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Zhao, X
Zainal Abidin, M.B
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Authors
Zainal Abidin, M.B
Shibusawa, S
Ohaba, M
Li, Q
Kodaira, M
Khalid, M.B
Shibusawa, S
Ohaba, M
Zainal Abidin, M.B
Kodaira, M
Li, Q
Lu, J
Chen, Z
Miao, Y
Li, Y
Zhang, Y
Zhao, X
Jia, M
Topics
Modeling and Geo-statistics
Engineering Technologies and Advances
In-Season Nitrogen Management
Type
Poster
Oral
Year
2012
2022
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Authors

Filter results3 paper(s) found.

1. Transient Water Flow Model in a Soil-Plant System for Subsurface Precision Irrigation

The spatial variability of plant-water characteristic in the soil is still unclear. This limits the attempt to model the soil-plant-atmosphere system with this factor. Understanding the non-steady water flow along the soil-plant component is essential to understand their spatial variability.... M.B. Zainal abidin, S. Shibusawa, M. Ohaba, Q. Li, M. Kodaira, M.B. Khalid

2. Water Distribution Response in a Soil-Root System for Subsurface Precision Irrigation

A subsurface capillary irrigation system with a water source buried in a soil has been developed for precision irrigation. This system has advantages in the efficient irrigation to save much water and the real time measurement of evapotranspiration of plants. Creating this new subsurface capillary... S. Shibusawa, M. Ohaba, M.B. Zainal abidin, M. Kodaira, Q. Li

3. 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