Assessing the potential spray drift of a six-rotor unmanned aerial vehicle sprayer using a test bench and airborne drift collectors under low wind velocities: impact of atomization characteristics and application parameters.

Background: The unmanned aerial spraying systems (UASS) have gained widespread use for plant protection in recent years. However, spray drift from UASS is a major concern when controlling weeds over large areas and warrants a thorough investigation. This study examined the atomization characteristics of the herbicide florpyrauxifen-benzyl under downwash airflow using a UASS spray test platform.

Effects of different ground segmentation methods on the accuracy of UAV-based canopy volume measurements.

The nonuniform distribution of fruit tree canopies in space poses a challenge for precision management. In recent years, with the development of Structure from Motion (SFM) technology, unmanned aerial vehicle (UAV) remote sensing has been widely used to measure canopy features in orchards to balance efficiency and accuracy. A pipeline of canopy volume measurement based on UAV remote sensing was developed, in which RGB and digital surface model (DSM) orthophotos were constructed from captured RGB images, and then the canopy was segmented using U-Net, OTSU, and RANSAC methods, and the volume was calculated.

Toward a remote sensing method based on commercial LiDAR sensors for the measurement of spray drift and potential drift reduction.

Spray drift is inevitable in chemical applications, drawing global attention because of its potential environmental pollution and the risk of exposing bystanders to pesticides. This issue has become more pronounced with a growing consensus on the need for enhanced environmental safeguards in agricultural practices. Traditionally, spray drift measurements, crucial for refining spray techniques, relied on intricate, time-consuming, and labor-intensive sampling methods utilizing passive collectors.

Spray performance and control efficacy against pests in paddy rice by UAV-based pesticide application: effects of atomization, UAV configuration and flight velocity.

Background: Over the past decade, unmanned aerial vehicle (UAV) sprayers have emerged as valuable tools for pesticide application across various crops. Despite their increasing usage, the impact of several factors on spray performance and control efficacy in paddy fields warrants further investigation. This study examines atomization characteristics using a UAV spray test platform.

Effect of adjuvants on physicochemical properties of lime sulfur on flower/paraffin and application on flower thinning.

Introduction: Adjuvants can effectively enhance the utilization rate of pesticides, but the application of adjuvants in plant growth regulators is rarely studied.

Methods: This work explored the effects of adjuvants dioctyl sulfosuccinate sodium salt (AOT) and methyl oleate (MO) on lime sulfur (LS), especially the drop behavior on flower and paraffin surface.

Results: The results showed that the addition of AOT and AOT+MO can significantly reduce the static and dynamic surface tension of LS from 72mN/m to 28mN/m and 32mN/m respectively, and increase the spreading factor from 0.

Changes of cropping structure lead diversity decline in China during 1985-2015.

China's agriculture is in the transformation and development stage to adapt to the influences of climate change, technological progress and the requirements for resources and environmental protection. Optimization of cropping structure variation in the new stage is urgent. Our study systematically described the spatiotemporal variation in crop patterns in China from 1985 to 2015 and further analyzed the changes in cropping diversity and dominant cropping structure based on a county-level agricultural database.

Field evaluation of a six-rotor unmanned agricultural aerial sprayer: effects of application parameters on spray deposition and control efficacy against rice planthopper.

Background: Unmanned Aerial Spraying System (UASS) has emerged as an advanced, precise, and efficient tool for pesticide application in numerous nations in recent years. Despite this, there is a noticeable gap in research advocating viable, quantifiable methodologies for application parameter optimization. This investigation was primarily oriented toward identifying optimal UASS application parameters.

Nano-based smart formulations: A potential solution to the hazardous effects of pesticide on the environment.

