Replacing chemical fertilizers with organic alternatives represents a viable strategy for enhancing agricultural productivity. The optimized integration of both fertilizer types can reduce the chemical input while improving soil conditions. However, the specific impacts of combined organic and inorganic fertilization on soil quality and crop performance require further investigation. To address this, a two-year field experiment was conducted to examine the effects of varying ratios of organic fertilizer substitution on wheat growth, grain yield, nutrient uptake, and soil quality. The results showed that the application of a 100% organic fertilizer combined with a 90% chemical fertilizer significantly increased the wheat biomass and grain yield. In terms of the nutrient uptake efficiency, the aboveground uptake of nitrogen (N), phosphorus (P), and potassium (K) increased significantly by 29.2%, 29.0%, and 56.5%, respectively. The nutrient use efficiency was also improved, with increases of 30.4% for N, 21.1% for P, and 47.7% for K. The partial factor productivity, total nutrient uptake, and the translocation efficiency of N, P, and K were all significantly enhanced. The soil quality was also markedly improved, with increases in both the soil organic matter and nutrient content. In conclusion, substituting chemical fertilizers with organic fertilizers improves the soil moisture and organic matter content, thereby enhancing the total uptake and translocation efficiency of nitrogen, phosphorus, and potassium. This leads to increased nutrient content in wheat grains, resulting in higher yields and improved grain quality. Moreover, this study provides practical guidance for wheat production and supports policy objectives related to sustainable agriculture, reduced chemical fertilizer use, and improved food security.

The Unmanned Aerial Vehicle (UAV) sprayer has the advantages of high work efficiency, simple operation, and high safety factor, and has broad application prospects UAV sprayer are widely used in the agricultural field, and the application of UAV sprayer spraying technology in agriculture has provided convenience and increased profits for farmers, and has also become a research hotspot in the field of agriculture. In recent years, although research has been conducted on the feasibility and application effects of UAV sprayer spraying crown shaped plants, there have been no experiments or studies in the field of garden plants. This experiment conducted a droplet deposition experiment of UAV sprayer spraying garden plants, exploring the droplet deposition effect of UAV sprayer in the field of garden plants, and conducting experiments on the influence of spray volume and nozzle type on droplet deposition. The experimental results showed that the canopy performance of small and medium-sized garden plants was better at a flight altitude of 1.5m, a spray volume of 180L/hm², and a flight speed of 2m/s. Reducing flight altitude, increasing spray volume, and reducing flight speed can improve the distribution of droplets in the canopy. This experiment lays the foundation for the application of UAV sprayer for the prevention and control of pests and diseases in garden plants, as well as for the application of growth regulators, and provides a basis for further innovative research in the field of garden plant application technology.

Celtis sinensis Pers. (Chinese hackberry), belonging to the family Ulmaceae, is widely used as a street tree or landscape plant because of its longevity and aesthetic growth habit. Additionally, C....

Cotton growth monitoring can provide macroscopic information for cotton field management. In this paper, we utilised UAV multispectral remote sensing to monitor cotton growth and constructed a Comprehensive Growth Index (CGI) by combining cotton multi-period Leaf Area Index (LAI) and relative chlorophyll content (Soil and plant analyser development, SPAD) through the coefficient of variation method and constructed 28 types of vegetation cover indexes by combining multispectral data. CGI combined with multispectral data to construct 28 vegetation indices and a digital surface model, selected the indexes with higher correlation through correlation analysis, and constructed a single growth model (LAI and SPAD) and CGI by using the support vector machine (SVM), random forest (RF), and gradient boosted decision tree (GBDT) model. In the GBDT model, the comprehensive growth model was better than the single growth index model, with an R² of 0.85 and an RMSE of 0.044, and in the RF model, the comprehensive growth model was better than the single growth index model, with an R² of 0.86 and an RMSE of 0.037. In the comprehensive analysis, the comprehensive growth index can improve the accuracy of the inversion model of the cotton growth and provide a new method for the monitoring of the cotton growth by remote sensing.

Physostegia virginiana Benth. (false dragon head flower), belonging to the family Lamiaceae, is a perennial plant and is usually used as landscape plant in parks and wetlands in China. It is also w...