Citation: | ZHOU Zhilei, HENG Yangyang, CHEN Chao, et al. Construction of Fourier Transform Near Infrared Spectroscopy Prediction Model for Main Components in Lycium ruthenicum Murr[J]. Science and Technology of Food Industry, 2024, 45(5): 234−242. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2023040248. |
[1] |
LIU Z G, LIU B L, WEN H X, et al. Phytochemical profiles, nutritional constituents and antioxidant activity of black wolfberry ( Lycium ruthenicum Murr.)[J]. Industrial Crops and Products,2020,154(10):81−90.
|
[2] |
LU K K, WANG J, YU Y Y, et al. Lycium ruthenicum Murr. alleviates nonalcoholic fatty liver in mice[J]. Food Science & Nutrition,2020,8(6):2588−2597.
|
[3] |
XING X Y, KE Y. Nutritional value of Lycium ruthenicum Murr. and its relieving resistance to exercise-induced fatigue[J]. Progress in Nutrition,2019,21(4):876−881.
|
[4] |
邓楷, 欧阳健, 胡娜, 等. 黑果枸杞花青素结构差异对其稳定性及细胞抗氧化活性的影响[J]. 天然产物研究与开发,2022,34(2):213−219. [DENG K, OUYANG J, HU N, et al. Effects of structural difference on stability and cellular antioxidative activity of anthocyanins from Lycium ruthenicum Murr[J]. Natural Product Research and Development,2022,34(2):213−219.]
|
[5] |
张静, 米佳, 禄璐, 等. 黑果枸杞花色苷提取物对胰脂肪酶活性的影响[J]. 食品科学,2020,41(5):8−14. [ZHANG J, MI J, LU L, et al. Effect of anthocyanins extract from Lycium ruthenicum Murr. fruit on pancreatic lipase activity[J]. Food Science,2020,41(5):8−14.]
|
[6] |
甘小娜, 王辉俊, 李廷钊, 等. 黑果枸杞化学成分的UPLC-Triple TOF/MS分析及其总花色苷类含量测定[J]. 食品科学,2021,42(18):185−190. [GAN X N, WANG H J, LI T Z, et al. Lycium ruthenicum Murray fruit:Chemical composition analysis by ultra-high performance liquid chromatography coupled to triple time of flight mass spectrometry and determination of total anthocyanins[J]. Food Science,2021,42(18):185−190.]
|
[7] |
徐金楠, 刘玮, 刘春晶, 等. 不同枸杞中多糖含量与结构特征的对比研究[J]. 中国食品学报,2015,15(4):233−239. [XU J N, LIU W, LIU C J, et al. Comparative study of the content and structural features of polysaccharides from different Lycium[J]. Journal of Chinese Institute of Food Science and Technology,2015,15(4):233−239.]
|
[8] |
王玥, 陈楠, 王博雨, 等. 基于激光驱动等离子体光源的近红外傅里叶变换光谱系统[J]. 光谱学与光谱分析,2022,42(6):1666−1673. [WNG Y, CHENG N, WANG B Y, et al. Near infrared Fourier transform spectroscopy system based on laser-driven plasma light source[J]. Spectroscopy and Spectral Analysis,2022,42(6):1666−1673.]
|
[9] |
ARSLAN M, XIAOBO Z, XUETAO H, et al. Near infrared spectroscopy coupled with chemometric algorithms for predicting chemical components in black goji berries ( Lycium ruthenicum Murr.)[J]. Journal of Near Infrared Spectroscopy,2018,26(5):275−286. doi: 10.1177/0967033518795597
|
[10] |
TAGHAVI T, PATEL H, RAFIE R. Comparing pH differential and methanol-based methods for anthocyanin assessments of strawberries[J]. Food Science & Nutrition,2022,10(7):2123−2131.
|
[11] |
OSCAR V C, OSCAR N, CASSOU S H , et al. Assessment of experimental factors affecting the sensitivity and selectivity of the spectrophotometric estimation of proanthocyanidins in foods and nutraceuticals[J]. Food Analytical Methods, 2021, 14(3):485−495.
|
[12] |
张洋婷, 郗艳丽, 葛红娟, 等. 福林酚比色法测定酸浆宿萼中总多酚含量[J]. 食品研究与开发,2016,37(23):138−141. [ZHANG Y T, XI Y L, GE H J, et al. Determination of total polyphenols in calyx physalis by Folin-ciocalteu method[J]. Food Research and Development,2016,37(23):138−141.] doi: 10.3969/j.issn.1005-6521.2016.23.032
|
[13] |
冯琳. 发酵枸杞汁的制备及解酒护肝功能的评价[D]. 无锡:江南大学, 2021. [FENG L. Liver-protectionjuice and its evaluation of anti-alcoholism and preparation of fermented Lycium barbarum[D]. Wuxi:Jiangnan University, 2021.]
