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1. Rumex and Urtica Detection in Grassland by UAVPrevious work (Binch & Fox, 2017) used autonomous ground robotic platforms to successfully detect Urtica (nettle) and Rumex (dock) weeds in grassland, to improve farm productivity and the environment through precision herbicide spraying. It assumed that ground robots swathe entire fields to both detect and spray weeds, but this is a slow process as the slow ground platform must drive over every square meter of the field even where there are no weeds. The present study examines a complimen... A. Binch, N. Cooke, C.W. Fox |
2. Yield Assessment of a 270 000 Plant Perennial Ryegrass Field Trial Using a Multispectral Aerial Imaging PlatformCurrent assessment of non-destructive yield in forage breeding programs relies largely on the visual assessment by experts, who would categorize biomass to a discrete scale. Visual assessment of biomass yield has inherent pitfalls as it can generate bias between experimental repeats and between different experts. Visual assessment is also time-consuming and would be impractical on large-scale field trials. A method has been established to allow for a rapid, non-destructive assessment of bioma... P.E. Badenhorst, A. Phelan |
3. Using Unmanned Aerial Vehicle and Active-Optical Sensor to Monitor Growth Indices and Nitrogen Nutrition of Winter WheatUsing unmanned aerial vehicle (UAV) remote sensing monitoring system can rapidly and cost-effectively provide crop canopy information for growth diagnosis and precision fertilizer regulation. RapidScan CS-45 (Holland, Lincoln, NE, USA) is a portable active-optical sensor designed for timely, non-destructive obtaining plant canopy information without being affected by weather condition. UAV equipped with RapidScan, is of great significant for rapidly monitoring crop growth and nitrogen (N) sta... X. Liu, Q. Cao, Y. Tian, Y. Zhu, Z. Zhang, W. Cao |
4. Prototype Unmanned Aerial Sprayer for Plant Protection in Agricultural and Horticultural CropsAerial application of pesticides has the potential to reduce the amount of pesticides required as chemicals are applied where needed. A prototype Unmanned Aerial Sprayer with a payload of 20 kg; a spraying rate of 6 liters per minute; a spraying swathe of 3 meters, coverage rate of 2 to 4 meters per second and 10 minutes of flight time was built using state of the art technologies. The project is a joint development by University of Agricultural Sciences, Dharwad, KLE Technological University... S. Reddy, D.P. Biradar, V.C. Patil, B.L. Desai, V.B. Nargund, P. Patil, V. Desai, V. Tulasigeri, S.M. Channangi, W. John |
5. Unmanned Aerial Systems (UAS) for Mitigating Bird Damage in Wine GrapesBird predation is a significant problem in high-value fruit crops, such as apples, cherries, blueberries, and wine grapes. Conventional methods such as netting, falconry, auditory scaring devices, lethal shooting, and visual scare devices are reported to be ineffective, costly, and/or difficult to manage. Therefore, farmers are in need of more effective and affordable bird control methods. In this study, two UAS wasused as a bird-deterring agent in a commercial vineyard. The experimental... S. Bhusal, K. Khanal, M. Karkee, K.M. Steensma, M.E. Taylor |
6. Assessment of Red-Edge Based Vegetation Indices Derived from Unmanned Arial Vehicle for Plant Nitrogen Content EstimationUnmanned Aerial Vehicles (UAVs) have become increasingly popular in recent years for agricultural research. High spatial and temporal resolution images obtained with UAVs are ideal for many applications in agriculture. The objective of this study was to evaluate the performance of red edge based vegetation indices (VIs) derived from UAV images for quantification of plant nitrogen (N) content of spring wheat, a major cereal crop worldwide. This study was conducted at three locations in Idaho, ... O.S. Walsh, S. Shafian |
7. Temporal Analysis of Correlation of NDVI with Growth and Yield Features of Rice PlantsIn this paper we present a temporal correlation analysis of NDVI with with Growth and Yield Features of Rice Plants. A half ha experimental rice field was established south-west of Ibagué, Tolima, Colombia (4°22'54.192"N, 75°09'17.222"W. For the experimental design in the plot, four rows were established for nitrogen, three for phosphorous and three for potassium. For nitrogen, each row contained five treatments allocated randomly.&n... O. Barrero, L.A. Castilla |
