Relevant bibliographies by topics / Crop growth simulation modelling

Academic literature on the topic 'Crop growth simulation modelling'

Author: Grafiati
Published: 4 June 2021
Last updated: 21 February 2023

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Contents

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Crop growth simulation modelling.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Crop growth simulation modelling"

1

Sangale, Bhagwan, U. M. Khodke H. W. Awari, and Vishal Ingle. "Crop Growth Simulation Modelling - A Review." International Journal of Current Microbiology and Applied Sciences 11, no. 1 (January 10, 2022): 78–84. http://dx.doi.org/10.20546/ijcmas.2022.1101.010.

Full text
Abstract:
Agriculture plays a key role in overall economic and social wellbeing of the specially developing countries. Now it is the right option to increase the quality and quantity of food production through the technological and managerial interventions like crop growth and yield prediction models. Agricultural models are mathematical equations that represent the reactions that occur within the plant and the interactions between the plant and its environment. The model simulates or imitates the behaviour of real crop by predicting the growth of its components, such as leaves, roots, stems and grains. Thus, a crop growth model not only predicts the final state of total biomass or harvestable yield, but also contains quantitative information about major processes involved in the growth and development of a plant. Crop Growth Simulation models are a formal way to present quantitative knowledge about how a crop grows in interaction with its environment. Using weather data and other data about the crop environment, these models can simulate crop development, growth, yield, water, and nutrient uptake. Crop models are mathematical algorithms that capture the quantitative information of agronomy and physiology experiments in a way that can explain and predict crop growth and development. They can simulate many seasons, locations, treatments, and scenarios in a few minutes. Crop models contribute to agriculture in many ways. They help explore the dynamics between the atmosphere, the crop, and the soil, assist in crop agronomy, pest management, breeding, and natural resource management, and assess the impact of climate change.
APA, Harvard, Vancouver, ISO, and other styles
2

Bouman, B. A. M. "Crop modelling and remote sensing for yield prediction." Netherlands Journal of Agricultural Science 43, no. 2 (June 1, 1995): 143–61. http://dx.doi.org/10.18174/njas.v43i2.573.

Full text
Abstract:
Methods for the application of crop growth models, remote sensing and their integrative use for yield forecasting and prediction are presented. First, the general principles of crop growth models are explained. When crop simulation models are used on regional scales, uncertainty and spatial variation in model parameters can result in broad bands of simulated yield. Remote sensing can be used to reduce some of this uncertainty. With optical remote sensing, standard relations between the Weighted Difference Vegetation Index and fraction ground cover and LAI were established for a number of crops. The radar backscatter of agricultural crops was found to be largely affected by canopy structure, and, for most crops, no consistent relationships with crop growth indicators were established. Two approaches are described to integrate remote sensing data with crop growth models. In the first one, measures of light interception (ground cover, LAI) estimated from optical remote sensing are used as forcing function in the models. In the second method, crop growth models are extended with remote sensing sub-models to simulate time-series of optical and radar remote sensing signals. These simulated signals are compared to measured signals, and the crop growth model is re-calibrated to match simulated with measured remote sensing data. The developed methods resulted in increased accuracy in the simulation of crop growth and yield of wheat and sugar beet in a number of case-studies.
APA, Harvard, Vancouver, ISO, and other styles
3

van Walsum, P. E. V., and I. Supit. "Influence of ecohydrologic feedbacks from simulated crop growth on integrated regional hydrologic simulations under climate scenarios." Hydrology and Earth System Sciences 16, no. 6 (June 1, 2012): 1577–93. http://dx.doi.org/10.5194/hess-16-1577-2012.

