Proceedings :: International Society of Precision Agriculture

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Zhen, X

Pravia, V

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Authors

Pravia, V

Terra, J.A

Roel

Zhen, X

Miao, Y

Feng, G

Huang, Y

Yang, Z

Liu, P

Bindish, R

Topics

Spatial Variability in Crop, Soil and Natural Resources

Weather and Models for Precision Agriculture

Type

Oral

Year

2010

2024

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Filter results2 paper(s) found.
1. Does Pasture Longevity Under Direct Grazing Affect Field-scale Sorghum Yield Spatial Variability In Crop-pasture Rotation Systems? Crop yield spatial variability is usually related to terrain attributes and soil properties. In pasture systems, soil properties are affected by animal grazing. However, soil and terrain attributes relation with crop yield variability has not been assessed in crop-pasture rotations.... V. Pravia, J.A. Terra, Roel Download paper
2. Evaluating the Potential of In-season Spatial Prediction of Corn Yield and Responses to Nitrogen by Combining Crop Growth Modeling, Satellite Remote Sensing and Machine Learning Nitrogen (N) is a critical yield-limiting factor for corn (Zea mays L.). However, over-application of N fertilizers is a common problem in the US Midwest, leading to many environmental problems. It is crucial to develop efficient precision N management (PNM) strategies to improve corn N management. Different PNM strategies have been developed using proximal and remote sensing, crop growth modeling and machine learning. These strategies have both advantages and disadvantages. There is... X. Zhen, Y. Miao, K. Mizuta, S. Folle, J. Lu, R.P. Negrini, G. Feng, Y. Huang

Filter results2 paper(s) found.

1. Does Pasture Longevity Under Direct Grazing Affect Field-scale Sorghum Yield Spatial Variability In Crop-pasture Rotation Systems?

Crop yield spatial variability is usually related to terrain attributes and soil properties. In pasture systems, soil properties are affected by animal grazing. However, soil and terrain attributes relation with crop yield variability has not been assessed in crop-pasture rotations.... V. Pravia, J.A. Terra, Roel

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2. Evaluating the Potential of In-season Spatial Prediction of Corn Yield and Responses to Nitrogen by Combining Crop Growth Modeling, Satellite Remote Sensing and Machine Learning

Nitrogen (N) is a critical yield-limiting factor for corn (Zea mays L.). However, over-application of N fertilizers is a common problem in the US Midwest, leading to many environmental problems. It is crucial to develop efficient precision N management (PNM) strategies to improve corn N management. Different PNM strategies have been developed using proximal and remote sensing, crop growth modeling and machine learning. These strategies have both advantages and disadvantages. There is... X. Zhen, Y. Miao, K. Mizuta, S. Folle, J. Lu, R.P. Negrini, G. Feng, Y. Huang