Enhancing Groundnut Yield Sustainability in Drought-Prone Anantapur, India
Introduction: The Challenge of Drought in Anantapur
Drought poses a significant challenge to rainfed agriculture in India, with about 69% of the total sown area vulnerable to it. Andhra Pradesh, the 8th largest state in terms of area, ranks third among drought-prone states. The Anantapur district in Andhra Pradesh, characterized by arid Alfisols and Vertisols, experiences some of the lowest rainfall in the country. Groundnut is the primary crop grown here, but yields are often low due to erratic rainfall, poor soil fertility, and lack of adequate irrigation.
Objectives: Examining Factors Influencing Groundnut Yields
This study examines the impact of rainfall, length of growing period (LGP), and cultivated area on the sustainability of groundnut yields under farmer field conditions across 31 locations in Anantapur from 2001 to 2020. By understanding these factors, we aim to identify strategies to enhance groundnut productivity and sustainability in arid regions.
Study Parameters and Methodology
Key Variables Assessed
The study considered the following variables:
- Rainfall (mm)
- Pod yield (kg/ha)
- Crop area (ha)
- Length of Growing Period (LGP) (days)
Locations were grouped into five categories based on the mean and standard deviation (SD) of each parameter:
- G1: < (Mean–2SD)
- G2: (Mean–2SD) to (Mean–SD)
- G3: (Mean–SD) to (Mean+SD)
- G4: (Mean+SD) to (Mean+2SD)
- G5: > (Mean+2SD)
Out of 31 locations, most fell into the G3 group for area and rainfall, LGP, and yield, indicating a moderate level of these variables.
Rainfall and Yield Relationship
Influence of Rainfall on Groundnut Yields
Rainfall significantly influenced groundnut yields across different locations, with correlations ranging from 0.433 in Kalyandurg to 0.765 in Putlur. This indicates that higher rainfall generally leads to better yields. Regression analysis showed that the amount of rainfall could predict yields with a reasonable degree of accuracy. For instance, at Putlur, the regression model explained 58.6% of the yield variation due to rainfall.
Area and Yield Relationship
Complex Dynamics Between Cultivated Area and Yield
The relationship between the area cultivated and yield was more complex. In some locations like Kalyandurg, Brahmasamudram, and Rapthadu, there was a significant negative correlation between the area and yield. This suggests that increasing the cultivated area without adequate resources or favorable conditions can lead to lower yields. Regression analysis supported these findings, showing that expanding the area without considering other factors could negatively impact yields.
Combining Factors to Predict Yield
Multi-Factor Regression Model for Yield Prediction
A combined regression model considering rainfall, LGP, and area showed that while the area had a negative effect on yield, rainfall, and LGP had positive effects. This model had an R² value of 0.46, indicating a moderate ability to predict yield variations. The sustainability yield index (SYI), which measures the stability of yields over time, ranged from 26.6% in Kambadur to 87.5% in Peddavadagur, with an average of 53.9%. This wide range highlights the variability in how different locations manage to sustain yields under varying conditions.
Evaluating Location Superiority
Top Performing Locations Based on Key Metrics
Locations were ranked based on mean and coefficient of variation (CV) of area, rainfall, yield, LGP, and SYI. Guntakal, Gooty, and Vidapanakal emerged as the top locations with rank sums of 30, 38, and 70, respectively. Guntakal, with a mean area of 16,570 ha, received 436.1 mm of rainfall, had an LGP of 140 days, a yield of 644 kg/ha, and an SYI of 76.5%. Gooty, with a slightly smaller area of 14,146 ha, received 429.6 mm of rainfall, had the same LGP of 140 days, a yield of 663 kg/ha, and an SYI of 79.1%. Vidapanakal had a smaller area of 5077 ha, received 403.2 mm of rainfall, had the same LGP of 140 days, a yield of 654 kg/ha, and a SYI of 77.9%.
Discussion: Insights and Strategic Recommendations
Factors Contributing to Higher Yields in Top Locations
Farmers in Guntakal, Gooty, and Vidapanakal benefit from longer growing periods and higher rainfall, enabling them to cultivate larger areas and achieve higher yields. These locations demonstrate how better rainfall distribution and longer growing periods contribute to sustainable groundnut production. The findings suggest that strategic planning and resource allocation in these regions could further enhance productivity.
Conclusion: Pathways to Sustainable Groundnut Production
This study highlights the critical role of rainfall, growing period, and cultivated area in sustaining groundnut yields in arid regions like Anantapur. By identifying superior locations and understanding the relationships between these variables, farmers can adopt better practices to maximize yields and ensure sustainability. Future efforts should focus on improving soil fertility, developing drought-resistant crop varieties, and enhancing irrigation infrastructure to support farmers in these challenging environments.
Disclaimer: This simplified research paper aims to provide a comprehensive understanding of the factors affecting groundnut yields in arid regions, making it accessible to a broader audience while retaining essential details and findings.
References
- Rao et al. (2011). Long-term rainfall effects on crop yields.
- Sinha, Anil. (2001). Strategies for disaster management in India.
- Wilhite, D.A. (2000). Drought as a natural disaster.
- Maruthi Sankar et al. (2013). Rainfall and fertilizer effects on crop yields.
- Venkatachalapathi et al. (2012). Rainfall characteristics in Anantapur.
- Parmar, et al. (2017). Inter-relationships of rainfall and yield.
- Srinivasan, et al. (2020). Land suitability for groundnut cultivation in arid soils.
Further reading:
Groundnut: Plant Information, History, Uses and Nutrition Value
