Journal Article10.1007/978-981-97-3690-4_47
Enhancing Agricultural Resilience in India: Leveraging Ensemble Learning for Crop Yield Prediction
Smaranika Mohapatra,Neha Chaudhary +1 more
- 01 Jan 2024
- pp 631-640
About: The article was published on 01 Jan 2024. The article focuses on the topics: Resilience (materials science) & Yield (engineering).
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References
Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison
Cynthia Rosenzweig,Joshua Elliott,Joshua Elliott,Delphine Deryng,Alex C. Ruane,Alex C. Ruane,Christoph Müller,Almut Arneth,Kenneth J. Boote,Christian Folberth,Michael Glotter,Nikolay Khabarov,K. Neumann,Franziska Piontek,Thomas A. M. Pugh,Erwin Schmid,Elke Stehfest,Hong Yang,James W. Jones +18 more
TL;DR: Uncertainties related to the representation of carbon dioxide, nitrogen, and high temperature effects demonstrated here show that further research is urgently needed to better understand effects of climate change on agricultural production and to devise targeted adaptation strategies.
On the use of statistical models to predict crop yield responses to climate change
TL;DR: In this paper, the CERES-Maize model was used to simulate historical maize yield variability at nearly 200 sites in Sub-Saharan Africa, as well as the impacts of hypothetical future scenarios of 2°C warming and 20% precipitation reduction.
928
Machine Learning Applications for Precision Agriculture: A Comprehensive Review
TL;DR: In this paper, the authors present a systematic review of ML applications in the field of agriculture, focusing on prediction of soil parameters such as organic carbon and moisture content, crop yield prediction, disease and weed detection in crops and species detection.
Crop Selection Method to maximize crop yield rate using machine learning technique
Rakesh Kumar,Munindar P. Singh,Prabhat Kumar,Jyoti Prakash Singh +3 more
- 06 May 2015
TL;DR: Wang et al. as discussed by the authors proposed a method named Crop Selection Method (CSM) to solve crop selection problem, and maximize net yield rate of crop over season and subsequently achieves maximum economic growth of the country.
309
Crop Yield Prediction Using Machine Learning Algorithms
Aruvansh Nigam,Saksham Garg,Archit Agrawal,Parul Agrawal +3 more
- 01 Nov 2019
TL;DR: The prediction made by machine learning algorithms will help the farmers to decide which crop to grow to get the maximum yield by considering factors like temperature, rainfall, area, etc.
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