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1. Spectral Discrimination Of Early Dchinochloa Crasgalli And Echinochloa Crusgalli In Corn And Soybean By Using Support Vector MachinesThe key to realize precise chemical application is weed identification. This paper introduces a kind of multi-classification mode based on Support Vector Machines (SVM) and one-against-one-algorithm for weed seedlings (Dchinochloa crasgalli, and Echinochloa crusgalli) in corn and soybean fields. A handheld FieldSpec® 3 Spectroradiometer manufactured by ASD Inc., in USA was used to measure the spectroscopic data of the canopies of the seedlings of corn, soybean,... W. Deng, G. Wu |
2. Using Late-season Uncalibrated Digital Aerial Imagery For Predicting Corn Nitrogen Status Within FieldsUsing uncalibrated digital aerial imagery (DAI) for diagnosing in-season nitrogen (N) deficiencies of corn (Zea mays L.) is challenging because of the dynamic nature of corn growth and the difficulty of obtaining timely imagery. Digital aerial imagery taken later during the growing season is more accurate in identifying areas deficient in N. Even so, the quantitative use of late-season DAI across many fields is still limited because the imagery is not truly calibrated. This study... P.M. Kyveryga, T.M. Blackmer, R. Pearson |
3. A Systematic Approach For Using Precision Agriculture Tools For On-farm Evaluations In IowaThe competitive nature of modern agriculture requires constant refinements of many crop production management decisions. Precision agriculture tools (PAT) can allow growers to rapidly evaluate different management practices across large areas at a relatively low cost. But a systematic approach and a decision-making process describing how to utilize different PAT for on-farm evaluations have not been yet developed and adopted. This presentation will focus on how approximately... T.M. Blackmer, P.M. Kyveryga |
4. Estimating Soil Moisture And Organic Matter Content Variabality Using Electromagnatic Induction MetodAbstract: Electromagnetic induction (EMI) methods are gaining popularity due to their non-destructive nature, rapid response and ease of integration into mobile platforms for assessment of the soil moisture content, water table depth, and salinity etc. The objective of this study was to estimate and map soil moisture content and organic matter content using DualEM.... A. Farooque, Q. Zaman, A.W. Schumann, D.C. Percival, T.J. Esau, T. Stauffer |
5. Design And Experiment On Target Spraying Robot For GreenhouseIn greenhouse, the robot sprayers give rise to concern as they reduce the labor intensity and improve the accuracy of the spraying. This paper details the progress to date in the development of a precision robot sprayer. The precision robot sprayer is able to adjust both liquid and air volume to match, the branches contour and location of the greenhouse crops with two ultrasonic sensors which ensures the position of the plants in the greenhouse. The spraying robot with the... W. Ma, C. Zhao, Q.U. Zaman, D. Zach |
6. Performance Of The Veris Nir Spectrophotometer For Mapping Soil C In The Palouse Soils Of Eastern WashingtonRecent advances in sensing technology have made measuring and mapping the dynamics of important soil properties that regulate carbon and nutrient budgets possible. The Veris Technologies (Salinas, KS) Near Infrared (NIR) Spectrometer is one of the first sensors available for collecting geo-referenced NIR soil spectra on-the-go. Field studies were conducted to evaluate the performance of the Veris NIR in wheat grown under both conventional and no-till management in the Palouse region of eastern... F. Pierce, E.M. Perry, S.L. Young, H.P. Collins, P.G. Carter |
7. Automatic Remote Image Processing For Agriculture Uses Through Specific SoftwareAbstract ... D. Gómez-candón, J.J. Caballero-novella, J.M. Peña-barragán, M. Jurado-expósito, F. López-granados, L. Garcia-torres, A.I. Decastro |
8. Position Error of Input Prescription Map Delineated From Remote ImagesThe spatial variability of biotic factors... D. Gómez-candón, J.J. Caballero-novella, J.M. Peña-barragán, M. Jurado-expósito, L. Garcia-torres, F. López-granados, A.I. Decastro |
9. Comparison and Evaluation of Spray Characteristics of Three Types of Variable-Rate SprayFor the present developing direction of "low-input sustainable agriculture", variable-rate technology is increasingly concerned in agricultural engineering field. The technology of variable-rate precision chemical application is the typical of variable-rate technology. In China, agro-chemical production technology has reached the international advanced level, but the chemical application... C. Zhao, J. Zhou, W. Deng |
