Evaluation of Conditional Treatment Effect of Salt Stress on Tomato Sugar Content Using Causal Machine Learning: A Pilot Study

This dataset contains the raw data used for the analyses presented in the manuscript titled “Evaluation of Conditional Treatment Effect of Salt Stress on Tomato Sugar Content Using Causal Machine Learning: A Pilot Study”. The study investigated the effects of salt stress on tomato sugar content (Brix) under hydroponic cultivation across multiple environmental conditions, and applied causal inference and machine learning techniques to estimate treatment effects and analyze fruit traits. The dataset includes environmental measurements, sugar content data, treatment information, and image data collected from a commercial greenhouse. The data were obtained from a single production site and were collected continuously throughout the cultivation periods.

本数据集包含题为《利用因果机器学习（Causal Machine Learning）评估盐胁迫（Salt Stress）对番茄糖含量的条件处理效应（Conditional Treatment Effect）：一项预试验研究》的手稿中所呈现分析的原始数据。本研究探究了多环境条件下水培栽培模式下，盐胁迫对番茄糖度（Brix）的影响，并运用因果推断与机器学习技术估算处理效应、解析果实性状。本数据集涵盖从某商业温室采集的环境测量数据、糖含量数据、处理信息与图像数据，所有数据均取自单一生产基地，并在整个栽培周期内持续采集所得。