• Authors:
    • Drinkwater, L. E.
    • Schipanski, M. E.
  • Source: Nutrient Cycling in Agroecosystems
  • Volume: 90
  • Issue: 1
  • Year: 2011
  • Summary: The incorporation of legume cover crops into annual grain rotations remains limited, despite extensive evidence that they can reduce negative environmental impacts of agroecosystems while maintaining crop yields. Diversified grain rotations that include a winter cereal have a unique niche for interseeding cover crops. To understand how management-driven soil fertility differences and inter-seeding with grains influenced red clover (Trifolium pratense) N(2) fixation, we estimated biological N(2) fixation (BNF) in 2006 and 2007, using the (15)N natural abundance method across 15 farm fields characterized based on the reliance on BNF derived N inputs as a fraction of total N inputs. Plant treatments included winter grain with and without interseeded red clover, monoculture clover, monoculture orchardgrass (Dactylis glomerata), and clover-orchardgrass mixtures. Fields with a history of legume-based management had larger labile soil nitrogen pools and lower soil P levels. Orchardgrass biomass was positively correlated with the management-induced N fertility gradient, but we did not detect any relationship between soil N availability and clover N(2) fixation. Interseeding clover with a winter cereal did not alter winter grain yield, however, clover production was lower during the establishment year when interseeded with taller winter grain varieties, most likely due to competition for light. Interseeding clover increased the % N from fixation relative to the monoculture clover (72% vs. 63%, respectively) and the average total N(2) fixed at the end of the first growing season (57 vs. 47 kg N ha(-1), respectively). Similar principles could be applied to develop more cash crop-cover crop complementary pairings that provide both an annual grain harvest and legume cover crop benefits.
  • Authors:
    • Hart, C.
    • Gassman, P. W.
    • Kurkalova, L.
    • Secchi, S.
  • Source: Biomass and Bioenergy
  • Volume: 35
  • Issue: 6
  • Year: 2011
  • Summary: This study looks at the land use impact of the biofuels expansion on both the intensive and extensive margin, and its environmental consequences. We link economic, geographical and environmental models by using spatially explicit common units of analysis and use remote sensing crop cover maps and digitized soils data as inputs. Land use changes are predicted via economic analysis of crop rotation choice and tillage under alternative crop prices, and the Environmental Policy Integrated Climate (EPIC) model is used to predict corresponding environmental impacts. The study focuses on Iowa, which is the leading biofuels hotspot in the U.S. due to intensive corn production and the high concentration of ethanol plants that comprise 28% of total U.S. production. We consider the impact of the biofuels industry both on current cropland and on land in the Conservation Reserve Program (CRP), a land set-aside program. We find that substantial shifts in rotations favoring continuous corn rotations are likely if high corn prices are sustained. This is consistent with larger scale analyses which show a shift of the current soybean production out of the Corn Belt. We find that sediment losses increase substantially on the intensive margin, while nitrogen losses increase less. Returning CRP land into production has a vastly disproportionate environmental impact, as non-cropped land shows much higher negative marginal environmental effects when brought back to row crop production. This illustrates the importance of differentiating between the intensive and extensive margin when assessing the expansion of biofuel production. (C) 2010 Elsevier Ltd. All rights reserved.
  • Authors:
    • Fahandezh-Saadi, S.
    • Sepaskhah, A. R.
    • Zand-Parsa, S.
  • Source: Agricultural Water Management
  • Volume: 99
  • Issue: 1
  • Year: 2011
  • Summary: Simulation of crop yield allows better planning and efficient management under different environmental inputs such as water and nitrogen application. However, most of the models are complicated and difficult to understand. Furthermore, input data are not readily available. The objectives of this investigation were to use logistic equation to quantify the influence of seasonal water and nitrogen application on maize biomass accumulation and grain yield and to develop empirical models for prediction of maize biomass and grain yield. Logistic equations were fitted to dray matter (DM) yield at different times in the growing season at different irrigation water and nitrogen levels. The parameters of the logistic equations were then fitted to irrigation water and nitrogen as empirical functions. Further, the harvest index (HI) was related to the applied water and nitrogen as another empirical model. The empirical logistic models were used to estimate the DM and grain yield based on data from another experiment in the same area. Results indicated that the empirical models predicted the DM yield during the growing season with an acceptable accuracy, but dry matter (DM) prediction at harvest was very good. The grain yield also was predicted with a very good accuracy. It is concluded that logistic equation along with the presented empirical models for prediction of constants in logistic equation and HI are appropriate for accurate prediction of DM and grain yield of maize at the study region.
