Identifying the value of pasture improvement using wholefarm modelling

The economic value of pasture improvement in a farming system in a Mediterranean-type environment is assessed using farm modelling. Bioeconomic modelling combined with sensitivity analysis is used to explore how new annual legume species may impact on farm profit and land use. If introduced on all suitable soils the new pastures lead to a 26% increase in farm profit with an additional 12% of farm area being switched into pasture to support more livestock. However, stocking rates decline slightly, the enterprise mix becomes less diversified and several rotational changes are required. If the new pastures are only introduced on particular soils then farm profit increases by a lesser percentage and the pathways to additional profit vary, with both the pasture area and stocking rate either increasing or decreasing. To extract maximum profit from pasture improvement on any particular land management unit often requires management changes on other land management units, apart from those on which pasture improvement initially takes place. The economic value of pasture improvement is found to depend on the portfolio of pastures available for improvement and the nature and mix of the farm’s land management units.     

Regional crop modelling in Europe: The impact of climatic conditions and farm characteristics on maize yields

Impacts of climate variability and climate change on regional crop yields are commonly assessed using process-based crop models. These models, however, simulate potential and water limited yields, which do not always relate to observed yields. The latter are largely influenced by crop management, which varies by farm and region. Data on specific management strategies may be obtained at the field level, but at the regional level information about the diversity in management strategies is rarely available and difficult to be considered adequately in process-based crop models. Alternatively, understanding the factors influencing management may provide helpful information to improve simulations at the regional level.In this study, we aim to identify factors at the regional level that explain differences between observed and simulated yields. Observed yield data were provided by the Farm Accountancy Data Network (FADN) and Eurostat. The Crop Growth Monitoring System (CGMS), based on the WOFOST model, was used to simulate potential and water limited maize yields in the EU15 (i.e., the old member states of the European Union). Differences between observed and simulated maize yields were analysed using regression models including: (i) climatic factors (temperature and precipitation), (ii) farm size, (iii) farm intensity, (iv) land use, (v) income and (vi) subsidies. We assumed that the highest yields observed in a region were close to the yield potential as determined by climate and considered the average regional yields as also influenced by management. Model performance was analysed with respect to spatial and temporal yield variability.Results indicate that for potential yield, the model performed unsatisfactory in southern regions, where high temperatures increased observed yields which was in contrast to model simulations. When considering management effects, we find that especially irrigation and the maize area explain much of the differences between observed and simulated yields across regions. Simulations of temporal yield variability also diverted from observed data of which about 80% could be explained by the climatic factors (35%) and farm characteristics (50%) considered in the analysis. However, effects of specific factors differed depending on the regions. Accordingly, we propose different groups of regions with factors related to management which should be considered to improve regional yield simulations with CGMS.     

Water use efficiency and associated traits in winter wheat cultivars in the North China Plain

Selecting more water efficient cultivars is an important way to reduce water use in a water-scarce region. The objectives of this study were to measure the grain yield and water use efficiency (WUE) of winter wheat (Triticum aestivum L.) cultivars to understand the genetic gains in yield and WUE and their associated physiological and agronomic traits in Hebei province, North China Plain (NCP). Two groups of winter wheat cultivars were tested. Group 1 included 16 winter wheat cultivars that were released between 1998 and 2002 and were tested during the 2002/2003 and 2003/2004 seasons under two water regimes. Group 2 included 10 cultivars released between 1970 and 2000, and were tested during the 2005/2006 and 2006/2007 seasons under three water regimes. Results showed that WUE increased substantially from 1.0-1.2 kg m⁻³ for cultivars from the early 1970s to 1.4-1.5 kg m⁻³ for recently released cultivars. There was also a variation in yield and WUE of about 20% among Group 1 cultivars. Most of the cultivars in both groups had similar responses to water supply. WUE was greater for less irrigated treatments and maximum grain production was achieved with moderate water deficit. The genetic gains in grain yield were associated with increasing in biomass, harvest index and kernel numbers per spike for cultivars released in different years. Among the Group 1 cultivars, the ones with higher yield generally had higher WUE. No significant correlations were found between WUE and physiological traits such as ash content, chlorophyll content, or relative water content among the cultivars released recently. However, a significant relationship was found between stomatal conductance or ash contents and WUE or grain yield among the Group 2 cultivars. Relationships were apparent between WUE and date of anthesis and harvest index (P < 0.05) in Group 1. Earlier flowering cultivars tended to have higher grain yield. In Group 2, flowering date was advancing by about 4 days over the 30 years of crop breeding. The positive relationship between grain yield and WUE for all the cultivars indicated that using a higher yielding cultivar has the potential to improve WUE and thereby to save water.     

