文献类型： 外文期刊

作者： Zhang Xiao-yan ¹ ; Hou Xue-hui ¹ ; Wang Meng ¹ ; Wang Li-li ¹ ; Liu Feng ¹ ;

作者机构： 1.Shandong Acad Agr Sci, Inst Agr Informat & Econ, Jinan 250100, Peoples R China

关键词： Wheat; Stripe rust; Photosynthetic rate; Imaging hyperspectral; Estimating model

期刊名称：SPECTROSCOPY AND SPECTRAL ANALYSIS （ 影响因子：0.609； 五年影响因子：0.516 ）

ISSN： 1000-0593

年卷期： 2022 年 42 卷 3 期

页码：

收录情况： SCI

摘要： For real-time monitor of wheat stripe rust and large-scale recognization of crop diseases using remote sensing technology, the relations of wheat spectral reflectivity and net photosynthetic rate with disease index were studied under stripe rust stress, and the variation of photosynthetic rate was estimated with spectral vegetation indexes. The stripe rust inoculation test was conducted in field plots during the 2018-2019 wheat growth period. The varieties of Jimai 22 and Luyuan 502 with larger sowing areas were used as test materials, and Jimai 15, sensitive to stripe rust, was used as control. The photosynthetic rate and spectral reflectivity of wheat flag leaves were determined, and the disease index was investigated every 7-10 days from heading stage to milk-ripe stage. It was found that the photosynthetic rate decreased significantly with the increase of disease degree. During the flowering stage, the photosynthetic rate of Jimai 22 was higher than that of Luyuan 502. During the grain filling stage, the reflectivity in the visible spectrum range was higher at the diseased part because of lower chlorophyll content leading to lower absorption but the higher reflex of light. However, in the range of reflection platforms, the spectral reflectivity of the diseased part was much lower than that of the healthy part. The indexes related to disease stress, crop growth and yields, such as photochemical reflectance index (PRI), plant senescence reflectance index (PSRI) and ratio vegetation index (RVI) were used to reflect the variation of the disease index. Compared with the healty part, the PRI and PSRI of the diseased part were high, and the change ratio of PSRI was higher; the RVI of diseased part was lower. At different growth stages of wheat, there were different correlations between photosynthetic rate and spectral reflectivity, and the vegetation index was also different. At the grain filling stage, the correlation between photosynthetic rate and spectral reflectivity of Luyuan 502 was positive in all spectrum ranges, and that of Jimai 15 was also positive in visible spectrum range, while that of Jimai 22 was negative. However, in the range of reflectance platform, that of Jimai 15 and Jimai 22 was opposite. The PSRI could be used to recognize disease degree and estimate the photosynthetic rate in the grain filling period of wheat. These results could provide theoretical bases for monitoring wheat growth status and disease occurrence at a large scale using remote sensing method and layed foundations for estimating wheat stripe rust occurrence and degrees using lossless monitoring spectral indicators.