A Canopy Density Model for Planar Orchard Target Detection Based on Ultrasonic Sensors

Weather conditions can affect sensors’ readings when sampling outdoors. Although sensors are usually set up covering a wide range of conditions, their operational range must be established. In recent years, depth cameras have been shown as a promising tool for plant phenotyping and other related uses. However, the use of these devices is still challenged by prevailing field conditions. Although the influence of lighting conditions on the performance of these cameras has already been established, the effect of wind is still unknown. This study establishes the associated errors when modeling some tree characteristics at different wind speeds. A system using a Kinect v2 sensor and a custom software was tested from null wind speed up to 10 m·s−1. Two tree species with contrasting architecture, poplars and plums, were used as model plants. The results showed different responses depending on tree species and wind speed. Estimations of Leaf Area (LA) and tree volume were generally more consistent at high wind speeds in plum trees. Poplars were particularly affected by wind speeds higher than 5 m·s−1. On the contrary, height measurements were more consistent for poplars than for plum trees. These results show that the use of depth cameras for tree characterization must take into consideration wind conditions in the field. In general, 5 m·s−1 (18 km·h−1) could be established as a conservative limit for good estimations.

Section: Introductionmentioning

confidence: 99%

Influence of Wind Speed on RGB-D Images in Tree Plantations

Andújar

Dorado

Bengochea-Guevara

et al. 2017

“…The canopy density is measured by dividing the number of leaves of a tree by the total leaf canopy area. Li et al [ 51 ] utilized an ultrasonic-sensing method to build the relationship between canopy density and leaf layers using an orthogonal regression rotation test. The maximum relative errors were 29.92%, 21.33%, 25.64%, and 17.68% between the model values and the actual values.…”

Section: Core Components and Technologies For Precision Sprayingmentioning

confidence: 99%

Opportunities and Possibilities of Developing an Advanced Precision Spraying System for Tree Fruits

Mahmud

Zahid

et al. 2021

Reducing risk from pesticide applications has been gaining serious attention in the last few decades due to the significant damage to human health, environment, and ecosystems. Pesticide applications are an essential part of current agriculture, enhancing cultivated crop productivity and quality and preventing losses of up to 45% of the world food supply. However, inappropriate and excessive use of pesticides is a major rising concern. Precision spraying addresses these concerns by precisely and efficiently applying pesticides to the target area and substantially reducing pesticide usage while maintaining efficacy at preventing crop losses. This review provides a systematic summary of current technologies used for precision spraying in tree fruits and highlights their potential, briefly discusses factors affecting spraying parameters, and concludes with possible solutions to reduce excessive agrochemical uses. We conclude there is a critical need for appropriate sensing techniques that can accurately detect the target. In addition, air jet velocity, travel speed, wind speed and direction, droplet size, and canopy characteristics need to be considered for successful droplet deposition by the spraying system. Assessment of terrain is important when field elevation has significant variability. Control of airflow during spraying is another important parameter that needs to be considered. Incorporation of these variables in precision spraying systems will optimize spray decisions and help reduce excessive agrochemical applications.

“…The CCD was used to design the four structural parameters and obtain 16 cubic points, eight axial points, and one center point, which The central composite design can analyze the importance of factors and the interactive responses between factors. CCD is widely used in chemical reagent ratios and processing technology optimization [54,55]. In 2006, Idris et al conducted a central composite design study and built a response surface methodology to identify the essential interfacial reaction factors that influence membrane performance [56].…”

Section: Endurance Time Response Surfacementioning

confidence: 99%

Development of Response Surface Model of Endurance Time and Structural Parameter Optimization for a Tailsitter UAV

Yao

Liu

Han

et al. 2020

This study designed a vertical take-off and landing tailsitter unmanned aerial vehicle (UAV) with a long endurance time. Nine parameters of the tailsitter UAV were investigated. Using a 2k full factorial test, 512 experiments on the nine parameters were conducted at their maximum and minimum values. The time coefficient and air resistance were calculated using the computational fluid dynamics (CFD) method under different parameter combinations. The analysis of variance determined that the specific factors influencing the time coefficient and air resistance were the root chord, wingtip chord, wingspan, and sweep angle. By carrying out a central composite design (CCD) test, 25 sample points of the four particular factors were constructed. The time coefficient and air resistance were simulated under different structural parameter combinations using the CFD method. CFD simulation was verified by carrying out a wind tunnel test, and the results revealed that the aerodynamic coefficient error was less than 5%, while the air resistance error was less than 6%. The response surface methodology (RSM) for the time coefficient and air resistance was established using a genetic aggregation method. A multi-objective genetic algorithm (MOGA) was used to optimize the parameters with regard to the maximum time coefficient and minimum air resistance. The optimal structural parameters were wing root chord length at 315 mm, wingtip chord length at 182 mm, wingspan length at 1198 mm, and sweep angle at 16°. Compared with the original layout and size, the time coefficient of the new design of the tailsitter UAV improved by 19.5%, while the air resistance reduced by 34.78%. The results obtained by this study are significant for the design of tailsitter UAVs.