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Premise of the StudyAccess to improved crop cultivars is the foundation for successful agriculture. New cultivars must have improved yields that are determined by quantitative and qualitative traits. Genotype‐by‐environment interactions (GEI) occur for quantitative traits such as reproductive fitness, longevity, height, weight, yield, and disease resistance. The stability of genotypes across a range of environments can be analyzed using GEI analysis. GEI analysis includes univariate and multivariate analyses with both parametric and non‐parametric models.Methods and ResultsThe program STABILITYSOFT is online software based on JavaScript and R to calculate several univariate parametric and non‐parametric statistics for various crop traits. These statistics include Plaisted and Peterson's mean variance component (θ i), Plaisted's GE variance component (θ (i)), Wricke's ecovalence stability index (W i 2), regression coefficient (b i), deviation from regression (S di 2), Shukla's stability variance (σ i 2), environmental coefficient of variance (CV i), Nassar and Huhn's statistics (S (1), S (2)), Huhn's equation (S (3) and S (6)), Thennarasu's non‐parametric statistics (NP (i)), and Kang's rank‐sum. These statistics are important in the identification of stable genotypes; hence, this program can compare and select genotypes across multiple environment trials for a given data set. This program supports both the repeated data across environments and matrix data types. The accuracy of the results obtained from this software was tested on several crop plants.ConclusionsThis new software provides a user‐friendly interface to estimate stability statistics accurately for plant scientists, agronomists, and breeders who deal with large volumes of quantitative data. This software can also show ranking patterns of genotypes and describe associations among different statistics with yield performance through a heat map plot. The software is available at https://mohsenyousefian.com/stabilitysoft/.

Premise In crop breeding programs, breeders use yield performance in both optimal and stressful environments as a key indicator for screening the most tolerant genotypes. During the past four decades, several yield‐based indices have been suggested for evaluating stress tolerance in crops. Despite the well‐established use of these indices in agronomy and plant breeding, a user‐friendly software that would provide access to these methods is still lacking. Methods and Results The Plant Abiotic Stress Index Calculator ( i PASTIC ) is an online program based on JavaScript and R that calculates common stress tolerance and susceptibility indices for various crop traits including the tolerance index ( TOL ), relative stress index ( RSI ), mean productivity ( MP ), harmonic mean ( HM ), yield stability index ( YSI ), geometric mean productivity ( GMP ), stress susceptibility index ( SSI ), stress tolerance index ( STI ), and yield index ( YI ). Along with these indices, this easily accessible tool can also calculate their ranking patterns, estimate the relative frequency for each index, and create heat maps based on Pearsonʼs and Spearmanʼs rank‐order correlation analyses. In addition, it can also render three‐dimensional plots based on both yield performances and each index to separate entry genotypes into Fernandezʼs groups (A, B, C, and D), and perform principal component analysis. The accuracy of the results calculated from our software was tested using two different data sets obtained from previous experiments testing the salinity and drought stress in wheat genotypes, respectively. Conclusions i PASTIC can be widely used in agronomy and plant breeding programs as a user‐friendly interface for agronomists and breeders dealing with large volumes of data. The software is available at https://mohsenyousefian.com/ipastic/ .