Full text
Abstract:
Abstract. Hydrologic climate change modelling is hampered by climate-dependent model parameterizations. To reduce this dependency, we extended the regional hydrologic modelling framework SIMGRO to host a two-way coupling between the soil moisture model MetaSWAP and the crop growth simulation model WOFOST, accounting for ecohydrologic feedbacks in terms of radiation fraction that reaches the soil, crop coefficient, interception fraction of rainfall, interception storage capacity, and root zone depth. Except for the last, these feedbacks are dependent on the leaf area index (LAI). The influence of regional groundwater on crop growth is included via a coupling to MODFLOW. Two versions of the MetaSWAP-WOFOST coupling were set up: one with exogenous vegetation parameters, the "static" model, and one with endogenous crop growth simulation, the "dynamic" model. Parameterization of the static and dynamic models ensured that for the current climate the simulated long-term averages of actual evapotranspiration are the same for both models. Simulations were made for two climate scenarios and two crops: grass and potato. In the dynamic model, higher temperatures in a warm year under the current climate resulted in accelerated crop development, and in the case of potato a shorter growing season, thus partly avoiding the late summer heat. The static model has a higher potential transpiration; depending on the available soil moisture, this translates to a higher actual transpiration. This difference between static and dynamic models is enlarged by climate change in combination with higher CO2 concentrations. Including the dynamic crop simulation gives for potato (and other annual arable land crops) systematically higher effects on the predicted recharge change due to climate change. Crop yields from soils with poor water retention capacities strongly depend on capillary rise if moisture supply from other sources is limited. Thus, including a crop simulation model in an integrated hydrologic simulation provides a valuable addition for hydrologic modelling as well as for crop modelling.
APA, Harvard, Vancouver, ISO, and other styles
4

Kleemola, Jouko, and Tuomo Karvonen. "Modelling growth and nitrogen balance of barley under ambient and future conditions." Agricultural and Food Science 5, no. 3 (May 1, 1996): 299–310. http://dx.doi.org/10.23986/afsci.72748.

Full text
Abstract:
According to current scenarios, atmospheric CO2 -concentration ([CO2]) and average air temperature will rise in the future. The predicted longer growing season in Finland would imply that more productive cultivars and even new crop species could be grown. Moreover, higher [CO2] is also likely to increase dry matter production of crops. This study analyzed the growth of spring barley (Hordeum vulgare L.) under ambient and suggested future conditions, and its response to N fertilization. Model simulations of soil temperature and of snow accumulation and melting were also studied. The calibration and validation results showed that the model performed well in simulating snow dynamics, soil temperature, the growth of barley, and the response of crop growth to N fertilization under present conditions. According to the simulation runs, if a cultivar was adapted to the length of the growing period, the increase in dry matter production was 23% in a low estimate scenario of climate change, and 56% in a high estimate scenario under a high level of nitrogen fertilization. The simulation study showed that the shoot dry weight increased by 43%, on average, under high N fertilization (150-200 kg N/ha), but by less (20%) under a low level of N (25-50 kg N/ha) when the conditions under a central scenario for the year 2050 were compared with the present ones.
APA, Harvard, Vancouver, ISO, and other styles
5

Racsko, P., and M. Semenov. "Analysis of mathematical principles in crop growth simulation models." Ecological Modelling 47, no. 3-4 (September 1989): 291–302. http://dx.doi.org/10.1016/0304-3800(89)90007-0.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Chander, Subhash, Naveen Kalra, and P. K. Aggarwal. "Development and Application of Crop Growth Simulation Modelling in Pest Management." Outlook on Agriculture 36, no. 1 (March 2007): 63–70. http://dx.doi.org/10.5367/000000007780223704.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Zhang, Yu, Changsheng Li, Xiuji Zhou, and Berrien Moore. "A simulation model linking crop growth and soil biogeochemistry for sustainable agriculture." Ecological Modelling 151, no. 1 (May 2002): 75–108. http://dx.doi.org/10.1016/s0304-3800(01)00527-0.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Probert, M. E., P. S. Carberry, R. L. McCown, and J. E. Turpin. "Simulation of legume-cereal systems using APSIM." Australian Journal of Agricultural Research 49, no. 3 (1998): 317. http://dx.doi.org/10.1071/a97070.

Full text
Abstract:
A major issue for the sustainability of cropping systems is the maintenance of soil fertility and especially the supply of nitrogen to cereal crops. Choice of appropriate management strategies, including the role of legumes, is problematic, especially where climatic variation is large. Simulation models provide the means of extrapolation from the site- and season-specific bounds of experimental data to permit scenario analyses that can explore alternative management options. This paper is a status report on the capabilities of the APSIM modelling framework to simulate legume-cereal systems. APSIM deals with water and nitrogen constraints to crop growth and is well suited to the task of modelling whole systems involving crop rotations. The components that are not yet fully developed are modules for growing the legume crops and coupling these with the module describing the dynamics of soil organic matter to obtain sensible predictions of nitrogen supply to subsequent crops. Evidence is provided that those parts of the system that can be represented by current APSIM modules are predicted satisfactorily. The closest approach to a whole system that has been simulated to date is grass or legume (Stylosanthes hamata cv. Verano) leys followed by crops of maize or sorghum grown in experiments at Katherine, NT. Predictions of the yields of the leys and the cereal crops, especially the benefit from the legume leys to a second crop, were sufficiently close to measured yields to suggest that there are good prospects for developing useful models of other systems involving legumes and cereals. A simulation scenario exploring a chickpea-wheat system demonstrates how models can be used to analyse both productivity and sustainability aspects of the system.
APA, Harvard, Vancouver, ISO, and other styles
9

