Optimum molecular descriptors based on 89 machine learning methods for predicting the recovery rate of pesticides in crops by GC-MS

Postery | 2020 | Agilent TechnologiesInstrumentace
GC/MSD, Software
Zaměření
Potraviny a zemědělství
Výrobce
Agilent Technologies
PDF verze ke stažení a čtení
 

Podobná PDF

Comprehensive machine learning prediction of GC/MS pesticide recovery based on the molecular fingerprinting for food QA/QC
Classifying the pesticides in foods between GC-amenable and LC-amenable using the prediction model with molecular descriptors
Agilent ASMS 2020 Posters Book
Agilent ASMS 2020 Posters Book
2020|Agilent Technologies|Postery
Retention time prediction for 653 pesticides on a biphenyl liquid chromatography stationary phase using machine learning