R-Based Graphical Representation of Trends in Food Production and Agriculture Value Chains in India

This study analyses the dynamics in agricultural economics in India during 2000-2023. Agricultural economics in India is a critical sector, supporting population and contributing around to the GDP through food security, the economic growth, and rising exports. Nevertheless, agriculture of India strongly depends on climate and soil setting, as these factors affect the cultivation of crops and growth cycle. Several datasets on agriculture economics of India were evaluated to reveal trends in food production and show effects climate and soil types on agriculture. The materials include three types of data: agricultural production from Food and Agriculture Organization (FAO), climate data from Climate Change Knowledge Portal, soil data from FAO/UNESCO World Digital Soil, and administrative data on India from governmental map repository. The methodology is based on the statistical analysis and GIS mapping. Practical approach includes statistical analysis and plotting of parameters to analyse dynamics in regional context. Statistical analysis was performed by R libraries, while cartographic visualization was based on the QGIS software. The core R packages include ‘ggplot2’, ‘tidyverse’, ‘dplyr’, ‘RColorBrewer’, and ‘viridisLite’. The results demonstrated dynamics in food production, export and consumption in India in recent two decades. The dominant role in export was identified as rice (basmati), spices, tea levels, fruits (mangoes) and cane sugar. The links between agriculture production, climate and soil setting shown that rising temperatures and extremes in precipitation negatively affect agricultural activities and food production in India by decreasing crop yields. This study demonstrated the use of R as effective method of large dataset processing for analysis of trends.