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Predicting Straw Yield of Hard Red Spring Wheat
Author(s) -
Engel R. E.,
Long D. S.,
Carlson G. R.
Publication year - 2003
Publication title -
agronomy journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.752
H-Index - 131
eISSN - 1435-0645
pISSN - 0002-1962
DOI - 10.2134/agronj2003.1454
Subject(s) - straw , agronomy , cultivar , fertilizer , yield (engineering) , grain yield , mathematics , environmental science , biology , materials science , metallurgy
Accurate estimates of straw production for spring wheat ( Triticum aestivum L.) are important in the Great Plains for conservation planning, nutrient cycling, and fertilizer recommendations. Frequently, these estimates are based on grain yield and the assumption of a constant ratio between straw and grain. This approach may not always be accurate because straw/grain ratios can vary greatly across environments and genotypes. Spring wheat studies were conducted to contrast straw/grain ratios over diverse water and N environments and to determine if plant height and grain protein at maturity, in addition to grain yield, would significantly improve predictions of straw production. A 3‐yr field study consisting of four cultivars, three water regimes, and a wide range of N levels served as a database for this analysis. Straw/grain ratios ranged from 0.91 to 2.37 and were affected by water, N, and cultivar selection. Extended periods of water stress during grain fill and/or vegetative growth and improved N fertility generally resulted in wider ratios. Stability of straw/grain ratios over the diverse environments improved as cultivar height decreased. Straw yield models that considered only grain yield provided a modest fit to the data ( R 2 = 0.66, SE = 701 kg ha −1 ). Prediction models that included terms for plant height and plant N status (straw N or grain protein) in addition to grain yield provided a considerably better fit to the experimental data ( R 2 = 0.88, SE = 425). Observations from validation data sets confirmed that inclusion of plant height (two of two data sets) and grain protein (one of two data sets) improved accuracy of straw yield predictions.