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The overapplication of nitrogen to wheat reduces profits and has adverse environmental consequences. Machine learning techniques are employed to identify the factors that hold the most potential in improving nitrogen recommendations. The database used in our analysis consisted of a formula fertilization project, the second soil census of China, and cultivated land fertility evaluation. The results showed that the wheat nitrogen yield response was mainly concentrated around 1300–2400 kg/ha in Henan Province, with the highest values observed in the southern and eastern regions and the lowest in the northern region. The soil nitrogen content, nitrogen fertilizer, wet nitrogen deposition, dry nitrogen deposition, and soil nitrogen supply capacity were mainly concentrated around 0.65–1.30 g/kg, 173–203 kg N/ha, 15–39 kg N/(ha yr), 7–49 kg N/(ha yr), and 105–150 kg N/ha, respectively. When comparing the spatial distribution of the soil nitrogen content, nitrogen fertilizer, and nitrogen deposition, we found that the soil nitrogen supply capacity emerged as the predominant factor controlling wheat grain production. Soil types, precipitation, and temperature demonstrated a notable positive correlation with the soil nitrogen supply capacity. Given this background, it would be unreasonable to rely solely on the soil nitrogen content as the standard for fertilizer management. Particularly in high-yield fields, our focus should be on preserving optimal soil fertility by placing greater emphasis on the soil nitrogen supply capacity rather than simply reducing fertilizer application during wheat growth. [ABSTRACT FROM AUTHOR]

Sensor- and satellite-based determination of nitrogen uptake provides critical data in site-specific fertilization algorithms. Therefore, two basic noncontact measurement methods (sensor and satellite) were investigated in winter wheat, and their precision was evaluated in this study. Nitrogen uptake at four characteristic growth stages (BBCH 31, BBCH 39, BBCH 55, and BBCH 65) was determined using algorithms based on sensor and satellite data. As a reference, nitrogen uptake was determined using biomass samples in the laboratory (ground truth data). The precision of the tested methods was evaluated using statistical indicators (mean, median, minimum, maximum, and standard deviation) and correlation analyses between the nitrogen uptake of the ground truth data and that of the respective method. The results showed moderate to strong correlations with the nitrogen uptake of the ground truth data for both methods (R2 = 0.57–0.83). Both sensor and satellite data best represented nitrogen uptake in BBCH 39 and 55 (R2 = 0.63–0.83). In sum, there were only slight deviations in the absolute amount of nitrogen uptake (≤±15%). Clear deviations can be explained by external influences during measurement. Overall, the investigations showed that the nitrogen uptake could be appropriately determined as a data basis for site-specific fertilization systems using sensor and satellite data. [ABSTRACT FROM AUTHOR]