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Srinivasa Rao, C
Sauvageau, G
Sell, S.G
Sleichter, R
Sunohara, M
Salunga, N.G
Sapkota, T.B
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Authors
Srinivasa Rao, C
Rao, K
Magen, H
Venkateswarlu, B
Subba Rao, A
Sapkota, T.B
Maja, J.M
Blocker, A.K
Stuckey, E.G
Sell, S.G
Tuttle, G
Mueller, J
Andrae, J
Kross, A
Kaur, G
Callegari, D
Lapen, D
Sunohara, M
McNairn, H
Rudy, H
van Vliet, L
Kross, A
Kaur, G
Znoj, E
Callegari, D
Sunohara, M
McNairn, H
Lapen, D
Rudy, H
van Vliet, L
Caron, J
Anderson, L
Sauvageau, G
Gendron, L
Scudiero, E
Nugent, C.I
Ng, C
Jones, N
Azzam, T
Salunga, N.G
Lemus, S
Sleichter, R
Topics
Precision Nutrient Management
Precision Nutrient Management
Farm Animals Health and Welfare Monitoring
Decision Support Systems
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Precision Horticulture
Education of Precision Agriculture Topics and Practices
Robotics and Automation with Row and Horticultural Crops
Type
Poster
Oral
Year
2012
2010
2018
2024
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Filter results8 paper(s) found.

1. Categorization of Districts Based on Nonexchangeable Potassium: Generation GIS Maps and Implications in Efficient K Fertility Management in Indian Agriculture

Recommendations of K fertilizer are made based on available (exchangeable + water soluble) K status only  in India and other despite of  substantial contribution of nonexchangeable fraction of soil K to crop K uptake. Present paper examines the information generated in the last 30 years on the status of nonexchangeable K in Indian soils, categorization of Indian soils based on exchangeable and nonexchangeable K fractions and making K recommendations. Data for both K fractions of different... C. Srinivasa rao, K. Rao, H. Magen, B. Venkateswarlu, A. Subba rao

2. Soil Quality Improvement Through Proper Combination Of Tillage, Nitrogen Fertilization And Cover Cropping Systems

No-tillage, N fertilization and cover cropping affect physical, chemical and biological qualities of soil. We investigated the effect of 15-yr of tillage systems, N fertilization and cover crops on soil organic matter, aggregation, bulk density and on microbial community in the sandy loam soil of central Italy. The soil in no-tillage (NT) system had 50% more organic matter and 3 folds higher aggregate stability than the soil in conventional tillage (CT) system. The NT system significantly increased... T.B. Sapkota

3. Development of a Small Tracking Device for Cattle Using IoT Technology

The US is the largest producer of beef in the world. Last year alone, it produces nearly 19% of the world’s beef.  This translate to about almost $90 billion in economic impact in the country. Aside from being a producer, the US also consumed more than 26 billion pounds of beef which have a retail value of the entire beef industry to more than $74B. For this level of production and consumption, each rancher in the US must produce a herd size of at least 100 or more to sustain the current... J.M. Maja, A.K. Blocker, E.G. Stuckey, S.G. Sell, G. Tuttle, J. Mueller, J. Andrae

4. Spatial Decision Support System: Controlled Tile Drainage – Calculate Your Benefits

Climate projection studies suggest that extreme heat waves and floods will become more frequent, affecting future crop yields by 20%-30%, globally. Managing vulnerability and risk begins at the farm level where best management practices can reduce the impacts associated with extreme weather events. A practice that can assist in mitigating the impact of some extreme events is controlled tile drainage (CTD). With CTD, producers use water flow control structures to manage the drainage of water from... A. Kross, G. Kaur, D. Callegari, D. Lapen, M. Sunohara, H. Mcnairn, H. Rudy, L. Van vliet

5. Evaluation of an Artificial Neural Network Approach for Prediction of Corn and Soybean Yield

The ability to predict crop yield during the growing season is important for crop income, insurance projections and for evaluating food security. Yet, modeling crop yield is challenging because of the complexity of the relationships between crop growth and the interrelated predictor variables. Artificial neural networks (ANNs) are useful for such complex systems as they can capture non-linear relationships of data without explicitly knowing the underlying processes. In this study, an ANN-based... A. Kross, G. Kaur, E. Znoj, D. Callegari, M. Sunohara, H. Mcnairn, D. Lapen, H. Rudy, L. Van vliet

6. Real Time Precision Irrigation with Variable Setpoint for Strawberry to Generate Water Savings

Water is a precious resource that is becoming increasingly scarce as the population grows and water resources are depleted in some locations or under increased control elsewhere, due to local availability or groundwater contamination issues. It obviously affects strawberry (Fragaria x ananassa Duch.) production in populated areas and water cuts are being imposed to many strawberry growers to save water, with limited information on the impact on crop yield. Precision irrigation technologies are... J. Caron, L. Anderson, G. Sauvageau, L. Gendron

7. Cultivating Future Leaders in Sustainable Agriculture: Insights from the Digital Agriculture Fellowship Program at the University of California, Riverside

Funded by USDA's National Institute of Food and Agriculture’s Sustainable Agricultural Systems Program and housed at the University of California, Riverside (UCR), the Digital Agriculture Fellowship (DAF) aims at equipping undergraduate students with the knowledge and experience necessary to meet the agricultural challenges posed by climate change and sustainability concerns. The program was established in 2020 and will be funded through 2026. Activities span over fifteen months for... E. Scudiero, C.I. Nugent, C. Ng, N. Jones, T. Azzam, N.G. Salunga, S. Lemus

8. Utilizing ArUco Markers to Define Implement Boundaries

John Deere and Blue River Technology’s autonomous tillage system combines multidisciplinary efforts and cutting-edge technology to achieve Level 5—Unsupervised Autonomy. To create this engineering marvel, countless parameters need defined to ensure safe operation of the system; some of these parameters are static, while other of these parameters are dynamic. One particular set of parameters define the tillage implement’s boundaries for the software stack to utilize, and today... R. Sleichter