Unmanned aerial vehicle based tree canopy characteristics measurement for precision spray applications

The critical components for applying the correct amount of agrochemicals are fruit tree characteristics such as canopy height, canopy volume, and canopy coverage. An unmanned aerial vehicle (UAV)-based tree canopy characteristics measurement system was developed using image processing approaches. The UAV captured images using a high-resolution red-green-blue (RGB) camera. A digital surface model (DSM) and a digital terrain model (DTM) were generated from the captured images. A tree canopy height map was generated from the subtraction of DSM and DTM. A total of 24 apple trees were randomly targeted to measure the canopy characteristics. Region of interest (ROI) was generated across the boundary of each targeted tree. The height of all pixels within each ROI was computed separately. The pixel with maximum height was considered as the height of the respective tree. For computing canopy volume, the sum of all pixel heights from individual ROI was multiplied by the square of ground sample distance (GSD) of 5.69 mm·pixel−1. A segmentation method was employed to calculate the canopy coverage of the individual trees. The segmented canopy pixel area was divided by the total pixel area within the ROI. The results showed an average relative error of 0.2 m(6.64%) while comparing automatically measured tree height with ground measurements. For tree canopy volume, a mean absolute error of 0.25 m3 and a root mean square error of 0.33 m3 were achieved. The study estimated the possible agrochemical requirement for spraying the fruit trees, ranging from 0.1 to 0.32 l based on tree canopy volumes. The overall investigations suggest that the UAV-based tree canopy characteristics measurements could be a potential tool to calculate the pesticide requirement for precision spraying applications in tree fruit orchards

In-situ fruit analysis by means of LiDAR 3D point cloud of normalized difference vegetation index (NDVI)

A feasible method to analyse fruit at the tree is requested in precise production management. The employment of light detection and ranging (LiDAR) was approached aimed at measuring the number of fruit, quality-related size, and ripeness-related chlorophyll of fruit skin. During fruit development (65 – 130 day after full bloom, DAFB), apples were harvested and analysed in the laboratory (n = 225) with two LiDAR laser scanners measuring at 660 and 905 nm. From these two 3D point clouds, the normalized difference vegetation index (NDVILiDAR) was calculated. The correlation analysis of NDVILiDAR and chemically analysed fruit chlorophyll content showed R2 = 0.81 and RMSE = 3.63 % on the last measuring date, when fruit size reached 76 mm. The method was tested on 3D point clouds of 12 fruit trees measured directly in the orchard, during fruit growth on five measuring dates, and validated with manual fruit analysis in the orchard (n = 4632). Point clouds of individual apples were segmented from 3D point clouds of trees and fruit NDVILiDAR were calculated. The non-invasively obtained field data showed good calibration performance capturing number of fruit, fruit size, fruit NDVILiDAR, and chemically analysed chlorophyll content of R2 = 0.99, R2 = 0.98 with RMSE = 3.02 %, R2 = 0.65 with RMSE = 0.65 %, R2 = 0.78 with RMSE = 1.31 %, respectively, considering the related reference data at last measuring date 130 DAFB. The new approach of non-invasive laser scanning provided physiologically and agronomically valuable time series data on differences in fruit chlorophyll affected by the leaf area to number of fruit and leaf area to fruit fresh mass ratios. Concluding, the method provides a tool for gaining production-relevant plant data for, e.g., crop load management and selective harvesting by harvest robots

Strategies for the optimization of the efficiency in the plant protection product applications in olive canopies

