• Authors:
    • Suh, Sangwon
    • Yang, Yi
  • Source: INTERNATIONAL JOURNAL OF LIFE CYCLE ASSESSMENT
  • Volume: 20
  • Issue: 2
  • Year: 2015
  • Summary: Purpose Rising corn prices in the USA due partly to increasing ethanol demands have led to a significant expansion of corn areas displacing natural vegetation and crops including cotton. From 2005 to 2009, cotton area harvested in the USA nearly halved with a reduction of 2.5 million hectares, while that of corn increased by 1.8 million hectares. However, environmental impacts of land shifts from cotton and corn have been largely neglected in literature. Methods In this study, we evaluate the environmental properties of US corn and cotton production and implications of land cover change from cotton to corn using state-specific data and life cycle impact assessment. Focusing on regional environmental issues, we cover both on-farm direct emissions such as different types of volatile organic compounds and pesticides and indirect emissions embodied in input materials such as fertilizers. TRACI 2.0 is used to evaluate the environmental impacts of these emissions. Results and discussion The results show that US cotton and corn productions per hectare on average generate roughly similar impacts for most impact categories such as eutrophication and smog formation. For water use and freshwater ecotoxicity, corn shows a smaller impact. When land shifts from cotton to corn in cotton-growing states, however, the process may aggravate most of the regional environmental impacts while relieving freshwater ecotoxicity impact. The differences in the two estimates are due mainly to underlying regional disparities in crop suitability that affects input structure and environmental emissions. Conclusions Our results highlight the importance of potential, unintended environmental impacts that cannot be adequately captured when average data are employed. Understanding the actual mechanisms under which certain policy induces marginal changes at a regional and local level is crucial for evaluating its net impact. Further, our study calls for an attention to biofuel-induced land cover change between crops and associated regional environmental impacts.
  • Authors:
    • Johnston, D.
    • Bange, M.
    • Luo, Q. Y.
    • Braunack, M.
  • Source: AGRICULTURE ECOSYSTEMS & ENVIRONMENT
  • Volume: 202
  • Year: 2015
  • Summary: Daily outputs from the CSIRO Conformal Cubic Atmospheric Model, driven by four general circulation models, were used in a stochastic weather generator, LARS-WG, to construct local climate scenarios for key cotton production areas in eastern Australia. These scenarios along with elevated atmospheric carbon dioxide concentration were then linked to a process-oriented cotton model (CSIRO OZCOT) to quantify their potential impacts on cotton lint yield, water use, and water use efficiency (WUE) under irrigated and rain-fed conditions in 2030. For irrigated cotton, we considered four water supply levels (2, 4, 6 and 8 ML/ha) at nine cotton production locations (Emerald, Dalby, St. George, Goondiwindi, Moree, Bourke, Narrabri, Warren and Hillston). For rain-fed cotton, we considered three planting configurations (solid, single skip and double skip) at four locations (Emerald, Dalby, Moree and Narrabri). Simulation results show that (1) season temperatures will increase 1-1.2°C and rainfall will increase 2-16% across locations; (2) for irrigated cotton (assuming full access to water and nitrogen), cotton crop water use will increase 0-4% in more than half of the cases (the combinations of the number of locations and water supply levels); cotton lint yield will increase 0-26% and WUE will increase 0-24% in most of the cases due to counteractive effects of elevated CO 2 and future climate, which are location- and water supply-specific; (3) for rain-fed cotton (assuming full initial soil profile), cotton water use will increase 2-8% at Emerald and Narrabri and decrease by -5 to -2% at Dalby and Moree; cotton lint yield will increase 4-26% in most of the cases and WUE will increase 2-22% in all cases. For irrigated cotton, it was found that water supply level with 2 ML/ha generated the greatest positive effects to future climate scenarios across locations except at Dalby where 4 ML/ha was greatest. For rain-fed cotton, a solid planting configuration had the greatest positive response to future climate scenarios at Emerald, Dalby and Moree while double skip planting generated the maximum benefit in lint yield at Narrabri. This simulation analysis also demonstrated the ability of the OZCOT in capturing the interactive effects of elevated CO 2 and future climate, indicating the usefulness of this tool in this important research area.
  • Authors:
    • Kouadio, L.
    • Power, B.
    • Cockfield, G.
    • Mushtaq, S.
    • White, N.
