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Canopy characterization is essential for pesticide dosage adjustment according to vegetation volume and density. It is especially important for fresh exportable vegetables like greenhouse tomatoes. These plants are thin and tall and are planted in pairs, which makes their characterization with electronic methods difficult. Therefore, the accuracy of the terrestrial 2D LiDAR sensor is evaluated for determining canopy parameters related to volume and density and established useful correlations between manual and electronic parameters for leaf area estimation. Experiments were performed in three commercial tomato greenhouses with a paired plantation system. In the electronic characterization, a LiDAR sensor scanned the plant pairs from both sides. The canopy height, canopy width, canopy volume, and leaf area were obtained. From these, other important parameters were calculated, like the tree row volume, leaf wall area, leaf area index, and leaf area density. Manual measurements were found to overestimate the parameters compared with the LiDAR sensor. The canopy volume estimated with the scanner was found to be reliable for estimating the canopy height, volume, and density. Moreover, the LiDAR scanner could assess the high variability in canopy density along rows and hence is an important tool for generating canopy maps. [ABSTRACT FROM AUTHOR]

Spraying techniques have been undergoing continuous evolution in recent decades. This paper presents part of the research work carried out in Spain in the field of sensors for characterizing vineyard canopies and monitoring spray drift in order to improve vineyard spraying and make it more sustainable. Some methods and geostatistical procedures for mapping vineyard parameters are proposed, and the development of a variable rate sprayer is described. All these technologies are interesting in terms of adjusting the amount of pesticides applied to the target canopy. [ABSTRACT FROM AUTHOR]

The use of a scanning Light Detection and Ranging (LIDAR) system to characterize drift during pesticide application is described. The LIDAR system is compared with an ad hoc test bench used to quantify the amount of spray liquid moving beyond the canopy. Two sprayers were used during the field test; a conventional mist blower at two air flow rates (27,507 and 34,959 m³·h-1) equipped with two different nozzle types (conventional and air injection) and a multi row sprayer with individually oriented air outlets. A simple model based on a linear function was used to predict spray deposit using LIDAR measurements and to compare with the deposits measured over the test bench. Results showed differences in the effectiveness of the LIDAR sensor depending on the sprayed droplet size (nozzle type) and air intensity. For conventional mist blower and low air flow rate; the sensor detects a greater number of drift drops obtaining a better correlation (r = 0.91; p < 0.01) than for the case of coarse droplets or high air flow rate. In the case of the multi row sprayer; drift deposition in the test bench was very poor. In general; the use of the LIDAR sensor presents an interesting and easy technique to establish the potential drift of a specific spray situation as an adequate alternative for the evaluation of drift potential. [ABSTRACT FROM AUTHOR]

The use of electronic devices for canopy characterization has recently been widely discussed. Among such devices, LiDAR sensors appear to be the most accurate and precise. Information obtained with LiDAR sensors during reading while driving a tractor along a crop row can be managed and transformed into canopy density maps by evaluating the frequency of LiDAR returns. This paper describes a proposed methodology to obtain a georeferenced canopy map by combining the information obtained with LiDAR with that generated using a GPS receiver installed on top of a tractor. Data regarding the velocity of LiDAR measurements and UTM coordinates of each measured point on the canopy were obtained by applying the proposed transformation process. The process allows overlap of the canopy density map generated with the image of the intended measured area using Google Earth®, providing accurate information about the canopy distribution and/or location of damage along the rows. This methodology was applied and tested on different vine varieties and crop stages in two important vine production areas in Spain. The results indicate that the georeferenced information obtained with LiDAR sensors appears to be an interesting tool with the potential to improve crop management processes. [ABSTRACT FROM AUTHOR]

Canopy characterization is a key factor to improve pesticide application methods in tree crops and vineyards. Development of quick, easy and efficient methods to determine the fundamental parameters used to characterize canopy structure is thus an important need. In this research the use of ultrasonic and LIDAR sensors have been compared with the traditional manual and destructive canopy measurement procedure. For both methods the values of key parameters such as crop height, crop width, crop volume or leaf area have been compared. Obtained results indicate that an ultrasonic sensor is an appropriate tool to determine the average canopy characteristics, while a LIDAR sensor provides more accuracy and detailed information about the canopy. Good correlations have been obtained between crop volume (CVU) values measured with ultrasonic sensors and leaf area index, LAI (R2 = 0.51). A good correlation has also been obtained between the canopy volume measured with ultrasonic and LIDAR sensors (R2 = 0.52). Laser measurements of crop height (CHL) allow one to accurately predict the canopy volume. The proposed new technologies seems very appropriate as complementary tools to improve the efficiency of pesticide applications, although further improvements are still needed. [ABSTRACT FROM AUTHOR]