Inefficient usage, overdose, and post-application losses of conventional pesticides have resulted in severe ecological and environmental issues, such as pesticide resistance, environmental contamination, and soil degradation. Advances in nano-based smart formulations are promising novel methods to decrease the hazardous impacts of pesticide on the environment. In light of the lack of a systematic and critical summary of these aspects, this work has been structured to critically assess the roles and specific mechanisms of smart nanoformulations (NFs) in mitigating the adverse impacts of pesticide on the environment, along with an evaluation of their final environmental fate, safety, and application prospects.

The pattern of abandoned cropland and its productivity potential in China: A four-years continuous study.

The increased requirement of food production with the rising population challenges limited cultivation land in China. The abandoned cropland has high potential in grain production to ensure China's food security. However, the spatial distributions of abandoned cropland in China are understudied and therefore it is difficult to estimate its potential grain production.

Field evaluation of spray drift and nontargeted soybean injury from unmanned aerial spraying system herbicide application under acceptable operation conditions.

Background: Droplets of plant production products sprayed from unmanned aerial spraying system (UASS) applications are prone to drift, threatening nontarget crops, humans, and environment. There are few studies that have investigated plant bioassay of UASS spray drift, and even fewer when it comes to herbicide application. This work reports a combined field-scale evaluation of spray drift and plant bioassay for a rice herbicide florpyrauxifen-benzyl application using a six-rotor motor UASS under acceptable operating conditions.

Comprehensive assessment of intelligent unmanned vehicle techniques in pesticide application: A case study in pear orchard.

The intelligent pesticide application techniques in orchards have grown rapidly worldwide due to the decrease in agricultural populations and the increase in labor costs. However, whether and how intelligent pesticide application techniques are better than conventional pesticide application remains unclear. Here, we evaluated the performance of the unmanned aircraft vehicle (UAV) and unmanned ground vehicle (UGV) on pesticide application, ecological environment protection, and human's health protection compared to conventional manual methods.

Design and development of orchard autonomous navigation spray system.

Driven by the demand for efficient plant protection in orchards, the autonomous navigation system for orchards is hereby designed and developed in this study. According to the three modules of unmanned system "perception-decision-control," the environment perception and map construction strategy based on 3D lidar is constructed for the complex environment in orchards. At the same time, millimeter-wave radar is further selected for multi-source information fusion for the perception of obstacles.

Development of multifunctional unmanned aerial vehicles versus ground seeding and outplanting: What is more effective for improving the growth and quality of rice culture?

The agronomic processes are complex in rice production. The mechanization efficiency is low in seeding, fertilization, and pesticide application, which is labor-intensive and time-consuming. Currently, many kinds of research focus on the single operation of UAVs on rice, but there is a paucity of comprehensive applications for the whole process of seeding, fertilization, and pesticide application.

Rh(I)-Catalyzed Coupling of Azides with Boronic Acids Under Neutral Conditions.

Because of the importance of polyfunctional amines, C-N bond formation is important in synthetic organic chemistry. Here we present a neutral amination reaction using azides as the nitrogen source and arylboronic acids with a rhodium(I) catalyst to afford alkyl-aryl and aryl-aryl secondary amines. Natural products and pharmaceutical derivatives were applied, and gram-scale reactions were performed, which demonstrated the utility.

Weed Density Extraction Based on Few-Shot Learning Through UAV Remote Sensing RGB and Multispectral Images in Ecological Irrigation Area.

With the development of ecological irrigation area, a higher level of detection and control categories for weeds are currently required. In this article, an improved transfer neural network based on bionic optimization to detect weed density and crop growth is proposed, which used the pre-trained AlexNet network for transfer learning. Because the learning rate of the new addition layer is difficult to tune to the best, the weight and bias learning rate of the newly added fully connected layer is set with particle swarm optimization (PSO) and bat algorithm (BA) to find the optimal combination on the small data set.

Spray performance evaluation of a six-rotor unmanned aerial vehicle sprayer for pesticide application using an orchard operation mode in apple orchards.

