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Near-Infrared Hyperspectral Imaging Rapidly Detects the Decay of Postharvest Strawberry Based on Water-Soluble Sugar Analysis
摘要： This paper presents a novel strategy to detect the fungal decay in strawberry using reflectance near-infrared hyperspectral imaging (NIR-HSI, 1000–2500 nm). The variation of fructose, glucose, sucrose, and total water-soluble sugar (TWSS) content was analyzed using HPLC with a reference method during fungal infection in strawberry. The feasibility of quantifying sugar constituents relevant to the different stages of decay in strawberry was evaluated using NIR-HSI with key wavelengths selected via successive projection algorithm. The results showed that the predicted performance of TWSS content was acceptable within 2 and 2.603 for RPD, respectively. Five to seven key wavelengths were obtained based on sugar constituents, and excellent performance for classification accuracy among the three stages of decay was 89.4 to 95.4% for calibration and 87.0 to 94.4% for prediction, respectively. This rapid approach provides a new strategy for the selection of key wavelengths to detect the decay and sugar constituents in strawberries.
关键词： Strawberry,Key wavelength,Decay,Sugar content,Hyperspectral imaging
更新于2025-09-23 15:23:52
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Portable, visual, and nondestructive detector integrating Vis/NIR spectrometer for sugar content of kiwifruits
摘要： A portable sugar content detector for intact kiwifruits was developed using a visible/near-infrared spectrometer over the wavelength of 350–1,100 nm as spectra collector, a tablet computer as controller, a micro-halogen lamp as light source, and a self-made “Y” shape optical fiber as light transmitter and light receiver. The software applied to collect spectra, to establish sugar content prediction model, and to predict sugar content of kiwifruits was developed by Java language. Partial least square regression model was established to determine sugar content of kiwifruits. Contrasted with the sugar content obtained by digital refractometer, the root-mean-square error of the developed detector was 0.93% in soluble solids content. The obtained sugar content using the developed detector could be given in 2.5 s. The study shows that the developed portable sugar content detector is a promising tool for on-site or in field nondestructive measurement on sugar content of kiwifruits.
关键词： kiwifruits,portable detector,Vis/NIR spectrometer,nondestructive measurement,sugar content
更新于2025-09-23 15:23:52
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Sugar Contents and Firmness of Apples Based on Multi-Spectral Imaging Technology
摘要： The paper proposed a prediction method of apple sugar content and firmness based on multi-spectral imaging. Firstly, four characteristic wavelengths (670, 750, 780 and 810 nm) were selected by correlation coefficient method. The gray images of samples at different wavelengths were collected by multi-spectral imaging system, then fitted with Lorenz function, modified Lorenz function, Gaussian function and polynomial function, respectively. It was found that the fitting effect of modified Lorenz function was best. Therefore, the experiment was performed by multiple linear regression and partial least square regression analysis of sugar content and firmness with the fitting parameters of modified Lorenz function. The result showed that the prediction of multiple linear regression model was better than partial least squares regression model. The modeling correction correlation coefficient, calibration standard deviation, the prediction correlation coefficient and predicted standard deviation of sugar content were 0.8568, 0.6736, 0.8395 and 0.7068, respectively. The modeling correction correlation coefficient, calibration standard deviation, the prediction correlation coefficient and the predicted standard deviation of firmness were 0.8660, 0.3275, 0.8407 and 0.3555, respectively. The results also showed that this method was feasible for the prediction of apple sugar content and firmness.
关键词： Firmness,Multi-spectral imaging,Curve fitting,Apple,Multiple linear regression,Sugar content
更新于2025-09-04 15:30:14