Climate Variability and its Effects on Green Gram Yield in Nalanda, Bihar, India
Kumari Sakshi *
Department of Agronomy, Naini Agriculture Institute, Sam Higginbottom University of Agriculture Technology and Sciences, Prayagraj, Uttar Pradesh – 211007, India.
Shraddha Rawat
Department of Agronomy, Naini Agriculture Institute, Sam Higginbottom University of Agriculture Technology and Sciences, Prayagraj, Uttar Pradesh – 211007, India.
Rupesh Ranjan
Department of Agronomy, Naini Agriculture Institute, Sam Higginbottom University of Agriculture Technology and Sciences, Prayagraj, Uttar Pradesh – 211007, India.
*Author to whom correspondence should be addressed.
Abstract
Rainfall is a very important natural resource, which plays a pivotal role in the success or failure of agricultural crop production in an area. In the recent years, successful and profitable production of kharif rice, which is a very important crop in Bihar, has been a gamble with erratic monsoon system. This study evaluates the impact of climate variability and long-term weather trends on green gram (Vigna radiata) productivity in Nalanda district of Bihar, India. A comprehensive climatic analysis was carried out using 32 years (1992–2024) of weather data, including maximum and minimum temperature, rainfall, and relative humidity. The data regarding the annual production (measured in kilograms) and the area under cultivation (expressed in hectares) for green gram crop (Kharif season) in the Nalanda district, has been obtained from the district-level yield database curated by the Directorate of Economics and Statistics within the Department of Agriculture and Farmers Welfare. The annual mean values observed were: maximum temperature 32.67 ± 0.79%, minimum temperature 20.37 ± 0.44%, relative humidity 56.30 ± 4.57%, and annual rainfall 1001.2 ± 199.9 mm, indicating notable inter-annual variability and emerging climate trends. Green gram yield data for the period 1999–2022 were sourced from the official Agriculture Production Yield (APY) portal of the Directorate of Economics and Statistics, Ministry of Agriculture, Government of India. Trend analysis of weather variables was performed using XLSTAT. To assess the influence of climate on yield, Pearson correlation analysis was carried out between weekly weather variables and crop yield. The results showed that maximum temperature during the vegetative stage (SMW 27) had a significant positive correlation with green gram yield (r = 0.262*), indicating beneficial thermal conditions during early growth. Similarly, rainfall during the flowering stage (SMW 30) exhibited a highly significant positive correlation (r = 0.234**). Additional positive associations were observed during harvest maturity stages (SMW 35–37) with both maximum and minimum temperatures. The study highlights that green gram yield in the region is highly sensitive to climatic conditions during specific phenological stages. These findings underline the need for climate-resilient agricultural strategies and weather-based planning to enhance pulse productivity in the face of ongoing climate change.
Keywords: Climate variability, trend analysis, correlation analysis, XLSTAT, excel