  • Authors:
    • Dobermann, A.
    • Weiss, A.
    • Cassman, K. G.
    • Bastidas, A. M.
    • Setiyono, T. D.
    • Specht, J. E.
  • Source: Agronomy Journal
  • Volume: 103
  • Issue: 4
  • Year: 2011
  • Summary: At any given time, the leaf area index (LAI) of a soybean [Glycine max (L.) Merr.] crop consists of the summed contributions of each trifoliolate leaf present at each main stem node and on branches. No data are available on nodal LAI distributions in modern indeterminate (IN) or semi-determinate (SD) cultivars grown in irrigated, early-planted, high-yield production systems. The impact of stem termination type and row spacing on that distribution was investigated in such environments at Lincoln, NE in 2003, 2004, and 2005. Trifoliolate LAI at each stem node followed a temporal pattern of rapid increase (after leaf initiation) to a peak before declining due to senescence-driven leaf abscission, thus emulating, on a shorter time-scale, the canopy LAI pattern. The post-peak decline in nodal LAI was rapid in nodes initiated prebloom (i.e., nearly 100% abscission before seed-fill), but was gradual in nodes initiated after pod initiation (i.e., little abscission before plant maturity). Nodal LAI peaked at the eighth node of the IN cultivar, but rapid leaf expansion at preflowering nodes of the SD cultivar led to a broad peak spanning the fifth to eighth node. Simulation of the Beer-Lambert law of light attenuation in both canopies revealed that light penetration was deeper in the IN canopy than in the SD canopy. Although higher plant density suppressed branching (and thus branch leaf area) in the SD cultivar, this was not observed in the IN cultivar. These findings suggested that nodal LAI development can be used to mechanistically model canopy LAI.
  • Authors:
    • Kabenge, I.
    • Irmak, S.
    • Sharma, V.
    • Kilic, A.
  • Source: Transactions of the ASABE
  • Volume: 54
  • Issue: 3
  • Year: 2011
  • Summary: Understanding the relationship between the spatial distribution of precipitation and crop yields on large scales (i.e., county, state, regional) while accounting for the spatial non-stationarity can help managers to better evaluate the long-term trends in agricultural productivity to make better assessments in food security, policy decisions, resource assessments, land and water resources enhancement, and management decisions. A relatively new technique, geographically weighted regression (GWR), has the ability to account for spatial non-stationarity with space. While its application is growing in other scientific disciplines (i.e., social sciences), the application of this new technique in agricultural settings has not been practiced. The geographic information system (GIS), along with two different statistical techniques [GWR and conventional ordinary least square regression (OLS)], was utilized to analyze the relationships between various precipitation categories and irrigated and rainfed maize and soybean yields for all 93 counties in Nebraska from 1996 to 2008. Precipitation was spatially interpolated in ArcGIS using a spline interpolation technique with zonal statistics. Both measured and GWR- and OLS-predicted yields were correlated to spatially interpolated annual (January 1 to December 31), seasonal (May 1 to September 30), and monthly (May, June, July, August, and September) precipitation for each county. Statewide average annual precipitation in Nebraska from 1996 to 2008 was 564 mm, with a maximum of 762 mm and minimum of 300 mm. Mean precipitation decreased gradually from May to September during the growing season. County average yields followed the same temporal trends as precipitation. When the OLS regression model was used, there was a general trend of linear correlation between observed yield and long-term average mean annual total precipitation with a varying coefficient of determination (R 2). For rainfed crops, 67% of the variability in mean yield was explained by the mean annual precipitation. About 23% and 17% of the variability in mean yield was explained by mean annual precipitation for irrigated maize and soybean, respectively. However, the performance of the GWR technique in predicting the yields from spatially interpolated precipitation for irrigated and rainfed maize and soybean was significantly better than the performance of the OLS model. For both rainfed maize and soybean, 77% to 80% of the variation in yield was explained by the mean annual precipitation alone. For irrigated crops, 42% of the variation in the yield was explained by the mean annual precipitation. For rainfed crops, there was a strong correlation between seasonal precipitation and yield, with R 2 values of 0.73 and 0.76 for maize and soybean, respectively. The mean annual total precipitation was a better predictor of rainfed maize yield than rainfed soybean yield. On a statewide average, July precipitation as a predictor had the greatest correlation with yields of both maize and soybean. June, July, and August precipitation had greater impact on maize yield than on soybean under rainfed conditions due to more sensitivity of maize to water stress than soybean. For irrigated yields, July precipitation had more impact on soybean yield than on maize. The performance of the GWR technique was superior to the OLS model in analyzing the relationship between yield and precipitation. The superiority of the GWR technique to OLS is mainly due to its ability to account for the impact of spatial non-stationarity on the precipitation vs. yield relationships.
