Greenhouse gas emissions from the Canadian beef industry

Commodity-specific estimates of the greenhouse gas (GHG) emissions from Canadian agriculture are required in order to identify the most efficient GHG mitigation measures. In this paper, the methodology from the Intergovernmental Panel on Climate Change (IPCC) for estimating bovine GHG emissions, for census years from 1981 to 2001, was applied to the Canadian beef industry. This analysis, which is based on several adaptations of IPCC methodology already done for the Canadian dairy industry, includes the concept of a beef crop complex, the land base that feeds the beef population, and the use of recommendations for livestock feed rations and fertilizer application rates to down-scale the national area totals of each crop, regardless of the use of that crop, to the feed requirements of the Canada’s beef population. It shows how high energy feeds are reducing enteric methane emissions by displacing high roughage diets. It also calculates an emissions intensity indicator based on the total weight of live beef cattle destined for market. While total GHG from Canadian beef production have increased from 25 to 32 Tg of CO₂ equiv. between 1981 and 2001, this increase was mainly driven by expansion of the Canadian cattle industry. The emission intensity indicator showed that between 1981 and 2001, the Canadian beef industry GHG emissions per kg of live animal weight produced for market decreased from 16.4 to 10.4 kg of CO₂ equiv.     

The environmental performance of milk production on a typical Portuguese dairy farm

The activities associated with raw milk production on dairy farms require an effective evaluation of their environmental impact. The present study evaluates the global environmental impacts associated with milk production on dairy farms in Portugal and identifies the processes that have the greatest environmental impact by using life cycle assessment (LCA) methodology. The main factors involved in milk production were included, namely: the dairy farm, maize silage, ryegrass silage, straw, concentrates, diesel and electricity. The results suggest that the major source of air and water emissions in the life cycle of milk is the production of concentrates. The activities carried out on dairy farms were the major source of nitrous oxides (from fuel combustion), ammonia, and methane (from manure management and enteric fermentation). Nevertheless, dairy farm activities, which include manure management, enteric fermentation and diesel consumption, make the greatest contributions to the categories of impact considered, with the exception of the abiotic depletion category, contributing to over 70% of the total global warming potential (1021.3 kg CO₂ eq. per tonne of milk), 84% of the total photochemical oxidation potential (0.2 kg C₂H₄ eq. per tonne of milk), 70% of the total acidification potential (20.4 kg SO₂ eq. per tonne of milk), and 41% of the total eutrophication potential (7.1 kg eq. per tonne of milk). The production of concentrates and maize silage are the major contributors to the abiotic depletion category, accounting for 35% and 28%, respectively, of the overall abiotic depletion potential (1.4 Sb eq. per tonne of milk). Based on this LCA case study, we recommend further work to evaluate some possible opportunities to improve the environmental performance of Portuguese milk production, namely: (i) implementing integrated solutions for manure recovery/treatment (e.g. anaerobic digestion) before its application to the soil as organic fertiliser during maize and ryegrass production; (ii) improving manure nutrient use efficiency in order to decrease the importation of nutrients; (iii) diversifying feeding crops, as the dependence on two annual forage crops is expected to lead to excessive soil mobilisation (and related impacts) and to insignificant carbon dioxide sequestration from the atmosphere; and (iv) changing the concentrate mixtures.     

Life cycle assessment of greenhouse gas emissions from beef production in western Canada: A case study

A life cycle assessment (LCA) was conducted to estimate whole-farm greenhouse gas (GHG) emissions from beef production in western Canada. The aim was to determine the relative contributions of the cow-calf and feedlot components to these emissions, and to examine the proportion of whole-farm emissions attributable to enteric methane (CH₄). The simulated farm consisted of a beef production operation comprised of 120 cows, four bulls, and their progeny, with the progeny fattened in a feedlot. The farm also included cropland and native prairie pasture for grazing to supply the feed for the animals. The LCA was conducted over 8 years to fully account for the lifetime GHG emissions from the cows, bulls and progeny, as well as the beef marketed from cull cows, cull bulls, and progeny raised for market. The emissions were estimated using Holos, a whole-farm model developed by Agriculture and Agri-Food Canada. Holos is an empirical model, with a yearly time-step, based on the Intergovernmental Panel on Climate Change methodology, modified for Canadian conditions and farm scale. The model considers all significant CH₄, N₂O, and CO₂ emissions and removals on the farm, as well as emissions from manufacture of inputs (fertilizer, herbicides) and off-farm emissions of N₂O derived from nitrogen applied on the farm. The LCA estimated the GHG intensity of beef production in this system at 22 kg CO₂ equivalent (kg carcass)⁻¹. Enteric CH₄ was the largest contributing source of GHG accounting for 63% of total emissions. Nitrous oxide from soil and manure accounted for a further 27% of the total emissions, while CH₄ emissions from manure and CO₂ energy emissions were minor contributors. Within the beef production cycle, the cow-calf system accounted for about 80% of total GHG emissions and the feedlot system for only 20%. About 84% of enteric CH₄ was from the cow-calf herd, mostly from mature cows. It follows that mitigation practices to reduce GHG emissions from beef production should focus on reducing enteric CH₄ production from mature beef cows. However, mitigation approaches must also recognize that the cow-calf production system also has many ancillary environmental benefits, allowing use of grazing and forage lands that can preserve soil carbon reserves and provide other ecosystems services.     

