Determination of the quantitative content of chlorophylls in leaves by reflection spectra using the random forest algorithm.

Determining the quantitative content of chlorophylls in plant leaves by their reflection spectra is an important task both in monitoring the state of natural and industrial phytocenoses, and in laboratory studies of normal and pathological processes during plant growth. The use of machine learning methods for these purposes is promising, since these methods allow inferring the relationships between input and output variables (prediction model), and in order to improve the quality of the prediction, a researcher may modify predictors and selects a set of method parameters. Here, we present the results of the implementation and evaluation of the random forest algorithm for predicting the total concentration of chlorophylls a and b from the reflection spectra of plant leaves in the visible and infrared wavelengths.

[Participation of non-specific rat liver microsome oxidases in destruction of Nl-furanidylpyrimidines].

N1-(3'-Butyrolactono)-5-fluorouracil, N1-(2'-furanidyl) 5-trifluoromethyluracil, N1-(2'-furanidyl)-5-fluoracil are split in the rat organism with the formation of free 5-fluorouracil. The destruction of the C--N bonds in the molecule of the N1-(2'-furanidyl)-5-fluoracil takes place in the liver microsomes. This process is strengthened by NADPH and weakened by SKF-525A.