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.     

Pasture and forage crop systems for non-irrigated dairy farms in southern Australia. 2. Inter-annual variation in forage supply,and business risk

Inter-annual climatic variability poses a substantial management and profitability challenge for pasture-based dairy producers in southern Australia. The effects of a range of seasonal scenarios on the production and profit of non-irrigated dairy farm systems using several different forage bases were investigated for two regions in southeast Australia using a systems modeling approach. For the Terang district, seasonal scenarios were constructed around combinations of early, average or late autumn rains, and short, average or long spring flushes. For the higher-rainfall Ellinbank district, scenarios were constructed around either above- or below-average summer–autumns or winter–springs.     

Pasture and forage crop systems for non-irrigated dairy farms in southern Australia. 1. Physical production and economic performance

The dairy industry in southern Australia relies on perennial ryegrass pasture to supply 60–70% of the diet of lactating cows. Improvements in the amount and quality of home-grown forage used for dairy cow feeding are critical for further productivity gains in the industry. A modeling approach was used to estimate the effects of changing the forage system on farm business profit. Base models (using 100% of farm area in perennial ryegrass pasture) were constructed for above-average (Top 40%) and high performing (Top 10%) farm types typical of two locations: Terang in southwest Victoria and Ellinbank in Gippsland, eastern Victoria. These models were then re-simulated using different forage base options such as: oversowing annual ryegrass, winter crops (annual ryegrass monoculture, winter cereal grown for whole crop silage), summer crops (grazing brassicas, maize), combinations of these (double cropping), or summer shoulder pasture (notionally based on tall fescue) on between 10% and 100% of farm area.     

Farm types for beef production and their economic success in a mountainous province of northern Vietnam

The objective of this study was to compare the management and economic success of beef production by three types of farm in northwestern Vietnam. The potential of household farms to supply beef for the market and their competition with large farms were examined.The fieldwork was done in 2007 on 73 farms consisting of 58 small mixed farms (small farms), 10 medium mixed farms (medium farms) and 5 specialised large-scale beef farms (large farms) in Son La province. The three types of farm differed in ethnicity (Thai, H’mong, and Kinh), remoteness (lowland, highland), production objectives (subsistence, market output), degree of specialization (mixed farm, specialised beef farm) and integration of production (single farmers, cooperative). Data on biological productivity, inputs and outputs, and the social contribution of cattle production were collected by household and key person interviews, participatory rural appraisal tools and cattle body measurements. Economic values were derived by assessment of market or replacement costs. Quantitative data analysis was done with linear models (PROC GLM) in the SAS software (version 9.1).Lowland small farms had higher costs for cattle production than the highland farms (0.8 Mill. VND head⁻¹ year⁻¹ compared with 0.02 Mill. VND head⁻¹ year⁻¹, respectively). The large farms had high production costs, with an average of 2.5-3.6 Mill. VND head⁻¹ year⁻¹. Cattle brought high benefits of non-cash values to the household farms. The total revenue from cattle was in the range 4.5-11.5 Mill. VND head⁻¹ year⁻¹, which depended on the use of non-market functions of cattle on the household farm. The value of net benefit/kg live weight (LW) of lowland small farms with an average of 39,000 VND/kg LW was significantly higher than that of the medium and small farms in the highlands (26,000 VND/kg LW). However, the small farms kept fewer cattle than the medium farms (average of 2-4 cattle/farm compared with 9 cattle/farm, respectively) because of forage and labour shortages and have no option to further develop cattle production. Keeping larger numbers of cattle based on available natural pasture brought high benefit from stock value as farm liquidity to only the medium farms. This was the most promising type of farm for future development of beef production, given its actual success and the availability of underutilised resources. Large-scale farms suffered high economic losses of 0.3-1.4 Mill. VND cattle⁻¹ year⁻¹, due to the lack of professional management, high feed costs and low animal performance, and showed no potential for developing cattle production.     

