Rapid identification and quantitative pit mud by near infrared Spectroscopy with chemometrics
Tài liệu tham khảo
Liu, 2017, Deep sequencing reveals high bacterial diversity and phylogenetic novelty in pit mud from Luzhou Laojiao cellars for Chinese strong-flavor Baijiu, Food research international, 102, 68, 10.1016/j.foodres.2017.09.075
Hu, 2016, Illuminating anaerobic microbial community and cooccurrence patterns across a quality gradient in Chinese liquor fermentation pit muds, Appl. Environ. Microbiol., 82, 2506, 10.1128/AEM.03409-15
Tao, 2014, Prokaryotic communities in pit mud from different-aged cellars used for the production of Chinese strong-flavored liquor, Appl. Environ. Microbiol., 80, 2254, 10.1128/AEM.04070-13
Wang, 2017, Classification of Chinese Herbal Medicine by Laser-Induced Breakdown Spectroscopy with Principal Component Analysis and Artificial Neural Network, Analytical Letters, 51, 575, 10.1080/00032719.2017.1340949
Liang, 2015, Analysis of the bacterial community in aged and aging pit mud of Chinese Luzhou‐flavour liquor by combined PCR‐DGGE and quantitative PCR assay, Journal of the Science of Food and Agriculture, 95, 2729, 10.1002/jsfa.7013
Zhang, 2020, Prokaryotic communities in multidimensional bottom-pit-mud from old and young pits used for the production of Chinese Strong-Flavor Baijiu, Food Chemistry, 312, 10.1016/j.foodchem.2019.126084
Luo, 2014, Phylum-Specific Primer Design and Implication in Quantification of the Microbial Community Structure in GuJingGong Pit Mud, Advanced Materials Research, 1051, 311, 10.4028/www.scientific.net/AMR.1051.311
Spohn, 2016, Dynamics of soil carbon, nitrogen, and phosphorus in calcareous soils after land-use abandonment – A chronosequence study, Plant Soil, 401
Kizewski, 2011, Spectroscopic approaches for phosphorus speciation in soils and other environmental systems, J Environ Qual, 40, 751, 10.2134/jeq2010.0169
McLaren, 2015, Complex Forms of Soil Organic Phosphorus-A Major Component of Soil Phosphorus, Environ Sci Technol, 49, 13238, 10.1021/acs.est.5b02948
George, 2016, Phosphorus in soils and plants – facing phosphorus scarcity, Plant and Soil, 401, 1, 10.1007/s11104-016-2846-9
Xiao, 2012, Determination of main categories of components in corn steep liquor by near-infrared spectroscopy and partial least-squares regression, J Agric Food Chem, 60, 7830, 10.1021/jf3012823
Calazans, 2016, Soil organic carbon as a key predictor of N in forest soils of Brazil, Journal of Soils and Sediments, 18, 1242, 10.1007/s11368-016-1557-4
dos Santos, 2017, A review on the application of vibrational spectroscopy in the wine industry: From soil to bottle, TrAC Trends in Analytical Chemistry, 88, 100, 10.1016/j.trac.2016.12.012
Porep, 2015, On-line application of near infrared (NIR) spectroscopy in food production, Trends in Food Science & Technology, 46, 211, 10.1016/j.tifs.2015.10.002
Wang, 2017, Quality analysis, classification, and authentication of liquid foods by near-infrared spectroscopy: A review of recent research developments, Crit Rev Food Sci Nutr, 57, 1524, 10.1080/10408398.2015.1115954
Lopo, 2018, Near infrared spectroscopy as a tool for intensive mapping of vineyards soil, Precis. Agric., 19, 445, 10.1007/s11119-017-9529-2
Catelani, 2018, Real-time monitoring of a coffee roasting process with near infrared spectroscopy using multivariate statistical analysis: A feasibility study, Talanta, 179, 292, 10.1016/j.talanta.2017.11.010
dos Santos, 2017, Merging vibrational spectroscopic data for wine classification according to the geographic origin, Food Res. Int., 102, 504, 10.1016/j.foodres.2017.09.018
Ning, 2012, Simultaneous determination of heavy metal ions in water using near-infrared spectroscopy with preconcentration by nano-hydroxyapatite, Spectrochim Acta A Mol Biomol Spectrosc, 96, 289, 10.1016/j.saa.2012.05.034
