Python and MATLAB script used for analysing (regression and classification) the data extracted from hyperspectral images of wheat grain samples infected by Fusarium graminearum

Python and MATLAB scripts were utilised to analyse hyperspectral imaging data from wheat grain samples, which were extracted and organised into Excel spreadsheets. The Python script was employed for classifying wheat grains using Support Vector Machine (SVC) for differentiating between levels of DON concentrations, whilst the MATLAB script was used for regression modelling with Artificial Neural Networks (ANN) for quantifying DON concentrations.

本研究采用Python与MATLAB脚本，对从已提取并整理至Excel电子表格的小麦籽粒样本中获取的高光谱成像数据开展分析。其中Python脚本依托支持向量机（Support Vector Machine, SVC）实现小麦籽粒分类，以区分不同脱氧雪腐镰刀菌烯醇（DON）浓度水平；MATLAB脚本则借助人工神经网络（Artificial Neural Networks, ANN）构建回归模型，实现DON浓度的定量测定。