A dataset on multi-trait selection approach for the evaluation of F1 tomato hybrids along with their parents under hot and humid conditions in Bangladesh

The dataset was generated using 14 cross combinations from a Line × Tester mating design, along with seven parental lines and two tester parents of tomatoes with diverse genetic bases and heat tolerance qualities in a randomized complete block (RCB) design. This dataset aims to evaluate the use of multiple trait-based selection methods with multi-trait genotype-ideotype distance index (MGIDI) models to identify superior summer F1 tomato hybrids suitable for the climatic conditions of countries like Bangladesh. The dataset of MGIDI can be universally applied to rank treatments based on desired values of multiple traits, with its potential for rapid expansion in evaluating various types of plant experiments.

本数据集基于测交系交配设计（Line × Tester mating design）构建，包含14个杂交组合、7个亲本自交系与2个遗传基础多样且具备耐热特性的番茄测验种亲本，并采用完全随机区组（randomized complete block, RCB）试验设计开展相关试验。
本数据集的研究目标为评估结合多性状基因型理想型距离指数（multi-trait genotype-ideotype distance index, MGIDI）模型的多性状选择方法的应用效果，以筛选适配孟加拉国等国气候条件的优良夏季种植型F₁番茄杂交品种。
该基于多性状基因型理想型距离指数（MGIDI）构建的数据集可依据多性状的目标设定值对试验处理进行统一排序，在各类植物试验的评价领域具备快速推广应用的潜力。