Multivariate Clustering and Decomposition of Cereal Production in Rajasthan: Insights for Agricultural Policy
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Authors
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Manoj Kumar Sharma
Sri Karna Narendra Agriculture University, Jobner
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Kiran Gaur
Sri Karna Narendra Agriculture University, Jobner
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Pratibha Manohar
Sri Karna Narendra Agriculture University, Jobner
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Suresh Kumar Sharma
Sri Karna Narendra Agriculture University, Jobner
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Sarvesh Kumar Dubey
Sri Karna Narendra Agriculture University, Jobner
Keywords:
Cluster-Specific Decomposition Analysis; Decomposition of production changes, Multivariate Time Series Clustering; Production; YieldAbstract
Agriculture is the backbone of India; however, some states, like Rajasthan, have diverse conditions with potential for agricultural production. The
present article has statistically evaluated five major cereal crops, i.e., Jowar, Bajra, Maize, Wheat and Barley. The analysis was based on time series
data on area (thousand hectares), production (thousand tonnes) and yield (tonnes per hectare) for the five crops mentioned above from 1970–71 to
2023–24. The methodology is implemented using R (version 4.3.2) in R Studio. Findings revealed that the two clusters, i.e., high-yield, have found
stable and low-yield clusters that require differentiated policy approaches. Yield-driven growth in Cluster 1 demonstrated the success of irrigation
and modern inputs, while Cluster 2’s reliance on area expansion signals an opportunity for yield-enhancing innovations. The policy recommendations
address these patterns, promoting sustainable productivity in a region critical to India’s food security.
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