Dataset on Stability Analysis of High Biomass and Yield in Maize Across Multiple Genotypes and Environments under Normal and Intercropping Systems

Description

This dataset contains raw data collected from field experiments involving 20 maize genotypes grown in various environments with replicated blocks. The primary aim of the study was to evaluate biomass production and grain yield performance under two cropping systems: sole cropping and intercropping. The dataset includes genotype codes, environmental identifiers, replication numbers, grain yield (tons per hectare), and total biomass (kilograms per hectare). These data support in-depth stability analyses, including biplot visualizations and the Genotype Stability Index (GSI), facilitating the assessment of adaptability and consistency of maize genotypes across diverse agro-ecological contexts. Researchers in plant genetics, breeding, and agronomy can leverage this dataset to identify superior genotypes and implement sustainable cultivation strategies. Additionally, the open availability of this dataset promotes scientific transparency, reproducibility, and enables further meta-analytical research on crop stability.

Steps to reproduce

The field trials evaluated twenty maize genotypes across multiple environments with three replications using a Randomized Complete Block Design (RCBD). Each genotype was cultivated in standardized plots with a spacing of 75 × 20 cm. Some genotypes were also grown in polybags (64 × 64 cm) in a screenhouse, with two plants per polybag. Shading stress was applied using paranet roofing that reduced light by 45%, while drought stress was simulated by covering the greenhouse roof with thick plastic to prevent rainfall. Four commercial genotypes were included as checks. Data were collected on two main traits: grain yield (tons/ha) and total biomass (kg/ha). Harvesting and measurements adhered to standardized protocols to ensure accuracy. Raw data were recorded in Excel, with columns for genotype ID (geno), environment (env), replication (rep), yield, and biomass. Statistical analyses for trait variation and genotype stability were performed using PBtools. Genotype × Environment interactions were analyzed using GGE and AMMI biplots, as well as multi-trait indices such as MDigi and MTSI, implemented in RStudio.

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