    • Williams, A.
  • Source: CLIMATIC CHANGE
  • Volume: 129
  • Issue: 1-2
  • Year: 2015
  • Summary: The paper evaluates the effect of future climate change (as per the CSIRO Mk3.5 A1FI future climate projection) on cotton yield in Southern Queensland and Northern NSW, eastern Australia by using of the biophysical simulation model APSIM (Agricultural Production Systems sIMulator). The simulations of cotton production show that changes in the influential meteorological parameters caused by climate change would lead to decreased future cotton yields without the effect of CO2 fertilisation. By 2050 the yields would decrease by 17 %. Including the effects of CO2 fertilisation ameliorates the effect of decreased water availability and yields increase by 5.9 % by 2030, but then decrease by 3.6 % in 2050. Importantly, it was necessary to increase irrigation amounts by almost 50 % to maintain adequate soil moisture levels. The effect of CO2 was found to have an important positive impact of the yield in spite of deleterious climate change. This implies that the physiological response of plants to climate change needs to be thoroughly understood to avoid making erroneous projections of yield and potentially stifling investment or increasing risk.
  • Authors:
    • Chen, J.
    • Burke, J.
  • Source: PLOS ONE
  • Volume: 10
  • Issue: 4
  • Year: 2015
  • Summary: Comparison of average crop yields with reported record yields has shown that major crops exhibit annual average yields three-to seven-fold lower than record yields because of unfavorable environments. The current study investigated the enhancement of pollen heat tolerance through expressing an Arabidopsis thaliana heat shock protein 101 (AtHSP101) that is not normally expressed in pollen but reported to play a crucial role in vegetative thermotolerance. The AtHSP101 construct under the control of the constitutive ocs/mas 'superpromoter' was transformed into cotton Coker 312 and tobacco SRI lines via Agrobacterium mediated transformation. Thermotolerance of pollen was evaluated by in vitro pollen germination studies. Comparing with those of wild type and transgenic null lines, pollen from AtHSP101 transgenic tobacco and cotton lines exhibited significantly higher germination rate and much greater pollen tube elongation under elevated temperatures or after a heat exposure. In addition, significant increases in boll set and seed numbers were also observed in transgenic cotton lines exposed to elevated day and night temperatures in both greenhouse and field studies. The results of this study suggest that enhancing heat tolerance of reproductive tissues in plant holds promise in the development of crops with improved yield production and yield sustainability in unfavorable environments.
  • Authors:
    • Southard, R. J.
    • Horwath, W. R.
    • Shrestha, A.
    • Mitchell, J. P.
    • Madden, N.
    • Veenstra, J.
    • Munk, D. S.
  • Source: Article
  • Volume: 107
  • Issue: 2
  • Year: 2015
  • Summary: Rising costs and air quality regulations have created interest in California's San Joaquin Valley (SJV) in production systems that reduce tillage operations and soil disturbance. From 1999 to 2009, we evaluated conventional (CT) and reduced tillage (RT) systems for a cotton ( Gossypium hirsutum L.)/tomato ( Solanum lycopersicon Mill.) rotation with (CC) and without (NO) cover crops in a Panoche clay loam soil (fine-loamy, mixed, superactive, thermic Typic Haplocambid) in Five Points, CA, in terms of yield, soil C, and the NRCS soil conditioning index (SCI). The RT reduced tractor operations by 50% for tomato and 40% for cotton. Cover cropping produced 38.7 t ha -1 of biomass. Tomato yields were 9.5% higher in RT vs. CT systems and 5.7% higher in NO vs. CC systems. The CT cotton yields were 10.0% higher than RT yields and 4.8% higher in NO systems, but yield patterns were not consistent from 2005 to 2009. Soil C content was uniform (0-30-cm depth) in 1999 (19.72 t ha -1) and increased in all systems in 2007 (t ha -1): RTCC 29.11, CTCC 26.36, RTNO, 24.09, and CTNO 22.65. Soil C content of RT and CT systems did not differ, but was greater in CC than in NO systems. In the 0- to 15-cm depth, RT increased soil C, indicating stratification, and also increased C in the occluded light and mineral fractions. The SCI was positive for RT treatments, predicting a soil C increase, and negative for CT systems, predicting a soil C decline, but measured soil C content increased in all systems. Results show that RT maintains or increases yields relative to CT, and CC stores more soil C than NO.
