Abstract Optical imaging techniques have gained wide attention for quality detection of agricultural and food products. In this work, the non-destructive ability of the laser-light backscattering imaging technique (LLBI) for monitoring and classifying the quality changes of sweet potatoes under different storage conditions was investigated. Freshly-harvested sweet potato root samples were stored at 5 °C, 15 °C and 30 °C for a period of 21 d with 120 samples in each storage group. Laser diode emitting light at 658 nm wavelength along with the camera system was employed to capture the backscattered light from the subjected samples. The acquired backscattering images were then pre-processed and segmented, and the intended backscattering parameters (BP) were extracted. Quality parameters (QP) such as moisture content (MC), soluble solids content (SSC), texture and color properties (L*, a*, b*) were measured using the conventional methods as standard reference data. Multivariate analysis in terms of partial least squares regression (PLSR), principal component analysis (PCA) and linear discriminant analysis (LDA) was carried out to correlate and classify the sweet potatoes based on the BP. Results showed that storage had a significant effect both in the BP and QP of sweet potatoes as well as in the interaction between the BP and the treatments (day and temperature) applied. Among all the QP, SSC gave the most promising results (R = 0.56-0.66; RMSE = 0.76–1.10) across all the storage conditions. The analysis also revealed that 15 °C was the most suitable storage condition with the favourable PLSR results (R > 0.50) in all the examined parameters. Moreover, variations on the BP of the samples with respect to the different storage conditions were correctly classified with over 90 % and 80 % accuracies using the PCA and LDA, respectively. Thus, the study indicates that the LLBI technique is feasible and can be a useful tool for a non-destructive quality measurement and classification of sweet potatoes under different storage conditions.

中文翻译：

---

激光背散射成像方法监测和分类不同贮藏条件下红薯品质变化

摘要 光学成像技术在农产品和食品的质量检测中受到广泛关注。在这项工作中，研究了激光背散射成像技术（LLBI）在不同储存条件下监测和分类红薯质量变化的无损能力。新鲜收获的甘薯根样品在 5°C、15°C 和 30°C 下储存 21 天，每个储存组 120 个样品。激光二极管发射 658 nm 波长的光与相机系统一起用于捕获来自受试样品的背向散射光。然后对获取的反向散射图像进行预处理和分割，并提取预期的反向散射参数（BP）。质量参数 (QP)，例如水分含量 (MC)、可溶性固形物含量 (SSC)、使用常规方法作为标准参考数据测量质地和颜色特性（L*、a*、b*）。进行了偏最小二乘回归（PLSR）、主成分分析（PCA）和线性判别分析（LDA）方面的多变量分析，以基于BP对红薯进行关联和分类。结果表明，贮藏对红薯的 BP 和 QP 以及 BP 与处理（天和温度）之间的相互作用都有显着影响。在所有 QP 中，SSC 在所有储存条件下给出了最有希望的结果（R = 0.56-0.66；RMSE = 0.76-1.10）。分析还表明，在所有检查参数中，15 °C 是最合适的储存条件，具有良好的 PLSR 结果（R > 0.50）。而且，使用 PCA 和 LDA 分别以超过 90% 和 80% 的准确度对不同储存条件下样品的 BP 变化进行了正确分类。因此，该研究表明 LLBI 技术是可行的，并且可以成为在不同储存条件下对红薯进行无损质量测量和分类的有用工具。