10. Precision Tools to Evaluate Alternative Weed Management Systems in Soybean... T.M. Blackmer, P.M. Kyveryga |
11. Site-Specific Evaluations of Nitrification Inhibitor with Fall Applications of Liquid Swine Manure... P.M. Kyveryga, T.M. Blackmer |
12. Digital Aerial Imagery Guides a Statewide Nutrient Management Benchmarking Survey... P.M. Kyveryga, T.M. Blackmer |
13. Precision Tools to Evaluate Benefits of Tile Drainage in a Corn and Soybean Rotation in Iowa... P.R. Reeg, T.M. Blackmer, P.M. Kyveryga |
14. Spot- Application of Pre-Emergence Herbicide Using a Variable Rate Sprayer in Wild BlueberryWild blueberry producers apply herbicides uniformly to control grasses and weeds without considering the significant weed density variability and bare spots within fields. The repeated and excessive use of herbicides... Q. Zaman, Y. Chang, A. Farooque, A. Schumann, D. Percival, M. Cheema, T. Esau |
15. Development of Sensing System Using Digital Photography Technique for Spot-Application of Herbicide in Wild Blueberry FieldsAn automated sensing system, hardware and software, was developed for spot-application of herbicide with 6.1 m boom automated prototype sprayer.... Q. Zaman, T.J. Esau, A.A. Farooque, A.W. Schumann, D.C. Percival, Y.K. Chang |
16. Relationship of Soil Properties to Apparent Ground Conductivity in Wild Blueberry FieldsOne of the fundamental deficiencies in high value crops is the lack of detailed, up-to-date and pertinent geo-referenced soil information for site-specific crop management to improve productivity. This experiment was designed to estimate and map soil properties rapidly and reliably using an electromagnetic induction (EMI) method. Two wild blueberry... F.S. Khan, Q.U. Zaman, A.W. Schumann, A. Madani, D.C. Percival, A.A. Farooque, S.R. Saleem, F.S. Khan |
17. Impact of Variable Rate Fertilization on Nutrients Losses in Surface Runoff for Wild Blueberry FieldsWild blueberry producers apply agrochemicals uniformly without considering substantial variation in soil properties, topographic features that may affect fruit yield within field. A wild blueberry field was selected to evaluate the impact of variable rate (VR) fertilization on nutrient losses in surface runoff from steep slope to low lying areas to improve crop... S. Slaeem, Q.U. Zaman, A. Madani, A. Schumann, D. Percival, H.N. Ahmad, A.A. Farooque, F. Khan |
18. Sensor Fusion on a Wild Blueberry Harvester for Fruit Yield, Plant Height and Topographic Features Mapping to Improve Crop ProductivitySite-specific crop management can improve profitability and environmental risks of wild blueberry crop having large spatial variation in soil/plant characteristics, topographic features which may affect fruit yield. An integrated automated sensor fusion system including an ultrasonic sensor, a digital color camera, a slope sensor,... A.A. Farooque, Q.U. Zaman, D. Groulx, A.W. Schumann, T.J. Esau, Y.K. Chang |
19. Weed Identification From Seedling Cabbages Using Visible And Near-Infrared Spectrum AnalysisTarget identification is one of the main research content and also a key point in precision crop protection. The main purpose of the study is to choose the characteristic wavelengths (CW for short) to classify the cabbages and the weeds at their seedling stage using different data analysis methods. Using a handheld full-spectrum FieldSpec-FR, the canopies of the seedling plants, cabbage ‘8398, cabbage ‘zhonggan’, Barnyard grass, green foxtail, goosegrass,... W. Deng, X. Wang, C. Zhao, Y. Huang |
20. Comparison Of Management Zones Generated By The K-Means And Fuzzy C-Means MethodsThe generation of Management Zones (MZ) is an economic alternative to make viable the precision agriculture (RODRIGUES & ZIMBACK, 2002) because they work as operation units for the inputs localized application and as soil and culture sample indicators. For the field division in... E. Souza, K. Schenatto, F. Rodrigues, D. Rocha, C. Bazzi |
21. The Influence Of The Interpolation Method In The Management Zones GenerationThe definition of management zones (MZ) allows the concepts of precision agriculture (PA) to be used even in small producers. Methods for defining these MZ were created and are being used, obtaining satisfactory results with different crops and parameters (FLEMING & WESTFALL, 2000; ORTEGA & SANTIBÁÑEZ, 2007; MILANI et al., 2006). Through methodologies, the attributes that are influencing the productivity are selected and thematic maps are generated with the... K. Schenatto, C. Bazzi, V. Bier, E. Souza |
