کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
84135 158865 2015 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Low-cost assessment of wheat resistance to yellow rust through conventional RGB images
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
Low-cost assessment of wheat resistance to yellow rust through conventional RGB images
چکیده انگلیسی


• RGB imagery is a low-cost approach for field phenotyping of rust tolerance in wheat.
• It performs better than chlorophyll content and gas exchange of individual leaves.
• Hue, Green Fraction, Greener Fraction, a and u are the most effective color traits.

Establishing low-cost methods for stripe (yellow) rust (Puccinia striiformis f. sp. tritici) phenotyping is paramount to maintain the breeding pipeline in wheat. Twelve winter wheat genotypes were grown to test rust resistance and yield performance. Physiological traits, including leaf chlorophyll content (Chl), net photosynthesis rate (Pn), stomatal conductance (gs), transpiration rate (E) and canopy temperature depression (CTD), together with diverse color components derived from Red, Green and Blue (RGB) images, were measured at different crop stages. Grain yield (GY) and grain yield loss index (GYLI) were assessed through comparison with the previous normal planting year. Genotypes exhibited a wide range of resistance to yellow rust, with GYLI values ranging from about −3% for the more resistant (Zhoumai 22) to 89% for the most susceptible (Lankao 298) genotypes. Moreover yellow rust reduced Chl and to a lesser extent, Pn, while traits related to water status were lower (gs) or not affected (E and CTD). The color parameters Green Fraction, Greener Fraction, Hue, a and u measured during grain filling were much better correlated with GY and GYLI (r2 ranging between 74% and 81%) than the set of photosynthetic and transpirative traits (Chl, Pn, gs, E, CTD) measurements in the same stage. Conventional digital imaging appears to be a potentially affordable approach for high-throughput phenotyping of yellow rust resistance.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers and Electronics in Agriculture - Volume 116, August 2015, Pages 20–29
نویسندگان
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