Abstract
Real-time non-destructive monitoring of water use efficiency (WUE) is important for screening high-yielding high-efficiency varieties and determining the rational allocation of water resources in winter wheat production. Compared with vertical observation angles, multi-angle remote sensing provides more information on mid to lower parts of the wheat canopy, thereby improving estimates of physical and chemical indicators of the entire canopy. In this study, multi-angle spectral reflectance and the WUE of the wheat canopy were obtained at different growth stages based on field experiments carried out across 4 years using three wheat varieties under different water and nitrogen fertilizer regimes. Using appropriate spectral parameters and sensitive observation angles, the quantitative relationships with wheat WUE were determined. The results revealed that backward observation angles were better than forward angles, while the common spectral parameters Lo and NDDAig were found to be closely related to WUE, although with increasing WUE, both parameters tended to become saturated. Using this data, we constructed a double-ratio vegetation index (NDDAig/FWBI), which we named the water efficiency index (WEI), reducing the impact of different test factors on the WUE monitoring model. As a result, we were able to create a unified monitoring model within an angle range of −20–10°. The equation fitting determination coefficient (R2) and root mean square error (RMSE) of the model were 0.623 and 0.406, respectively, while an independent experiment carried out to test the monitoring models confirmed that the model based on the new index was optimal, with R2, RMSE, and relative error (RE) values of 0.685, 0.473, and 11.847%, respectively. These findings suggest that the WEI is more sensitive to WUE changes than common spectral parameters, while also allowing wide-angle adaptation, which has important implications in parameter design and the configuration of satellite remote sensing and UAV sensors.
Highlights
Wheat is one of the important food crops in the world, and with recent economic development and population growth, the level of winter wheat production has become even more important for ensuring world food security
Based on the data from experiments 1–3, the relationships between the leaf nitrogen content (LNC), leaf water content (LWC), and ratio between LNC/LWC under different experimental conditions was analyzed in terms of the water use efficiency (WUE) (Figure 2)
This study confirmed that the relationship between the LNC and WUE is affected by irrigation treatment, while at the same time, the relationship between the LWC and WUE is affected by nitrogen fertilizer treatment
Summary
Wheat is one of the important food crops in the world, and with recent economic development and population growth, the level of winter wheat production has become even more important for ensuring world food security. Due to global climate change, lack of water has become a key limiting factor in winter wheat production. Efficient use of limited water resources and increases in overall WUE has become an urgent goal of winter wheat production. Rapid development of remote sensing technology has provided an effective tool for largescale analysis of water use in crops. Compared with traditional crop WUE monitoring and diagnostic tools, hyperspectral remote sensing technology has made it possible to obtain a huge amount of continuous large-scale data in a more efficient manner (Peñuelas et al, 1993b; Dong et al, 2011). Ground hyperspectral remote sensing technology selects sensitive bands using spectral characteristic information to obtain vegetation indexes, which are used to establish estimation models (Hatfield et al, 2008; Mistele and Schmidhalter, 2008)
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