8. Estimates of Plant Number of Maize Crop at Seedling from High-Throughput UAV ImageryThe acquisition of such agricultural information as crop growth and output is of great significance for the development of modern agriculture. Using the image analysis is important to gain information on plant properties, health and phenotype. This study uses the unmanned aerial vehicle images about Maize breeding material collected in Beijing Xiao Tang mountain town in June 2017. The four color space transformation of RGB, HSV, YCbCr and L*A*B was used to divide the UAV image foreground (cro... S. Liu, G. Yang |
9. Flourish - A Robotic Approach for Automation in Crop ManagementThe Flourish project aims to bridge the gap between current and desired capabilities of agricultural robots by developing an adaptable robotic solution for precision farming. Combining the aerial survey capabilities of a small autonomous multi-copter Unmanned Aerial Vehicle (UAV) with a multi-purpose agricultural Unmanned Ground Vehicle (UGV), the system will be able to survey a field from the air, perform targeted intervention on the ground, and provide detailed information for decision supp... A. Walter, R. Khanna, P. Lottes, C. Stachniss, R. Siegwart, J. Nieto, F. Liebisch |
10. The Guelph Plot Analyzer: Semi-Automatic Extraction of Small-Plot Research Data from Aerial ImagerySmall-plot trials are the foundation of open-field agricultural research because they strike a balance between the control of an artificial environment and the realism of field-scale production. However, the size and scope of this research field is often limited by the ability to collect data, which is limited by access to labour. Remote sensing has long been investigated to allocate labour more efficiently, therefore enabling the rapid collection of data. Imagery collected by unmanned aerial... J. Nederend, D. Drover, B. Reiche, B. Deen, L. Lee, G.W. Taylor |
11. Using UAV Imagery for Crop AnalyticsUAV imagery was collected in April and July of 2017 over a grape vineyard in California’s San Joaquin Valley. Using spectral signatures, a landcover classification was performed to isolate table grapes from the background vegetation and soil. A novel vegetation index was developed based off the unique spectral characteristics of the yellowing effects of chlorosis within the table grape vines. Spatial statistics were run only on the pixels containing grape plants, and a relative vegetati... C. Adams, A. Coates |
12. Autonomous Mapping of Grass-Clover Ratio Based on Unmanned Aerial Vehicles and Convolutional Neural NetworksThis paper presents a method which can provide support in determining the grass-clover ratio, in grass-clover fields, based on images from an unmanned aerial vehicle. Automated estimation of the grass-clover ratio can serve as a tool for optimizing fertilization of grass-clover fields. A higher clover content gives a higher performance of the cows, when the harvested material is used for fodder, and thereby this has a direct impact on the dairy industry. An android ... D. Larsen, S. Skovsen, K.A. Steen, K. Grooters, O. Green, R.N. Jørgensen, J. Eriksen |
13. Wheat Biomass Estimation Using Visible Aerial Images and Artificial Neural NetworkIn this study, visible RGB-based vegetation indices (VIs) from UAV high spatial resolution (1.9 cm) remote sensing images were used for modeling shoot biomass of two Brazilian wheat varieties (TBIO Toruk and BRS Parrudo). The approach consists of a combination of Artificial Neural Network (ANN) with several Vegetation Indices to model the measured crop biomass at different growth stages. Several vegetation indices were implemented: NGRDI (Normalized Green-Red Difference Index), CIVE (Color In... M.R. De souza, T.D. Bertani, A. Parraga, C. Bredemeier, C. Trentin, D. Doering, A. Susin, M. Negreiros |
14. Use of UAV Acquired Imagery As a Precision Agriculture Method for Measuring Crop Residue in Southwestern Ontario, CanadaResidue management on agriculture land is a practice of great importance in southwestern Ontario, where soil management practices have an important effect on Great Lakes water quality. The ability of tillage or planting system to maintain soil residue cover is currently measured by using one or more of the common methods, line transect (e.g. knotted rope, Meter stick) and photographic (grid, script, and image analysis) methods. Each of these techniques has various advantages and disadvantages... A. Laamrani, A. Berg, M. March, A. Mclaren, R. Martin |
15. Site-Specific Management Zones Delineation Using Drone-Based Hyperspectral ImageryConventional techniques (e.g., intensive soil sampling) for site-specific management zones (MZ) delineation are often laborious and time-consuming. Using drones equipped with hyperspectral system can overcome some of the disadvantages of these techniques. The present work aimed to develop a drone-based hyperspectral imagery method to characterize the spatial variability of soil physical properties in order to delineate site-specific MZ. Canonical correlation analysis (CCA) was used to extract... H. Agili, K. Chokmani, A. Cambouris, I. Perron, J. Poulin |
