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Thompson, L
Zydenbos, S
Tanny, J
Klapp, I
Ikpi, A
Damerow, L.M
Johnson, E
Kumar, R
Dota, M.A
Zhou, J
Jimenez, N
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Authors
Damerow, L.M
Blanke, M.M
Zhou, R.R
Santos, C
Weschter, E.O
Dota, M.A
Cugnasca, C.E
Blanke, M.M
Damerow, L.M
Seehuber, C
Makkar, M.S
Kaul, A
Kumar, R
Sharma, A
Sekhon, B.S
Pannu, C.S
Khot, L
Zhou, J
Boydston, R
Miklas, P.N
Porter, L
Luck, J
Parrish, J
Thompson, L
Krienke, B
Glewen, K
Ferguson, R.B
Olayide, O
Alene, A
Ikpi, A
Nziguheba, G
Alabi, T
Rozenstein, O
Haymann, N
Kaplan , G
Tanny, J
Zhou, J
Sudduth, K.A
Feng, A
King, W
Dynes, R
Laurenson, S
Zydenbos, S
MacAuliffe, R
Taylor, A
Manning, M
Roberts, A
White, M
Osann, A
Campos, I
Calera, M
Plaza, C
Bodas, V
Calera, A
Villodre, J
Campoy, J
Sanchez, S
Jimenez, N
Lopez, H
Zhou, J
Xu, Z
Zhou, J
Zhou, J
Ha, T
Aldridge, K
Johnson, E
Shirtliffe, S.J
Ryu, S
Krys, K
Shirtliffe, S
Duddu, H
Ha, T
Attanayake, A
Johnson, E
Andvaag, E
Stavness, I
Ransom, C.J
Vong, C
Veum, K.S
Sudduth, K.A
Kitchen, N.R
Zhou, J
Lee, K
Sudduth, K.A
Zhou, J
Rozenstein, O
Cohen, Y
Alchanatis , V
Behrendt, K
Bonfil, D.J
Eshel, G
Harari, A
Harris, W.E
Klapp, I
Laor, Y
Linker, R
Paz-Kagan, T
Peets, S
Rutter, M.S
Salzer, Y
Lowenberg-DeBoer, J
Zhou, J
Xu, Z
Safranski, T.J
Bromfield, C
Topics
Precision Horticulture
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change, Standards)
Engineering Technologies and Advances
Precision Nutrient Management
Unmanned Aerial Systems
Sensor Application in Managing In-season Crop Variability
Spatial and Temporal Variability in Crop, Soil and Natural Resources
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Applications of Unmanned Aerial Systems
Site-Specific Pasture Management
In-Season Nitrogen Management
Farm Animals Health and Welfare Monitoring
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Applications of Unmanned Aerial Systems
Drivers and Barriers to Adoption of Precision Ag Technologies or Digital Agriculture
Precision Dairy and Livestock Management
Type
Poster
Oral
Year
2012
2014
2016
2008
2018
2022
2024
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Authors

Filter results19 paper(s) found.

1. Recognition Algorithms for Detection of Apple Fruit in an Orchard for Early Yield Prediction

... L.M. Damerow, M.M. Blanke, R.R. Zhou

2. Radio Frequency Identification For Implementing Traceability In The Cotton Production In The Brazilian Midwest

According to the International Cotton Advisory Committee - ICAC projection for the fiber in cotton production for the crop year 2012/2013 is expected to reach an amount of 15.19 million tons , according to a forecast released in August 2012 . In the Brazilian context , according to the Ministry of Agriculture, Livestock and Supply of Brazil cotton cultivation in Brazil has grown especially in the Midwest . In particular , exports of cotton fiber increased twice in one season in 2003/2004... C. Santos, E.O. Weschter, M.A. Dota, C.E. Cugnasca

3. Precision Thinning Of Fruit Crops

L. Damerow, C. Seehuber and M. Blanke University of Bonn, Germany Correspondence: damerow@uni-bonn.de   Abstract for o r a l   Thinning is a pre-requisite in the majority of fruit crops worldwide in order to overcome or prevent alternate bearing (change of years with large and low yields) and to provide regular yields of high quality... M.M. Blanke, L. Damerow, C. Seehuber

