Systems of aerial spraying for soybean rust control

A ferrugem asiática da soja, causada pelo fungo Phakopsora pachyrhizi, é considerada a principal doença da soja, e, portanto, a escolha e o uso adequado dos equipamentos de pulverização são essenciais para seu controle. O objetivo deste trabalho foi avaliar o desempenho de diferentes equipamentos de pulverização aérea para o controle curativo da ferrugem da soja, utilizando o fungicida Impact 125 SC (flutriafol) a 0,5 L p c ha-1. Os seguintes tratamentos foram avaliados: atomizador Micronair AU 5000 (10 L ha-1 com óleo e 20 L ha-1 sem óleo na calda); atomizador Stol ARD (10 e 20 L ha-1 ambos com óleo) e o sistema eletrostático Spectrum (10 L ha-1 sem óleo a 64 e 71% de umidade relativa). Utilizou-se óleo de algodão (1,0 L ha-1) acrescido de emulsificante BR 455 a 0,025 L ha-1. O ensaio foi realizado na terceira aplicação de fungicidas, quando foram analisadas quatro repetições nas áreas aplicadas e quatro testemunhas não aplicadas para cada tratamento, avaliando-se a severidade da ferrugem, os depósitos de flutriafol nas folhas de soja e o percentual de redução de ferrugem. A análise dos depósitos nas folhas mostrou que não houve diferenças significativas entre os tratamentos. Os melhores controles da ferrugem foram obtidos com os tratamentos Micronair (10 L ha-1 com óleo), Stol (20 L ha-1 com óleo) e o sistema elestrostático (10 L ha-1) com a menor umidade relativa do ar (64 %).

Numeric model to estimate pesticide deposition and losses from aerial spraying.

Pesticides applications have been described by many researches as a very inefficient process. In some cases, there are reports that only 0.02% of the applied products are used for the effective control of the problem. The main factor that influences pesticides applications is the droplet size formed on spraying nozzles. Many parameters affects the dynamic of the droplets, like wind, temperature, relative humidity, and others. Small droplets are biologically more active, but they are affected by evaporation and drift. On the other hand, the great droplets do not promote a good distribution of the product on the target. In this sense, associated with the risk of non target areas contamination and with the high costs involved in applications, the knowledge of the droplet size is of fundamental importance in the application technology. When sophisticated technology for droplets analysis is unavailable, is common the use of artificial targets like water-sensitive paper to sample droplets. On field sampling, water-sensitive papers are placed on the trials where product will be applied. When droplets impinging on it, the yellow surface of this paper will be stained dark blue, making easy their recognition. Collected droplets on this papers have different kinds of sizes. In this sense, the determination of the droplet size distribution gives a mass distribution of the material and so, the efficience of the application of the product. The stains produced by droplets shows a spread factor proportional to their respectives initial sizes. One of methodologies to analyse the droplets is a counting and measure of the droplets made in microscope. The Porton N-G12 graticule, that shows equaly spaces class intervals on geometric progression of square 2, are coulpled to the lens of the microscope. The droplet size parameters frequently used are the Volumetric Median Diameter (VMD) and the Numeric Median Diameter. On VMD value, a representative droplets sample is divided in two equal parts of volume, in such away one part contains droplets of sizes smaller than VMD and the other part contains droplets of sizes greater that VMD. The same process is done to obtaining the NMD, which divide the sample in two equal parts in relation to the droplets size. The ratio between VMD and NMD allows the droplets uniformity evaluation. After that, the graphics of accumulated probability of the volume and size droplets are plotted on log scale paper (accumulated probability versus median diameter of each size class). The graphics provides the NMD on the x-axes point corresponding to the value of 50% founded on the y-axes. All this process is very slow and subjected to operator error. So, in order to decrease the difficulty envolved with droplets measuring it was developed a numeric model, implemented on easy and accessfull computational language, which allows approximate VMD and NMD values, with good precision. The inputs to this model are the frequences of the droplets sizes colected on the water-sensitive paper, observed on the Porton N-G12 graticule fitted on microscope. With these data, the accumulated distribution of the droplet medium volumes and sizes are evaluated. The graphics obtained by plotting this distributions allow to obtain the VMD and NMD using linear interpolation, seen that on the middle of the distributions the shape of the curves are linear. These values are essential to evaluate the uniformity of droplets and to estimate the volume deposited on the observed paper by the density (droplets/cm2). This methodology to estimate the droplets volume was developed by 11.0.94.224 Project of the CNPMA/EMBRAPA. Observed data of herbicides aerial spraying samples, realized by Project on Pelotas/RS county, were used to compare values obtained manual graphic method and with those obtained by model has shown, with great precision, the values of VMD and NMD on each sampled collector, allowing to estimate a quantities of deposited product and, by consequence, the quantities losses by drifty. The graphics of variability of VMD and NMD showed that the quantity of droplets that reachs the collectors had a short dispersion, while the deposited volume shows a great interval of variation, probably because the strong action of air turbulence on the droplets distribution, enfasizing the necessity of a deeper study to verify this influences on drift.