22. Recognition And Classification Of Weeds In Sugarcane Using The Technique Of The Bag Of WordsThe production of sugar and ethanol in Brazil is very prominent economically and the reducing costs and improving the production system being necessary. The management crops operations of sugarcane and the control of weed is one of the processes that cause the greatest increase in production costs; because the competition that exists between cane plants and weed, for water, nutrients and sunlight is big, contribute to the loss of up to 20% of the useful cane. The use of image processing techniques... W.E. Santiago, A.R. Barreto, D.G. Figueredo, R.C. Tinini, B.T. Mederos, N.J. Leite |
23. Advances In Automating Individual Plant Care Of Vegetable CropsAutomation of individual crop plant care in commercial vegetable crop fields has increased practical feasibility and improved efficiency and economic benefit if a systems approach is taken in the engineering design to mechanization that incorporates precision planting techniques. In addition to the optimization in the biological productivity of crop plants when the spatial distribution of crop plants allows their uniform access to nutrients, water and light in an optimum utilization... M. Pérez ruiz, D.C. Slaughter |
24. The Daily Erosion Project - High Resolution, Daily Estimates of Runoff, Detachment, Erosion, and Soil MoistureRunoff and sediment transport from agricultural uplands are substantial threats to water quality and sustained crop production. Farmers, conservationists, and policy makers must understand how landforms, soil types, farming practices, and rainfall affect soil erosion and runoff in order to improve management of soil and water resources. A system was designed and implemented a decade ago to inventory precipitation, runoff, and soil erosion across the state of Iowa, United States. That system utilized... B.K. Gelder, R. Cruse, D. James, D. Herzmann, C. Sandoval-green, T. Sklenar |
25. Regional Usefulness of Nitrogen Management Zone Delineation ToolsIn the Northern Plains of Montana, North Dakota and Minnesota, a number of site-specific tools have been used to delineate nitrogen management zones. A three-year study was conducted using yield mapping, elevation measurements, satellite imagery, aerial Ektochrome® photography, and soil EC to delineate nitrogen management zones and compare these zones to residual fall soil nitrate. At most of the sites, variable-rate N was applied and compared with uniform N application. The site-specific... D. Franzen, F. Casey, J. Staricka, D. Long, J. Lamb, A. Sims, M. Halvorson, V. Hofman |
26. Three Years of On-Farm Evaluation of Dynamic Variable Rate Irrigation: What Have We Learned?This paper will present a dynamic Variable Rate Irrigation System developed by the University of Georgia. The system consists of the EZZone management zone delineation tool, the UGA Smart Sensor Array (UGA SSA) and an irrigation scheduling decision support tool. An experiment was conducted in 2015, 2016 and 2017 in two different peanut fields to evaluate the performance of using the UGA SSA to dynamically schedule Variable Rate Irrigation (VRI). For comparison reasons strips were designed within... V. Liakos, W. Porter, X. Liang, M. Tucker, A. Mclendon, C. Perry, G. Vellidis |
27. Management Zone Delineation for Irrigation Based on Sentinel-2 Satellite Images and Field PropertiesThis paper presents a case study of the first application of the dynamic Variable Rate Irrigation (VRI) System developed by the University of Georgia to cotton. The system consists of the EZZone management zone software, the University of Georgia Smart Sensor Array (UGA SSA) and an irrigation scheduling decision support tool. An experiment was conducted in 2017 in a cotton field to evaluate the performance of the system in cotton. The field was divided into four parallel strips. All four strips... V. Liakos, G. Vellidis, L. Lacerda, W. Porter, M. Tucker, C. Cox |
28. 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 application... D. Larsen, S. Skovsen, K.A. Steen, K. Grooters, O. Green, R.N. Jørgensen, J. Eriksen |
29. Creating Thematic Maps and Management Zones for Agriculture FieldsThematic maps (TMs) are maps that represent not only the land but also a topic associated with it, and they aim to inform through graphic symbols where a specific geographical phenomenon occurs. Development of TMs is linked to data collection, analysis, interpretation, and representation of the information on a map, facilitating the identification of similarities, and enabling the visualization of spatial correlations. Important issues associated with the creation of TMs are: selection of the... E. Souza, K. Schenatto, C. Bazzi |
30. 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-truthing... 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 |
