• Authors:
    • Gitelson, A. A.
    • Peng, Y.
  • Source: Remote Sensing of Environment
  • Volume: 117
  • Issue: 440–448
  • Year: 2012
  • Summary: The synoptic quantification of crop gross primary productivity (GPP) is essential for studying carbon budgets in croplands and monitoring crop status. In this study, we applied a recently developed model, which relates crop GPP to a product of total crop chlorophyll content and incoming photosynthetically active radiation, for the remote estimation of GPP in two crop types (maize and soybean) with contrasting canopy architectures and leaf structures. The objective of this study was to evaluate performances of twelve vegetation indices used for detecting different vegetation biophysical characteristics, in estimating GPP of rainfed and irrigated crops over a period from 2001 through 2008. Indices tested in the model exhibited strong and significant relationships with widely variable GPP in each crop (GPP ranged from 0 to 19 gC/m 2/d for soybean and 0 to 35 gC/m 2/d for maize), however, they were species-specific. Only three indices, which use MERIS red edge and NIR spectral bands (i.e. red edge chlorophyll index, MERIS Terrestrial Chlorophyll Index and red edge NDVI), were found to be able to estimate GPP accurately in both crops combined, with root mean square errors (RMSE) below 3.2 gC/m 2/d. It was also shown that two indices, red edge chlorophyll index and red edge NDVI with a red edge band around 720 nm, were non-species-specific and yielded a very accurate estimation of GPP in maize and soybean combined, with RMSEs below 2.9 gC/m 2/d and coefficients of variation below 21%.
  • Authors:
    • Prasuhn, V.
  • Source: Soil & Tillage Research
  • Volume: 120
  • Year: 2012
  • Summary: The positive effects of soil conserving farming methods have mostly been demonstrated using small test plots. The present study is aimed at confirming that they also occur on the catchment scale. The impact of crops and soil tillage practises on the extent of soil erosion was determined in 203 crop fields over 10 years in the Swiss Midlands. Soil erosion totalled 1969 t or 0.75 t ha(-1) yr(-1). Most erosion took place in winter wheat fields (33%), which accounted for 22% of the crop area. Second and third most erosion was observed in potato (26%) and fallow (14%) fields. By far the highest mean soil loss was found for potatoes, at 2.87 t ha(-1) yr(-1). Fallow (1.06 t ha(-1) yr(-1)) and winter wheat (1.05 t ha(-1) yr(-1)) fields were also relatively susceptible to soil erosion. In contrast, values for soil loss below mean were observed for maize (0.44 t ha(-1) yr(-1)), sugar beet (0.27 t ha(-1) yr(-1)), and rape seed (0.39 t ha(-1) yr(-1)). 88% of soil erosion took place on plough tilled land (PT), 9% on non-ploughed land with less than 30% surface residue cover (RT), 1% on mulch-tilled land with more than 30% surface residue cover (MT), and 2% in non-tilled or strip-tilled land with >30% soil cover (NT). At 0.07 and 0.12 t ha(-1) yr(-1), respectively, the mean soil loss in MT and NT fields was more than an order of magnitude lower than that under PT (1.24 t ha(-1) yr(-1)). Field mappings confirmed the positive effects of the soil conserving soil tillage practises. The risk of soil erosion was significantly influenced by crop rotation. The carry-over effects should be taken into account when studying the effects of cropping methods on soil erosion. (C) 2012 Elsevier B.V. All rights reserved.
  • Authors:
    • Zhang, Y. M.
    • Li, X. X.
    • Oenema, O.
    • Hu, C. S.
    • Wang, Y. Y.
    • Qin, S. P.
    • Dong, W. X.
  • Source: Atmospheric Environment
  • Volume: 55
  • Year: 2012
  • Summary: Emissions of nitrous oxide (N 2O) from agricultural soils contribute to global warming and stratospheric ozone depletion. Applications of fertilizer nitrogen (N) increase N 2O emission, but also increase agricultural production. Here, we report on the responses of crop yield, N 2O emission and yield-scaled N 2O emission (N 2O emission per unit N uptake by grain and aboveground biomass) to different N fertilizer rates in a winter wheat-summer corn double-cropping system in the North China Plain. Soil N 2O emission measurements were carried out for two years in a long-term field experiment, under semi-arid conditions with four flood irrigations events per year. Our results indicated that N 2O emissions were linear functions and yield-scaled N 2O emissions were cubic functions of N fertilizer application rate. Yield-scaled N 2O emissions were lowest at application rates of 136 kg N ha -1 yr -1. Using a quadratic-plateau model, it was found that maximal crop yields were achieved at an application rate of 317 kg N ha -1 yr -1, which is 20% less than current practice. This level is suggested to be a compromise between achieving food security and mitigation N 2O emissions.