Modelling the fate of water and nitrogen in the mixed vegetable farming systems of northern Tasmania, Australia

A combination of high input management systems, high annual rainfall and deep, permeable soils in northern Tasmania create conditions that are conducive to high drainage and nitrogen losses below the root zone. An understanding of the extent and mechanism of such losses will enable farm managers and their consultants to identify and implement more sustainable management practices that minimise potential adverse financial and environmental consequences. Analysing the fate of water and nutrients in farming systems is complex and influenced by a wide range of factors including management, soil characteristics, seasonal climate variability and management history of the paddock/farm in question. This paper describes a novel farm system modelling approach based on the model APSIM, for analysing the fate of nitrogen and water in mixed vegetable-based farming enterprises. The study was based on seven case farms across the Panatana catchment in northern Tasmania. Substantial simulated drainage losses (>100 mm average seasonal loss) were apparent for all crop and rotation elements across all farms in response to the surplus between crop water supply and crop water use. Crop nitrogen demand was found to be close to crop nitrogen supply for all crop and pasture rotation elements with the exception of potato, which had an average surplus nitrogen supply of 89 kg N/ha. This resulted in potato having much higher nitrate nitrogen leaching losses (32 kg N/ha) compared to other crops (<10 kg N/ha). Simulations suggest that practicable management options such as deficit-based irrigation and reduced N fertiliser rates will maintain current levels of productivity while reducing potential offsite N loss and generating significant financial savings via reduced input costs.     

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.     

Identifying and controlling critical sources of farm phosphorus imbalances for Vermont dairy farms

Lake Champlain, located between Vermont, New York, and Quebec exhibits eutrophication mainly due to continuing phosphorus (P) losses from upstream nonpoint source areas. Several state and local agencies have initiated efforts aimed at assessing and identifying critical sources areas for P loss. To augment these efforts, accounting of farm P inputs (in purchased animal feed and fertilizers) and P outputs (in milk, meat, or off-farm sales of harvested crops or other products) is needed as a means of determining potential P build-up in farm soils. When farm P inputs exceed P outputs, P surplus occurs on the farm. This leads to potential soil-P accumulations and risk of P loss in runoff, negatively impacting the quality of receiving water bodies. In this study, a combination of farm record data and a model-based approach, using the Integrated Farming System Model (IFSM), was used to estimate farm P inputs and outputs, identify root causes of farm P imbalances, and explore viable P balancing strategies. Three Vermont dairy farms with varying farm systems (grass-based organic farm, fully confined farm, and a mixed system farm with high-producing confined dairy cows and grazing heifers) were studied. These farms were found to have P surpluses ranging from 5.5 kg/ha to 18.7 kg/ha on annual basis. This study also identified critical causes of P imbalances for each farm and suggested farm specific alternative strategies needed to address the P imbalances. By balancing farm P inputs and outputs, potential accumulation of soil-P can be prevented. As a result, maximum benefits can be obtained from land treatment measures implemented to control off-field P loss without the additional concern of continuing P build-up that could reduce their effectiveness.     

Adaptation and evaluation of the integrated farm system model to simulate temperate multiple-species pastures

Whole-farm simulation provides a tool for predicting the effects of farm management strategies on farm productivity and profitability. One such model, the Integrated Farm System Model (IFSM), was modified to allow representation of up to four forage species coexisting in a pasture mixture. The model was calibrated to simulate net herbage accumulation (NHA) observed during six periods of a 2002 experiment in a 3-species pasture in Pennsylvania, USA, composed of orchardgrass (Dactylis glomerata L.), white clover (Trifolium repens L.), and chicory (Cichorium intybus L.). The model also predicted sward botanical composition, total annual NHA, crude protein (CP), and neutral detergent fiber (NDF). Sensitivity analysis showed that predictions of NHA were most sensitive to both chicory and orchardgrass specific leaf area and partitioning of photosynthate to the shoot, as well as chicory photosynthetic efficiency. The model was evaluated against data from the same 3-species pasture in 2003 as well as a 2-species pasture (lacking chicory) from the same experiment in 2002 and 2003. Predictions of total annual NHA in 2- and 3-species pastures were within ±18% of observed values, though predictions of within-season NHA were less accurate. Predictions of botanical composition tended to remain within ±15% of observed values by species. Predictions of within-season CP and NDF concentrations in the whole sward tended to remain within ±22% and ±15%, respectively. Given the generality and realism required of IFSM, the degree of precision in the modified pasture submodel is acceptable for achieving IFSM’s primary goal of comparing the effects of different management scenarios on forage productivity and the long-term profitability and environmental impact of farms.     