Pesticide applications are necessary to guarantee the proper development of crops and, therefore, to ensure the profitability for the farmer. However, their mismanagement in last years has led to important environmental problems, triggering the emergence of a generalized animosity towards these practices. The European Administration, by taking into account this social concern, has developed a restrictive legal framework to guarantee the sustainability of treatments through their rationalization. In the case of olive, a very important crop in Spain, this problem is especially critical because of three main reasons. First, it is very concentrated in the Guadalquivir river basin, what makes the negative impacts to be very intense in the area, Next, the lack of knowledge and training makes farmers and technicians to not to be able to properly plan the treatments, generally overdosing to ensure biological efficiency. Last, the traditional nature of this crop and their structural characteristics (big-sized trees with very irregular tree crown shapes, wide tree and row spacing, high slope conditions…) make it especially complex with respect to spray applications to the tree canopy. The objective of this thesis is to develop new strategies to increase the efficiency of pesticide applications to olive tree crowns, through the simultaneous action on three key lines: to determine the influence of the variations in the main working parameters on the application quality, to obtain a simple model to adjust the sprayed volume to the canopy characteristics and to test new solutions to adapt the spraying equipment to the canopy shape, These objectives are developed along four main chapters. In chapter II, the influence of the spray volume and the airflow rate on the efficiency, coverage, penetration and spray homogeneity is studied. The results show that it is appropriate to reduce these parameters with respect to those usually applied in the field, reducing in this way the applied volumes and the power needs in tractors. In chapter III, different manual canopy characterization methods are compared to the most accurate technology: a LiDAR scanner. It is demonstrated that manual methods are reliable and, therefore, they can be useful to farmers and technicians to make adjustments to the spray volumes to be applied. The Mean Vector method showed to be the most polyvalent for different olive plantation systems. In chapter IV, two trials were undertaken to determine the optimum specific spray volume (sprayed L per m3 canopy volume) in isolated trees. It was determined that the specific volume of 0.12 L · m-3 resulted in an optimum coverage, in addition to improve the homogeneity of deposition throughout the crown and the spray penetration. This finding can lead to an important reduction in the volumes to be applied by farmers. In chapter V, the development of three new air-assisted sprayers adapted to the particular conditions of traditional and intensive olive orchards is explained. Each one presents some particularities that make it to be more appropriate for one system or the other, but they all showed to have the potential to improve the efficiency of the conventional airblast sprayer. Coverage increases up to 61% were achieved with these new sprayers. Keywords: olive, working parameters, pesticides, spray volume, airflow rate, LiDAR, canopy characterization, dose adjustment, specific spray volume, prototype development.La aplicación de productos fitosanitarios resulta necesaria para el correcto desarrollo de los cultivos y, por tanto, para asegurar su rentabilidad. No obstante, su mala gestión en los últimos años ha llevado a la aparición de problemas medioambientales de gran calado, lo que ha propiciado que haya una animadversion generalizada contra esta práctica. La Administración europea se ha hecho eco de esta preocupación social y ha impulsado un restrictivo marco legal para garantizar la sostenibilidad de los tratamientos mediante su racionalización. El caso del olivar, un cultivo de gran importancia en España, es especialmente crítico por tres motivos: por una parte, el cultivo se halla muy concentrado en la Cuenca del río Guadalquivir, con lo que la importancia de los impactos es muy alta. En segundo lugar, la escasez de investigación y transferencia hace que los agricultores y técnicos difícilmente estén en condiciones de llevar a cabo sus tratamientos de forma segura, optando generalmente por la sobre-dosificación para garantizar su eficacia biológica. Por ultimo, su carácter tradicional y sus características estructurales (copas de gran dimensión y de forma muy irregular, amplios anchos de calle, alta pendiente…) lo hacen especialmente complejo de cara a la pulverización sobre la copa de los árboles. El objetivo de esta tesis es desarrollar nuevas estrategias para aumentar la eficiencia de las aplicaciones de fitosanitarios a la copa de los olivos, mediante la actuación simultánea sobre tres líneas clave: determinar la influencia de las variaciones en los principales parámetros de trabajo sobre la calidad de las aplicaciones, obtener un modelo simple para ajustar el volumen de caldo empleado a las características de la vegetación y ensayar nuevas soluciones para adaptar los equipos de pulverización a la forma de la copa de los árboles. Se establecen cuatro capítulos principales que desarrollan estos objetivos. En el capítulo II, se estudia la influencia del volumen de caldo y del caudal de aire en la eficiencia, cobertura, penetración y homogeneidad de la pulverización. Los resultados muestran que es deseable reducir estos parámetros respecto a los comúnmente empleados en el campo, reduciendo así los volúmenes aplicados y las necesidades de potencia en los tractores. En el capítulo III se comparan diversos métodos de caracterización del volumen de copa manuales con la tecnología más precisa disponible en la actualidad: el escáner LiDAR. Se muestra que los métodos manuales son precisos y, por tanto, pueden ser útiles a agricultores y técnicos para realizar ajustes sobre el volumen de caldo a aplicar. Se establece el método del ‘Mean Vector’ como el más polivalente para los diferentes tipos de olivar. En el capítulo IV se llevan a cabo dos ensayos para determinar el óptimo volumen de aplicación específico (L de caldo por m3 de volumen de copa) en árboles aislados. Se determina que el volumen de 0.12 L · m-3 resulta en un grado de cobertura óptimo, además de mejorar la homogeneidad en la copa y la penetración. Esto supone una importante reducción en los volúmenes a aplicar por parte de los agricultores. En el capítulo V se detalla el desarrollo de tres nuevos equipos de pulverización adaptados a las condiciones particulares del olivar tradicional e intensivo. Cada equipo presenta unas particularidades que hace que trabaje major en un sistema o en otro, pero mejoran en todo caso al equipo comercial en términos de eficiencia. Incrementos de cobertura de hasta el 61% pueden ser conseguidos con estos nuevos atomizadores