The impact of various parameters on the carbon footprint of milk production in New Zealand and Sweden

The carbon footprint (CF) of milk production was analysed at the farm gate for two contrasting production systems; an outdoor pasture grazing system in New Zealand (NZ) and a mainly indoor housing system with pronounced use of concentrate feed in Sweden (SE). The method used is based on the conceptual framework of lifecycle assessment (LCA), but only for greenhouse gas (GHG) emissions. National average data were used to model the dairy system in each country. Collection of inventory data and calculations of emissions were harmonised to the greatest extent possible for the two systems. The calculated CF for 1 kg of energy corrected milk (ECM), including related by-products (surplus calves and culled cows), was 1.00 kg carbon dioxide equivalents (CO₂e) for NZ and 1.16 kg CO₂e for SE. Methane from enteric fermentation and nitrous oxide emissions from application of nitrogen (as fertiliser and as excreta dropped directly on the field) were the main contributors to the CF in both countries. The most important parameters to consider when calculating the GHG emissions were dry matter intake (DMI), emission factor (EF) for methane from enteric fermentation, amount of nitrogen applied and EF for direct nitrous oxide emissions from soils. By changing one parameter at a time within ‘reasonable’ limits (i.e. no extreme values assumed), the impact on the total CF was assessed and showed changes of up to 15%. In addition, the uncertainty in CF estimates due to uncertainty in EF for methane from enteric fermentation and nitrous oxide emissions (from soil and due to ammonia volatilisation) were analysed through Monte Carlo simulation. This resulted in an uncertainty distribution corresponding to 0.60-1.52 kg CO₂e kg⁻¹ ECM for NZ and 0.83-1.56 kg CO₂e kg⁻¹ ECM for SE (in the prediction interval 2.5-97.5%). Hence, the variation within the systems based on the main EF is relatively large compared with the difference in CF between the countries.     

Analysis of greenhouse gas emissions from the average Irish milk production system

Actions to moderate the major emission contributors of enteric fermentation, fertiliser and manure management on farms should not simply move the emissions elsewhere in the system, but actually reduce them. Life cycle assessment methodology was used to provide an objective framework for estimating emissions and to evaluate emission management scenarios with respect to kg CO₂ eq emitted per unit of milk produced. An average dairy unit was defined and emissions were compartmentalised to calculate a total emission of 1.50 kg CO₂ eq kg⁻¹ (energy corrected milk) yr⁻¹ and 1.3 kg CO₂ eq kg⁻¹ yr⁻¹ with economic allocation between milk and meat. Of the total emissions, 49% was enteric fermentation, 21% fertiliser, 13% concentrate feed, 11% dung management and 5% electricity and diesel consumption. Scenario testing indicated that more efficient cows with extensive management could reduce emissions by 14–18%, elimination of non-milking animals could reduce emissions by 14–26% and a combination of both could reduce emissions by 28–33%. It was concluded that the evolution of the Irish dairy sector, driven by the Common Agricultural Policy (CAP), should result in reduced GHG emissions.     

Introducing greenhouse gas mitigation as a development objective in rice-based agriculture: I. Generation of technical coefficients

