FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4313889927> ?p ?o ?g. }

• W4313889927 endingPage "666" @default.
• W4313889927 startingPage "666" @default.
• W4313889927 abstract "Genetic improvement of milk fatty acid content traits in dairy cattle is of great significance. However, chromatography-based methods to measure milk fatty acid content have several disadvantages. Thus, quick and accurate predictions of various milk fatty acid contents based on the mid-infrared spectrum (MIRS) from dairy herd improvement (DHI) data are essential and meaningful to expand the amount of phenotypic data available. In this study, 24 kinds of milk fatty acid concentrations were measured from the milk samples of 336 Holstein cows in Shandong Province, China, using the gas chromatography (GC) technique, which simultaneously produced MIRS values for the prediction of fatty acids. After quantification by the GC technique, milk fatty acid contents expressed as g/100 g of milk (milk-basis) and g/100 g of fat (fat-basis) were processed by five spectral pre-processing algorithms: first-order derivative (DER1), second-order derivative (DER2), multiple scattering correction (MSC), standard normal transform (SNV), and Savitzky-Golsy convolution smoothing (SG), and four regression models: random forest regression (RFR), partial least square regression (PLSR), least absolute shrinkage and selection operator regression (LassoR), and ridge regression (RidgeR). Two ranges of wavebands (4000~400 cm-1 and 3017~2823 cm-1/1805~1734 cm-1) were also used in the above analysis. The prediction accuracy was evaluated using a 10-fold cross validation procedure, with the ratio of the training set and the test set as 3:1, where the determination coefficient (R2) and residual predictive deviation (RPD) were used for evaluations. The results showed that 17 out of 31 milk fatty acids were accurately predicted using MIRS, with RPD values higher than 2 and R2 values higher than 0.75. In addition, 16 out of 31 fatty acids were accurately predicted by RFR, indicating that the ensemble learning model potentially resulted in a higher prediction accuracy. Meanwhile, DER1, DER2 and SG pre-processing algorithms led to high prediction accuracy for most fatty acids. In summary, these results imply that the application of MIRS to predict the fatty acid contents of milk is feasible." @default.
• W4313889927 created "2023-01-10" @default.
• W4313889927 creator A5003673520 @default.
• W4313889927 creator A5004794322 @default.
• W4313889927 creator A5011599984 @default.
• W4313889927 creator A5021293751 @default.
• W4313889927 creator A5023364371 @default.
• W4313889927 creator A5023419190 @default.
• W4313889927 creator A5030691366 @default.
• W4313889927 creator A5041891627 @default.
• W4313889927 creator A5044149277 @default.
• W4313889927 creator A5047285212 @default.
• W4313889927 creator A5053447705 @default.
• W4313889927 creator A5067827761 @default.
• W4313889927 creator A5073090975 @default.
• W4313889927 creator A5087822498 @default.
• W4313889927 date "2023-01-09" @default.
• W4313889927 modified "2023-10-15" @default.
• W4313889927 title "Predictions of Milk Fatty Acid Contents by Mid-Infrared Spectroscopy in Chinese Holstein Cows" @default.
• W4313889927 cites W1414586245 @default.
• W4313889927 cites W1967791032 @default.
• W4313889927 cites W1975522965 @default.
• W4313889927 cites W2001036435 @default.
• W4313889927 cites W2006402323 @default.
• W4313889927 cites W2038242845 @default.
• W4313889927 cites W2054091689 @default.
• W4313889927 cites W2085165105 @default.
• W4313889927 cites W2101603862 @default.
• W4313889927 cites W2104163499 @default.
• W4313889927 cites W2118051155 @default.
• W4313889927 cites W2131866307 @default.
• W4313889927 cites W2148370581 @default.
• W4313889927 cites W2150841961 @default.
• W4313889927 cites W2156026072 @default.
• W4313889927 cites W2156567926 @default.
• W4313889927 cites W2326116348 @default.
• W4313889927 cites W2508737210 @default.
• W4313889927 cites W2606047366 @default.
• W4313889927 cites W2788373759 @default.
• W4313889927 cites W2941503106 @default.
• W4313889927 cites W2980456607 @default.
• W4313889927 cites W3000234984 @default.
• W4313889927 cites W3019328443 @default.
• W4313889927 cites W3024533587 @default.
• W4313889927 cites W3034371696 @default.
• W4313889927 cites W3036266207 @default.
• W4313889927 cites W3037051586 @default.
• W4313889927 cites W3047071846 @default.
• W4313889927 cites W3142643366 @default.
• W4313889927 cites W3162705563 @default.
• W4313889927 cites W3163421532 @default.
• W4313889927 cites W3177823658 @default.
• W4313889927 cites W3186485493 @default.
• W4313889927 cites W3216437710 @default.
• W4313889927 doi "https://doi.org/10.3390/molecules28020666" @default.
• W4313889927 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36677723" @default.
• W4313889927 hasPublicationYear "2023" @default.
• W4313889927 type Work @default.
• W4313889927 citedByCount "3" @default.
• W4313889927 countsByYear W43138899272023 @default.
• W4313889927 crossrefType "journal-article" @default.
• W4313889927 hasAuthorship W4313889927A5003673520 @default.
• W4313889927 hasAuthorship W4313889927A5004794322 @default.
• W4313889927 hasAuthorship W4313889927A5011599984 @default.
• W4313889927 hasAuthorship W4313889927A5021293751 @default.
• W4313889927 hasAuthorship W4313889927A5023364371 @default.
• W4313889927 hasAuthorship W4313889927A5023419190 @default.
• W4313889927 hasAuthorship W4313889927A5030691366 @default.
• W4313889927 hasAuthorship W4313889927A5041891627 @default.
• W4313889927 hasAuthorship W4313889927A5044149277 @default.
• W4313889927 hasAuthorship W4313889927A5047285212 @default.
• W4313889927 hasAuthorship W4313889927A5053447705 @default.
• W4313889927 hasAuthorship W4313889927A5067827761 @default.
• W4313889927 hasAuthorship W4313889927A5073090975 @default.
• W4313889927 hasAuthorship W4313889927A5087822498 @default.
• W4313889927 hasBestOaLocation W43138899271 @default.
• W4313889927 hasConcept C105795698 @default.
• W4313889927 hasConcept C128990827 @default.
• W4313889927 hasConcept C140793950 @default.
• W4313889927 hasConcept C185592680 @default.
• W4313889927 hasConcept C22354355 @default.
• W4313889927 hasConcept C27181475 @default.
• W4313889927 hasConcept C2776977481 @default.
• W4313889927 hasConcept C31903555 @default.
• W4313889927 hasConcept C33923547 @default.
• W4313889927 hasConcept C48921125 @default.
• W4313889927 hasConcept C543025807 @default.
• W4313889927 hasConcept C55493867 @default.
• W4313889927 hasConcept C86803240 @default.
• W4313889927 hasConceptScore W4313889927C105795698 @default.
• W4313889927 hasConceptScore W4313889927C128990827 @default.
• W4313889927 hasConceptScore W4313889927C140793950 @default.
• W4313889927 hasConceptScore W4313889927C185592680 @default.
• W4313889927 hasConceptScore W4313889927C22354355 @default.
• W4313889927 hasConceptScore W4313889927C27181475 @default.
• W4313889927 hasConceptScore W4313889927C2776977481 @default.
• W4313889927 hasConceptScore W4313889927C31903555 @default.
• W4313889927 hasConceptScore W4313889927C33923547 @default.

• next