Proceedings

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Orellana, M.C
Oliveira, R
Sanders, K
Panneton, B
Romani, M
Wu, G
Santos, A.B
Dhiman, V
Yalcin, H
Zhao, J.C
Bellenguez, R
Harkin, S.J
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Authors
Panneton, B
Simard, M
Leroux, G.D
Longchamps, L
Longchamps, L
Panneton, B
Westfall, D.G
Khosla, R
Deng, W
Wu, G
Longchamps, L
Panneton, B
Simard, M
Theriault, R
Roger, T
Longchamps, L
Panneton, B
Leroux, G.D
Simard, M
Theriault, R
McNeill, D
Bishop-Hurley, G.J
Irvine, L
Freeman, M
Bellenguez, R
Tekin, A.B
Yalcin, H
Chen , J
Chen, P.L
Zhao, J.C
Wang, S.Y
Li, J.C
Zhang, Q
Hu, T.H
Shi, G.L
Fageria, N.K
Santos, A.B
Cordero, E
Sacco, D
Moretti, B
Miniotti, E.F
Tenni, D
Beltarre, G
Romani, M
Grignani, C
Longchamps, L
Panneton, B
Tremblay, N
Ortega, R.A
Ortega, A.F
Orellana, M.C
Harkin, S.J
Barai, K
Ewanik, C
Dhiman, V
Zhang, Y
Hodeghatta, U.R
Felipe dos Santos, A
Silva, J.E
Costa, O.P
Inácio , F.D
Oliveira, R
Silva, W
Lacerda, L
Orlando Costa Barboza, T
Kerry, R
Sanders, K
Swenson, A
Henrie, A
Hansen, N
Hopkins, B
Ingram, B
Zhang, Y
Hodeghatta, U.R
Dhiman, V
Barai, K
Trang, T
Buckmaster, D
Krogmeier, J
Evans, J
Zhang, Y
Glavin, M
Byrne, D
Harkin, S.J
Topics
Precision Crop Protection
Guidance, Robotics, Automation, and GPS Systems
Spatial Variability in Crop, Soil and Natural Resources
Precision Weed Management
Precision Livestock Management
Proximal Sensing in Precision Agriculture
Profitability, Sustainability and Adoption
Remote Sensing for Nitrogen Management
In-Season Nitrogen Management
Precision Horticulture
Land Improvement and Conservation Practices
Geospatial Data
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Drone Spraying
Drainage Optimization and Variable Rate Irrigation
Data Analytics for Production Ag
Artificial Intelligence (AI) in Agriculture
Type
Poster
Oral
Year
2012
2010
2014
2016
2008
2018
2022
2024
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Authors

Filter results18 paper(s) found.

1. Spectral Discrimination Of Early Dchinochloa Crasgalli And Echinochloa Crusgalli In Corn And Soybean By Using Support Vector Machines

    The key to realize precise chemical application is weed identification. This paper introduces a kind of multi-classification mode based on Support Vector Machines (SVM) and one-against-one-algorithm for weed seedlings (Dchinochloa crasgalli, and Echinochloa crusgalli) in corn and soybean fields. A handheld FieldSpec® 3 Spectroradiometer manufactured by ASD Inc., in USA was used to measure the spectroscopic data of the canopies of the seedlings of corn, soybean,... W. Deng, G. Wu

2. Sensing The Inter-row For Real-time Weed Spot Spraying In Conventionally Tilled Corn Fields

The spatial distribution of weeds is aggregated most of the time in crop fields. Site-specific management of weeds could result in economical and environmental benefits due to herbicide... L. Longchamps, B. Panneton, M. Simard, R. Theriault, T. Roger

3. Partial Weed Scouting For Exhaustive Real-time Spot Spraying Of Herbicides In Corn

Real-time spot spraying of weeds implies the use of plant detectors ahead of a sprayer. The range of weed spatial autocorrelation perpendicularly to crop rows is often greater than the space between the corn rows. To assess the possibility of using less than one plant detector scouting each inter-row, a one hectare field was entirely sampled with ground pictures at the appropriate timing for weed spraying. Different ways of disposing the detectors ahead of the sprayer were virtually tested. Scouting... L. Longchamps, B. Panneton, G.D. Leroux, M. Simard, R. Theriault

4. A Preliminary Evaluation Of Proximity Loggers To Detect Oestrus Behaviour In Grazing Dairy Cows

... D. Mcneill, G.J. Bishop-hurley, L. Irvine, M. Freeman, R. Bellenguez

5. Development of a Quick Diagnosis Method to Target Fields with Better Potential for Site-Specific Weed Management

Site-specific weed management appears as an innovative way of saving herbicides in crop while maintaining yield. This can potentially lead economic and ecological benefits. However, it was reported in the literature that savings range from 1 % to 94 % from one field to the other. This implies that certain fields... B. Panneton, M. Simard, G.D. Leroux, L. Longchamps

6. Testing The Author Sequence - Finalize

This is just a test to verify the bug with the authors sequence. ... L. Longchamps, B. Panneton, D.G. Westfall, R. Khosla

7. Development Of Online Soil Profile Sensor For Variable Depth Tillage

Introduction First introduced in the early 1990s, precision agriculture technologies, or site-specific management, were considered by many to be perhaps the most significant development in production agriculture focused on improving farm profitability. The initial focus was on fertility, and treating the variability that we all knew existed from our experiences with soil sampling. However, to a large extent this application still... A.B. Tekin, H. Yalcin