  • Authors:
    • Jaynes, D. B.
    • Malone, R. W.
    • Singer, J. W.
    • Ma, L.
  • Source: Agricultural Water Management
  • Volume: 98
  • Issue: 10
  • Year: 2011
  • Summary: Studies quantifying winter annual cover crop effects on water quality are mostly limited to short-term studies at the plot scale. Long-term studies scaling-up water quality effects of cover crops to the watershed scale provide more integrated spatial responses from the landscape. The objective of this research was to quantify N loads from artificial subsurface drainage (tile drains) in a subbasin of the Walnut Creek, Iowa (Story county) watershed using the hybrid RZWQ-DSSAT model for a maize (Zen mays L.)soybean [Glycine max (L.) Merr.] and maize-maize-soybean rotations in all phases with and without a winter wheat (Triticum aestivum L.) cover crop during a 25-year period from 1981 to 2005. Simulated cover crop dry matter (DM) and N uptake averaged 1854 and 36 kgha(-1) in the spring in the maize-soybean phase of the 2-year rotation and 1895 and 36 kg ha(-1) in the soybean-maize phase during 1981-2005. In the 3-year rotation, cover crop DM and N uptake averaged 2047 and 44 kg ha(-1) in the maize-maize-soybean phase, 2039 and 43 kg ha(-1) in the soybean-maize-maize phase. and 1963 and 43 kg ha(-1) in the maize-soybean-maize phase during the same period. Annual N loads to tile drains averaged 29 kg ha(-1) in the maize-soybean phase and 25 kg ha(-1) in the soybean-maize phase compared to 21 and 20 kg ha(-1) in the same phases with a cover crop. In the 3-year rotation. annual N loads averaged 46, 43, and 45 kg ha(-1) in each phase of the rotation without a cover crop and 37, 35, and 35 kg ha(-1) with a cover crop. These results indicate using a winter annual cover crop can reduce annual N loads to tile drains 20-28% in the 2-year rotation and 19-22% in the 3-year rotation at the watershed subbasin scale over a 25-year period. Published by Elsevier B.V.
  • Authors:
    • Jain, K.
    • Kudrat, M.
    • Singh, N. J.
    • Pandey, K.
  • Source: International Journal of Remote Sensing
  • Volume: 32
  • Issue: 16
  • Year: 2011
  • Summary: The cropping pattern (rotation) of a region depends on the soil, water availability, economic conditions and climatic factors. Remote sensing is one of the effective tools that can provide precise and up-to-date information on the performance of agricultural systems. Four seasons data from the Indian Remote Sensing Satellite (IRS)-P6 Advanced Wide Field Sensor (AWiFS) were used for the generation of the cropping pattern of Uttar Pradesh by geographic information system (GIS)-aided integration of digitally classified crop and land use inventories of the kharif, rabi and zaid crop seasons. Twelve different cropping patterns were delineated and mapped in the Indo-Gangetic plain of Uttar Pradesh. The forests covered about 6.32% of the total geographical area. The net cropped area was 20 282 159.46 ha (84.18% of the total geographical area) and the non-agricultural area observed was 3 437 376.00 ha (14.26% of the total geographical area). Rice was the single most dominant crop of the state, occupying about 32.94% of the total geographical area during the kharif season. Maize/jowar was the second major cereal crop, accounting for 13.77% of the total geographical area of the state. The major crops grown during the rabi season were wheat and pulses/oilseed, covering areas of 7 979 267.71 ha (33.12%) and 5 974 742.58 ha (24.80%), respectively. Rice-wheat, sugarcane and rice-pulses were the major cropping patterns, occupying about 3 958 739.85 ha (16.43%), 3 609 939.74 ha (14.98%) and 2 511 298.24 ha (10.42%), respectively. The areas under pulses/oilseed were significantly higher in the rabi season. Sugarcane-wheat and pulses shared an almost equal area (6.49%). The maize/jowar-wheat cropping pattern occupied 6.14% of the total geographical area of the state. Single cropping patterns (i.e. rice-fallow, fallow-pulses, fallow-wheat, maize-fallow and sugarcane-fallow) were minor, occupying 6.08, 2.94, 4.06, 2.69 and 2.51%, respectively. Waste land, including gulley, salt-affected, waterlogged and rock land, accounted for 3.80% of the total geographical area. The results of this study indicate that temporal IRS-P6 (AWiFS) data are very useful for studying spatial cropping patterns. The values of the Multiple Cropping Index (MCI) and the Cultivated Land Utilization Index (CLUI) show that the study area has a high cropping intensity.
