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Yogananda, S
Vona, V
Vitantonio, L
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Authors
T, S
giriyappa, M
Hanumanthappa, D
Dr., N
K, S
Yogananda, S
Kiran, A
Kulmany, I.M
Benke, S
Bede, L
Pecze, R
Vona, V
Puntel, L.A
Pellegrini, P
Joalland , S
Rattalino, J
Vitantonio, L
Topics
Spatial Variability in Crop, Soil and Natural Resources
Land Improvement and Conservation Practices
Decision Support Systems
Type
Oral
Year
2016
2022
2024
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Filter results3 paper(s) found.

1. Spatial Variability of Soil Nutrients and Site Specific Nutrient Management in Maize

A field study was conducted during kharif 2014 and rabi 2014-15 at Southern Transition Zone of Karnataka under the jurisdiction of University of Agricultural Sciences, GKVK, Bangalore, India to know the spatial variability for available nutrient content in cultivator’s field and effect of site specific nutrient management in maize. The farmer’s fields have been delineated with each grid size of 50 m x 50 m using geospatial technology. Soil samples from 0-15 cm were... S. T, M. Giriyappa, D. Hanumanthappa, N. Dr., S. K, S. Yogananda, A. Kiran

2. The Effect of Slope Gradient on the Modelling of Soil Carbon Dioxide Emissions in Different Tillage Systems at a Farm Using Precision Tillage Technology in Hungary

Understanding the role of natural drivers in greenhouse gas (GHG) emitted by agricultural soils is crucial because it contributes to selecting and adapting acceptable eco-friendly farming practices. Hence, Syngenta Ltd. collaborating with researchers, aimed to investigate the effect of two tillage treatments, conventional-tillage (CT) and minimum-tillage (MT) on soil carbon dioxide (CO2) emissions. The research field is in Hungary. Soil columns were derived from different tillage systems... I.M. Kulmany, S. Benke, L. Bede, R. Pecze, V. Vona

3. Integrated Data-driven Decision Support Systems

Site-specific and data-driven decision support systems in agriculture are evolving fast with the rapid advancements in cutting-edge technologies such as Agricultural Artificial Intelligence (AgAI) and big data integration. Data driven decision support systems have the potential to revolutionize various aspects of farming, from crop monitoring and precision management decisions to the way growers interact with complex technologies. The AgAI decision support-based systems excel at analyzing... L.A. Puntel, P. Pellegrini, S. Joalland , J. Rattalino, L. Vitantonio