scholarly journals ScreenSeed as a novel high throughput seed germination phenotyping method

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Nicolas Merieux ◽  
Pierre Cordier ◽  
Marie-Hélène Wagner ◽  
Sylvie Ducournau ◽  
Sophie Aligon ◽  
...  
Keyword(s):  
Arabidopsis Thaliana ◽  
Image Analysis ◽  
Seed Germination ◽  
High Throughput ◽  
Automated Image Analysis ◽  
Experimental Protocol ◽  
Visual Scoring ◽  
Radicle Protrusion ◽  
High Throughput Phenotyping ◽  
Fast Procedure

AbstractA high throughput phenotyping tool for seed germination, the ScreenSeed technology, was developed with the aim of screening genotype responsiveness and chemical drugs. This technology was presently used with Arabidopsis thaliana seeds to allow characterizing seed samples germination behavior by incubating seeds in 96-well microplates under defined conditions and detecting radicle protrusion through the seed coat by automated image analysis. This study shows that this technology provides a fast procedure allowing to handle thousands of seeds without compromising repeatability or accuracy of the germination measurements. Potential biases of the experimental protocol were assessed through statistical analyses of germination kinetics. Comparison of the ScreenSeed procedure with commonly used germination tests based upon visual scoring displayed very similar germination kinetics.

scholarly journals High-throughput microfluidic micropipette aspiration device to probe time-scale dependent nuclear mechanics in intact cells

Lab on a Chip ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 3652-3663 ◽  
Author(s):  
Patricia M. Davidson ◽  
Gregory R. Fedorchak ◽  
Solenne Mondésert-Deveraux ◽  
Emily S. Bell ◽  
Philipp Isermann ◽  
...  
Keyword(s):  
Image Analysis ◽  
High Throughput ◽  
Time Scale ◽  
Viscoelastic Properties ◽  
Micropipette Aspiration ◽  
Automated Image Analysis ◽  
Cell Nuclei ◽  
Intact Cells ◽  
Nuclear Mechanics ◽  
Analysis Platform

We report the development, validation, and application of an easy-to-use microfluidic micropipette aspiration device and automated image analysis platform that enables high-throughput measurements of the viscoelastic properties of cell nuclei.

scholarly journals SmartGrain: High-Throughput Phenotyping Software for Measuring Seed Shape through Image Analysis

2012 ◽  
Vol 160 (4) ◽  
pp. 1871-1880 ◽  
Author(s):  
Takanari Tanabata ◽  
Taeko Shibaya ◽  
Kiyosumi Hori ◽  
Kaworu Ebana ◽  
Masahiro Yano
Keyword(s):  
Image Analysis ◽  
High Throughput ◽  
Seed Shape ◽  
High Throughput Phenotyping

scholarly journals Rhizoslides: paper-based growth system for non-destructive, high throughput phenotyping of root development by means of image analysis

Plant Methods ◽  
2014 ◽  
Vol 10 (1) ◽  
pp. 13 ◽  
Author(s):  
Chantal Le Marié ◽  
Norbert Kirchgessner ◽  
Daniela Marschall ◽  
Achim Walter ◽  
Andreas Hund
Keyword(s):  
Image Analysis ◽  
High Throughput ◽  
Root Development ◽  
Growth System ◽  
High Throughput Phenotyping ◽  
Non Destructive

scholarly journals 227 Leveraging on high-throughput phenotyping technologies to optimize livestock genetic improvement and husbandry

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 55-55
Author(s):  
Guilherme J M Rosa ◽  
João R R Dorea ◽  
Arthur Francisco Araujo Fernandes ◽  
Tiago L Passafaro
Keyword(s):  
Computer Vision ◽  
Image Analysis ◽  
High Throughput ◽  
Feed Intake ◽  
Genetic Improvement ◽  
Milk Composition ◽  
Sensor Technology ◽  
Efficient Data ◽  
High Throughput Phenotyping ◽  
Complex Relationships

Abstract The advent of fully automated data recording technologies and high-throughput phenotyping (HTP) systems has opened up a myriad of opportunities to advance breeding programs and livestock husbandry. Such technologies allow scoring large number of animals for novel phenotypes and indicator traits to boost genetic improvement, as well as for real-time monitoring of animal behavior and development for optimized management decisions. HTP tools include, for example, image analysis and computer vision, sensor technology for motion, sound and chemical composition, and spectroscopy. Applications span from health surveillance, precision nutrition, and control of meat and milk composition and quality. However, the application of HTP requires sophisticated statistical and computational approaches for efficient data management and appropriate data mining, as it involves large datasets with many covariates and complex relationships. In this talk we will discuss some of the challenges and potentials of HTP in livestock. Some examples to be presented include the utilization of automated feeders to record feed intake and to monitor feeding behavior in broilers, milk-spectra information to predict dairy cattle feed intake, and image analysis and computer vision to monitor growth and body condition in pigs and cattle. HTP and big data will become an essential component of modern livestock operations in the context of precision animal agriculture, boosting animal welfare, environmental footprint, and overall sustainability of animal production.

scholarly journals Measuring Quantitative Virulence in the Wheat Pathogen Zymoseptoria tritici Using High-Throughput Automated Image Analysis

2014 ◽  
Vol 104 (9) ◽  
pp. 985-992 ◽  
Author(s):  
Ethan L. Stewart ◽  
Bruce A. McDonald
Keyword(s):  
Image Analysis ◽  
High Throughput ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Continuous Distribution ◽  
Automated Image Analysis ◽  
Host Specialization ◽  
Septoria Tritici Blotch ◽  
Septoria Tritici ◽  
Zymoseptoria Tritici

Zymoseptoria tritici, causal agent of Septoria tritici blotch on wheat, produces pycnidia in chlorotic and necrotic lesions on infected leaves. A high-throughput phenotyping method was developed based on automated digital image analysis that accurately measures the percentage of leaf area covered by lesions (PLACL) as well as pycnidia size and number. A seedling inoculation assay was conducted using 361 Z. tritici isolates originating from a controlled cross and two different winter wheat cultivars. Pycnidia size and density were found to be quantitative traits that showed a continuous distribution in the progeny. There was a weak correlation between pycnidia density and size (r = −0.27) and between pycnidia density and PLACL (r = 0.37). There were significant differences in PLACL and pycnidia density on resistant and susceptible cultivars. In all, >20% of the offspring exhibited significantly different pycnidia density on the two cultivars, consistent with host specialization. Automated image analysis provided greater accuracy and precision compared with traditional visual estimates of virulence. These results show that digital image analysis provides a powerful tool for measuring differences in quantitative virulence among strains of Z. tritici.

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