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。数据集涵盖草莓成熟过程中的物理与生化指标，以及供应商用于市场分级的主客观分级标准。品质属性通过人工评估与设备测量两种方式确定。田间监测数据包含草莓的RGB图像与OCN图像，其中较大草莓通过自动与手动两种方式完成图像分割。同时提供每小时的微气候数据，涵盖温度、湿度、二氧化碳浓度、光照强度以及植株营养状况。针对货架期研究，本数据集还提供了追踪存储过程中重量损耗的监测图像。该数据集包含两个子数据集：其一为「单株品质评估」（Individual Quality Evaluations），对应与图像中可见草莓关联的测量数据；其二为「综合品质评估」（Aggregated Quality Evaluations），收录全部测量数据，包含未关联图像的样本。本资源为探索影响草莓品质的各类因素提供了极佳的研究载体。

搜集汇总

背景与挑战

背景概述

该数据集支持基于田间监测数据的草莓质量预测模型，包含物理和生化成熟指标、供应商标准、RGB与OCN图像、微气候数据（如温度、湿度和光照）以及存储期间重量损失监测图像。数据集分为“个体质量评估”和“聚合质量评估”两个子集，适用于探索草莓质量影响因素，并覆盖2021年至2024年在荷兰多个地点的数据，格式为.csv、.png和.jpg。