31. Spatially Explicit Prediction of Soil Nutrients and Characteristics in Corn Fields Using Soil Electrical Conductivity Data and Terrain AttributesSite specific nutrient management (SSNM) in corn production environments can increase nutrient use efficiency and reduce gaseous and leaching losses. To implement SSNM plans, farmers need methods to monitor and map the spatial and temporal trends of soil nutrients. High resolution electrical conductivity (EC) mapping is becoming more available and affordable. The hypothesis for this study is that EC of the soil, in conjunction with detailed terrain attributes, can be used to map soil nutrients... S. Sela, N. Graff, K. Mizuta, Y. Miao |
32. Meta Deep Learning Using Minimal Training Images for Weed Classification in Wild BlueberryDeep learning convolutional neural networks (CNNs) have gained popularity in recent years for their ability to classify images with high levels of accuracy. In agriculture, they have been applied for disease identification, crop growth monitoring, animal behaviour tracking, and weed classification. Datasets traditionally consisting of thousands of images of each desired target are required to train CNNs. A recent survey of Nova Scotia wild blueberry (Vaccinium angustifolium Ait.) fields,... P.J. Hennessy, T.J. Esau, A.W. Schumann, A.A. Farooque, Q.U. Zaman, S.N. White |
33. Establishing the First Soil Water Characteristics Curve for the Soils of Prince Edward Island, CanadaSoil water characteristics curve (SWCC), for Prince Edward Island (PEI), is much more needed currently for the sustainable production of agriculture yields. It will not only fulfil the requirements of the province’s farmers for irrigation scheduling but also help the government to decide about permitting the use of groundwater for supplemental irrigation on the island. A soil water characteristics curve in PEI does not exist to support precision agriculture practices. Precision irrigation... S.J. Cheema, A.A. Farooque, F. Abbas, T. Esau, K. Grewal |
34. Evaluating a Satellite Remote Sensing and Calibration Strip-based Precision Nitrogen Management Strategy for Corn in Minnesota and IndianaPrecision nitrogen (N) management (PNM) aims to match N supply with crop N demand in both space and time and has the potential to improve N use efficiency (NUE), increase farmer profitability, and reduce N losses and negative environmental impacts. However, current PNM adoption rate is still quite low. A remote sensing and calibration strip-based PNM strategy (RS-CS-PNM) has been developed by the Precision Agriculture Center at the University of Minnesota.... K. Mizuta, Y. Miao, A.C. Morales, L.N. Lacerda, D. Cammarano, R.L. Nielsen, R. Gunzenhauser, K. Kuehner, S. Wakahara, J.A. Coulter, D.J. Mulla, D. . Quinn, B. Mcartor |
35. Identifying Key Factors Influencing Yield Spatial Pattern and Temporal Stability for Management Zone DelineationManagement zone delineation is a practical strategy for site-specific management. Numerous approaches have been used to identify these homogenous areas in the field, including approaches using multiple years of historical yield maps. However, there are still knowledge gaps in identifying variables influencing spatial and temporal variability of crop yield that should be used for management zone delineation. The objective of this study is to identify key soil and landscape properties affecting... L.N. Lacerda, Y. Miao, K. Mizuta, K. Stueve |
36. Evaluating the Potential of Improving In-season Nitrogen Status Diagnosis of Potato Using Leaf Fluorescence Sensors and Machine LearningPrecision nitrogen (N) management is particularly important for potato crops due to their high N fertilizer demand and high N leaching potential caused by their shallow root systems and preference for coarse-textured soils. Potato farmers have been using a standard lab analysis called petiole nitrate-N (PNN) test as a tool to diagnose potato N status and guide in-season N management. However, the PNN test suffers from many disadvantages including time constraints, labor, and cost of analysis.... S. Wakahara, Y. Miao, S. Gupta, C. Rosen, K. Mizuta, J. Zhang, D. Li |
37. Spatial Analysis of Soil Moisture and Turfgrass Health to Determine Zones for Spatially Variable Irrigation ManagementThe Western United States is currently experiencing a “Mega Drought”. This makes efficient water use more important than ever. Turfgrass is a major vegetation type in urban areas and performs many ecosystem services such as cooling through evapotranspiration, fixing carbon from the atmosphere and reducing wild-fire risk. There are now more acres of irrigated turfgrass (>40 million) in the USA than irrigated corn, wheat and fruit trees combined (Milesi et al., 2005). It has been... R. Kerry, S. Shumate, B. Ingram, K. Hammond, D. Gunther, R. Jensen, S. Schill, N. Hansen, B. Hopkins |
