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Items: 1 to 20 of 52

1.

PhenoPhyte: a flexible affordable method to quantify 2D phenotypes from imagery.

Green JM, Appel H, Rehrig EM, Harnsomburana J, Chang JF, Balint-Kurti P, Shyu CR.

Plant Methods. 2012 Nov 6;8(1):45. doi: 10.1186/1746-4811-8-45.

2.
3.

Cumulative impact of GM herbicide-tolerant cropping on arable plants assessed through species-based and functional taxonomies.

Squire GR, Hawes C, Begg GS, Young MW.

Environ Sci Pollut Res Int. 2009 Jan;16(1):85-94. doi: 10.1007/s11356-008-0072-6. Epub 2008 Dec 2.

PMID:
19048321
4.
5.

Quantification of fungal infection of leaves with digital images and Scion Image software.

Goodwin PH, Hsiang T.

Methods Mol Biol. 2010;638:125-35. doi: 10.1007/978-1-60761-611-5_9.

PMID:
20238265
7.

Automatic quantification of morphological traits via three-dimensional measurement of Arabidopsis.

Kaminuma E, Heida N, Tsumoto Y, Yamamoto N, Goto N, Okamoto N, Konagaya A, Matsui M, Toyoda T.

Plant J. 2004 Apr;38(2):358-65.

8.

Utilizing image processing techniques to compute herbivory.

Olson TE, Barlow VM.

Biomed Sci Instrum. 2001;37:391-7.

PMID:
11347423
9.

A new method of skin erythrosis evaluation in digital images.

Mezzana P, Anniboletti T, Curinga G, Onesti MG.

Acta Chir Plast. 2007;49(1):21-6.

PMID:
17469442
10.

An inexpensive, accurate method for measuring leaf area and defoliation through digital image analysis.

O'Neal ME, Landis DA, Isaacs R.

J Econ Entomol. 2002 Dec;95(6):1190-4.

PMID:
12539831
11.

Computer vision as a tool to study plant development.

Spalding EP.

Methods Mol Biol. 2009;553:317-26. doi: 10.1007/978-1-60327-563-7_16. Review.

PMID:
19588113
12.

Quantifying fungal infection of plant leaves by digital image analysis using Scion Image software.

Wijekoon CP, Goodwin PH, Hsiang T.

J Microbiol Methods. 2008 Aug;74(2-3):94-101. doi: 10.1016/j.mimet.2008.03.008. Epub 2008 Apr 3.

PMID:
18466990
13.

An automated field phenotyping pipeline for application in grapevine research.

Kicherer A, Herzog K, Pflanz M, Wieland M, Rüger P, Kecke S, Kuhlmann H, Töpfer R.

Sensors (Basel). 2015 Feb 26;15(3):4823-36. doi: 10.3390/s150304823.

14.

Phenotiki: an open software and hardware platform for affordable and easy image-based phenotyping of rosette-shaped plants.

Minervini M, Giuffrida MV, Perata P, Tsaftaris SA.

Plant J. 2017 Apr;90(1):204-216. doi: 10.1111/tpj.13472. Epub 2017 Mar 2.

PMID:
28066963
15.

Phenotyping of Arabidopsis mutants for developmental effects of gene deletions.

Bolle C.

Methods Mol Biol. 2009;479:17-34. doi: 10.1007/978-1-59745-289-2_2.

PMID:
19083179
16.

Computational analysis of live cell images of the Arabidopsis thaliana plant.

Cunha A, Tarr PT, Roeder AH, Altinok A, Mjolsness E, Meyerowitz EM.

Methods Cell Biol. 2012;110:285-323. doi: 10.1016/B978-0-12-388403-9.00012-6.

PMID:
22482954
17.

Biomarkers in aquatic plants: selection and utility.

Brain RA, Cedergreen N.

Rev Environ Contam Toxicol. 2009;198:49-109. doi: 10.1007/978-0-387-09647-6_2. Review.

PMID:
19253039
18.

Three-dimensional definition of leaf morphological traits of Arabidopsis in silico phenotypic analysis.

Kaminuma E, Heida N, Tsumoto Y, Nakazawa M, Goto N, Konagaya A, Matsui M, Toyoda T.

J Bioinform Comput Biol. 2005 Apr;3(2):401-14.

PMID:
15852512
19.

Three-dimensional quantification of color-marked occlusal paths on anatomically oriented casts.

Dirksen D, Runte C, Böröcz Z, Thomas C, von Bally G, Bollmann F.

J Prosthet Dent. 2001 Feb;85(2):156-61.

PMID:
11208205
20.

OSCILLATOR: A system for analysis of diurnal leaf growth using infrared photography combined with wavelet transformation.

Bours R, Muthuraman M, Bouwmeester H, van der Krol A.

Plant Methods. 2012 Aug 7;8(1):29. doi: 10.1186/1746-4811-8-29.

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