Nguyen, Van Cuong, Seungtaek Jeong, Jonghan Ko, Chi Tim Ng, and Jongmin Yeom. "Mathematical Integration of Remotely-Sensed Information into a Crop Modelling Process for Mapping Crop Productivity." Remote Sensing 11, no. 18 (September 13, 2019): 2131. http://dx.doi.org/10.3390/rs11182131.

Full text
Abstract:
Remote sensing is a useful technique to determine spatial variations in crop growth while crop modelling can reproduce temporal changes in crop growth. In this study, we formulated a hybrid system of remote sensing and crop modelling based on a random-effect model and the empirical Bayesian approach for parameter estimation. Moreover, the relationship between the reflectance and the leaf area index was incorporated into the statistical model. Plant growth and ground-based canopy reflectance data of paddy rice were measured at three study sites in South Korea. Spatiotemporal vegetation indices were processed using remotely-sensed data from the RapidEye satellite and the Communication Ocean and Meteorological Satellite (COMS). Solar insulation data were obtained from the Meteorological Imager (MI) sensor of the COMS. Reanalysis of air temperature data was collected from the Korea Local Analysis and Prediction System (KLAPS). We report on a statistical hybrid approach of crop modelling and remote sensing and a method to project spatiotemporal crop growth information. Our study results show that the crop growth values predicted using the hybrid scheme were in statistically acceptable agreement with the corresponding measurements. Simulated yields were not significantly different from the measured yields at p = 0.883 in calibration and p = 0.839 in validation, according to two-sample t tests. In a geospatial simulation of yield, no significant difference was found between the simulated and observed mean value at p = 0.392 based on a two-sample t test as well. The fabricated approach allows us to monitor crop growth information and estimate crop-modelling processes using remote sensing data from various platforms and optical sensors with different ground resolutions.
APA, Harvard, Vancouver, ISO, and other styles
10

Li, F. Y., P. D. Jamieson, P. R. Johnstone, and A. J. Pearson. "Mechanisms of nitrogen limitation affecting maize growth: a comparison of different modelling hypotheses." Crop and Pasture Science 60, no. 8 (2009): 738. http://dx.doi.org/10.1071/cp08412.

Full text
Abstract:
Two hypothetical mechanisms exist for quantifying crop nitrogen (N) demand and N-deficit effects on crop growth. The Critical N mechanism uses a critical N concentration, while the Leaf N mechanism distinguishes active N in leaves from the N elsewhere in shoots. These two mechanisms were implemented in parallel in a maize model (Amaize) to evaluate their adequacy in predicting crop growth and development. In the Leaf N mechanism, two approaches for quantifying N-deficit effects, by reducing green leaf area (GAI) or diluting specific leaf nitrogen (SLN), were also examined. The model-predicted plant biomass, grain yield, and N uptake were compared with measurements from 47 maize crops grown on 16 sites receiving different N fertiliser treatments. The results showed that model-predicted plant biomass, grain yield and N uptake were insensitive to the approaches used for quantifying N-deficit effects in the Leaf N mechanism. The model-predicted plant biomass, grain yield and N uptake using either N approach were significantly related to measurements (P < 0.01) but had considerable deviations (r2 = 0.66–0.69 for biomass, 0.50–0.54 for grain yield: 0.17–0.33 for N uptake). The linear fits of the predicted against measured values showed no significant difference (P > 0.1) among the three N approaches, with the Leaf N mechanism predicting smaller deviation than the Critical N mechanism. However, the Critical N mechanism was better in simulating plant growth dynamics in early plant growth stages. The Leaf N mechanism distinguished functional from structural N pools in plants, having a sound physiological base. The simulation using the Leaf N mechanism with both SLN dilution and GAI reduction for quantifying N-deficit effects was the best in predicting crop growth and yield.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Crop growth simulation modelling"

1

Florin, Madeleine Jill. "Towards Precision Agriculture for whole farms using a combination of simulation modelling and spatially dense soil and crop information." Thesis, The University of Sydney, 2008. http://hdl.handle.net/2123/3169.

