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.     

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.     

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.     

Bio-economic evaluation of farmers’ perceptions of viable farms in western Kenya

Arable land in western Kenya is under considerable pressure from increasing human population. Rural households depend on farming for at least part of their livelihood, and poverty rates are among the highest in Kenya. Land is often depleted of nutrients, and for most farmers, access to inputs and markets is poor. There is a need to identify options that are manageable within the context of the farmer’s resource base and the household’s objectives that could improve farm household well-being. In this study we integrated qualitative informal participatory approaches with quantitative mathematical programming and biophysical simulation modelling. Households in four sub-locations in Vihiga District were clustered and pilot cases identified. Meetings were held with farmers to elicit their perceptions of what their ideal farm would look like, and how its performance might compare with their own farm’s performance. With farmers’ help, a range of scenarios was analysed, relating to changes in current enterprise mixes, changes in current farm sizes, and changes in prices of staples foods and cash crops. A considerable mismatch was found between farmers’ estimates of their own farm’s performance, and what was actually produced. There seems to be a threshold in farm size of 0.4 ha, below which it is very difficult for households to satisfy their income and food security objectives. Even for larger farms whose households are largely dependent on agriculture, the importance of a cash crop in the system is critical. There is a crucial role for extension services in making farmers aware of the potential impacts on farm revenue of modest changes in their farm management systems. We are monitoring nine households in the district, whose farmers have made some changes to their system in an attempt to increase household income and enhance food security.     

Communicating complexity: Integrated assessment of trade-offs concerning soil fertility management within African farming systems to support innovation and development

African farming systems are highly heterogeneous: between agroecological and socioeconomic environments, in the wide variability in farmers’ resource endowments and in farm management. This means that single solutions (or ‘silver bullets’) for improving farm productivity do not exist. Yet to date few approaches to understand constraints and explore options for change have tackled the bewildering complexity of African farming systems. In this paper we describe the Nutrient Use in Animal and Cropping systems - Efficiencies and Scales (NUANCES) framework. NUANCES offers a structured approach to unravel and understand the complexity of African farming to identify what we term ‘best-fit’ technologies - technologies targeted to specific types of farmers and to specific niches within their farms. The NUANCES framework is not ‘just another computer model’! We combine the tools of systems analysis and experimentation, detailed field observations and surveys, incorporate expert knowledge (local knowledge and results of research), generate databases, and apply simulation models to analyse performance of farms, and the impacts of introducing new technologies. We have analysed and described complexity of farming systems, their external drivers and some of the mechanisms that result in (in)efficient use of scarce resources. Studying sites across sub-Saharan Africa has provided insights in the trajectories of change in farming systems in response to population growth, economic conditions and climate variability (cycles of drier and wetter years) and climate change. In regions where human population is dense and land scarce, farm typologies have proven useful to target technologies between farmers of different production objectives and resource endowment (notably in terms of land, labour and capacity for investment). In such regions we could categorise types of fields on the basis of their responsiveness to soil improving technologies along soil fertility gradients, relying on local indicators to differentiate those that may be managed through ‘maintenance fertilization’ from fields that are highly-responsive to fertilizers and fields that require rehabilitation before yields can improved. Where human population pressure on the land is less intense, farm and field types are harder to discern, without clear patterns. Nutrient cycling through livestock is in principle not efficient for increasing food production due to increased nutrient losses, but is attractive for farmers due to the multiple functions of livestock. We identified trade-offs between income generation, soil conservation and community agreements through optimising concurrent objectives at farm and village levels. These examples show that future analyses must focus at farm and farming system level and not at the level of individual fields to achieve appropriate targeting of technologies - both between locations and between farms at any given location. The approach for integrated assessment described here can be used ex ante to explore the potential of best-fit technologies and the ways they can be best combined at farm level. The dynamic and integrated nature of the framework allows the impact of changes in external drivers such as climate change or development policy to be analysed. Fundamental questions for integrated analysis relate to the site-specific knowledge and the simplification of processes required to integrate and move from one level to the next.     

