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Zhang, J
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Authors
Ma, Y
Zhang, J
Pan, D
Wu, Q
Xiaoyu, S
Xu, X
Xiaoyu, S
Wu, Q
Ma, Y
Zhang, J
Dong, P
Xu, X
Topics
Precision Crop Protection, Pest, and Plant Health
Artificial Intelligence, Big Data, and Advanced Analytics in Agriculture
Type
Poster
Year
2026
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Filter results2 paper(s) found.

1. Inversion of Potato Chlorophyll Content Based on Radiation Transfer Model and Machine Learning Algorithm

Leaf chlorophyll content (LCC) significantly correlates with crop growth conditions, nitrogen content, yield, etc. It is a crucial indicator for elucidating the senescence process of plants and can reflect their growth and nutrition status. However, the performance of traditional LCC inversion models is limited by the quality and scale of training data. It is difficult to satisfy the needs of precision agriculture. 【Objective】Therefore, this study proposes a hybrid modeling framework based... Y. Ma, J. Zhang, D. Pan, Q. Wu, S. Xiaoyu, X. Xu

2. Study on the Phenological Zoning Method for Winter Wheat in the Huang-Huai-Hai Region of China

The impact of global climate change on agricultural phenology is becoming increasingly significant. As a major producer of winter wheat, China's cultivation areas span multiple climate zones. Against the backdrop of climate change, the spatiotemporal differentiation of crop phenology has raised new scientific demands for agricultural zoning. Phenological zoning has guiding significance for variety selection, irrigation management, and pest prediction. However, existing research often relies... S. Xiaoyu, Q. Wu, Y. Ma, J. Zhang, P. Dong, X. Xu