Generating crop sequences in land-use models using maximum entropy and Markov chains

Farm management models often produce average crop shares over a number of years, whereas models from the natural sciences often require inputs of sequences of crops grown on a specific field over several years. In interdisciplinary modelling, this difference can be a relevant obstacle. To bridge this gap, an approach is presented that allows disaggregating results from farm management models to the level required by many natural science models. The approach presented includes two methodological innovations: first, minimum cross entropy is used to ensure a unique solution when modelling a linear programming model at the field level, even when objective and constraint coefficients are identical for different fields. Second, the use of a calibrated Markov chain approach allows the creation of land-use sequences that are closer to the linear programming model’s results than an unconditional stochastic simulation would be. The calibrated Markov chain makes use of a prior matrix of transition probabilities that can be empirically derived. Both simulations and analytical calculations with case study data show that the variances of the Markov chain approach are systematically lower than those yielded by a simple stochastic simulation approach. The approach introduced in this paper can improve the coupling of farm-level economic models with natural science models at the field level.     

Crop rotations in Argentina: Analysis of water balance and yield using crop models

Cropping schemes have developed in east-central Argentina for rainfed soybean (Glycine max Merr.) production that invariably employ no-tillage management. Often these schemes include growing soybean in a sequence of crops including wheat (Triticum aestivum L.) and maize (Zea mays L.). The full impact of various rotation schemes on soil water balance through a sequence of seasons has not been explored, although the value of these rotations has been studied experimentally. The objective of this work was to investigate through simulations, potential differences in temporal soil water status among rotations over five years. In this study, mechanistic models of soybean (Soy), maize (Maz), and wheat (Wht) were linked over a five-years period at Marcos Juárez, Argentina to simulate soil water status, crop growth, and yield of four no-till rotations (Soy/Soy, Soy/Wht, Soy/Maz, and Soy/Maz/Wht). Published data on sowing dates and initial soil water contents in the first year from a no-till rotation experiment were used as inputs to the model. After the first year, soil water status output from the model was used to initiate the next crop simulation in the sequence. The results of these simulations indicated a positive impact on soil water balance resulting from crop residue on the soil surface under no-till management. Continuous soybean and the two-year soybean/maize rotation did not efficiently use the available water from rainfall. Residue from maize was simulated to be especially effective in suppressing soil evaporation. Thus, the Soy/Maz simulation results indicated that this rotation resulted in enhanced soil water retention, increased deep water percolation, and increased soybean yields compared with continuous soybean crops. The simulated results matched well with experimental observations. The three-crop rotation of Soy/Maz/Wht did not increase simulated soybean yields, but the additional water retained as a result of decreased soil evaporation resulting from the maize residue allowed the addition of a wheat crop in this two-year rotation. Simulated soybean yields were poorly correlated with both the amount of soil water at sowing and the rainfall during the cropping period. These results highlight the importance of temporal distribution of rainfall on final yield. These models proved a valuable tool for assessing the consequences of various rotation schemes now being employed in Argentina on temporal soil water status, and ultimately crop yield.     

Integrated agricultural research and crop breeding: Allelopathic weed control in cereals and long-term productivity in perennial biomass crops

