Seed Yield Prediction Models of Four Common Moist-Soil Plant Species in Texas

Texas Journal of Agriculture and Natural Resources

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Title Seed Yield Prediction Models of Four Common Moist-Soil Plant Species in Texas
Creator Collins, Daniel P.
Conway, Warren C.
Mason, Corey D.
Gunnels, Jeffrey W.
Subject barnyard grass, east-central Texas, jungle rice, moist-soil plants, moist-soil wetlands, rice, seed yield, wild millet
Description Seed production by moist-soil plant species often varies within and among managed wetlands and on larger landscapes. Quantifying seed production of moist-soil plants can be used to evaluate wetland management strategies and estimate wetland energetic carrying capacity, specifically for waterfowl.  In the past, direct estimation techniques were used, but due to excessive personnel and time costs, other indirect methods have been developed. Because indirect seed yield models do not exist for moist-soil plant species in east-central or coastal Texas, we developed direct and indirect methods to model seed production on regional managed wetlands.  In September 2004 and 2005, we collected Echinochloa crusgalli (barnyard grass), E. walterii (wild millet), E. colona (jungle rice), and Oryza sativa (cultivated rice) for phytomorphological measurements and seed yield modeling.  Initial simple linear and point of origin regression analyses demonstrate strong relationships (P < 0.001) among phytomorphological and dot grid methods in predicting seed production for all four species.  These models should help regional wetland managers evaluate moist-soil management success and create models for seed production for other moist-soil plants in this region.
Publisher Agricultural Consortium of Texas
Contributor Texas Parks and Wildlife Department Statewide Grant T-8-1, Arthur Temple College of Forestry and Agriculture (MacIntire-Stennis) at Stephen F. Austin State Universityl
Date 2018-03-06
Type info:eu-repo/semantics/article
Peer-reviewed Article
Format application/pdf
Source Texas Journal of Agriculture and Natural Resources; Vol 30 (2017); 78-86
Language eng
Rights Copyright (c) 2018 Texas Journal of Agriculture and Natural Resources

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