Grazing lands in warm-temperate and subtropical North America have become less diverse. Pastures are typically grass monocultures, while rangelands are generally managed for the grass components. Overstocking, selective herbicides, fire exclusion and heavy rates of nitrogen fertilizer have contributed to near exclusion of native, warm-season legumes. The simplicity of managing grass monocultures, pasture production responses to nitrogen fertilizer and profitability of grass-only systems have limited interest in legume-based approaches. Changing economics and ecological concerns with ecosystem accumulation of industrial inputs contribute to an increasing interest in legumes. Unlike the development of temperate pasture legumes and recent research in the tropics, legumes tolerant of both freezing temperatures and hot weather have received less attention. Poor establishment, limited persistence and potential invasiveness limit currently available introduced species. Native, herbaceous, warm-season legume species occur throughout warm-temperate North America, but little attention has been directed to these plants as potential forage species. Some success with a few native legume species, primarily in the genus Desmanthus, suggests potential for expanded assessment of forage value of the many species available. Current assessments of native legumes, primarily for conservation purposes, provide an opportunity to expand evaluations of these species for pasture and rangeland potential while economics of livestock production and public interest in ecosystem health are supportive. Experiences with legumes of warm-temperate origin in North America, along with results with temperate and tropical pasture legumes globally, provide a starting point for future efforts at incorporating greater legume diversity in pastures and rangelands of subtropical and warm-temperate regions around the world.

been released through public and private breeding programs. Differences among annual ryegrass (Lolium multiflorum Lam.)To date, most studies on annual ryegrass have focused cultivars for weight gain of grazing steers have been reported, even on critical establishment factors, such as sod-suppresthough plot experiments suggest that forage dry matter yield among sion and tillage (Cuomo and Blouin, 1997; Cuomo et cultivars should not be a limiting factor. Likewise, forage nutritive value differences among cultivars have not been assessed. The objec- al., 1999; Lang, 1989). There have been few studies contives of this research were to evaluate differences in cumulative forage ducted to determine animal performance (Hafley, 1996; yield, yield distribution, and nutritive value among 'Gulf', 'Jackson', Hoveland et al., 1991) and these have evaluated a mini-'Marshall', 'Rio', 'Rustmaster', and 'Surrey' annual ryegrass. Plots mal number of cultivars due to the expense of conductwere harvested six times beginning in December at approximate 30-d ing these studies. Recent reports indicate annual ryeintervals during the 1997-1998 and 1998-1999 growing seasons. Nutrigrass cultivar differences for gains by growing cattle tive value measurements included crude protein (CP), neutral deter-(Bransby et al., 1997; Wyatt and Granger, 2001). The gent fiber (NDF), in vitro true digestibility (IVTD), and digestible increased animal gain on Marshall versus Gulf pasture NDF (DNDF). There were no differences among cultivars for cumulahas ranged from 77 to 27% in Alabama (Bransby et al., tive forage yield (P ϭ 0.99). However, for the January harvest, Surrey 1997) and 16% to essentially no difference over 3 yr in and Gulf averaged 1030 (Ϯ65) kg DM ha Ϫ1 , whereas Marshall yielded only 672 (Ϯ79) kg DM ha Ϫ1 . For the March harvest, yields of all Louisiana (Wyatt and Granger, 2001). Gains were simivarieties were similar and averaged 1350 (Ϯ95) kg DM ha Ϫ1 .A tt h e lar for cattle grazing Marshall and Jackson (Wyatt and May harvest, Marshall and Jackson yielded 1232 (Ϯ123) kg DM ha Ϫ1 , Granger, 2001) and for cattle grazing Marshall and Surwhereas Gulf yielded only 929 (Ϯ74) kg DM ha Ϫ1 . Crude protein rey (Hafley, 1996). Animal performance advantages apconcentration differed significantly among harvests with a general pear to be associated with forage mass as suggested decrease from 260 to 120 g CP kg Ϫ1 as the growing season progressed. by plant height differences (Bransby et al., 1997) and Similar declines in nutritive value occurred for NDF, IVTD, and measurements using a rising plate meter (Wyatt and DNDF. Trends in yield distribution and forage quality may indicate Granger, 2001). Possible contributions of nutritive value a need for cultivar specific recommendations based on intended forage differences among annual ryegrass cultivars to differneed and season of use.

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Quantifying pasture composition requires either laborious or subjective approaches. Evaluations of near‐infrared reflectance spectroscopy (NIRS) to determine botanical composition of mixed pasture swards have shown potential. In this study, characterization of botanical composition of pastures comprised primarily of bahiagrass (Paspalum notatum Flugge), aeschynomene (Aeschynomene americana L.) and phasey bean [Macroptilium lathyriodes (L.) Urb.] by NIRS was evaluated. Three approaches (hand‐composited samples, single‐component samples, and actual pasture samples) were compared for equation development. Theoretical potential of NIRS is illustrated by high coefficients of determination (0.98–0.99) and low standard errors (1.4–2.9%) of equations for the above species from hand‐composited samples. Equations developed from the three approaches were evaluated for estimation of the botanical composition of a separate group of pasture samples. Equations developed from hand‐composited samples from a single source of each component were not acceptable for estimating composition of pasture samples despite the excellent calibration statistics. Single‐component samples approached adequate results only for composite total grass and total legume groups, even though the pasture sample composition appeared to be well represented in the calibration sample set. Equations from pasture samples provided useful estimates of sample means, although some individual samples were poorly estimated. Thus, botanical composition of these pastures may be estimated using equations from actual pasture samples, and estimates of total grass and total legume may be obtained from use of single‐component samples, which provides further labor reductions. A comparison of original software and updated software packages CAL, BEST, REG70, and partial least squares principal component regression showed none to be consistently superior.