  • Authors:
    • Kohmann, M. M.
    • Torres, C. M. M. E.
    • Fraisse, C. W.
  • Source: Agricultural Journal
  • Volume: 137
  • Year: 2015
  • Summary: Agriculture is an important source of greenhouse gases (GHG), especially from crop production practices and enteric fermentation by ruminant livestock. Improved production practices in agriculture and increase in terrestrial carbon sinks are alternatives for mitigating GHG emissions in agriculture. The objective of this study was to estimate GHG emissions from hypothetical farm enterprise combinations in the southeastern United States with a mix of cropland and livestock production and estimate the area of forest plantation necessary to offset these emissions. Four different farm enterprise combinations (Cotton; Maize; Peanut; Wheat + Livestock + Forest) with different production practices were considered in the study resulting in different emission scenarios. We assumed typical production practices of farm operations in the region with 100 ha of cropland area and a herd of 50 cows. GHG emissions were calculated regarding production, storage and transportation of agrochemicals (pre-farm) and farm activities such as fertilization, machinery operation and irrigation (on-farm). Simulated total farm GHG emissions for the different farm enterprise combinations and production practices ranged from 348.8 t CO2e year-1 to 765.6 t CO2e year-1. The estimated forest area required to neutralize these emissions ranged from 19 ha to 40 ha. In general, enterprise combinations with more intense production practices that include the use of irrigation resulted in higher total emissions but lower emissions per unit of commodity produced. © 2015 Elsevier Ltd.
  • Authors:
    • Singh,R. J.
    • Ahlawat,I. P. S.
  • Source: Environmental Monitoring and Assessment
  • Volume: 187
  • Issue: 5
  • Year: 2015
  • Summary: Two of the most pressing sustainability issues are the depletion of fossil energy resources and the emission of atmospheric green house gases like carbon dioxide to the atmosphere. The aim of this study was to assess energy budgeting and carbon footprint in transgenic cotton–wheat cropping system through peanut intercropping with using 25–50 % substitution of recommended dose of nitrogen (RDN) of cotton through farmyard manure (FYM) along with 100 % RDN through urea and control (0 N). To quantify the residual effects of previous crops and their fertility levels, a succeeding crop of wheat was grown with varying rates of nitrogen, viz. 0, 50, 100, and 150 kg ha-1. Cotton + peanut–wheat cropping system recorded 21 % higher system productivity which ultimately helped to maintain higher net energy return (22 %), energy use efficiency (12 %), human energy profitability (3 %), energy productivity (7 %), carbon outputs (20 %), carbon efficiency (17 %), and 11 % lower carbon footprint over sole cotton–wheat cropping system. Peanut addition in cotton–wheat system increased the share of renewable energy inputs from 18 to 21 %. With substitution of 25 % RDN of cotton through FYM, share of renewable energy resources increased in the range of 21 % which resulted into higher system productivity (4 %), net energy return (5 %), energy ratio (6 %), human energy profitability (74 %), energy productivity (6 %), energy profitability (5 %), and 5 % lower carbon footprint over no substitution. The highest carbon footprint (0.201) was recorded under control followed by 50 % substitution of RDN through FYM (0.189). With each successive increase in N dose up to 150 kg N ha-1 to wheat, energy productivity significantly reduced and share of renewable energy inputs decreased from 25 to 13 %. Application of 100 kg N ha-1 to wheat maintained the highest grain yield (3.71 t ha-1), net energy return (105,516 MJ ha-1), and human energy profitability (223.4) over other N doses applied to wheat. Application of 50 kg N ha-1 to wheat maintained the least carbon footprint (0.091) followed by 100 kg N ha-1 (0.100). Our study indicates that system productivity as well as energy and carbon use efficiencies of transgenic cotton–wheat production system can be enhanced by inclusion of peanut as an intercrop in cotton and substitution of 25 % RDN of cotton through FYM, as well as application of 100 kg N ha-1 to succeeding wheat crop. © 2015, Springer International Publishing Switzerland.
