Population dynamics and crop yield effects of nematodes and white mold in peanuts,cotton and velvet beans

Dynamic population equations for the root-knot nematode (Meloidogyne arenaria), Southern blight (`white mold') fungus (Sclerotium rolfsii), and microbivorous nematodes in peanuts, cotton, and the Alabama velvet bean were statistically estimated with replicated experimental data from Headland, AL, USA. The level of microbivorous nematodes the previous crop year was found to suppress the root-knot nematode and white mold in peanuts the following crop year in monoculture peanut production and in peanuts after velvet beans. Statistical results showed that both the root-knot nematode and white mold had a negative effect on peanut yield, while microbivorous nematodes had a positive effect on peanut and cotton yields. Scientific knowledge of these organisms does not fully explain the results, but the statistical results strongly suggest that these relationships exist. On the basis of statistical results for peanuts, each white mold occurrence (in a 60-ft row) cost $21.41, each root-knot nematode (in 100-cm³ soil sample) cost $0.41, and each microbivorous nematode (in 100-cm³ soil sample) had a benefit of $0.11. In cotton production, microbivorous nematodes had a benefit of $0.13.     

A model of the life cycle of sheep nematodes and the epidemiology of nematodiasis in sheep

A computer model (NEMAT) of the life cycle of sheep nematodes and of the epidemiology of nematodiasis in sheep was constructed. Its purpose is to predict the development of nematodiasis in weaner sheep and to determine optimum nematode control programmes. It has been developed for use in western Victoria, Australia, but it should also be of use in other localities.NEMAT simulates the growth of perennial ryegrass (Lolium perenne) and subterranean clover (Trifolium subterraneum) pasture and weaner sheep and the development of populations of the sheep nematodes Ostertagia spp. and Trichostrongylus spp. The development and death rate parameters of the free-living stages of these nematodes were estimated by a direct search optimisation procedure specifically developed for this study. The death rates of the parasitic stages of Ostertagia spp. were determined in a field experiment and expressed as a function of the rate of infection and the time of exposure to infection. Other probability density functions and deterministic functions needed to complete the quantification of the sheep-nematode system were derived from published reports or personal communications.NEMAT was validated against data from two independent field experiments carried out in western Victoria. Predicted serial measurements of pasture availability, liveweights, total nematode counts, nematode eggs per gram of faeces and numbers of infective nematode larvae per hectare were compared with those actually observed. The predicted and observed measurements were subjectively similar and could not be differentiated statistically by spectral analysis.NEMAT was then used to evaluate some nematode control programmes in western Victoria. Using observed weather data, it simulated the continuous development of nematode populations during 1957–1976 on pastures set stocked on the 1st of January each year with recently drenched weaner sheep.If sheep were drenched in only one month of the year, the effect of this drench on liveweights and woolweights at the end of the year was greatest if it was given in February. There was a progressive decline in final liveweights and woolweights if it was given in subsequent months to December. If sheep were drenched in February and given a second drench in any one of the remaining months of the year, the effects of this second drench on final liveweights and woolweights was greatest if it was given at the autumn break. A drench in February and a drench and shift to ‘clean’ pasture (<10⁴ nematode larvae per hectare) in July were always sufficient to limit the mean yearly effects of nematodiasis to 1 kg in liveweight and 0·1 kg in woolweight. When such a shift was not possible, a drench in February, another at the autumn break and 0–5 drenches in winter and spring were required to attain similar productivity. The number and timing of these drenches after the autumn break depended on the daily effects of weather on the nematode population and could be determined only by a model of the sheep-nematode system such as NEMAT.     