Full text
Abstract:
Precision Agriculture (PA) strives towards holistic production and environmental management. A fundamental research challenge is the continuous expansion of ideas about how PA can contribute to sustainable agriculture. Some associated pragmatic research challenges include quantification of spatio-temporal variation of crop yield; crop growth simulation modelling within a PA context and; evaluating long-term financial and environmental outcomes from site-specific crop management (SSCM). In Chapter 1 literature about managing whole farms with a mind towards sustainability was reviewed. Alternative agricultural systems and concepts including systems thinking, agro-ecology, mosaic farming and PA were investigated. With respect to environmental outcomes it was found that PA research is relatively immature. There is scope to thoroughly evaluate PA from a long-term, whole-farm environmental and financial perspective. Comparatively, the emphasis of PA research on managing spatial variability offers promising and innovative ways forward, particularly in terms of designing new farming systems. It was found that using crop growth simulation modelling in a PA context is potentially very useful. Modelling high-resolution spatial and temporal variability with current simulation models poses a number of immediate research issues. This research focused on three whole farms located in Australia that grow predominantly grains without irrigation. These study sites represent three important grain growing regions within Australia. These are northern NSW, north-east Victoria and South Australia. Note-worthy environmental and climatic differences between these regions such as rainfall timing, soil type and topographic features were outlined in Chapter 2. When considering adoption of SSCM, it is essential to understand the impact of temporal variation on the potential value of managing spatial variation. Quantifying spatiotemporal variation of crop yield serves this purpose; however, this is a conceptually and practically challenging undertaking. A small number of previous studies have found that the magnitude of temporal variation far exceeds that of spatial variation. Chapter 3 of this thesis dealt with existing and new approaches quantifying the relationship between spatial and temporal variability in crop yield. It was found that using pseudo cross variography to obtain spatial and temporal variation ‘equivalents’ is a promising approach to quantitatively comparing spatial and temporal variation. The results from this research indicate that more data in the temporal dimension is required to enable thorough analysis using this approach. This is particularly relevant when questioning the suitability of SSCM. Crop growth simulation modelling offers PA a number of benefits such as the ability to simulate a considerable volume of data in the temporal dimension. A dominant challenge recognised within the PA/modelling literature is the mismatch between the spatial resolution of point-based model output (and therefore input) and the spatial resolution of information demanded by PA. This culminates into questions about the conceptual model underpinning the simulation model and the practicality of using point-based models to simulate spatial variability. iii The ability of point-based models to simulate appropriate spatial and temporal variability of crop yield and the importance of soil available water capacity (AWC) for these simulations were investigated in Chapter 4. The results indicated that simulated spatial variation is low compared to some previously reported spatial variability of real yield data for some climate years. It was found that the structure of spatial yield variation was directly related to the structure of the AWC and interactions between AWC and climate. It is apparent that varying AWC spatially is a reasonable starting point for modelling spatial variation of crop yield. A trade-off between capturing adequate spatio-temporal variation of crop yield and the inclusion of realistically obtainable model inputs is identified. A number of practical solutions to model parameterisation for PA purposes are identified in the literature. A popular approach is to minimise the number of simulations required. Another approach that enables modelling at every desired point across a study area involves taking advantage of high-resolution yield information from a number of years to estimate site-specific soil properties with the inverse use of a crop growth simulation model. Inverse meta-modelling was undertaken in Chapter 5 to estimate AWC on 10- metre grids across each of the study farms. This proved to be an efficient approach to obtaining high-resolution AWC information at the spatial extent of whole farms. The AWC estimates proved useful for yield prediction using simple linear regression as opposed to application within a complex crop growth simulation model. The ability of point-based models to simulate spatial variation was re-visited in Chapter 6 with respect to the exclusion of lateral water movement. The addition of a topographic component into the simple point-based yield prediction models substantially improved yield predictions. The value of these additions was interpreted using coefficients of determination and comparing variograms for each of the yield prediction components. A result consistent with the preceding chapter is the importance of further validating the yield prediction models with further yield data when it becomes available. Finally, some whole-farm management scenarios using SSCM were synthesised in Chapter 7. A framework that enables evaluation of the long-term (50 years) farm outcomes soil carbon sequestration, nitrogen leaching and crop yield was established. The suitability of SSCM across whole-farms over the long term was investigated and it was found that the suitability of SSCM is confined to certain fields. This analysis also enabled identification of parts of the farms that are the least financially and environmentally viable. SSCM in conjunction with other PA management strategies is identified as a promising approach to long-term and whole-farm integrated management.
APA, Harvard, Vancouver, ISO, and other styles
2

Florin, Madeleine Jill. "Towards Precision Agriculture for whole farms using a combination of simulation modelling and spatially dense soil and crop information." University of Sydney, 2008. http://hdl.handle.net/2123/3169.