A method for comparing cost and productivity of aerial spray delivery /

Mode of access: Internet.

Pine wilt disease and the pinewood nematode

Pine wilt disease (PWD) is one of the most damaging events affecting conifer forests (in particular Pinus spp.), in the Far East (Japan, China and Korea), North America (USA and Canada) and, more recently, in the European Union (Portugal). In Japan it became catastrophic, damaging native pine species (Pinus thunbergii and P. densiflora), and becoming the main forest problem, forcing some areas to be totally replaced by other tree species. The pine wilt nematode (PWN) Bursaphelenchus xylophilus, endemic, with minor damage, to North America, was introduced in Japan in the early XX century and then spread to Asia (China and Korea) in the 1980s. In 1999 it was detected for the first time in Portugal, where, due to timely detection and immediate government action, it was initially (1999-2008) contained to a small area 30 km SE of Lisbon. In 2008, the PWN spread again to central Portugal, the entire country now being classified as “affected area”. Being an A1 quarantine pest, the EU acted to avoid further PWN spreading and to eradicate it, by actions including financial support for surveyes and eradication, annual inspections and research programs. Experience from control actions in Japan included aerial spraying of insecticides to control the insect vector (the Cerambycid beetle Monochamus alternatus), injection of nematicides to the trunk of infected trees, slashing and burning of large areas out of control, beetle traps, biological control and tree breeding programs. These actions allowed some positive results, but also unsuccessful cases due to the PWN spread and virulence. Other Asian countries also followed similar strategies, but the nematode is still spreading in many regions. In Portugal, despite lower damage than Asia, PWD is still significant with high losses to the forestry industry. New ways of containing PWD include preventing movement of contaminated wood, cutting symptomatic trees and monitoring. Despite a national and EU legislative body, no successful strategy to control and eventually eradicate the nematode and the disease will prevail without sound scientific studies regarding the nematode and vector(s) bioecology and genetics, the ecology and ecophysiology of the pine tree species, P. pinaster and P. pinea , as well as the genomics and proteomics of pathogenicity (resistance/ susceptibility).

Selectivity of the plant growth regulators trinexapac-ethyl and sulfometuron-methyl to cultivated species

The aerial spraying of plant ripeners on sugar cane (Saccharum officinarum L.) crops causes often the contamination of neighboring areas, which subsidizes formal complaints from the neighbors. These contaminations are due to spraying taking place during inadequate environmental conditions or from technical mistakes during the application. One of the most important causes of this contamination is the susceptibility of the species being cultivated surrounding sugar cane. In order to evaluate the effects of sugar cane plant ripeners trinexapac-ethyl and sulfometuron-methyl on peanuts, cotton, potato, coffee, citrus, beans, sunflower, cassava, rubber, soybean, and grapes, eleven experiments - one for each species - were carried out from May 2009 to Jan. 2010. The field experiment was set according to a completely random design with five treatments and four replications. Just before or during flowering, a single treatment of trinexapac-ethyl at 100 or 200 g ha-1 and sulfometuron-methyl at 7.5 or 15 g ha-1 was applied to plants. A control treatment (plants not treated) for each species was part of each experiment. Trinexapac, at the doses of 100 and 200 g ha-1, showed selectivity to peanuts, cotton, potato, coffee, citrus, sunflower, cassava, rubber, soybean, and grape. At the lowest dose (100 g ha-1), it was selective for bean. Sulfometuron, at the dose of 7.5 g ha-1, was selective for peanuts and, at the two studied doses (7.5 and 15 g ha-1), it was selective for coffee, citrus, cassava, and rubber.

Planejamento Ambiental da Bacia Hidrográfica do Ribeirão Santo Antonio – Mirante do Paranapanema (SP)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise da deposição em aplicações aéreas de defensivos em função de diferentes alturas de vôo e volumes de calda

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Uso sustentável de pesticidas : análise comparativa entre a União Europeia e o Brasil

Tese de doutoramento, Ciências do Ambiente, Universidade de Lisboa, Faculdade de Ciências, 2016

Evaluation of the Bell 205A-1 turbojet helicopter and spray system for forest application of insecticide /

"GPO 990-424"--P. [4] of cover.