Optimal rotation of peanuts and cotton to manage soil-borne organisms

Damage from the root-knot nematode (Meloidogyne arenaria) and Southern blight (white mold) fungus (Sclerotium rolfsii) are principal yield-limiting factors in the production of peanuts (Arachis hypogaea) in the USA. Both are widespread in the southeastern USA and yield losses caused by them can be severe. Both organisms can be suppressed by pesticides, but both can also be suppressed by rotation with cotton and certain other crops. This article presents a stochastic dynamic programming model that maximizes the expected present value of profit over a multi-year planning horizon with production of peanuts and cotton, accounting for: (1) the stochastic population dynamics of the peanut root-knot nematode, Southern blight fungus, and beneficial microbivorous nematodes; (2) the stochastic market prices for cotton and peanuts; and (3) land use in each of the previous 2 years. Expected profit from this seven-state variable dynamic programming model is compared to expected profit for monoculture peanuts, monoculture cotton, three fixed rotations, and a myopic, but flexible, rotation. Comparison of expected returns for these decision models indicates that an information-based strategy—the optimal dynamic strategy or the myopic strategy—is better than any of the fixed rotations. The myopic strategy results in expected profits almost as high as the optimal strategy for this particular problem. Since a myopic strategy is much more easily computed and more easily explained to producers, it has much more promise for adoption than difficult-to-understand results from a stochastic dynamic programming model.     

土壤高温蒸汽消毒对蕃茄根结线虫的防治效果评价

针对传统化学防治解决土壤连作障碍存在农药残留、食品安全及环境污染等问题,引进一种移动式土壤高温蒸汽消毒机并进行技术可行性分析。通过田间试验及数据分析,使用高温蒸汽处理技术2 h可以显著降低番茄根结线虫数量、有效控制番茄根结线虫的危害。统计结果表明,在高温蒸汽处理后2 d,根结线虫的线虫减退率为92.9%;移动式土壤高温蒸汽消毒处理对番茄根结线虫的防治效果高达92.7%。该研究提供了一种物理防治番茄根结线虫的方法,为克服土壤连作障碍提供了新的途径。      

聊城市园林植物线虫种类调查与群体密度消长动态研究

2004—2006年对聊城园林植物线虫病进行了系统调查。采用筛淘-改良贝尔曼漏斗法分离根际土壤或介质中的线虫,通过鉴定共发现植食性线虫11种、腐生线虫3种、捕食性线虫1种,掌握了从春至秋各类线虫种群数量呈增长趋势、群体结构呈多样化发展的规律,确定晚秋是线虫种群数量、种类最为繁盛的时期。     

Estimation of instantaneous and daily net radiation from MODIS data under clear sky conditions: a case study in East Asia

The Moderate Resolution Imaging Spectroradiometer-based net radiation (R _N) model was built and applied in East Asia in 2005. Because there have hardly been simple parameterization schemes developed over a large area using remote-sensing technology, the model was aimed to present physical simplicity in complex topography at multiple spatiotemporal scales. The model successfully reproduced the instantaneous R _N values obtained at four flux tower sites having individually different ecohydrology. The diurnal cycle of R _N was contextually simulated using a simple sine curve to determine the daily and monthly average net radiation. The diurnal R _N estimation method was proven to be a reliable model as long as accurate boundary conditions, sunrise and sunset times, for example, were obtained. The monthly average net radiation (MANR) was estimated using the diurnal patterns of the instantaneous R _N. Distribution of the monthly R _N demonstrated that elevation and latitude were the primary factors affecting the MANR. The proposed R _N algorithm turned out to be a promising method for valuable applications in various fields due to systematic simplicity and fewer input parameters.     

Crop coefficient (K c) for apple: comparison between measurements by a weighing lysimeter and prediction by CropSyst

Accurate prediction of crop coefficient (K _c) is necessary for proper irrigation management. We explored CropSyst for determining irrigation requirements of apple trees and for accuracy of K _c prediction. Values of K _c were compared to those obtained, over 2002–2010, from lysimeter-grown trees. Over these years, trees had different ratios of height (H) to width (W). CropSyst predicted irrigation requirements using tree light interception and water uptake sub-model components. Parameters of the model were adjusted using data obtained from the lysimeter in 2010. Tree light interception sub-model was verified by 2007 data. After parameterization, good agreement was found between simulated and measured K _c over different seasons. The porosity coefficient of the canopy was related to changes in tree’s H/W ratio and leaf overlapping. Accordingly, different porosity values could be estimated for each year. When yearly changes in canopy porosity was considered, CropSyst improved K _c prediction and generated relevant information for managing irrigation under changing canopy shape for apple trees.     