38. AgDataBox-IoT - Managing IoT Data and Devices on Precision AgricultureThe increasing global population has resulted in a substantial demand for nourishment, which has prompted the agricultural sector to investigate ways to improve efficiency. Precision agriculture (PA) uses advanced technologies such as the Internet of Things (IoT) and sensor networks to collect and analyze field information. Although the advantages are numerous, the available data storage, management, and analysis resources are limited. Therefore, creating and providing a user-friendly web application... C.L. Bazzi, W.K. Oliveira, R. Sobjak, K. Schenatto, E. Souza, A. Hachisuca, F. Franz |
39. Within-field Spatial Variability in Optimal Sulfur Rates for Corn in Minnesota: Implications for Precision Sulfur ManagementThe ongoing decline in sulfur (S) atmospheric depositions and high yield crop production have resulted in S deficiency and the need for S fertilizer applications in corn cropping systems. Many farmers are applying S fertilizers uniformly across their fields. Little has been reported on the within-field spatial variability in optimal S rates and the potential benefits of variable rate S applications. The objectives of this study were to 1) assess within-field variability of optimal S rates (OSR),... R.P. Negrini, Y. Miao, K. Mizuta, K. Stueve, D. Kaiser, J.A. Coulter |
40. Effects of Crop Rotation on In-season Estimation of Optimal Nitrogen Rates for Corn Based on Proximal and Remote Sensing DataA remote sensing and calibration strip-based precision nitrogen (N) management (RS-CS-PNM) strategy has been developed by the Precision Agriculture Center at the University of Minnesota to provide in-season N recommendation rates based on satellite imagery. This strategy involves the application of multiple N rates before planting and the identification of the agronomic optimum N rate (AONR) at V7-V8 growth stages using normalized difference vegetation index (NDVI) calculated using satellite imagery.... A.C. Morales, D. . Quinn, K. Mizuta, Y. Miao |
41. In-season Diagnosis of Corn Nitrogen and Water Status Using UAV Multispectral and Thermal Remote SensingFor irrigated corn fields, how to optimize nitrogen (N) and irrigation simultaneously is a great challenge. A promising strategy is to use remote sensing to diagnose corn N and water status during the growing season, which can then be used to guide in-season variable rate N application and irrigation management. The objective of this study was to evaluate the effectiveness of UAV multispectral and thermal remote sensing in simultaneous diagnosis of corn N and water status. Two field experiments... Y. Miao, A. Kechchour, V. Sharma, A. Flores, L. Lacerda, K. Mizuta, J. Lu, Y. Huang |
42. On-farm Evaluation of the Potential Benefits of Variable Rate Seeding for Corn in MinnesotaMany farmers in Minnesota are interested in adopting variable rate seeding technology for corn, however, little has been reported about their potential benefits. The objectives of this study were to 1) determine within-field variability of optimal seeding rates, and 2) evaluate the potential benefits of variable rate seeding in commercial corn fields in Minnesota. Four on-farm variable rate seeding trials were conducted in Minnesota in 2022 and 2023, with seeding rates ranging from 31,000 to 41,000... Y. Miao, A. Kechchour, S. Folle, K. Mizuta |
43. Remote and Proximal Sensing for Sustainable Water Use in Almond Orchards in Southeast Spain in a Digital Farming ContextThe increasing expansion of irrigated almond orchards in regions of southeast Spain, facing water scarcity, underscores the need for a more effective and precise monitoring of the crop water status to optimize irrigation scheduling and improve crop water use efficiency. Remote and proximal sensing, combining visible, multispectral and thermal capabilities at different scales allows to estimate water needs, detect and quantify crop water stress, or identify different productivity zones within an... |
44. Evaluating Different Strategies to Analyze On-farm Precision Nitrogen Trial DataOn-farm trials are being conducted by more and more researchers and farmers. On-farm trials are very different to traditional small plot experiments due to the existence of significant within-field variability in soil-landscape conditions. Traditional statistical techniques like analysis of variance (ANOVA) are commonly adopted for on-farm trial analysis to evaluate overall performance of different treatments, assuming uniform environmental and management factors within a field. As a result, the... K. Mizuta, Y. Miao, J. Lu, R.P. Negrini |