Dataset Information

Sustained Agricultural Spraying: From Leaf Wettability to Dynamic Droplet Impact Behavior.

ABSTRACT: Crop production and quality safety system have the potential to nurture human health and improve environmental sustainability. Providing a growing global population with sufficient and healthy food is an immediate challenge. However, this system largely depends on the spraying of agrochemicals. Crop leaves are covered with different microstructures, exhibiting distinct hydrophilic, hydrophobic, or even superhydrophobic wetting characteristics, thus leading to various deposition difficulties of sprayed droplets. Here, the relationship between wettability and surface microstructure in different crop leaves from biological and interfacial structural perspectives is systematically demonstrated. A relational model is proposed in which complex microstructures lead to stronger leaf hydrophobicity. And adding surfactant with a faster dynamically migrating velocity and reducing droplet size can improve agrochemical precise deposition. These contribute toward highly accurate and efficient targeted applications with fewer agrochemicals use and promote sustainable models of eco-friendly agriculture systems.

SUBMITTER: Wang B

PROVIDER: S-EPMC10517293 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Sustained Agricultural Spraying: From Leaf Wettability to Dynamic Droplet Impact Behavior.

Wang Bo B Wang Jie J Yu Cunlong C Luo Siqi S Peng Jia J Li Ning N Wang Tengda T Jiang Lei L Dong Zhichao Z Wang Yilin Y

Global challenges (Hoboken, NJ) 20230719 9

Crop production and quality safety system have the potential to nurture human health and improve environmental sustainability. Providing a growing global population with sufficient and healthy food is an immediate challenge. However, this system largely depends on the spraying of agrochemicals. Crop leaves are covered with different microstructures, exhibiting distinct hydrophilic, hydrophobic, or even superhydrophobic wetting characteristics, thus leading to various deposition difficulties of s ...[more]

PMID: 37745823

Similar Datasets

Project description:Adding tank-mix adjuvants into the spray mixture is a common practice to improve droplet distribution for field crops (e.g., rice, wheat, corn, etc.) when using Unmanned Aerial Vehicle (UAV) sprayers. However, the effectiveness of tank-mix adjuvant for UAV spraying in orchard crops is still an open problem, considering their special canopy structure and leaf features. This study aims to evaluate the effects of a typical tank-mix adjuvant concentrations (i.e., Nong Jian Fei (NJF)) on Contact Angle (CA) and droplet distribution in the citrus tree canopy. Three commonly used parameters, namely dynamic CA, droplet coverage, and Volume Median Diameter (VMD), are adopted for performance evaluation. The dynamic CAs on the adaxial surface of citrus leaves, for water-only and NJF-presence sprays, respectively, are measured with five concentration levels, where three replications are performed for each concentration. The sprays with 0.5‰ NJF are adopted in the field experiment for evaluating droplet distributions, where Water Sensitive Papers (WSPs) are used as collectors. Two multi-rotor UAVs (DJI T20 and T30) which consist of different sizes of pesticide tanks and rotor diameters are used as the spraying platforms. Both water-only and NJF-presence treatments are conducted for the two UAVs, respectively. The results of the CA experiment show that NJF addition can significantly reduce the CAs of the sprays. The sprays with 0.5‰ NJF obtain the lowest CA within the observing time, suggesting a better spread ability on solid surface (e.g., WSPs or/and leaves). With respect to the effects of NJF addition on individual UAVs, the field trial results indicate that NJF addition can remarkably increase both the droplet coverage and VMD at three canopy layers, except for T30 droplet coverage of the inside and bottom layers. Comparing the difference of droplet coverage between two UAVs, while significant difference is found in the same layer before NJF addition, there is no notable difference appearing in the outside and bottom layers after NJF addition. The difference of VMD in the same layer between two UAVs is not affected by NJF addition except for the bottom layer. These results imply that the differences of droplet coverage among different UAVs might be mitigated, thus the droplet distribution of some UAVs could be improved by adding a tank-mix adjuvant into the sprays. This hypothesis is verified by investigating the droplet penetration and the correlation coefficient (CC) of droplet coverage and VMD. After NJF addition, the total percentage of T20 droplet coverage in the bottom and inside layers is increased by 5%. For both UAVs, the CCs indicate that both droplet coverage and VMD increase at the same time in most cases after NJF addition. In conclusion, the addition of a tank-mix adjuvant with the ability to reduce CA of the sprays, can effectively improve droplet distribution using UAV spraying in the citrus canopy by increasing droplet coverage and VMD.

Dataset Information

Sustained Agricultural Spraying: From Leaf Wettability to Dynamic Droplet Impact Behavior.

Publications

Sustained Agricultural Spraying: From Leaf Wettability to Dynamic Droplet Impact Behavior.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets