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1. Robustness of Pigment Analysis in Tree FruitThe non-destructive application of spectrophotometry for analyzing fruit pigments has become a promising tool in precise fruit production. Particularly, the pigment contents are interesting to the growers as they provide information on the harvest maturity and fruit quality for marketing. The absorption of chlorophyll at its Q band provides quantitative information on the chlorophyll pool of fruit. As a challenge appears the in-situ measurement at varying developmental stage of the fruit due ... M. Zude-sasse, C. Regen, J. Käthner |
2. Comparison of Plant and Soil Mapping in Prunus Domestica L. OrchardIn the present study, the soil apparent electrical conductivity, ECa, and the plant water status were analyzed in plum production (Prunus domestica L 'Tophit plus'/Wavit) targeting (i) the spatial characterization of soil ECa and fruit yield, (ii) instantaneous water status, and (iii) cumulative pattern of water status and yield. The plum orchard is located in semi-humid, temperate climate (Potsdam, Germany), capturing 0.37 ha with 156 trees. Measurements were carried out on... M. Zude-sasse, J. Käthner, W.B. Herppich, J. Selbeck |
3. Spatial Variability of Canopy Volume in a Commercial Citrus GroveLiDAR (light detection and ranging) sensors have shown good potential to estimate canopy volume and guide variable rate applications in different fruit crops. Oranges are a major crop in Brazil; however the spatial variability of geometrical parameters remains still unknown in large commercial groves, as well as the potential benefit of sensor guided variable rate applications. Thus, the objective of this work was to characterize the spatial variability of the canopy volume in a commercial or... A.F. Colaço, J.P. Molin, R.G. Trevisan, J.R. Rosell-polo, A. Escolà |
4. Use of the Active Sensor Optrx to Measure Canopy Changes to Evaluate Foliar Treatments and to Identify Soil Quality in Table GrapeTable Grape (Vitis vinifera L.) is the main exporting horticultural crop in Chile, with the country being one of the top exporters at the world level. Commonly, grape producers perform trials of different commercial products which are not evaluated in an objective way. On the other hand they do not have the tools to easily identify areas within the field that may have some limiting factor. The use of active ground sensors that pass under the canopy several times during the season ma... R.A. Ortega, M.M. Martinez, H.P. Poblete |
5. A Case Study Approach for Teaching and Applying Precision AgricultureStudents often struggle understanding precision agriculture principles and how these principles can be applied to farming operations. A case-study approach that requires students to own a recreational global positioning system (GPS) for collecting on-farm data could be a method for helping students understand and apply precision agriculture. This paper describes a case-study approach to teaching precision agriculture using student owned GPS units and geographical information systems (GIS) sof... J.D. Williams |
6. Map@Syst – Geospatial Solutions for Rural and Community SustainabilityMap@Syst is a part of the USDA Cooperative State Research, Education and Extension Service (CSREES) eXtension online Web information service. eXtension is an educational partnership of more than 70 universities to provide online access to objective, research-based information and educational opportunities. Map@Syst is a Wiki-based Web site assembled and maintained cooperatively by geospatial technology educational specialists and practitioners. Map@Syst is a primary source of geospatial infor... P. Rasmussen, J. Nowatzki |
7. Teaching Critical Thinking Skills Using Geospatial Technology As Instructional ToolsTechniques in data collection and analysis of data are important concepts for students of precision farming. Also needed in conjunction with these concepts are critical thinking and problem solving skills. Employers often list critical thinking skills as one of the most important characteristics for new employees. Helping students experience and acquire critical thinking skills can be difficult. Geospatial technologies are not only useful precision farming tools, they are also educational too... T.A. Brase |
8. 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 |
9. 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 |
10. 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 |
11. 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 |
12. 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 |
13. 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 |
14. 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 |
15. 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 |
16. 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 |
17. 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 |
18. 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 |
19. 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 |
