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.本数据集可用于构建基于田间监测数据的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，以及用于市场分级的主、客观供应商评定标准。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，其中体积较大的草莓采用自动与手动结合的方式完成图像分割。数据集同时提供每小时更新的微气候数据，涵盖温度、湿度、CO₂_22浓度、光照强度以及植株营养状况。针对货架期研究，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：「单果品质评估集」，收录与图像中可见草莓相关的测量数据；「综合品质评估集」，收录全部测量数据，包括未关联图像的样本。本数据集为探究影响草莓品质的各类因素提供了理想的研究支撑。

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、市场分类标准，以及RGB和OCN图像、微气候数据等。数据集分为'Individual Quality Evaluations'和'Aggregated Quality Evaluations'两个子集，覆盖2021年至2024年在荷兰多个地点的监测数据，适用于探索草莓质量影响因素的研究。