Orchard spraying can effectively control pests and diseases. Over-spraying commonly results in excessive pesticide residues on agricultural products and environmental pollution. To avoid these problems, variable spraying technology uses target canopy detection to evaluate the leaf area in a canopy and adjust the application rate accordingly. In this study, a mobile LiDAR detection platform was set up to automatically measure point cloud data for a thick canopy in an apple orchard. A test platform was built, and manual measurements of the canopy leaf area were taken. Then, polynomial regression, back propagation (BP) neural network regression, and partial least squares regression (PLSR) algorithms were used to study the relationship between the orchard tree canopy point clouds and leaf areas. The BP neural network algorithm (86.1% and 73.6% accuracies for the test and verification data, respectively) and the PLSR algorithm (78.46% and 60.3%, respectively) performed better than the Fourier function of the polynomial regression (59.73% accuracy). The leaf area model obtained using PLSR was intuitive and simple, while the BP neural network algorithm was more accurate and could meet the requirements for high-precision variable spraying.

Precision pesticide application mainly relies on canopy volume, resulting in varied application effectiveness across different density areas of orchard trees. This study examined pesticide application effectiveness based on the spray wind, canopy volume, and leaf area within the canopy, providing variable bases for precise regulation of spray wind and pesticide dosage. The study addresses the knowledge gap by utilizing laser detection and ranging (LiDAR) to measure the thickness and leaf area of orchard tree canopies. The spray experiments were conducted on canopies of different regions, using an air-assisted sprayer with varying fan speeds of 1381 r/min, 1502 r/min, and 1676 r/min. The deposition effects were analyzed using water-sensitive papers. The inlet air speed within the canopy did not increase proportionally when the spray fan speed increased, and it showed a significant variation in locations with sparse foliage. Furthermore, droplets exhibited abnormal median volume diameters of the canopy regions with lower wind loss rates and smaller leaf areas. The influences were in the order of canopy thickness, leaf area, and inlet air speed on the cumulative deposition of droplets on both sides of the water-sensitive papers, as well as the ratio of deposition between the two sides, from big to small, are inlet air speed, leaf area, and canopy thickness. The study provides a scientific foundation for air control in precision pesticide application in apple orchards and contributes to the rapid development of precision spraying technologies.

During variable-rate spraying in orchards, the atomization characteristics and distribution of droplets in and out of the target area can be affected by the sprayer pressure. In this study, a variable-rate spraying control system test bench was designed, and a hollow cone nozzle QY82.317.22 was selected. The droplet atomization characteristics, including volume median diameter (D_v0.5), the relative span of the droplet spectrum, and droplet velocity at different spray pressures, were studied at distances ranging from 0.4 to 2.4 m from the nozzle orifice with an air velocity of 10 m/s at the nozzle orifice position. The effects of longitudinal distance, transverse distance, and spray pressure on D_v0.5, relative span, and droplet velocity were analysed by multiple linear regression analysis, and the regression model was established. The experimental results show that at a longitudinal distance of 1.8 m, D_v0.5 ranges from 120 to 150 μm, meeting the requirements for optimal droplet size for controlling crawling pests and plant diseases on crop leaves; and the relative span is 1.2, indicating a wide droplet spectrum. At different pressure conditions, D_v0.5 decreases as pressure increases. Through multiple linear regression analysis, the longitudinal distance, the transverse distance, and the spray pressure have high significance for D_v0.5 and the droplet velocity. The longitudinal distance and the transverse distance have a highly significant effect on the relative span. In this study, the mathematical relational model of droplet characteristics at different spatial positions and different pressures was established, providing an agricultural reference for predicting the droplet characteristics at different spatial positions to achieve the best application effect. This model is conducive to the effective use of pesticides and reduces environmental pollution.

