The non-destructive detection of fruit quality is indispensable in the agricultural and food industries. This study aimed to explore the application of hyperspectral imaging (HSI) technology, combined with machine learning, for a quality assessment of pears, so as to provide an efficient technical method. Six varieties of pears were used for inspection, including ‘Sucui No.1’, ‘Zaojinxiang’, ‘Huangguan’, ‘Akizuki’, ‘Yali’, and ‘Hongli No.1’. Spectral data within the 398~1004 nm wavelength range were analyzed to compare the predictive performance of the Least Squares Support Vector Machine (LS-SVM) models on various quality parameters, using different preprocessing methods and the selected feature wavelengths. The results indicated that the combination of Fast Detrend-Standard Normal Variate (FD-SNV) preprocessing and Competitive Adaptive Reweighted Sampling (CARS)-selected feature wavelengths yielded the best improvement in model predictive ability for forecasting key quality parameters such as firmness, soluble solids content (SSC), pH, color, and maturity degree. They could enhance the predictive capability and reduce computational complexity. Furthermore, in order to construct a quality prediction model, integrating hyperspectral data from six pear varieties resulted in an RPD (Ratio of Performance to Deviation) exceeding 2.0 for all the quality parameters, indicating that increasing the fruit sample size and variety number further strengthened the robustness of the model. The Backpropagation Neural Network (BPNN) model could accurately distinguish six distinct pear varieties, achieving prediction accuracies of above 99% for both the calibration and test sets. In summary, the combination of HSI and machine learning models enabled an efficient, rapid, and non-destructive detection of pear quality and provided a practical value for quality control and the commercial processing of pears.

As a traditional folk medicine, pear paste has important nutritional and health effects. The physicochemical properties and antioxidant activities of pear pastes prepared from 23 different cultivars were investigated, including color parameters ( L*, a*, b* and h°), transmittance, pH, titratable acidity (TA), soluble sugar content, total phenolics content (TPC), total flavonoids content (TFC), DPPH and ^•OH radical scavenging activity (RSA), and ferric reducing antioxidant power (FRAP). It was demonstrated that the physicochemical properties and antioxidant activities of pear pastes from various cultivars differed significantly. Pear cultivars of “Mantianhong”, “Xiangshui” and “Anli” possessing higher TPC and TFC exhibited excellent antioxidant activity determined by DPPH RSA, ^•OH RSA and FRAP, while the lowest TPC and TFC was observed for the cultivars of "Xueqing", "Nansui", "Hongxiangsu", and “Xinli No. 7”, which also demonstrated the poor antioxidant activity. Multivariate analyses, including factor and cluster analysis, were used for the quality evaluation and separation of pear pastes based on their physicochemical and antioxidant properties. Factor analysis reduced the above thirteen parameters to final four effective ones, i.e. DPPH RSA, color b*, FRAP and TA, and subsequently these four parameters were used to construct the comprehensive evaluation prediction model for evaluating the quality of pear pastes. The pear pastes could be separated into three clusters and differentiated for the diverse of pear cultivars via cluster analysis. Consistently, “Mantianhong”, “Xiangshui” and “Anli” pear with higher quality clustered into one group, in contrast, "Xueqing", "Nansui", "Hongxiangsu", and “Xinli No. 7” with lower quality clustered into the other group. It provided a theoretical method to evaluate the quality of pear paste and may help the fruit processing industry select the more suitable pear cultivars for pear paste making.

The radical cation generated during photobleaching of β-carotene is scavenged efficiently by the anion of methyl salicylate from wintergreen oil in a second-order reaction approaching the diffusion limit with k₂ = 3.2 × 10⁹ L mol⁻¹ s⁻¹ in 9 : 1 v/v chloroform–methanol at 23 °C, less efficiently by the anion of salicylic acid with 2.2 × 10⁸ L mol⁻¹ s⁻¹, but still of possible importance for light-exposed tissue. Surprisingly, acetylsalicylate, the aspirin anion, reacts with an intermediate rate in a reaction assigned to the anion of the mixed acetic–salicylic acid anhydride formed through base induced rearrangements. The relative scavenging rate of the β-carotene radical cation by the three salicylates is supported by DFT-calculations.