16. Soybean Maturity Stage Estimation with Unmanned Aerial SystemsMany agronomic decisions in soybean production systems revolve around crop maturity. The primary objective of this research was to evaluate the ability of UAS to determine when soybeans have reached maturity stage sufficient for harvest aid application. A producer typically applies harvest aid chemicals when he or she perceives the crop has reached a critical level of maturity (R6.5) based on a subjective assessment. A convention is to apply harvest aids when 65% of soybean pods reach a matur... J.M. Prince czarnecki, L.L. Wasson, J.T. Irby, A.B. Scholtes, S.M. Carver |
17. Using an Unmanned Aerial Vehicle with Multispectral with RGB Sensors to Analyze Canola Yield in the Canadian PrairiesIn 2017 canola was planted on 9 million hectares in Canada surpassing wheat as the most widely planted crop in Canada. Saskatchewan is the dominant producer with nearly 5 million hectares planted in 2017. This crop, seen both as one of the highest-yielding and most profitable, is also one of most expensive and input-intensive for producers on the Canadian Prairies. In this study, the effect of natural and planted shelterbelts on canola yield was compared with canola yi... K. Hodge, L. Bainard, A. Smith, F. Akhter |
18. Snap Bean Flowering Detection from UAS Imaging SpectroscopySclerotinia sclerotiorum (white mold) is a fungus that infects the flowers of snap beans and causes a reduction in the number of pods, and subsequent yields, due to premature pod abscission. Snap bean fields typically are treated with prophylactic fungicide applications to control white mold, once 10% of the plants have at least one flower. The holistic goal of this research is to develop spatially-explicit white mold risk models, based on inputs from remote sensing systems aboard unmann... E.W. Hughes, S.J. Pethybridge, C. Salvaggio, J. Van aardt, J.R. Kikkert |
19. Estimating Corn Biomass from RGB Images Acquired with an Unmanned Aerial VehicleAbove-ground biomass, along with chlorophyll content and leaf area index (LAI), is a key biophysical parameter for crop monitoring. Being able to estimate biomass variations within a field is critical to the deployment of precision farming approaches such as variable nitrogen applications. With unprecedented flexibility, Unmanned Aerial Vehicles (UAVs) allow image acquisition at very high spatial resolution and short revisit time. Accordingly, there has been an increasing interest i... K. Khun, P. Vigneault, E. Fallon, N. Tremblay, C. Codjia, F. Cavayas |
20. Effectiveness of UAV-Based Remote Sensing Techniques in Determining Lettuce Nitrogen and Water StressesThis paper presents the results of the investigation on the effectiveness of UAV-based remote sensing data in determining lettuce nitrogen and water stresses. Multispectral images of the experimental lettuce plot at Cal Poly Pomona’s Spadra farm were collected from a UAV. Different rows of the lettuce plot were subject to different level of water and nitrogen applications. The UAV data were used in the determination of various vegetation indices. Proximal sensors used for ground-truthin... S. Bhandari, A. Raheja, M.R. Chaichi, R.L. Green, D. Do, M. Ansari, J.G. Wolf, A. Espinas, F.H. Pham, T.M. Sherman |
21. Rape Plant NDVI Spatial Distribution Model Based on 3D ReconstructionPlants’ morphology changes in their growing process. The 3D reconstruction of plant is of great significance for studying the impacts of plant morphology on biomass estimation, illness and insect infestation, genetic expression, etc. At present, the 3D point cloud reconstructed through 3D reconstruction mainly includes the morphology, color and other features of the plant, but cannot reflect the change in spatial 3D distribution of organic matters caused by the nutritional status (e.g. ... Y. Chen, Y. He |
22. Assessment of Crop Growth Under Modified Center Pivot Irrigation Systems Using Small Unmanned Aerial System Based Imaging TechniquesIrrigation accounts for about 80% consumptive use of water in the Northwest of United States. Even small increases in water use efficiency can improve crop production, yield, and have more water available for alternative uses. Center pivot irrigation systems are widely recognized in the irrigation industry for being one of the most efficient sprinkler systems. In recent years, there has been a shift from high pressure impact sprinklers on the top of center pivots to Mid Elevation Spray Applic... M. Chakraborty, T. Peters, L. Khot |
