Physiological storage disorders affect a range of commercially important pomefruit and result in fruit losses and wastage of resources. Disorders can develop during and/or after storage and symptoms are strongly influenced by the growing environment and orchard management. Furthermore, fruit which receive similar orchard management and storage can vary greatly in disorder incidence and severity. Biological systems are complex and simple cause-and-effect approaches have not up until now resulted in robust methods to predict disorder risk. Reliable predictions are needed by fruit industries worldwide to better manage fruit production processes, to determine optimal harvest dates and long-term storage regimes. The current work proposes a new methodological approach to model ‘Braeburn’ apple disorder risk. Autoregressive time series (ARX) models via model identification techniques for chlorophyll, anthocyanins, soluble solids and dry matter content were obtained from weather conditions and different orchard management treatments and then served as input into a classifier for internal browning, cavities and fruit firmness after long-term controlled atmosphere storage. The classification results for internal browning disorder show a 90% agreement between two separate years and for fruit firmness an 80% success rate was obtained by training the classifier with two years of data.

生理贮藏障碍会影响一系列具有重要商业意义的柚子，并导致水果损失和资源浪费。贮藏期间和/或贮藏之后可能会出现疾病，并且生长环境和果园管理会严重影响症状。此外，接受类似果园管理和贮藏的水果在疾病发生率和严重性方面可能有很大差异。生物系统是复杂的，并且迄今为止还没有简单的因果方法产生了预测疾病风险的可靠方法。全球水果行业需要可靠的预测，以更好地管理水果生产过程，确定最佳收获日期和长期保存制度。当前的工作提出了一种新的方法学方法来模拟“ Braeburn”苹果疾病风险。通过天气条件和不同的果园处理方法，通过叶绿素，花色苷，可溶性固形物和干物质含量的模型识别技术，建立了自回归时间序列（ARX）模型，然后将其输入分类器中，以进行长期褐变，蛀牙和果实硬度的分类长期可控气氛存储。内部褐变障碍的分类结果显示，两个单独的年份之间有90％的一致性，而对于水果硬度，通过训练带有两年数据的分类器可获得80％的成功率。长期控制气氛储存后的蛀牙和水果硬度。内部褐变障碍的分类结果显示，两个单独的年份之间有90％的一致性，而对于水果硬度，通过训练带有两年数据的分类器可获得80％的成功率。长期控制气氛储存后的蛀牙和水果硬度。内部褐变障碍的分类结果显示，两个单独的年份之间有90％的一致性，而对于水果硬度，通过训练带有两年数据的分类器可获得80％的成功率。