Application of Remote Sensing for Phenotyping Tar Spot Complex Resistance in Maize

被引:24
|
作者
Loladze, Alexander [1 ]
Augusto Rodrigues, Francelino, Jr. [1 ]
Toledo, Fernando [1 ]
San Vicente, Felix [1 ]
Gerard, Bruno [1 ]
Boddupalli, Maruthi Prasanna [2 ]
机构
[1] Int Maize & Wheat Improvement Ctr CIMMYT, Texcoco, Mexico
[2] Kenya World Agroforestry Ctr ICRAF, Int Maize & Wheat Improvement Ctr CIMMYT, Nairobi, Kenya
来源
关键词
corn; disease control; plant pathogen; new diseases; UAV; VEGETATION INDEXES; HYPERSPECTRAL INDEXES; VERTICILLIUM WILT; DISEASE DETECTION; THERMAL IMAGERY; STRIPE RUST; LEAF; QUANTIFICATION; VISUALIZATION; FLUORESCENCE;
D O I
10.3389/fpls.2019.00552
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
Tar spot complex (TSC), caused by at least two fungal pathogens, Phyllachora maydis and Monographella maydis, is one of the major foliar diseases of maize in Central and South America. P. maydis was also detected in the United States of America in 2015 and since then the pathogen has spread in themaize growing regions of the country. Although remote sensing (RS) techniques are increasingly being used for plant phenotyping, they have not been applied to phenotyping TSC resistance in maize. In this study, several multispectral vegetation indices (VIs) and thermal imaging of maize plots under disease pressure and disease-free conditions were tested using an unmanned aerial vehicle (UAV) over two crop seasons. A strong relationship between grain yield, a vegetative index (MCARI2), and canopy temperature was observed under disease pressure. A strong relationship was also observed between the area under the disease progress curve of TSC and three vegetative indices (RDVI, MCARI1, and MCARI2). In addition, we demonstrated that TSC could cause up to 58% yield loss in the most susceptible maize hybrids. Our results suggest that the RS techniques tested in this study could be used for high throughput phenotyping of TSC resistance and potentially for other foliar diseases of maize. This may help reduce the cost and time required for the development of improved maize germplasm. Challenges and opportunities in the use of RS technologies for disease resistance phenotyping are discussed.
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页数:10
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