阿森泰克苹果（Malus domestica Borkh .cv. Aztec Fuji）是在新西兰选育的富士浓红型芽变品种，糖含量达14%以上。为了调节水果生产淡季的市场供应，苹果采收后大部分进行贮藏。成熟度、合理的贮藏环境是保证苹果采后品质的关键因素。智慧农业已成为现代农业发展的重要方向，在贮藏环节，智慧农业技术的应用能够实现对贮藏环境的智能调控，为农产品提供良好的贮藏条件。传统的品质检测技术大多是破坏性的，费时费力，不能实时监测，因此，亟需找到一种无损检测技术，以实现不同成熟度阿森泰克苹果气调贮藏期品质的实时监测，同时探究不同气调条件下苹果品质的变化趋势，实现气调环境参数的智能化选择，从而提高贮藏效率、优化贮藏管理以及降低贮藏成本，为苹果产业的发展提供有力的技术支撑。因此，本研究以阿森泰克为研究对象，借助近红外光谱技术探究在果实生长发育及不同气调条件贮藏中的品质变化以及光学响应规律，最后基于贮前的光谱信息、贮后的实时光谱建立阿森泰克苹果的品质指标预测模型，优化气调贮藏参数。具体研究内容及结果如下：

1. 不同成熟度阿森泰克苹果近红外光谱差异及品质预测研究

为明确阿森泰克苹果成熟过程中的品质变化及光学响应规律，测定了不同采收期苹果的品质指标，基于可见-近红外（Visible and near-infrared，Vis-NIR）和近红外光谱（Near-infrared，NIR），分析不同成熟度苹果的光谱反射率变化，并建立混合成熟度苹果品质的定量预测模型。结果表明：随着苹果不断成熟，阿森泰克的a*值、可溶性固形物（Soluble solid content，SSC）、干物质（Dry matter content，DMC）、可溶性糖增加，L*值、b*值、硬度（Firmness，FI）、可滴定酸（Titratable acid，TA）和水分含量（Moisture content，MC）降低。两个波段范围内的反射率均呈现下降的趋势，510~680 nm、1170~1270 nm、1430 nm、1880 nm、2300 nm是相关度较高的特征波段，可以区分不同成熟度的阿森泰克苹果。Vis-NIR范围内，L*、a*、b*的最优模型预测集决定系数（Determination coefficient of prediction，R_P²）分别为0.95、0.97、0.92；在NIR范围内，SSC最优模型为基于竞争性自适应重加权算法（Competitive adaptive reweighted sampling, CARS）建立的偏最小二乘（Partial least squares, PLS）模型，R_P²为0.91，FI、TA、MC、DMC的最优模型为基于连续投影算法（Successive projections algorithm, SPA）建立的PLS模型，R_P²分别为0.80、0.81、0.82、0.83。所有模型的相对预测偏差（Relative percent deviation，RPD）均大于2.00，说明Vis-NIR和NIR光谱方法能够预测不同成熟度阿森泰克苹果品质。

2. 不同成熟度阿森泰克苹果的品质指标与气调贮藏环境的关系研究

贮藏前的成熟度及贮藏环境是影响果实贮藏品质和耐贮性的重要因素。探究三个不同成熟度阶段（M1、M2、M3）的阿森泰克苹果品质指标与不同气调贮藏环境的关系，揭示其品质变化的规律以及不同贮藏环境对果实品质的影响程度。结果表明：标准气调贮藏环境对三种成熟度阿森泰克苹果品质影响不同，能维持M2阶段的L*值、b*值、硬度、固酸比；对M1阶段果实SSC、L*值、b*值没有显著作用，能延缓a*值上升、硬度下降；对M3阶段果实的硬度、TA有抑制下降作用。在不同气调贮藏环境下，各成熟度苹果的L*值、硬度、可滴定酸均下降，固酸比均保持上升。不同成熟度苹果的SSC、a*值、b*值在贮藏过程中的变化有差异，M1阶段果实SSC呈现上升趋势，a*值上升，b*值上下波动，M2、M3阶段苹果的SSC先上升后下降，a*值上下波动，b*值显著上升。TA、硬度、固酸比、a*、b*值等指标对不同成熟度阿森泰克苹果贮藏过程中聚类贡献率较大，考虑实际生产情况以及指标之间相关性，选取硬度、固酸比作为关键品质指标。

