NOVELTY - Prediction of compositional characteristics of a corn plant population involves analyzing homogeneous plant mixture sample by near infrared spectrometer and comparing near infrared analyses with wet-test chemistry tested nutritional compositional characteristics. The sample is analyzed by scanning the sample at multiple locations.    USE - For prediction of the compositional characteristics of the corn plant (claimed) useful in silage production and subsequent nutritional and economic benefits.    ADVANTAGE - The method is more accurate than current method since it provides ability to: (a) obtain samples of whole corn plants that are more uniform; (b) obtain samples that are more representative of the population which they are intended to represent; (c) better address the sampling and analytical variation inherent in this type of process through an improved for sample handling, preparation, analysis and real-time cross-checking of analytical results; and (d) use analytical results in such a way that better estimates the economic significance of differences observed relative to animal production applications. The method is less expensive because its greater accuracy reduces the required size and scope of the evaluation process; also the time required to physically process and analyze samples is reduced. The process is faster since the need for certain processing steps is reduced and because greater precision allows more succinct evaluation. Samples are evaluated using a near infrared (NIR) analytical process, which enables the multiple scanning i.e. analysis of a relatively large production of the sample. The process incorporates a real-time comparative evaluation of samples from the same plant that allows for the rapid identification of non-representative samples, the re-sampling of sub samples and their re-analysis. Indirect analytical technologies e.g. NIR offer much greater speeds and much lower costs than typical wet chemistry methods. The data captured through the process is easily translated into information that is of benefit to a decision making process. This final translation of information becomes a powerful tool for those needing to make business decisions relative to the comparative use of corn verities.    DETAILED DESCRIPTION - Prediction of compositional characteristics of a corn plant population involves analyzing homogeneous plant mixture sample by near infrared spectrometer and comparing near infrared analyses with wet-test chemistry tested nutritional compositional characteristics. The sample is analyzed by scanning the sample at multiple locations. Then comparing the analysis with an existing correlation between near infrared analyses and wet-chemistry tested nutritional composition characteristics.