The Experts below are selected from a list of 306 Experts worldwide ranked by ideXlab platform
Bruno Basso - One of the best experts on this subject based on the ideXlab platform.
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environmental and economic benefits of variable rate nitrogen fertilization in a nitrate vulnerable zone
Science of The Total Environment, 2016Co-Authors: Bruno Basso, Davide Cammarano, Benjamin Dumont, Andrea Pezzuolo, Franscesco Marinello, Luigi SartoriAbstract:Agronomic input and management practices have traditionally been applied uniformly on agricultural fields despite the presence of spatial variability of soil properties and landscape position. When spatial variability is ignored, uniform agronomic management can be both economically and environmentally inefficient. The objectives of this study were to: i) identify optimal N fertilizer rates using an integrated spatio-temporal analysis of yield and site-specific N rate response; ii) test the sensitivity of site specific N management to nitrate leaching in response to different N rates; and iii) demonstrate the environmental benefits of variable rate N fertilizer in a Nitrate Vulnerable Zone. This study was carried out on a 13.6 ha field near the Venice Lagoon, northeast Italy over four years (2005-2008). We utilized a validated Crop Simulation Model to evaluate Crop response to different N rates at specific zones in the field based on localized soil and landscape properties under rainfed conditions. The simulated rates were: 50 kg N ha(-1) applied at sowing for the entire study area and increasing fractions, ranging from 150 to 350 kg N ha(-1) applied at V6 stage. Based on the analysis of yield maps from previous harvests and soil electrical resistivity data, three management zones were defined. Two N rates were applied in each of these zones, one suggested by our Simulation analysis and the other with uniform N fertilization as normally applied by the producer. N leaching was lower and net revenue was higher in the zones where variable rates of N were applied when compared to uniform N fertilization. This demonstrates the efficacy of using Crop Models to determine variable rates of N fertilization within a field and the application of variable rate N fertilizer to achieve higher profit and reduce nitrate leaching.
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agronomic and economic evaluation of irrigation strategies on cotton lint yield in australia
Crop & Pasture Science, 2012Co-Authors: Bruno Basso, Davide Cammarano, Jose O Payero, Paul W Wilkens, Peter GraceAbstract:Cotton is one of the most important irrigated Crops in subtropical Australia. In recent years, cotton production has been severely affected by the worst drought in recorded history, with the 2007–08 growing season recording the lowest average cotton yield in 30 years. The use of a Crop Simulation Model to simulate the long-term temporal distribution of cotton yields under different levels of irrigation and the marginal value for each unit of water applied is important in determining the economic feasibility of current irrigation practices. The objectives of this study were to: (i) evaluate the CropGRO-Cotton Simulation Model for studying Crop growth under deficit irrigation scenarios across ten locations in New South Wales (NSW) and Queensland (Qld); (ii) evaluate agronomic and economic responses to water inputs across the ten locations; and (iii) determine the economically optimal irrigation level. The CropGRO-Cotton Simulation Model was evaluated using 2 years of experimental data collected at Kingsthorpe, Qld The Model was further evaluated using data from nine locations between northern NSW and southern Qld. Long-term Simulations were based on the prevalent furrow-irrigation practice of refilling the soil profile when the plant-available soil water content is <50%. The Model closely estimated lint yield for all locations evaluated. Our results showed that the amounts of water needed to maximise profit and maximise yield are different, which has economic and environmental implications. Irrigation needed to maximise profits varied with both agronomic and economic factors, which can be quite variable with season and location. Therefore, better tools and information that consider the agronomic and economic implications of irrigation decisions need to be developed and made available to growers.
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a strategic and tactical management approach to select optimal n fertilizer rates for wheat in a spatially variable field
European Journal of Agronomy, 2011Co-Authors: Bruno Basso, J T Ritchie, Davide Cammarano, Luigi SartoriAbstract:Abstract Wheat yield and protein content in a field are spatially variable due to inherent variability of soil properties and landscape. In Mediterranean environments yield variability in space and time is caused by irregular weather patterns, particularly rainfall, and by position in the landscape. A tested Crop Simulation Model, SALUS, was used to select optimal nitrogen fertilizer rates using strategic and tactical approaches in a spatially variable field where three distinct management zones had been previously identified. The Crop Model was tested and then used to simulate seven N rates from 0 to 180 kg N ha−1 with a 30 kg N ha−1 increments for 56 years using historical weather data. The available soil water at the time of N sidedressing each year and each management zone was correlated with yield response to N to evaluate the possibility of using the stored soil water to tactically determine N rates. Assuming recent production costs and grain prices the Simulations helped identify an optimal N rate for each of the zones based on agronomic, economic and environmental sustainability of N management. Results showed the high yielding zone had a maximum economic return and minimal environmental impact in terms of nitrate leaching by applying 90 kg N ha−1annually. On the other hand, the low yielding zone had little economic returns for application higher than 30 kg N ha−1. When simulated soil root-zone water was low at sidedressing, a lower fertilizer rate increased profit and decreased N leaching in the medium and high yielding zones.