  • Authors:
    • Armstrong, S. D.
    • Hernandez-Ramirez, G.
    • Smith, D. R.
    • Bucholtz, D. L.
    • Stott, D. E.
  • Source: Soil Science Society of America Journal
  • Volume: 75
  • Issue: 3
  • Year: 2011
  • Summary: Recent efforts have attempted to establish emission estimates for greenhouse gas (GHGs) from agricultural soils in the United States. This research project was conducted to assess the influence of cropping system management on non-CO(2) GHG emissions from an eastern Corn Belt Alfisol. Corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] rotation plots were established, as were plots in continuous management of native grasses or sorghum-sudan-grass [Sorghum bicolor (L.) Moench nothossp. drummondii (Steud.) de Wet ex Davidse]. Greenhouse gas fluxes were monitored throughout each growing season from 2004 through 2007. Fluxes of N(2)O were significantly correlated with soil temperature (P
  • Authors:
    • Hyde, J.
    • Mortensen, D. A.
    • Barbercheck, M. E.
    • Smith, R. G.
    • Hulting, A. G.
  • Source: Agronomy Journal
  • Volume: 103
  • Issue: 1
  • Year: 2011
  • Summary: In the mid-Atlantic region, the demand for organic dairy has provided incentives for farmers to transition their land to organic feed grain production. At the same time, interest in minimum-tillage organic production is growing. Two field experiments were conducted to assess the effects of a first year cover crop and tillage system on weed populations, cash crop yield, and net returns over the 3-yr transition period in a cover crop-soybean (Glycine max (L.) Merr.)-corn (Zea mays L.) feed grain rotation. The cover crop treatments were rye (Secale cereale L.)-hairy vetch (Vicia villosa Roth) (hereaft er RYE) and timothy (Phleum pratense L.)-red clover (Trifolium pratense L.) (hereaft er TIM). Tillage system treatments were moldboard plow (full tillage, FT) and chisel plow (minimum tillage, MT). Across both experiments, soybean yields ranged from 1190 to 3721 kg ha(-1). Corn grain yields were affected by tillage in the first experiment only, and were 59% higher in FT (9370 kg ha(-1)) compared to MT (5906 kg ha(-1)). Weed abundance was primarily affected by tillage, with densities in corn being 244% higher in MT compared to FT. Cumulative net returns in the first experiment were profit-generating in systems where TIM was the initial cover crop (mean = U.S. $ 317 ha(-1)). Mean cumulative net returns were positive in three of the four treatment combinations in the second experiment (U.S. $ 74-299 ha(-1)). Improved strategies for minimizing the costs associated with fertilization and management of weeds in minimal tillage will be necessary to improve the profitability and sustainability of reduced-tillage organic systems.
  • Authors:
    • Naranjani, L.
    • Shahrajabian, M. H.
    • Soleymani, A.
  • Source: Journal of Food, Agriculture and Environment (JFAE)
  • Volume: 9
  • Issue: 1
  • Year: 2011
  • Summary: Population growth and the consequent pressure on land resources and frequent crop failures have led to greater land use as well as intercropping systems. In order to investigate the changes of ash percentage, important elements and solar radiation absorption of three cultivars of berseem clover as cover crops intercropped with forage corn in different levels of nitrogen starter fertilizer, an experiment was conducted in 2010, at Research Farm, Faculty of Agriculture, Islamic Azad University, Khorasgan Branch (Isfahan). A factorial layout within randomized complete block design with 3 replications was used. Cultivars were Karaj, Sacromont and Multicut, and nitrogen levels included 0, 40 and 60 kg/ha. The nitrogen fertilizer was provided from urea source (46% pure N). Cultivar had significant effect on ash percentage and solar radiation absorption. The effect of nitrogen also was significant on ash percentage, Fe content, Mn content and solar radiation absorption. Ash percentage, Fe content, solar radiation absorption and light transmission were significantly influenced by interaction between cultivar and nitrogen. The highest ash percentage, Fe and Zn content were related to Sacromont. The maximum Mn content, Cu content and light transmission were obtained by Multicut. The maximum solar radiation absorption was related to Karaj. The nutritive value of berseem clover was influenced by changes in different levels of nitrogen starter fertilizer. The highest ash percentage, Mn content, Cu content and light transmission was obtained by application of 40 kg N/ha. The maximum Zn content was related to application of 60 kg N/ha. Control treatment had the maximum Fe content and solar radiation absorption.