Estimating episodic recharge under different crop/pasture rotations in the Mallee region. Part 1. Experiments and model calibration

Changes in land use in the Mallee region of southeastern Australia have led to increased groundwater recharge and salinisation. This study was conducted to determine the impact of different agronomic practices on recharge control, in particular episodic recharge. During the period 1991–1995, two field experiments were carried out at Hillston (New South Wales) and Wallpeup (Victoria) where soil hydraulic properties, soil-moisture content, and leaf area index were measured. Various crop and pasture rotations were considered involving fallow, field pea (Piscum salivum L cv Dunndale), Indian mustard (Brassica juncca cv F2 cross), wheat (Triticum aestivum cv Janz Meering), oats (Avena sateva L. cv Coolabah), lucerne (Medicago sativa L. cv. Arora) and medic pastures (Medicago truncatula cv Parriagio, Sephi and Hykon). Data obtained from these experiments were used to calibrate and test a biophysically based model WAVES. With minimum calibration, the simulated soil-moisture content and leaf area index are in good agreement with field observations. The parameter values are within a physically reasonable range. The success of the model in simulating soil-moisture dynamics and plant growth was due to the accurate representation of the soil and canopy processes. WAVES combined with field measurements provides a powerful tool for estimating the impacts of land-management options on water balance.     

CORNMOD,a dynamic simulator of corn production

Aftern an extensive literature search, CORNMOD, a comprehensive mathematical model that simulates energy and gas exchange at the plant-air interface, was developed. Predictions of profiles (CO₂ concentration, water vapour, temperature, light, photosynthesis) in the canopy were biologically good enough for many applications, but they revealed the inadequacies in our understanding of the environment within the plant canopy.Also considered were spring and fall tillage and harvest operations. After calculating several spring freeze-thaw periods for the test year, 1969, enough work days were accumulated to complete tillage operations, allowing completion of planting by 12 May. Two 63 hp tractors and associated equipment were used to farm the 81 ha hypothetical farmstead used for test purposes. Without this large investment in equipment, planting date would have been delayed until late June or early July since the spring of 1969 was very wet.The simulated crop was grown under actual 1969 weather conditions. On 4 September the corn crop reached harvest maturity as gauged by a GDD (Growing Degree Day) ‘clock’. The simulator predicted a yield of 7368 kg/ha. This was a gross over-prediction of the 4088 kg/ha average reported for 1969 in central Missouri. This over-prediction was accounted for by the ideal conditions given the simulator when actual data were not available. This included leaf angles, CO₂ concentration, and stomatal resistance.Harvesting took 30 days to complete, using one four-row sheller, two trucks, a farm elevator, and 127 272 kg of storage capacity. It appered that the farm dryer was the limiting piece of equipment in the harvesting operation.This crop production simulator forms the basic framework that can eventually analyse more complex systems. However, at this point, the simulator is only in the initial stages of development, and it should be realised that much more extensive development is necessary before the ultimate simulator is achieved.     