A bio-economic evaluation of the profitability of adopting subtropical grasses and pasture-cropping on crop-livestock farms

Pasture-cropping is a novel approach to increasing the area of perennial forages in mixed livestock and cropping systems. It involves planting annual cereals directly into a living perennial pasture. There is interest in using subtropical grasses for pasture-cropping as they are winter dormant and their growth profile is complementary with winter crops. The ability of subtropical grasses to maintain feed quality in summer is likely to be an important attribute. However, a wide range of factors can affect the uptake of such systems. This paper evaluates the farm-system economics of subtropical grasses and pasture-cropping. The research question is: what factors affect the profitability of a new technology such as (1) subtropical grass and (2) subtropical grass that is pasture-cropped. The analysis uses the MIDAS model of a central wheatbelt farm in Western Australia. The results suggest the profitability and adoption of subtropical grasses is likely to be strongly influenced by the mix of soil types present on the farm; the feed quality of the subtropical grass; whether the production emphasis of the farm is for grazing or cropping, and the level of production in summer and early autumn. The same factors are relevant to pasture-cropping, with the addition of yield penalties due to competition between the arable crop and the host perennial. The results were less sensitive to changes in the winter production of subtropical grass. Pasture-cropping was more profitable and likely to involve a larger area of the farm when a meat rather than a wool-dominant sheep system was present. However, there was little difference between the meat and wool flocks in their sensitivity to other factors in this analysis.     

Sensitivity to information upscaling of agro-ecological assessments: Application to soil organic carbon management

Upscaling of agro-ecological indicators applied in regional analyses is sensitive to scale issues of the input data. This study develops a methodology to quantify this sensitivity for an indicator of soil organic carbon (SOC) dynamics at the farming system level. A reference case consists of seven fully described farms in northern Italy. Both upscaling in complexity by substituting measured input with estimated input and upscaling in space by extending the methods to farms not included in the reference case are addressed. The indicator increased with 3-107% at four farms after substituting measured management input with that estimated by an expert, whereas it remained unchanged or decreased at the other three farms. Taking the modal value from a cluster of pedological input did not lead to additional uncertainty in most cases, and only slightly increased it in others. We evaluated spatial upscaling by including 733 farms divided in 18 clusters that were described with less information as compared to the reference farms. Within each cluster, we observed relevant variability of the indicator (coefficients of variation of 12-43%), as a consequence of the heterogeneity of farms comprised in each cluster. In each cluster we calculated the indicator for one virtual farm, defined by using modal values for basic farm inputs. In this case the indicator was highly correlated (R² = 0.98) with the average of the values obtained using measured basic farm inputs. We conclude that upscaling in complexity and space introduces uncertainty in the values of the indicator compared to the reference case. The extent of such differences depends on the variability of the systems under analysis and on indicator sensitivity.     

The diversity of rural livelihoods and their influence on soil fertility in agricultural systems of East Africa - A typology of smallholder farms

Technological interventions to address the problem of poor productivity of smallholder agricultural systems must be designed to target socially diverse and spatially heterogeneous farms and farming systems. This paper proposes a categorisation of household diversity based on a functional typology of livelihood strategies, and analyses the influence of such diversity on current soil fertility status and spatial variability on a sample of 250 randomly selected farms from six districts of Kenya and Uganda. In spite of the agro-ecological and socio-economic diversity observed across the region (e.g. 4 months year⁻¹ of food self-sufficiency in Vihiga, Kenya vs. 10 in Tororo, Uganda) consistent patterns of variability were also observed. For example, all the households with less than 3 months year⁻¹ of food self-sufficiency had a land:labour ratio (LLR) < 1, and all those with LLR > 1 produced enough food to cover their diet for at least 5 months. Households with LLR < 1 were also those who generated more than 50% of their total income outside the farm. Dependence on off/non-farm income was one of the main factors associated with household diversity. Based on indicators of resource endowment and income strategies and using principal component analysis, farmers’ rankings and cluster analysis the 250 households surveyed were grouped into five farm types: (1) Farms that rely mainly on permanent off-farm employment (from 10 to 28% of the farmers interviewed, according to site); (2) larger, wealthier farms growing cash crops (8-20%); (3) medium resource endowment, food self-sufficient farms (20-38%); (4) medium to low resource endowment relying partly on non-farm activities (18-30%); and (5) poor households with family members employed locally as agricultural labourers by wealthier farmers (13-25%). Due to differential soil management over long periods of time, and to ample diversity in resource endowments (land, livestock, labour) and access to cash, the five farm types exhibited different soil carbon and nutrient stocks (e.g. Type 2 farms had average C, N, P and K stocks that were 2-3 times larger than for Types 4 or 5). In general, soil spatial variability was larger in farms (and sites) with poorer soils and smaller in farms owning livestock. The five farm types identified may be seen as domains to target technological innovations and/or development efforts.     