This study presents a modeling tool to assess emission of greenhouse gases (GHG) from the agricultural sector as affected by land-use and residue utilization options. The overall purpose of this tool is twofold: (i) a spreadsheet model for comprehensive compilation of the direct and indirect emissions from land management, residue-burning and fossil fuel consumption through on-farm and off-farm operations and (ii) a decision support tool to explore economically viable mitigation options through detailed cost–benefit analysis of different technological options. We developed TechnoGAS (technical coefficient generator for mitigation technologies of greenhouse gas emissions from agricultural sectors), which integrates analytical and expert knowledge with regional databases on bio-physical, agronomic and socio-economic features to establish input–output relationships (‘Technical Coefficients’) related to GHG emissions in agriculture. The approach includes emissions of methane (CH₄) from rice fields, rice straw burning and cattle; carbon dioxide (CO₂) from fossil fuel and soil organic carbon decline as well as nitrous oxide (N₂O) from soil, rice straw burning and fertilizer use. To illustrate the approach of the spreadsheet model for comprehensive compilation of emissions, we applied TechnoGAS for an entire rice–wheat cropping cycle in the state of Haryana in northern India as a case study. Twenty technologies of rice production, which can be adopted by farmers, are analysed for their operation-specific emissions including their global warming potential (GWP). The technologies differ in terms of water regime, residue management/utilization, soil management and additives, which represent different mitigation options for GHG emissions. With the current farmers’ practice in various districts in Haryana, soil-borne emissions are the major source of GHG contributing 53% of the average GWP (3288 kg CO₂ equivalent ha⁻¹) in rice followed by burning of rice straw (13% of the GWP). Cattle, farm operations, off-farm and inorganic fertilizer contributes 12%, 10%, 10% and 2% of the GWP, respectively. Emissions from wheat are relatively low (1204 kg CO₂ equivalent ha⁻¹) as there is no CH₄ emission and wheat straw is not burnt. Different mitigation technologies show pronounced effects on the GWP of the rice crop and varied between 1715 kg CO₂ equivalent ha⁻¹ with continuous flooding, urea and rice straw used for building materials and 10,020 kg CO₂ equivalent ha⁻¹ with continuous flooding, and application of nutrients through organic manure. Compared to current farmers’ practice, 13 technologies are found to have the potential to reduce the GWP by 8–51%, but they also reduce the net income of farmers. Upscaling of the estimates to the entire state of Haryana shows that the GWP with the current farmers’ practice in rice is 2617 Gg CO₂ equivalent. Modification of water management from continuous flooding to alternate flooding or application of urea alone instead of urea plus FYM will reduce the GWP by 15% and 29%, respectively, while feeding of rice straw to cattle and supplying N through urea will reduce it by 41% compared to the current practice of burning rice straw and use of FYM. The study shows that the TechnoGAS tool can be used for estimating GHG emission from various land-use types and for identifying promising mitigation options. A detailed cost/benefit analysis is supplied by Wassmann and Pathak [Wassmann, R., Pathak, H., this volume. Introducing greenhouse gas mitigation as a development objective in rice-based agriculture: II. Cost–benefit assessment for different technologies, regions and scales.].     

A systems approach to quantify greenhouse gas fluxes from pastoral dairy production as affected by management regime

A model was developed to determine what effect management practices would have on the production of the greenhouse gases (GHG) within pastorally based dairy production systems typical of those practiced in Ireland. The model simulates two levels of GHG emissions, firstly the on-farm GHG emissions of methane, nitrous oxide and carbon dioxide for example from the pastorally spreading of slurry and secondly, off-farm GHG emissions associated with both inputs brought onto the farm to maintain productivity (for example emissions arising from manufacture of concentrate feeds and fertiliser) as well as from indirect GHG emissions associated with nitrate leaching and ammonia. The aim of this work was to allow the development of effective GHG mitigation strategies at the farm level capable of reducing GHG emissions per litre of milk.Greenhouse gas emissions were modelled for nine farming systems differing in the level of concentrate supplementation (376, 810 and 1540 kg per cow per lactation) and genotype for milk production as assessed by their pedigree index (<100, 100–200 and 200–300 kg) of milk production. A three-year study to evaluate the influence of cow genetic potential for milk production and concentrate supplementation level on profitability of pasture-based systems of milk production was used to drive the Moorepark Dairy Systems Model (MDSM). Output from this model then described farm size, feed budgets, animal numbers and farm profitability when annual milk quota was set to 468,000 kg of milk year. Relating GHG emissions to annual milk sales revealed that for these pastorally based systems increasing concentrate usage reduced both on-farm and off-farm emissions, but that increasing the genotype of the dairy cow (i.e., the genetic capacity of the animal to produce milk) will increase both on-farm and off-farm GHG emissions. Lowest GHG emissions per kilogram of milk were achieved for an intermediate genotype type cow fed within a high concentrate system whilst the highest emissions were associated with high genotype cows fed within a low concentrate system. Maximum profitability was obtained when either a high concentrate feeding regime was combined with high genotype cows or where low concentrate systems were fed to low genotype cows.Relating farm profitability to GHG emissions allowed the identification of scenarios where changing from one management systems to another would achieve a simultaneous reduction in GHG emissions whilst improving farm profitability. By implementing this approach of assessing management induced change on both GHG emissions arising from the farm together with farm profitability, individual whole farm GHG mitigation strategies could be developed with a high degree of acceptability to the producer.     

