Computer-based image analysis to quantify the number of micro-arthropods in a sample

Entomologia Experimentalis et Applicata

Volumn 132, Issue 3, 2009, Pages 289-294

  Lukas, J ^a   Kucerova, Z ^a   Stejskal, V ^a  

^a CROP RESEARCH INSTITUTE   (Czech Republic)

Author keywords

Acari; Acaridae; Acarus siro; Automated computer imaging; Booklice; Grain; Liposcelididae; Liposcelis bostrychophila; Mites; Psocoptera; Stored product pests

Indexed keywords

CROP PEST; IMAGE ANALYSIS; IMAGING METHOD; MITE; POPULATION DENSITY; SOFTWARE;

ACARI; ACARIDAE; ACARUS SIRO; ARTHROPODA; LIPOSCELIDAE; LIPOSCELIS BOSTRYCHOPHILA; PSOCOPTERA;

EID: 68949132878     PISSN: 00138703     EISSN: 15707458     Source Type: Journal    
DOI: 10.1111/j.1570-7458.2009.00892.x     Document Type: Article

References (29)

1. Asquish D (1965) Photography in mite counting. Journal of Economic Entomology 58 : 677 678.
2. Athanassiou CG, Kavallieratos NG, Palyvos NE Buchelos CTH (2003) Three dimensional distribution and sampling indices of insects and mites in horizontally stored wheat. Applied Entomology and Zoology 38 : 413 426.
3. Bischoff ERC, Fischer A Liebenberg B (1992) Assessment of mite numbers: new methods and results. Experimental and Applied Acarology 16 : 1 14.
4. Brieri M, Fritschy A Ziegler FJ (1987) Electronic image processing: evaluation of a new technique in quantitative soil ecology, demonstrated by counts of Heterorhabditis heliothidis larvae (Nematode) from a mass rearing. Soil Fauna and Soil Fertility. Proceedings of the 9th International Colloquium on Soil Zoology, Moscow, August 1985 (ed. by BRD Striganova pp. 217 229. Nauka, Moscow, Russia.
5. Brosnan T Sun DW (2002) Inspection and grading of agricultural and food products by computer vision systems - a review. Computers and Electronics in Agriculture 36 : 193 213.
6. Crawley MJ (1993) GLIM for Ecologists. Blackwell Science, Oxford, UK.
7. Daniel O, Schönholzer F Zeyer J (1995) Quantification of fungal hyphae in leaves of desiduous trees by automated image analysis. Applied and Environmental Microbiology 61 : 3910 3918.
8. Davis A, Farrey B Altizer S (2004) Quantifying monarch butterfly larval pigmentation using digital image analysis. Entomologia Experimentalis et Applicata 113 : 145 147.
9. Erickson BJ, Persons KR, Hangiandreou NJ, James EM, Hanna CJ Gehring DG (2001) Requirements for an enterprise digital image archive. Journal of Digital Imaging 14 : 72 82.
10. Fornal J, Jelinski T, Sadowska J, Stainslaw G, Nawrot J, Niewiada A, Warchalewski JR Blaszczak W (2007) Detection of granary weevil Sitophilus granarius (L.) eggs and internal stages in wheat grain using soft X-ray and image analysis. Journal of Stored Products Research 43 : 142 148.
11. Hubert J, Munzbergerová Z, Kučerová Z Stejskal V (2006) Comparison of communities of stored product mites in grain mass and grain residues in the Czech Republic. Experimental and Applied Acarology 39 : 149 158.
12. Krizkova-Kudlikova I, Stejskal V Hubert J (2007) Comparison of detection methods for Acarus siro (Acari: Acaridida: Acarididae) contamination in grain. Journal of Economic Entomology 100 : 1928 1937.
13. Krogh PH, Johansen K Holmstrup M (1998) Automatic counting of collembolans for laboratory experiments. Applied Soil and Ecology 7 : 201 205.
14. Kučerová Z, Aulický R Stejskal V (2003) Accumulation of pest-arthropods in grain residues found in an empty store. Zeitschrift für Pflanzenkrankheiten und Pflanzenschutz 110 : 499 504.
15. Lukáš J Stejskal V (2004) Image analysis of occupancy and contamination - Mediterranean flour moth, Ephestia kuehniella and parasitoid Venturia canescens. IOBC/wspr Bulletin 27 (9 85 92.
16. Morgan P, Cooper CJ, Battersby NS, Lee SA, Lewis ST et al. (1991) Automated image analysis method to determine fungal biomass in soil and solid matrices. Soil Biology and Biochemistry 23 : 609 616.
17. Palyvos NE, Emmanouel NG Saitanis CJ (2008) Mites associated with stored products in Greece. Experimental and Applied Acarology 44 : 213 226.
18. Panneton B Drummond AM (1991) Digital image analysis of spray samples. Applied Engineering in Agriculture 7 : 273 278.
19. R Development Core Team R (2007) A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Australia. URL http://www.R-project.org (accessed 26 June 2009).
20. Richardson MD, Karcher DE Purcell LC (2001) Quantifying turfgrass cover using digital image analysis. Crop Science 41 : 1884 1888.
21. Sircom J (2000) Photographic sampling: a photographic sampling methods for mites on plants. Experimental and Applied Acarology 24 : 55 61.
22. Solomon ME (1945) Tyroglyphid mites in stored products. Methods for the study of population density. Annals of Applied Biology 32 : 71 75.
23. Spring KR (2000) Scientific imaging with digital camera. BioTechniques 29 : 70 76.
24. SPSS (1999) SigmaScan Pro 5.0 Users guide. SPSS, Chicago, IL, USA.
25. Stejskal V, Hubert J, Kučerová Z, Munzbergová Z, Lukáš J Žďárková E (2003) The influence of type of storage on pest infestation of stored grain in the Czech Republic. Plant Soil Environment 49 : 55 62.
26. Stejskal V, Aulický R, Kučerová Z Lukáš J (2008) Method of sampling and laboratory extraction affects interpretation of grain infestation by storage pests. Journal of Plant Diseases and Protection 115 : 129 133.
27. Weeks PJD, O'Neill MA, Gatson KJ Gauls ID (1999) Automatic insect identification: exploring the limitations of a prototype system. Journal of Applied Entomology 123 : 1 8.
28. Weyda F (2002) Scientific digital photography and its application to modern zoological research. Studies on Soil Fauna in Central Europe. Proceedings of the 6th Central European Workshop on Soil Zoology (ed. by K Tajovský, V Balík V Pižl pp. 259 271. Institute of Soil Biology, České Budějovice, Czech Republic.
29. Wolfe JM (2005) Rare items often missed in visual searches. Nature 435 : 439.