A new mathematical modeling framework able to simulate the combined effect of fruit growth and post-harvest storage conditions (temperature and relative humidity) on nectarine quality is here proposed. The seasonal course of fruit surface conductance to water vapor, fruit mass loss during storage, and sugar concentration dynamics in fruit pulp were modeled. The three sub-models were integrated into a model capable of calculating a fruit sweetness index and relative water loss during storage, which were selected as nectarine quality criteria. Sub-models parameters were calibrated through results from experiments carried on during 2018 and 2019, where horticultural practices (irrigation and fruit load) and storage conditions were jointly varied.

Irrigation level influenced fruit surface conductance to water vapor at harvest, but experimental results point out that this variable may have little influence on fruit mass loss during storage, which was mainly driven by relative humidity in the storage chamber. Irrigation intensity was also influential on sugar dynamics, along with storage temperature, with fruit stored at the higher temperature (25 °C) being sweeter than those stored at lower ones (2 and 15 °C). These experimental results were well replicated by the sub-model outputs.

Model simulations during storage revealed a trade-off between the two selected quality criteria, which increased with increasing storage temperature and decreasing relative humidity. The best scenario in terms of acceptable fruit mass loss and sweetness index was for fruit from water-stressed and low crop-loaded trees, 15 °C and 70% relative humidity. Moreover, storage duration was shown to increase fruit mass loss and, to a lesser extent, the sweetness index, while fruit from late harvest dates had higher sweetness at the end of storage. The model can potentially be used to manage and optimize pre-harvest and storage practices that will maximize sweetness and minimize mass loss to meet fruit quality standards along supply chains.

本文提出了一种新的数学建模框架，该框架能够模拟水果生长和收获后的储存条件（温度和相对湿度）对油桃品质的综合影响。模拟了果实表面对水蒸气的电导率的季节性变化过程，储存过程中果实质量的损失以及果肉中糖浓度的动态变化。将这三个子模型集成到一个能够计算水果甜度指数和存储期间相对失水量的模型中，这些模型被选作油桃质量标准。子模型参数是通过2018年和2019年进行的实验结果进行校准的，其中园艺做法（灌溉和水果负荷）和储存条件共同变化。

灌溉水平影响收获时果实表面对水蒸气的电导率，但实验结果表明，该变量可能对贮藏过程中的果实质量损失几乎没有影响，这主要是由贮藏室中的相对湿度驱动的。灌溉强度对糖的动力学以及储藏温度也有影响，在较高温度（25°C）下储存的水果要比在较低温度（2和15°C）下储存的水果甜。这些实验结果被子模型输出很好地复制了。

在存储过程中的模型仿真显示，在两个选定的质量标准之间进行了权衡，该标准随着存储温度的升高和相对湿度的降低而增加。就可接受的果实质量损失和甜度指数而言，最佳方案是水分胁迫和低作物负荷树，温度为15°C和相对湿度为70％的果实。此外，显示贮藏时间增加了果实的质量损失，并在较小程度上增加了甜度指数，而收获后期的果实在贮藏结束时具有较高的甜度。该模型可以潜在地用于管理和优化收获前和储存实践，从而最大限度地提高甜度并减少质量损失，从而满足整个供应链上的水果质量标准。