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Campos, R.P
Castillejo-Gonz, I
Cardoso, T.F
Coulter, J.A
Chou, T
Crnojevic, V
Chen, Y
Choi, J
Castrignanò, A
Chen, Y
Cardoso, G.M
Takahashi, T
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Authors
Chung, S
Kim, K
Kim, H
Choi, J
Zhang, Y
Kang, S
Han, K
Hur, S
Chung, S
Huh, Y
Choi, J
Ryu, D
Kim, K
Kim, H
Kim, H
Chou, T
Yeh, M
Chen, J
Basso, B
Mueller, T
Corá, J
Castrignanò, A
Rodrigues, M
Rienzi, E
Garcia-Torres, L
Gomez-Candon, D
Caballero-Novella, J.J
Gomez-Casero, M
Pe, J.M
Jurado-Exp, M
Lopez-Granados, F
Castillejo-Gonz, I
Garc, A
Garcia-Torres, L
Gomez-Candon, D
Caballero-Novella, J.J
Pe, J.M
Jurado-Exp, M
Castillejo-Gonz, I
Garc, A
Lopez-Granados, F
Prassack, L
Li, L
Jiang, D
Campos, R.P
Lu, Z
Tian, L.F
Castro, S.G
Sanches, G.M
Cardoso, G.M
Silva, A.E
Franco, H.C
Magalhães, P.S
Zhao, T
Chen, Y
Franzen, J
Gonzalez, J
Yang, Q
Zhao, T
Cisneros, M
Chen, Y
Yang, Q
Zhang, Y
Sanches, G.M
Cardoso, T.F
Chagas, M.F
Luciano, A.C
Duft, D.G
Magalhães, P.S
Franco, H.C
Bonomi, A
Tagarakis, A.C
van Evert, F
Milic, D
Crnojevic, V
Crnojevic-Bengin, V
Kempenaar, C
Ljubicic, N
Chen, Y
He, Y
Behrendt, K
Takahashi, T
Rutter, M.S
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
Topics
Precision Horticulture
Modeling and Geo-statistics
Spatial Variability in Crop, Soil and Natural Resources
Remote Sensing Applications in Precision Agriculture
Proximal Sensing in Precision Agriculture
Precision Nutrient Management
Remote Sensing Applications in Precision Agriculture
Precision Agriculture and Global Food Security
Small Holders and Precision Agriculture
Applications of Unmanned Aerial Systems
ISPA Community: Economics
In-Season Nitrogen Management
Type
Poster
Oral
Year
2012
2010
2014
2016
2018
2022
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Filter results15 paper(s) found.

1. Remote Control System for Greenhouse Environment Using Mobile Devices

Protected crop production facilities such as greenhouse and plant factory have drawn interest and the area is increasing in Korea as well as in other countries in the world. Remote... S. Chung, K. Kim, H. Kim, J. Choi, Y. Zhang, S. Kang, K. han, S. Hur

2. Determination of Sensor Locations for Monitoring of Soil Water Content in Greenhouse

 Monitoring and control of environmental condition is highly important for optimum control of the conditions, especially in greenhouse and plant factor, and the condition... S. Chung, Y. Huh, J. Choi, D. Ryu, K. Kim, H. Kim, H. Kim

3. I-SALUS: New Web Based Spatial Systems for Simulating Crop Yield and Environmental Impact

  SALUS (System Approach to Land Use Sustainability) model is designed to simulate the impact of agronomic management on yield and environmental impact. SALUS model has new approaches and algorithms for simulating soil carbon, nitrogen, phosphorous, tillage, soil water balance and yield components. In the past, the use of the crop model was not easy for general... T. Chou, M. Yeh, J. Chen, B. Basso

4. Spatial and Temporal Variability of Corn Grain Yield as a Function of Soil Parameters, and Climate Factors

Effective site-specific management requires an understanding the influence of soil and weather on yield variability. Our objective was to examine the influence of soil, precipitation, and temperature on spatial and temporal corn grain yield variability.  The study site (10 by 250 -m in size) was located in Jaboticabal, São Paulo State, on a Rhodic Hapludox. Corn yield (planted with 0.9-m spacing) was measured... T. Mueller, J. Corá, A. Castrignanò, M. Rodrigues, E. Rienzi

5. Sectioning And Assessment Remote Images For Precision Agriculture: The Case Of Orobanche Crenate In Pea Crop

  The software SARI® has been developed to implement precision agriculture strategies through remote sensing imagery. It is written in IDL® and works as an add-on of ENVI®. It has been designed to divide remotely sensed imagery into “micro-images”, each corresponding to a small area (“micro-plot”), and to determine the quantitative agronomic and/or environmental biotic (i.e. weeds, pathogens) and/or non-biotic (i.e. nutrient levels) indicator/s... L. Garcia-torres, D. Gomez-candon, J.J. Caballero-novella, M. Gomez-casero, J.M. Pe, M. Jurado-exp, F. Lopez-granados, I. Castillejo-gonz, A. Garc