A method for exploring sustainable development options at farm scale: a case study for vegetable farms in South Uruguay

The methodology presented in this paper aims at analysing whether there is room for improvement of vegetable farmers’ income in Canelón Grande (Uruguay), while reducing soil erosion and improving physical and biological soil fertility, and to gain insight in the influence of farmers’ resource availability on the opportunities for sustainable development. The (generic) approach we developed to support re-design of farming systems in this region is unique in dealing with complex temporal interactions in crop rotations and spatial heterogeneity on farms in one integrated method, while revealing trade-off between economic and environmental objectives. Rather than an arbitrary sub-set, all feasible crop rotations were generated, using a tool named ROTAT. The crop rotations were combined with a range of production techniques according to pre-defined design criteria to create a wide variety of alternative production activities at the field scale. We used process-based simulation models supplemented with empirical data and expert knowledge to quantify inputs and outputs of production activities. We developed a mixed integer linear programming model (MILP), named Farm Images, to allocate production activities to a farm with land units differing in soil quality, while maximising or minimising socio-economic and environmental objectives, subject to constraints at the farm level. Production activities comprised current practices as well as activities new to the area. We used Farm Images to design farm systems for seven existing farms in Canelón Grande with different resource availability. The farm systems designed by the model had higher family income than current systems for six of the seven farms studied. The estimated average soil erosion per ha decreased by a factor of 2–4 in the farm systems proposed compared to the current systems, while the rate of change of soil organic matter increased from negative in the current systems to +130 to +280 kg ha⁻¹ yr⁻¹ in the proposed farm systems. The degree to which the objectives could be achieved was strongly affected by farm resource endowment, i.e., particularly by the fraction of the area irrigated, soil quality and labour availability per ha. The study suggests that decreasing the area of vegetable crops by introducing long crop rotations with pastures and green manure during the inter-crop periods and integrating beef cattle production into the farm systems would often be a better strategy than the actual farmers’ practice.     

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.     

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.     

Pasture and forage crop systems for non-irrigated dairy farms in southern Australia: 3. Estimated economic value of additional home-grown feed

Dairy systems in southern Australia rely on grazed feed from pasture to supply between 50% and 70% of total herd feed requirements on an annual basis. However, the dominant pasture type in the region, which is based on perennial ryegrass (Lolium perenne), commonly results in feed deficits in summer which must be filled with supplements purchased off-farm, and feed surpluses in spring which must be conserved. Both of these strictures impose costs on farm businesses. It is likely, therefore, that additional grazeable feed available to dairy herds in southern Australia may have different economic value when interactions between season, stocking rate, calving date, and locality are taken into account. The analysis reported in this paper aimed to estimate, using the farm systems simulation model UDDER, the effect of these interactions on the efficiency with which extra feed can be converted to extra milk production, and therefore the possible gross economic value of the additional feed.‘Base’ farm simulations for ‘average’ and ‘top 10%’ farms (ranked according to farm profitability) in two localities (Terang: average annual rainfall 796 mm, 8 month growing season; and Ellinbank: average annual rainfall 1085 mm, 9-10 month growing season) were created to mimic the physical production and profitability of these farms as seen in regional farm benchmark datasets. These simulations were then altered to add the equivalent of 10% of the total annual herbage accumulation used in the Base simulation either on a pro-rata basis all year round, or in autumn only, in winter only, in spring only, or in summer only. The additional feed amounted to 620 and 780 kg DM/ha for Terang average and top 10% farms respectively, and 735 and 905 kg DM/ha for Ellinbank average and top 10% farms respectively. The management policies used in the Base simulations were then adjusted to harvest as much of the extra feed as possible, either by direct grazing or through silage conservation, while keeping the key system state indicators of cow condition score and average farm pasture cover within the limits known to result in long-term sustainable production.The efficiency with which extra feed was utilised was greatest in summer in all scenarios (80-100% of the extra feed supplied was harvested, all by direct grazing). This translated into consistently high gross economic returns of between $0.26 and $0.34 per kg DM of extra feed added to the model. Utilisation efficiency was lower in all other seasons and/or required marked increases in silage conservation, both of which resulted in lower gross economic returns per kg DM of additional feed. The impact of interactions between locality, season, stocking rate (higher in top 10% farm simulations than average farm simulations) and calving date (earlier at Terang than at Ellinbank) were clearly captured in the model. These interactions have very large effects on the profitability of growing extra feed at different times of the year. Agronomic research for the southern Australia dairy industry should focus on low-cost ways for supplying additional grazeable feed in summer, since current forage species options for this time of year are limited.     