Full text
Abstract:
Doctor of Philosophy
Precision Agriculture (PA) strives towards holistic production and environmental management. A fundamental research challenge is the continuous expansion of ideas about how PA can contribute to sustainable agriculture. Some associated pragmatic research challenges include quantification of spatio-temporal variation of crop yield; crop growth simulation modelling within a PA context and; evaluating long-term financial and environmental outcomes from site-specific crop management (SSCM). In Chapter 1 literature about managing whole farms with a mind towards sustainability was reviewed. Alternative agricultural systems and concepts including systems thinking, agro-ecology, mosaic farming and PA were investigated. With respect to environmental outcomes it was found that PA research is relatively immature. There is scope to thoroughly evaluate PA from a long-term, whole-farm environmental and financial perspective. Comparatively, the emphasis of PA research on managing spatial variability offers promising and innovative ways forward, particularly in terms of designing new farming systems. It was found that using crop growth simulation modelling in a PA context is potentially very useful. Modelling high-resolution spatial and temporal variability with current simulation models poses a number of immediate research issues. This research focused on three whole farms located in Australia that grow predominantly grains without irrigation. These study sites represent three important grain growing regions within Australia. These are northern NSW, north-east Victoria and South Australia. Note-worthy environmental and climatic differences between these regions such as rainfall timing, soil type and topographic features were outlined in Chapter 2. When considering adoption of SSCM, it is essential to understand the impact of temporal variation on the potential value of managing spatial variation. Quantifying spatiotemporal variation of crop yield serves this purpose; however, this is a conceptually and practically challenging undertaking. A small number of previous studies have found that the magnitude of temporal variation far exceeds that of spatial variation. Chapter 3 of this thesis dealt with existing and new approaches quantifying the relationship between spatial and temporal variability in crop yield. It was found that using pseudo cross variography to obtain spatial and temporal variation ‘equivalents’ is a promising approach to quantitatively comparing spatial and temporal variation. The results from this research indicate that more data in the temporal dimension is required to enable thorough analysis using this approach. This is particularly relevant when questioning the suitability of SSCM. Crop growth simulation modelling offers PA a number of benefits such as the ability to simulate a considerable volume of data in the temporal dimension. A dominant challenge recognised within the PA/modelling literature is the mismatch between the spatial resolution of point-based model output (and therefore input) and the spatial resolution of information demanded by PA. This culminates into questions about the conceptual model underpinning the simulation model and the practicality of using point-based models to simulate spatial variability. iii The ability of point-based models to simulate appropriate spatial and temporal variability of crop yield and the importance of soil available water capacity (AWC) for these simulations were investigated in Chapter 4. The results indicated that simulated spatial variation is low compared to some previously reported spatial variability of real yield data for some climate years. It was found that the structure of spatial yield variation was directly related to the structure of the AWC and interactions between AWC and climate. It is apparent that varying AWC spatially is a reasonable starting point for modelling spatial variation of crop yield. A trade-off between capturing adequate spatio-temporal variation of crop yield and the inclusion of realistically obtainable model inputs is identified. A number of practical solutions to model parameterisation for PA purposes are identified in the literature. A popular approach is to minimise the number of simulations required. Another approach that enables modelling at every desired point across a study area involves taking advantage of high-resolution yield information from a number of years to estimate site-specific soil properties with the inverse use of a crop growth simulation model. Inverse meta-modelling was undertaken in Chapter 5 to estimate AWC on 10- metre grids across each of the study farms. This proved to be an efficient approach to obtaining high-resolution AWC information at the spatial extent of whole farms. The AWC estimates proved useful for yield prediction using simple linear regression as opposed to application within a complex crop growth simulation model. The ability of point-based models to simulate spatial variation was re-visited in Chapter 6 with respect to the exclusion of lateral water movement. The addition of a topographic component into the simple point-based yield prediction models substantially improved yield predictions. The value of these additions was interpreted using coefficients of determination and comparing variograms for each of the yield prediction components. A result consistent with the preceding chapter is the importance of further validating the yield prediction models with further yield data when it becomes available. Finally, some whole-farm management scenarios using SSCM were synthesised in Chapter 7. A framework that enables evaluation of the long-term (50 years) farm outcomes soil carbon sequestration, nitrogen leaching and crop yield was established. The suitability of SSCM across whole-farms over the long term was investigated and it was found that the suitability of SSCM is confined to certain fields. This analysis also enabled identification of parts of the farms that are the least financially and environmentally viable. SSCM in conjunction with other PA management strategies is identified as a promising approach to long-term and whole-farm integrated management.
APA, Harvard, Vancouver, ISO, and other styles
3