Assessment of the Accuracy of a Multi-Beam LED Scanner Sensor for Measuring Olive Canopies

MDPI. CC BYCanopy characterization has become important when trying to optimize any kind of agricultural operation in high-growing crops, such as olive. Many sensors and techniques have reported satisfactory results in these approaches and in this work a 2D laser scanner was explored for measuring canopy trees in real-time conditions. The sensor was tested in both laboratory and field conditions to check its accuracy, its cone width, and its ability to characterize olive canopies in situ. The sensor was mounted on a mast and tested in laboratory conditions to check: (i) its accuracy at different measurement distances; (ii) its measurement cone width with different reflectivity targets; and (iii) the influence of the target’s density on its accuracy. The field tests involved both isolated and hedgerow orchards, in which the measurements were taken manually and with the sensor. The canopy volume was estimated with a methodology consisting of revolving or extruding the canopy contour. The sensor showed high accuracy in the laboratory test, except for the measurements performed at 1.0 m distance, with 60 mm error (6%). Otherwise, error remained below 20 mm (1% relative error). The cone width depended on the target reflectivity. The accuracy decreased with the target density

Advanced technologies for the improvement of spray application techniques in spanish viticulture: an overview

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.Postprint (published version

Digitalna procjena lisne površine krošnje stijenke vinove loze (Vitis vinifera cv. Sauvignon) korištenjem LIDAR mjerne tehnologije

A dosage rate reduction of plant protection products mixed with water, i.e. spray mixture, in a prescribed concentration in the vineyard will only be possible in the future, if the natural characteristics of vine canopy structures (leaf wall area) and canopy management are taken into account. In a practical experiment in the vineyard we evaluated the leaf wall area of the vine cv. Sauvignon on different segments on the left and right side of the vine canopy. We compared the results of manual measurements and laser measuring technology (LIDAR) with the corresponding algorithm, with which we enabled the digital reconstruction of the leaf wall area of the vine. The manual measurement of the leaf wall area was carried out using an automated image analyser. The digital system for measuring the leaf wall area on different segments consisted of a LIDAR sensor and a Differential Global Positioning System (hereinafter DGPS). To determine the exact DGPS position of the LIDAR sensor during the measurement, we set up a DGPS base station. Using the Excel software (CORREL function), we estimated the relationship between the dependent variable (digital number of points in the cloud) and an independent variable (leaf wall area, manually measured). An analysis of six randomly selected vines in the vineyard revealed the maximum value of the correlation coefficient r = 0.80 for the left side and r = 0.90 for the right side of the leaf wall area of the vine, respectively. In the near future the virtual three-dimensional space will provide more even control of spray mixture over the entire structure of the leaf wall area in the vineyard based on autonomous decision-making models.Smanjenje količine utroška sredstava za zaštitu bilja i same smjese za prskanje u budućnosti će biti moguće samo ako se uzmu u obzir prirodne karakteristike krošnje vinove loze tj. lisne površine krošnje trsa. U praktičnom pokusu u vinogradu procijenjena je lisna površinu krošnje vinove loze cv. Sauvignon na različitim segmentima s lijeve i desne strane krošnje uz pomoć ručnih mjerenja i laserske mjerne tehnologije (LIDAR). Dobiveni rezultati uspoređeni su s pripadajućim algoritmom čime je dobivena digitalna rekonstrukcija lisne površine vinove loze. Ručno mjerenje površine listova provedeno je u laboratoriju pomoću digitalnog lisnog skenera nakon što je lišće ručno pobrano s trsova i dopremljeno u sam laboratorij. Digitalni sustav za mjerenje lisne površine na različitim segmentima krošnje sastojao se od LIDAR senzora i DGPS navigacijskog sustava. Da bi se odredio točan DGPS položaj LIDAR senzora tijekom mjerenja, postavljena je DGPS bazna stanica. Pomoću regresijske metode utvrđen je odnos između zavisne varijable (digitalni broj točaka u oblaku) i nezavisne varijable (površina listova izmjerena skenerom). Rezultati analize imeđu dvije uspoređivane metode na šest slučajno odabranih trsova vinove loze otkrivaju vrijednost koeficijenta korelacije r = 0,80 za lijevu i r = 0,90 za desnu stranu krošnje. U bliskoj budućnosti virtualni trodimenzionalni prostor pružit će ravnomjerniju kontrolu smjese raspršivača preko cijele strukture područja stijenke lišča u vinogradu na temelju autonomnih modela odlučivanja