High-air temperature stress inhibits the growth of hydroponic lettuce. The practical application of conventional air cooling is constrained by high cost and moderate efficacy. However, root-zone cooling represents a more promising temperature regulation strategy for vegetable production, offering advantages such as ease of integration and lower cost. This study used lettuce (Spanish Green) as the plant material under four RZT treatments: T0 (control: 24.65~31.65 °C), T1 (24.5 °C), T2 (20.5 °C), and T3 (16.5 °C). Growth parameters and nutritional quality indicators under each treatment were systematically monitored, and a comprehensive evaluation was performed using the fuzzy membership function method. All cooling treatments (T1–T3) enhanced lettuce plant height, leaf area, and shoot dry weight. According to the fuzzy membership function analysis, the T1 treatment was found to exhibit the highest overall nutritional value. Although the T0 control group displayed the poorest growth performance, with a shoot dry weight 47.24% lower than that of T1, it accumulated significantly higher levels of P, Ca, and Zn. These findings demonstrate that regulating RZT to approximately 24.5 °C synergistically enhances both biomass and quality in lettuce, providing theoretical and practical support for optimizing hydroponic production in summer conditions.

Air-assisted spraying is the primary method of plant protection in orchards, and precision spraying according to the canopy characteristics of fruit trees can reduce waste and pollution due to pesticide drift. To facilitate targeted pesticide application in the canopy of fruit trees, this study employed a newly developed wind-speed-adjustable orchard sprayer and established a prediction model for deposition based on data from orthogonal trials using a central composite design accounting for the coupling effect of three-dimensional spatial parameters. The experimental design systematically quantified the interaction effects of spray distance (1.5–2.5 m), fan wind speed (10–20 m/s), and deposition height (0.5–3 m) on the spatial distribution of droplets. Model significance was p < 0.0001 and the misfit term was significant (p = 0.2193), supporting its validity. The research found that wind speed and distance significantly interact in influencing deposition. By adjusting fan speed and spray distance, variable applications can be achieved in different canopy zones during plant protection operations. The response surface model developed in this study can be applied to variable-rate spraying control systems, thus providing a quantitative basis for dynamic droplet control guided by canopy characteristics. Validation tests revealed that the model’s accuracy was lower in high canopy regions and upwind spraying scenarios, indicating areas for further research.

In the Nutrient Film Technique (NFT) system, air-temperature stress presents a severe challenge to the cultivation of hydroponic lettuce, often limiting its yield and quality during warm seasons. Although previous studies have confirmed that regulating air temperature can alleviate the stress on crops, challenges such as uneven temperature distribution and high equipment costs hinder effective air temperature management in greenhouse environments. In contrast, independently regulating root-zone temperature (RZT) under the same air-temperature stress conditions offers a more practical approach to enhancing crop growth, which can significantly improve crop outcomes without incurring substantial additional costs. This study used 'Spanish Green' lettuce as the test material and established four RZT treatments: T0 (control: 24.65–31.65℃), T1 (24.5℃), T2 (20.5℃), and T3 (16.5℃). Over a 38-day cultivation period, we systematically monitored the effects of different RZT treatments on lettuce growth parameters (such as plant height, leaf area, and shoot dry weight) and nutritional quality indicators (including vitamin C, nitrate, and mineral element content). The fuzzy membership function method was employed for a comprehensive evaluation of lettuce quality.The results showed that all cooling treatments (T1, T2, T3) promoted increases in plant height, leaf area, and shoot dry weight. Based on calculations from the fuzzy membership function, lettuce under treatment T1 achieved the best balance between growth performance and nutritional quality. Lettuce in treatment T0 exhibited the poorest growth; compared to T0, shoot dry weight increased by 47.24%, 16.24%, and 12.21% for treatments T1, T2, and T3, respectively. However, mineral element contents such as P, Ca, and Zn were significantly higher in treatment T0 than in the other three treatments. The overall quality of lettuce in treatment T2 was superior to that in T3; although T2 promoted growth relative to T0, its growth performance was significantly lower than that of T1, and both T2 and T3 exhibited a decline in overall growth quality. Nutrient solution consumption was highest for treatment T1 and lowest for treatment T0.This study demonstrates that independently regulating RZT to approximately 24.5℃ can achieve a synergistic enhancement of biomass and quality in lettuce, providing a theoretical basis and practical guidelines for optimizing NFT system production during summer conditions.