Artus, Sally. "VEGIGRO: a crop growth teaching model." Thesis, University of Nottingham, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.484201.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Song, Yu. "Modelling and analysis of plant image data for crop growth monitoring in horticulture." Thesis, University of Warwick, 2008. http://wrap.warwick.ac.uk/2032/.

Full text
Abstract:
Plants can be characterised by a range of attributes, and measuring these attributes accurately and reliably is a major challenge for the horticulture industry. The measurement of those plant characteristics that are most relevant to a grower has previously been tackled almost exclusively by a combination of manual measurement and visual inspection. The purpose of this work is to propose an automated image analysis approach in order to provide an objective measure of plant attributes to remove subjective factors from assessment and to reduce labour requirements in the glasshouse. This thesis describes a stereopsis approach for estimating plant height, since height information cannot be easily determined from a single image. The stereopsis algorithm proposed in this thesis is efficient in terms of the running time, and is more accurate when compared with other algorithms. The estimated geometry, together with colour information from the image, are then used to build a statistical plant surface model, which represents all the information from the visible spectrum. A self-organising map approach can be adopted to model plant surface attributes, but the model can be improved by using a probabilistic model such as a mixture model formulated in a Bayesian framework. Details of both methods are discussed in this thesis. A Kalman filter is developed to track the plant model over time, extending the model to the time dimension, which enables smoothing of the noisy measurements to produce a development trend for a crop. The outcome of this work could lead to a number of potentially important applications in horticulture.
APA, Harvard, Vancouver, ISO, and other styles
5

Ghaffari, Abdolali. "Application of geographical information systems (GIS) and crop simulation modelling in sustainable agriculture." Thesis, Imperial College London, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.312108.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Browne, David John. "Modelling columnar and equiaxed growth." Thesis, University of Oxford, 2002. http://ora.ox.ac.uk/objects/uuid:3d8ae26b-e0b4-4d54-801d-4951705d53aa.

Full text
Abstract:
A novel computer model of the evolution of columnar and equiaxed microstructure during alloy solidification has been developed. A control volume finite difference model of conduction heat transfer is applied to a two-dimensional domain bounded by a relatively cold mould. The initial condition is that of superheated liquid, and nucleation occurs either at the mould wall, leading to columnar dendritic growth, or within the bulk liquid, leading to the growth of equiaxed dendrites. The columnar front or the equiaxed grain boundaries are represented by computationally sharp interfaces, which separate liquid from partially solid alloy. Interpolation between discrete computational markers is employed to describe these interfaces, and a front-tracking technique is used to predict the evolution of the grain structure, via movement of the markers, across the fixed grid. The front velocity is determined via considerations of the kinetics of dendrite growth. The heat equation is fully coupled to the front-tracking algorithm by means of source terms which represent the evolution of latent heat due to the dendritic growth (advancing tips and thickening mushy zone). The model, applied to binary Al-Cu alloys, is computationally efficient. It predicts the variation of the extent of liquid undercooling ahead of the growing columnar front, and new metrics have been established to determine the likelihood of the formation of an equiaxed zone here. The employment of these metrics to establish the influence of heat extraction rate and alloy composition agrees with reports from the literature. The model does not distinguish between individual grains of the columnar zone, but it is shown that this is not an important limitation for most metal casting applications. Direct simulation of the nucleation and growth of multiple equiaxed crystals has been carried out, in which the nucleation and growth of individual grams can be observed via animation, and the influence of melt superheat and heat extraction rate on equiaxed solidification has been determined.
APA, Harvard, Vancouver, ISO, and other styles
7

Gillett, A. G. "Modelling the response of winter wheat to different environments : a parsimonious approach." Thesis, University of Nottingham, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.339658.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Mokoko-Mokeba, Michael Christian. "Computer simulation : modelling the dynamics of agrochemical sprays above and within a crop canopy." Thesis, University of Portsmouth, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.310384.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Vianna, Murilo dos Santos. "Functional, structural and agrohydrological sugarcane crop modelling: towards a simulation platform for Brazilian farming systems." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/11/11152/tde-01082018-150704/.

