Abstract: A method for predicting a trait of interest in an agricultural sample comprises (a) obtaining a set of input data from: (i) at least one agronomic property; and (ii) at least one of a chemical property and physical property; (b) inputting the data into a processor containing at least one algorithm wherein the processor performs correlations of the input data with the trait of interest; and (c) outputting a predicted efficacy for the trait of interest. A computer-aided system comprises: (a) a computer readable medium including computer-executable instructions configured for estimating a trait of interest in an agricultural sample; (b) input data from: (i) at least one agronomic property; and (ii) at least one of a chemical property and physical property; and (c) an algorithm capable of correlating the data with the trait of interest; wherein the system outputs a predicted efficacy for the trait of interest. The trait of interest can include ethanol yield and/or digestibility.

Abstract: A method of predicting a trait of interest from a plant by measuring the degree of starch-protein association in the plant is provided. The degree of starch-protein association can be determined by identifying either chemical properties or physical properties, or both chemical and physical properties of plant cells. In a particular embodiment, the degree of starch-protein association is determined by identifying the protein composition of the plant.

Abstract: A method for the high throughput screening of fatty acid characteristics in seeds is provided. The method comprises feeding seeds individually to a sampling station; removing a sample from the seed in the sampling station; conveying the sample to a compartment in a sample tray; converting extracted oil from the sample in the sample tray to form a mixture of fatty acid methyl esters; and analyzing the mixture of fatty acid methyl esters from the sample to determine the fatty acid profile of the corresponding seed.