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Mizuta, K
Wallor, E
Cai, S
Fernandez-Novales, J
Deckers, T
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Authors
Wouters, N
Van Beers, R
De Ketelaere, B
Deckers, T
De Baerdemaeker, J
Saeys, W
Gebbers, R
Dworak, V
Mahns, B
Weltzien, C
Büchele, D
Gornushkin, I
Mailwald, M
Ostermann, M
Rühlmann, M
Schmid, T
Maiwald, M
Sumpf, B
Rühlmann, J
Bourouah, M
Scheithauer, H
Heil, K
Heggemann, T
Leenen, M
Pätzold, S
Welp, G
Chudy, T
Mizgirev, A
Wagner, P
Beitz, T
Kumke, M
Riebe, D
Kersebaum, C
Wallor, E
Tardaguila, J
Diago, M
Gutierrez, S
Fernandez-Novales, J
Moreda, E.A
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
Cai, S
Xu, S
Zhang, D
Zhu, H
Longchamps, L
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
Sensor Application in Managing In-season CropVariability
Precision Nutrient Management
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Site-Specific Nutrient, Lime and Seed Management
In-Season Nitrogen Management
Big Data, Data Mining and Deep Learning
Land Improvement and Conservation Practices
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
Oral
Poster
Year
2014
2016
2018
2022
2024
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Filter results13 paper(s) found.

1. Towards Automated Pneumatic Thinning Of Floral Buds On Pear Trees

Thinning of pome and stone fruit is an important horticultural practice that is used to enhance fruit set and quality by removing excess floral buds. As it is still mostly conducted through manual labor, thinning comprises a large part of a grower’s production costs. Various thinning machines developed in recent years have clearly demonstrated that mechanization of this technique is both feasible and cost effective. Generally, these machines still lack sufficient selectivity... N. Wouters, R. Van beers, B. De ketelaere, T. Deckers, J. De baerdemaeker, W. Saeys

2. Integrated Approach to Site-specific Soil Fertility Management

In precision agriculture the lack of affordable methods for mapping relevant soil attributes is a funda­mental problem. It restricts the development and application of advanced models and algorithms for decision making. The project “I4S - Integrated System for Site-Specific Soil Fertility Management” combines new sensing technologies with dynamic soil-crop models and decision support systems. Using sensors with different measurement principles improves the estimation of soil fertility... R. Gebbers, V. Dworak, B. Mahns, C. Weltzien, D. Büchele, I. Gornushkin, M. Mailwald, M. Ostermann, M. Rühlmann, T. Schmid, M. Maiwald, B. Sumpf, J. Rühlmann, M. Bourouah, H. Scheithauer, K. Heil, T. Heggemann, M. Leenen, S. Pätzold, G. Welp, T. Chudy, A. Mizgirev, P. Wagner, T. Beitz, M. Kumke, D. Riebe, C. Kersebaum, E. Wallor

3. On-the-Go Nir Spectroscopy and Thermal Imaging for Assessing and Mapping Vineyard Water Status in Precision Viticulture

New proximal sensing technologies are desirable in viticulture to assess and map vineyard spatial variability. Towards this end, high-spatial resolution information can be obtained using novel, non-invasive sensors on-the-go. In order to improve yield, grape quality and water management, the vineyard water status should be determined. The goal of this work was to assess and map vineyard water status using two different proximal sensing technologies on-the-go: near infrared (NIR) reflectance spectroscopy... J. Tardaguila, M. Diago, S. Gutierrez, J. Fernandez-novales, E.A. Moreda

4. 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

5. 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

6. 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

7. 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

8. Soil Microbial Biomass and Bacterial Diversity Enhanced Through Winter Cover Cropping in Paddy Fields

Rice production is typically based on input-intensive and often environmentally unsustainable monoculture system. Alternatives are increasing, such as fallow cover cropping and rice–fish coculture (RFC). However, options of fallow cover cropping in RFC are scarcely explored, and the soil microbial response strategies to cover cropping remain unclear. Here, we evaluated soil-plant-microbe interactions under three cover cropping systems: Chinese milk vetch single cropping (CM), rapeseed single... S. Cai, S. Xu, D. Zhang, H. Zhu, L. Longchamps

9. 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

10. 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

11. 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

12. 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

13. 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