<![CDATA[Analysis in agro-climate research often uses long and varied time series data and even involves complex simulation models. Software is required to produce information quickly, precisely, and accurately. Agro-climate research is sometime constrained by the availability proprietary software since cost of proprietary/ licensed software is relatively high. Open source software (OSS) is one solution to overcome this constrain whereas OSS can be used freely. This paper discusses the utilization of "R" for agro-climatic research that comprise of available “R†packages for agro-climate research, several studies have applied “ Râ€Â and advantage of “R†over other statistics software. Nowadays, there are many agroclimate researches and studies have utilized R both for spatial and tabular analysis. R can be used for simple statistical analysis such as variance analysis for experimental research and even for complex climate model. Many “R†packages for agro-climate research have been developed. The “R†capabilities on data management, model simulation, modelling and machine learning are “R†advantages that very useful for current agro-climate research. By using "R" researchers have greater opportunity to explore the historical agro-climate data. "R" should be developed in agro-climate research with existing packages. Researchers can develop new packages from existing packages to solve agro-climate problems and agricultural issues in general.]]>
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