Proceedings

Find matching any: Reset
Yost, M.A
Yajia, L
Yore, A
Add filter to result:
Authors
Xiongkui, H
Longlong, L
Jianli, S
Aijun, Z
Yajia, L
Kitchen, N.R
Yost, M.A
Ransom, C.J
Bean, G
Camberato, J
Carter, P
Ferguson, R
Fernandez, F
Franzen, D
Laboski, C
Nafziger, E
Sawyer, J
Lanza, P
Yore, A
Longchamps, L
Topics
Engineering Technologies and Advances
In-Season Nitrogen Management
Geospatial Data
Type
Poster
Oral
Year
2016
2018
2024
Home » Authors » Results

Authors

Filter results3 paper(s) found.

1. Design of VAV System of Air Assisted Sprayer in Orchard and Experimental Study in China

One type of new automatic target detecting based on size of canopy with variable chemical dosage and air-flow of fan orchard sprayer was designed and developed to meet the demand of chemical pest control in orchards. Canopy parameter data scanned by infrared sensors and LIDAR (Light Detection and Ranging) were used to detect the target and to design spraying algorithm and PWM (Pulse Width Modulation) control system. Four integrated five-finger atomizers were equipped on each side of sprayer, independent... H. Xiongkui, L. Longlong, S. Jianli, Z. Aijun, L. Yajia

2. Utilizing Weather, Soil, and Plant Condition for Predicting Corn Yield and Nitrogen Fertilizer Response

Improving corn (Zea mays L.) nitrogen (N) fertilizer rate recommendation tools should increase farmer’s profits and help mitigate N pollution. Weather and soil properties have repeatedly been shown to influence crop N need. The objective of this research was to improve publicly-available N recommendation tools by adjusting them with additional soil and weather information. Four N recommendation tools were evaluated across 49 N response trials conducted in eight U.S. states over three growing... N.R. Kitchen, M.A. Yost, C.J. Ransom, G. Bean, J. Camberato, P. Carter, R. Ferguson, F. Fernandez, D. Franzen, C. Laboski, E. Nafziger, J. Sawyer

3. A Data Retrieval System to Support Observational Research of On-Farm Experimentation

Observational research is a powerful methodology, capable of rapidly identifying trends and patterns present in complex systems. New work seeks to apply these techniques to agronomic production systems. While data generated from on-farm experimentation are often considered anecdotal, these data hold significant importance for farmers because they originate from their distinctive agricultural systems. Combining the large volumes of farmer-collected data with remote sensing, environmental, and biophysical... P. Lanza, A. Yore, L. Longchamps