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Reese, C.L
Rund, Q
Ruiz Diaz, D
Rodrigues Alves Franchi, M
Rains, G
Romani, M
Rivest, J
Reitsma, K.D
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Authors
Rund, Q
Williams, R
Reese, C.L
Clay, D.E
Beck, D.L
Clay, S.A
Long, D.S
Shahinian, M
Reitsma, K.D
Schumacher, T.E
Rund, Q
Murrell, S
Erbe, A
Williams, R
Williams, E
Cordero, E
Sacco, D
Moretti, B
Miniotti, E.F
Tenni, D
Beltarre, G
Romani, M
Grignani, C
Pomar, C
Andretta, I
Rivest, J
Hauschild, L
Pomar, J
Byers, C
Virk, S
Meena, R.K
Rains, G
Roa Acosta, G
Ruiz Diaz, D
Rodrigues Alves Franchi, M
Molina Cyrineu, I
Kagami Taira, F
Hunhoff, L
Gimenez, L.M
Topics
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change)
Remote Sensing Applications in Precision Agriculture
Precision Carbon Management
Big Data Mining & Statistical Issues in Precision Agriculture
In-Season Nitrogen Management
Precision Dairy and Livestock Management
Drone Spraying
Site-Specific Nutrient, Lime and Seed Management
On Farm Experimentation with Site-Specific Technologies
Type
Oral
Poster
Year
2010
2016
2018
2024
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Filter results9 paper(s) found.

1. Nugis: The Development Of A Nutrient Use Geographic Information System

NuGIS is a project of the International Plant Nutrition Institute (IPNI). The goal was to examine sources of nutrients (fertilizers and manure) and compare this to crop removal. The project used GIS and database analysis to create maps at the state and county level and then used GIS to migrate the budget analysis to the local watershed and regional watershed levels. This paper will cover the sources of data used, how the data was processed to generate county level numbers, and how GIS was used... Q. Rund, R. Williams

2. Nitrogen And Water Stress Impacts Hard Red Spring Wheat (Triticum Aestivum) Canopy Reflectance

  Remote sensing-based in-season N recommendations have been proposed as a technique to improve N fertilizer use efficiency. Remote sensing estimation of South Dakota hard red spring wheat N requirements needs assessment. Research objectives were: (1) determine the effect of an in-season N application on grain yield, yield loss to nitrogen stress (YLNS), and grain protein; and (2) assess if remote sensing collected at different growth stages may be used to predict yield... C.L. Reese, D.E. Clay, D.L. Beck, S.A. Clay, D.S. Long, M. Shahinian

3. Estimating Soil Productivity And Energy Efficiency Using Websoil Survey, Soil Productivity Index Calculator, And Biofuel Energy Systems Simulator

Soils have varying production capacities for a specific plant or sequence of plants under defined management strategies. The production capacity or “productivity” can be quantified as a mathematical function of a soils ability to sufficiently sustain plant growth... K.D. Reitsma, T.E. Schumacher

4. North American Soil Test Summary

With the assistance and cooperation of numerous private and public soil testing laboratories, the International Plant Nutrition Institute (IPNI) periodically summarizes soil test levels in North America (NA). Soil tests indicate the relative capacity of soil to provide nutrients to plants. Therefore, this summary can be viewed as an indicator of the nutrient supplying capacity or fertility of soils in NA. This is the eleventh summary completed by IPNI or its predecessor, the Potash &... Q. Rund, S. Murrell, A. Erbe, R. Williams, E. Williams

5. Deriving Fertiliser VRA Calibration Based on Ground Sensing Data from Specific Field Experiments

Nitrogen (N) fertilisation affects both rice yield and quality. In order to improve grain yield while limiting N losses, providing N fertilisers during the critical growth stages is essential. NDRE is considered a reliable crop N status indicator, suitable to drive topdressing N fertilisation in rice. A multi-year experiment on different rice varieties (Gladio, Centauro, and Carnaroli) was conducted between 2011 and 2017 in Castello d’Agogna (PV), northwest Italy, with the aim of i) establishing... E. Cordero, D. Sacco, B. Moretti, E.F. Miniotti, D. Tenni, G. Beltarre, M. Romani, C. Grignani

6. Precision Feeding Can Significantly Reduce Lysine Intake and Nitrogen Excretion Without Compromising the Performance of Growing Pigs

The impact of using a mathematical model estimating real-time daily lysine requirements in a sustainable precision feeding program for growing pigs was investigated in two performance trials. Three treatments were tested in the first trial (60 pigs of 41.2±0.5 kg): a three-phase feeding program (3P) obtained by blending fixed proportions of feeds A (high nutrient concentration) and B (low nutrient concentration); and two daily-phase feeding programs in which the blended proportions of feeds... C. Pomar, I. Andretta, J. Rivest, L. Hauschild, J. Pomar

7. Spray Deposition Characterization of Uniform and Variable-rate Applications with Spray Drones

The use of unmanned aerial application systems (also known as spray drones) has seen rapidly increasing interest in recent years due to their potential to allow for timely application of pesticides and being able to apply in areas inaccessible to ground application sprayers. Newer spray drone models’ have improved application systems such as rotary atomizers for creating spray droplets and capabilities such as variable-rate (VR) application for site-specific pesticide applications. An investigation... C. Byers, S. Virk, R.K. Meena, G. Rains

8. Enhancing Phosphorus Nutrient Management in Corn Through Tissue Analysis and Diagnostic Tools

Phosphorus (P) plays a pivotal role in crop growth, and optimizing its application is crucial for sustainable agriculture. This research focuses on advancing nutrient management by precisely evaluating tissue phosphorus concentrations in corn. The study delves into identifying critical P levels during various growth stages, assessing alternative diagnostic tools, and exploring correlations to refine phosphorus nutrition strategies. Across 26 locations in Kansas, field experiments employed a randomized... G. Roa Acosta, D. Ruiz Diaz

9. On-farm Experimentation Case Study in Brazil: Evaluation of Soybean Seeding Rate Using Resources Available at the Farm

In order to maximize grain yield in soybean (Glycine max [L.] Merr.) it is necessary that the plant population is correctly defined. Production environments differ spatially, and cultivar holders suggest plant populations across macroregions and in broad ranges. Refinements of planting seasons and populations are carried out through tests on many properties, often costly and sometimes unrepresentative of most fields. Tools for managing spatial variability are ways to conduct more... M. Rodrigues Alves Franchi, I. Molina Cyrineu, F. Kagami Taira, L. Hunhoff, L.M. Gimenez