Abstract

Leaf equivalent water thickness (LEWT) is an important indicator of crop water status. Effectively monitoring the water status of wheat under different nitrogen treatments is important for effective water management in precision agriculture. Trends in the variation of LEWT in wheat plants during plant growth were analyzed based on field experiments in which wheat plants under various water and nitrogen treatments in two consecutive growing seasons. Two-band spectral indices [normalized difference spectral indices (NDSI), ratio spectral indices (RSI), different spectral indices (DSI)], and then three-band spectral indices were established based on the best two-band spectral index within the range of 350–2500 nm to reduce the noise caused by nitrogen and saturation. Then, optimal spectral indices were selected to construct models of LEWT monitoring in wheat. The results showed that the two-band spectral index NDSI(R1204, R1318) could be used for LEWT monitoring throughout the wheat growth season, but the model performed differently before and after anthesis. Therefore, further two-band spectral indices NDSIb(R1445, R487), NDSIa(R1714, R1395), and NDSI(R1429, R416), were constructed for the two developmental phases, with NDSI(R1429, R416) considered to be the best index. Finally, a three-band index (R1429−R416−R1865)/(R1429+R416+R1865), which was superior for monitoring LEWT and reducing the noise caused by nitrogen, was formed on the best two-band spectral index NDSI(R1429, R416) by adding the 1,865 nm wavelenght as the third band. This produced more uniformity and stable performance compared with the two-band spectral indices in the LEWT model. The results are of technical significance for monitoring the water status of wheat under different nitrogen treatments in precision agriculture.

Highlights

  • Real-time, non-destructive monitoring of crop water content based on hyperspectra is an important area of research in precision irrigation in agriculture [1,2,3,4,5,6,7]

  • During the late stages of plant development, evaporation increased with the air temperature, which resulted in greater differences in leaf-equivalent water thickness (LEWT) among water treatments

  • To monitor plant water content, some sensitive wavelength and spectral indices that are strongly correlated with LEWT, but less well correlated with leaf nitrogen content (LNC), should be extracted with consideration of the fact that the spectrum reflectance is affected by both water and nitrogen

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Summary

Introduction

Real-time, non-destructive monitoring of crop water content based on hyperspectra is an important area of research in precision irrigation in agriculture [1,2,3,4,5,6,7]. As a widely used measure of crop water status, leaf-equivalent water thickness (LEWT) and canopy-equivalent water thickness (CEWT) directly indicate crop water content, and provide information for leaf area indices. They can visually reflect crop water requirements and crop growth status. CEWT has been found to be linearly related to the vegetation water content (VWC), with an R2 value of 0.87 for corn [8]. Beans, and sugar beet, the R1300/R1450 leaf water index (ratio of reflectance at 1,300 to 1,450 nm) displayed a characteristic logarithmic correlation with LEWT [10]. During the late period of wheat development (after anthesis), LEWT is more useful than FMC for assessing the water status of wheat. Several optimal water indices for different stages of wheat development are available [11]

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