Competing use of organic resources, village-level interactions between farm types and climate variability in a communal area of NE Zimbabwe

In communal areas of NE Zimbabwe, feed resources are collectively managed, with herds grazing on grasslands during the rainy season and mainly on crop residues during the dry season, which creates interactions between farmers and competition for organic resources. Addition of crop residues or animal manure is needed to sustain agricultural production on inherently poor soils. Objectives of this study were to assess the effect of village-level interactions on carbon and nutrient flows, and to explore their impact on the long-term productivity of different farm types under climate variability. Crop and cattle management data collected in Murewa Communal area, NE Zimbabwe was used together with a dynamic farm-scale simulation model (NUANCES-FARMSIM) to simulate village-level interactions. Simulations showed that grasslands support most cattle feed intake (c. 75%), and that crop residues produced by non-cattle farmers sustain about 30% of the dry season feed intake. Removal of crop residues (0.3-0.4 t C ha⁻¹ yr⁻¹) from fields of non-cattle farmers resulted in a long-term decrease in crop yields. No-access to crop residues of non-cattle farmers increased soil C modestly and improved yields in the long-term, but not enough to meet household energy requirements. Harvest of grain and removal of most crop residues by grazing cattle caused a long-term decline in soil C stocks for all farm types. The smallest decrease (−0.5 t C ha⁻¹) was observed for most fertile fields of cattle farmers, who manure their fields. Cattle farmers needed to access 4-10 ha of grassland to apply 3 t of manure ha⁻¹ yr⁻¹. Rainfall variability intensifies crop-livestock interactions increasing competition for biomass to feed livestock (short-term effect) or to rehabilitate soils (long-term effect). Prolonged dry seasons and low availability of crop residues may lead to cattle losses, with negative impact in turn on availability of draught power, affecting area under cultivation in consecutive seasons until farmers re-stock. Increasing mineral fertiliser use concurrently with keeping crop residues in fertile fields and allocating manure to poor fields appears to be a promising strategy to boost crop and cattle productivity at village level. The likelihood of this scenario being implemented depends on availability of fertilisers and decision of farmers to invest in rehabilitating soils to obtain benefits in the long-term. Adaptation options cannot be blind to what occurs beyond field and farm level, because otherwise recommendations from research and development do not fit the local conditions and farmers tend to ignore them.     

Raising surface water levels in peat areas with dairy farming: Upscaling hydrological, agronomical and economic effects from farm-scale to local scale

Raising surface water levels in peat areas is a measure to reduce soil subsidence, to prevent decay of wooden foundations and to stimulate wet nature restoration and reduce greenhouse gas emissions. However, in these areas dairy farms are present and farming at wetter soils is difficult due to lower bearing capacity of the soil for cattle and machines. Water boards are responsible for the water management of peat areas and thus have to evaluate the effects of water management strategies for the different land use functions. Therefore the hydrological, agronomical and economic effects of different surface water levels are calculated for dairy farms. The ‘Waterpas’ model is used to simulate hydrological effects, dairy farm management and economic results for different meteorological years. The raised surface water level causes a decrease in gross grass yield and a reduction in grass quality. This leads to higher costs and less farmers’ income relative to a reference situation with a freeboard of 60 cm. Raising the surface water increases the average costs for farmers with €89 ha⁻¹ year⁻¹ for a freeboard of 50 cm, €170 ha⁻¹ year⁻¹ for a freeboard of 40 cm and €239 ha⁻¹ year⁻¹ for a freeboard of 30 cm.However, water boards are not only interested in the effects for individual farms, but also for an entire region. A new spatial method was developed for upscaling from farm to polder level. For grassland fields in a typical Dutch peat area classes can be distinguished using GIS data on soil type, soil surface elevation, surface water levels, locations of farms and farm characteristics. The classification is based on 4 classes of freeboards of the grassland fields and 7 typical distributions of grassland fields within a dairy farm. The farm economics were simulated for these typical classes. An increase in costs was simulated for the whole polder Zegveld (1400 ha grassland) of €119,000 year⁻¹ at 10 cm surface water level rise; €133,000 year⁻¹ at 20 cm surface water level rise and €185,000 year⁻¹ at 30 cm surface water level rise.For an integral environmental evaluation of changing hydrological conditions it is advised to incorporate effects on nutrient emission to groundwater and surface water and emission of ammonia and greenhouse gases to the atmosphere.     

