Data underlying the research of strawberry quality prediction with infield data

This dataset supports predictive models for assessing strawberry quality using infield monitoring data. It includes physical and biochemical indicators of ripening, as well as subjective and objective supplier criteria for market categorization. Quality attributes are determined through human assessment and device measurements.Infield data includes RGB and OCN images of strawberries, with larger strawberries segmented using automated and manual methods. Hourly micro-climate data, such as temperature, humidity, CO2_22​ density, illumination, and plant nutrition, is also provided. For on-shelf studies, monitoring images tracking weight loss during storage are available.The dataset has two subsets: "Individual Quality Evaluations" for measurements linked to visible strawberries in images, and "Aggregated Quality Evaluations" containing all measurements, including those without image links. This resource is ideal for exploring factors affecting strawberry quality.

本数据集可支撑基于田间监测数据构建草莓品质评估预测模型的相关研究。数据集涵盖草莓成熟过程中的物理与生化指标，以及用于市场分级的供应商主客观评判标准。草莓品质属性通过人工评估与仪器测量两种方式确定。田间监测数据包含草莓的RGB图像与OCN图像，并采用自动与手动分割方法对较大尺寸草莓进行实例分割。此外还提供每小时更新的微气候数据，包括温度、湿度、二氧化碳（CO₂）浓度、光照强度以及植株营养水平。针对货架期研究场景，数据集还提供了存储过程中追踪重量损耗的监测图像。本数据集包含两个子集：「单果品质评估集」（Individual Quality Evaluations），用于关联图像中可见草莓的各项测量数据；以及「综合品质评估集」（Aggregated Quality Evaluations），涵盖全部测量数据（包括未关联图像的样本）。该数据集是探究草莓品质影响因素的理想研究资源。