Novel Studies in High-Performance and Precision Plant Protection Products Application

1. Introduction

The need for sustainable and precise crop protection has never been more urgent. Globally, agricultural systems strive to minimize environmental pollution, particularly spray drift and water contamination, while ensuring high yields and food safety. Over the past few decades, the widespread deployment of Plant Protection Products (PPPs) has vastly improved food quality; however, the need to enhance pesticide utilization efficiency remains paramount. This Special Issue (SI), “Novel Studies in High-Performance and Precision Plant Protection Products Application—2nd Edition,” aimed to capture the rapid advancements in technology, methodology, and fundamental theory driving this critical shift towards intelligent agriculture.

2. Recent Developments and Knowledge Gaps

Recent progress in the field is characterized by the convergence of high-efficiency machinery and digital intelligence. We have witnessed the rapid development of agricultural unmanned aerial vehicles (UAVs)/unmanned aerial spraying systems (UASSs), celebrated for their high flexibility, mobility, and capacity to leverage rotor-induced wind fields to enhance droplet penetration. Concurrently, ground-based systems are undergoing unmanned, precise, and high-performance standardization and informationization.

Despite these developments, several persistent knowledge gaps continue to represent challenges for the realization of truly precise application.

2.1. Canopy Penetration and Efficacy

Traditional and even early precision methods struggle to deliver droplets effectively to the biologically critical areas of plants—the middle-lower canopy and the abaxial (underside) leaf surfaces—where pests and diseases often originate. This inadequacy necessitates high application rates, creating a vicious cycle of overuse and environmental risk.

2.2. Drift Control and Utilization Efficiency

Low pesticide utilization rates (historically around 41.8% in China, falling short of international standards by 15% to 25%) highlight the persistent issue of off-target drift and waste. Furthermore, common practices, such as arbitrarily increasing the boom height on electric sprayers to improve clearance, present severe, unassessed drift risks.

2.3. Automation and Fundamental Measurement

The fundamental process of atomization, particularly the complex liquid sheet breakup mechanisms and resulting droplet spectra, relies on time-consuming, manual, or invasive measurement techniques. The lack of automated, robust evaluation tools hinders the rapid optimization and development of new nozzle designs and formulations.

3. Overview of the SI

The contributions within this Special Issue provide compelling evidence of how researchers are employing novel studies in theory, systems, equipment, and technology to close these gaps.

Guo et al. [1] showcased innovative approaches to achieving targeted droplet placement. In soybean fields, optimizing airflow-assisted spraying parameters (initial airflow speed, outlet-to-canopy distance, and forward deflection angle) demonstrated a significant impact. Specifically, an optimized parameter combination increased droplet deposition on the underside of the leaves by 2.3 times and on the middle-lower canopy by 2.1 times compared to conventional airflow-assisted spraying.

For aerial applications, Li et al. [2] confirmed the critical role of rotor-induced wind fields. UAVs generating stronger downwash airflow (e.g., a T60 model in cotton fields) achieved notably higher penetration rates (up to 56.04%) than those with weaker wind fields (44.76% for T30). This superior delivery translated into a significantly higher pesticide utilization rate (75.47–77.86%) compared to boom sprayers (58.88%).

This Special Issue highlights that the optimization of application strategies can facilitate significant pesticide level reductions. A study utilizing an intelligent precision variable-rate boom sprayer in maize demonstrated that an herbicide dose reduction (15% to 30%) was feasible [3]. This reduced dosage significantly decreased maize phytotoxicity by 47% to 53% compared to the recommended rate. However, the success of dose reduction hinges on appropriate timing; efficacy remained high (>90%) for early-stage weeds (3–4 leaf stage) but dropped to an unacceptable level (minimum 72.67%) for older, larger weeds at the same reduced dosage and lower spray volume (180 L/ha). This highlights the importance of tailoring application strategies to weed growth stage and optimizing the nozzle/volume combination for maximized efficiency.