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landscape position and precipitation effects on spatial variability of wheat yield and grain protein in southern italy
Journal of Agronomy and Crop Science, 2009Co-Authors: Bruno Basso, Davide Cammarano, Deli Chen, Giovanni Cafiero, Mariana Amato, Giovanni Bitella, Roberta Rossi, F BassoAbstract:Wheat yield and protein content are spatially variable because of inherent spatial variability of factors affecting the yield at field scale. In Mediterranean environments, yield variability is often caused by the irregular weather pattern, particularly rainfall and by position on the landscape. The objective of this study was to determine the effects of landscape position and rainfall on spatial variability of wheat yield and protein in a rolling terrain field of Southern Italy, and to propose stable management areas through Simulation Modelling and georesistivity imaging in rolling landscape. The study was carried out in Southern Italy, during 2 years of wheat monoculture; extensive soil properties and in-season plant measurements were measured. This study showed that soil water content was the main factor affecting spatial variation of yield for both years. The interactions between rainfall, topography and soil attributes increase the chances to observe yield variability among years. The principal component analysis demonstrated that for both years, soil water content explained most of the variability. The Crop Simulation Model provided excellent results when compared with measured data with root mean square error of 0.2 t ha ―1 . The simulated cumulative probability function showed that the Model was able to confirm the yield temporal stability of three different zones.
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water use efficiency is not constant when Crop water supply is adequate or fixed the role of agronomic management
European Journal of Agronomy, 2008Co-Authors: J T Ritchie, Bruno BassoAbstract:Increases in Crop production per unit of water used is imperative for supplying adequate food, feed, and fiber in an environment where future water supplies are expected to decrease. Previous work on Crop productivity per unit of water used (water use efficiency; WUE) has primarily dealt with Crops grown under water limited conditions and have usually not considered Crop management factors other than irrigation. Crop management can strongly influence yields when water is not limited. The aim of this paper is to demonstrate that transpiration per unit of productivity can vary greatly with agronomic management of Crops when soil water supply is adequate or fixed. Moreover, when yield from Crops with common development patterns are increased by better Crop management and improved cultivars, WUE is also increased. In recent decades high yields of maize have been accomplished with increased fertilizer and cultivars that tolerate high plant populations and uniform spacing. Although transpiration and soil evaporation (ET) occur simultaneously in the field, they are difficult to measure as separate components. However, the Crop Simulation Model CERES maize can reasonably estimate each component. The CERES Maize Model was used to assess how plant population, genetic type and weather influence yields and WUE. Simulated yield response of an old and modern hybrid to a wide range of plant densities and uniformity patterns agreed reasonably well with observations suggesting that plant densities need to be near 10‐11plantm −2 and uniformly spaced to obtain near maximum yield and WUE for Midwest USA climate.
Neil B Mclaughlin - One of the best experts on this subject based on the ideXlab platform.