The use of unmanned aerial vehicles and wireless sensor networks for spraying pesticides

The application of pesticides and fertilizers in agricultural areas is of crucial importance for crop yields. The use of aircrafts is becoming increasingly common in carrying out this task mainly because of their speed and effectiveness in the spraying operation. However, some factors may reduce the yield, or even cause damage (e.g., crop areas not covered in the spraying process, overlapping spraying of crop areas, applying pesticides on the outer edge of the crop). Weather conditions, such as the intensity and direction of the wind while spraying, add further complexity to the problem of maintaining control. In this paper, we describe an architecture to address the problem of self-adjustment of the UAV routes when spraying chemicals in a crop field. We propose and evaluate an algorithm to adjust the UAV route to changes in wind intensity and direction. The algorithm to adapt the path runs in the UAV and its input is the feedback obtained from the wireless sensor network (WSN) deployed in the crop field. Moreover, we evaluate the impact of the number of communication messages between the UAV and the WSN. The results show that the use of the feedback information from the sensors to make adjustments to the routes could significantly reduce the waste of pesticides and fertilizers.

Automatic Detection of Marine Mammal from Aerial Imagery

The following technical report describes the approach and algorithm used to detect marine mammals from aerial imagery taken from manned/unmanned platform. The aim is to automate the process of counting the population of dugongs and other mammals. We have developed and algorithm that automatically presents to a user a number of possible candidates of these mammals. We tested the algorithm in two distinct datasets taken from different altitudes. Analysis and discussion is presented in regards with the complexity of the input datasets, the detection performance.

Enhancing digital road map with lane details extracted from large-scale stereo aerial imagery using object-oriented image analysis

Precise, up-to-date and increasingly detailed road maps are crucial for various advanced road applications, such as lane-level vehicle navigation, and advanced driver assistant systems. With the very high resolution (VHR) imagery from digital airborne sources, it will greatly facilitate the data acquisition, data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lane information from aerial images with employment of the object-oriented image analysis method. Our proposed algorithm starts with constructing the DSM and true orthophotos from the stereo images. The road lane details are detected using an object-oriented rule based image classification approach. Due to the affection of other objects with similar spectral and geometrical attributes, the extracted road lanes are filtered with the road surface obtained by a progressive two-class decision classifier. The generated road network is evaluated using the datasets provided by Queensland department of Main Roads. The evaluation shows completeness values that range between 76% and 98% and correctness values that range between 82% and 97%.

Towards an automatic road lane marks extraction based on ISODATA segmentation and shadow detection from large-scale aerial images

The automatic extraction of road features from remote sensed images has been a topic of great interest within the photogrammetric and remote sensing communities for over 3 decades. Although various techniques have been reported in the literature, it is still challenging to efficiently extract the road details with the increasing of image resolution as well as the requirement for accurate and up-to-date road data. In this paper, we will focus on the automatic detection of road lane markings, which are crucial for many applications, including lane level navigation and lane departure warning. The approach consists of four steps: i) data preprocessing, ii) image segmentation and road surface detection, iii) road lane marking extraction based on the generated road surface, and iv) testing and system evaluation. The proposed approach utilized the unsupervised ISODATA image segmentation algorithm, which segments the image into vegetation regions, and road surface based only on the Cb component of YCbCr color space. A shadow detection method based on YCbCr color space is also employed to detect and recover the shadows from the road surface casted by the vehicles and trees. Finally, the lane marking features are detected from the road surface using the histogram clustering. The experiments of applying the proposed method to the aerial imagery dataset of Gympie, Queensland demonstrate the efficiency of the approach.

Automated road pavement marking detection from high resolution aerial images based on Multi-resolution image analysis and anisotropic Gaussian filtering

Road features extraction from remote sensed imagery has been a long-term topic of great interest within the photogrammetry and remote sensing communities for over three decades. The majority of the early work only focused on linear feature detection approaches, with restrictive assumption on image resolution and road appearance. The widely available of high resolution digital aerial images makes it possible to extract sub-road features, e.g. road pavement markings. In this paper, we will focus on the automatic extraction of road lane markings, which are required by various lane-based vehicle applications, such as, autonomous vehicle navigation, and lane departure warning. The proposed approach consists of three phases: i) road centerline extraction from low resolution image, ii) road surface detection in the original image, and iii) pavement marking extraction on the generated road surface. The proposed method was tested on the aerial imagery dataset of the Bruce Highway, Queensland, and the results demonstrate the efficiency of our approach.