Economic and environmental evaluation of three goal-vision based scenarios for organic dairy farming in Denmark

The objective of this study was to explore the sustainability of future organic dairy farming systems in Denmark, by evaluating the economic and environmental consequences of three scenarios at the farm level based on different visions of future sustainability leading to different farm-based goals. The future sustainable organic dairy farming systems were deduced from participative sessions with stakeholders, and used to define specific scenarios and related key parameters. Parameterization of the scenarios was based on model simulations and the invoking of expert knowledge. Each scenario was designed to fulfil different aspects of sustainability. The business as usual scenario (BAU) was driven by economic incentives and implemented new technologies and measures to enhance productivity and efficiency. This scenario was expected to be the mainstream strategy of future organic dairy production in Denmark. In the animal welfare scenario (ANW), economic efficiency was subordinate to animal welfare, and measures to improve animal welfare, such as lower milk yield, extra grazing area and a deep-litter barn, were incorporated. The environmental scenario (ENV) was designed to minimize N losses into the environment, reduce emission of greenhouse gases and the use of fossil energy, and was based on self-sufficiency regarding nutrients and feed. The economic evaluation of the scenarios was based on quantification of farm profitability (i.e. net profit), whereas environmental evaluation was based on the quantification of the N-surplus per ha, emission of greenhouse gases, and use of fossil energy per kg energy-corrected milk (ECM).Compared to prolonging the current main stream strategy (BAU), the evaluation of scenarios revealed that investing in animal welfare comprised trade-offs regarding farm profitability, climate change and the use of fossil energy. In ANW, net profit per farm was almost 39 k€ lower than in BAU, whereas emission of greenhouse gases and energy per kg ECM was 8% and 3% higher, respectively. Minimizing environmental impact in ENV reduced local as well as global environmental impact without an economic trade-off. Greenhouse gas emission per kg ECM was 5% lower and fossil energy use was 11% lower than in BAU. The N-surplus of ENV was 80 kg per ha, whereas the N-surplus was approximately 116 in both BAU and ANW. Prolonging the current main stream strategy (BAU) resulted in a high local environmental impact, a moderate global environmental impact and a high economic risk related to changes in milk price or costs.     

Heterogeneity of crop productivity and resource use efficiency within smallholder Kenyan farms: Soil fertility gradients or management intensity gradients?

The decrease in crop yields at increasing distances from the homesteads within smallholder farms of Sub-Saharan Africa (SSA) is normally ascribed to the existence of within-farm soil fertility gradients. Field observations also suggest that a large part of such variability is concomitantly caused by poor agronomy. To understand the interaction between soil fertility (S factors) and management decisions (M factors) affecting crop variability, we combined field research conducted in western Kenya (Vihiga, Kakamega and Teso districts; rainfall: 1600, 1800 and 1200 mm, respectively) with explorations using the simple dynamic crop/soil model for dynamic simulation of nutrient balances, previously tested for the region. Field measurements indicated within-farm differences in average maize grain yields of 48% (2.7 vs. 1.4 t ha⁻¹) in Vihiga and of 60% (1.5 vs. 0.6 t ha⁻¹) in Teso, between fields that were close and far from the homestead, respectively. Extreme values ranged widely, e.g. between 4.9 and 0.3 t ha⁻¹ for all the farms surveyed in Vihiga, where the average farm size was 0.6 ha. Maize grain yields tended to increase with increasing contents of soil C, total N, extractable P and exchangeable bases. However, the negative relationship between S factors and distance from the homestead was not as strong as expected, and yield variability was better explained by multiple regression models considering M factors such as planting date, plant density, resource use and weed infestation (40–60% across sites). Then, we analysed the variation in resource (cash, labour, N) use efficiency within farms of different resource endowments with the aid of the simulation model. N balances at plot scale varied from ca. +20 to −18 kg ha⁻¹, from −9 to −20 kg ha⁻¹ and from −16 to −18 kg ha⁻¹ for the different fields of the high, medium and low resource endowment case-study farms, respectively. Labour productivities ranged between ca. 10 and 38 kg grain man-day⁻¹ across field and farm types. The results indicate the need of considering within farm heterogeneity when designing soil fertility management interventions. Resource use efficiency was strongly affected by soil quality. As farmers invest more effort and resources in the more productive and less risky fields, the interaction between S and M factors leads to farmer-driven resource use efficiency gradients within smallholder farms.     