Liu, 2013, Micro-analysis by near-infrared diffuse reflectance spectroscopy with chemometric methods, Analyst, 138, 6617, 10.1039/c3an01232h
Shan, 2019, Rapid prediction of atrazine sorption in soil using visible near-infrared spectroscopy, Spectrochim Acta A Mol Biomol Spectrosc, 224
Knox, 2018, Total soil carbon assessment: linking field, lab, and landscape through VNIR modelling, Landscape Ecology, 33, 2137, 10.1007/s10980-018-0729-6
Brereton, 2017, Chemometrics in analytical chemistry-part I: history, experimental design and data analysis tools, Anal Bioanal Chem, 409, 5891, 10.1007/s00216-017-0517-1
Ding, 2016, A novel NIR spectroscopic method for rapid analyses of lycopene, total acid, sugar, phenols and antioxidant activity in dehydrated tomato samples, Vib. Spectrosc., 82, 1, 10.1016/j.vibspec.2015.10.004
Shao, 2003, Wavelet: A new trend in chemistry, Accounts of Chemical Research, 36, 276, 10.1021/ar990163w
Engel, 2013, Breaking with trends in pre-processing?, TrAC Trends in Analytical Chemistry, 50, 96, 10.1016/j.trac.2013.04.015
Zhou, 2016, Structural damage detection using transmissibility together with hierarchical clustering analysis and similarity measure, Structural Health Monitoring: An International Journal, 16, 711, 10.1177/1475921716680849
Heil, 2019, Advantages of fuzzy k-means over k-means clustering in the classification of diffuse reflectance soil spectra: A case study with West African soils, Geoderma, 337, 11, 10.1016/j.geoderma.2018.09.004
Fajardo, 2016, Fuzzy clustering of Vis–NIR spectra for the objective recognition of soil morphological horizons in soil profiles, Geoderma, 263, 244, 10.1016/j.geoderma.2015.05.010
Brereton, 2015, Pattern recognition in chemometrics, Chemometrics Intell. Lab. Syst., 149, 90, 10.1016/j.chemolab.2015.06.012
Barra, 2019, FTIR fingerprints associated to a PLS-DA model for rapid detection of smuggled non-compliant diesel marketed in Morocco, Vib. Spectrosc., 101, 40, 10.1016/j.vibspec.2019.02.001
Tian, 2020, An rapid nondestructive testing method for distinguishing rice producing areas based on Raman spectroscopy and support vector machine, Vib. Spectrosc., 107, 10.1016/j.vibspec.2019.103017
Wold, 1977, 52, 243
Dixon, 2009, Chemometrics Intell. Lab. Syst., 95, 1, 10.1016/j.chemolab.2008.07.010
Morellos, 2016, Machine learning based prediction of soil total nitrogen, organic carbon and moisture content by using VIS-NIR spectroscopy, Biosystems Engineering, 152, 104, 10.1016/j.biosystemseng.2016.04.018
Wold, 2001, PLS-regression: a basic tool of chemometrics, Chemometrics Intell. Lab. Syst., 58
Gredilla, 2016, Non-destructive Spectroscopy combined with chemometrics as a tool for Green Chemical Analysis of environmental samples: A review, TrAC Trends in Analytical Chemistry, 76, 30, 10.1016/j.trac.2015.11.011
Carra, 2019, Macedo Dos Santos Tonial, L., Near-Infrared Spectroscopy Coupled with Chemometrics Tools: A Rapid and Non-Destructive Alternative on Soil Evaluation, Communications in Soil Science and Plant Analysis, 50, 421, 10.1080/00103624.2019.1566465
Geladi, 1985, Linearization and scatter-correction for near-infrared reflectance spectra of meat, Applied Spectroscopy, 39, 491, 10.1366/0003702854248656
Soriano-Disla, 2013, The Performance of Visible, Near-, and Mid-Infrared Reflectance Spectroscopy for Prediction of Soil Physical, Chemical, and Biological Properties, Applied Spectroscopy Reviews, 49, 139, 10.1080/05704928.2013.811081
Curcio, 2013, Prediction of soil texture distributions using VNIR-SWIR reflectance spectroscopy, Vol. 19, 494
Steinier, 1972, Smoothing and differentiation of data by simplified least square procedure, Analytical chemistry, 44, 1906, 10.1021/ac60319a045
Morón, 2007, Measurement of Phosphorus in Soils by Near Infrared Reflectance Spectroscopy: Effect of Reference Method on Calibration, Communications in Soil Science and Plant Analysis, 38, 1965, 10.1080/00103620701548498