20. 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 |
21. 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 |
22. 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 |
23. 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 |
24. 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 |
25. 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 |
26. 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 |
27. 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 |
28. 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 |
29. 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 |
30. 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 |
31. 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 |
32. 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 |
33. 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 |
34. 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 |
35. 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 |
36. 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 |
37. Application of Drone Data to Assess Damage Intensity of Bacterial Leaf Blight Disease on Rice Crop in IndonesiaThe Government of Indonesia has launched agricultural insurance program since 2016. A key in agricultural insurance is damage assessment which is required to be as precise, quick, quantitative and inexpensive as possible. Current method is to inspect the damage by human eyes of specialist having experiences. This method, however, costs much and is difficult to estimate disease infected fields precisely in wide area. So, there is increasing need to develop effective, simplified and low cost me... C. Hongo, S. Isono, G. Sigit, B. Utoyo, E. Tamura |
38. Evaluation of Image Acquisition Parameters and Data Extraction Methods on Plant Height Estimation with UAS ImageryAerial imagery from unmanned aircraft systems (UASs) has been increasingly used for field phenotyping and precision agriculture. Plant height is one important crop growth parameter that has been estimated from 3D point clouds and digital surface models (DSMs) derived from UAS-based aerial imagery. However, many factors can affect the accuracy of aerial plant height estimation. This study examined the effects of image overlap, pixel resolution, and data extraction methods on estimati... C. Yang, C. Suh, W. Guo, H. Zhao, J. Zhang, R. Eyster |
39. Temperature Effect on Wild Blueberry Fruit Quality During Mechanical HarvestMechanical harvesters, utilizing a range of technologies, have been developed for timely operations and remain the most cost-effective means of picking the wild blueberry crop. Approximately 95% of wild blueberries in Atlantic Canada are immediately frozen and processed, while only a small percentage is sold in the fresh market. However, the producers can benefit by increasing the value of their harvested crop through fresh market sales. The objective of this study was to determine the optimu... T.J. Esau, A.A. Farooque, F. Abbas |
40. Variable Rate Fertilization in a High-yielding Vineyard of Cv. Trebbiano Romagnolo May Reduce Nitrogen Application and Vigour Variability Without Loss of Crop LoadThe site-specific management of vineyard cultural practices may reduce the spatial variability of vine vigor, contributing to achieve the desired yield and grape composition. In this framework, variable rate fertilization may effectively contribute to reduce the different availability of mineral nutrients between different areas of the vineyard, and so achieving the vine’s aforementioned performances. The present study was aimed to apply a variable rate fertilization in a high... G. Allegro, R. Martelli, G. Valentini, C. Pastore, R. Mazzoleni, F. Pezzi, I. Filippetti, A. Ali |
41. Knowledge-based Approach for Weed Detection Using RGB ImageryA workflow was developed to explore the potential use of Phase One RGB for weed mapping in a herbicide efficacy trial in wheat. Images with spatial resolution of 0.8 mm were collected in July 2020 over an area of nearly 2000 square meters (66 plots). The study site was on a research farm at the University of Saskatchewan, Canada. Wheat was seeded on June 29, 2020, at a rate of 75 seeds per square meter with a row spacing of 30.5 cm. The weed species seeded in the trial were kochia, wild oat, ... T. Ha, K. Aldridge, E. Johnson, S.J. Shirtliffe, S. Ryu |
42. UAV-based Hyperspectral Monitoring of Peach Trees As Affected by Silicon Applications and Water Stress StatusPrevious research has shown that the application of reduced doses of Silicon (Si) improves crop tolerance to water stress, which is common in commercial young peach trees because irrigation is not usually applied during their first two years. In this study, aerial images were used to monitor the impact of different Si and water treatments on the hyperspectral response of peach trees. An experiment with 60 young (under 1 year old) peach trees located at the Musser Fruit Research Center (Seneca... J. Peña, J. Melgar, A. De castro, J. Maja, K. Nascimento-silva |
