科研产出
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1Solving the identification problems of Bolete origins based on multiple data processing: Take Boletus bainiugan as an example
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来源：JOURNAL OF FOOD COMPOSITION AND ANALYSIS
关键词： Infrared spectroscopy; Boletus bainiugan; Data fusion; Chemometrics; Deep learning; Authentication
年份：2023
2Research Progress on Elements of Wild Edible Mushrooms
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来源：JOURNAL OF FUNGI
关键词： mushroom; trace elements; heavy metals; enrichment pattern; influencing factors
年份：2022
3Building deep learning and traditional chemometric models based on Fourier transform mid- infrared spectroscopy: Identification of wild and cultivated Gastrodia elata
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来源：FOOD SCIENCE & NUTRITION
关键词： authentication; chemometrics; deep learning; Fourier transform mid-infrared (FT-MIR) spectroscopy; Gastrodia elata; three-dimensional correlated spectral (3DCOS)
年份：2023
4Artificial and Algorithmic Screening of Infrared Spectral Feature Bands of Gastrodia elata to Achieve Rapid Identification of Its Species
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来源：JOURNAL OF CHEMOMETRICS
关键词： Chemometrics model; Gastrodia elata; infrared fingerprint region; ResNet; three-dimensional projected image
年份：2025
5Accreditations of the optimal origins of Boletus bainiugan using Fourier transform near-infrared spectroscopy in combination with environmental variables and heavy metal element determinations
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来源：INFRARED PHYSICS & TECHNOLOGY
关键词： Wild porcini mushroom; MaxEnt; Suitable habitats; Spectrum; Chemometrics; Heavy metal elements
年份：2025
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