The role of grassland ecosystems as net sinks or sources of greenhouse gases (GHGs) is limited by a paucity of information regarding management impacts on the flux of nitrous oxide (N(2)O) and methane (CH(4)). Furthermore, no long-term evaluation of net global warming potential (GWP) for grassland ecosystems in the northern Great Plains (NGP) of North America has been reported. Given this need, we sought to determine net GWP for three grazing management systems located within the NGP. Grazing management systems included two native vegetation pastures (moderately grazed pasture [MGP], heavily grazed pasture [HGP]) and a heavily grazed crested wheatgrass [Agropyron desertorum (Fisch. ex. Link) Schult.] pasture (CWP) near Mandan, ND. Factors evaluated for their contribution to GWP included (i) CO(2) emissions associated with N fertilizer production and application, (ii) literature-derived estimates of CH(4) production for enteric fermentation, (iii) change in soil organic carbon (SOC) over 44 yr using archived soil samples, and (iv) soil-atmosphere N(2)O and CH(4) fluxes over 3 yr using static chamber methodology. Analysis of SOC indicated all pastures to be significant sinks for SOC, with sequestration rates ranging from 0.39 to 0.46 Mg C ha(-1) yr(-1). All pastures were minor sinks for CH(4) (<2.0 kg CH(4)-C ha(-1) yr(-1)). Greater N inputs within CWP contributed to annual N(2)O emission nearly threefold greater than HGP and MGP. Due to differences in stocking rate, CH(4) production from enteric fermentation was nearly threefold less in MGP than CWP and HGP. When factors contributing to net GWP were summed, HGP and MGP were found to serve as net CO(2equiv.) sinks, while CWP was a net CO(2equiv.) source. Values for GWP and GHG intensity, however, indicated net reductions in GHG emissions can be most effectively achieved through moderate stocking rates on native vegetation in the NGP.

The inclusion of cover crops during fallow (i.e., green fallow) may mitigate greenhouse gas (GHG) emissions from dryland cropping systems. An investigation was conducted to quantify the effects of chemical and green fallow on soil organic C (SOC) and CO2, CH4, and N2O flux within spring wheat (Triticum aestivum L.)–fallow (chemical fallow) and spring wheat–safflower (Carthamus tinctorius L.)–rye (Secale cereale L.) (green fallow) under no‐till management in west‐central North Dakota. Using static chamber methodology, flux measurements were made during 19 mo of the fallow period of each cropping system. Soil samples collected before initiation of flux measurements indicated no difference in SOC in the surface 10 cm between cropping systems. Additionally, differences in gas flux between cropping systems were few. Emission of CO2 was greater under green fallow than chemical fallow during spring thaw until the termination of rye (P = 0.0071). Uptake of atmospheric CH4 was the dominant exchange process during the evaluation period, and was significantly (P = 0.0124) greater under chemical fallow (−2.7 g CH4–C ha−1 d−1) than green fallow (−1.5 g CH4–C ha−1 d−1) following the termination of rye. Cumulative fluxes of CO2, CH4, and N2O did not differ between the chemical‐ and green‐fallow phases during the 19‐mo period (P = 0.1293, 0.2629, and 0.9979, respectively). The results from this evaluation suggest there was no net GHG benefit from incorporating a rye cover crop during the fallow phase of a dryland cropping system under no‐till management.

J. Gross, B.P. Marks and M. Daniels. Cereal Chem. 75, 714-720 (1998).A trained texture profiling panel and an extrusion cell fitted into the TA.XT2 Texture Analyzer were used to quantify textural characteristics of three cooked rice cultivars exhibiting small differences in tlexture. Nine sensory and five instrumental parameters were used to establish predictive models for the sensory characteristics evaluated. Most effectively pred3icted were hardness (R2=@.62) and toothpack (R2=0.70). Partial least square regression techniques gave the following RAP (relative ability of prediction) values: hardness 0.52, cohesiveness of mass 0.60, toothpull 0.73, and toothpack 0.54. These values take into account the accuracy of the sensory methodology and provide a more accurate evaluation of the quality of the predictive models. Poor predictability was related to small textural differences between test samples, and need for better statistical methods applicable to such situations.A. S. Sz.

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