FENG L. Liver-protectionjuice and its evaluation of anti-alcoholism and preparation of fermented Lycium barbarum[D]. Wuxi: Jiangnan University, 2021.
|
[14] |
张媛媛, 张彬. 苯酚-硫酸法与蒽酮-硫酸法测定绿茶茶多糖的比较研究[J]. 食品科学,2016,37(4):158−163. [ZHANG Y Y, ZHANG B. Comparison of phenol-sulfuric acid and anthrone-sulfuric methods for determination of polysaccharide in green tea[J]. Food Science,2016,37(4):158−163.]
|
[15] |
LIU J, SUN S, TAN Z, et al. Nondestructive detection of sunset yellow in cream based on near-infrared spectroscopy and interval random forest[J]. Spectrochimica Acta Part A-Molecular and Biomolecular Spectroscopy,2020,242(1):12−17.
|
[16] |
卢洁, 田婧, 梁振华, 等. 近红外光谱法快速测定香菇总糖含量[J]. 食品科学,2021,42(12):189−194. [LU J, TIAN J, LIANG Z H, et al. Application of near infrared spectroscopy in the rapid detection of total sugar content in Lentinula edodes[J]. Food Science,2021,42(12):189−194.]
|
[17] |
白京, 李家鹏, 邹昊, 等. 近红外特征光谱定量检测羊肉卷中猪肉掺假比例[J]. 食品科学,2019,40(2):287−292. [BAI J, LI J P, ZOU H, et al. Quantitative detection of pork in adulterated mutton rolls based on near infrared spectroscopy[J]. Food Science,2019,40(2):287−292.]
|
[18] |
LI Y H, ZOU X B, SHEN T T, et al. Determination of geographical origin and anthocyanin content of black goji berry ( Lycium ruthenicum Murr.) using near-infrared spectroscopy and chemometrics[J]. Food Analytical Methods,2017,10(4):1034−1044. doi: 10.1007/s12161-016-0666-4
|
[19] |
唐保山, 李坤, 张雯雯, 等. 近红外漫反射光谱结合偏最小二乘法对紫胶理化指标的快速测定[J]. 食品与发酵工业, 2020, 46(18):236−244. [TANG B S, LI K, ZHANG W W, et al. Rapid determination of physicochemical indexes in shellac using near infrared diffuse reflectance spectroscopy combined with PLS algorithm[J]. Food and Fermentation Industries, 2020, 46(18):236−244.]
TANG B S, LI K, ZHANG W W, et al. Rapid determination of physicochemical indexes in shellac using near infrared diffuse reflectance spectroscopy combined with PLS algorithm[J]. Food and Fermentation Industries, 2020, 46(18): 236−244.
|
[20] |
GUO Z, BARIMAH A O, YIN L, et al. Intelligent evaluation of taste constituents and polyphenols-to-amino acids ratio in matcha tea powder using near infrared spectroscopy[J]. Food Chemistry,2021,353:129372.
|
[21] |
MISHRA P, BIANCOLILLO A, ROGER J M, et al. New data preprocessing trends based on ensemble of multiple preprocessing techniques[J]. Trac-Trends in Analytical Chemistry,2020,132(9):28−33.
|
[22] |
吕都, 唐健波, 姜太玲, 等. 基于近红外光谱技术快速检测稻谷水分含量[J]. 食品与机械,2022,38(2):51−56,63. [LÜ D, TANG J B, JIANG T L, et al. Research on rapid prediction model of rice moisture content based on near infrared spectroscopy[J]. Food and Machinery,2022,38(2):51−56,63.]
|
[23] |
HOSSEINI E, GHASEMI J B, DARAEI B , et al. Near-infrared spectroscopy and machine learning-based classification and calibration methods in detection and measurement of anionic surfactant in milk[J]. Journal of Food Composition and Analysis, 2021, 104:104170.
|
[24] |
HUANG J, JIA X, ZHANG H , et al. Rapid determination of the total phosphorus and the nitrate nitrogen in denitrifying phosphorus removal with iPLS and near infrared spectroscopy[J]. Polish Journal of Environmental Studies, 2021, 30(4):3077−3084.
|
[25] |
ZAREEF M. 基于无损检测技术的红茶发酵过程快速监测研究[D]. 镇江:江苏大学, 2019. [ZAREEF M. Study on fast monitoring of the black tea fermentation using non-destructive techniques[D]. Zhenjiang:Jiangsu University, 2019.]
ZAREEF M. Study on fast monitoring of the black tea fermentation using non-destructive techniques[D]. Zhenjiang: Jiangsu University, 2019.
|
1. |
石翠,孔东升,吴尧,包景伟. 黑果枸杞果实不同表型特征的活性物质差异. 西北植物学报. 2024(12): 1946-1953 .
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