Skip to content
Research Article Open access CC BY 4.0

Study on Effect of Rainfall Variability on Crop Productivity of Tur (Arhar) and Cotton Crops for Various Districts of Maharashtra, India

S. Y. Khedikar, S. N. Panchabhai, T. K. Mandal

International Journal of Environment and Climate Change · pp. 2347–2357 · Published 29 Jul 2023

10.9734/ijecc/2023/v13i92468

Abstract

This research article investigates the impact of rainfall variability on the productivity of Tur (Arhar) and Cotton crops in the districts of Maharashtra, India. The study analyzes the correlation between rainfall departure (deviation from the normal) and crop productivity, focusing on specific months when rainfall has the most significant influence on crop yield. Secondary data from the India Meteorological Department and the Ministry of Agriculture and Farmers Welfare were utilized for the analysis. Statistical methods such as detrending, correlation analysis, and significance testing were employed to measure the relationship between rainfall variability and crop productivity. For the Tur (Arhar) crop, the study covers data from 1997-1998 to 2018-2019 for 34 districts in Maharashtra. The analysis reveals the effects of rainfall on different stages of crop growth, such as sowing, germination, vegetative growth, flowering, grain formation, and harvesting. Similarly, for the Cotton crop, data from 28 districts were examined to determine the impact of rainfall on various stages of crop development. The findings indicate that rainfall plays a crucial role in crop productivity, with both positive and negative correlations observed in different districts and months. The study highlights the significance of rainfall during specific stages of crop growth and emphasizes the importance of considering rainfall patterns when making agricultural decisions. This research contributes valuable insights into the relationship between rainfall variability and crop productivity, providing farmers and policymakers with knowledge to develop sustainable agricultural strategies in Maharashtra. By understanding the influence of rainfall on crop yield, farmers can make informed decisions regarding crop selection and adopt appropriate agricultural practices to mitigate the effects of rainfall variability.

Rainfall variability crop productivity Maharashtra Tur cotton

Cited by 6

A Decision Support Framework for Crop Prediction and Recommendation Using Supervised Learning

Ruchika Gupta, V. Jain, Ranjana Sharma · 2026 6th International Conference on Emerging VLSI and Semiconductor Technology for AI and Computing Applications (EVST) · 2026

Leveraging Remote Sensing and AI for Smart Crop Monitoring and Management

P. L. · Communications on Applied Nonlinear Analysis · 2025

Agrometeorology

Janvi Patel

Climatic variability, drought vulnerability and agrometeorological constraints in Nandurbar and Dhule districts of Maharashtra

PP Patil, SM Apturkar, SV Bagade · International Journal of Research in Agronomy · 2025

Article metrics

Real usage data collected on this platform.

0

Page views

0

PDF downloads

0

Outbound clicks

6

Citations

Views by country

Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".

No views recorded yet.

Traffic sources

Referring site, by host.

No traffic recorded yet.

Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.