Full text
Abstract:
Sugarcane crop is the main source of sugar and the second largest source of biofuel in the world. Since the 1980s, Brazil has been the largest sugarcane producing nation, producing half of the global amount. Ethanol and biomass from sugarcane account for more than 15% of the country´s energy source. Nevertheless, commercial Brazilian sugarcane yield has plateaued at 75 t ha-1, and to meet the increasing demand for sugar and ethanol, the crop has strongly expanded towards central-western regions, where irrigation is mandatory to offset water stress risks. To support decision making and scientific guidance towards where and how the crop should expand and/or to increase yields, a heuristic view of the crop system is needed, which can mathematically be translated into a crop model. In turn, the effects of crop management, land use change, climate variability and agro-economic change factors on crop production and associated quantities can and have been assessed by using crop process-based models (PBM). In contrast to other crops, however, sugarcane has only two PBMs available for end users (DSSAT-CANEGRO and APSIM-Sugar), and further modifications of these models are required to better assess and support sustainable sugarcane production in Brazil. Therefore, this study aimed to develop, calibrate and evaluate different crop modelling approaches for Brazilian sugarcane farming systems, water management strategies, climate change impacts and canopy structures to support improved decisions for private and public stakeholders in the sugarcane sector, provide scientific guidance and establish a Brazilian platform of crop simulations. A new version of the sugarcane process-based model (SAMUCA) was developed to operate at phytomer level, focusing on soil mulch effects on crop growth and development, tillering process under competition for light and sucrose accumulation based on source-sink relations. The model was embedded into a modular platform dedicated to simulating the soil-plant-atmosphere and the management of the sugarcane farm system. The previous version of SAMUCA was also re-structured and coupled to the SWAP (Soil, Water, Atmosphere and Plant) agrohydrological model platform, focusing on soil water relations to crop growth. Moreover, a Functional-Structural Plant Model (FSPM) for sugarcane was developed by integrating the main crop components at the organ level (phytomer), based on a relative source-sink approach and a robust light model embedded into a three-dimensional modelling platform (GroIMP). All approaches were evaluated, and the performance under experimental conditions for different Brazilian conditions was determined. The performance of the new version of SAMUCA in a long-term experiment and under different Brazilian conditions was satisfactory, with agreement indices close to those of other widely used sugarcane crop models (CANEGRO and APSIM-Sugar). In addition, the modulated crop simulation platform can be used to host more crop models and integrate new features of Brazilian farming systems. The coupling of the SWAP-SAMUCA model was accomplished, and although non-expressive improvements in model performance regarding crop yield were noticed (with an overall 6% lower RMSE), the ability of SWAP-SAMUCA to simulate soil water content was higher than that of the original \"tipping bucket\" approach (32% lower RMSE). The Functional-Structural Plant Model for sugarcane was able to satisfactorily simulate canopy development, tillering and sucrose accumulation at the organ level and its integration at the whole-plant level. Besides its ability to simulate competition for light, helping to understand intra-specific competition among tillers, the sugarcane FSPM framework can be used to support sucrose accumulation and translocation mechanism studies as well as intercropping studies for sugarcane, which has already successfully been done for other crops.
A cultura da cana-de-açúcar é a principal fonte de açúcar e a segunda maior fonte de biocombustíveis do mundo. O Brasil é o maior produtor mundial desde a década de 80 e atualmente representa metade da produção mundial, enquanto que ao mesmo tempo o etanol e a biomassa correspondem a mais de 15% da fonte de energia do país. Contudo, a produtividade comercial da cana-de-açúcar brasileira atingiu um limiar de cerca de 75 t ha-1 e para atender à crescente demanda de açúcar e etanol, a cultura expandiu-se fortemente para a região centro-oeste, onde a irrigação é obrigatória para manter os níveis de produção e diminuir riscos de quebra de safra. Para dar suporte a tomada de decisão e avanço científico