%A Komyshev,Evgenii %A Genaev,Mikhail %A Afonnikov,Dmitry %D 2017 %J Frontiers in Plant Science %C %F %G English %K Wheat grain,phenotyping,Computer image analysis,Mobile Devices,Android %Q %R 10.3389/fpls.2016.01990 %W %L %M %P %7 %8 2017-January-04 %9 Original Research %+ Dmitry Afonnikov,Laboratory of Evolutionary Bioinformatics and Theoretical Genetics, Department of Systems Biology, Institute of Cytology and Genetics Siberian Branch of Russian Academy of Sciences (SB RAS),Novosibirsk, Russia,ada@bionet.nsc.ru %+ Dmitry Afonnikov,Chair of Informational Biology, Novosibirsk State University,Novosibirsk, Russia,ada@bionet.nsc.ru %# %! Mobile Application for Grain Phenotyping %* %< %T Evaluation of the SeedCounter, A Mobile Application for Grain Phenotyping %U https://www.frontiersin.org/articles/10.3389/fpls.2016.01990 %V 7 %0 JOURNAL ARTICLE %@ 1664-462X %X Grain morphometry in cereals is an important step in selecting new high-yielding plants. Manual assessment of parameters such as the number of grains per ear and grain size is laborious. One solution to this problem is image-based analysis that can be performed using a desktop PC. Furthermore, the effectiveness of analysis performed in the field can be improved through the use of mobile devices. In this paper, we propose a method for the automated evaluation of phenotypic parameters of grains using mobile devices running the Android operational system. The experimental results show that this approach is efficient and sufficiently accurate for the large-scale analysis of phenotypic characteristics in wheat grains. Evaluation of our application under six different lighting conditions and three mobile devices demonstrated that the lighting of the paper has significant influence on the accuracy of our method, unlike the smartphone type.