Estimating potential nitrate leaching in nitrogen fertilized and irrigated tomato using the computer model NLEAP

Groundwater pollution caused by leaching of NO₃-N from agricultural systems has caused public concern for decades. To preserve the groundwater and reduce economic losses for the farmers, a rapid and accurate estimation of NO₃-N moving below the root zone is crucial. In this study, the value of the computer program NLEAP (Nitrate Leaching and Economic Analysis Package) to simulate nitrate leaching was evaluated using data from an experiment conducted with 12 lysimeters (1.25 m i.d. and 2 m deep) in 1996 and 1997. Three tomato (H2274 variety) seedlings were planted in each lysimeter and nitrogen rates of 0, 80, 160, and 240 kg N ha⁻¹, as ammonium nitrate and ammonium sulphate, were applied to the lysimeters under a fixed irrigation program. Effluent was collected from the outlets of the lysimeters and analyzed for NO₃. The model adequately simulated nitrogen leaching for each year (R²=0.93 and P<0.03 for 1996, and R²=0.87 and P<0.06 for 1997). The high coefficients of determination, between observed and simulated values, revealed that the model can be successfully used to estimate the amount of the NO₃ leaching under the experimental conditions. The results also showed that the NO₃ available for leaching (NAL) values were important background information for determining an optimum N rate for groundwater quality and maximum gain, and NO₃ available for leaching (NAL), amount of NO₃ leached (NL), movement risk index (MRI), and annual leaching risk potential (ALRP) parameters should be considered together to estimate the nitrogen pollution risk.     

Development and evaluation of integrated water and nitrogen model for maize

Maize (Zea mays L.) is an important food crop for irrigated regions in the world. Its growth and production may be estimated by different crop models in which various relationships between growth and environmental parameters are used. For simulation of maize growth and grain yield, a simulation model was developed (Maize Simulation Model, MSM). Dynamic flow of water, nitrogen (N) movement, and heat flow through the soil were simulated in unsteady state conditions by numerical analysis in soil depth of 0–1.8 m. Hourly potential evapotranspiration [ET_p(t)] for maize field was estimated directly by Penman–Monteith method. Hourly potential evaporation [E_p(t)] was estimated based on ET_p(t) and canopy shadow projection. Actual evaporation of soil surface was estimated based on its potential value, relative humidity of air, water pressure head and temperature at soil surface layer. Actual transpiration (T_a(t)) was estimated based on soil water content and root distribution at each soil layer. Hourly N uptake by plant was simulated by N mass flow and diffusion processes. Hourly top dry matter production (HDMA^j + 1, where j is number of hours after planting) was estimated by hourly corrected intercepted radiation (RSLT^j + 1) by plant leaves [determined from leaf area index (LAI^j + 1)] with air temperature, the maximum and minimum plant top N concentration and the amounts of nitrogen uptake. The value of LAI^j + 1 at each hour was estimated by the accumulated top dry matter production at previous hour using an empirical equation. Maize grain yield was estimated by a relationship between harvest index and seasonal plant top dry matter production. The model was calibrated using data obtained under field conditions by a line source sprinkler irrigation. When the values of water and nitrogen application were optimum, grain yield (moisture content of 15.5%) was 16.2 Mg ha⁻¹. Model was validated using two independent experimental data obtained from other experiments in the Badjgah (Fars province). The experimental results validated the proposed simulation model fairly well.     

Evaluation of the parameters involved in Gardner's relation between unsaturated hydraulic conductivity and soil water matric suction

An experimental study on evaporation from homogeneous sandy and loamy soils was carried out to define the unsaturated hydraulic conductivity function. Gardner's empirical function k(ψ) (1958) was used in the analysis of experimental data. Parameters involved in the k(ψ) functions obtained were evaluated. The error due to exclusion of the b-factor varied with the depth of water table for both sandy and loamy soils.     

An upscaling approach to simulate unsaturated flow in horizontally heterogeneous soils at field scale under flood irrigation

