Chen Yuzhen, Sun Wanxia, Jiu Songtao, Wang Lei, Deng Bohan, Chen Zili, Jiang Fei, Hu Menghan, Zhang Caixi
School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China.
Shanghai Key Laboratory of Multidimensional Information Processing, School of Communication and Electronic Engineering, East China Normal University, Shanghai, China.
Front Plant Sci. 2022 Jul 18;13:841452. doi: 10.3389/fpls.2022.841452. eCollection 2022.
Citrus is one of the most important fruits in China. Miyagawa Satsuma, one kind of citrus, is a nutritious agricultural product with regional characteristics of Chongming Island. Near-infrared Spectroscopy (NIR) is a proper method for studying the quality of fruits, because it is low-cost, efficient, non-destructive, and repeatable. Therefore, the NIR technique is used to detect citrus's soluble solid content (SSC) in this study. After obtaining the original spectral data, the first 70% of them are divided into the training set and 30% into the test set. Then, the Random Frog algorithm is chosen to select characteristic wavelengths, which reduces the dimension of the data and the complexity of the model, and accordingly makes the generalization of the classification model better. After comparing the performance of various classifiers (AdaBoost, KNN, LS-SVM, and Bayes) under different characteristic wavelength numbers, the AdaBoost classifier outperforms using 275 characteristic wavelengths for modeling eventually. The accuracy, precision, recall, and -score are 78.3%, 80.5%, 78.3%, and 0.780, respectively and the ROC (Receiver Operating Characteristic Curve, ROC curve) is close to the upper left corner, suggesting that the classification model is acceptable. The results demonstrate that it is feasible to use the NIR technique to estimate whether the citrus is sweet or not. Furthermore, it is beneficial for us to apply the obtained models for identifying the quality of citrus correctly. For fruit traders, the model helps them to determine the growth cycle of citrus more scientifically, improve the level of citrus cultivation and management and the final fruit quality, and thus increase the economic income of fruit traders.
柑橘是中国最重要的水果之一。宫川温州蜜柑作为柑橘的一种，是具有崇明岛地域特色的营养农产品。近红外光谱法（NIR）是研究水果品质的一种合适方法，因为它成本低、效率高、无损且可重复。因此，本研究采用近红外技术检测柑橘的可溶性固形物含量（SSC）。获取原始光谱数据后，将其中前70%分为训练集，30%分为测试集。然后，选择随机蛙跳算法来选择特征波长，这降低了数据维度和模型复杂度，从而使分类模型的泛化能力更好。在比较不同特征波长数量下各种分类器（AdaBoost、KNN、LS - SVM和贝叶斯）的性能后，最终AdaBoost分类器在使用275个特征波长进行建模时表现最佳。准确率、精确率、召回率和F1值分别为78.3%、80.5%、78.3%和0.780，并且ROC（受试者工作特征曲线）接近左上角，表明该分类模型是可接受的。结果表明，使用近红外技术估计柑橘是否甜是可行的。此外，将获得的模型应用于正确识别柑橘品质对我们有益。对于水果贸易商来说，该模型有助于他们更科学地确定柑橘的生长周期，提高柑橘种植和管理水平以及最终的水果品质，从而增加水果贸易商的经济收入。