8. Yield, Residual Nitrogen and Economic Benefit of Precision Seeding and Laser Land Leveling for Winter Wheat

Rapid socio-economic changes in China, such as land conversion and urbanization etc., are creating new scopes for application of precision agriculture (PA). It remains unclear the application effective and economic benefits of precision agriculture technologies in China. In this study, our specific goal was to analyze the impact of precision seeding and laser land leveling on winter wheat yield,... J. Chen , P.L. Chen, J.C. Zhao, S.Y. Wang, J.C. Li, Q. Zhang, T.H. Hu, G.L. Shi

9. Nitrogen Management in Lowland Rice

Rice is staple diet for more than fifty percent of the world population and nitrogen (N) deficiency is one of the major yields limiting constraints in most of the rice producing soils around the world. The lowland rice N recovery efficiency is <50% of applied fertilizers in most agro-ecological regions. The low N efficiency is associated with losses caused by leaching, volatilization, surface runoff, and denitrification. Hence, improving N use efficiency is crucial for higher yields, low cost... N.K. Fageria, A.B. Santos

10. 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

11. Observational Studies in Agriculture: Paradigm Shift Required

There is a knowledge gap in agriculture. For instance, there is no way to tell with precision what is the outcome of cutting N fertilizer by a quarter on important outcomes such as yield, net return, greenhouse gas emissions or groundwater pollution. Traditionally, the way to generate knowledge in agriculture has been to conduct research with the experimental method where experiments are conducted in a controlled environment with trials replicated in space and... L. Longchamps, B. Panneton, N. Tremblay

12. Analysis of the Mapping Results Using SoilOptix TM Technology in Chile After Two Seasons

Soil mapping is a key element to successfully implement Integrated Nutrient Management (INM) in high value crops.  SoilOptixTM is a mapping service based on the use of gamma radiation technology that arrived in Chile in 2019. Since then, around 2000 ha have been mapped, mainly in fruit orchards and vineyards. The technology has demonstrated its value in determining the most limiting factors in new and old orchards, and the possibility of correcting them in a site-specific... R.A. Ortega, A.F. Ortega, M.C. Orellana

13. Automated Geometrical Field Boundary Delineation Algorithm for Adjacent Job Sites

Establishing farmland geometric boundaries is a critical component of any assistive technology, designed towards the automation of mechanized farming systems. Observing farmland boundaries enables farmers and farm machinery contractors to determine; seed purchase orders, fertiliser application rate, and crop yields. Farmers must supply acreage measurements to regulatory bodies, who will use the geometric data to develop environmental policies and allocate farm subsidies appropriately. Agricultural... S.J. Harkin

14. Airborne Spectral Detection of Leaf Chlorophyll Concentration in Wild Blueberries

Leaf chlorophyll concentration (LCC) detection is crucial for monitoring crop physiological status, assessing the overall health of crops, and estimating their photosynthetic potential. Fast, non-destructive, and spatially extensive monitoring of LCC in crops is critical for accurately diagnosing and assessing crop health in large commercial fields. Advancements in hyperspectral remote sensing offer non-destructive and spatially extensive alternatives for monitoring plant parameters such as LCC.... K. Barai, C. Ewanik, V. Dhiman, Y. Zhang, U.R. Hodeghatta

15. Comparative Analysis of Spray Nozzles on Drones: Volumetric Distribution at Different Heights

Agricultural drones are emerging as a revolutionary tool in modern agriculture, aiming to enhance precision and efficiency in crop management. One of their main advantages is the ability to operate in adverse soil and canopy height conditions, making them a valuable instrument for the application of agrochemicals. In this context, the optimization of spraying systems plays a critical role, with the goal of ensuring the effective application of agrochemicals, aiming to maximize productivity and... A. Felipe dos santos, J.E. Silva, O.P. Costa, F.D. Inácio , R. Oliveira, W. Silva, L. Lacerda, T. Orlando costa barboza

16. Spatio-temporal Analysis of Soil Moisture and Turfgrass Health to Investigate the Temporal Stability of Variable Rate Irrigation Zones

The western USA has been experiencing severe drought conditions for at least the last 20 years. The population in many areas of the west, like Utah, has also increased greatly in this time putting greater strain on the limited freshwater supply. While agriculture is generally the sector consuming the largest proportion of freshwater, conversion of agricultural land to urban areas with lawns, parks and playing fields may result in some reduction of water use, but the EPA have estimated that as... R. Kerry, K. Sanders, A. Swenson, A. Henrie, N. Hansen, B. Hopkins, B. Ingram

17. Predicting Water Potentials of Wild Blueberries During Drought Treatment Using Hyperspectral Sensor and Machine Learning

Detecting water stress on crops early and accurately is crucial to minimize its impact. This study aims to measure water stress in wild blueberry crops non-destructively by analyzing proximal hyperspectral data. The data collection took place in the summer growing season of 2022. A drought experiment was conducted on wild blueberries in the randomized block design in the greenhouse, incorporating various genotypes and irrigation treatments. Hyperspectral data ( spectral range: 400-1000 nm) using... Y. Zhang, U.R. Hodeghatta, V. Dhiman, K. Barai, T. Trang

18. In-Field and Loading Crop: A Machine Learning Approach to Classify Machine Harvesting Operating Mode

This paper addresses the complex issue of classifying mode of operation (active, idle, stationary unloading, on-the-go unloading, turning) and coordinating agricultural machinery. Agricultural machinery operators must operate within a limited time window to optimize operational efficiency and reduce costs. Existing algorithms for classifying machinery operating modes often rely on heuristic methods. Examples include rules conditioned on machine speed, bearing angle and operational time... D. Buckmaster, J. Krogmeier, J. Evans, Y. Zhang, M. Glavin, D. Byrne, S.J. Harkin