  • Authors:
    • Portela, S. I.
    • Andriulo, A. E.
    • Restovich, S. B.
  • Source: Field Crops Research
  • Volume: 128
  • Year: 2012
  • Summary: The agricultural system of the Humid Pampas consists of continuous cropping of soybean and maize under no tillage. This system may loose nitrogen (N) through leaching during the early and final stages of summer crops and during fallow. In this study (2005-2011) we evaluated the effect of fall-winter species (rescue grass, ryegrass, oats, barley, vetch, rape seed and forage radish) and a mixture of vetch and oats used as cover crops on water and N dynamics and main crop yield. Above-ground biomass production and N uptake by cover crops ranged from 1.1 to 11.9 Mg ha(-1) and from 17 to 223 kg N ha(-1), respectively, depending on sowing and killing dates and on the preceding crop. At killing, soil nitrate content in treatments with cover crops was 50-90% lower than in the control, reducing spring N leaching risk. When preceding maize, cover crops were killed in winter or early spring and their low C/N ratio (12-38) favored N release through residue decomposition. Vetch and rape seed as predecessors of fertilized maize increased residual N by approximate to 50 kg NO3-N compared to the control, posing the risk of fall N leaching. When preceding soybean, cover crops were killed in spring and, although their C/N ratios were higher (13-85), crucifers and legumes increased soil nitrate content. Maize yield was related to soil N availability at sowing (control and legumes > crucifers > grasses) which was inversely related to the preceding cover crop C/N ratio at killing. In normal to high rainfall years there were no differences in soybean yield among treatments. Water use by cover crops did not affect the main crop production except during an exceptionally dry year. Best synchronicity between N release from cover crop residues and harvest crop demand was achieved with the oats-vetch mixture before maize and with grasses before soybean. (C) 2011 Elsevier B.V. All rights reserved.
  • Authors:
    • Isla, R.
    • Urrego, Y. F.
    • Salmeron, M.
    • Cavero, J.
  • Source: Agricultural Water Management
  • Volume: 113
  • Issue: October
  • Year: 2012
  • Summary: Typical field conditions under sprinkler irrigation include low irrigation uniformity and non-uniform plant density, which can affect the crop yield and the environmental impact of irrigation. The effect of the uniformity of sprinkler irrigation and plant density on the variability of maize grain yield under semi-arid conditions was evaluated, and the relevance of the spatial variability of these two variables on the simulation of maize grain yield was tested with the DSSAT-CERES-Maize model (V 4.5). Experimental field data from three maize growing seasons (2006, 2009 and 2010) with nighttime or daytime sprinkler irrigation were used to test the model performance. Yield, irrigation depths and plant density distribution were measured in 18 m * 18 m plots divided in 25 sub-plots. Regression analysis showed that the variability of plant density and seasonal irrigation depth (due to irrigation non-uniformity) was able to explain from 28 to 77% of the variability in maize grain yield for the experiments with a relatively high coefficient of uniformity (CU) (73-84%) and high plant density (more than 74,844 plants ha -1). Taking into account irrigation depth distribution improved maize yield simulations compared to simulations with the average irrigation water applied. The root mean square error ( RMSE) decreased from 637 to 328 kg ha -1. Maize yield was over-predicted by 3% when irrigation depth distribution was not considered. Including plant density distribution in the simulations did not improve maize yield simulations. The simulated decrease in maize yield with decreasing CU of irrigation from 100 to 70% varied from year to year and caused reductions in yield ranging from 0.75 to 2.5 Mg ha -1. The ability of the model to simulate CU effects on maize yield is shown.
  • Authors:
    • Nichols ,R. L.
    • Webster, T. M.
