Proceedings
Authors
| Filter results5 paper(s) found. |
|---|
1. Inversion of Potato Chlorophyll Content Based on Radiation Transfer Model and Machine Learning AlgorithmLeaf 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. Proximal and suborbital vegetation indices in yield prediction of ‘Syrah’ grapevinesThe various vegetation indices (VIs) reported in the literature, derived from different wavelengths, necessitate identifying the most suitable spectral combinations to represent agronomic variables in precision viticulture. This study evaluated the performance of proximal and suborbital VIs to explain the spatial variability of yield of the ‘Syrah’ grapevine. The study was conducted in a trellised vineyard under double pruning management in Ribeirão Preto, state of São... L.H. Bassoi, L.A. Jorge, A. Pereira, I. Oliveira Junior |
3. Consistency of Three Vegetation Indices from Suborbital and Proximal Sensing in Precision ViticultureThe integration of proximal and suborbital sensing platforms can expand the practice of precision viticulture. However, the consistency of vegetation indices (VIs) derived from different sensors remains a critical issue. This study quantified the agreement between VIs obtained by proximal and suborbital sensing using complementary metrics of association, error, and agreement. The research was conducted in a ‘Syrah’ vineyard in Ribeirão Preto, state of São Paulo, Brazil,... L.H. Bassoi, L.A. Jorge, A. Pereira, I. Oliveira Junior |
4. Study on the Phenological Zoning Method for Winter Wheat in the Huang-Huai-Hai Region of ChinaThe 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 |
5. Early Detection of Soybean Pest Infestations Using Leaf-Level Reflectance Spectroradiometry and Machine LearningThe agricultural sector plays a central role in sustaining global food production, energy supply, and economic development. However, population growth, climate change, resource scarcity, and increasing sustainability demands have intensified production challenges. Pest and disease outbreaks are major contributors to crop losses worldwide, underscoring the urgent need for reliable methods capable of enabling early detection and timely intervention. In this context, leaf-level spectroradiometry... M. Lima, J.C. Felipe, E.J. Ferreira, L.A. Jorge, L. Zhao |