive Review of High Throughput Phenotyping and Machine Learning for Plant Stress Phenotyping.Phenomics (Cham, Switzerland) · 2022Review
- Plant trait measurement in 3D for growth monitoring.Plant methods · 2022Article
- Surveying soil-borne disease development on wild rocket salad crop by proximal sensing based on high-resolution hyperspectral features.Scientific reports · 2022Article
- Advanced high-throughput plant phenotyping techniques for genome-wide association studies: A review.Journal of advanced research · 2022Review
- Comprehensive evaluation of mapping complex traits in wheat using genome-wide association studies.Molecular breeding : new strategies in plant improvement · 2022Review
- Blue Light Improves Photosynthetic Performance during Healing and Acclimatization of Grafted Watermelon Seedlings.International journal of molecular sciences · 2021Article
- Technical workflows for hyperspectral plant image assessment and processing on the greenhouse and laboratory scale.GigaScience · 2020Review
- Exploring Deep Learning for Complex Trait Genomic Prediction in Polyploid Outcrossing Species.Frontiers in plant science · 2020Article
- Application of Remote Sensing for Phenotyping Tar Spot Complex Resistance in Maize.Frontiers in plant science · 2019Article
- A low-cost and open-source platform for automated imaging.Plant methods · 2019Article
- Improved classification accuracy of powdery mildew infection levels of wine grapes by spatial-spectral analysis of hyperspectral images.Plant methods · 2017Article
- Quantifying the Onset and Progression of Plant Senescence by Color Image Analysis for High Throughput Applications.PloS one · 2016Article
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCombined assessment of leaf reflectance and transmittance is currently limited to spot (point) measurements. This study introduces a tailor-made hyperspectral absorption-reflectance-transmittance imaging (HyperART) system, yielding a non-invasive determination of both reflectance and transmittance of the whole leaf. We addressed its applicability for analysing plant traits, i.e. assessing Cercospora beticola disease severity or leaf chlorophyll content. To test the accuracy of the obtained data, these were compared with reflectance and transmittance measurements of selected leaves acquired by the point spectroradiometer ASD FieldSpec, equipped with the FluoWat device.
resultsThe working principle of the HyperART system relies on the upward redirection of transmitted and reflected light (range of 400 to 2500 nm) of a plant sample towards two line scanners. By using both the reflectance and transmittance image, an image of leaf absorption can be calculated. The comparison with the dynamically high-resolution ASD FieldSpec data showed good correlation, underlying the accuracy of the HyperART system. Our experiments showed that variation in both leaf chlorophyll content of four different crop species, due to different fertilization regimes during growth, and fungal symptoms on sugar beet leaves could be accurately estimated and monitored. The use of leaf reflectance and transmittance, as well as their sum (by which the non-absorbed radiation is calculated) obtained by the HyperART system gave considerably improved results in classification of Cercospora leaf spot disease and determination of chlorophyll content.
conclusionsThe HyperART system offers the possibility for non-invasive and accurate mapping of leaf transmittance and absorption, significantly expanding the applicability of reflectance, based on mapping spectroscopy, in plant sciences. Therefore, the HyperART system may be readily employed for non-invasive determination of the spatio-temporal dynamics of various plant properties.
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