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.     

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.     

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.     

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.     

Constraints to farmers’ adoption of direct-seeding mulch-based cropping systems: A farm scale modeling approach applied to the mountainous slopes of Vietnam

Substantial initiatives are under way in the tropical world to develop and promote direct-seeding mulch-based cropping systems (DMC) in order to reduce soil erosion and improve crop nutrient and water balances. DMC have been adopted by large-scale mechanized farmers, especially in America and Australia, but seldom by resource-poor farmers in the developing world. This study was conducted in Vietnam with the aim of evaluating the feasibility of farmers’ implementing DMC in a mountainous area. The method involved simulation of rational households maximizing their income subject to food security constraints and availability of resources. It generated insight into why farmers of a small region were reluctant to adopt DMC due to the extra labor and input required to implement these techniques during the first years, which hampers their economic performance. In another region, under different biophysical and economic environmental conditions, the study showed that DMC were more likely to be adopted provided that possible constraints at the community level are overcome. The method also allowed us to discuss the types of technical improvements that would make DMC more attractive to farmers. For most farm types, labor required by mulch establishment would have to be reduced by more than 30%. This would mean spreading much less biomass than the 7 t ha⁻¹ currently necessary, compromising the weed-control function of mulch. This would be technically feasible only by using herbicides but this would not be economically sound since it would increase cash requirements. The study showed that subsidies of 50 to more than 200 USD ha⁻¹ were necessary to enable the conversion of all conventionally managed sloping land into DMC in the simulations. These amounts are high relatively to gross margins (250-750 USD ha⁻¹) under conventional management.     

Soil random roughness and depression storage on coffee farms of varying shade levels

Water availability in rainfed coffee agroecosystems is an important factor in determining the production success of the crop. In this study, an estimate of soil water capture and storage was conducted in order to understand the differences of soil water availability among coffee farms or various management intensities, distinguished here by differences in shade cover level. Measurements of effective soil depression storage, leaf litter and soil moisture were taken in each of the sites. These measurements were taken to better understand how different shade coffee systems may gain or lose opportunities to keep water within the system due to contributions of shade. Three sites of varying shade were chosen in the Soconusco region of Chiapas, Mexico. The medium (30-50% cover) shade site was found to be more effective for precipitation capture when compared to the low (10-30% cover) shade site because of a larger value of effective depression storage (t-test, p = 0.05) due to increased soil roughness. This conclusion was supported by significantly higher soil moisture measurements in the medium shade site when compared to the low shade site in the dry season (repeated measure GLM, p = 0.001). The high shade (60-80% cover) site was found to have a greater slope than the other two sites, yielding smaller effective storage capacities; yet the high shade site was able to retain 15% of the available rainfall during the dry season through surface storage, possibly because of greater leaf litter and other shade contributions. Farmers may consider the use of shade trees within coffee farms as a practical method toward preserving water within the agroecosystem.     