23. Monitoring Soybean Growth and Yield Due to Topographic Variation Using UAV-Based Remote SensingRemote sensing has been used as an important tool in precision agriculture. With the development of unmanned aerial vehicle (UAV) technology, collection of high-resolution site-specific field data becomes promising. Field topography affects spatial variation in soil organic carbon, nitrogen and water content, which ultimately affect crop performance. To improve crop production and reduce inputs to the field, it is critical to collect site-specific information in a real-time manner and at a la... J. Zhou, K.A. Sudduth, A. Feng |
24. Late Season Imagery for Harvest ManagementThe overall objective of this project was to preliminarily assess the use of UAV-based thermal imagery to sense harvest-related factors. Results suggested that thermal imagery can be used to detect areas of high grain moisture content late in the harvest season. Time periods closer to physiological maturity were less likely to show significant differences in thermal imagery data. Additional research is needed to determine if moisture content trends with other measurable quan... J. Ward, G. Roberson, R. Phillips |
25. Unmanned Aerial Systems and Remote Sensing for Cranberry ProductionWisconsin is the largest producer of Cranberries in the United States with 5.6 million barrels produced in 2017. To date, Precision Agriculture technologies adapted to cranberry production have been limited. The objective of this research was to assess the feasibility of the use of commercial remote sensing devices and Unmanned Aerial Systems in cranberry production. Two commercially available sensors were assessed for use in cranberry production: 1) MicaSense Red Edge and 2) Zenmuse XT. Init... B. Luck, J. Drewry, E. Chassen, S. Steffan |
26. Crop Price Variation and Water Saving Technologies in Alborz Province of IranConsidering the importance and scarcity of water resources, the efficient management of water resources is of great imp,ortance. Adoption of modern irrigation technology is considered to be a key of increasing the efficiency of water used in agriculture. Policy makers have implemented several ways to induce the adoption of new irrigation technology. The empirical studies show that farmers are reluctant to utilize the use of new irrigation methods. This study aims to assess factors affecting o... S. Yazdani, S. Nikravesh, S. Bagheri |
27. Salinity Stress Assessment on Vegetation Cover in Arid Regions Using Visible Range Indices of True Color Aerial UAV/Drone ImagesDate palm (Phoenix dactylifera L.) is one of the most important plant growing in arid and semi-arid regions, where it has a social, cultural, economic and nutritious importance. Although date palm can be ranked as the highest salt tolerance plant among fruit crop, extreme salinity can negatively affect its growth, yield and fruit quality. Inadequate annual rainfall of arid regions has stressed and rapidly decreased date palm plantation due to salinity and drought. In this study unmanned ... Y.A. Al-mulla, S. Al-rahbi |
28. Correlating Plant Nitrogen Status in Cotton with UAV Based Multispectral ImageryCotton is an indeterminate crop; therefore, fertility management has a major impact on the growth pattern and subsequent yield. Remote sensing has become a promising method of assessing in-season cotton N status in recent years with the adoption of reliable low-cost unmanned aerial vehicles (UAVs), high-resolution sensors and availability of advanced image processing software into the precision agriculture field. This study was conducted on a UGA Tifton campus farm located in Tifton, GA. The ... W. Porter, D. Daughtry, G. Harris, R. Noland, J. Snider, S. Virk |
29. Prototype Unmanned Aerial Sprayer for Plant Protection in Agricultural and Horticultural CropsAerial application of pesticides has the potential to reduce the amount of pesticides required as chemicals are applied where needed. A prototype Unmanned Aerial Sprayer with a payload of 20 kg; a spraying rate of 6 liters per minute; a spraying swathe of 3 meters, coverage rate of 2 to 4 meters per second and 10 minutes of flight time was built using state of the art technologies. The project is a joint development by University of Agricultural Sciences, Dharwad, KLE Technological University... S. G, D.P. Biradar, B.L. Desai, V.C. Patil, P. Patil, V.B. Nargund, V. Desai, W. John, S.M. Channangi, V. Tulasigeri |