The profitability and risk of dairy cow wintering strategies in the Southland region of New Zealand

A survey amongst stakeholders in 2007 identified wintering systems with less environmental impact and a reliable supply of high quality feed, which are cost effective and simple to implement, as one of the top three issues requiring research and demonstration in the Southland region of New Zealand. This study used a modelling approach to examine the cost effectiveness, exposure to climate-induced risk and major economic drivers of four selected wintering strategies, i.e. (1) grazing a forage brassica crop on support land (Brassica system), (2) grazing pasture on support land (All pasture system), (3) cows fed grass silage, made on the support land, on a loafing pad where effluent is captured (Standoff system), and (4) cows fed grass silage, made on the support land, in a housed facility where effluent is captured (Housed system). The model was driven by virtual climate data generated by the National Institute of Water and Atmospheric Research and economic input data from the DairyNZ Economics Group for the 08/09 season with a milk price of NZ$4.55¹/kg milksolids (fat + protein). The Housed system had the highest average (± STDEV) operating profit (profit after depreciation but before interest charges) over 35 independently simulated climate years (NZ$743 ± 122/ha), followed by All pasture (NZ$681 ± 197/ha), Standoff (NZ$613 ± 135/ha) and Brassica (NZ$599 ± 212/ha). This ranking was sensitive to the assumptions and treatment of capital costs. The Housed system was the least exposed to climate-induced risk with a coefficient of variation of operating profit of 16% compared to 35% of the Brassica system. The four systems demonstrated different financial strengths and weaknesses that largely balanced out in the end. The Brassica system is a high risk system from an environmental perspective and the All pasture system an unlikely alternative because of scarcity of suitable land. Both the Housed and Standoff systems appear to be cost effective alternatives that allow high control over cow feeding, body condition and comfort over winter. Furthermore, both systems have the potential to provide high control over the storage and release of animal effluent onto land, thus saving fertiliser costs and reducing environmental footprint.     

Factors influencing potential scale of adoption of a perennial pasture in a mixed crop-livestock farming system

Evaluating the potential scale of adoption of a technological innovation or management practice at the farm business scale can help gauge the potential size of an industry for the purposes of prioritising resources for research and development. In this paper we address the question of quantifying the potential area of adoption of a perennial pasture, lucerne (Medicago sativa L.), in dryland mixed farming systems in Australia. Lucerne pastures play a significant role in dryland farming systems in the wheat-sheep zone of southern and western Australia. While there are benefits of integrating lucerne into cropping systems there will inevitably be additional costs, and the scale of adoption of lucerne will depend largely on the increase in farm profit resulting from the introduction of lucerne. Whole-farm economic models of representative farms in the Australian wheat-sheep belt were used to determine the key drivers for the scale of adoption of lucerne.For a particular farming system the optimal area of lucerne which maximises whole-farm profit is found to depend on production, price and cost conditions. Generally, no more than 30% of a farm was allocated to lucerne according to those conditions and location of the farm. For most scenarios examined the response of profit was flat around the optimal area. This implies that lucerne could be grown on areas greater than the optimum, in order to reduce groundwater recharge (and thereby reduce the risk of dryland salinity), without greatly reducing whole-farm profit. The optimal area of lucerne in all regions was limited by the area of suitable soil types and proportion of lucerne in the most profitable lucerne-crop sequences.At all price levels assumed in this study lucerne remained as part of the optimal enterprise mix for all farm types examined. Lucerne productivity was also a major determinant of the optimal area of lucerne. The sensitivity of profit to changes in winter and/or summer production varied between regions and for different livestock enterprises. The differences were driven by the timing of energy demands and supply of feed in individual farming systems.In all regions the optimal area and profitability of lucerne varied with livestock enterprise. The analyses showed that changing from wool production to meat production enabled greater economic benefit to be realised from lucerne. This was consistent across farm types and demonstrated the value of lucerne as a source of high quality feed for finishing prime lambs in summer.The results of this study demonstrate that lucerne is profitable in a range of environments on a significant proportion of the farm area, but that this area is small relative to that required to significantly influence in its own right the environmental issue of salinity.     