An upscaling approach was developed for simulating soil water flow in horizontal heterogeneous unsaturated zone at field scale under flood irrigation. Based on the assumption of stream tube model and the van Genuchten-Mualem soil hydraulic function with five parameters K_s, α, n, θ_r and θ_s, the Richards equation was transformed into a dimensionless form by using the dimensionless forms of temporal and spatial variables, and pressure head. Although a strong dependency of parameters K_s and α on scale does not exist in the transformed Richards equation, the parameter n, which is slightly dependent on scale, still exists in the transformed equation, and the parameter α is introduced in the transformed initial and boundary conditions. Therefore, a power law averaging technique was also included in our upscaling approach. Compared with traditional numerical methods, the distribution of pressure head of each soil column, and the mean and variance of soil water dynamics in all the soil columns can be obtained by numerically solving the transformed Richards equation only one time and by returning to the dimensionless variable expressions, while the traditional Richards equation must be solved once for every soil column. The new approach was calibrated by two numerical experiments, and the soil water content as a function of time and depth was reasonably well simulated for the two experiments which involved different soil textures. Different combinations of α and n were applied for comparing the accuracy of numerical simulations: n had little effect on the simulated results whereas α had some significant effect on the simulated results. To further verify the numerical efficiency of the new approach, we adopted the effective α values corresponding to the exponent p of the power law averaging technique [Eq. (16)] when p approaches 0, p = ± 1 and ± 0.5 to conduct more numerical experiments. It showed that with an initial pressure head profile of equilibrium for Example 1, and with an initial pressure head profile of constant for Example 2, the simulated results of the wetting front at the specific depths were in agreement with that of traditional numerical method, and the errors in simulated pressure heads were small. In summary, the proposed approach can be useful for upscaling unsaturated water flow characteristics in horizontally heterogeneous soils.     

Application of epic model to nitrogen cycling in irrigated processing tomatoes under different management systems

Vegetable crops such as processing tomatoes (Lycopersicon esculentum Mill.) are usually complex in terms of nitrogen (N) dynamics because of the large amounts absorbed by the crop, the short growing season and the use of irrigation. Complexity increases when N is supplied from an organic source. A crop simulation model could be very useful to improve N management in this crop. Processing tomatoes were grown on raised beds and furrow irrigated in 1994 and 1995 in the Sacramento Valley of California. Fertilizer N and/or purple vetch (Vicia sativa L.) as green manure and composted turkey manure were used as sources of N. The Erosion Productivity Impact Calculator (EPIC) model was calibrated with 1994 data and validated with 1995 data. Plant growth was accurately simulated in the conventional systems that used fertilizer N and in the low input system that used fertilizer N plus vetch. The model accurately simulated above-ground biomass in a system that used vetch and no synthetic fertilizer N, but it over-predicted Leaf Area Index (LAI). Nitrogen deficiency was observed in the plants in this system. The model simulated nitrogen deficiency mainly as a reduction in biomass production but in the real world the reduction of leaf area was the first effect of nitrogen deficiency in the vegetative phase. Yields were accurately predicted except when diseases affected plant growth. A simple reduction factor of nitrate movement in the bed adequately addressed the movement of nitrate. In general, the model accurately predicted the evolution of inorganic nitrogen in different soil layers during the crop season. However, simulated inorganic N in the upper 15 cm was underestimated in the last part of the crop season and consequently N uptake at harvest was slightly over-predicted in some cases. Nitrogen distribution and access of the roots to inorganic nitrogen are discussed as causes of this discrepancy between model simulated and observed values.     

Simulation of the dry matter production and seed yield of common beans under varying soil water and salinity conditions

We present a model that simulates the effects of water and salinity stress on the growth of beans. The model derives a combined soil water/salinity stress factor from the total water potential (combination of the matric and the osmotic potentials) and uses this stress factor as a growth limiter in a growth model. The model was tested on data obtained from two greenhouse trials of beans (Phaseolus vulgaris) grown under a range of soil water and salinity conditions. The simulated dry weight of the bean generally followed those observed. In the first trial, the comparison between simulated and observed total dry weight and seed yield gave R² values of 0.97 and 0.92, respectively. Comparison of the simulated to the observed dry weight for the second trial gave R² values of 0.85 and 0.89, respectively. These indicate a good performance of the model in general. The principle of deriving a combined water/salinity stress from the matric and osmotic potentials is simple and can be included as a simple routine in many existing crop models without much difficulty.     