43. N-management Using Structural Data: UAV-derived Crop Height As an Estimator for Biomass, N Concentration, and N Uptake in Winter WheatIn the last 15 years, sensors mounted on Unmanned Aerial Vehicles (UAVs) have been intensively investigated for crop monitoring. Besides known remote sensing approaches based on multispectral and hyperspectral sensors, photogrammetric methods became very important. Structure for Motion (SfM) and Multiview Stereopsis (MVS) analysis approaches enable the quantitative determination of absolute crop height and crop growth. Since the first paper on UAV-derived crop height was published by Bendig e... G. Bareth, A. Jenal, H. Hüging |
44. Cotton Boll Detection and Yield Estimation Using UAS Lidar Data and RGB ImageCotton boll distribution is a critical phenotypic trait that represents the plant's response to its environment. Accurate quantification of boll distribution provides valuable information for breeding cultivars with high yield and fiber quality. Manual methods for boll mapping are time-consuming and labor-intensive. We evaluated the application of Lidar point cloud and RGB image data in boll detection and distribution and yield estimation. Lidar data was acquired at 15 m using a DJI Matri... Z. Lin, W. Guo, N. Gill |
45. Integration of Unmanned Aerial Systems Images and Yield Monitor in Improving Cotton Yield EstimationThe yield monitor is one of the most adopted precision agriculture technologies because it generates dense yield data to quantify the spatial variability of crop yield as a basis for site-specific management. However, yield monitor data has various errors that prevent proper interpretation and precise field management. The objective of this study was to evaluate the application of unmanned aerial systems (UAS) images in improving cotton yield monitor data. The study was conducted in a dryland... H. Gu, W. Guo |
46. Deep Learning-Based Corn Disease Tracking Using RTK Geolocated UAS ImageryDeep learning-based solutions for precision agriculture have achieved promising results in recent times. Deep learning has been used to accurately classify different disease types and disease severity estimation as an initial stage for developing robust disease management systems. However, tracking the spread of diseases, identifying disease hot spots within cornfields, and notifying farmers using deep learning and UAS imagery remains a critical research gap. Therefore, in this study, high re... A. Ahmad, V. Aggarwal, D. Saraswat, A. El gamal, G. Johal |
47. Evaluation of Unmanned Aerial Vehicle Images in Estimating Cotton Nitrogen ContentEstimating crop nitrogen content is a critical step for optimizing nitrogen fertilizer application. The objective of this study was to evaluate the application of UAV images in estimating cotton (Gossypium hirsutum L.) N content. This study was conducted in a dryland cotton field in Garza County, Texas, in 2020. The experiment was implemented as a randomized complete block design with three N rates of 0, 34, and 67 kg N ha-1. A RedEdge multispectral sensor was used to acqu... R. Karn, H. Gu, O. Adedeji, W. Guo |
48. Establishment of a Canola Emergence Assessment Methodology Using Image-based Plant Count and Ground Cover AnalysisManual assessment of emergence is a time-consuming practice that must occur within a short time-frame of the emergence stage in canola (Brassica napus). Unmanned aerial vehicles (UAV) may allow for a more thorough assessment of canola emergence by covering a wider scope of the field and in a more timely manner than in-person evaluations. This research aims to calibrate the relationship between emerging plant population count and the ground cover. The field trial took place at the Uni... K. Krys, S. Shirtliffe, H. Duddu, T. Ha, A. Attanayake, E. Johnson, E. Andvaag, I. Stavness |
49. Utilization of UASs to Predict Sugarcane Yields in Louisiana Prior to HarvestOne of the most difficult tasks that both sugarcane producers and processors face every year is estimating the yields of sugarcane fields prior to the start of harvest. This information is needed by processors to determine when the harvest season is to be initiated each year and by producers to decide when each field should be harvested. This is particularly important in Louisiana because the end of the harvest season is often affected by freeze events. These events can severely damage the cr... R.M. Johnson, B. Ramachandran |
50. Increasing the Accuracy of UAV-Based Remote Sensing Data for Strawberry Nitrogen and Water Stress DetectionThis paper presents the methods to increase the accuracy of unmanned aerial vehicles (UAV)-based remote sensing data for the determination of plant nitrogen and water stresses with increased accuracy. As the demand for agricultural products is significantly increasing to keep up with the growing population, it is important to investigate methods to reduce the use of water and chemicals for water conservation, reduction in the production cost, and reduction in environmental impact. UAV-based r... S. Bhandari, A. Raheja |