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effects of tillage and traffic on Crop production in dryland farming systems i evaluation of perfect soil Crop Simulation Model
Soil & Tillage Research, 2008Co-Authors: J N Tullberg, D M Freebairn, Neil B MclaughlinAbstract:Agricultural production systems are complex involving variability in climate, soil, Crop, tillage management and interactions between these components. The traditional experimental approach has played an important role in studying Crop production systems, but isolation of these factors in experimental studies is difficult and time consuming. Computer Simulation Models are useful in exploring these interactions and provide a valuable tool to test and further our understanding of the behavior of soil-Crop systems without repeating experimentation. Productivity erosion and runoff functions to evaluate conservation techniques (PERFECT) is one of the soil-Crop Models that integrate the dynamics of soil, tillage and Crop processes at a daily resolution. This study had two major objectives. The first was to calibrate the use of the PERFECT soil-Crop Simulation Model to simulate soil and Crop responses to changes of traffic and tillage management. The second was to explore the interactions between traffic, tillage, soil and Crop, and provide insight to the long-term effects of improved soil management and Crop rotation options. This contribution covers only the first objective, and the second will be covered in a subsequent contribution. Data were obtained from field experiments on a vertisol in Southeast Queensland, Australia which had controlled traffic and tillage treatments for the previous 5 years. Input data for the Simulation Model included daily weather, runoff, plant available water capacity, and soil hydraulic properties, Cropping systems, and traffic and tillage management. After Model calibration, predicted and measured total runoffs for the 5-year period were similar. Values of root mean square error (RMSE) for daily runoff ranged from 5.7 to 9.2 mm, which were similar to those reported in literature. The Model explained 75-95% of variations of daily, monthly and annual runoff, 70-84% of the variation in total available soil water, and 85% of the variation in yield. The results showed that the PERFECT daily soil-Crop Simulation Model could be used to generate meaningful predictions of the interactions between Crop, soil and water under different tillage and traffic systems. Ranking of management systems in order of decreasing merit for runoff, available soil water and Crop yield was (1) controlled traffic zero tillage, (2) controlled traffic stubble mulch, (3) wheeled zero tillage, and (4) wheeled stubble mulch.
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effects of tillage and traffic on Crop production in dryland farming systems ii long term Simulation of Crop production using the perfect Model
Soil & Tillage Research, 2008Co-Authors: J N Tullberg, D M Freebairn, Neil B MclaughlinAbstract:Abstract Soil water conservation is critical to long-term Crop production in dryland Cropping areas in Northeast Australia. Many field studies have shown the benefits of controlled traffic and zero tillage in terms of runoff and soil erosion reduction, soil moisture retention and Crop yield improvement. However, there is lack of understanding of the long-term effect of the combination of controlled traffic and zero tillage practices, as compared with other tillage and traffic management practices. In this study, a Modeling approach was used to estimate the long-term effect of tillage, traffic, Crop rotation and type, and soil management practices in a heavy clay soil. The PERFECT soil–Crop Simulation Model was calibrated with data from a 5-year field experiment in Northeast Australia in terms of runoff, available soil water and Crop yield; the procedure and outcomes of this calibration were given in a previous contribution. Three Cropping systems with different tillage and traffic treatments were simulated with the Model over a 44-year-period using archived weather data. Results showed higher runoff, and lower soil moisture and Crop production with conventional tillage and accompanying field traffic than with controlled traffic and zero tillage. The effect of traffic is greater than the effect of tillage over the long-term. The best traffic, tillage and Crop management system was controlled traffic zero tillage in a high Crop intensity rotation, and the worst was conventional traffic and stubble mulch with continuous wheat. Increased water infiltration and reduced runoff under controlled traffic resulted in more available soil water and higher Crop yield under opportunity Cropping systems.
Gilles Tison - One of the best experts on this subject based on the ideXlab platform.
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heliaphen an outdoor high throughput phenotyping platform for genetic studies and Crop Modeling
Frontiers in Plant Science, 2019Co-Authors: Florie Gosseau, Nicolas Blanchet, D Vares, Philippe Burger, Didier Campergue, Celine Colombet, Louise Gody, Jeanfrancois Lievin, Brigitte Mangin, Gilles TisonAbstract:Heliaphen is an outdoor platform designed for high-throughput phenotyping. It allows the automated management of drought scenarios and monitoring of plants throughout their lifecycles. A robot moving between plants growing in 15-L pots monitors the plant water status and phenotypes the leaf or whole-plant morphology. From these measurements, we can compute more complex traits, such as leaf expansion (LE) or transpiration rate (TR) in response to water deficit. Here, we illustrate the capabilities of the platform with two practical cases in sunflower (Helianthus annuus): a genetic and genomic study of the response of yield-related traits to drought, and a Modeling study using measured parameters as inputs for a Crop Simulation. For the genetic study, classical measurements of thousand-kernel weight (TKW) were performed on a biparental population under automatically managed drought stress and control conditions. These data were used for an association study, which identified five genetic markers of the TKW drought response. A complementary transcriptomic analysis identified candidate genes associated with these markers that were differentially expressed in the parental backgrounds in drought conditions. For the Simulation study, we used a Crop Simulation Model to predict the impact on Crop yield of two traits measured on the platform (LE and TR) for a large number of environments. We conducted Simulations in 42 contrasting locations across Europe using 21 years of climate data. We defined the pattern of abiotic stresses occurring at the continental scale and identified ideotypes (i.e., genotypes with specific trait values) that are more adapted to specific environment types. This study exemplifies how phenotyping platforms can assist the identification of the genetic architecture controlling complex response traits and facilitate the estimation of ecophysiological Model parameters to define ideotypes adapted to different environmental conditions.
