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Image Analysis for Mapping Immeasurable Phenotypes in Maize [Life Sciences]

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6 Author(s)
Chi-ren Shyu ; Missouri-Columbia Univ., Columbia, MO ; Jason M. Green ; Daniel P. K. Lun ; Toni Kazic
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This work will allow bio-informaticians to analyze the ever-increasing gene sequence data, discover valuable knowledge in maize biology and related plant; development, and understand subtle variations among different phenotypes. Furthermore, successful measuring of visual phenotypes will advance plant research by finding the genes and/or environmental factors that cause a given visual phenotype. In what follows, the field of plant genetics is introduced (particularly quantitative trait loci and disease scoring) to the signal processing community, discuss the challenges involved, and present an image analysis system for precisely quantifying and mapping immeasurable phenotypes in maize

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IEEE Signal Processing Magazine  (Volume:24 ,  Issue: 3 )