Systematic design and evaluation of crop rotations enhancing soil conservation, soil fertility and farm income: a case study for vegetable farms in South Uruguay

Rapid changes in the social and economic environment in which agriculture is developing, together with the deterioration of the natural resource base threatens sustainability of farm systems in many areas of the world. For vegetable farms in South Uruguay, survival in the long term depends upon the development of production systems able to reduce soil erosion, maintain or improve physical and biological soil fertility, and increase farmer’s income to socially acceptable levels. We propose a model-based explorative land use study to support the re-orientation of vegetable production systems in South Uruguay. In this paper we present a new method to quantitatively integrate agricultural, environmental and socio-economic aspects of agricultural land use based on explicit design objectives. We describe the method followed to design and evaluate a wide variety of land use activities for Canelón Grande (South Uruguay) and we illustrate the usefulness of this approach in an ex-ante evaluation of new farming systems using data from 25 farms in this region. Land use activities resulted from systematic combination of crops and inter-crop activities into crop rotations, different crop management techniques (i.e., mechanisation, irrigation and crop protection) and animal production. We identified and quantified all possible rotations and estimated inputs and outputs at crop rotation scale, explicitly considering interactions among crops. Relevant inputs and outputs (i.e., soil erosion, balance of soil organic matter and nutrients, environmental impact of pesticides, labour and machinery requirements, and economic performance) of each land use activity were quantified using different quantitative methods and following the target-oriented approach. By applying the methodology presented in this paper we were able to design and evaluate 336,128 land use activities suitable for the different soil types in Canelón Grande and for farms with different availability of resources, i.e., land, labour, soil quality, capital and water for irrigation. After theoretical evaluation, a large subset of these land use activities showed promise for reducing soil erosion, maintaining soil organic matter content of the soil and increasing farmer’s income, allowing improvement of current farming systems in the region and providing a widely diverse set of strategic options for farmers in the region to choose from. This method can be used as a stand-alone tool to explore options at the field and farm scale or to generate input for optimisation models to explore options at the farm or regional scale.     

Faecal contamination and hygiene aspect associated with the use of treated wastewater and canal water for irrigation of potatoes (Solanum tuberosum)

Clean water has become one of the main limiting factors in agricultural food production in Europe, especially for countries around the Mediterranean, who now face more severe and frequent seasonal water shortages. In order to overcome water shortages the European Water Framework Directive encourages and promotes the use of treated urban wastewater in agriculture. However, the use of poor quality water in agriculture poses potential health risks. The application of wastewater through subsurface drip irrigation lines could possibly overcome public health concerns by minimizing contact with wastewater by farmers, farm workers but it is uncertain if the risk for consumers of wastewater irrigated produces would be acceptable. The objective of the current study was therefore to assess whether subsurface irrigation of potatoes with low quality water was associated with higher food safety and reduced human health risks as compared with surface irrigation. The microbial quality of soil and potatoes irrigated by sprinkler, furrow and subsurface drip irrigation, using treated urban wastewater, canal water and tap water were compared at experimental sites near Belgrade, Serbia and in Bologna, Italy. Water, soil and potato samples were collected from March 2007 to September 2008 and their faecal contamination estimated by enumeration of the faecal indicator Escherichia coli. In addition, water and potatoes in Italy were analysed for the presence of helminth eggs, another important indicator of faecal pollution. A quantitative microbial risk assessment (QMRA) model combined with Monte Carlo simulations was used to assess whether the different irrigation practices and associated health risks complied with guidelines set by the World Health Organization (WHO). The study found low levels of E. coli in irrigation water (Italy mean value: 1.7 colony forming units (cfu)/ml and Serbia 11 cfu/ml), as well as in soil (Italy mean: 1.0 cfu/g and Serbia 1.1 cfu/g). Similar low concentrations of E. coli were found on potatoes (Italy mean: 1.0 cfu/g and Serbia 0.0 cfu/g). The vast majority (442/516) of the collected different samples were free of E. coli. No helminth eggs were found in any types of irrigation water or on the surface of potatoes. The risk assessment models found the use of treated wastewater to exceed the levels of risks for gastro-intestinal disease (1.0 × 10⁻³ disease risk) as recommended by the World Health Organization (WHO) for the accidental ingestion of soil by farmers (Serbia: 0.22 and Italy: 5.7 × 10⁻²). However, samples that exceeded disease risks set by the WHO were collected before initiation of wastewater irrigation and were limited to a few numbers of samples, which would indicate environmental contamination not linked to irrigation practice. Disease risk from consumption of potatoes in Italy and in Serbia was found to be within acceptable levels. No relationship was found between E. coli concentrations in irrigation water, soil and produce. Similar lack of association was found for E. coli findings in sprinkler, furrow or subsurface drip irrigated soils and produce. This indicates that subsurface drip irrigation can be practiced while ensuring food safety and protecting the health of consumers and farmers.     