  • Source: Weed Science
  • Volume: 60
  • Issue: 2
  • Year: 2012
  • Summary: Changes in the weed flora of cropping systems reflect the impacts of factors that create safe sites for weed establishment and facilitate the influx and losses to and from the soil seedbank. This analysis of the annual surveys of the Southern Weed Science Society documents changes in the weed flora of the 14 contiguous southern states since the advent of transgenic, herbicide-resistant crops. In 1994 and 2009, the top five weeds in corn were morningglories, Texas millet, broadleaf signalgrass, johnsongrass, and sicklepod; in this same period Palmer amaranth, smartweeds, and goosegrass had the greatest increases in importance in corn. In cotton, morningglories and nutsedges were among the top five most troublesome weeds in 1995 and 2009. Palmer amaranth, pigweeds, and Florida pusley were also among the five most troublesome species in 2009; the weeds with the largest increases in importance in cotton were common ragweed and two species with tolerance to glyphosate, Benghal dayflower and Florida pusley. In soybean, morningglories, nutsedges, and sicklepod were among the top five weed species in 1995 and 2009. Two species with glyphosate resistance, Palmer amaranth and horseweed, were the second and fourth most troublesome weeds of soybean in 2009. In wheat, the top four weeds in 2008 were the same as those in 1994 and included Italian ryegrass, wild garlic, wild radish, and henbit. Crop production in the southern region is a mosaic of various crop rotations, soil types, and types of tillage. During the interval between the surveys, the predominant change in weed management practices in the region and the nation was the onset and rapid dominance of the use of glyphosate in herbicide-resistant cultivars of corn, cotton, and soybean. Because of the correspondence between the effects of glyphosate on the respective weed species and the observed changes in the weed flora of the crops, it is likely the very broad use of glyphosate was a key component shaping the changes in weed flora. Only eight of the top 15 most troublesome weeds of cotton and soybean, the crops with the greatest use of glyphosate, were the same in 1995 and 2009. In contrast, in corn and wheat where adoption of glyphosate-resistant cultivars lags or is absent, 12 of the 15 most troublesome weeds were the same in 1994 and 2008. These findings show on a regional scale that weeds adapt to recurrent selection from herbicides, currently the predominant weed management tool. Future research should seek methods to hinder the rapid spread of herbicide-tolerant and evolution of herbicide-resistant weed species. As new tools are developed, research should focus on ways to preserve the efficacy of those tools through improved stewardship. Nomenclature: annual bluegrass, Poa annua L. POAAN; Benghal dayflower, Commelina benghalensis L. COMBE; broadleaf signalgrass, Urochloa platyphylla (Nash) R.D. Webster BRAPP; common ragweed, Ambrosia artemisiifolia L. AMBEL; Florida pusley Richardia scabra L. RCHSC; goosegrass Eleusine indica (L.) Gaertn. ELEIN; groundcherries, Physalis spp.; henbit, Lamium amplexicaule L. LAMAM; horseweed, Conyza canadensis (L.) Cronq. ERICA; Italian ryegrass, Lolium perenne L. ssp. multiflorum (Lam.) Husnot LOLMU; johnsongrass, Sorghum halepense (L.) Pers. SORHA; morningglories, Ipomoea spp.; nutsedges, Cyperus spp.; Palmer amaranth, Amaranthus palmeri S. Wats. AMAPA; pigweed, Amaranthus spp.; sicklepod, Senna obtusifolia (L.) H.S. Irwin & Barneby CASOB; smartweeds, Polygonum spp.; Texas millet, Urochloa texana (Buckl.) R. Webster PANTE; wild garlic, Allium vineale L. ALLVI; wild radish, Raphanus raphanistrum L. RAPRA; corn, Zea mays L.; cotton, Gossypium hirsutum L.; soybean Glycine max. (L.) Merr.; wheat, Triticum aestivum L.
  • Authors:
    • Weirich Neto, P. H.
    • Lopes, A. R. C.
  • Source: Engenharia Agrícola
  • Volume: 32
  • Issue: 2
  • Year: 2012
  • Summary: The seeding process was the operation that suffered the most changes in no-tillage system due the cover crop soil and new particle soil arrangement. The objective of this study was to verify the effects of loads applied to the wheels and adjustments of sowing depth on seedling emergence of corn in no-tillage system. The experimental design was completely randomized with a factorial arrangement 5*4, with five loads applied to the wheels and four theoretical sowing depth adjustments. The real sowing depth increased in the lower theoretical depth and decreased in the higher theoretical depth, due to the compaction loads. Regarding the time of emergence, loads applied had not influence at the greater depths. Emergence time decreased with the load increase in the lower depths. Thus, the adjustment of the compactor wheels can influence in the corn seeding process.
  • Authors:
    • Li, Y. Q.
    • Liu, H. B.
    • Li, M. F.
    • Fan, L.
    • Wu, W.