6. Management Of Remote Imagery For Precision Agriculture

Satellite and airborne remotely sensed images cover large areas, which normally include dozens of agricultural plots. Agricultural operations such as sowing, fertilization, and pesticide applications are designed for the whole plot area, i.e. 5 to 20 ha, or through precision agriculture. This takes into account the spatial variability of biotic and of abiotic factors and uses diverse technologies to apply inputs at variable rates, fitted to the needs of each small defined area, i.e. 25 to 200... L. Garcia-torres, D. Gomez-candon, J.J. Caballero-novella, J.M. Pe, M. Jurado-exp, I. Castillejo-gonz, A. Garc, F. Lopez-granados, L. Prassack

7. Field-Based High-Throughput Phenotyping Approach For Soybean Plant Improvement

The continued development of new, high yielding cultivars needed to meet the world’s growing food demands will be aided by improving the technology to rapidly phenotype potential cultivars. High-throughput phenotyping (HTP) is essential to maximize the greatest value of genetics analysis and to better understand the plant biology and physiology in view of a “Feed the World in 2050” theme. Field-based high-throughput phenotyping platform... L. Li, D. Jiang, R.P. Campos, Z. Lu, L.F. Tian

8. Use of Crop Canopy Reflectance Sensor in Management of Nitrogen Fertilization in Sugarcane in Brazil

Given the difficulty to determine N status in soil testing and lack of crop parameters to recommend N for sugarcane in Brazil raise the necessity of identify new methods to find crop requirement to improve the N use efficiency. Crop canopy sensor, such as those used to measure indirectly chlorophyll content as N status indicator, can be used to monitor crop nutritional demand. The objective of this experiment was to assess the nutritional status of the sugarcane fertilized with different nitrogen... S.G. Castro, G.M. Sanches, G.M. Cardoso, A.E. Silva, H.C. Franco, P.S. Magalhães

9. Melon Classification and Segementation Using Low Cost Remote Sensing Data Drones

Object recognition represents currently one of the most developing and challenging areas of the Computer Vision. This work presents a systematic study of various relevant parameters and approaches allowing semi-automatic or automatic object detection, applied onto a study case of melons on the field to be counted. In addition it is of a cardinal interest to obtain the quantitative information about performance of the algorithm in terms of metrics the suitability whereof is determined by the final... T. Zhao, Y. Chen, J. Franzen, J. Gonzalez, Q. Yang

10. Almond Canopy Detection and Segmentation Using Remote Sensing Data Drones

The development of Unmanned Aerial System (UAV) makes it possible to take high resolution images of trees easily. These images could help better manage the orchard. However, more research is necessary to extract useful information from these images. For example, irrigation schedule and yield prediction both rely on accurate measurement of canopy size. In this paper, a workflow is proposed to count trees and measure the canopy size of each individual tree. The performances of three different methods... T. Zhao, M. Cisneros, Y. Chen, Q. Yang, Y. Zhang

11. Economic and Environmental Impacts in Sugarcane Production to Meet the Brazilian Ethanol Demands by 2030: The Role of Precision Agriculture

The agreement signed at COP-21 reaffirms the vital compromise of Brazil with sugarcane and ethanol production. To meet the established targets, the ethanol production should be 54 billion liters in 2030. From the agronomic standpoint, two alternatives are possible; increase the planted area and/or agricultural yield. The present study aimed to evaluate the economic and environmental impacts in sugarcane production meeting the established targets in São Paulo state. In this context, were... G.M. Sanches, T.F. Cardoso, M.F. Chagas, A.C. Luciano, D.G. Duft, P.S. Magalhães, H.C. Franco, A. Bonomi

12. Opportunities for Precision Agriculture in Serbia

The aim of this paper is to analyze the factors leading to low adoption rate of precision farming in Serbia and to describe steps being taken by BioSense institute to increase it. The majority of the arable land in Serbia is grown by small family owned and operated farms most of which are in the range of 2 to 5 ha making them highly unsustainable. Only 16% of the arable land is managed by agricultural companies and cooperatives. We believe that the adoption of advanced technologies with the currently... A.C. Tagarakis, F. Van evert, D. Milic, V. Crnojevic, V. Crnojevic-bengin, C. Kempenaar, N. Ljubicic

13. Rape Plant NDVI Spatial Distribution Model Based on 3D Reconstruction

Plants’ 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. chlorophyll... Y. Chen, Y. He

14. Determining the Marginal Value of Extra Precision in Precision Grazing Systems – an Ex Ante Analysis of Impacts on System Productivity, Sustainability and Economics

The development of precision livestock farming (PLF) technologies for application in grazing systems is rapidly evolving. PLF technologies that facilitate the spatial and temporal management of variability in landscapes, pastures and animals promise to improve the efficiency, profitability and sustainability of livestock farming. However, such technologies as a complete package do not yet exist in grazing systems and the question of impacts at the farm system level remains unresolved. Other potential... K. Behrendt, T. Takahashi, M.S. Rutter

15. 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