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Jurado-Expósito, M
Green, R.L
Souza, E
Sandoval-Green, C
Sims, A
Mizuta, K
Tinini, R.C
Pérez Ruiz, M
Blackmer, T.M
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Authors
Gómez-Candón, D
Caballero-Novella, J.J
Peña-Barragán, J.M
Jurado-Expósito, M
Garcia-Torres, L
López-Granados, F
deCastro, A.I
Blackmer, T.M
Kyveryga, P.M
Kyveryga, P.M
Blackmer, T.M
Kyveryga, P.M
Blackmer, T.M
Reeg, P.R
Blackmer, T.M
Kyveryga, P.M
Kyveryga, P.M
Blackmer, T.M
Pearson , R
Blackmer, T.M
Kyveryga, P.M
Souza, E
Schenatto, K
Rodrigues, F
Rocha, D
Bazzi, C.L
Schenatto, K
Bazzi, C.L
Bier, V
Souza, E
Santiago, W.E
Barreto, A.R
Figueredo, D.G
Tinini, R.C
Mederos, B.T
Leite, N.J
Pérez Ruiz, M
Slaughter, D.C
Gelder, B.K
Cruse, R
James, D
Herzmann, D
Sandoval-Green, C
Sklenar, T
Franzen, D.W
Casey, F
Staricka, J
Long, D
Lamb, J
Sims, A
Halvorson, M
Hofman, V
Souza, E
Schenatto, K
Bazzi, C
Bhandari, S
Raheja, A
Chaichi, M.R
Green, R.L
Do, D
Ansari, M
Wolf, J.G
Espinas, A
Pham, F.H
Sherman, T.M
Sela, S
Graff, N
Mizuta, K
Miao, Y
Mizuta, K
Miao, Y
Morales, A.C
Lacerda, L.N
Cammarano, D
Nielsen, R.L
Gunzenhauser, R
Kuehner, K
Wakahara, S
Coulter, J.A
Mulla, D.J
Quinn, D.
McArtor, B
Lacerda, L.N
Miao, Y
Mizuta, K
Stueve, K
Wakahara, S
Miao, Y
Gupta, S
Rosen, C
Mizuta, K
Zhang, J
Li, D
Bazzi, C.L
Oliveira, W.K
Sobjak, R
Schenatto, K
Souza, E
Hachisuca, A
Franz, F
Negrini, R.P
Miao, Y
Mizuta, K
Stueve, K
Kaiser, D
Coulter, J.A
Morales, A.C
Quinn, D.
Mizuta, K
Miao, Y
Miao, Y
Kechchour, A
Sharma, V
Flores, A
Lacerda, L
Mizuta, K
Lu, J
Huang, Y
Miao, Y
Kechchour, A
Folle, S
Mizuta, K
Mizuta, K
Miao, Y
Lu, J
Negrini, R.P
Topics
Remote Sensing Applications in Precision Agriculture
Precision Crop Protection
Precision Nutrient Management
Spatial Variability in Crop, Soil and Natural Resources
Precision A-Z for Practitioners
Precision Conservation Management
Precision Crop Protection
Engineering Technologies and Advances
Precision Conservation Management
Spatial and Temporal Variability in Crop, Soil and Natural Resources
Education and Outreach in Precision Agriculture
Applications of Unmanned Aerial Systems
Site-Specific Nutrient, Lime and Seed Management
In-Season Nitrogen Management
Big Data, Data Mining and Deep Learning
Wireless Sensor Networks and Farm Connectivity
Site-Specific Nutrient, Lime and Seed Management
In-Season Nitrogen Management
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
On Farm Experimentation with Site-Specific Technologies
Type
Poster
Oral
Year
2012
2010
2014
2016
2008
2018
2022
2024
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Filter results25 paper(s) found.

1. Using Late-season Uncalibrated Digital Aerial Imagery For Predicting Corn Nitrogen Status Within Fields

Using 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

2. A Systematic Approach For Using Precision Agriculture Tools For On-farm Evaluations In Iowa

 The 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

3. Position Error of Input Prescription Map Delineated From Remote Images

     The 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

4. Precision Tools to Evaluate Alternative Weed Management Systems in Soybean

... T.M. Blackmer, P.M. Kyveryga

5. Site-Specific Evaluations of Nitrification Inhibitor with Fall Applications of Liquid Swine Manure

... P.M. Kyveryga, T.M. Blackmer

6. Digital Aerial Imagery Guides a Statewide Nutrient Management Benchmarking Survey

... P.M. Kyveryga, T.M. Blackmer

7. 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

8. Comparison Of Management Zones Generated By The K-Means And Fuzzy C-Means Methods

The 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

9. The Influence Of The Interpolation Method In The Management Zones Generation

The 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

10. Recognition And Classification Of Weeds In Sugarcane Using The Technique Of The Bag Of Words

The 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

11. Advances In Automating Individual Plant Care Of Vegetable Crops

Automation 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

12. The Daily Erosion Project - High Resolution, Daily Estimates of Runoff, Detachment, Erosion, and Soil Moisture

Runoff 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

13. Regional Usefulness of Nitrogen Management Zone Delineation Tools

In 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

14. Creating Thematic Maps and Management Zones for Agriculture Fields

Thematic 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

15. Effectiveness of UAV-Based Remote Sensing Techniques in Determining Lettuce Nitrogen and Water Stresses

This 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

16. Spatially Explicit Prediction of Soil Nutrients and Characteristics in Corn Fields Using Soil Electrical Conductivity Data and Terrain Attributes

Site 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

17. Evaluating a Satellite Remote Sensing and Calibration Strip-based Precision Nitrogen Management Strategy for Corn in Minnesota and Indiana

Precision 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

18. Identifying Key Factors Influencing Yield Spatial Pattern and Temporal Stability for Management Zone Delineation

Management 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

19. Evaluating the Potential of Improving In-season Nitrogen Status Diagnosis of Potato Using Leaf Fluorescence Sensors and Machine Learning

Precision 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

20. AgDataBox-IoT - Managing IoT Data and Devices on Precision Agriculture

The 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

21. Within-field Spatial Variability in Optimal Sulfur Rates for Corn in Minnesota: Implications for Precision Sulfur Management

The 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

22. Effects of Crop Rotation on In-season Estimation of Optimal Nitrogen Rates for Corn Based on Proximal and Remote Sensing Data

A 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

23. In-season Diagnosis of Corn Nitrogen and Water Status Using UAV Multispectral and Thermal Remote Sensing

For 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

24. On-farm Evaluation of the Potential Benefits of Variable Rate Seeding for Corn in Minnesota

Many 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

25. Evaluating Different Strategies to Analyze On-farm Precision Nitrogen Trial Data

On-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