The contribution of maize cropping in the Midwest USA to global warming: A regional estimate

Agricultural soils emit about 50% of the global flux of N₂O attributable to human influence, mostly in response to nitrogen fertilizer use. Recent evidence that the relationship between N₂O fluxes and N-fertilizer additions to cereal maize are non-linear provides an opportunity to estimate regional N₂O fluxes based on estimates of N application rates rather than as a simple percentage of N inputs as used by the Intergovernmental Panel on Climate Change (IPCC). We combined a simple empirical model of N₂O production with the SOCRATES soil carbon dynamics model to estimate N₂O and other sources of Global Warming Potential (GWP) from cereal maize across 19,000 cropland polygons in the North Central Region (NCR) of the US over the period 1964-2005. Results indicate that the loading of greenhouse gases to the atmosphere from cereal maize production in the NCR was 1.7 Gt CO₂e, with an average 268 t CO₂e produced per tonne of grain. From 1970 until 2005, GHG emissions per unit product declined on average by 2.8 t CO₂e ha⁻¹ annum⁻¹, coinciding with a stabilisation in N application rate and consistent increases in grain yield from the mid-1970’s. Nitrous oxide production from N fertilizer inputs represented 59% of these emissions, soil C decline (0-30 cm) represented 11% of total emissions, with the remaining 30% (517 Mt) from the combustion of fuel associated with farm operations. Of the 126 Mt of N fertilizer applied to cereal maize from 1964 to 2005, we estimate that 2.2 Mt N was emitted as N₂O when using a non-linear response model, equivalent to 1.75% of the applied N.     

Dairy farm nutrient management model. 1. Model description and validation

Intensive dairy farming results in significant phosphorus (P) emission to the environment. Field data indicates that farm-gate P surplus is highly positive in Finland and strategies to mitigate the surplus are needed. The objectives of this study were to build a P cycle model for dairy farms (1) and to validate the model with independent field data (2). The dairy farm nutrient management model (“Lypsikki”) described in this paper includes three sub-models: (1) soil and crop, (2) dairy herd and (3) manure management. The model is based on empirical regression equations allowing estimations of crop and milk yields in response to increased fertilisation and nutrient supply, respectively. In addition, the model includes a dynamic simulation model of the dairy herd structure and calculation of the farm-gate nutrient surplus. The model was validated with independent annual (average for 1-4 years) farm-gate P surplus data from 21 dairy farms. Model simulations were conducted using two levels of soil productivity, mean (M) and low (L). The model validation indicated a strong relationships between model-predicted and observed farm-gate P surplus: (M: R² = 0.77 and L: R² = 0.80). The line bias between the model-predicted and observed data was negligible and insignificant (P > 0.6) suggesting a robustness of the model. The mean biases were relatively high and significant (M: 4.7 and L: 1.8 kg/ha, P < 0.001), but evidently related to overestimation of crop yields that has to be taken into account when using the model on a single farm. The prediction error of the model (observed minus predicted P surplus) was significantly correlated to the difference between simulated and observed P import in feeds (M: R² = 0.55 and L: R² = 0.51). This suggests either that all the dairy farms did not fully exploit the possibilities in the crop production or that all the model assumptions are not correct. The effects of purchased feed and fertiliser P and exported milk P (per cow or cropping area) on farm-gate P surplus were of the same magnitude in both observed and simulated data. This implies that the model developed can be used as a management decision tool to find strategies to mitigate P surplus on dairy farms.     

Intensification of New Zealand beef farming systems

This study used whole-farm management, nutrient budgeting/greenhouse gas (GHG) emissions and feed formulation computer tools to determine the production, environmental and financial implications of intensifying the beef production of typical New Zealand (NZ) sheep and beef farming systems. Two methods of intensification, feeding maize silage (MS) or applying nitrogen (N) fertiliser, were implemented on two farm types differing in the proportions of cultivatable land to hill land (25% vs. 75% hill). In addition, the consequences of intensification by incorporating a beef feedlot (FL) into each of the farm types were also examined.Feeding MS or applying N fertiliser substantially increased the amount of beef produced per ha. Intensifying production was also associated with increased total N leaching and GHG emissions although there were differences between the methods of intensification. Feeding MS resulted in lower environmental impacts than applying N even after taking into account the land to grow the maize for silage. Based on 2007/08 prices, typical NZ sheep and beef farms were making a financial loss and neither method of intensification increased profitability with the exception of small annual applications of N, especially to the 75% hill farm. These small annual additions of N fertiliser (<50 kg N/ha/yr applied in autumn and late winter) resulted in only small increases in annual N leaching (from 11 to 14 kg N/ha) and GHG emissions (from 3280 to 4000 kg CO₂ equivalents/ha). Limited N applications were particularly beneficial to 75% hill farms because small increases in winter carrying capacity resulted in relatively large increases in the utilisation of pasture growth during spring and summer than the 25% hill farms. Intensification by incorporating a beef feedlot reduced environmental emissions per kg of beef produced but considerably decreased profitability due to higher capital, depreciation and labour costs. The lower land-use capability farm type (75% hill) was able to intensify beef production to a proportionally greater extent than the higher land-use capability farm (25% hill) because of greater potential to increase pasture utilisation associated with a lower initial farming intensity and inherent constraints in the pattern of pasture supply.     

