Agricultural Sciences

Agricultural Sciences

ISSN Print: 2156-8553
ISSN Online: 2156-8561
www.scirp.org/journal/as
E-mail: as@scirp.org
"A Dual Ensemble Agroclimate Modelling Procedure to Assess Climate Change Impacts on Sugarcane Production in Australia"
written by Yvette Everingham, Geoff Inman-Bamber, Justin Sexton, Chris Stokes,
published by Agricultural Sciences, Vol.6 No.8, 2015
has been cited by the following article(s):
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[1] Climate change and Australia's primary industries: factors hampering an effective and coordinated response
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[2] Potential for sugarcane production under current and future climates in South Africa: sugar and ethanol yields, and crop water use
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[3] Sugarcane Yield Prediction Using Vegetation Indices in Northern Karnataka, India
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[4] Employment Challenges in Agriculture in Australia
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[5] The impact of climate change and climate extremes on sugarcane production
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[6] A Random Forest Algorithm for Predicting Crop Yield in Hilly Regions of North East India
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[7] Global Optimization of Cultivar Trait Parameters in the Simulation of Sugarcane Phenology Using Gaussian Process Emulation
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[8] Sugarcane: Contribution of Process-Based Models for Understanding and Mitigating Impacts of Climate Variability and Change on Production
2020
[9] An improved workflow for calibration and downscaling of GCM climate forecasts for agricultural applications–A case study on prediction of sugarcane yield in Australia
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[10] Crop Yield Estimation Using Decision Trees and Random Forest Machine Learning Algorithms on Data from Terra (EOS AM-1) & Aqua (EOS PM-1) Satellite Data
2020
[11] Traits for canopy development and light interception by twenty-seven Brazilian sugarcane varieties
2020
[12] Modeling Environmental Actions of Corporate Sustainable Activity: Evidence from Lithuania
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[13] The impact of climate change on the Australian sugarcane industry
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[14] Crop Yield Estimation Using Decision Trees and Random Forest Machine Learning Algorithms on Data from Terra
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[15] Site-specific assessment of spatial and temporal variability of sugarcane yield related to soil attributes
Geoderma, 2019
[16] New APSIM-Sugar features and parameters required to account for high sugarcane yields in tropical environments
2019
[17] Predicting the effect of climate change on sugarcane cultivation Fábio R. Marin, University of São Paulo (USP)-Luiz de Queiroz College of Agriculture …
Achieving …, 2019
[18] Data Mining Efficiency in Auctions on the basis of Random Forest Algorithm A Case Study on Source-Area Wholesale Market in Atsumi Area, Aichi Prefecture
The Agricultural Marketing Journal of Japan, 2018
[19] Spatial and temporal variability of soil attributes and their relationship with crop yield, topographic parameters and apparent electrical conductivity (ECa) in sugarcane …
2018
[20] Implications of climate change for the sugarcane industry
Wiley Interdisciplinary Reviews: Climate Change, 2018
[21] Refining the Canegro model for improved simulation of climate change impacts on sugarcane
European Journal of Agronomy, 2018
[22] Future climate change projects positive impacts on sugarcane productivity in southern China
European Journal of Agronomy, 2018
[23] Predicting the effect of climate change on sugarcane cultivation
2018
[24] Measuring and modelling CO 2 effects on sugarcane
Environmental Modelling & Software, 2016
[25] Accurate prediction of sugarcane yield using a random forest algorithm
Agronomy for Sustainable Development, 2016
[26] Quantification of the effects of climate warming and crop management on sugarcane phenology
2016
[27] Measuring and modelling CO2 effects on sugarcane
Environmental Modelling & Software, 2016
[28] Bayesian statistical calibration of variety parameters in a sugarcane crop model
2015
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