Policy incentives for reducing nitrate leaching from intensive agriculture in desert oases of Alxa, Inner Mongolia, China

Excessive irrigation and nitrogen applications result in substantial nitrate leaching into groundwater in intensively cropped oases in desert areas of Alxa, Inner Mongolia. An integrated modelling approach was developed and applied to compare policy incentives to reduce nitrate leaching. The integrated model consists of a process-based biophysical model, a meta-model, a farm economic model and an assessment of policy incentives. The modelling results show that there are “win-win” opportunities for improving farm profitability and reducing nitrate leaching. We found that 4471 Yuan ha⁻¹ of farm gross margin could be obtained with a reduction in nitrate leaching of 373 kg ha⁻¹. Farmers’ lack of knowledge about water and nitrogen in soil, and on crop requirements for water and nitrogen could explain the differences, so that agricultural extension is an appropriate policy incentive for this area. When the economic optimum is obtained reductions in nitrate leaching are not achievable without profit penalties and there is a “trade-off” relationship between farm profitability and groundwater quality protection. The combination of low elasticity of nitrate leaching and large elasticity of farm gross margin against water price increases results in very high costs for reducing nitrate leaching (105.6 Yuan kg⁻¹). It is suggested that if the water price increases were coupled with subsidies for adopting nitrate leaching mitigation practices, environmental gains could come at a lower cost.     

Evaporative water use of different land uses in the upper-Thukela river basin assessed from satellite imagery

Evaporative water use of various land use classes in the upper-Thukela river basin was estimated using the public domain version of the Surface Energy Balance Algorithm for Land (SEBAL) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images. Twenty eight images were analyzed covering the period between June 2005 and September 2006. The South Africa land use map developed in the year 2000 was used to compute the evaporative water use of the various land uses in 13 Quaternary Catchments (QCs) in the upper-Thukela river basin.There was a good correlation between the SEBAL estimates of total evaporation and ground measurements from a Large Aperture Scintillometer installed at a site in one of the QCs in the study area. It was observed that the land uses that generated relatively large volumes of evaporative water were forestry (i.e. Eucalyptus, Pine, mixed species & indigenous), “water bodies” (i.e. water supply reservoirs, farm reservoirs) and wetlands. Total evaporation rates for all land use classes were high during the summer season (wet), with Eucalyptus ranging between 3 mm d⁻¹ during the winter season (dry) and about 5 mm d⁻¹ during the summer season. Bare rocks and eroded soil surface land use class had the least evaporative water use i.e., less than 1 mm d⁻¹. The relatively low evaporation rates over “water bodies” during the dry winter season could be attributed to the averaging of mixed pixels (wet and dry) due to change in areal coverage and which could not be captured in the 1 km × 1 km low resolution MODIS images. Thus, the potential for applying remote sensing techniques, using low resolution satellite images, to quantify water use by various land uses in the Thukela river basin was explored with promising results.     

Ten consecutive years of regulated deficit irrigation probe the sustainability and profitability of this water saving strategy in loquat

The successful application of postharvest regulated deficit irrigation (RDI) over ten consecutive years (from season 1999/2000 to season 2007/2008) confirms the sustainability of this strategy for producing ‘Algerie’ loquat. Postharvest RDI consisting in a reduction of watering (between 45 and 80% depending on the season) from early June until the end of August, improved loquat profitability by increasing fruit value and by reducing water consumption with respect to fully irrigated trees (control). The increase in fruit value in RDI trees was due to a consistent improvement in harvest earliness as a result of an earlier blooming. Water savings of around 20% did not diminish yield nor fruit quality. Water use efficiency in RDI trees rose by over 30%. Water productivity reached 9.5 € m⁻³ of water applied in RDI trees versus 6.6 € m⁻³ in control trees. The most noticeable effect of RDI on vegetative growth was a significant and progressive decline in trunk growth. The canopy volume seems to be strongly influenced by pruning and no significant effects were detected in this parameter. Our results confirm the suitability of RDI in loquat and the economic benefits of saving water during the summer.