2020
DOI: 10.1016/j.lwt.2020.109216
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Intelligent evaluation of black tea fermentation degree by FT-NIR and computer vision based on data fusion strategy

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Cited by 64 publications
(24 citation statements)
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“…Here, 24 mice (all mice are provided by the experimental center, 12 males and 12 females) were fed in a laboratory at a constant temperature and humidity. The conditions were controlled at a 12 hr light/dark cycle at 20-27°C and 40%-70% humidity (Lu et al 2019). The mice were given basic meals and enough drinking water, and the cages were cleaned regularly.…”
Section: Animal Group Experimentsmentioning
confidence: 99%
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“…Here, 24 mice (all mice are provided by the experimental center, 12 males and 12 females) were fed in a laboratory at a constant temperature and humidity. The conditions were controlled at a 12 hr light/dark cycle at 20-27°C and 40%-70% humidity (Lu et al 2019). The mice were given basic meals and enough drinking water, and the cages were cleaned regularly.…”
Section: Animal Group Experimentsmentioning
confidence: 99%
“…The primer sequences were separated from the single-end reads, and then use the parameters recommended by Cutadapt (V1.9.1) quality-controlled process to perform quality ltering (Martin 2011). The chimera sequences (Haas et al 2011) were removed by using the SILVA reference database (Quast et al 2013) and the UCHIME algorithm (Edgar et al 2011).…”
Section: Bioinformatics and Statistical Analysesmentioning
confidence: 99%
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