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Dempsey, D
Li, Y
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Authors
Krol, C
Dempsey, D
Lu, J
Chen, Z
Miao, Y
Li, Y
Zhang, Y
Zhao, X
Jia, M
Miao, Y
liu, X
Tian, Y
Zhu, Y
Cao, W
Cao, Q
Chen, X
Li, Y
Topics
Precision A to Z for Practitioners
In-Season Nitrogen Management
In-Season Nitrogen Management
Type
Poster
Oral
Year
2012
2022
2024
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Filter results3 paper(s) found.

1. AMMO Ag: Agricultural Marketing & Merchandising Optimizer

EHedger provides an integrated risk management solution for farm operations utilizing our proprietary AMMO platform combined with proven hedging strategies, first-hand market insight, effective trade execution and farming expertise. AMMO software enables real-time analysis of crop/livestock production. Farmers can set profit margins, evaluate variable profit scenarios, understand production costs and risks, and create sustainable marketing programs to maximize their... C. Krol, D. Dempsey

2. In-season Diagnosis of Winter Wheat Nitrogen Status Based on Rapidscan Sensor Using Machine Learning Coupled with Weather Data

Nitrogen nutrient index (NNI) is widely used as a good indicator to evaluate the N status of crops in precision farming. However, interannual variation in weather may affect vegetation indices from sensors used to estimate NNI and reduce the accuracy of N diagnostic models. Machine learning has been applied to precision N management with unique advantages in various variables analysis and processing. The objective of this study is to improve the N status diagnostic model for winter wheat by combining... J. Lu, Z. Chen, Y. Miao, Y. Li, Y. Zhang, X. Zhao, M. Jia

3. 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