Future agricultural research will need to increasingly integrate ecological, physiological and molecular methods, in order to understand agricultural crops in situ and their interaction with the environment as well as organisms impacting on their long-term health and productivity (‘agricultural eco-genomics’). The need for integration will increasingly implicate on crop breeding strategies for most agricultural systems. In this paper, implications are highlighted for two contrasting areas of agricultural research related to sustainable crop production: first, the possibilities to utilize crop allelopathic activity to suppress weeds as an alternative to chemical weed control; and second the increasing interest to environmentally friendly and sustainable produce perennial energy crops on agricultural land. ‘Sustainability’ in agriculture is difficult to define unequivocally, but frequently implies the increased utilization of ecological processes. Breeding strategies towards increased utilization of allelopathic crops require initially the integration and verification of allelopathic processes in various agricultural contexts, because there is currently great uncertainty about the predictable operation of allelopathic activity in different ecological contexts. Breeding programs for future biomass crops, most promising are perennials such as Salix, would greatly benefit from the integration of ecological information affecting long-term productivity, e.g., eco-physiological growth determinants at stand level and the biological control of pests. Agricultural eco-genomics could facilitate a compromise between intensive agriculture and the frequently expressed demand for greater sustainability in agriculture.     

InfoCrop: A dynamic simulation model for the assessment of crop yields,losses due to pests,and environmental impact of agro-ecosystems in tropical environments. II. Performance of the model

InfoCrop, a generic crop model, simulates the effects of weather, soils, agronomic management (planting, nitrogen, residues and irrigation) and major pests on crop growth, yield, soil carbon, nitrogen and water, and greenhouse gas emissions. This paper presents results of its evaluation in terms of its validation for rice and wheat crops in contrasting agro-environments of tropics, sensitivity to the key inputs, and also illustrates two typical applications of the model. Eleven diverse field experiments, having treatments of location, seasons, varieties, nitrogen management, organic matter, irrigation, and multiple pest incidences were used for validation. Grain yields in these experiments varied from 2.8 to 7.2 ton ha⁻¹ in rice and from 3.6 to 5.5 ton ha⁻¹ in wheat. The results indicated that the model was generally able to explain the differences in biomass, grain yield, emissions of carbon dioxide, methane and nitrous oxides, and long-term trends in soil organic carbon, in diverse agro-environments. The losses in dry matter and grain yield due to different pests and their populations were also explained satisfactorily. There were some discrepancies in the simulated emission of these gases during first few days after sowing/transplanting possibly because of the absence of tillage effects in the model. The sensitivity of the model to change in ambient temperature, crop duration and pest incidence was similar to the available field knowledge. The application of the model to quantify multiple pests damage through iso-loss curves is demonstrated. Another application illustrated is the use of InfoCrop for analyzing the trade-offs between increasing crop production, agronomic management strategies, and their global warming potential.     

InfoCrop: A dynamic simulation model for the assessment of crop yields,losses due to pests,and environmental impact of agro-ecosystems in tropical environments. I. Model description

The problems of agriculture in many tropical countries are gradually becoming more intense due to increasing food demand led by population growth, stagnation in farm productivity, mounting yield losses due to multiple pests, increasing vulnerability to global environmental changes and the need to reduce emission of greenhouse gases. Tools and techniques are needed to assist in developing strategies that can lead to higher food production, prevent crop production losses, and ensure minimal greenhouse gas emissions while maintaining soil fertility. Several dynamic models have been developed in recent past but most of these are generally strong either in soils and crops, or in greenhouse gases (GHG) emissions. Pest induced yield losses, a critical issue in the tropics, is not addressed in most models. InfoCrop, a generic dynamic crop model, has been developed to meet these specific requirements. It provides integrated assessment of the effect of weather, variety, pests, soil and management practices on crop growth and yield, as well as on soil nitrogen and organic carbon dynamics in aerobic as well as anaerobic conditions, and greenhouse gas emissions. The model considers the key processes related to crop growth, effects of water deficit, flooding, nitrogen management, temperature and frost stresses, crop–pest interactions, soil water and nitrogen balance and (soil) organic carbon dynamics. Its general structure relating to basic crop growth and yield is largely based on several earlier models, especially SUCROS series, and is written in Fortran Simulation Environment (FSE) programming language. The model has been validated for dry matter and grain yields of several annual crops, losses due to multiple diseases and pests, and emissions of carbon dioxide, methane and nitrous oxide in a variety of agro-environments. To increase the applications of model in research and development, an extremely simple menu driven version of InfoCrop has also been developed. The users of this version do not need any background in programming.     

