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Xia, T

Xu, Z

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Authors

Wang, X

Miao, Y

Xia, T

Dong, R

Mi, G

Mulla, D.J

Zhou, J

Xu, Z

Topics

In-Season Nitrogen Management

Farm Animals Health and Welfare Monitoring

Type

Oral

Year

2018

2022

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Filter results2 paper(s) found.
1. Improving Active Canopy Sensor-Based In-Season N Recommendation Using Plant Height Information for Rain-Fed Maize in Northeast China The inefficient utilization of nitrogen (N) fertilizer due to leaching, volatilization and denitrification has resulted in environmental pollution in rain-fed maize production in Northeast China. Active canopy sensor-based in-season N application has been proven effective to meet maize N requirement in space and time. The objective of this research was to evaluate the feasibility of using active canopy sensor for guiding in in-season N fertilizer recommendation for rain-fed maize in Northeast... X. Wang, Y. Miao, T. Xia, R. Dong, G. Mi, D.J. Mulla Download paper
2. Detect Estrus in Sows Using a Lidar Sensor and Machine Learning Accurate estrus detection of sows is labor intensive and is crucial to achieve high farrowing rate. This study aims to develop a method to detect accurate estrus time by monitoring the change in vulvar swollenness around estrus using a light detection and ranging (LiDAR) camera. The measurement accuracy of the LiDAR camera was evaluated in laboratory conditions before it was used in monitoring sows in a swine research facility. In this study, twelve multiparous individually housed sows were continuously... J. Zhou, Z. Xu

Filter results2 paper(s) found.

1. Improving Active Canopy Sensor-Based In-Season N Recommendation Using Plant Height Information for Rain-Fed Maize in Northeast China

The inefficient utilization of nitrogen (N) fertilizer due to leaching, volatilization and denitrification has resulted in environmental pollution in rain-fed maize production in Northeast China. Active canopy sensor-based in-season N application has been proven effective to meet maize N requirement in space and time. The objective of this research was to evaluate the feasibility of using active canopy sensor for guiding in in-season N fertilizer recommendation for rain-fed maize in Northeast... X. Wang, Y. Miao, T. Xia, R. Dong, G. Mi, D.J. Mulla

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2. Detect Estrus in Sows Using a Lidar Sensor and Machine Learning

Accurate estrus detection of sows is labor intensive and is crucial to achieve high farrowing rate. This study aims to develop a method to detect accurate estrus time by monitoring the change in vulvar swollenness around estrus using a light detection and ranging (LiDAR) camera. The measurement accuracy of the LiDAR camera was evaluated in laboratory conditions before it was used in monitoring sows in a swine research facility. In this study, twelve multiparous individually housed sows were continuously... J. Zhou, Z. Xu