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In order to determine the optimal extraction process, and antioxidant and antibacterial activities of anthocyanins from Perilla friesians leaf, in this study, Perilla friesians leaf was used as raw material. Response surface method was used to optimize the optimal process conditions of ultrasonic-assisted extraction of anthocyanins from Perilla friesians leaf, and liquid mass combined technology was used to conduct qualitative and quantitative analysis of anthocyanins and anthocyanins in the extracts. The antioxidant activity and antibacterial activity of the extracts were studied. The results showed that the optimum conditions were as follows: The ratio of material to liquid was 1:20 g/mL, the ultrasonic temperature was 47 ℃, the ultrasonic time was 57 min, and ethanol concentration was 62%, and the maximum extraction rate was 7.18±0.32 mg/g DW under these conditions. The extract was mainly composed of cyanidin, delphinidin 3-O-glucoside, and cyanidin 3-O-glucoside. The extract showed significant scavenging activity on DPPH and ABTS+ free radicals, and the IC50 values were 0.49 and 0.32 mg/mL, respectively. The lowest inhibitory concentration against Staphylococcus aureus was 160 mg/mL. This study provides a theoretical basis for the extraction and application of anthocyanins from Perilla friesians leaf.

The objective of this study is to investigate the variations of optical properties during the progression of black spot disease and select the characteristic wavelengths for disease detection. The optical absorption and scattering properties were measured on winter jujubes using a single integrating sphere detection system in the band range of 900~1650 nm combined with inverse adding-doubling (IAD) algorithm in this study. The characteristic wavelengths were obtained depending on the correlation analysis between optical properties absorption and physicochemical indicators. Finally, the effectiveness of characteristic wavelengths was verified using near-infrared spectroscopy. The results indicated that a* and weight loss increased with storage time, while L*, soluble solids content and chlorophyll showed a consistent decrease. Both the absorption coefficient (μa) and the reduced scattering coefficient (μs') of the winter jujubes showed a significant downward trend with the development of black spot disease. The μa and μs' curves were highly correlated with disease extent (spot area) and some quality indicators (weight loss, L*, a*, soluble solids content and chlorophyll) in the 1400~1650 and 900~1360 nm, respectively. The discriminant models built based on the 10 characteristic variables selected by optical properties performed best compared with the models based on full wavelengths and algorithm-based characteristic wavelengths, with an overall accuracy of 92.53% and 92.35% for the calibration and prediction set, respectively. This study demonstrated the potential of the short- and mid-wave infrared optical signal in the disease detection on winter jujubes and the effectiveness of characteristic wavelengths on the basis of optical properties.

In this paper, the bioactive components and antioxidant activities of Cistanche tubulosa (CT) cultivated in Qinghai Province were comprehensively analyzed. The results showed that the bioactive components in different parts of Cistanche tubulosa were significantly different (P

In this work, the potential of a hyperspectral imaging (HSI) system for the detection of black spot disease on winter jujubes infected by Alternaria alternata during postharvest storage was investigated. The HSI images were acquired using two systems in the visible and near-infrared (Vis-NIR, 400–1000 nm) and short-wave infrared (SWIR, 1000–2000 nm) spectral regions. Meanwhile, the change of physical (peel color, weight loss) and chemical parameters (soluble solids content, chlorophyll) and the microstructure of winter jujubes during the pathogenic process were measured. The results showed the spectral reflectance of jujubes in both the Vis-NIR and SWIR wavelength ranges presented an overall downtrend during the infection. Partial least squares discriminant models (PLS-DA) based on the HSI spectra in Vis-NIR and SWIR regions of jujubes both gave satisfactory discrimination accuracy for the disease detection, with classification rates of over 92.31% and 91.03%, respectively. Principal component analysis (PCA) was carried out on the HSI images of jujubes to visualize their infected areas during the pathogenic process. The first principal component of the HSI spectra in the Vis-NIR region could highlight the diseased areas of the infected jujubes. Consequently, Vis-NIR HSI and NIR HSI techniques had the potential to detect the black spot disease on winter jujubes during the postharvest storage, and the Vis-NIR HSI spectral information could visualize the diseased areas of jujubes during the pathogenic process.