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Liu, Z
Hedley, C
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Authors
Hedley, C
Yule, I
Sharp, J
Hedley, C
Liu, Z
liu, X
Tian, Y
Zhu, Y
Cao, W
Cao, Q
Topics
Engineering Technologies and Advances
Drainage Optimization and Variable Rate Irrigation
Big Data, Data Mining and Deep Learning
Type
Poster
Oral
Year
2012
2018
2024
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Filter results3 paper(s) found.

1. Farmer Uptake of Variable Rate Irrigation Technologies in New Zealand

Cost effective technological advances in recent years have allowed the uptake of variable rate irrigation (VRI) systems in New Zealand. Typically an existing sprinkler irrigator is modified for variable rate irrigation, irrigation management zones are defined using EM (electromagnetic)... C. Hedley, I. Yule

2. Application of a Systems Model to a Spatially Complex Irrigated Agricultural System: A Case Study

Although New Zealand is water-rich, many of the intensively farmed lowland areas suffer frequent summer droughts. Irrigation schemes have been developed to move water from rivers and aquifers to support agricultural production. There is therefore a need to develop tools and recommendations that consider both water dynamics and outcomes in these irrigated cropping systems. A spatial framework for an existing systems model (APSIM Next Generation) was developed that could capture the variability... J. Sharp, C. Hedley

3. Optimizing Nitrogen Application in Global Wheat Production by an Integrated Bayesian and Machine Learning Approach

Wheat production plays a pivotal role in global food security, with nitrogen fertilizer application serving as a critical factor. The precise application of nitrogen fertilizer is imperative to maximize wheat yield while avoiding environmental degradation and economic losses resulting from excess or inadequate usage. The integration of Bayesian and machine learning methodologies has gained prominence in the realm of agricultural research. Bayesian and machine learning based methods have great... Z. Liu, X. Liu, Y. Tian, Y. Zhu, W. Cao, Q. Cao