Works matching AU Kicherer, Anna
Results: 27
Sensor application in grapevine breeding.
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- Berichte aus dem Julius Kühn-Institut, 2019, n. 204, p. 86
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Early detection of the grapevine disease Esca using hyperspectral sensors.
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- Berichte aus dem Julius Kühn-Institut, 2019, n. 204, p. 34
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Detection of grapevine characteristics using hyperspectral sensors.
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- 2017
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- Abstract
Grapevine berry wax: One trait supporting resilience to Botrytis cinerea.
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- 2017
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Detection of grapevine characteristics using hyperspectral sensors.
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- 2017
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Grapevine berry wax: One trait supporting resilience to Botrytis cinerea.
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- 2017
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Non-invasive phenotyping methods for abiotic and biotic stress in grapevine breeding.
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- 2016
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Development of methods for pre-symptomatic detection of grapevine diseases like esca, phytoplasmoses and viruses using hyperspectral sensors.
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- 2016
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NoViSys: Novel Viticulture Systems for sustainable production and products.
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- Berichte aus dem Julius Kühn-Institut, 2015, n. 181, p. 32
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Detection of Anomalous Grapevine Berries Using Variational Autoencoders.
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- Frontiers in Plant Science, 2022, v. 13, p. 1, doi. 10.3389/fpls.2022.729097
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Transcriptomic analysis of temporal shifts in berry development between two grapevine cultivars of the Pinot family reveals potential genes controlling ripening time.
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- BMC Plant Biology, 2021, v. 21, n. 1, p. 1, doi. 10.1186/s12870-021-03110-6
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A Concept Study for Feature Extraction and Modeling for Grapevine Yield Prediction.
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- Vitis, 2024, v. 63, p. 1, doi. 10.5073/vitis.2024.63.03
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PHENOquad: A new multi sensor platform for field phenotyping and screening of yield relevant characteristics within grapevine breeding research.
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- Vitis, 2023, v. 62, p. 41, doi. 10.5073/vitis.2023.62.special-issue.41-48
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Interactive Effects of Scion and Rootstock Genotypes on the Root Microbiome of Grapevines (Vitis spp. L.).
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- Applied Sciences (2076-3417), 2021, v. 11, n. 4, p. 1615, doi. 10.3390/app11041615
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Detection of Two Different Grapevine Yellows in Vitis vinifera Using Hyperspectral Imaging.
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- Remote Sensing, 2020, v. 12, n. 24, p. 4151, doi. 10.3390/rs12244151
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Detection of Grapevine Leafroll-Associated Virus 1 and 3 in White and Red Grapevine Cultivars Using Hyperspectral Imaging.
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- Remote Sensing, 2020, v. 12, n. 10, p. 1693, doi. 10.3390/rs12101693
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Determination of Sugars and Acids in Grape Must Using Miniaturized Near-Infrared Spectroscopy.
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- Sensors (14248220), 2023, v. 23, n. 11, p. 5287, doi. 10.3390/s23115287
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SmartSpectrometer—Embedded Optical Spectroscopy for Applications in Agriculture and Industry.
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- Sensors (14248220), 2021, v. 21, n. 13, p. 4476, doi. 10.3390/s21134476
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Phenoliner: A New Field Phenotyping Platform for Grapevine Research.
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- Sensors (14248220), 2017, v. 17, n. 7, p. 1625, doi. 10.3390/s17071625
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Towards Automated Large-Scale 3D Phenotyping of Vineyards under Field Conditions.
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- Sensors (14248220), 2016, v. 16, n. 12, p. 2136, doi. 10.3390/s16122136
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An Automated Field Phenotyping Pipeline for Application in Grapevine Research.
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- Sensors (14248220), 2015, v. 15, n. 3, p. 4823, doi. 10.3390/s150304823
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P28 - Using near-infrared spectroscopy to quantify quality-determining sugars and acids in grape must.
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- Julius-Kühn-Archiv, 2022, n. 470, p. 110
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P61 - Identification and functional annotation of candidate genes for the control of phenotypic differences between early and late ripening 'Pinot' cultivars.
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- Julius-Kühn-Archiv, 2022, n. 470, p. 143
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P32 - Improving high throughput sensor-based data acquisition of breeding material.
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- Julius-Kühn-Archiv, 2022, n. 470, p. 114
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Sensor based screening of yield relevant characteristics within grapevine breeding research.
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- Julius-Kühn-Archiv, 2022, n. 470, p. 32
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Evaluating the suitability of hyper- and multispectral imaging to detect foliar symptoms of the grapevine trunk disease Esca in vineyards.
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- Plant Methods, 2020, v. 16, n. 1, p. N.PAG, doi. 10.1186/s13007-020-00685-3
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Non-destructive quantification of key quality characteristics in individual grapevine berries using near-infrared spectroscopy.
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- Frontiers in Plant Science, 2024, p. 1, doi. 10.3389/fpls.2024.1386951
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- Article