Method of predicting a performance characteristic of a plant or yeast hydrolysate measured in powder form comprising the steps of: a) providing a training set comprising a plurality of plant or yeast hydrolysate samples, each sample having a predetermined value of a manufacturing parameter of interest, b) irradiating a sample of said training set with light of a plurality of wavelengths in a predetermined range, wherein the predetermined range of wavelengths of light of irradiating a sample of said training set lies within a range of 290 to 550 nm, c) determining at least one measured value indicative of radiation emitted from the sample, d) repeating steps b) and c) for all samples of said training set, e) performing multivariate data analysis of the at least one measured value determined for each of the plurality of samples and corresponding predetermined manufacturing parameters of interest to obtain model parameters correlating the at least one measured value determined for each of the plurality of samples with the corresponding predetermined manufacturing parameters of interest, f) obtaining information correlated to the manufacturing parameter of interest of a new sample different from the samples of said training set from an at least one measured value indicative of radiation emitted from the sample according to step c) after irradiating said sample according to step b) by using those model parameters obtained in step e), g) obtaining predictive information related to the performance characteristic of the new sample by determining whether said manufacturing parameter of interest falls into a predetermined range, wherein steps b) and c) comprise 2D-multiwavelength fluorescence spectroscopy analysis of the plant or yeast hydrolysate. a) providing a training set comprising a plurality of plant or yeast hydrolysate samples, each sample having a predetermined value of a manufacturing parameter of interest, b) irradiating a sample of said training set with light of a plurality of wavelengths in a predetermined range, wherein the predetermined range of wavelengths of light of irradiating a sample of said training set lies within a range of 290 to 550 nm, c) determining at least one measured value indicative of radiation emitted from the sample, d) repeating steps b) and c) for all samples of said training set, e) performing multivariate data analysis of the at least one measured value determined for each of the plurality of samples and corresponding predetermined manufacturing parameters of interest to obtain model parameters correlating the at least one measured value determined for each of the plurality of samples with the corresponding predetermined manufacturing parameters of interest, f) obtaining information correlated to the manufacturing parameter of interest of a new sample different from the samples of said training set from an at least one measured value indicative of radiation emitted from the sample according to step c) after irradiating said sample according to step b) by using those model parameters obtained in step e), g) obtaining predictive information related to the performance characteristic of the new sample by determining whether said manufacturing parameter of interest falls into a predetermined range, <EOS>