30. Map Whiteboard As Collaboration Tool for Smart Farming Advisory ServicesPrecision agriculture, a branch of smart farming, holds great promise for modernization of European agriculture both in terms of environmental sustainability and economic outlook. The vast data archives made available through Copernicus and related infrastructures, combined with a low entry threshold into the domain of AI-technologies has made it possible, if not outright easy, to make meaningful predictions that divides individual agricultural fields into zones where variable rat... K. Charvat, R. Berzins, R. Bergheim, F. Zadrazil, J. Macura, D. Langovskis, H. Snevajs, H. Kubickova, S. Horakova, K. Charvat jr. |
31. Comparison of Different Aspatial and Spatial Indicators to Assess Performance of Spatialized Crop Models at Different Within-field ScalesMost current crop models are point-based models, i.e. they simulate agronomic variables on a spatial footprint on which they were initially designed (e.g. plant, field, region scale). To assess their performances, many indicators based on the comparison of estimated vs observed data, can be used such as root mean square error (RMSE) or Willmott index of agreement (D-index) among others. However, shifting model use from a strategic objective to tactical in-season management is becoming a signi... D. Pasquel, S. Roux, B. Tisseyre, J.A. Taylor |
32. Investigating Spatial Relationship of Apparent Electrical Conductivity with Turfgrass and Soil Characteristics in Sand-capped Golf Course FairwaysTurfgrass quality decreases when grown on fine textured soils that are irrigated with poor quality water. As a result, sand-capping (i.e., a sand layer above existing native soil) is now considered during golf course fairway renovation and construction. Mapping spatial variability of soil apparent electrical conductivity (ECa) has recently been suggested to have applications for precision turfgrass management (PTM) in native soil fairways, but sand-capped fairways have received les... C. Straw, B. Wyatt, A.P. Smith, K. Watkins, S. Hong, W. Floyd, D. Williams, C. Garza, T. Jansky |
33. Scaling Up Window-based Regression for Crop-row DetectionCrop-row detection is a central element of weed detection and agricultural image processing tasks. With the increased availability of high-resolution imagery, a precise locating of crop rows is becoming practical in the sense that the necessary data are commonly available. However, conventional image processing techniques often fail to scale up to the data volumes and processing time expectations. We present an approach that computes regression lines ... A.M. Denton, G.E. Hokanson, P. Flores |
34. Comparison and Validation of Different Soil Survey Techniques to Support a Precision Agricultural SystemThe data need of precision agriculture has resulted in an intensive increase in the number of modern soil survey equipment and methods available for farmers and consultants. In many cases these survey methods cannot provide accurate information under the used environmental conditions. On a 36 hectare experimental field, several methods have been compared to identify the ones which can support the PA system the best. The methods included contact and non contact soil scanning, yield mapping, hi... V. Lang, G. Tóth, S. Csenki, D. Dafnaki |
35. Optimization of Batch Processing of High-density Anisotropic Distributed Proximal Soil Sensing Data for Precision Agriculture PurposesThe amount of spatial data collected in agricultural fields has been increasing over the last decade. Advances in computer processing capacity have resulted in data analytics and artificial intelligence becoming hot topics in agriculture. Nevertheless, the proper processing of spatial data is often neglected, and the evaluation of methods that efficiently process agricultural spatial data remains limited. Yield monitor data is a good example of a well-established methodology for data processi... F. Hoffmann silva karp, V. Adamchuk, A. Melnitchouck, P. Dutilleul |
36. Using On-the-Go Soil Sensors to Assess Spatial Variability within the KS Wheat Breeding ProgramIn plant breeding the impacts of genotype by environment interactions and the challenges to quantify these interactions has long been recognized. Both macro and microenvironment variations in precipitation, temperature and soil nutrient availability have been shown to impact breeder selections. Traditionally, breeders mitigate these interactions by evaluating genotype performance across varying environments over multiple years. However, limitations in labor, equipment and seed availably can l... B. Evers, M. Rekhi, G. Hettiarachchi, S. Welch, A. Fritz, P.D. Alderman, J. Poland |