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Data_Sheet_4_Heliaphen, an Outdoor High-Throughput Phenotyping Platform for Genetic Studies and Crop Modeling.CSV
2019Co-Authors: Florie Gosseau, Nicolas Blanchet, D Vares, Philippe Burger, Didier Campergue, Celine Colombet, Louise Gody, Jeanfrancois Lievin, Brigitte Mangin, Gilles TisonAbstract:Heliaphen is an outdoor platform designed for high-throughput phenotyping. It allows the automated management of drought scenarios and monitoring of plants throughout their lifecycles. A robot moving between plants growing in 15-L pots monitors the plant water status and phenotypes the leaf or whole-plant morphology. From these measurements, we can compute more complex traits, such as leaf expansion (LE) or transpiration rate (TR) in response to water deficit. Here, we illustrate the capabilities of the platform with two practical cases in sunflower (Helianthus annuus): a genetic and genomic study of the response of yield-related traits to drought, and a Modeling study using measured parameters as inputs for a Crop Simulation. For the genetic study, classical measurements of thousand-kernel weight (TKW) were performed on a biparental population under automatically managed drought stress and control conditions. These data were used for an association study, which identified five genetic markers of the TKW drought response. A complementary transcriptomic analysis identified candidate genes associated with these markers that were differentially expressed in the parental backgrounds in drought conditions. For the Simulation study, we used a Crop Simulation Model to predict the impact on Crop yield of two traits measured on the platform (LE and TR) for a large number of environments. We conducted Simulations in 42 contrasting locations across Europe using 21 years of climate data. We defined the pattern of abiotic stresses occurring at the continental scale and identified ideotypes (i.e., genotypes with specific trait values) that are more adapted to specific environment types. This study exemplifies how phenotyping platforms can assist the identification of the genetic architecture controlling complex response traits and facilitate the estimation of ecophysiological Model parameters to define ideotypes adapted to different environmental conditions.
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Table_1_Heliaphen, an Outdoor High-Throughput Phenotyping Platform for Genetic Studies and Crop Modeling.DOCX
2019Co-Authors: Florie Gosseau, Nicolas Blanchet, D Vares, Philippe Burger, Didier Campergue, Celine Colombet, Louise Gody, Jeanfrancois Lievin, Brigitte Mangin, Gilles TisonAbstract:Heliaphen is an outdoor platform designed for high-throughput phenotyping. It allows the automated management of drought scenarios and monitoring of plants throughout their lifecycles. A robot moving between plants growing in 15-L pots monitors the plant water status and phenotypes the leaf or whole-plant morphology. From these measurements, we can compute more complex traits, such as leaf expansion (LE) or transpiration rate (TR) in response to water deficit. Here, we illustrate the capabilities of the platform with two practical cases in sunflower (Helianthus annuus): a genetic and genomic study of the response of yield-related traits to drought, and a Modeling study using measured parameters as inputs for a Crop Simulation. For the genetic study, classical measurements of thousand-kernel weight (TKW) were performed on a biparental population under automatically managed drought stress and control conditions. These data were used for an association study, which identified five genetic markers of the TKW drought response. A complementary transcriptomic analysis identified candidate genes associated with these markers that were differentially expressed in the parental backgrounds in drought conditions. For the Simulation study, we used a Crop Simulation Model to predict the impact on Crop yield of two traits measured on the platform (LE and TR) for a large number of environments. We conducted Simulations in 42 contrasting locations across Europe using 21 years of climate data. We defined the pattern of abiotic stresses occurring at the continental scale and identified ideotypes (i.e., genotypes with specific trait values) that are more adapted to specific environment types. This study exemplifies how phenotyping platforms can assist the identification of the genetic architecture controlling complex response traits and facilitate the estimation of ecophysiological Model parameters to define ideotypes adapted to different environmental conditions.
