Determination of the physico-chemical attributes of plant cell walls, such as lignin content and composition, is of paramount importance in germplasm screening and for evaluating the results of plant breeding and genetic engineering. There are escalating needs for analyses to be robust, reproducible, accurate, and efficient. We have recently modified an established protocol for discrimination of lignin monomers, thioacidolysis, with the goal of increasing sample throughput while maintaining accuracy and reducing equipment load and consumption of reagents. Numerous methodological changes related to volume scaling, selection of the processing vessel, and sample handling were addressed. The revised protocol permitted rapid processing of some 50 or more samples per person per day. A direct comparison between methods using hybrid poplar (Populus alba × tremula) wood samples, resulted in quantities of p-hydroxyphenyl (H), guaiacyl (G), and syringyl (S) lignin monomers that were equivalent to those derived from the original protocol. The revised methodology was then applied to quickly generate phenotypic trait data from 267 hybrid poplar trees (including wild type and eight C4H::F5H transgenic lines), for the development of a near-infrared-based model for predicting the proportion of lignin monomers across a broad phenotypic range of S:G. The resulting partial least squares regression model performed well under full cross-validation, giving strong, linear relationships between actual and predicted monomer proportions, and very high predictive accuracy for the predominant G and S monomers. This research brings considerable refinement to the thioacidolysis procedure, and establishes a method for rapidly and accurately quantifying cell-wall lignin composition that could effectively be employed in routine phenotypic screening platforms.