Furthermore, concerning drift, field experiments quantified the risk posed by mechanical instability and improper operation [4]. The total drift amount (TDA) increased sharply when boom height exceeded a critical range (0.6 m for one nozzle type), with increases reaching up to 282.69% in the highest stage, underscoring the need for robust boom height control and nozzle selection tailored for drift reduction.

Novel application systems, such as the multi-fluid swirling mixing atomizer, have demonstrated the ability to generate specialized treatments like ozonated droplets (up to 3.73 mg/L concentration) with uniform distribution, dramatically reducing transportation loss (to less than 15%) through in situ mixing [5]. Moreover, a modified rotating cage atomizer based on the AU5000 atomizer in manned aircraft was designed for large-payload UAVs. Yang J. et al. investigated the impacts of different wind speeds, flow rates, and cage diameters on the atomization characteristic distribution of the atomizer and established a model [6] providing a reference for the selection of the diameter of the rotating cage.

To overcome the challenges of manual evaluation, Yang W. et al. introduced a pioneering use of deep learning (LM-YOLO model) coupled with high-speed photography for automated liquid sheet analysis [7]. This technological innovation achieved high recognition accuracy (e.g., 81.0% for the LU nozzle) and provided reliable quantitative measurement of key structural parameters, including breakup length, spray angle, liquid sheet area, and perforation structure. This development replaces labor-intensive traditional image processing and sets a new standard for characterizing nozzle performance

4. Future Research Focus

While this Special Issue provides key insights into precision application strategies and technology, the path toward fully autonomous, highly effective, and environmentally sound plant protection necessitates addressing several complex, interconnected challenges. The following primary areas for future research focus are proposed.

4.1. Development of Fully Adaptive and Intelligent Systems

Future research must focus on integrating advanced sensing technologies (such as LiDAR, NDVI, thermal, or hyperspectral imaging) and machine learning algorithms (e.g., neural networks, SVMs) to create intelligent UASSs and ground sprayers capable of real-time adaptive parameter adjustment. These systems must dynamically adjust operational parameters—including flight altitude, speed, nozzle pressure, and auxiliary airflow intensity/angle—based on instantaneous field conditions, varying canopy architectures, and pest/weed development stages.

4.2. Expansion of Application Scope and Crop-Specific Protocols

Research should expand beyond the studied field crops (soybean, maize, and cotton) to investigate the adaptability of high-performance technologies (UAV wind fields, air-assisted spraying) in structurally diverse systems, such as dense orchards, vineyards, or tall cereal crops. This is essential for developing comprehensive, crop-specific operational protocols that maximize deposition efficiency and minimize yield risk across varied agricultural systems.

4.3. Fundamental Optimization of Atomizer Dynamics

There remains a need for an in-depth exploration of the relationship between nozzle internal structure, droplet velocity, and the relative span (RS) value. Optimization strategies should aim to increase droplet velocity and reduce RS without sacrificing droplet size, as this promises lower drift potential. Furthermore, research on rotary cage atomizers should be expanded by varying cage diameter gradients and investigating the influence of different mesh numbers and fluid additives to better control atomization characteristics for large-payload UAVs.

4.4. Long-Term Environmental and Economic Impact Assessment

To solidify the sustainability case for precision applications, researchers must conduct long-term ecological and environmental impact studies. This includes assessing pesticide residue dynamics in soil and water systems, quantifying the risk to non-target organisms (e.g., pollinators and beneficial insects), and calculating the overall carbon footprint of advanced operations compared to conventional methods.

4.5. Addressing Mechanization Gaps with Advanced Control

Given the confirmed impact of boom instability on drift risk, there is an urgent need to develop advanced, stable boom leveling systems and real-time height control technologies that are robust enough for high-speed operation in heterogeneous field terrain.

By focusing on these areas, the next generation of research will continue to bridge the gap between application science and agronomic reality, advancing the goal of precision agriculture to utilize minimal agrochemicals while sustaining global food production.