Abstract: Methods are provided for predicting warp of a lumber product at a given condition, such as relative humidity, temperature, moisture content, or the like. Note that this methodology may apply to any of crook, bow, twist, cup, or combinations of these quantities. The method involves measuring an original warp of a first wood product at a known condition; changing the condition of the first wood product to a new condition; measuring a second warp of the first wood product at the new condition; developing a prediction model based on data from the original warp and condition and the second warp; measuring an original warp and condition of the given wood product; and inputting data from the original warp and condition of the given wood product to the prediction model to determine warp at a given condition.

Abstract: The present disclosure includes a wood product package comprising a plurality of wood products having a performance attribute. The performance attribute of the wood products is certified in statistical terms based on a degree to at which at least one of a morphology, microstructure, macrostructure or chemical composition property remains substantially symmetrical about a cross-sectional centroid of each of the wood products. Each of the plurality of wood products have a cross-sectional centroid. The plurality of wood products each have a property that is substantially symmetrical about the cross-sectional centroids. The property is related to morphology, microstructure, macrostructure, and chemical composition. Further aspects of the disclosure are directed towards methods for sorting wood products.

Abstract: A warp stable wood product and methods for detecting the same are provided. The wood product may be sorted based on its morphology, microstructure, macrostructure, and/or chemical composition properties being substantially symmetric relative to at least one or more cross-sectional centroids of the wood product, thereby imparting warp stability.

Abstract: Methods are provided for predicting warp of a lumber product at a given condition, such as relative humidity, temperature, moisture content, or the like. Note that this methodology may apply to any of crook, bow, twist, cup, or combinations of these quantities. The method involves measuring an original warp of a first wood product at a known condition; changing the condition of the first wood product to a new condition; measuring a second warp of the first wood product at the new condition; developing a prediction model based on data from the original warp and condition and the second warp; measuring an original warp and condition of the given wood product; and inputting data from the original warp and condition of the given wood product to the prediction model to determine warp at a given condition.