  • Authors:
    • Kibue,Grace Wanjiru
    • Pan,Genxing
    • Zheng,Jufeng
    • Li Zhengdong
    • Mao,Li
  • Source: Environment, Development and Sustainability
  • Volume: 17
  • Issue: 3
  • Year: 2015
  • Summary: Agricultural production is a complex interaction between human and natural environment, making agriculture both significantly responsible and vulnerable to climate change. China, whose socioeconomy is fundamentally dependent on agriculture, is already experiencing climate-change-related issues that threaten food security and sustainable development. Climate change mitigation and adaptation are of great concern to ensure food security for the growing population and improve the livelihoods of poor smallholder producers. A questionnaire survey was conducted in Henan Province, China to assess agronomic practices of smallholder farmers, adaptation strategies and how climate change awareness and perceptions influence the farmers' choice of agronomic practices. The results showed that the vast majority of farmers owned < 10 Chinese Mu (0.7 ha) and nearly all farmers' relied on intensive use of chemical fertilizers and pesticides to increase yield at the detriment of environment. However, farmers who were aware of climate change had adopted agronomic practices that reduce impacts of climate change. Information about climate change, lack of incentives, lack of credit facilities and small farm sizes were major hindrance to adaptation and adoption of farming practices that can reduce impacts of climate change. This study recommends that research findings should be disseminated to farmers in timely and appropriate ways. The central government should formulate policies to include subsidies and incentives for farmers to motivate adoption of eco-friendly agronomic practices.
  • Authors:
    • Torres,C. M. M. E.
    • Kohmann,M. M.
    • Fraisse,C. W.
  • Source: Agricultural Systems
  • Volume: 137
  • Year: 2015
  • Summary: Agriculture is an important source of greenhouse gases (GHG), especially from crop production practices and enteric fermentation by ruminant livestock. Improved production practices in agriculture and increase in terrestrial carbon sinks are alternatives for mitigating GHG emissions in agriculture. The objective of this study was to estimate GHG emissions from hypothetical farm enterprise combinations in the southeastern United States with a mix of cropland and livestock production and estimate the area of forest plantation necessary to offset these emissions. Four different farm enterprise combinations (Cotton; Maize; Peanut; Wheat+Livestock+Forest) with different production practices were considered in the study resulting in different emission scenarios. We assumed typical production practices of farm operations in the region with 100 ha of cropland area and a herd of 50 cows. GHG emissions were calculated regarding production, storage and transportation of agrochemicals (pre-farm) and farm activities such as fertilization, machinery operation and irrigation (on-farm). Simulated total farm GHG emissions for the different farm enterprise combinations and production practices ranged from 348.8 t CO 2e year -1 to 765.6 t CO 2e year -1. The estimated forest area required to neutralize these emissions ranged from 19 ha to 40 ha. In general, enterprise combinations with more intense production practices that include the use of irrigation resulted in higher total emissions but lower emissions per unit of commodity produced.
  • Authors:
    • Baumhardt,R. L.
    • Mauget,S. A.
    • Gowda,P. H.
    • Brauer,D. K.
    • Marek,G. W.
  • Source: Agronomy Journal
  • Volume: 107
  • Issue: 5
  • Year: 2015
  • Summary: Equatorial Pacific sea surface temperature anomalies can cause a systematic El Nino-Southern Oscillation (ENSO) coupling with the atmosphere to produce predictable weather patterns in much of North America. Adapting irrigation strategies for drought-tolerant crops like cotton ( Gossypium hirsutum L.) to exploit forecast climatic conditions represents one potential innovative technique for managing the declining Ogallala Aquifer beneath the US Southern High Plains. The crop simulation model GOSSYM was used with ENSO phase-specific weather records during 1959 to 2000 at Bushland, TX, to estimate lint yields of cotton emerging on three dates from soil at 50 or 75% available water content for all possible combinations of irrigation durations (0, 4, 6, 8, and 10 wk) and rates (2.5, 3.75, and 5.0 mm d -1). From those data, our objective was to compare partial center pivot deficit irrigation strategies that optimize calculated net cotton lint yield in relation to ENSO phase, initial soil water content, and emergence date. Although phase classification in June was inconsistent with maturing fall phases, the most accurately classified La Nina phase had limited rain that reduced lint yields compared with wetter Neutral and El Nino phases. During La Nina phase conditions, irrigation strategies that focused fixed water resources on smaller areas were better suited to increase net yield than spreading water across larger areas. Alternatively, during less predictable and wetter Neutral and El Nino phases, irrigation strategies that spread water increased net lint yield over focused applications except when both initial soil water and irrigation amount were limiting.