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heliaphen an outdoor high throughput phenotyping platform designed to integrate genetics and Crop Modeling
bioRxiv, 2018Co-Authors: Florie Gosseau, Nicolas Blanchet, D Vares, Philippe Burger, Didier Campergue, Celine Colombet, Louise Gody, Jeanfrancois Lievain, Brigitte Mangin, Gilles TisonAbstract:Heliaphen is an outdoor pot platform designed for high-throughput phenotyping. It allows automated management of drought scenarios and plant monitoring during the whole plant cycle. A robot moving between plants growing in 15L pots monitors plant water status and phenotypes plant or leaf morphology, from which we can compute more complex traits such as the response of leaf expansion (LE) or plant transpiration (TR) to water deficit. Here, we illustrate the platform capabilities for sunflower on two practical cases: a genetic and genomics study for the response to drought of yield-related traits and a Simulation study, where we use measured parameters as inputs for a Crop Simulation Model. For the genetic study, classical measurements of thousand-kernel weight (TKW) were done on a sunflower bi-parental population under water stress and control conditions managed automatically. The association study using the TKW drought-response highlighted five genetic markers. A complementary transcriptomic experiment identified closeby candidate genes differentially expressed in the parental backgrounds in drought conditions. For the Simulation study, we used the SUNFLO Crop Simulation Model to assess the impact of two traits measured on the platform (LE and TR) on Crop yield in a large population of environments. We conducted Simulations in 42 contrasted locations across Europe and 21 years of climate data. We defined the pattern of abiotic stresses occurring at this continental scale and identified ideotypes (i.e. genotypes with specific traits values) that are more adapted to specific environment types. This study exemplifies how phenotyping platforms can help with the identification of the genetic architecture of complex response traits and the estimation of eco-physiological Model parameters in order to define ideotypes adapted to different environmental conditions.
J N Tullberg - One of the best experts on this subject based on the ideXlab platform.
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effects of tillage and traffic on Crop production in dryland farming systems i evaluation of perfect soil Crop Simulation Model
Soil & Tillage Research, 2008Co-Authors: J N Tullberg, D M Freebairn, Neil B MclaughlinAbstract:Agricultural production systems are complex involving variability in climate, soil, Crop, tillage management and interactions between these components. The traditional experimental approach has played an important role in studying Crop production systems, but isolation of these factors in experimental studies is difficult and time consuming. Computer Simulation Models are useful in exploring these interactions and provide a valuable tool to test and further our understanding of the behavior of soil-Crop systems without repeating experimentation. Productivity erosion and runoff functions to evaluate conservation techniques (PERFECT) is one of the soil-Crop Models that integrate the dynamics of soil, tillage and Crop processes at a daily resolution. This study had two major objectives. The first was to calibrate the use of the PERFECT soil-Crop Simulation Model to simulate soil and Crop responses to changes of traffic and tillage management. The second was to explore the interactions between traffic, tillage, soil and Crop, and provide insight to the long-term effects of improved soil management and Crop rotation options. This contribution covers only the first objective, and the second will be covered in a subsequent contribution. Data were obtained from field experiments on a vertisol in Southeast Queensland, Australia which had controlled traffic and tillage treatments for the previous 5 years. Input data for the Simulation Model included daily weather, runoff, plant available water capacity, and soil hydraulic properties, Cropping systems, and traffic and tillage management. After Model calibration, predicted and measured total runoffs for the 5-year period were similar. Values of root mean square error (RMSE) for daily runoff ranged from 5.7 to 9.2 mm, which were similar to those reported in literature. The Model explained 75-95% of variations of daily, monthly and annual runoff, 70-84% of the variation in total available soil water, and 85% of the variation in yield. The results showed that the PERFECT daily soil-Crop Simulation Model could be used to generate meaningful predictions of the interactions between Crop, soil and water under different tillage and traffic systems. Ranking of management systems in order of decreasing merit for runoff, available soil water and Crop yield was (1) controlled traffic zero tillage, (2) controlled traffic stubble mulch, (3) wheeled zero tillage, and (4) wheeled stubble mulch.
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effects of tillage and traffic on Crop production in dryland farming systems ii long term Simulation of Crop production using the perfect Model
Soil & Tillage Research, 2008Co-Authors: J N Tullberg, D M Freebairn, Neil B MclaughlinAbstract:Abstract Soil water conservation is critical to long-term Crop production in dryland Cropping areas in Northeast Australia. Many field studies have shown the benefits of controlled traffic and zero tillage in terms of runoff and soil erosion reduction, soil moisture retention and Crop yield improvement. However, there is lack of understanding of the long-term effect of the combination of controlled traffic and zero tillage practices, as compared with other tillage and traffic management practices. In this study, a Modeling approach was used to estimate the long-term effect of tillage, traffic, Crop rotation and type, and soil management practices in a heavy clay soil. The PERFECT soil–Crop Simulation Model was calibrated with data from a 5-year field experiment in Northeast Australia in terms of runoff, available soil water and Crop yield; the procedure and outcomes of this calibration were given in a previous contribution. Three Cropping systems with different tillage and traffic treatments were simulated with the Model over a 44-year-period using archived weather data. Results showed higher runoff, and lower soil moisture and Crop production with conventional tillage and accompanying field traffic than with controlled traffic and zero tillage. The effect of traffic is greater than the effect of tillage over the long-term. The best traffic, tillage and Crop management system was controlled traffic zero tillage in a high Crop intensity rotation, and the worst was conventional traffic and stubble mulch with continuous wheat. Increased water infiltration and reduced runoff under controlled traffic resulted in more available soil water and higher Crop yield under opportunity Cropping systems.
