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Lundström, C
Lattanzi, P
Lobo Júnior, A
Love, D.J
Lessl, J
Landivar, J
Leduc , M
Lacroix, R
Lee, J
Li, Y
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Authors
Lundström, C
Lindblom, J
Dallago, G.M
Guimarães, M
Godinho, R
Carvalho, R
Lobo Júnior, A
Dallago, G.M
Guimarães, M
Godinho, R
Carvalho, R
Lobo Júnior, A
Lee, J
Fulton, J
Port, K
Colley III, R
Li, Y
Zhang, Y
Liu, X
Liu, C
Shinde, S
Adamchuk, V
Lacroix, R
Tremblay, N
Bouroubi, Y
Saifuzzaman, M
Adamchuk, V
Leduc , M
Canavari, M
Lattanzi, P
Vitali, G
Emmi, L
Tucker, M.W
Virk, S
Harris, G
Lessl, J
Levi, M
Jha, S
Krogmeier, J
Buckmaster, D
Love, D.J
Grant, R.H
Crawford, M
Brinton, C
Wang, C
Cappelleri, D
Balmos, A
Bhandari, M
Landivar, J
Ghansah, B
Zhao, L
Landivar, J
Pal, P
Topics
Decision Support Systems in Precision Agriculture
Farm Animals Health and Welfare Monitoring
Decision Support Systems
Robotics, Guidance and Automation
Decision Support Systems
Factors Driving Adoption
Site-Specific Nutrient, Lime and Seed Management
Big Data, Data Mining and Deep Learning
Artificial Intelligence (AI) in Agriculture
Type
Oral
Poster
Year
2016
2018
2022
2024
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Filter results11 paper(s) found.

1. Considering Farmers' Situated Expertise in AgriDSS Development to Fostering Sustainable Farming Practices in Precision Agriculture

Agriculture is facing immense challenges and sustainable intensification has been presented as a way forward where precision agriculture (PA) plays an important role. More sustainable agriculture needs farmers who embrace situated expertise and can handle changing farming systems. Many agricultural decision support systems (AgriDSS) have been developed to support farm management, but the traditional approach to AgriDSS development is mostly based on knowledge transfer. This has resulted in technology... C. Lundström, J. Lindblom

2. The Animal Welfare of Dairy Cows Housed in Free-Stall Barn According to the Welfare Quality® Protocol: Good Feeding and Good Housing Principles

The objective of the present study was to evaluate the animal welfare of dairy cows according to good feeding and good housing principles of the Welfare Quality® protocol. The protocol was applied to animals kept confined in a free-stall barn during their lactation. The farm was located in São João Batista do Glória, Minas Gerais state - Brazil. One hundred and one animals were evaluated (47 primiparous and 54 multiparous). The welfare measures were collected mostly through... G.M. Dallago, M. Guimarães, R. Godinho, R. Carvalho, A. Lobo júnior

3. The Correlation Between Criteria from Welfare Quality® Protocol Applied to Dairy Cows Housed in Free-Stall Barn

The objective of this study was to evaluate correlations between animal welfare criteria from the Welfare Quality® protocol applied to dairy cows. The protocol was applied on 47 primiparous and 54 multiparous dairy cows housed in a free-stall barn located in São João Batista do Glória, Minas Gerais - Brazil. Twelve welfare criteria were obtained from mostly animal-based welfare measures as proposed by the protocol. Pearson correlation coefficients (r) were calculated between... G.M. Dallago, M. Guimarães, R. Godinho, R. Carvalho, A. Lobo júnior

4. Overview and Value of Digital Technologies for North American Soybean Producers

In the current state of digital agriculture, many digital technologies and services are offered to assist North American soybean producers.  Opportunities for capturing and analyzing information related to soybean production methods are made available through the adoption of these technologies.  However, often it is difficult for producers to know which digital tools and services are available to them or understand the value they can provide.  The objective of this... J. Lee, J. Fulton, K. Port, R. Colley iii

