Abstract
Nursery growers develop container substrate blends based on factors such as cost, availability of substrate components, and the physical and chemical properties of the blends. Comparative examination of potential substrate blends typically involves comparison of measured values one variable at a time; however, multivariate methods are available that can allow simultaneous consideration of all variables. In this study, 127 container substrate blends were prepared, each blend containing two to four of 11 individual substrate components with at least one inorganic component (soil, sand, soil + sand, soil + perlite) and at least one organic component (coir, peatmoss, compost, pine bark, cedar bark, redwood shavings, fine-grade coconut husk chips, and medium-grade coconut husk chips). One blend containing only soil and perlite was an exception. Mean values for air space, container capacity, and bulk density were determined using five samples of each blend in #1 (2.84 L) containers. Among the 127 blends, air space ranged from 5.1% to 40.4% (by volume) and container capacity ranged from 24.8% to 59.4% (by volume). Bulk density among the blends ranged from 0.35 g·cm−3 to 1.00 g·cm−3 with bulk densities below and above ≈0.55 g·cm−3 represented almost exclusively by blends with and without perlite, respectively. Principal components analysis and hierarchical cluster analysis (Ward's method) were used to group the blends into eight groups based on the three physical property variables with each group distinguishable from all other groups based on simultaneous consideration of the three variables. In this study, we demonstrate that exploratory multivariate statistical techniques can be used to create groups of substrate blends, thus providing information to assist nursery growers in identifying and comparing substrate blends with similar or dissimilar physical properties among blends containing similar or different inorganic and organic components and proportions of those components.
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