Crop combination of Srikalahasti Revenue Division, Andhra Pradesh, India using J.C. Weaver’s method

Introduction

Agriculture remains the backbone of the Indian economy, contributing approximately 16-18% of the GDP and the sector employs over 46% of the workforce, providing crucial livelihood security and sustaining rural demand. Agriculture remains the primary economic driver in rural India, shaping not only the livelihood of the population but also the physical landscape. Cropping patterns means the proportion of area under various crops at a given point in time. They continuously adapt to a complex matrix of physical parameters, such as rainfall distribution and soil characteristics, alongside economic pressures like market demand and government policy. Understanding the spatial arrangement of crops is essential for optimizing agricultural resources, managing water allocation, and ensuring regional food security. In agricultural geography, researchers utilize crop combination analysis to map the integrated reality of farming practices, rather than analyzing crops in isolation. Farmers typically cultivate multiple crops in a given season to maximize yield and mitigate risk. To scientifically delineate these regions, J.C. Weaver (1954) introduced the minimum deviation method. Weaver's technique provides a mathematically rigorous approach by calculating the variance between a theoretical, idealized crop distribution and the actual cultivated land area. By identifying the combination that yields the lowest deviation, the method objectively highlights the dominant crop structures within a specific administrative boundary. The Srikalahasti Revenue Division of Andhra Pradesh presents a critical area for micro-level agricultural analysis. Comprising distinct administrative division which experiences unique meteorological conditions like rainfall during both southwest monsoon and north east monsoon seasons that directly dictate farming capabilities. The region supports a diverse agricultural profile, typically encompassing cereals, pulses, fruits, fodder crop and oilseeds. However, due to fluctuating rainfall characteristics and shifting socio-economic variables mean that the agricultural focus across these mandals is highly susceptible to change. While historical cropping patterns for the region have been broadly documented, there is a distinct need to analyze recent temporal shifts at the micro-level. Tracking how agricultural priorities transition over time allows planners to identify emerging vulnerabilities, such as a dangerous over-reliance on a single water-intensive crop. Therefore, this study aims to evaluate the evolving agricultural landscape of the Srikalahasti Revenue Division by analyzing mandal-level data of the year 2023.

The primary objectives of this study are

To calculate and delineate the crop combination regions across the mandals of the Srikalahasti Revenue Division for the years 2023 using J.C. Weaver's minimum deviation method.

Study area

The study deals with the geographical perspectives of the agriculture in Srikalahasti revenue division. Srikalahasti revenue division is administratively located in Tirupati district, Andhra Pradesh, India. The study region geographically extends 13°61´75" N to 13°88´29" N Latitude

Data and Methodology

The present study is entirely based on secondary data sources. The data has been taken from the following secondary sources: 𝑛 will be identified as the "Best Crop Combination" for that specific mandal.

Result and Discussion

Conclusion

This study applies J.C. Weaver's minimum deviation method to delineate and map the crop combination regions across the eight mandals of the Srikalahasti Revenue Division for the year 2023. The variance analysis provides a clear spatial picture of the integrated farming practices across the division's total cultivated area of 32,093 hectares. The study reveals a distinct spatial divide in cropping strategies within the region. Half of the study area specifically the Renigunta, Srikalahasti, Thotambedu, and Yerpedu mandals exhibits a monocrop agricultural pattern that is dominated by paddy. Whereas, the remaining mandals of KvbPuram, Nagalapuram, Narayanavanam, and Pichatur display a slightly broader three-crop combination. In these areas, farmers have integrated commercial and resilient crops such as groundnut, sugarcane, and bajra alongside paddy to diversify their agricultural pattern in the region and likely mitigate risk. Furthermore, the analysis highlights a significant inverse relationship between total cultivated area and crop diversification. For instance, while the Srikalahasti mandal accounts for the highest cultivated area at 7,000 hectares, it demonstrates the lowest diversification with only five crops grown. In contrast, Narayanavanam mandal features the highest crop diversification with 14 different crops cultivated, despite managing a much smaller agricultural area. The spatial analysis of crop combinations in the Srikalahasti Revenue Division underscores a heavy regional dependency on paddy cultivation. This monoculture trend poses long-term agricultural risks. By utilizing Weaver's minimum deviation method, this study provides actionable data for regional planners to drive targeted interventions, promoting necessary crop diversification and sustainable resource management to secure the region's farming future.

Acknowledgement

AcknowledgementsThe author sincerely acknowledges the University Grants Commission (UGC), India, for providing financial support under the Junior Research Fellowship (JRF) scheme. The author also expresses gratitude to Supervisor and the Department of Geography, Sri Venkateswara university, for academic guidance and institutional support respectively.

References

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