A longitudinal examination of business performance indicators for drought-affected farms

Frequent severe droughts can financially cripple dryland farm businesses and farmers need effective business strategies to survive. This study analysed the economic performance of 123 farms in a rainfed agricultural region of Australia from 2004 to 2009, a period that included severe droughts in 2006 and 2007. The business indicators examined were business equity, operating profit/ha, return on capital, and the debt to income ratio and the droughts altered these indicators for many of the farms surveyed. Over the study period the equity position of just over 60% of farms declined, although 55% of these had more than 80% equity in the business initially and were able to absorb a short term decline in equity caused by the drought. In addition, 9% of farms had levels of equity below 80% at the start of the investigation, but actually improved their equity position by the end of the study. Strong links were found between wheat yield and the business indicators. Mostly this was due to the crop dominant nature of the farm businesses where wheat was by far the main crop. However, farms that were able to capitalise on favourable conditions in other years were better placed to enhance or recover their financial position. Farms that cropped a higher proportion of their farm area were at an advantage. Structural indicators, including the percentage of area cropped, had a small but significant effect on the debt to income ratio, the return on capital and operating profit. Farm diversity also favourably lessened the debt to income ratio. Other factors, including farm size did not influence the outcome of any business indicator. Farms that remained resilient, despite the serious droughts were those that cropped more than 50% of their farm area, were prudent in their expenditure, maintained some enterprise diversity and often generated wheat yields in each year that were near the yield potential for that year.     

Ameliorating water repellency under turfgrass of contrasting soil organic matter content: Effect of wetting agent formulation and application frequency

Water conservation strategies are being developed in regions of the world expected to experience decreases in water resources due to changing climates. Strategies advocated for improving water-use efficiency may increase the incidence of soil water repellency in sandy-textured soils. We evaluated the effect of soil wetting agent formulation, and application frequency, on water repellency in sandy soil with two contrasting organic matter (OM) contents under kikuyugrass [Pennisetum clandestinum (Holst. Ex Chiov)], and irrigated at 60% replacement of net evaporation in a climate subject to hot, dry summers. The randomized plot design included two turfgrass ages [established from 20 week (7.7% OM) or 20 year old (30% OM) turfgrass in 2005, the latter included a 50 mm ‘mat’ layer], two soil wetting agent formulations (granular or liquid); two application frequencies (one or two applications per irrigation season); and plots of both turfgrass ages that did not receive any wetting agent (nil control). Both wetting agent formulations contained the same active ingredient (propylene oxide-ethylene oxide block polymer), and all wetting agent treatments received the same rate (69 L active ingredient ha⁻¹). Water repellency in the surface soil (0-5 mm), measured using the molarity of ethanol droplet test (MED), ranged from 1.09 M to 4.32 M during the irrigation season, and was more severe in the soil with high OM (average MED, 3.3 M) than low OM content (average MED, 2.7 M). Applying one application of either granular or liquid soil wetting agent at the commencement of the irrigation season decreased the severity of soil water repellency by up to 30% in the high OM soil and by up to 60% in the low OM soil during the summer, and without the need for a second application. The decline in soil water repellency in response to soil wetting agent application was not matched by an increase in soil VWC in summer, and turfgrass quality was considered acceptable throughout the study. The soil wetting agents were less effective at treating water repellent sand containing a significant amount of OM than sand with low OM content.