Pesticide application equipment (PAE) is the last part of the chain during the plant protection process. The use-phase of plant protection products (PPP) has been addressed in two EU Directives: 128/2009/EC and 127/2009/EC. This last one covers all the mandatory technical requirements to be fulfilled by new sprayers prior to their placement in the market. The objective of this research was to develop a potential decision support system (DSS) to evaluate and quantify the degree of implementation of all the required characteristics of new sprayers, including not only the mandatory requirements but also specifications widely described in the corresponding harmonized standard ISO 16119. It includes 10 independent elements of the sprayer, including a list of technical specifications listed in the applied standards ISO 16119 and ISO 16122. The relative influence of every one of the different elements has been quantified based on previous research. The algorithm enables the establishment of an objective relative classification of the sprayers to differentiate among different machines, mainly based on their quantified environmental contamination risk. The DSS can also discriminate among sprayers that should not reach the market due to their non-compliance with any of the mandatory requirements. [ABSTRACT FROM AUTHOR]

An orchard variable-rate sprayer applies the appropriate amount of plant protection products only where they are needed based on detection data from advanced sensors, a system that has attracted increasing attention. The latest developments in the detection unit, variable control unit, and signal-processing algorithm of the variable-rate sprayer are discussed. The detection of target position and volume is realized with an ultrasonic sensor, a laser scanning sensor, or other methods. The technology of real-time acquisition of foliage density, plant diseases and pests and their severity, as well as meteorological parameters needs further improvements. Among the three variable-flow-rate control units, pulse width modulation was the most widely used, followed by pressure-based, and variable concentration, which is preliminarily verified in the laboratory. The variable air supply control unit is tested both in the laboratory and in field experiments. The tree-row-volume model, the leaf-wall-area model, and the continuous application mode are widely used algorithms. Advanced research on a variable-rate sprayer is analyzed and future prospects are pointed out. A laser-based variable-rate intelligent sprayer equipped with pulse width modulation solenoid valves to tune spray outputs in real time based on target structures may have the potential to be successfully adopted by growers on a large scale in the foreseeable future. It will be a future research direction to develop an intelligent multi-sensor-fusion variable-rate sprayer based on target crop characteristics, plant diseases and pests and their severity, as well as meteorological conditions while achieving multi-variable control. [ABSTRACT FROM AUTHOR]

Canopy characterisation is a key factor for the success and efficiency of the pesticide application process in vineyards. Canopy measurements to determine the optimal volume rate are currently conducted manually, which is time-consuming and limits the adoption of precise methods for volume rate selection. Therefore, automated methods for canopy characterisation must be established using a rapid and reliable technology capable of providing precise information about crop structure. This research providedregression models for obtaining canopy characteristics of vineyards from unmanned aerial vehicle (UAV) and satellite images collected in three significant growth stages. Between 2018 and 2019, a total of 1400 vines were characterised manually and remotely using a UAV and a satellite-based technology. The information collected from the sampled vines was analysed by two different procedures. First, a linear relationship between the manual and remote sensing data was investigated considering every single vine as a data point. Second, the vines were clustered based on three vigour levels in the parcel, and regression models were fitted to the average values of the ground-based and remote sensing-estimated canopy parameters. Remote sensing could detect the changes in canopy characteristics associated with vegetation growth. The combination of normalised differential vegetation index (NDVI) and projected area extracted from the UAV images is correlated with the tree row volume (TRV) when raw point data were used. This relationship was improved and extended to canopy height, width, leaf wall area, and TRV when the data were clustered. Similarly, satellite-based NDVI yielded moderate coefficients of determination for canopy width with raw point data, and for canopy width, height, and TRV when the vines were clustered according to the vigour. The proposed approach should facilitate the estimation of canopy characteristics in each area of a field using a cost-effective, simple, and reliable technology, allowing variable rate application in vineyards. [ABSTRACT FROM AUTHOR]