Estimation of water consumption and crop water productivity of winter wheat in North China Plain using remote sensing technology

The North China Plain (NCP) is one of the most water stressed areas in the world. The water consumption of winter wheat accounts for more than 50% of the total water consumption in this region. An accurate estimate of the evapotranspiration (ET) and crop water productivity (CWP) at regional scale is therefore key to the practice of water-saving agriculture in NCP. In this research, the ET and CWP of winter wheat in 83 counties during October 2003 to June 2004 in NCP were estimated using the remote sensing data. The daily ET was calculated using SEBAL model with NOAA remote sensing data in 17 non-cloud days whereas the reference daily crop ET was estimated using meteorological data based on Hargreaves approach. The daily ET and the total ET over the entire growing season of winter wheat were obtained using crop coefficient interpolation approach. The calculated average and maximum water consumption of winter wheat in these 83 counties were 424 and 475 mm, respectively. The calculated daily ET from SEBAL model showed good match with the observed data collected in a Lysimeter. The error of ET estimation over the entire growing stage of winter wheat was approximately 4.3%. The highest CWP across this region was 1.67 kg m⁻³, and the lowest was less than 0.5 kg m⁻³. We observed a close linear relationship between CWP and yield. We also observed that the continuing increase of ET leads to a peaking and subsequent decline of CWP, which suggests that the higher water consumption does not necessarily lead to a higher yield.     

A rule-based method for the development of crop management systems applied to grain sorghum in south-western France

A generic approach is proposed for the development and testing of crop management systems in contrasting situations of water availability. Ecophysiological knowledge, expertise, regional references and simulation models are combined to devise management strategies adapted to production targets and constraints. The next stage consists of converting these crop management strategies into logical and consistent sets of decision rules. Each rule describes the reasoning which is used to apply a technical decision by taking account of observed or simulated environmental conditions or predicted agronomic risks.

This approach was applied to design crop management systems for grain sorghum (Sorghum bicolor L. Moench.) in south-western France. For spring-sown crops, management (sowing date, plant density, varietal choice, N fertilizer rate and timing) was based on water availability, both for economic and environmental reasons. Specific sets of decision rules were written for irrigated and rainfed conditions. The establishment of rules was based on agronomic principles (e.g. for plant density) or on the application of a simulation model (e.g. for sowing date, variety). N fertilization and irrigation were applied using combined N and water dynamic models.

A novel methodology combining crop diagnosis, analytical trials and crop simulation was developed to evaluate the management systems. An irrigated and a rainfed rule-based management system were compared near Toulouse (S.W. France) from 1995 to 2002. The profitability of rainfed low-input management was confirmed for sorghum in spite of high yields under irrigation (up to 10 t ha⁻¹). The adaptation of sorghum management in rainfed conditions was mainly achieved through early maturing cultivars and by reducing N applications by 65%.     

Cropping systems and crop residue management in the Trans-Gangetic Plains: Issues and challenges for conservation agriculture from village surveys

Conservation agriculture practices are being advocated to help sustain crop productivity gains and secure environmental sustainability in the Trans-Gangetic Plains, India’s Green Revolution heartland. The paper illustrates the use of village surveys as a quasi-quantitative system analysis tool to derive implications for agricultural research and development. Drawing from village surveys in 170 communities, the paper assesses current crop residue management practices in Punjab and Haryana’s rice-wheat, basmati-wheat and non-rice-wheat cropping systems. The prevalence of wheat as the winter crop implies an intensive collection, trading and use of wheat straw as basal feed for dairy livestock; which contrasts with the diverse crop residue management of the monsoon crops. The increased use of combine harvesters has spurred the rapid advent of mechanical wheat straw reapers whereas the bulk of combine harvested rice straw is burned in situ. Present crop residue management practices are largely incompatible with year-round mulch retention despite significant biomass production. The research and development community faces the challenge of evening out straw use and management over seasons to ensure at least partial residue retention if its calls for conservation agriculture in this important sub-region are to succeed. The paper also reiterates the worrying decline of groundwater tables associated with the rice-wheat system.     

