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BackgroundProperly reduced irrigation combined with nitrogen (N) application can be used to improve crop water use efficiency (WUE) in arid regions, but its effect on sugar beet is unknown at present. A two‐year field experiment was conducted to evaluate the effects of N application (N0, 0; N1, 150; N2, 225 kg N ha−1) on the canopy production capacity (CPC), yield and WUE of sugar beet under normal irrigation (W1, 70% of field capacity (FC)) and deficit irrigation (DI) (W2, 50% FC) in the early growth stage (EGS).ResultsThe results showed that the W2 treatment reduced the CPC by reducing gas exchange, leaf area index (LAI) and chlorophyll content (SPAD value) of sugar beet leaves compared to the W1 treatment. However, DI combined with N application increased these parameters. Specifically, N application increased the net photosynthetic rate by 40.7% by increased gas exchange, SPAD and LAI compared to the N0 treatment. In addition, N application increased WUE by 12.5% by increasing thickness of upper surface, stomatal aperture and cross‐sectional area of petiole. This ultimately led to a significant increase in taproot yield (TY; 19.7%) and sugar yield (SY; 57.6%). Although the TY of the N2 treatment was higher than that of the N1 treatment, the SY and WUE did not increase significantly and the harvest index decreased significantly by 9.3%.ConclusionDI combined with 150 kg N ha−1in the EGS of sugar beet increases the WUE in arid areas while avoiding yield loss by improving the CPC. © 2023 Society of Chemical Industry.

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The relationship between the leaf nitrogen content (LNC) and hyperspectral remote sensing imagery (HYP) was determined to construct an estimation model of the LNC of drip-irrigated sugar beets, aiming to provide supports for the in-time monitoring of sugar beet growth and nitrogen management in arid areas. In this study, a field hyperspectrometer was used to collect the leaf reflectance at the 350–2500 nm for each treatment on the 65th, 85th, 104th, 124th, and 140th day after emergence, and the LNC and leaf chlorophyll content (CHL) of sugar beets were also determined. The spectral characteristic parameters were selected to construct the vegetation indices. The LNC estimation model using HYP as the independent variable (HYP-LNC), and that using CHL and HYP as the independent variables (HYP-CHL-LNC), were compared. The results shows that the HYP-CHL-LNC models had a better linear relationship and a higher fitting accuracy than the HYP-LNC models.