PDF(Pubmed)
Abstract：
(1) Background: To achieve the rapid, non-destructive detection of corn freshness and staleness for better use in the storage, processing and utilization of corn. (2) Methods: In this study, three varieties of corn were subjected to accelerated aging treatment to study the trend in fatty acid values of corn. The study focused on the use of hyperspectral imaging technology to collect information from corn samples with different aging levels. Spectral data were preprocessed by a convolutional smoothing derivative method (SG, SG1, SG2), derivative method (D1, D2), multiple scattering correction (MSC), and standard normal transform (SNV); the characteristic wavelengths were extracted by the competitive adaptive reweighting method (CARS) and successive projection algorithm (SPA); a neural network (BP) and random forest (RF) were utilized to establish a prediction model for the quantification of fatty acid values of corn. And, the distribution of fatty acid values was visualized based on fatty acid values under the corresponding optimal prediction model. (3) Results: With the prolongation of the aging time, all three varieties of corn showed an overall increasing trend. The fatty acid value of corn can be used as the most important index for characterizing the degree of aging of corn. SG2-SPA-RF was the quantitative prediction model for optimal fatty acid values of corn. The model extracted 31 wavelengths, only 12.11% of the total number of wavelengths, where the coefficient of determination RP2 of the test set was 0.9655 and the root mean square error (RMSE) was 3.6255. (4) Conclusions: This study can provide a reliable and effective new method for the rapid non-destructive testing of corn freshness.
摘要：
(1)背景:实现快速,对玉米新鲜度和陈旧性进行无损检测，以便更好地在储存中使用，玉米加工利用.(2)方法：在本研究中，对3个玉米品种进行加速老化处理，研究玉米脂肪酸值的变化趋势。研究重点是利用高光谱成像技术从不同老化水平的玉米样品中收集信息。光谱数据通过卷积平滑导数方法(SG，SG1、SG2)，导数法(D1，D2)，多重散射校正(MSC)，利用竞争自适应重加权法(CARS)和连续投影算法(SPA)提取特征波长,利用神经网络(BP)和随机森林(RF)建立玉米脂肪酸值定量预测模型。And,在相应的最优预测模型下，根据脂肪酸值可视化脂肪酸值的分布。(3)结果:随着老化时间的延长,三个品种玉米均呈总体增长趋势。玉米的脂肪酸值可以作为表征玉米老化程度的最重要指标。SG2-SPA-RF是玉米最佳脂肪酸值的定量预测模型。该模型提取了31个波长，仅占波长总数的12.11%，其中测试集的确定系数RP2为0.9655，均方根误差（RMSE）为3.6255。(4)结论:本研究可为玉米鲜度的快速无损检测提供可靠有效的新方法。
