Drought is a significant stress factor for crops in arid and semi-arid regions, leading to considerable crop losses. Groundnut, a valuable oilseed crop in these regions, is particularly susceptible to water stress, resulting in reduced yields and poor product quality. Traditionally, drought stress experiments have been conducted under artificial conditions using imposed stress or rainout shelters, which may not accurately mimic the conditions faced by crops in natural drought-prone areas. In such areas, commonly known as “drought hot spots,” crops experience frequent dry spells and irregular rainfall distribution, creating a challenging environment for cultivation.
One such drought hot spot is located in Anantapur, Andhra Pradesh, India. Anantapur is characterized by a hot, arid climate with limited and variable rainfall, making it an ideal location for evaluating crop performance under drought stress. Over 50% of the rainfall in the region shows significant variability. Additionally, the soil in Anantapur is red sandy loam with shallow depth and compact sub-surface, restricting root growth and exacerbating the effects of drought stress.
India has released more than 200 groundnut cultivars for commercial cultivation, with 30-35 of them claimed to possess drought-tolerant characteristics. However, these claims have not been adequately validated in drought hot spot locations like Anantapur. To address this gap, a study was conducted to evaluate the drought tolerance of 30 groundnut cultivars in the naturally drought-prone areas of Anantapur under rainfed conditions during the Kharif seasons from 2017 to 2019.
The study used a randomized complete block design with two replications. Pod yield and rainfall-use-efficiency (RUE) were measured for each genotype across the three consecutive rainy seasons. The analysis of variance (ANOVA) revealed significant genotype, environment, and genotype-environment interaction (GEI) effects on pod yield and RUE.
To assess stability, the study employed the Additive Main Effects and Multiplicative Interaction (AMMI) stability model. The model partitioned the GEI into signal and noise, where signal represents the known factors affecting the performance, such as genotypes and drought phase, while noise represents the unexplained variance. The AMMI model provided insights into the stable performance of genotypes, and the Modified AMMI Stability Index (MASI) was used to rank the genotypes based on stability.
Furthermore, the study employed the GGE biplot analysis to visualize the genotype-environment interaction. The biplots helped identify the most discriminative and representative environments for genotype evaluation and facilitated the identification of ideal genotypes based on their positions in the biplots.
Based on the analysis, Kadiri 5 was identified as the most stable and high-yielding groundnut genotype under drought-stress conditions. The rainy season of 2018 was considered the most discriminative for evaluating drought-tolerant genotypes. Kadiri 5 exhibited high stability and yield across environments, making it a promising candidate for cultivation in drought-prone regions, including Anantapur and adjacent areas.
The identification of Kadiri 5 as a drought-tolerant cultivar has significant implications for groundnut cultivation in arid and semi-arid regions. By cultivating Kadiri 5 and other identified drought-tolerant genotypes, farmers can potentially mitigate the adverse effects of water stress on groundnut production. Additionally, these cultivars could be used as a foundation for breeding programs to develop more drought-resistant groundnut variants suitable for drought-prone regions.
This study demonstrated the importance of conducting drought stress experiments in natural drought hot spots to accurately assess the performance of crop varieties under real-world conditions. The identification of drought-tolerant genotypes like Kadiri 5 in Anantapur provides valuable insights for sustainable agriculture in water-scarce regions, ensuring food security and increasing groundnut productivity.
Photo by Markus Spiske on Unsplash