Financial implications of recent declines in reproduction and survival of Holstein-Friesian cows in spring-calving Irish dairy herds

Milk production and reproductive performance were monitored in 14 spring calving dairy herds in the south of Ireland between 1990 and 2003. In these herds, the average pedigree index for milk yield increased by 25 kg per year from 1990 to 2001, while the average proportion of Holstein-Friesian genes in the cows increased from 8% in 1990 to 63% in 2001. Over this period, milk production per cow increased by 54 kg/year, while replacement rate increased from 16% in 1990 to 27% in 2003. To evaluate the farm-level financial implications of associated changes in calving pattern, milk production and replacement rate, data from the 14 spring-calving herds were included in the Moorepark Dairy System Model for each of the 14 years. Two milk production scenarios were investigated, which included EU milk quota applied at farm level (S1) and no milk quota (S2). The influence of variation in milk price, cull cow value, replacement heifer cost and replacement rate were modelled using stochastic budgeting. In S1 there was a significant linear increase (P < 0.05) in margin per cow (€10.8), margin per kg of milk produced (0.13 cent) and net farm profit (€546) over the 14-year period. Similarly in S2 there was a significant linear increase in margin/cow (€11.3), margin/kg (0.14 cent) and farm profit (€1089) over the 14-year period. However, the analysis showed that if reproductive performance, calving spread and replacement rate could have been maintained at 1990 levels for each of the 14 years then the increase per cow, per kg of milk and farm profit per year would have been €22.1, 0.31 cent and €1341 for S1, and €22.8, 0.32 cent and €2183 for S2, respectively. Stochastic analysis showed that farm profit was most sensitive to changes in milk price, followed by replacement rate.     

Offsetting greenhouse gas emissions through biological carbon sequestration in North Eastern Australia

The Kyoto Protocol recognises trees as a sink of carbon and a valid means to offset greenhouse gas emissions and meet internationally agreed emissions targets. This study details biological carbon sequestration rates for common plantation species Araucaria cunninghamii (hoop pine), Eucalyptus cloeziana, Eucalyptus argophloia, Pinus elliottii and Pinus caribaea var hondurensis and individual land areas required in north-eastern Australia to offset greenhouse gas emissions of 1000 t CO₂e. The 3PG simulation model was used to predict above and below-ground estimates of biomass carbon for a range of soil productivity conditions for six representative locations in agricultural regions of north-eastern Australia. The total area required to offset 1000 t CO₂e ranges from 1 ha of E. cloeziana under high productivity conditions in coastal North Queensland to 45 ha of hoop pine in low productivity conditions of inland Central Queensland. These areas must remain planted for a minimum of 30 years to meet the offset of 1000 t CO₂e.     

Energy consumption, greenhouse gas emissions and economic performance assessments in French Charolais suckler cattle farms: Model-based analysis and forecasts

The environmental and economic performance of five Charolais beef production systems (three specialized beef producer test cases in grassland areas and two mixed crop-livestock test cases with a more intensive production system) were assessed by coupling an economic optimization model (“Opt’INRA”) with a model assessing non-renewable energy (NRE) consumption and greenhouse gas emissions (“PLANETE”). The test cases studied covered a relatively diverse range of raised and sold animals: calf-to-weanling or calf-to-beef systems (animals sold: from 10-month-old weaners to 36-month-old beef steers). In 2006, NRE consumption ranged from 26,440 to 31,863 MJ/ton of live weight produced over 1 year. Fuels and lubricants were the main factors of NRE consumption, followed by fertilizers and farm equipment. Livestock was the main driver of global warming potential. GHG emissions, at 14.3-18.3 tCO₂eq/t LW, were mainly determined by the proportion of cows in the total herd livestock units, according to the farming system deployed, i.e. calf-to-weanling vs. calf-to-beef. Against a background of rising energy costs, farms running mixed crop-livestock systems enjoy greater flexibility to adjust their farming systems than grassland-based farms, enabling them to minimize the drop in income over the timeframe to 2012 (−3%). In this same setting, specialist beef producers face a 15-25% drop in income. In all the scenarios run, system adjustments designed to minimize the drop in income have only a very limited impact on NRE consumption and GHG emissions.     