Effect of mixed cation solutions on hydraulic soil properties

Hydraulic conductivity (K) and soil water diffusivity (D) characterizing water flow under saturated and unsaturated conditions, respectively, were determined for a sandy loam and a clay loam soil, using water with different combinations of total electrolyte concentrations, C (i.e., 20, 40, 80, 125 and 250 meq 1^?1) and sodium adsorption ratios, SAR (i.e., 0, 20, 30, 40, 80 and ∞ mmole $\text{l}{}^{\mathrm{<mtext>?</mtext><mtext>1</mtext><mtext>2</mtext>}}$). Both K and D were found to increase with C and decrease with SAR. In low sodium adsorption ratio ranges (i.e., up to 20) the requirement of electrolyte concentration to maintain relative hydraulic conductivity = 0.5 was relatively more for sandy loam than for clay loam soil. However, the trend for electrolyte concentration requirements for the two soils was reversed at high sodium adsorption ratios (i.e. > 20). A spline function was used to draw the best fitting line through the data points of horizontal absorption experiments.     

Effects of water infiltration and storage in cultivated soil on surface irrigation

Surface irrigation analysis and design require the knowledge of the variation of the cumulative infiltration water Z (L) (per unit area) into the soil as a function of the infiltration time t (T). The purpose of this study is to evaluate water infiltration and storage under surface irrigation in an alluvial clay soil cultivated with grape yield, and to determine if partially wetted furrow irrigation has more efficient water storage and infiltration than traditional border irrigation. The two irrigation components considered were wet (WT) and dry (DT) treatments, at which water applied when available soil water reached 65% and 50%, and the traditional border irrigation control. Empirical power form equations were obtained for measured advance and recession times along the furrow length during the irrigation stages of advance, storage, depletion and recession. The infiltration (cumulative depth, Z and rate, I) was functioned to opportunity time (t_o) in minute for WT and DT treatments as: Z_WT = 0.528 t_o^0.6, Z_DT = 1.2 t_o^0.501, I_WT = 19 t_o^−0.4, and I_DT = 36 t_o^−0.498. The irrigation efficiency and soil water distribution have been evaluated using linear distribution and relative schedule depth. Coefficient of variation (CV) was 5.2 and 9.5% for WT and DT under furrow irrigation system comparing with 7.8% in border, respectively. Water was deeply percolated as 11.88 and 19.2% for wet and dry furrow treatments, respectively, compared with 12.8% for control, with no deficit in the irrigated area. Partially wetted furrow irrigation had greater water-efficiency and grape yield than both dry furrow and traditional border irrigations, where application efficiency achieved as 88.1% for wet furrow irrigation that achieved high grape fruit yield (30.71 Mg/ha) and water use efficiency 11.9 kg/m³.     

Determination of soil hydrologic properties under simulated rainfall condition

Two important soil hydrologic properties viz. soil water retention (h-θ relationship) and unsaturated hydraulic conductivity (K-θ relationship), were determined under simulated rainfall conditions. The h-θ relationship was determined using a rainfall simulator infiltrometer (RSI). The resulting h-θ relation was then used as input to the Van Genuchten's model (VGM) for determining the K-θ relationship. In order to validate the results obtained through RSI-VGM combination, the commonly adopted instantaneous profile method (IPM) was also applied to develop the K-θ relationship independently. Functional sensitivity analysis, conducted to simulate the soil water storage using the model Soil Water Actual Transpiration Rate (SWATR), showed that the simulated results obtained through RSI-VGM combination were in agreement with those from IPM.     