Accurate crown characterization of large isolated olive trees is vital for adjusting spray doses in three-dimensional crop agriculture. Among the many methodologies available, laser sensors have proved to be the most reliable and accurate. However, their operation is time consuming and requires specialist knowledge and so a simpler crown characterization method is required. To this end, three methods were evaluated and compared with LiDAR measurements to determine their accuracy: Vertical Crown Projected Area method (VCPA), Ellipsoid Volume method (VE) and Tree Silhouette Volume method (VTS). Trials were performed in three different kinds of olive tree plantations: intensive, adapted one-trunked traditional and traditional. In total, 55 trees were characterized. Results show that all three methods are appropriate to estimate the crown volume, reaching high coefficients of determination: R² = 0.783, 0.843 and 0.824 for VCPA, VE and VTS, respectively. However, discrepancies arise when evaluating tree plantations separately, especially for traditional trees. Here, correlations between LiDAR volume and other parameters showed that the Mean Vector calculated for VCPA method showed the highest correlation for traditional trees, thus its use in traditional plantations is highly recommended. [ABSTRACT FROM AUTHOR]

The photocatalytic and electrocatalytic conversion of CO2 has the potential to provide valuable products, such as chemicals or fuels of interest, at low cost while maintaining a circular carbon cycle. In this context, carbon dots possess optical and electrochemical properties that make them suitable candidates to participate in the reaction, either as a single component or forming part of more elaborate catalytic systems. In this review, we describe several strategies where the carbon dots participate, both with amorphous and graphitic structures, in the photocatalysis or electrochemical catalysis of CO2 to provide different carbon-containing products of interest. The role of the carbon dots is analyzed as a function of their redox and light absorption characteristics and their complementarity with other known catalytic systems. Moreover, detailed information about synthetic procedures is also reviewed. [ABSTRACT FROM AUTHOR]

Electronic canopy characterization is an important issue in tree crop management. Ultrasonic and optical sensors are the most used for this purpose. The objective of this work was to assess the performance of an ultrasonic sensor under laboratory and field conditions in order to provide reliable estimations of distance measurements to apple tree canopies. To this purpose, a methodology has been designed to analyze sensor performance in relation to foliage ranging and to interferences with adjacent sensors when working simultaneously. Results show that the average error in distance measurement using the ultrasonic sensor in laboratory conditions is ±0.53 cm. However, the increase of variability in field conditions reduces the accuracy of this kind of sensors when estimating distances to canopies. The average error in such situations is ±5.11 cm. When analyzing interferences of adjacent sensors 30 cm apart, the average error is ±17.46 cm. When sensors are separated 60 cm, the average error is ±9.29 cm. The ultrasonic sensor tested has been proven to be suitable to estimate distances to the canopy in field conditions when sensors are 60 cm apart or more and could, therefore, be used in a system to estimate structural canopy parameters in precision horticulture. [ABSTRACT FROM AUTHOR]

Visual navigation is developing rapidly and is of great significance to improve agricultural automation. The most important issue involved in visual navigation is extracting a guidance path from agricultural field images. Traditional image segmentation methods may fail to work in paddy field, for the colors of weed, duckweed, and eutrophic water surface are very similar to those of real rice seedings. To deal with these problems, a crop row segmentation and detection algorithm, designed for complex paddy fields, is proposed. Firstly, the original image is transformed to the grayscale image and then the treble-classification Otsu method classifies the pixels in the grayscale image into three clusters according to their gray values. Secondly, the binary image is divided into several horizontal strips, and feature points representing green plants are extracted. Lastly, the proposed double-dimensional adaptive clustering method, which can deal with gaps inside a single crop row and misleading points between real crop rows, is applied to obtain the clusters of real crop rows and the corresponding fitting line. Quantitative validation tests of efficiency and accuracy have proven that the combination of these two methods constitutes a new robust integrated solution, with attitude error and distance error within 0.02° and 10 pixels, respectively. The proposed method achieved better quantitative results than the detection method based on typical Otsu under various conditions. [ABSTRACT FROM AUTHOR]

We evaluate the potential of using a process-based ecosystem model (BEPS) for crop biomass mapping at 20 m resolution over the research site in Manitoba, western Canada driven by spatially explicit leaf area index (LAI) retrieved from Sentinel-2 spectral reflectance throughout the entire growing season. We find that overall, the BEPS-simulated crop gross primary production (GPP), net primary production (NPP), and LAI time-series can explain 82%, 83%, and 85%, respectively, of the variation in the above-ground biomass (AGB) for six selected annual crops, while an application of individual crop LAI explains only 50% of the variation in AGB. The linear relationships between the AGB and these three indicators (GPP, NPP and LAI time-series) are rather high for the six crops, while the slopes of the regression models vary for individual crop type, indicating the need for calibration of key photosynthetic parameters and carbon allocation coefficients. This study demonstrates that accumulated GPP and NPP derived from an ecosystem model, driven by Sentinel-2 LAI data and abiotic data, can be effectively used for crop AGB mapping; the temporal information from LAI is also effective in AGB mapping for some crop types. [ABSTRACT FROM AUTHOR]

