News from scientific literature

Barley biomass accumulation

Researchers at the IPK Gatersleben analysed biomass accumulation in barley using a LemnaTec Greenhouse Scanalyzer. Phenotypic data delivered information on temporal patterns and genetic architecture underlying the biomass accumulation.

Neumann, Kerstin; Zhao, Yusheng; Chu, Jianting; Keilwagen, Jens; Reif, Jochen C.; Kilian, Benjamin; Graner, Andreas (2017): Genetic architecture and temporal patterns of biomass accumulation in spring barley revealed by image analysis. In: BMC plant biology 17 (1), S. 137. DOI: 10.1186/s12870-017-1085-4.


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Nature Plants published a paper on research infrastructures authored by Jacques Roy, François Tardieu, Michèle Tixier-Boichard and Ulrich Schurr, pointing out the importance of phenotyping for the development of agricultural innovations that meet future demand of food and bio-based materials.

Roy, Jacques; Tardieu, François; Tixier-Boichard, Michèle; Schurr, Ulrich (2017): European infrastructures for sustainable agriculture. In: Nature Plants 3 (10), S. 756–758. DOI: 10.1038/s41477-017-0027-3.


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Einsatz von Laserscannern in der Hochdurchsatzphänotypisierung

LemnaTec scientists Dr. Tino Dornbusch and Dr. Stefan Paulus published a report on the use of laser scanners in high throughput phenotyping. The text in German is accessible here.


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Analysis of stress responsive pathways

When coping with environmental signals, complex networks of signal transduction and regulation processes are triggered. This particularly includes organelle functions. Nuclear-encoded organelle-targeted genes have central functions in such regulations. Mutations in such genes take influence on phenotypes and act pleiotropically. Researchers at the University of Nebraska Lincoln used a Lab Scanalyzer HTS to monitor plant growth in order to quantify mutant effects on growth phenotypes. Mutation-related growth reduction and phenotypic variances were set in relation to transcriptomic changes.

Shao, Mon-Ray; Kumar Kenchanmane Raju, Sunil; Laurie, John D.; Sanchez, Robersy; Mackenzie, Sally A. (2017): Stress-responsive pathways and small RNA changes distinguish variable developmental phenotypes caused by MSH1 loss. In: BMC plant biology 17 (1), S. 47. DOI: 10.1186/s12870-017-0996-4.


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Review on Importance of Phenotyping in Breeding

Researchers from the Italian Research Centre for Vegetable and Ornamental Crops published a review that points out the high importance of phenotyping at various scales for improving future breeding procedures. In particular, when using material from gene banks for horticultural crop breeding, precise phenotypic information is essential.

Nunzio D’Agostino and Pasquale Tripodi (2017): NGS-Based Genotyping, High-Throughput Phenotyping and Genome-Wide Association Studies Laid the Foundations for Next-Generation Breeding in Horticultural Crops. In: Diversity 9 (3), S. 38. DOI: 10.3390/d9030038.


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Automated growth stage determination with Rothamsted Field Scanalyzer

Current phenotyping technology fulfills tasks that are congruent with many “classical” measurements in agronomy or botany. Howerver, despite measuring the same object, data might lack comparability. One challenge is matching growth stages with non-invasive phenotyping data. Scientists at Rothamsted Research used machine learning methods to derive growth stage information in wheat from Field Scanalyzer-captured images.

Sadeghi-Tehran, Pouria; Sabermanesh, Kasra; Virlet, Nicolas; Hawkesford, Malcolm J. (2017): Automated Method to Determine Two Critical Growth Stages of Wheat: Heading and Flowering. In: Front. Plant Sci. 8, S. 252. DOI: 10.3389/fpls.2017.00252.


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Duckweed tests deliver data in screening for herbicidal compounds from natural sources

Looking for compounds with herbicidal activity, a fungus (Curvularia intermedia) was isolated from Pandanus amaryllifolius leaves, where it caused wilting symptoms. After isolating fungal metabolites, curvulatin and derivatives, toxicity was proven using a Lemna growth inhibiton test. LemnaTec software enabled growth analysis to figure out effective concentrations of the compounds. Future tests should show whether the substances are suitable for use in weed management.

Meepagala, Kumudini M.; Johnson, Robert D.; Duke, Stephen O. (2016): Curvularin and Dehydrocurvularin as Phytotoxic Constituents from Curvularia intermedia Infecting Pandanus amaryllifolius. In: JACEN 05 (01), S. 12–22. DOI: 10.4236/jacen.2016.51002.


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Shanghai Jiao Tong University tested responses to root zone water availability

Researchers of the Shanghai Jiao Tong University used a LemnaTec Greenhouse Scanalyzer to assess the impact of root zone water availability on shoot growth performance of pakchoi (Brassica rapa chinensis) plants. Aim was to establish a method to discriminate root zone water availability levels by applying shoot phenotyping methods. Visible light and near-infrared camera recordings were processed with LemnaGrid software. Resulting parameters on morphology, colour, and NIR reflectance were used in machine learning approaches in order to conclude from phenotypic traits to the root zone water availability. Particularly colour and NIR reflectance turned out to be good indicators of the root zone water status. This phenotype-based root zone water status rating method offers application potential for irrigation control in horticulture, particularly for indoor-cultivated plants. Phenotype-driven precision irrigation can minimise water stress during cultivation.

Guo, Doudou; Juan, Jiaxiang; Chang, Liying; Zhang, Jingjin; Huang, Danfeng (2017): Discrimination of plant root zone water status in greenhouse production based on phenotyping and machine learning techniques. In: Scientific reports 7 (1), S. 8303. DOI: 10.1038/s41598-017-08235-z.


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Water stress trials at Arkansas State University

Using an HTS Scanalyzer with RGB-, NIR-, and fluorescence cameras, researchers generated 4320 images of Arabidopsis plants in a drought study. Growth responses, water content, and chlorophyll-originating fluorescence signals were used to physiologically characterise the responses of the plants towards water limitation in different severities. Together with ionomic data, phenotypic data help to understand mecahnisms of plants coping with low water availability. The results were published in Functional Plant Biology:

Lucia M. Acosta-Gamboa, Suxing Liu, Erin Langley, Zachary Campbell, Norma Castro-Guerrero, David Mendoza-Cozatl, Argelia Lorence; Acosta-Gamboa, Lucia M.; Liu, Suxing; Langley, Erin; Campbell, Zachary; Castro-Guerrero, Norma et al. (2017): Moderate to severe water limitation differentially affects the phenome and ionome of Arabidopsis. In: Functional Plant Biol. 44 (1), S. 94. DOI: 10.1071/FP16172.


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