4. Estimation Of Nitrogen And Chlorophyll Content In Wheat Crop Using Hand Held Sensors

A Field experiment was conducted to estimate crop nitrogen (N) status and chlorophyll content in wheat crop by using chlorophyll content meter(Apogee’s CCM-200) and N-Tester®  (Make YARA International). The experiment was conducted by sowing university recommended wheat variety viz. PBW 550 with 5 nitrogen levels i.e. 0, 30, 60, 90, 120 & 150 kg N/ha. It was found that at tillering stage when nitrogen rates were increased from 0 to 150 kg ha-1 , the... M.S. Makkar, A. Kaul, R. Kumar, A. Sharma, B.S. Sekhon, C.S. Pannu

5. Small UAS Integrated Sensing Tools for Abiotic Stress Monitoring in Irrigated Pinto Beans

Precision agriculture is a practical approach to maximize crop yield with optimal use of rapidly depleting natural resources. Availability of specific and high resolution crop data at critical growth stages is a key for real-time data driven decision support for precision agriculture management during the production season. The goal of this study was to evaluate the feasibility of using small unmanned aerial system (UAS) integrated remote sensing tools to monitor the abiotic stress of eight irrigated... L. Khot, J. Zhou, R. Boydston, P.N. Miklas, L. Porter

6. Liquid Flow Control Requirements for Crop Canopy Sensor-Based N Management in Corn: A Project SENSE Case Study

While on-farm adoption of crop canopy sensors for directing in-season nitrogen (N) application has been slow, research focused on these systems has been significant for decades. Much emphasis has been placed on developing and testing algorithms based on sensor output to predict N needs, but little information has been published regarding liquid flow control requirements on equipment used in conjunction with these sensing systems. Addition of a sensor-based system to a standard spray rate controller... J. Luck, J. Parrish, L. Thompson, B. Krienke, K. Glewen, R.B. Ferguson

7. Application of Geographic Information Systems in Socioeconomic Analysis: A Case of Integrated Soil Fertility Management in the Savannas of Nigeria

Population pressure increases, shortened fallow cycles, cropping intensification, inaccessibility and low output prices as well as concerns about agricultural sustainability and self-sufficiency have combined to contribute to increased demand for integrated soil fertility management of the agricultural resource base. Following this situation, organic fertilizer in the form of animal manure becomes one of the principal sources of nutrients for soil fertility maintenance and crop production. Hence,... O. Olayide, A. Alene, A. Ikpi, G. Nziguheba, T. Alabi

8. Estimating Cotton Water Requirements Using Sentinel-2

Crop coefficient (Kc)-based estimation of crop water consumption is one of the most commonly used methods for irrigation management.  Spectral modeling of Kc is possible due to the high correlations between Kc and the crop phenologic development and spectral reflectance.  In this study, cotton evapotranspiration was measured in the field using several methods, including eddy covariance, surface renewal, and heat pulse.  Kc was estimated as the ratio between reference evapotranspiration... O. Rozenstein, N. Haymann, G. Kaplan , J. Tanny

9. Monitoring Soybean Growth and Yield Due to Topographic Variation Using UAV-Based Remote Sensing

Remote 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 large... J. Zhou, K.A. Sudduth, A. Feng

10. Through the Grass Ceiling: Using Multiple Data Sources on Intra-Field Variability to Reset Expectations of Pasture Production and Farm Profitability

Intra-field variability has received much attention in arable and horticultural contexts. It has resulted in increased profitability as well as reduced environmental footprint. However, in a pastoral context, the value of understanding intra-field variability has not been widely appreciated. In this programme, we used available technologies to develop multiple data layers on multiple fields within a dairy farm. This farm was selected as it was already performing at a high level, with well-developed... W. King, R. Dynes, S. Laurenson, S. Zydenbos, R. Macauliffe, A. Taylor, M. Manning, A. Roberts, M. White

Showing 1 to 10 of 19 entries