Showing results 1 to 20 of 35
next >
| Issue Date | Title | Author(s) |
| 2024-02-01 | Can agronomic options alleviate the risk of compound drought-heat events during the wheat flowering period in southeastern Australia? | Li, S; Wang, B; Liu, DL; Chen, C; Feng, P; Huang, M; Wang, X; Shi, L; Waters, C; Huete, A; Yu, Q |
| 2023-12-01 | The optimization of model ensemble composition and size can enhance the robustness of crop yield projections | Li, L; Wang, B; Feng, P; Jägermeyr, J; Asseng, S; Müller, C; Macadam, I; Liu, DL; Waters, C; Zhang, Y; He, Q; Shi, Y; Chen, S; Guo, X; Li, Y; He, J; Feng, H; Yang, G; Tian, H; Yu, Q |
| 2023-09-01 | Modelling interactions between cowpea cover crops and residue retention in Australian dryland cropping systems under climate change | He, Q; Liu, DL; Wang, B; Cowie, A; Simmons, A; Waters, C; Li, L; Feng, P; Li, Y; Voil, PD; Huete, A; Yu, Q |
| 2023-05-06 | China can be self-sufficient in maize production by 2030 with optimal crop management. | Luo, N; Meng, Q; Feng, P; Qu, Z; Yu, Y; Liu, DL; Müller, C; Wang, P |
| 2022-12-01 | Identifying effective agricultural management practices for climate change adaptation and mitigation: A win-win strategy in South-Eastern Australia | He, Q; Liu, DL; Wang, B; Li, L; Cowie, A; Simmons, A; Zhou, H; Tian, Q; Li, S; Li, Y; Liu, K; Yan, H; Harrison, MT; Feng, P; Waters, C; Li, GD; de Voil, P; Yu, Q |
| 2022-10-01 | Soil properties resulting in superior maize yields upon climate warming | Feng, P; Wang, B; Harrison, MT; Wang, J; Liu, K; Huang, M; Liu, DL; Yu, Q; Hu, K |
| 2022-09-01 | Assessing future runoff changes with different potential evapotranspiration inputs based on multi-model ensemble of CMIP5 projections | Shi, L; Feng, P; Wang, B; Liu, DL; Zhang, H; Liu, J; Yu, Q |
| 2022-07 | Catalytic Mechanism of Oxygen Vacancies in Perovskite Oxides for Lithium-Sulfur Batteries. | Hou, W; Feng, P; Guo, X; Wang, Z; Bai, Z; Bai, Y; Wang, G; Sun, K |
| 2022-05-01 | Dominant sources of uncertainty in simulating maize adaptation under future climate scenarios in China | Huang, M; Wang, J; Wang, B; Liu, DL; Feng, P; Yu, Q; Pan, X; Li, S; Jiang, T |
| 2022-03-01 | Developing machine learning models with multi-source environmental data to predict wheat yield in China | Li, L; Wang, B; Feng, P; Li Liu, D; He, Q; Zhang, Y; Wang, Y; Li, S; Lu, X; Yue, C; Li, Y; He, J; Feng, H; Yang, G; Yu, Q |
| 2022-02-01 | Assessing climate vulnerability of historical wheat yield in south-eastern Australia's wheat belt | Li, S; Wang, B; Feng, P; Liu, DL; Li, L; Shi, L; Yu, Q |
| 2022-01-01 | Centennial annual rainfall pattern changes show an increasing trend with higher variation over Northern Australia | He, J; Feng, P; Wang, B; Zhuang, W; Zhang, Y; Liu, DL; Cleverly, J; Huete, A; Yu, Q |
| 2021-12-15 | Assessing maize potential to mitigate the adverse effects of future rising temperature and heat stress in China | Huang, M; Wang, J; Wang, B; Liu, DL; Feng, P; Yu, Q; Pan, X; Waters, C |
| 2021-10-15 | Crop yield forecasting and associated optimum lead time analysis based on multi-source environmental data across China | Li, L; Wang, B; Feng, P; Wang, H; He, Q; Wang, Y; Liu, DL; Li, Y; He, J; Feng, H; Yang, G; Yu, Q |
| 2021-07-21 | Optimizing Sowing Date and Planting Density Can Mitigate the Impacts of Future Climate on Maize Yield: A Case Study in the Guanzhong Plain of China | Xu, F; Wang, B; He, C; Liu, DL; Feng, P; Yao, N; Zhang, R; Xu, S; Xue, J; Feng, H; Yu, Q; He, J |
| 2020-11-01 | Quantifying future drought change and associated uncertainty in southeastern Australia with multiple potential evapotranspiration models | Shi, L; Feng, P; Wang, B; Liu, DL; Yu, Q |
| 2020-11 | Sources of uncertainty for wheat yield projections under future climate are site-specific | Wang, B; Feng, P; Liu, DL; O’Leary, GJ; Macadam, I; Waters, C; Asseng, S; Cowie, A; Jiang, T; Xiao, D; Ruan, H; He, J; Yu, Q |
| 2020-09-15 | Quantifying the impacts of pre-occurred ENSO signals on wheat yield variation using machine learning in Australia | Wang, B; Feng, P; Waters, C; Cleverly, J; Liu, DL; Yu, Q |
| 2020-08-01 | Machine learning-based integration of large-scale climate drivers can improve the forecast of seasonal rainfall probability in Australia | Feng, P; Wang, B; Liu, DL; Ji, F; Niu, X; Ruan, H; Shi, L; Yu, Q |
| 2020-07 | Using large-scale climate drivers to forecast meteorological drought condition in growing season across the Australian wheatbelt. | Feng, P; Wang, B; Luo, J-J; Liu, DL; Waters, C; Ji, F; Ruan, H; Xiao, D; Shi, L; Yu, Q |
