基于红光波段日光诱导叶绿素荧光逃逸率的小麦条锈病 遥感监测.

Wheat stripe rust, caused by Puccinia striiformis, is one of the most serious diseases on wheat yield. It is of great significance to timely and accurately detect the disease, in order to monitor and prevent the wheat stripe rust. The stripe rust can infect the internal physical and chemical characteristics and external morphological structure of wheat. Solar-induced chlorophyll fluorescence (SIF) can be expected for the remote sensing detection of crop stress. The red-band sunlight-induced chlorophyll fluorescence (RSIF) has more information about photosystem II (PSII), thus sensitively representing the photosynthetic physiological state of plants. The SIF escape rate is closely related to the canopy geometry, leaf optical properties, and light energy utilization efficiency of vegetation. In this study, field-measured data was used to invert and calculate the SIF and its escape rate (εCP) at different scales (canopy scale SIFCanopy and photosystem scale SIFPS) in the red and far-red band. The contents of four wheat pigments were obtained to combine the leaf area index (LAI) closely related to vegetation growth. The physiological basis of RSIF escape rate (RεCP) was determined to monitor the wheat stripe rust. Subsequently, the response characteristics of RεCP under stripe rust stress were explored to compare with the SIF and its derived parameters (fluorescence yield ФF, apparent SIF yield SIFy) in the red and far-red light bands, the normalized difference vegetation index (NDVI), the MERIS terrestrial chlorophyll index (MTCI) and the simple ratio vegetation index (SR). In addition, a systematic analysis was performed on the response characteristics to SL under different disease severity (SL) and different chlorophyll contents (Chl). The results indicate that the correlations between nitrogen balance index (NBI), Chl, flavonoids (Flav), anthocyanins (Anth), and LAI and SL all reached the P<0.01 level, among which the correlation between Chl and SL was the highest. The correlations of RεCP with NBI, Chl, Flav, and Anth increased by 29.06% and 31.52% on average, respectively, compared with photosystem-scale RSIF and photosystem-scale far-red band SIF (far-red solarinduced chlorophyll fluorescence, FRSIF). The correlation with LAI increased by 15.63%, compared with the canopy-scale FRSIF. RεCP better reflected the variation in the crop physiology and canopy structure caused by disease stress. RεCP shared the highest correlation with SL, which was 60.87%, 42.31%, 17.46%, 39.62%, 34.55%, 5.71%, 13.85%, and 21.31% higher than those of canopy-scale FRSIF (FRSIFCanopy), photosystem-scale FRSIF (FRSIFPS), photosystem-scale RSIF (RSIFPS), apparent SIF yield in the red light band (RSIFy), fluorescence yield in the red light band (RФF), NDVI, MTCI and SR, respectively. In the mild to moderate (0%<SL≤45%) and severe (SL>45%) disease conditions, the correlation between RεCP and SL increased by an average of 56.34% and 53.97%, respectively, compared with SIF and their derived parameters and vegetation index at the P<0.01 level. RεCP was sensitively responded to the variation in SL, which was better than the rest parameters. RεCP was most sensitive to the wheat stripe rust stress under the low (Chl≤30) and medium to high chlorophyll content (Chl>30). The correlation with SL increased by an average of 42.77% and 43.25%, respectively, compared with SIF and their derived parameters and vegetation index at the P<0.01 level. RεCP can serve as a suitable factor for remote sensing monitoring of wheat stripe rust. RεCP can greatly contribute to disease prevention for better yields. The finding can also provide a strong reference and powerful tool for remote sensing monitoring of crops in agricultural production. RSIF and escape rate can be incorporated into the remote sensing monitoring, in order to greatly improve the detection and monitoring of plant health status. [ABSTRACT FROM AUTHOR]