Seeding Practices and Cultivar Maturity Effects on Simulated Dryland Grain Sorghum Yield

ett, 1999), planted early and at low populations; thus, relying on the sorghum hybrid to adapt to the growing Typical planting recommendations for dryland grain sorghum [Sorconditions by tillering. Research by Jones and Johnson ghum bicolor (L.) Moench] in the southern High Plains are to delay (1991, 1997) demonstrated that the optimum planting date, until soil water is adequate for crop establishment, but no population population, variety, and row spacing were interdepenor cultivar maturity class are specified. Our objectives were to use the SORKAM simulation model, long-term (1958–1998) weather records dent. That is, late maturing varieties performed best at Bushland, TX, and known Pullman soil (fine, mixed, superactive, when planted early and at lower populations; but, when thermic Torrertic Paleustolls) properties to identify an optimum plantsoil water delayed planting, early maturing varieties ing date, population, row spacing, and cultivar maturity combination planted at high populations in narrow rows increased to maximize dryland grain sorghum yield. We simulated sorghum grain yield. Furthermore, annual variability in growing grain yields for combinations of planting dates (15 May, 5 June, and season conditions also greatly limits application of field 25 June), populations (3, 6, and 12 plants m 2), row spacings (0.38 and tests to identify optimum planting date, population, cul0.76 m), and cultivar maturity class (early, medium, and late). SORtivar maturity, and row spacing combinations. KAM consistently (r 2 0.69, RMSE 792 kg ha 1) simulated grain Weather variability at Bushland, TX, for example, yields that averaged about 5% more than measured values and corgrowing season duration that ranges from 144 to 220 d rectly simulated row width and population effects on yield. Simulated grain yields increased with narrow row-spacing 9%, independent of around a 180-d mean, may easily bias short duration planting date or cultivar. Increasing plant population significantly trials comparing planting date or cultivar maturity efdecreased panicle seed number, seed mass, and plant tillers; however, fects on grain yield. Similarly, highly variable precipitathe simulated grain yield was unchanged (3996–4106 kg ha 1) by plant tion that ranges from 89 to 580 mm around a 335-mm populations. Mean simulated grain yields were greatest for the 5 June mean complicates evaluation of cultural practices in planting dates with early and medium maturity cultivars that avoided semiarid regions. One method to include this climatic late summer heat or water deficit stresses and matured before freezing variability and expand the basis for comparing cultural weather. Our results show early or medium maturity cultivars, planted practices used in producing grain sorghum is using com5 June, in 0.38-m row widths, using 3 or 6 plants m 2, achieve the puter models to simulate crop growth and yields under greatest dryland grain yield on a southern High Plains clay loam soil. recorded weather conditions. The grain sorghum computer simulation model SORKAM (Rosenthal et al., 1989) offers a standardized and economical means to G sorghum [Sorghum bicolor (L.) Moench] is compare multiple cropping practice combinations. Rowell adapted to and widely grown on the southern senthal and Gerik (1990) used SORKAM to compare Great Plains. Dryland grain sorghum yields at the the effects of cultivar maturity, planting date, and popuUSDA-ARS Conservation and Production Research lation on sorghum grain yield at eight Texas locations Laboratory, Bushland, TX, have increased 139% from from Amarillo to Weslaco. The uniform planting popu1600 to 3800 kg ha 1 during the years 1956 to 1997 (Unlations and dates they used were not appropriate for all ger and Baumhardt, 1999). These grain yield increments locations, but applying the model in this way did identify were attributed to improved hybrids and management potentially successful management practices. This appractices that utilize residue to conserve soil water; howproach was also used in Kansas to identify criteria for ever, no optimum combination of planting date and replanting sorghum injured by storms after the normal population has been determined for the range of cultivar or optimum planting date (Heiniger et al., 1997b). Simimaturity classes grown in this region. For example, the larly, SORKAM may be used to identify potentially optop dryland grain yields recognized in 2003 by the Natimum planting date, population, and row spacing comtional Grain Sorghum Producers were from fields sepabinations that maximize grain yield of select cultivars rated by a distance of 150 km but managed very difgrown under dryland conditions on the southern Great ferently, i.e., planted during late May to early June at Plains. populations ranging from 4.5 to 15.8 seed m 2. One To meet this goal, our study objective was, first, to Oklahoma producer, featured in a popular article (Hackvalidate SORKAM yield simulations by comparing measured grain sorghum yield with simulated yields for seR.L. Baumhardt and J.A. Tolk, USDA-ARS, Conservation and Prolected years where the measured initial soil water conduction Research Lab., P.O. Drawer 10, Bushland, TX 79012-0010; tent, known planting conditions, and corresponding and S.R. Winter (retired), Texas Agric. Exp. Stn., 2300 Experiment weather data were available. We subsequently simulated Station Rd., Bushland, TX 79012. Received 30 Mar. 2004. Agronomic growth and grain yield of early, medium, and late maturModeling. *Corresponding author ([email protected]). Published in Agron. J. 97:935–942 (2005). doi:10.2134/agronj2004.0087 Abbreviations: CM, cultivar maturity; D, planting date; HI, harvest index (kg kg 1); P, plant population; RW, row width; SM, seed mass © American Society of Agronomy 677 S. Segoe Rd., Madison, WI 53711 USA (mg seed 1). 935 Published online May 13, 2005