目的 探究西兰花加冰运输中不同加冰量对西兰花物流品质的影响，并建立品质预测模型。方法 将西兰花置于泡沫箱内，按照西兰花与碎冰不同质量比(1∶1.5、1∶2.5)加入碎冰封装，然后置于20 ℃下模拟运输条件贮藏，定期测定西兰花相关指标。同时通过将泡沫箱内微环境O2含量与叶绿素、质量损失率联立，构建灰色模型进行品质预测。结果 在西兰花加冰运输中，与Ice1.5组(西兰花与碎冰质量比为1∶1.5)相比，Ice2.5组(西兰花与碎冰质量比为1∶2.5)能够延缓西兰花的黄化和叶绿素含量的下降，减少质量损失和呼吸强度，具有更好的保鲜效果。GM(1,2)灰色模型可较好地预测西兰花的叶绿素含量，平均相对误差较小。结论 西兰花加冰运输中1∶2.5的加冰量更有利于维持西兰花的品质，GM(1,2)灰色模型能实现对西兰花品质的低成本预测，可为西兰花加冰运输中品质监测提供理论指导。

The work aims to explore the effect of different ice addition ratios on broccoli quality during ice-assisted transport and develop a quality prediction model. The fresh broccoli was packed in foam boxes with varying ice-to-broccoli ratios (1∶1.5 and 1∶2.5) and stored at 20 ℃ to simulate transport conditions and then the key quality indicators were regularly measured. Additionally, a grey model was constructed to predict the quality by combining the O2 content in the microenvironment in the foam box with chlorophyll and mass loss rate. Compared with the Ice1.5 group (1∶1.5), Ice2.5 group (1∶2.5) could delay the yellowing rate and the increase in weight loss rate of broccoli and inhibit the decline rate of chlorophyll content and respiratory intensity, having better preservation effect. The GM(1,2) grey model effectively predicted chlorophyll content with minimal error. In summary, Ice2.5 is more beneficial for maintaining broccoli quality during ice-assisted transport and the GM(1,2) grey model can realize low-cost prediction of broccoli quality and provide theoretical guidance for quality monitoring of broccoli in ice-assisted transport.