Does silicon and irrigation have impact on drought tolerance mechanism of sorghum?

Silicon absorption by crops in the form of silicic acid confers efficient utilization of available irrigation water by minimizing transpiration losses. In present study, silicon and irrigation effects on sorghum growth dynamics and drought tolerance mechanism were evaluated during 2007-2008. Two sorghum cultivars: PARCSS2 and Johar1 were treated with two levels of silicon (Si₀ = control and Si₂₀₀ = 200 ml l⁻¹ of potassium silicate per kg of soil) and irrigation (W₀ = control, crop lower limit and W₄₀ = 40 mm of water, crop upper limit). The results depicted that silicon absorption led to increased leaf water potential, growth, transpiration, net photosynthetic rate and decreased shoot to root ratio in sorghum cultivars compared to control treatment. It can be concluded that synergistic effect of silicon fertilization with ample irrigation may improve the crop stand under drought and biotic stresses.     

An assessment of the energy inputs and greenhouse gas emissions in sugar beet (Beta vulgaris) production in the UK

Reducing the energy derived from fossil fuels within agricultural systems has important implications for decreasing atmospheric emissions of greenhouse gases, thus assisting the arrest of global warming. The identification of crop production methods that maximise energy efficiency and minimise greenhouse gas emissions is vital. Sugar beet is grown in a variety of locations and under a variety of agronomic conditions within the UK. This study identified thirteen production scenarios, representative of over 90% of the UK beet crop, which included five soil types, nine fertiliser regimes and nine crop protection strategies. The fossil energy input, the overall energy efficiency and the global warming potential (GWP) of each production scenario was assessed. This study did not consider the processing of the beet to extract sugar.The overall energy input of the UK beet crop ranges between 15.72 and 25.94 GJ/ha. It produces between 7.3 and 15.0 times as much energy in dry matter at the sugar factory gate as consumed in its production, with an average ratio of 9.7. It has an average GWP of 0.024 eq. t CO₂ per tonne of clean beet harvested, equivalent to 0.0062 eq. t CO₂ per GJ output. The energy input into each scenario was dictated largely by the energy associated with crop nutrition. The smallest energy inputs per hectare were to crops grown under organic conditions or conventional crops grown on fertile soils (clay loam, silt or peat) or sand soil with broiler manure applied. Those crops with the greatest energy input were grown on sand soil that was irrigated and had mineral fertiliser applied. Although the organic scenario grown on sandy loam soil had one of the smallest energy inputs per hectare, the low yield meant that the energy input was similar per tonne of beet harvested to the conventional crops grown on sandy loam soil. The extra distance travelled by organic beet from the farm to the factory increased the energy input per tonne above that of the conventional scenarios. The GWP was smallest for the conventional crops on the fertile peat and silt soils and greatest on the irrigated sand soils and the sandy loam soils. The organic scenario had a similar GWP to the conventional scenarios on sandy loam to the farm gate, although the greater diesel requirement for transport increased the GWP overall. The GWP per GJ of output for sugar beet in England is similar to published values for wheat.     

Effects of elevated CO2 concentration,irrigation and nitrogenous fertilizer application on the growth and yield of spring wheat in semi-arid areas

In this paper, we discuss the effect of elevated CO₂ concentration, irrigation and nitrogenous fertilizer application on the growth and yield of spring wheat in semi-arid areas. A field experiment was conducted at the Dingxi Agricultural Experiment Station during 2000–2002. According to the experimental design, the CO₂ concentration increased to 14.5, 40 and 54.5 μmol mol⁻¹, respectively, by NH₄HCO₃ (involving CO₂) application, direct application of CO₂ gas and combination of fertilizer NH₄HCO₃ plus CO₂ application, which are equal to CO₂ concentration of the Earth's atmosphere in the next 5, 15 and 20 years. The fertilizer application was divided into three levels: application of NH₃NO₃ (250 kg h m⁻²), NH₄HCO₃ (500 kg h m⁻²) and no fertilizer. Irrigation was divided into two levels: with 90 mm irrigation in the growth period and without irrigation. They can be combined as eight treatments. Each treatment was replicated three times. The results showed that elevated CO₂ concentration owing to CO₂ application leads to remarkable increase in leaf area index (LAI) and shoot biomass, and also generates the higher value of leaf area duration (LAD) that can benefit the photosynthesis in the growth stage and yield increase in crop compared than the no CO₂ application treatment. When CO₂ concentration elevated by 14.5, 40 and 54.5 μmol mol⁻¹ with irrigation and fertilization, correspondingly, the grain yield increased by 6.3, 13.1 and 19.8%, respectively, whereas without irrigation and fertilization, the grain yield increased by only 4.2% when CO₂ concentration increased to 40 μmol mol⁻¹. Meanwhile, irrigation and fertilization can result in larger and deeper root system and have significantly positive influences on higher value of root/shoot (R/S) and water use efficiency. The grain yields in irrigation, irrigation plus NH₃NO₃ application and irrigation plus application of NH₄HCO₃ treatments are 73.4, 148.0 and 163.6% higher than that of no-irrigated and no-fertilized treatment, suggesting that both irrigation and fertilizer application contribute to remarkable increase of crop yield. In all treatments, the highest water use efficiency (WUE, 7.24 kg h m⁻² mm⁻¹) and grain yield (3286 kg h m⁻²) consistently occurred in the treatment with 90 mm irrigation plus fertilizer NH₄HCO₃ and elevated CO₂ concentration (54.5 μmol mol⁻¹), suggesting that this combination has an integrated beneficial effect on improving WUE and grain yield of spring wheat. These results may offer help to maintain and increase the crop yields in semi-arid areas.     