D M Freebairn - One of the best experts on this subject based on the ideXlab platform.
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effects of tillage and traffic on Crop production in dryland farming systems i evaluation of perfect soil Crop Simulation Model
Soil & Tillage Research, 2008Co-Authors: J N Tullberg, D M Freebairn, Neil B MclaughlinAbstract:Agricultural production systems are complex involving variability in climate, soil, Crop, tillage management and interactions between these components. The traditional experimental approach has played an important role in studying Crop production systems, but isolation of these factors in experimental studies is difficult and time consuming. Computer Simulation Models are useful in exploring these interactions and provide a valuable tool to test and further our understanding of the behavior of soil-Crop systems without repeating experimentation. Productivity erosion and runoff functions to evaluate conservation techniques (PERFECT) is one of the soil-Crop Models that integrate the dynamics of soil, tillage and Crop processes at a daily resolution. This study had two major objectives. The first was to calibrate the use of the PERFECT soil-Crop Simulation Model to simulate soil and Crop responses to changes of traffic and tillage management. The second was to explore the interactions between traffic, tillage, soil and Crop, and provide insight to the long-term effects of improved soil management and Crop rotation options. This contribution covers only the first objective, and the second will be covered in a subsequent contribution. Data were obtained from field experiments on a vertisol in Southeast Queensland, Australia which had controlled traffic and tillage treatments for the previous 5 years. Input data for the Simulation Model included daily weather, runoff, plant available water capacity, and soil hydraulic properties, Cropping systems, and traffic and tillage management. After Model calibration, predicted and measured total runoffs for the 5-year period were similar. Values of root mean square error (RMSE) for daily runoff ranged from 5.7 to 9.2 mm, which were similar to those reported in literature. The Model explained 75-95% of variations of daily, monthly and annual runoff, 70-84% of the variation in total available soil water, and 85% of the variation in yield. The results showed that the PERFECT daily soil-Crop Simulation Model could be used to generate meaningful predictions of the interactions between Crop, soil and water under different tillage and traffic systems. Ranking of management systems in order of decreasing merit for runoff, available soil water and Crop yield was (1) controlled traffic zero tillage, (2) controlled traffic stubble mulch, (3) wheeled zero tillage, and (4) wheeled stubble mulch.
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effects of tillage and traffic on Crop production in dryland farming systems ii long term Simulation of Crop production using the perfect Model
Soil & Tillage Research, 2008Co-Authors: J N Tullberg, D M Freebairn, Neil B MclaughlinAbstract:Abstract Soil water conservation is critical to long-term Crop production in dryland Cropping areas in Northeast Australia. Many field studies have shown the benefits of controlled traffic and zero tillage in terms of runoff and soil erosion reduction, soil moisture retention and Crop yield improvement. However, there is lack of understanding of the long-term effect of the combination of controlled traffic and zero tillage practices, as compared with other tillage and traffic management practices. In this study, a Modeling approach was used to estimate the long-term effect of tillage, traffic, Crop rotation and type, and soil management practices in a heavy clay soil. The PERFECT soil–Crop Simulation Model was calibrated with data from a 5-year field experiment in Northeast Australia in terms of runoff, available soil water and Crop yield; the procedure and outcomes of this calibration were given in a previous contribution. Three Cropping systems with different tillage and traffic treatments were simulated with the Model over a 44-year-period using archived weather data. Results showed higher runoff, and lower soil moisture and Crop production with conventional tillage and accompanying field traffic than with controlled traffic and zero tillage. The effect of traffic is greater than the effect of tillage over the long-term. The best traffic, tillage and Crop management system was controlled traffic zero tillage in a high Crop intensity rotation, and the worst was conventional traffic and stubble mulch with continuous wheat. Increased water infiltration and reduced runoff under controlled traffic resulted in more available soil water and higher Crop yield under opportunity Cropping systems.