Full
Outline
To determine the effects of efficient, reduced-input pesticide and nitrogen (N) fertilizer application via unmanned aerial vehicles (UAVs) on the yield formation and energy efficiency of machine-transplanted rice. This study proposes an optimal model for adapting reduced N fertilizer and pesticide inputs to UAV operational efficiency, providing a theoretical foundation and practical basis for integrated UAV fertilizer and pesticide application systems.
A randomized block design was used with two drone flight speeds and four fertilizer-pesticide reduction treatments. Two drone speeds were set: 5.0 m/s (F1) and 5.5 m/s (F2). Four treatments with proportionally reduced N fertilizer and pesticide application were established: conventional application rate (N1), 10% reduction (N2), 20% reduction (N3), and 30% reduction (N4). Manual conventional application (CK1) and no application (CK2) served as controls. The study examined the effects of UAV flight speed and combined reduction treatments on machine-transplanted rice yield, plant population quality, and energy efficiency, while exploring the relationship between yield formation and energy efficiency under the UAV-based integrated fertilizer and pesticide application model.
Compared with the CK1 treatment, the F1N1, F2N1, F1N2, and F2N2 treatments increased yields by 1.22%-1.96%, with no significant yield differences among treatments and disease control efficacy exceeding 84% in all cases. Notably, under 10% reduced fertilizer and pesticide application, treatments F1N2 and F2N2 exhibited increases of 1.73%-13.24% in both dry matter transport volume and rate, as well as N transport volume and rate. N partial factor productivity, N uptake efficiency, and N harvest index increased by 12.48%-12.89%, 17.84%-18.75%, and 1.86%-2.30%, respectively. Energy output, net energy and energy utilisation efficiency increased by 0.54%-0.66%, 0.98%-1.11%, and 5.47%-5.52%, respectively. Under identical fertilizer-pesticide regimes, a 10% increase in drone flight speed raised electricity consumption by 5.19%-10.11%. However, reduced labor hours offset electricity costs, yielding the highest net profit of 8,848.94 yuan/hm2 under the F2N2 treatment. This demonstrates that a 10% increase in UAV speed combined with a 10% reduction in N fertilizer and pesticide application (F2N2 treatment) enhances operational efficiency and reduces production costs (labor) while maintaining net profit. This achieves cost savings and efficiency gains, representing the optimal production model for N fertilizer and pesticide reduction adapted to UAV operational efficiency in this trial.
The 10% drone speed increase coupled with 10% integrated N fertiliser and pesticide reduction drives synergistic optimization of yield, ecology, and energy efficiency in machine-transplanted rice through an optimised compensation mechanism. This achieves unified synergies of fertilizer and pesticide savings alongside high yields and efficiency, providing theoretical and technical support for fully mechanised green rice production.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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