SEBAL for detecting spatial variation of water productivity and scope for improvement in eight irrigated wheat systems

A methodology has been developed to quantify spatial variation of crop yield, evapotranspiration (ET) and water productivity (WP_ET) using the SEBAL algorithm and high and low resolution satellite images. SEBAL-based ET estimates were validated over an irrigated, wheat dominated area in the Yaqui Valley, Mexico and proved to be accurate (8.8% difference for 110 days). Estimated average wheat yields in Yaqui Valley of 5.5 t ha⁻¹ were well within the range of measured yields reported in the literature. Measured wheat yields in 24 farmers’ fields in Sirsa district, India, were 0.4 t ha⁻¹ higher than SEBAL estimated wheat yields. Area average WP_ET in the Yaqui Valley was 1.37 kg m⁻³ and could be considered to be high as compared to other irrigated systems around the world where the same methodology was applied. A higher average WP_ET was found in Egypt's Nile Delta (1.52 kg m⁻³), Kings County (CA), USA (1.44 kg m⁻³) and in Oldambt, The Netherlands (1.39 kg m⁻³). The spatial variability of WP_ET within low productivity systems (CV = 0.33) is higher than in high productivity systems (CV = 0.05) because water supply in the former case is uncertain and farming conditions are sub-optimal. The high CV found in areas with low WP_ET indicates that there is considerable scope for improvement. The average scope for improvement in eight systems was 14%, indicating that 14% ET reduction can be achieved while maintaining the same yield. It is concluded that the proposed methodology is accurate and that better knowledge of the spatial variation of WP_ET provides valuable information for achieving local water conservation practices in irrigated wheat.     

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.     

An integrated modelling toolbox for water resources assessment and management in highland catchments: Model description

Water and land resource competition and environmental degradation pose difficult questions for resource managers. In particular, the ensuing trade-offs between economic, environmental, and social factors and their spatiotemporal variability must be considered when implementing management policies. This paper describes an integrated modelling toolbox that has been developed for highland catchments – specifically the Mae Chaem catchment in Northern Thailand. This toolbox contains models of crop growth, erosion and rainfall-runoff, as well as household decision and socioeconomic impact models. The approach described advances and complements previous approaches by: considering more complex interactions between land-use decisions and the hydrological cycle; modelling household decisions based on uncertain expectations; and assessing impacts of changes not only on flows and household income, but also on subsistence production and erosion. An example of the types of trade-offs and scenarios that can be assessed using the integrated modelling toolbox is also presented. This demonstrates that for the scenarios presented, the magnitude and direction of impacts simulated by the model is not dependent on climate. Further testing of the model is demonstrated in a companion paper. Overall, the plausibility of the model is shown.     

Modelling the effects of climate variability and water management on crop water productivity and water balance in the North China Plain

In the North China Plain (NCP), while irrigation using groundwater has maintained a high-level crop productivity of the wheat-maize double cropping systems, it has resulted in rapid depletion of groundwater table. For more efficient and sustainable utilization of the limited water resources, improved understanding of how crop productivity and water balance components respond to climate variations and irrigation is essential. This paper investigates such responses using a modelling approach. The farming systems model APSIM (Agricultural Production Systems Simulator) was first calibrated and validated using 3 years of experimental data. The validated model was then applied to simulate crop yield and field water balance of the wheat-maize rotation in the NCP. Simulated dryland crop yield ranged from 0 to 4.5 t ha⁻¹ for wheat and 0 to 5.0 t ha⁻¹ for maize. Increasing irrigation amount led to increased crop yield, but irrigation required to obtain maximum water productivity (WP) was much less than that required to obtain maximum crop yield. To meet crop water demand, a wide range of irrigation water supply would be needed due to the inter-annual climate variations. The range was simulated to be 140-420 mm for wheat, and 0-170 mm for maize. Such levels of irrigation applications could potentially lead to about 1.5 m year⁻¹ decline in groundwater table when other sources of groundwater recharge were not considered. To achieve maximum WP, one, two and three irrigations (i.e., 70, 150 and 200 mm season⁻¹) were recommended for wheat in wet, medium and dry seasons, respectively. For maize, one irrigation and two irrigations (i.e., 60 and 110 mm season⁻¹) were recommended in medium and dry seasons, while no irrigation was needed in wet season.     

