The aim of the current work was to use hyperspectral imaging (HSI) in the spectral range 1000–2500 nm to quantitatively predict fermentation index (FI), total polyphenols (TP) and antioxidant activity (AA) of individual dry fermented cocoa beans scanned on a single seed basis, in a non-destructive manner. Seventeen cocoa bean batches were obtained and 10 cocoa beans were used from each batch. PLS regression models were built on 170 samples. The developed HSI predictive models were able to quantify three quality-related parameters with sufficient performance for screening purposes, with external validation R² of 0.50 (RMSEP = 0.27, RPD = 1.40), 0.70 (RMSEP = 34.1 mg ferulic acid g⁻¹, RPD = 1.77) and 0.74 (60.0 mmol Trolog kg⁻¹, RPD = 1.91) for FI, TP and AA, respectively. The calibrations were subsequently applied at a single bean and pixel level, so that the distribution was visualised within and between single seeds (chemical images). HSI is thus suggested as a promising approach to estimate cocoa bean composition rapidly and non-destructively, thus offering a valid tool for food inspection and quality control.

当前工作的目的是使用 1000-2500 nm 光谱范围内的高光谱成像 (HSI) 来定量预测扫描的单个干发酵可可豆的发酵指数 (FI)、总多酚 (TP) 和抗氧化活性 (AA)以非破坏性方式，单一种子基础。获得 17 批可可豆，每批使用 10 颗可可豆。PLS 回归模型建立在 170 个样本上。开发的 HSI 预测模型能够量化三个质量相关参数，具有足够的性能用于筛选目的，外部验证 R ²为 0.50（RMSEP = 0.27，RPD = 1.40），0.70（RMSEP = 34.1 mg 阿魏酸 g ^-1， RPD = 1.77) 和 0.74 (60.0 mmol Trolog kg ^-1, RPD = 1.91) 分别为 FI、TP 和 AA。随后在单个豆子和像素级别上应用校准，以便在单个种子内部和之间可视化分布（化学图像）。因此，HSI 被认为是一种快速且无损地估计可可豆成分的有前景的方法，从而为食品检验和质量控制提供了一种有效的工具。