Background: In the last decade, unmanned aerial vehicle (UAV) sprayers have been growing rapidly worldwide as a new method for pesticide application, especially in Asian countries. More and more manufacturers and service providers are currently aiming at UAV spraying operation for fruit trees with higher economic value. We evaluated the spray performance of an electric six-rotor UAV sprayer using an orchard operation mode (different application volumes and flight patterns) in a hilly apple orchard with small and sparse trees (SS) and a plain orchard with tall-spindle trees (TS).

An adaptive composite disturbance rejection for attitude control of the agricultural quadrotor UAV.

Aiming at the problem that agricultural quadrotor UAV is easily disturbed in ultra-low altitude phenotype remote sensing and precision hovering of spraying, an adaptive composite anti-disturbance attitude controller is proposed for ground effect and propeller failure disturbances rejection. The adaptive composite disturbance rejection control (ACDRC) is composed of active disturbance rejection control (ADRC) and disturbance observer (DO) based on nominal inverse model, which is used to estimate wind disturbance, payload disturbance and propeller failure disturbance in real time. For the bandwidth tuning of the extended state observer (ESO), an online tuning method based on iterative learning control (ILC) is proposed to realize the adaptive extended state observer (ESO).

Diagnosis of Typical Apple Diseases: A Deep Learning Method Based on Multi-Scale Dense Classification Network.

Disease has always been one of the main reasons for the decline of apple quality and yield, which directly harms the development of agricultural economy. Therefore, precise diagnosis of apple diseases and correct decision making are important measures to reduce agricultural losses and promote economic growth. In this paper, a novel Multi-scale Dense classification network is adopted to realize the diagnosis of 11 types of images, including healthy and diseased apple fruits and leaves.

Assessment of spray deposition, drift and mass balance from unmanned aerial vehicle sprayer using an artificial vineyard.

Under the rapid development of unmanned aerial vehicle (UAV) plant protection products (PPP) application in Asian countries, the drift risk of UAV sprayer operation in orchard or vineyard is fairly high because of the much finer droplets generated and the higher height than ground sprayers, increasing threats to non-targeted crop, human and environment. However, there is few of comprehensive experimental study on the effects of UAV type and nozzle type on spray deposition and drift from UAV sprayer. The objectives of this study were to compare the spray performance of three different typical commercial UAV types (helicopter, 6-rotor and 8-rotor) with two nozzles types (hollow cone nozzle, HCN and air-injector flat fan nozzle, AIN) in vineyard.

Butyrylcholinesterase nanodepots with enhanced prophylactic and therapeutic performance for acute organophosphorus poisoning management.

Acute organophosphorus pesticide poisoning (AOPP) is a worldwide health concern that has threatened human lives for decades, which attacks acetylcholinesterase (AChE) and causes nervous system disorders. Classical treatment options are associated with short in vivo half-life and side effects. As a potential alternative, delivery of mammalian-derived butyrylcholinesterase (BChE) offers a cost-effective way to block organophosphorus attack on acetylcholinesterase, a key enzyme in the neurotransmitter cycle.

Pocket-based Lead Optimization Strategy for the Design and Synthesis of Chitinase Inhibitors.

Insect chitinases play an indispensable role in shedding old cuticle during molting. Targeting chitinase inhibition is a promising pest control strategy. Of ChtI, a chitinase from the destructive insect pest Ostrinia furnacalis (Asian corn borer), has been suggested as a potential target for designing green pesticides.

Structure-Based Virtual Screening, Compound Synthesis, and Bioassay for the Design of Chitinase Inhibitors.

Chitinases play a vital part in the molting phase of insect pests. Inhibiting their activities by the use of drug-like small chemical molecules is thought to be an efficient strategy in pesticide design and development. On the basis of the crystal structure of OfChtI, a chitinase indispensable for the molting of the insect pest Ostrinia furnacalis (Asian corn borer), here we report a chemical fragment and five variant compounds as inhibitors of OfChtI obtained from a library of over 200 000 chemicals by a structure-based-virtual-screening approach.