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Li, Y
Kanz, P
Tanny, J
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Authors
Rozenstein, O
Haymann, N
Kaplan , G
Tanny, J
Kanz, P
Krieger, S
Drillich, M
Iwersen, M
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
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Precision Dairy and Livestock Management
In-Season Nitrogen Management
In-Season Nitrogen Management
Type
Oral
Year
2018
2022
2024
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Filter results4 paper(s) found.

1. Estimating Cotton Water Requirements Using Sentinel-2

Crop coefficient (Kc)-based estimation of crop water consumption is one of the most commonly used methods for irrigation management.  Spectral modeling of Kc is possible due to the high correlations between Kc and the crop phenologic development and spectral reflectance.  In this study, cotton evapotranspiration was measured in the field using several methods, including eddy covariance, surface renewal, and heat pulse.  Kc was estimated as the ratio between reference evapotranspiration... O. Rozenstein, N. Haymann, G. Kaplan , J. Tanny

2. Evaluation of a Wireless Pulse Oximeter to Measure Arterial Oxygen Saturation and Pulse Rate in Newborn Holstein Friesian Calves

Pulse oximetry is a well-established technique in nowadays human and veterinarian medicine. Also in the farm animal sector, it could be a useful tool to detect critical conditions of the oxygen supply and the cardiovascular system of the patient. However, its use in ruminant medicine is still limited to experimental application. The objective of this study was to evaluate the accuracy of a Radius-7 Wearable Pulse Oximeter (Masimo Corporation, Irvine, CA) for monitoring the vital parameters of... P. Kanz, S. Krieger, M. Drillich, M. Iwersen

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

4. 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