3. 基于贮前/贮后近红外光谱的气调贮藏中阿森泰克苹果品质预测研究

使用Vis-NIR、NIR技术采集不同成熟度阿森泰克苹果的贮前光谱以及贮后的实时光谱，来实现气调贮藏中品质监测。分析不同成熟度苹果在气调贮藏过程中反射光谱的差异，基于贮后光谱建立固酸比、硬度的实时预测模型，基于贮前光谱结合时间因子、气调因子预测苹果在不同气调环境下的品质变化，进一步比较结合不同特征波段筛选方法构建的模型，确定最优模型。结果表明：M1阶段的阿森泰克苹果的光谱反射率高于M2、M3阶段，且NIR光谱聚类效果比Vis-NIR好。在NIR波段范围内，可以很好地实现阿森泰克苹果在气调贮藏期间硬度、固酸比的实时监测，最优模型均为SPA-PLS，R_P²分别为0.81、0.80，RPD分别为2.26、2.21；基于贮前NIR光谱实现了阿森泰克气调贮藏期间的品质预测，硬度、固酸比的最优模型都为SPA-PLS，R_P²分别为0.80、0.81，RPD分别为2.23、2.27。证明基于苹果贮前光谱信息预测气调贮藏期间的品质特性具有可行性，从而提供实用和合适的策略来估计苹果的质量潜力，以此来实现更高品质、高效率的贮藏目标。

4. 基于近红外光谱的阿森泰克苹果贮后品质预测及气调贮藏参数优化的软件开发

在前期研究的基础上，通过Python编程软件，开发了基于贮后近红外光谱实时预测阿森泰克苹果气调贮藏6个月内的品质，以及基于贮前近红外光谱预测苹果气调贮藏期间品质，并优化气调贮藏参数的软件。结果表明：基于贮前光谱对苹果硬度进行预测，验证集决定系数（Determination coefficient of validation，R_V²）、验证集均方根误差（Root mean square error of validation，RMSEV）分别为0.73、0.84 N；固酸比预测结果R_V²、RMSEV分别为0.79、3.32。同时动态监测气调贮藏6个月期间的硬度、固酸比验证结果为R_V²分别为0.71、0.76，RMSEV分别为0.88 N和3.03。证明NIR技术能够依据贮藏产品的特点需求，通过预测出不同成熟度苹果在不同气调环境下的品质变化，基于品质变化选择最适气调贮藏环境，以此来实现更高品质、高效率的贮藏目标，提升阿森泰克苹果市场竞争力。

Aztec Fuji apples (Malus domestica Borkh. cv. Aztec Fuji) were a Fuji-type bud mutation variety bred in New Zealand, with a sugar content of over 14%. To regulate market supply during the off-season of fruit production, the majority of apples are stored after harvest. Maturity and appropriate storage conditions are key factors in ensuring the post-harvest quality of apples. Smart agriculture has become an important direction in modern agricultural development. In the storage process, the application of smart agricultural technology can achieve intelligent control of storage environments, providing optimal storage conditions for agricultural products. Traditional quality detection techniques are mostly destructive, time-consuming, and cannot monitor in real-time. Therefore, there is an urgent need to find a non-destructive detection technology to realize real-time monitoring of the quality of Aztec apples at different maturities during controlled atmosphere storage periods, while investigating the changing trends of apple quality under different controlled atmosphere conditions, realizing the intelligent selection of controlled atmosphere environmental parameters, so as to improve the storage efficiency, optimize the management of storage, as well as to reduce the cost of storage, and to provide a strong technological support for the development of the apple industry. Therefore, this study focused on Aztec apples, utilizing near-infrared spectroscopy technology to explore quality changes during fruit growth and development under different controlled atmosphere conditions, as well as the optical response patterns. Finally, established prediction models for quality indexes of Aztec apples based on the spectral information during the harvesting period and real-time spectra after storage, and optimized controlled atmosphere storage parameters. The main research contents and conclusions are as follows:

1. Research on the difference of near-infrared spectra and quality prediction of Aztec apples at different maturity levels

In order to clarify the quality changes and optical response patterns during the maturation process of Aztec apples, the quality indexes of apples at different harvesting stages were determined, and based on visible-near-infrared and near-infrared spectroscopy, the spectral reflectance changes of apples with different maturity levels were analyzed. The quantitative prediction models of quality were established. The results showed that a*, soluble solids, dry matter content, and soluble sugars increased, and L*, b*, firmness, titratable acid, and moisture content decreased. The reflectance within both spectral ranges exhibited a decreasing trend, and the characteristic wavelengths with high correlation were 510~680 nm, 1170~1270 nm, 1430 nm, 1880 nm, and 2300 nm, which could be used to distinguish Aztec apples at different maturity levels. In the Vis-NIR band range, the optimal models of L*, a*, and b* had R_P² of 0.95, 0.97, and 0.92, respectively. In the NIR range, the optimal model of SSC was the CARS-PLS, with R_P² of 0.91, and the optimal models of FI, TA, MC, and DMC were the SPA-PLS models, with R_P² of 0.80, 0.81, 0.82, and 0.83. The RPD of all models were greater than 2.00, indicating that Vis-NIR and NIR spectroscopy methods can effectively predict the quality of Aztec apples at different maturity levels.

