Application Of Near Infrared Spectroscopy On Detection Of Penicillium Expansoum And Patulin

Patulin is a mycotoxin with neurotoxicity, widely found in apple juice concentrate. Penicillium expansum was reported as the major patulin-producing fungus in apple. Development of quick and easy method for testing Penicillium expansum and patulin is important to effectively control of the two harmful factors. Near infrared spectroscopy method has great potential in online detection due to its no damage to sample, quick and good reproducibility. In order to explore good method in test of Penicillium expansum and patulin, the thesis investigated the ability of near-infrared spectroscopy in detecting Penicillium expansum under different conditions including pure culture, solely contamination and multiple contamination of different mould in apple. The capability was evaluated in quality and quantity. The application of near infrared-spectroscopy in detection of patulin was also evaluated in different conditions including water solution, fresh apple juice and apple juice concentrates. The cluster analysis and predicting model establishment were used in quality test evaluation and quantity test evaluation, respectively. The main results were obtained are listed as following:(1)In the case of pure culture in solid medium, Penicillium expansum can be effectively distingushed from other fungi by using the information in whole wavelength region without any data pretreatment method, while the data pretreatment of first derivative method and vector normalization gave better results. In cases of spore suspension and contamination in apple, data pretreatment of first derivative method and vector normalization was needed to yield most effective distinguish when information was extracted from the wavelength regions of 5883⁵342 cm^-1 and 4579⁴324 cm^-1. The result was better to the contamination shallow under apple surface (3 mm) than that deeper (6mm). The testing limit of Penicillium expansum showed as 1.5x101 per ml for spore suspension and single mold contamination and 1.5x103 per ml for simultaneous contamination of different molds in apple.(2) In order to give good distinguish and quantitive test of patulin in different conditions, it is necessary to use suitable data pretreatment, main factor number and extraction of information from the spectroscopy in the wavelength regions of 5883⁵342 cm^-1. Results obtained for different conditions are listed in the follows.For water solution system, the best data pretreatment method is vector normalization at main factor number of 3. The best predicting model was obtained with coefficient of determination( R² )of 94.03% and cross-validation root deviation ( RMSECV )of 0.152 ug/L. The internal cross-validation of the predicting model yielded coefficient of determination (R²) of 93.1%, standard deviation of prediction (RMSEP) of 0.31μg/L. The detection limit was calculated as 9.29μg/L.For the apple juice concentrates, the best data pretreatment method was maximum and minimum normalized pretreatment with main factor number of 6. The predicting model was obtained as R²=93.53% and RMSECV=0.42μg/L. The internal cross-validation of the predicting model showed R²=92.65% and RMSEP=0.532μg/L with the detection limit of 9.76μg/L.For the fresh apple juice, the best data pretreatment showed as vector normalization with main factor number of 7. The best predicting model yield R²=92.01%, RMSECV=0.7 ug/L and internal cross-validation of R²=90.73% and RMSEP=0.264μg/L with the detection limit of 9.54μg/L.