Crop yield responses to climate change in the Huang-Huai-Hai Plain of China

Global climate change may impact grain production as atmospheric conditions and water supply change, particularly intensive cropping, such as double wheat-maize systems. The effects of climate change on grain production of a winter wheat-summer maize cropping system were investigated, corresponding to the temperature rising 2 and 5 °C, precipitation increasing and decreasing by 15% and 30%, and atmospheric CO₂ enriching to 500 and 700 ppmv. The study focused on two typical counties in the Huang-Huai-Hai (3H) Plain (covering most of the North China Plain), Botou in the north and Huaiyuan in the south, considering irrigated and rain-fed conditions, respectively. Climate change scenarios, derived from available ensemble outputs from general circulation models and the historical trend from 1996 to 2004, were used as atmospheric forcing to a bio-geo-physically process-based dynamic crop model, Vegetation Interface Processes (VIP). VIP simulates full coupling between photosynthesis and stomatal conductance, and other energy and water transfer processes. The projected crop yields are significantly different from the baseline yield, with the minimum, mean (±standardized deviation, SD) and maximum changes being −46%, −10.3 ± 20.3%, and 49%, respectively. The overall yield reduction of −18.5 ± 22.8% for a 5 °C increase is significantly greater than −2.3 ± 13.2% for a 2 °C increase. The negative effect of temperature rise on crop yield is partially mitigated by CO₂ fertilization. The response of a C3 crop (wheat) to the temperature rise is significantly more sensitive to CO₂ fertilization and less negative than the response of C4 (maize), implying a challenge to the present double wheat-maize systems. Increased precipitation significantly mitigated the loss and increased the projected gain of crop yield. Conversely, decreased precipitation significantly exacerbated the loss and reduced the projected gain of crop yield. Irrigation helps to mitigate the decreased crop yield, but CO₂ enrichment blurs the role of irrigation. The crops in the wetter southern 3H Plain (Huaiyuan) are significantly more sensitive to climate change than crops in the drier north (Botou). Thus CO₂ fertilization effects might be greater under drier conditions. The study provides suggestions for climate change adaptation and sound water resources management in the 3H Plain.     

Evaluating the Crop Water Stress Index and its correlation with latent heat and CO2 fluxes over winter wheat and maize in the North China plain

Plant water status is a key factor impacting crop growth and agricultural water management. Crop water stress may alter canopy temperature, the energy balance, transpiration, photosynthesis, canopy water use efficiency, and crop yield. The objective of this study was to calculate the Crop Water Stress Index (CWSI) from canopy temperature and energy balance measurements and evaluate the utility of CWSI to quantify water stress by comparing CWSI to latent heat and carbon dioxide (CO₂) flux measurements over canopies of winter wheat (Triticum aestivum L.) and summer maize (Zea mays L.). The experiment was conducted at the Yucheng Integrated Agricultural Experimental Station of the Chinese Academy of Sciences from 2003 to 2005. Latent heat and CO₂ fluxes (by eddy covariance), canopy and air temperature, relative humidity, net radiation, wind speed, and soil heat flux were averaged at half-hour intervals. Leaf area index and crop height were measured every 7 days. CWSI was calculated from measured canopy-air temperature differences using the Jackson method. Under high net radiation conditions (greater than 500 W m⁻²), calculated values of minimum canopy-air temperature differences were similar to previously published empirically determined non-water-stressed baselines. Valid measures of CWSI were only obtained when canopy closure minimized the influence of viewed soil on infrared canopy temperature measurements (leaf area index was greater than 2.5 m² m⁻²). Wheat and maize latent heat flux and canopy CO₂ flux generally decreased linearly with increases in CWSI when net radiation levels were greater than 300 W m⁻². The responses of latent heat flux and CO₂ flux to CWSI did not demonstrate a consistent relationship in wheat that would recommend it as a reliable water stress quantification tool. The responses of latent heat flux and CO₂ flux to CWSI were more consistent in maize, suggesting that CWSI could be useful in identifying and quantifying water stress conditions when net radiation was greater than 300 W m⁻². The results suggest that CWSI calculated by the Jackson method under varying solar radiation and wind speed conditions may be used for irrigation scheduling and agricultural water management of maize in irrigated agricultural regions, such as the North China Plain.     