Simulating the effects of tax exemptions on fertiliser use in Benin by linking biophysical and economic models

The sluggish increase in the area productivity of staple crops is a major factor causing increased dependence of African countries on food imports. The increased use of mineral fertiliser may dramatically improve the food balance of many countries and result in lower food prices, higher food supply and consumption, and improved food security and nutritional status. In Benin, West Africa, political measures to improve farmers’ access to fertiliser are biased in favour of cotton production. This article simulates the impact of universal tax exemptions for fertiliser use on crop yields, food balances, and the use of land resources for the most important staple crops in Benin using a crop growth model and an agricultural sector model. The simulation results indicate that tax exemptions on fertiliser use could have positive effects on physical productivity and would increase food security until 2025 as compared to a baseline scenario. At the same time, the pressure on land resources would not be aggravated, so that better access to fertiliser may help to curb excessive cropland expansion in Benin.     

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.     

The role and value of eastern star clover in managing herbicide-resistant crop weeds: A whole-farm analysis

In the broadacre dryland farming system of Western Australia herbicide resistance in major crop weeds is an increasingly serious problem. A new option to combat herbicide resistance involves growing eastern star clover (Trifolium dasyurum). This is a new pasture legume with a unique delayed germination that allows control of weeds using various chemical and non-chemical strategies, without unduly compromising the pasture’s subsequent production. This study assesses the role and value of eastern star clover in managing herbicide-resistant weeds on various farms. The study employs the farming system model known as MIDAS, a whole-farm, bioeconomic model. Key scenarios of different degrees of severity of herbicide resistance for three farm types are examined. The main findings of the analysis are that as the severity of herbicide resistance increases, eastern star clover becomes an increasingly attractive option. Although the introduction of eastern star clover does reduce a farm’s capacity to carry sheep, and thereby lessens profits generated by the sheep enterprise, it enables longer, more profitable sequences of crops to be grown with fewer weed problems. Sensitivity analysis suggests that reduced cost of eastern star clover seed, cheap supplementary feed, and higher grain prices will further increase the profitability of eastern star clover.     

Influence of plant traits on production costs and profitability of strawberry in southeast Queensland

In Queensland the subtropical strawberry (Fragaria × ananassa) breeding program aims to combine traits into novel genotypes that increase production efficiency. The contribution of individual plant traits to cost and income under subtropical Queensland conditions was investigated, with the overall goal of improving the profitability of the industry through the release of new strawberry cultivars. The study involved specifying the production and marketing system using three cultivars of strawberry that are currently widely grown annually in southeast Queensland, developing methods to assess the economic impact of changes to the system, and identifying plant traits that influence outcomes from the system.From May through September P (price; $ punnet⁻¹), V (monthly mass; tonne of fruit on the market) and M (calendar month; i.e. May = 5) were found to be related (r² = 0.92) by the function (±SE) P = 4.741(±0.469) − 0.001630(±0.0005)V − 0.226(±0.102)M using data from 2006 to 2010 for the Brisbane central market. Both income and cost elements in the gross margin were subject to sensitivity analysis.‘Harvesting’ and ‘Handling/Packing’ ‘Groups’ of ‘Activities’ were the major contributors to variable costs (each >20%) in the gross margin analysis. Within the ‘Harvesting Group’, the ‘Picking Activity’ contributed most (>80%) with the trait ‘display of fruit’ having the greatest (33%) influence on the cost of the ‘Picking Activity’. Within the ‘Handling/Packing Group’, the ‘Packing Activity’ contributed 50% of costs with the traits ‘fruit shape’, ‘fruit size variation’ and ‘resistance to bruising’ having the greatest (12-62%) influence on the cost of the ‘Packing Activity’. Non-plant items (e.g. carton purchases) made up the other 50% of the costs within the ‘Handling/Packing Group’. When any of the individual traits in the ‘Harvesting’ and ‘Handling/Packing’ groups were changed by one unit (on a 1-9 scale) the gross margin changed by up to 1%. Increasing yield increased the gross margin to a maximum (15% above present) at 1320 g plant⁻¹ (94% above present). A 10% redistribution of total yield from September to May increased the gross margin by 23%. Increasing fruit size increased gross margin: a 75% increase in fruit size (to ≈30 g) produced a 22% increase in the gross margin.The modified gross margin analysis developed in this study allowed simultaneous estimation of the gross margin for the producer and gross value of the industry. These parameters sometimes move in opposite directions.