2. Research on the relationship between quality indexes and controlled atmosphere storage environments of Aztec apples at different maturity levels

Pre-storage maturity and storage environment are crucial factors that affect the storage quality and shelf life of fruits. The objective of this study was to explore the relationship between the quality indicators of Aztec apples at three different maturity stages (M1, M2 and M3) and various controlled atmosphere storage environments, revealing the patterns of quality changes and the extent of the impact of different storage environments on fruit quality. The results showed that the standard air-conditioned storage environments had different effects on the quality of Aztec apples at the three maturity levels, which could maintain the L* value, b* value, FI, and SSC/TA in the M2 stage; it did not have significant effects on the SSC, L* value, and b* value of the fruits in the M1 stage, but could delay the increase of a* value and the decrease of FI; and it had inhibitory effects on the decrease of the FI and TA of the apples in the M3 stage. During the process of storage under different controlled atmospheres, the L* value, FI and TA of apples of all maturity levels decreased, and the SSC/TA kept increasing. The changes in SSC, a* value, and b* value differed during storage. At the M1 stage, the SSC of the fruits showed an upward trend, the a* value increased, and the b* value fluctuated. For apples at the M2 and M3 stages, the SSC first increased and then decreased, the a* value fluctuated, and the b* value increased significantly. Indicators such as TA, FI, SSC/TA, a*, b* values contributed significantly to the clustering of Aztec apples during storage at different maturity levels. Considering the actual production situation and the correlation between indicators, FI and SSC/TA were selected as key quality indicators for monitoring the quality of Aztec apples at different maturity levels during controlled atmosphere storage and as the basis for decision-making regarding storage conditions.

3. Research on quality prediction of asante apples during controlled atmosphere storage based on pre-storage and post-storage near-infrared spectroscopy

Visible-near-infrared and near-infrared spectroscopy were used to collect pre-storage spectra and real-time post-storage spectral data of Aztec apples at different maturity stages, aiming at monitoring the quality during controlled atmosphere storage. The differences in reflectance spectra of apples at different maturity stages during controlled atmosphere storage were analyzed. Real-time prediction models for SSC/TA and firmness were established based on post-storage spectra, while the quality changes of apples in different controlled atmosphere environments were predicted based on pre-storage spectra combined with time factors and controlled atmosphere factors. Furthermore, models constructed based on different feature band selection methods were compared to determine the optimal model. The results indicated that the spectral reflectance of Aztec apples in the M1 stage was higher than that in the M2 and M3 stages, and the clustering effect of NIR spectra was better than that of Vis-NIR. Within the NIR band range, real-time monitoring of firmness and SSC/TA of Aztec apples at different maturity stages during controlled atmosphere storage could be well achieved. The optimal models were both SPA-PLS, with R_P² values of 0.81 and 0.80, and RPD values of 2.26 and 2.21, respectively. Prediction of the quality of Aztec apples after harvesting in controlled atmosphere storage was realized based on pre-storage NIR spectra. These optimal models for firmness and SSC/TA were both SPA-PLS, with R_P² values of 0.80 and 0.81, and RPD values of 2.23 and 2.27, respectively. The above research results indicated that it was feasible to predict the quality characteristics during CA storage based on pre-storage spectral information of apples, thereby providing practical and appropriate strategies to estimate the quality potential of apples and achieving higher quality and more efficient storage goals.

4. Software development for quality prediction of post-storage Aztec apples based on near-infrared spectroscopy and optimization of controlled atmosphere storage parameters

Based on the previous research, a software was developed using Python programming that utilized post-storage near-infrared spectroscopy for real-time prediction within 6 months of controlled atmosphere storage quality of Aztec apples with different maturity levels. Additionally, the software predicted the quality during the storage period based on pre-storage near-infrared spectroscopy and optimized the controlled atmosphere parameters were developed by Python programming. The results showed that the prediction of FI using pre-storage spectra, the R_V², RMSEV were 0.73, 0.84, respectively; SSC/TA prediction results R_V², RMSEV were 0.79, 3.32, respectively. Meanwhile, dynamic monitoring of the FI and SSC/TA during 6 months controlled atmosphere storage period were 0.71 and 0.76 for R_V², 0.88 N and 3.03 for RMSEV respectively. This demonstrated that NIR technology could predict the quality changes of apples with different maturity levels in different controlled atmosphere environments according to the characteristics and requirements of storage products. Based on these quality changes, the most suitable controlled atmosphere storage environment could be selected to achieve higher quality and efficiency in storage objectives, thereby enhancing the competitiveness of Aztec apples in the market.

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