Matches in SemOpenAlex for { <https://semopenalex.org/work/W2483367142> ?p ?o ?g. }
- W2483367142 endingPage "571" @default.
- W2483367142 startingPage "561" @default.
- W2483367142 abstract "This study was conducted to assess the potential feasibility of using hyperspectral imaging (900–1700 nm) for rapid determination of the volatility of tuber compositions (VTC) and prediction of the tuber cooking degree (TCD) in low temperature baking (LTB). Tuber samples of six categories from different origins were imaged and calibrated. The partial least squares regression (PLSR) and three-layer back propagation artificial neural network (TBPANN) models were established to predict VTC and TCD using the entire spectral range and the feature wavelengths. The optimal combination of characteristic wavelengths (991, 1031, 1071, 1138, 1252, 1403, 1460 and 1641 nm) were selected by first derivative and mean centering iteration algorithm (FMCIA) rather than other conventional methods. Based on the qualified eight wavelengths, the FMCIA-TBPANN approach yielded greater overall performance for predicting both VTC and TCD. Furthermore, the distribution maps of VTC and TCD were generated using a resulting function to visualize each pixel of spectral image. This demonstrated the capability of spectral imaging technique for rapid and accurate evaluation of VTC and TCD during LTB." @default.
- W2483367142 created "2016-08-23" @default.
- W2483367142 creator A5057470021 @default.
- W2483367142 creator A5082461938 @default.
- W2483367142 date "2016-09-01" @default.
- W2483367142 modified "2023-09-27" @default.
- W2483367142 title "Multivariate analysis of hyper/multi-spectra for determining volatile compounds and visualizing cooking degree during low-temperature baking of tubers" @default.
- W2483367142 cites W1774856330 @default.
- W2483367142 cites W1911149471 @default.
- W2483367142 cites W1967554761 @default.
- W2483367142 cites W1967645350 @default.
- W2483367142 cites W1969705022 @default.
- W2483367142 cites W1974095058 @default.
- W2483367142 cites W1977640095 @default.
- W2483367142 cites W1980685796 @default.
- W2483367142 cites W1985600426 @default.
- W2483367142 cites W1986059252 @default.
- W2483367142 cites W1987891903 @default.
- W2483367142 cites W1992484170 @default.
- W2483367142 cites W1993801348 @default.
- W2483367142 cites W1995880858 @default.
- W2483367142 cites W1997270149 @default.
- W2483367142 cites W1999004572 @default.
- W2483367142 cites W1999286072 @default.
- W2483367142 cites W1999491539 @default.
- W2483367142 cites W1999861104 @default.
- W2483367142 cites W1999992383 @default.
- W2483367142 cites W2001736287 @default.
- W2483367142 cites W2002026510 @default.
- W2483367142 cites W2003183258 @default.
- W2483367142 cites W2007020941 @default.
- W2483367142 cites W2007561231 @default.
- W2483367142 cites W2010761836 @default.
- W2483367142 cites W2014675011 @default.
- W2483367142 cites W2018687573 @default.
- W2483367142 cites W2018708443 @default.
- W2483367142 cites W2019929115 @default.
- W2483367142 cites W2020605278 @default.
- W2483367142 cites W2021739420 @default.
- W2483367142 cites W2022744039 @default.
- W2483367142 cites W2024148616 @default.
- W2483367142 cites W2026394582 @default.
- W2483367142 cites W2028680076 @default.
- W2483367142 cites W2030710077 @default.
- W2483367142 cites W2031257684 @default.
- W2483367142 cites W2036174096 @default.
- W2483367142 cites W2039897671 @default.
- W2483367142 cites W2040164975 @default.
- W2483367142 cites W2040629518 @default.
- W2483367142 cites W2042290752 @default.
- W2483367142 cites W2042294628 @default.
- W2483367142 cites W2042747620 @default.
- W2483367142 cites W2042881803 @default.
- W2483367142 cites W2046305320 @default.
- W2483367142 cites W2048707409 @default.
- W2483367142 cites W2051760635 @default.
- W2483367142 cites W2052096248 @default.
- W2483367142 cites W2053436921 @default.
- W2483367142 cites W2054740957 @default.
- W2483367142 cites W2059415187 @default.
- W2483367142 cites W2062517144 @default.
- W2483367142 cites W2063992521 @default.
- W2483367142 cites W2065623357 @default.
- W2483367142 cites W2071521932 @default.
- W2483367142 cites W2072688990 @default.
- W2483367142 cites W2075844424 @default.
- W2483367142 cites W2078325702 @default.
- W2483367142 cites W2081182951 @default.
- W2483367142 cites W2082697267 @default.
- W2483367142 cites W2086031780 @default.
- W2483367142 cites W2086857151 @default.
- W2483367142 cites W2087379955 @default.
- W2483367142 cites W2087680512 @default.
- W2483367142 cites W2092028063 @default.
- W2483367142 cites W2092530059 @default.
- W2483367142 cites W2095027494 @default.
- W2483367142 cites W2096315690 @default.
- W2483367142 cites W2102991103 @default.
- W2483367142 cites W2105262278 @default.
- W2483367142 cites W2109606373 @default.
- W2483367142 cites W2116146912 @default.
- W2483367142 cites W2120839962 @default.
- W2483367142 cites W2138780420 @default.
- W2483367142 cites W2148067223 @default.
- W2483367142 cites W2151500442 @default.
- W2483367142 cites W2155622525 @default.
- W2483367142 cites W2168478992 @default.
- W2483367142 cites W2337207426 @default.
- W2483367142 cites W2390373839 @default.
- W2483367142 cites W4234549270 @default.
- W2483367142 doi "https://doi.org/10.1016/j.compag.2016.07.007" @default.
- W2483367142 hasPublicationYear "2016" @default.
- W2483367142 type Work @default.
- W2483367142 sameAs 2483367142 @default.
- W2483367142 citedByCount "29" @default.
- W2483367142 countsByYear W24833671422016 @default.
- W2483367142 countsByYear W24833671422017 @default.
- W2483367142 countsByYear W24833671422018 @default.