51. Estimation of Cotton Biomass Using Unmanned Aerial Systems and Satellite-based Remote SensingSatellite and unmanned aerial system (UAS) images are effective in monitoring crop growth at various spatial, temporal, and spectral scales. The objective of the study was to estimate cotton biomass at different growth stages using vegetation indices (VIs) derived from UAS and satellite images. This research was conducted in a cotton field in Hale County, Texas, in 2021. Data collected include 54 plant samples at different locations for three dates of the growing season. Multispectral images ... O.I. Adedeji, B.P. Ghimire, H. Gu, R. Karn, Z. Lin, W. Guo |
52. Enhancing Spatial Resolution of Maize Grain Yield DataGrain yield data is frequently used for precision agriculture management purposes and as a parameter for evaluating agronomy experiments, but unexpected challenges sometimes interfere with harvest plans or cause total losses. The spatial detail of modern grain yield monitoring data is also limited by combine header width, which could be nearly 14 m in some crops. Remote sensing data, such as multispectral imagery collected via satellite and unmanned aerial systems (UAS), could be used t... J. Siegfried, R. Khosla, D. Mandal, W. Yilma |
53. Digital Soil Sensing and Mapping for Crop SuitabilitySoil, central to any land-based production system, determines the success of any crops. While soil for a farm or field is fixed, the crops can be selected to best fit the soil’s capability and production. Traditionally crops are selected based on farm history, knowledge, and years of trial and error to tailor the right crop to the right soil. Inherent challenges associated with this make the whole process unsustainable. Due to the consistent nature of the information collected, soil sen... D. Saurette, A. Biswas, T.B. Gobezie |
54. Assessment of Goss Wilt Disease Severity Using Machine Learning Techniques Coupled with UAV ImageryGoss Wilt has become a common disease in corn fields in North Dakota. It has been one of the most yield-limiting diseases, causing losses of up to 50%. The current method to identify the disease is through visual inspection of the field, which is inefficient, and can be subjective, with misleading results, due to evaluator fatigue. Therefore, developing a reliable, accurate, and automated tool for assessing the severity of Goss's Wilt disease has become a top priority. The use of un... A. Das, P. Flores, Z. Zhang , A. Friskop, J. Mathew |
55. Precision Nitrogen and Water Management for Optimized Sugar Beet Yield and Sugar ContentSugar beet (SB) production profitability is based on maximizing three parameters: beet yield, sucrose content, and sucrose recovery efficiency. Efficient nitrogen (N) and water management are key for successful SB production. Nitrogen deficits in the soil can reduce root and sugar yield. Overapplication of N can reduce sucrose content and increase nitrate impurities which lowers sucrose recovery. Application of N in excess of SB crop need leads to vigorous canopy growth, while compromising ro... O.S. Walsh, S. Shafian |
56. Potential of UAS Multispectral Imagery for Predicting Yield Determining Physiological Parameters of CottonThe use of unmanned aerial systems (UAS) in precision agriculture has increased rapidly due to the availability of reliable, low-cost, and high-resolution sensors as well as advanced image processing software. Lint yield in cotton is the product of three physiological parameters: photosynthetically active radiation intercepted by canopy (IPAR), the efficiency of converting intercepted active radiation to biomass (RUE), and the ratio of economic yield to total dry matter (HI). The relationship... A. Pokhrel, S. Virk, J.L. Snider, G. Vellidis, V. Parkash |
57. Multispectral Assessment of Chickpea in the Northern Great PlainsChickpea is an increasingly important crop in the Montana agricultural system. From 2017 to 2021 the U.S. has planted an average of about 492,000 acres per year with Montana chickpea production accounting for around 44% of the U.S. total (USDA/NASS QuickStats accessed on 2/11/2021). This has led to an increase in breeding efforts for elite varieties adapted to the unique conditions in the Northern Great Plains. Breeding of chickpea often relies on traditional phenotyping techniques that are l... J.M. Vetch |
58. Assessing the Potential of Sentinel-1 in Retrieving Mango Phenology and Investigating Its Relation to Weather in Southern GhanaThe rise in global production of horticultural tree crops over the past few decades is driving technology-based innovation and research to promote productivity and efficiency. Although mango production is on the rise, application of the remote sensing technology is generally limited and the available study on retrieving mango phenology stages specifically, was focused on the application of optical data. We therefore sought to answer the questions; (1) can key phenology stages of mango be retr... B.A. Torgbor, M.M. Rahman, A. Robson, J. Brinkhoff |