Agitation inside agricultural sprayer tanks can be studied while using an international standard procedure, based on obtaining internal samples of liquid. However, in practice, this test is not easy to perform. Herein, we propose the explicit study of the mixing procedure with biphasic computer simulations using Computational Fluid Dynamics (CFD). An experimental test was performed on a 3000 L tank of a commercial air-assisted sprayer, with two different agitation system configurations, in order to compare the results of several theoretical physical models of biphasic flows for CFD, both Eulerian and Lagrangian. From the analysis of these theoretical models, we conclude that the Volume of Fluid model is not viable and the Discrete Phase Model produces erroneous results, while the Eulerian and Mixture models can both be useful. However, the results obtained suggest that complex streams generated by real-world agitation systems produce more errors in calculations. Both models can be conducted in the design phase, prior to the implementation of the machine. In addition, the computer simulations allow for researchers to analyse the mixing process in detail, making it possible to evaluate the efficiency of an agitation system according to the time that is required to reach mixture homogeneity. [ABSTRACT FROM AUTHOR]

Canopy characteristics are crucial for accurately and safely determining the pesticide quantity and volume of water used for spray applications in vineyards. The inevitably high degree of intraplot variability makes it difficult to develop a global solution for the optimal volume application rate. Here, the design procedure of, and the results obtained from, a variable rate application (VRA) sprayer are presented. Prescription maps were generated after detailed canopy characterization, using a multispectral camera embedded on an unmanned aerial vehicle, throughout the entire growing season in Torrelavit (Barcelona) in four vineyard plots of Chardonnay (2.35 ha), Merlot (2.97 ha), and Cabernet Sauvignonn (4.67 ha). The maps were obtained by merging multispectral images with information provided by DOSAVIÑA®, a decision support system, to determine the optimal volume rate. They were then uploaded to the VRA prototype, obtaining actual variable application maps after the application processes were complete. The prototype had an adequate spray distribution quality, with coverage values in the range of 20–40% and exhibited similar results in terms of biological efficacy on powdery mildew compared to conventional (and constant) application volumes. The VRA results demonstrated an accurate and reasonable pesticide distribution, with potential for reduced disease damage even in cases with reduced amounts of plant protection products and water. [ABSTRACT FROM AUTHOR]

A computational fluid dynamics (CFD) model of the fluid velocities generated by the agitation system of an air-assisted sprayer was developed and validated by practical experiments in a laboratory. The model was developed considering different settings of the agitation system: Three water levels in the tank (1000, 2000, and 3000 L); two different numbers of active nozzles (2 or 4); and three working pressures of the agitation circuit (8, 10, or 12 bar). Actual measurements of the fluid velocity into the tank were taken using an acoustic Doppler velocimeter (ADV). CFD simulations made it possible to estimate fluid velocities at 38% of the measuring points with relative errors of less than 30%. Additionally, the CFD models have allowed the correct prediction of the general behavior of the fluid in the tank considering mean velocities depending on the setting parameters of the agitation system (water level in the tank, hydraulic circuit pressure, and number of active nozzles). [ABSTRACT FROM AUTHOR]

An acoustic Doppler velocimeter (ADV) was used to analyse the impact of an agricultural sprayer's agitation system settings on fluid velocities inside the tank. A 3000 L capacity sprayer equipped with a 4-nozzle hydraulic agitation system was used. ADV measurements were carried at 32 points inside the tank under the following settings: circuit pressures of 8, 10, or 12 bar; water level in the tank of 1000, 2000, or 3000 L; 2 or 4 active nozzles. An agitation test with a concentration of 0.4% copper oxychloride was employed to analyse the concentration of active matter as a function of tank fill level and number of active nozzles. All parameters significantly affected the fluid velocity, which increased with increasing pressure, but decreased with increasing water level in the tank and an increased number of active nozzles. Concentration tests showed greater active matter concentrations when higher velocities were recorded by the ADV. The ADV was shown to be a useful tool for the rapid assessment of fluid velocities; in the future, it could be used to validate the design of agitation systems, and to estimate their capacity to ensure an adequate level of active matter concentration in the fluid. [ABSTRACT FROM AUTHOR]