Proceedings :: International Society of Precision Agriculture

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Chen, X

Luck, J

Wang, Y

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Authors

Thompson, L

Glewen, K

Mueller, N

Luck, J

Miao, Y

liu, X

Tian, Y

Zhu, Y

Cao, W

Cao, Q

Chen, X

Li, Y

Wang, Y

Lu, Y

Morris, D

Benjamin, M

Lavagnino, M

McIntyre, J

Topics

Education and Outreach in Precision Agriculture

In-Season Nitrogen Management

Farm Animals Health and Welfare Monitoring

Type

Oral

Poster

Year

2018

2024

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Filter results3 paper(s) found.
1. From Data to Decisions - Ag Technologies Provide New Opportunities and Challenges with On-Farm Research U.S. farmers are challenged to increase crop production while achieving greater resource use efficiency. The Nebraska On-Farm Research Network (NOFRN), enables farmers to answer critical production, profitability, and sustainability questions with their own fields and equipment. The NOFRN is sponsored by the University of Nebraska – Lincoln Extension and derives from two separate on-farm research efforts, the earliest originating in 1990. Over the course of the last 29 years,... L. Thompson, K. Glewen, N. Mueller, J. Luck Download paper
2. Developing a Wheat Precision Nitrogen Management Strategy by Combining Satellite Remote Sensing Data and WheatGrow Model Precision nitrogen (N) management (PNM) is becoming increasingly popular due to its ability to synchronize crop N demand with soil N supply spatiotemporally. The previous evidence has demonstrated that variable rate fertilization contributes to achieving high yields and high efficiencies. However, PNM at the regional level remains unclear and challenging. This study aims to develop a novel management zone (MZ)-based PNM strategy (MZ-PNM) to optimize the basal and topdressing N rates at the regional... Y. Miao, X. Liu, Y. Tian, Y. Zhu, W. Cao, Q. Cao, X. Chen, Y. Li Download paper
3. 3D Computer Vision with a Spatial-temporal Neural Network for Lameness Detection of Sows The lameness of sows is one of the biggest concerns for swine producers, which can lead to considerable economic losses due to reduced productivity and welfare. There is a real need for early detection of lameness in sows to enable timely intervention and minimize loss. Currently, lame detection relies on visual observation and locomotion scoring of sows, which is subjective, labor-intensive, and difficult to conduct for large groups of animals within a short time. This study presents 3D computer... Y. Wang, Y. Lu, D. Morris, M. Benjamin, M. Lavagnino, J. Mcintyre

Filter results3 paper(s) found.

1. From Data to Decisions - Ag Technologies Provide New Opportunities and Challenges with On-Farm Research

U.S. farmers are challenged to increase crop production while achieving greater resource use efficiency. The Nebraska On-Farm Research Network (NOFRN), enables farmers to answer critical production, profitability, and sustainability questions with their own fields and equipment. The NOFRN is sponsored by the University of Nebraska – Lincoln Extension and derives from two separate on-farm research efforts, the earliest originating in 1990. Over the course of the last 29 years,... L. Thompson, K. Glewen, N. Mueller, J. Luck

Download paper

2. Developing a Wheat Precision Nitrogen Management Strategy by Combining Satellite Remote Sensing Data and WheatGrow Model

Precision nitrogen (N) management (PNM) is becoming increasingly popular due to its ability to synchronize crop N demand with soil N supply spatiotemporally. The previous evidence has demonstrated that variable rate fertilization contributes to achieving high yields and high efficiencies. However, PNM at the regional level remains unclear and challenging. This study aims to develop a novel management zone (MZ)-based PNM strategy (MZ-PNM) to optimize the basal and topdressing N rates at the regional... Y. Miao, X. Liu, Y. Tian, Y. Zhu, W. Cao, Q. Cao, X. Chen, Y. Li

Download paper

3. 3D Computer Vision with a Spatial-temporal Neural Network for Lameness Detection of Sows

The lameness of sows is one of the biggest concerns for swine producers, which can lead to considerable economic losses due to reduced productivity and welfare. There is a real need for early detection of lameness in sows to enable timely intervention and minimize loss. Currently, lame detection relies on visual observation and locomotion scoring of sows, which is subjective, labor-intensive, and difficult to conduct for large groups of animals within a short time. This study presents 3D computer... Y. Wang, Y. Lu, D. Morris, M. Benjamin, M. Lavagnino, J. Mcintyre