Assessing Field-Specific Risk of Soybean Sudden Death Syndrome Using Satellite Imagery in Iowa

被引:7
|
作者
Yang, S. [1 ,2 ]
Li, X. [2 ]
Chen, C. [2 ]
Kyveryga, P. [3 ]
Yang, X. B. [2 ]
机构
[1] Guizhou Normal Univ, Sch Life Sci, Guiyang 550001, Peoples R China
[2] Iowa State Univ, Dept Plant Pathol & Microbiol, Ames, IA 50011 USA
[3] Iowa Soybean Assoc, Ankeny, IA 50023 USA
关键词
LEAF-AREA INDEX; F-SP GLYCINES; FUSARIUM-VIRGULIFORME; CAUSAL AGENT; HETERODERA-GLYCINES; VEGETATION INDEXES; PLANTING DATE; CROP-ROTATION; SOLANI; QUANTIFICATION;
D O I
10.1094/PHYTO-11-15-0303-R
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
Moderate resolution imaging spectroradiometer (MODIS) satellite imagery from 2004 to 2013 were used to assess the field-specific risks of soybean sudden death syndrome (SDS) caused by Fusarium virguliforme in Iowa. Fields with a high frequency of significant decrease (>10%) of the normalized difference vegetation index (NDVI) observed in late July to middle August on historical imagery were hypothetically considered as high SDS risk. These high-risk fields had higher slopes and shorter distances to flowlines, e. g., creeks and drainages, particularly in the Des Moines lobe. Field data in 2014 showed a significantly higher SDS level in the high-risk fields than fields selected without considering NDVI information. On average, low-risk fields had 10 times lower F. virguliforme soil density, determined by quantitative polymerase chain reaction, compared with other surveyed fields. Ordinal logistic regression identified positive correlations between SDS and slope, June NDVI, and May maximum temperature, but high June maximum temperature hindered SDS. A modeled SDS risk map showed a clear trend of potential disease occurrences across Iowa. Landsat imagery was analyzed similarly, to discuss the ability to utilize higher spatial resolution data. The results demonstrated the great potential of both MODIS and Landsat imagery for SDS field-specific risk assessment.
引用
收藏
页码:842 / 853
页数:12
相关论文
共 43 条
  • [1] Early detection of soybean sudden death syndrome using high-resolution satellite imagery
    Raza, M.
    Eggenberger, S.
    Nutter, F. W., Jr.
    Leandro, L. F. S.
    PHYTOPATHOLOGY, 2019, 109 (10) : 189 - 189
  • [2] Evaluating sudden death syndrome in soybean using multispectral imagery
    Mckinzie, L.
    Fakhoury, A. M.
    Li, R.
    Bond, J. P.
    PHYTOPATHOLOGY, 2020, 110 (12) : 76 - 76
  • [3] Recent outbreak of soybean sudden death syndrome in Iowa
    Sanogo, S.
    Yang, X.B.
    Plant Disease, 1999, 83 (06):
  • [4] Occurrence and distribution of soybean sudden death syndrome in Iowa
    Yang, XB
    Lundeen, P
    PLANT DISEASE, 1997, 81 (07) : 719 - 722
  • [5] Exploring the Potential of High-Resolution Satellite Imagery for the Detection of Soybean Sudden Death Syndrome
    Raza, Muhammad M.
    Harding, Chris
    Liebman, Matt
    Leandro, Leonor F.
    REMOTE SENSING, 2020, 12 (07)
  • [6] Effect of tillage and cultivar on sudden death syndrome and yield of soybean in Iowa
    Kandel, Y. R.
    Leandro, L. F. S.
    Mueller, D. S.
    PHYTOPATHOLOGY, 2017, 107 (12) : 5 - 5
  • [7] Soil variables associated with sudden death syndrome in soybean fields in Iowa
    Scherm, H
    Yang, XB
    Lundeen, P
    PLANT DISEASE, 1998, 82 (10) : 1152 - 1157
  • [8] Long-term crop rotations suppress soybean sudden death syndrome in Iowa
    Abdelsamad, N.
    Mbofung, G. C.
    Robertson, A. E.
    Liebman, M.
    Leandro, L. F.
    PHYTOPATHOLOGY, 2012, 102 (07) : 1 - 1
  • [9] Effect of Tillage and Cultivar on Plant Population, Sudden Death Syndrome, and Yield of Soybean in Iowa
    Kandel, Yuba R.
    Leandro, Leonor F. S.
    Mueller, Daren S.
    PLANT HEALTH PROGRESS, 2019, 20 (01): : 29 - 34
  • [10] Assessing the Variability of Corn and Soybean Yields in Central Iowa Using High Spatiotemporal Resolution Multi-Satellite Imagery
    Gao, Feng
    Anderson, Martha
    Daughtry, Craig
    Johnson, David
    REMOTE SENSING, 2018, 10 (09)