  • Source: Transactions of the Chinese Society of Agricultural Engineering
  • Volume: 28
  • Issue: 3
  • Year: 2012
  • Summary: The records of daily solar radiation (Rs, MJ.m -2.d -1) are the important inputs for crop simulation models. However, for some model users, Rs at longer temporal intervals are more available than that at daily scale. The objective of this study was to analyze the sensitivity of simulated crop growth and production using CERES-Maize and GROPGRO-Soybean, two widely used crop growth models, to uncertainty in Rs at different time scales (5-day, 10-day, and monthly). Daily radiation data (1961-1990) from Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) for the state of Georgia, USA were used to create 5-day, 10-day, and monthly mean daily Rs data sets. Datasets related to daily Rs were used as background baselines. The overall performance of the models was not significantly affected by Rs under the studied time scales. Within locations, the simulated days to anthesis and grain yields from 5-day, 10-day, and monthly Rs were close to that from daily Rs for maize and soybean under rainfed and irrigated conditions, respectively. Mean values of relative mean bias error (RMBE), mean bias error (MBE) and root mean square error (RMSE) of the simulated days to anthesis were 0, 0 and 3.5 d for the two crops under the studied scenarios, respectively. The simulated yields were underestimated for maize and overestimated for soybean using 5-day, 10-day, and monthly Rs for both rainfed and irrigated conditions, respectively. Under rainfed and irrigated conditions, the average RMBE and RMSE were -0.59%, 120 kg/hm 2 and -0.52%, 129 kg/hm 2 for maize yield, and 5%, 152 kg/hm 2 and 4.7%, 165 kg/hm 2 for soybean, respectively. Short-term bias in the difference between evaluated time scales and daily scale could affect the outputs of the crop models. Under the scenarios evaluated, CGOPGRO-Soybean model showed higher sensitivity to changes in multi-temporal Rs and water regimes than CERES-Maize model. Based on the results of this study, it can be concluded that 5-day, 10-day, and monthly mean daily Rs could be used as an input for crop growth simulation models when daily Rs are not available.
  • Authors:
    • Zheng, Y. K.
    • Yang, G. A.
    • Vasseur, L.
    • You, M. S.
    • Yao, F. L.
  • Source: Crop Protection
  • Volume: 34
  • Year: 2012
  • Summary: The frequent outbreaks of rice planthoppers, especially brown planthopper Nilaparvata lugens (Stal), in the last ten years in China and other Asian countries have caused serious rice ( Oryza sativa L.) yield losses. The key problem is possibly due to biodiversity loss in rice ecosystems. We examined the potential of intercrops of soybean ( Glycine max L.) and corn ( Zea mays L.), both of which are more profitable than rice and mostly planted in levees, to diversify rice ecosystems and enhance insect pest management. We studied the impacts of such intercrops on planthopper populations and their natural enemies. The results showed significantly lower numbers of rice planthoppers in rice fields with intercrops of corn than in rice monocultures and rice fields with intercrops of soybean. Rice fields with corn intercrops had 26-48% fewer planthoppers than rice monoculture. Rice fields with soybean intercrops had lower rice planthopper abundance compared to rice monoculture in 2008 but higher in 2009. However, neither parasitoid nor predator numbers were significantly affected by intercropping. There were no significant differences in directional movements of planthoppers or natural enemies between crop subplots in the different cropping systems. Moreover, movement of planthoppers was very limited. Our study indicated that soybean and corn intercrops do not greatly enhance the ability of natural enemies to suppress planthoppers. However, rice fields with intercrops of corn had lower abundance of planthoppers and this strategy may be useful as part of an integrated pest management strategy for the sustainable rice production.
  • Authors:
    • Hayes, R. M.
    • McClure, M. A.
    • Yin, X. H.
  • Source: Agricultural Sciences
  • Volume: 3
  • Issue: 2
  • Year: 2012
  • Summary: Nitrogen concentration in the ear leaf is a good indicator of corn (Zea mays L.) N nutrition status during late growing season. This study was done to examine the relationship of late-season ear leaf N concentration with early- to mid-season plant height of corn at Milan, TN from 2008 to 2010 using linear, quadratic, square root, logarithmic, and exponential models. Six N rate treatments (0, 62, 123, 185, 247, and 308 kg.N.ha -1) repeated four times were implemented each year in a randomized complete block design under four major cropping systems: corn after corn, corn after soybean [Glycine max (L.) Merr.], corn after cotton [Gossypium hirsutum (L.)], and irrigated corn after soybean. The relationship of ear leaf N concentration determined at the blister growth stage (R 2) with plant height measured at the 6-leaf (V6), 10-leaf (V10), and 12-leaf (V12) growth stages was statistically significant and positive in non-irrigated corn under normal weather conditions. However, the strength of this relationship was weak to moderate with the determination coefficient (R 2) values ranging from 0.21 to 0.51. This relationship was generally improved as the growing season progressed from V6 to V12. Irrigation and abnormal weather seemed to have adverse effects on this relationship. The five regression models performed similarly in the evaluation of this relationship regardless of growth stage, year, and cropping system. Our results suggest that unlike the relationship of corn yield at harvest with plant height measured during early- to mid-season or the relationship of leaf N concentration with plant height when both are measured simultaneously during early- to mid-season, the relationship of late-season ear leaf N concentration with early- to mid-season plant height may not be strong enough to be used to develop algorithms for variable-rate N applications on corn within a field no matter which regression model is used to describe this relationship.