Modelling for maize irrigation scheduling using long term experimental data from Plovdiv region, Bulgaria

Independent historic datasets on irrigated maize, collected over seven years (1984-1990), were used to parameterize the irrigation scheduling model ISAREG. Experimental data were obtained under rainfed, deficit, and full irrigation conditions in an alluvial soil at Tsalapitsa, Plovdiv region, in the Thracian plain, Bulgaria. Crop coefficients and depletion fractions for no-stress were calibrated by minimizing the differences between observed and simulated soil water content. The calibration was performed using data from full irrigation and rainfed treatments while deficit irrigation treatments were used for validation. The modelling efficiency was high, 0.91 for the calibration and 0.89 for the validation. The resulting average absolute errors of the estimate for the soil water content were smaller than 0.01 cm³ cm⁻³. The model was also tested by comparing computed versus observed seasonal evapotranspiration. Results for dry years show a modelling efficiency of 0.96 but the model slightly underestimated evapotranspiration for other years. The yield response factor was derived from observed yield data of the hybrid variety H708 when relative evapotranspiration deficits were smaller than 0.5. The value K_y = 1.32 was obtained. The relative yield decreases predicted with this K_y value compared well with observed data. Results support the use of the ISAREG model for developing water saving irrigation schedules for the Thracian plain.     

A computer simulation model of ovine fascioliasis

A computer simulation model of ovine fascioliasis was developed. The simulated flock, comprising a maximum of 60 non-reproductive sheep, grazed on a perennial pasture with a suitable habitat for the intermediate host snail Lymnaea tomentosa at the low end of a ‘gradient’ across the simulated 2-ha area. The driving force for both herbage production and the life cycle of Fasciola hepatica is meteorological information—comprising maximum and minimum daily temperatures and moisture (rainfall and any water supplied by irrigation). The model simulates intake of both herbage and metacercariae, with sheep seeking green herbage, if available, in preference to dry material. This automatically produces seasonal variation in the grazing pattern and hence in access to metacercariae. The production of wool and liveweight gain in sheep are simulated and include the interaction with fluke burden. Flock replacement is also dealt with and is made to closely replicate commercial management practices. The life cycle of F. hepatica is simulated in detail and the role of the intermediate host is dealt with by permitting the snail production to be in one of three states of physical activity, only one of which is suitable for completion of the development and release of cercariae. From information arising from the simulation, an economic comparison of the control strategies under test was made and the results printed.The completed model was validated against the results of a field study conducted by the authors at Prairie, Victoria, Australia (Meek & Morris, 1979) using meteorological data which had been measured at the field site as the model's driving force and then comparing the predictions of the model with the actual field measurements. The model was also validated against the results of a field investigation conducted in New South Wales, Australia, by Boray et al. (1969). The degree to which the model conformed with expectations and with the actual field data was assessed. In two respects the agreement between model predictions and field data was inadequate. First, the model overestimated the weight gain of the simular sheep on irrigated pasture under conditions of severe drought; secondly, simular snails were unexpectedly sensitive to changes in soil moisture. These aspects require further examination. Sensitivity analyses were also performed on the model. It was determined that simular financial return was sensitive to both stocking rate and the proportion of the simular area defined as snail habitat. Therefore both these factors warrant consideration in the choice of control strategies.Various control measures were simulated, by means of the validated model, either singly or in combination, and were assessed by means of the expected annual margin over variable husbandry costs obtained over the course of a five-year simulation period, from a standard flock of 100 sheep.With respect to the phophylactic use of anthelmintics, the model provided a method of ranking various alternatives at each of a number of combinations of stocking rate and snail habitat size. Under almost all simular circumstances tested, five to six strategically timed treatments produced the greatest economic benefit from controlling the disease. The model predicted that it was possible to eradicate ovine fascioliasis from a closed system if the recommended treatment strategy were rigidly followed over a number of years. Simular results also suggest that molluscicides may be integrated to economic advantage with anthelmintics in instances where the grazier opts for an anthelmintic treatment strategy with fever than the recommended optimal number of treatments per annum. It is also suggested that integration of rotational grazing with the use of anthelmintics warrants further investigation to ascertain if its apparent benefits can be realised in practice.It was concluded that the computer simulation model provides a formal framework within which alternative control strategies can be assessed and that it provides a basis for informed decision-making about potential control methods. Its predictions can now be tested under practical conditions.