Ru-Yu Lien, Chun-Gu Cheng, Shih-Hsin Hung, Chien-Ying Wang, Hui-Chen Lin, Shu-Fen Lu, Shu-I Chin, Yi-Wen Kuo, Chia-Wen Liu, Ming-Chi Yung, Chun-An Cheng
The Effect of the Knowledge, Skills, and Attitudes from Nurse Training Using In Situ Simulation in an Intensive Care Unit
Healthcare (Basel, Switzerland)
ginger zingiber officinale rosc varies widely due varying concentrations phytochemicals geographical origin rapid noninvasive quality traceability assessment techniques ensure sustainable value chain objective study development suitable machine learning models estimate concentration 6gingerol check traceability based spectral fingerprints dried ginger samples collected northeast india indian market using nearinfrared spectrometry samples market northeast india underwent high performance liquid chromatographic analysis 6gingerol content estimation near infrared nir spectrometer acquired spectral data quality prediction utilized partial least square regression plsr fingerprintbased traceability identification employed principal component analysis tdistributed stochastic neighbor embedding tsne model performance assessed using rmse r2 values across selective wavelengths spectral fingerprints standard normal variate pretreated spectral data wavelength region 11001250 nm 13251550 nm showed optimal calibration model root mean square error calibration r2c coefficient determination calibration values 087 0897 respectively lower value 024 root mean square error prediction higher value 0973 r2p coefficient determination prediction indicated effectiveness developed model tsne performed better clustering samples based geographical location independent gingerol content developed nir spectroscopic model indian ginger samples predicts 6gingerol content provides geographical traceabilitybased identification ensure sustainable value chain promote efficiency costeffectiveness consumer confidence sustainable sourcing traceability datadriven decisionmaking