Compared to conventional laboratory testing methods, crop nitrogen estimation methods based on canopy spectral characteristics have advantages in terms of timeliness, cost, and practicality. A variety of rapid and non-destructive estimation methods based on the canopy spectrum have been developed on the scale of space, sky, and ground. In order to understand the differences in estimation accuracy and applicability of these methods, as well as for the convenience of users to select the suitable technology, models for estimation of nitrogen status of winter wheat were developed and compared for three methods: drone equipped with a multispectral camera, soil plant analysis development (SPAD) chlorophyll meter, and smartphone photography. Based on the correlations between observed nitrogen status in winter wheat and related vegetation indices, green normalized difference vegetation index (GNDVI) and visible atmospherically resistant index (VARI) were selected as the sensitive vegetation indices for the drone equipped with a multispectral camera and smartphone photography methods, respectively. The correlation coefficients between GNDVI, SPAD, and VARI were 0.92 ** and 0.89 **, and that between SPAD and VARI was 0.90 **, which indicated that three vegetation indices for these three estimation methods were significantly related to each other. The determination coefficients of the 0–90 cm soil nitrate nitrogen content estimation models for the drone equipped with a multispectral camera, SPAD, and smartphone photography methods were 0.63, 0.54, and 0.81, respectively. In the estimation accuracy evaluation, the method of smartphone photography had the smallest root mean square error (RMSE = 9.80 mg/kg). The accuracy of the smartphone photography method was slightly higher than the other two methods. Due to the limitations of these models, it was found that the crop nitrogen estimation methods based on canopy spectrum were not suitable for the crops under severe phosphate deficiency. In addition, in estimation of soil nitrate nitrogen content, there were saturation responses in the estimation indicators of the three methods. In order to introduce these three methods in the precise management of nitrogen fertilizer, it is necessary to further improve their estimation models.

Current tillage practices in the important winter wheat–summer maize double cropping system of the North China Plain are under debate because of negative effects on soil quality and crop yield. Therefore, a long-term experiment was conducted from 2001 to 2018 to determine the effects of soil conservation practices on crop yield and soil quality. The treatments were imposed following maize harvest and prior wheat seeding, and were defined as follows: (1) moldboard ploughing (0–20 cm) following maize straw removal (CK); (2) moldboard ploughing (0–20 cm) following maize straw return (CT); (3) rotary tillage following maize straw return (RT); and (4) no tillage with maize straw covering the soil surface (NT). Wheat straw was chopped and spread on the soil in all treatments and maize seeded without prior tillage. Wheat yields were higher in CT than RT and NT treatments (p < 0.05); NT had 18% lower wheat yields than CT. No significant differences were found between treatments in summer maize yields. The soil organic carbon (SOC) content in the surface layer (0–5 cm) was higher in NT and RT compared to CT and CK. However, SOC content in the 10–20 cm and 20–30 cm layers was lower in NT and RT compared to CT and CK. Similarly, available phosphorus in the surface soil was higher in NT and RT than in CT and CK. but the opposite was true for the lower soil layers. SOC stocks (0–30 cm) increased in all treatments, and were initially faster in NT and RT than in CT and CK. However, SOC stocks were higher in CT than in other treatments at the end of the experiment. This finding indicates that no tillage and reduced tillage decreased both wheat yields and soil C sequestration over time; it also indicates that CT was the most robust in terms of crop yields and soil C sequestration.

Incorporating crop residues into the soil is an effective method for improving soil carbon sequestration, fertility, and crop productivity. Such potential benefits, however, may be offset if residue addition leads to a substantial increase in soil greenhouse gas (GHG) emissions. This study aimed to quantify the effect of different crop residues with varying C/N ratios and different nitrogen (N) fertilizers on GHG emissions, yield, and yield-scaled emissions (GHGI) in winter wheat. The field experiment was conducted during the 2018–2019 winter wheat season, comprising of four residue treatments (no residue, maize residue, soybean residue, and maize-soybean mixed residue) and four fertilizer treatments (control, urea, manure, and manure + urea). The experiment followed a randomized split-plot design, with N treatments as the main plot factor and crop residue treatments as the sub-plot factor. Except for the control, all N treatments received 150 kg N ha⁻¹ season⁻¹. The results showed that soils from all treatments acted as a net source of N₂O and CO₂ fluxes but as a net sink of CH₄ fluxes. Soybean residue significantly increased soil N₂O emissions, while mixed residue had the lowest N₂O emissions among the three residues. However, all residue amendments significantly increased soil CO₂ emissions. Furthermore, soybean and mixed residues significantly increased grain yield by 24% and 21%, respectively, compared to no residue amendment. Both soybean and mixed residues reduced GHGI by 25% compared to maize residue. Additionally, the urea and manure + urea treatments exhibited higher N₂O emissions among the N treatments, but they contributed to significantly higher grain yields and resulted in lower GHGI. Moreover, crop residue incorporation significantly altered soil N dynamics. In soybean residue-amended soil, both NH₄⁺ and NO₃⁻ concentrations were significantly higher (p < 0.05). Conversely, soil NO₃⁻ content was notably lower in the maize-soybean mixed residue amendment. Overall, our findings contribute to a comprehensive understanding of how different residue additions from different cropping systems influence soil N dynamics and GHG emissions, offering valuable insights into effective agroecosystems management for long-term food security and soil sustainability while mitigating GHG emissions.