Greenhouse gas implications of water reuse in the Upper Pumpanga River Integrated Irrigation System, Philippines

Enhancing water productivity is often recommended as a “soft option” in addressing the problem of increasing water scarcity. However, improving water productivity, particularly through water reuse, incurs additional investment and may result in increased greenhouse gas (GHG) emissions. In this study, we analysed the water productivity and GHG implications of water reuse through pumping groundwater and creek water, and compare this with gravity-fed canal irrigation in the Upper Pampanga River Integrated Irrigation System (UPRIIS) in the Philippines.Water productivity indicators show that water reuse contributes significantly to water productivity. For example, water productivity with respect to gross inflow (WP_gross) with water reuse (0.19 kg grain/m³) is 21% higher than without water reuse (0.15 kg grain/m³). However, there is a tradeoff between increasing water productivity and water reuse as water reuse increases GHG emissions. The estimated GHG emission from water reuse (pumping irrigation) is 1.47 times higher than without water reuse (gravity-fed canal irrigation). Given increasing concerns about climate change and the need to reduce carbon emissions, we recommend that a higher priority be given to water reuse only in areas where water scarcity is a serious issue.     

Drip irrigation of tea (Camellia sinensis L.): 1. Yield and crop water productivity responses to irrigation

The effects of drip irrigation on the yield and crop water productivity responses of four tea (Camellia sinensis (L.) O. Kuntze) clones were studied four consecutive years (2003/2004-2006/2007), in a large (9 ha) field experiment comprising of six drip irrigation treatments (labelled: I₁-I₆) and four clones (TRFCA PC81, AHP S15/10, BBK35 and BBT207) planted at a spacing of 1.20 m × 0.60 m at Kibena Tea Limited (KTL), Njombe in the Southern Tanzania in a situation of limited water availability. Each clone × drip irrigation treatment combination was replicated six times in a completely randomized design with 144 net plots each with an area of 72 m². Clone TRFCA PC81 gave the highest yields (range: 5920-6850 kg dried tea ha⁻¹) followed by clones BBT207 (5010-5940 kg dried tea ha⁻¹), AHP S15/10 (4230-5450 kg dried tea ha⁻¹) and BBK35 (3410-4390 kg dried tea ha⁻¹) and drip irrigation treatment I₂ gave the highest yields, ranging from 4954 to 6072 kg dried tea ha⁻¹) compared with those from other treatments (4113-5868 kg dried tea ha⁻¹). Most of these yields exceeded those (4200 kg dried tea ha⁻¹) obtained from overhead sprinkler irrigation system in Mufindi also Southern Tanzania, and Kibena Estate itself. Results showed that drip irrigation of tea not only increased yields but also gave water saving benefits of up to 50% from application of 50% less water to remove the cumulative soil water deficit (treatment I₂), and with labour saving of 85% for irrigation. The yield of dried tea per mm depth of water applied, i.e., “the crop water productivity” for drip irrigation of clones TRFCA PC81, BBT207 and BBK35, in 2003/2004 for instance, were 9.3, 8.5 and 7.1 kg dried tea [ha mm]⁻¹, respectively. The corresponding values in 2004/2005 were 2.7, 4.5 and 2.0 kg dried tea [ha mm]⁻¹ while the yield responses from clone AHP S15/10 were linear decreasing by 1 and 1.6 kg dried tea [ha mm]⁻¹ in 2003/2004 and 2004/2005, respectively. In 2005/2006 the crop water productivity from clones TRFCA PC81, AHP S15/10, BBK35 and BBT207 were 4.5, 0.4, 5.2 and 6.9 kg dried tea [ha mm]⁻¹, respectively with quadratic yield response functions to drip irrigation depth of water application. The results are presented and recommendations and implications made for technology-transfer scaling-up for increased use by large and smallholder tea growers.