5. High Accuracy Path Tracking for Rice Drill Seeder in Uneven Paddy Fields

High accuracy track tracing is a challenging task in paddy fields due to uneven grounds as well as wet soil conditions, thus restricting the development of autonomous rice drill seeder in China. For the purpose of overcoming the obstacles in application of autonomous rice drill seeder in paddy fields, a path tracking algorithm with high accuracy used for steering control during straight traveling in uneven mud paddy fields is introduced in this paper. Combining lateral deviation and heading angle... Y. Li, Y. Zhang, X. Liu, C. Liu

6. Development of an Online Decision-Support Infrastructure for Optimized Fertilizer Management

Determination of an optimum fertilizer application rate involves various influential factors, such as past management, soil characteristics, weather, commodity prices, cost of input materials and risk preference. Spatial and temporal variations in these factors constitute sources of uncertainties in selecting the most profitableapplication rate. Therefore, a decision support system (DSS) that could help to minimize production risks in the context of uncertain crop performance is needed. This... S. Shinde, V. Adamchuk, R. Lacroix, N. Tremblay, Y. Bouroubi

7. Stem Characteristics and Local Environmental Variables for Assessment of Alfalfa Winter Survival

Alfalfa (Medicago sativa L.) is considered the queen of forage due to its high yield, nutritional qualities, and capacity to sequester carbon. However, there are issues with its relatively low persistency and winter survival as compared to grass. Winter survival in alfalfa is affected by diverse factors, including the environment (e.g., snow cover, hardiness period, etc.) and management (e.g., cutting timing, manure application, etc.). Alfalfa's poor winter survival reduces the number of living... M. Saifuzzaman, V. Adamchuk, M. Leduc

8. Robot Safety Issues in Field Crops - EU Regulatory Issues and Technical Aspects

The use of robots in Precision Agriculture is becoming of great interest, but they introduce a new kind of risk in the field due to their self-acting and self-driving capability. Safety issues appear with respect to people working in the same field in human-robot collaboration (HRC) framework or to the accidental presence of humans or animals. A robot out of control may also invade other areas causing unpredictable harm and damage. Currently, the safety of highly automated agricultural... M. Canavari, P. Lattanzi, G. Vitali, L. Emmi

9. Effectiveness of Different Precision Soil Sampling Strategies for Site-Specific Nutrient Management in Row-Crops

Soil sampling is an important component of site-specific nutrient management in precision agriculture. While precision soil sampling strategies such as grid or zone have been around for a while, the adoption and utilization of these strategies varies considerably among the growers, especially in the southeastern United States. The selection of an appropriate grid size or management zone further differ among the users depending on several factors. In order to better understand how some of the commonly... M.W. Tucker, S. Virk, G. Harris, J. Lessl, M. Levi

10. Design of an Autonomous Ag Platform Capable of Field Scale Data Collection in Support of Artificial Intelligence

The Pivot+ Array is intended to serve as an innovative, multi-user research platform dedicated to the autonomous monitoring, analysis, and manipulation of crops and inputs at the plant scale, covering extensive areas. It will effectively address many constraints that have historically limited large-scale agricultural sensor and robotic research. This achievement will be made possible by augmenting the well-established center pivot technology, known for its autonomy, with robust power infrastructure,... S. Jha, J. Krogmeier, D. Buckmaster, D.J. Love, R.H. Grant, M. Crawford, C. Brinton, C. Wang, D. Cappelleri, A. Balmos

11. Cotton Yield Estimation Using High-resolution Satellite Imagery Obtained from Planet SkySat

Satellite images have been used to monitor and estimate crop yield. Over the years, significant improvements on spatial resolution have been made where ortho images can be generated at 30-centimeter resolution. In this study, we wanted to explore the potential use of Planet SKYSAT satellite system for cotton yield predictions. This system provided imagery data at 50 centimeters resolution, and we collected data 14 times during the season. The data were collected from two different cotton... M. Bhandari