37. Changes in Soil Quality when Building Ridges for Fruit PlantationMany fruit plantations are usually performed in ridges for various reasons including, escaping from a clay horizon, improving overall soil quality and drainage, among others. Normally ridges are built using the surface horizons, producing a mixture of soils layers, and therefore changing the quality of the soil at the rooting zone. We were interested in studying the changes in soil properties when building ridges in a flat alluvial soil that was planted with avocado. A det... H.P. Poblete, R.A. Ortega |
38. Yield Estimation for Avocado Using Systematic Sampling TechniquesAvocado is a high value crop ranking fourth among the planted fruit species in Chile with more than 32,000 ha. Yield estimation is an important challenge in avocado due to its phenology, the size of the tree, and to the large variability usually observed within the orchards. Due to the practical difficulties to sample the trees we use the following approach: 1) establish a systematic, non-aligned grid with > 20 sampling points (trees)/field, 2) previous to harvest, and ... H.P. Poblete, R.A. Ortega |
39. Cloud Correction of Sentinel-2 NDVI Using S2cloudless PackageOptical satellite-derived Normalized Difference Vegetation Index (NDVI) is by far the most commonly used vegetation index value for crop monitoring. However, it is quite sensitive to the cloud, and cloud shadows and significantly decreases its usability, especially in agricultural applications. Therefore, an accurate and reliable cloud correction method is mandatory for its effective application. To address this issue, we have developed an approach to correct the NDVI values of each and every... A. Saxena, M. Dash, A.P. Verma |
40. Next in Precision Agriculture: Detecting and Correcting Pixels with Machinery Track Line Within FarmsWith more satellites orbiting the earth, monitoring of fields using satellite data has become easier and ubiquitous. Frequent observations of a field can provide vital cues about field health and management practices. However, farm analytical statistics derived from such datasets often need modification to create practical applications. This paper focuses on the detection and removal of field machinery track line pixels to reduce their effect on satellite-based agronomic recommendation and pr... G. Rathee, M. Sielenkemper |
41. Automated Geometrical Field Boundary Delineation Algorithm for Adjacent Job SitesEstablishing farmland geometric boundaries is a critical component of any assistive technology, designed towards the automation of mechanized farming systems. Observing farmland boundaries enables farmers and farm machinery contractors to determine; seed purchase orders, fertiliser application rate, and crop yields. Farmers must supply acreage measurements to regulatory bodies, who will use the geometric data to develop environmental policies and allocate farm subsidies appropriately. Agricu... S.J. Harkin |
42. A Multi-objective Optimisation Analysis of Virtual Fencing in Precision GrazingVirtual fencing is a precision livestock farming tool consisting of invisible boundaries created via Global Navigation Satellite Systems (GNSS) and managed remotely and in real time by app-based technology. Grazing livestock are equipped with battery-powered collars capable of delivering audio or vibration cues and possibly electric shocks when approaching or crossing an invisible boundary. Virtual fencing makes precision grazing possible without the need for physical fences. This technology ... E. Maritan, K. Behrendt, J. Lowenberg-deboer, S. Morgan, M.S. Rutter |
43. Design of an Automatic Travelling Electric Fence System for Sustainable Grazing ManagementFences are used in Precision Livestock Farming (PLF) to prevent herbivores from overgrazing and under grazing forages. While effective in controlling animal entry and exit, traditional fences are not flexible enough to meet the needs of both foraging animals and plants in terms of both nutrient availability and physiological demands. An electric fencing system is a form of traditional fencing that employs an electric charge to create a barrier and dissuade animals or people from crossing it. ... M. Alahe, Y. Chang, J.O. Kemeshi, S. Gummi, H. Menendez iii |
44. Detection of Goat Herding Impact on Vegetation Cover Change Using Multi-season, Multi-herd Tracking and Satellite ImageryThe frequency and severity of Mediterranean forest fires are expected to worsen as climate change progresses, heightening the need to evaluate understory fuel management strategies as rigorously as possible. Prescribed small-ruminant foraging is considered a sustainable, cost-effective strategy, but demonstrating a link between animal presence and vegetation change is challenging. This study tested whether the effect of small-ruminant herd presence in Mediterranean woodlands can be detected b... T. Paz kagan, V. Alexandroff, E.D. Ungar |