sobre onde e como a cultura deve se expandir e/ou aumentar a produtividade, é necessária uma visão heurística do sistema agrícola brasileiro que pode ser traduzida matematicamente para um modelo de cultura. Desta forma, os efeitos do manejo e tipo de solo, variabilidade climática e fatores econômicos na produtividade de culturas agrícolas podem ser avaliados quantitativamente por meio de modelos de culturas baseados em processos (MBP). No entanto, em contraste a outras culturas, a cana-de-açúcar possui apenas dois MBPs disponíveis para usuários finais (DSSAT-CANEGRO e APSIM-Sugar) que requerem calibração e parametrização para melhor representar o sistema agrícola de cana-de-açúcar do Brasil. Portanto, este estudo teve como objetivo desenvolver, calibrar e avaliar diferentes abordagens de modelagem de culturas voltadas a produção de cana-de-açúcar no Brasil, para servir como ferramenta de tomada de decisão para o setor público e privado, auxilio no manejo da água e avaliação dos impactos nas mudanças climáticas. Portanto, uma nova versão do modelo baseado em processo de cana-de-açúcar (SAMUCA) foi desenvolvida para operar a nível de fitômeros, incluindo os efeitos no crescimento e desenvolvimento da cana com base na cobertura da palha no solo, competição por luz no processo de perfilhamento e acúmulo de sacarose com base nas relações fonte-dreno. O modelo foi incorporado em uma plataforma modular dedicada a simular o sistema solo-planta-atmosfera e manejo do sistema agrícola. Além disso, a versão anterior do SAMUCA também foi reestruturada e acoplada à plataforma agro-hidrológica SWAP (\"Soil, Water, Atmosphere and Plant\") com objetivo de aprimorar as simulações de balanço hídrico no solo e efeito no crescimento da cana-de-açúcar. Por fim, um Modelo Funcional-Estrutural de Plantas (MFEP) para a cana-de-açúcar foi desenvolvido integrando os principais componentes da cultura a nível de órgãos (fitômeros) com base em uma abordagem de fonte-dreno e um modelo robusto de radiação que foram introduzidos em uma plataforma de modelagem tridimensional (GroIMP). As três abordagens foram avaliadas e seu desempenho foi determinado com base em condições experimentais para diferentes regiões brasileiras. O desempenho da nova versão do modelo SAMUCA em experimento de longo prazo e em diferentes condições brasileiras foi satisfatório e os índices de concordância foram próximos de outros modelos de cana-de-açúcar amplamente utilizados (CANEGRO e APSIM-Sugar). Além disso, a plataforma de simulação de culturas modulada pode ser usada para hospedar mais modelos de culturas e integrar novas características do sistema de cultivo brasileiro. O acoplamento do modelo SWAP-SAMUCA foi realizado e apesar não apresentar melhorias expressivas no desempenho do modelo em simular os componentes da cultura (com erro médio quadrático [RMSE] 6% menor), a habilidade do modelo SWAP-SAMUCA em simular o teor de água no solo mostrou-se consideravelmente superior em comparação ao modelo original (RMSE 32% menor). O MFEP para cana-de-açúcar foi capaz de simular o desenvolvimento do dossel, o processo de perfilhamento e o acúmulo de sacarose ao nível de órgãos e planta de forma satisfatória. Além de sua capacidade em simular com precisão a interceptação da radiação por cada estrutura do dossel, podendo auxiliar na compreensão do processo de competição intraespecífica entre perfilhos, a estrutura do MFEP da cana-de-açúcar também pode ser usada no apoio à pesquisa focando os mecanismos de acúmulo de sacarose e translocação de açúcares bem como em estudos de consórcio em cana-de-açúcar, como têm sido realizado com sucesso para outras culturas nos últimos anos.
APA, Harvard, Vancouver, ISO, and other styles
10

Chew, Yin Hoon. "Multi-scale whole-plant model of Arabidopsis growth to flowering." Thesis, University of Edinburgh, 2013. http://hdl.handle.net/1842/8008.

Full text
Abstract:
In this study, theoretical and experimental approaches were combined, using Arabidopsis as the studied species. The multi-scale model incorporates the following, existing sub-models: a phenology model that can predict the flowering time of plants grown in the field, a gene circuit of the circadian clock network that regulates flowering through the photoperiod pathway, a process-based model describing carbon assimilation and resource partitioning, and a functional-structural module that determines shoot structure for light interception and root growth. First, the phenology model was examined on its ability to predict the flowering time of field plantings at different sites and seasons in light of the specific meteorological conditions that pertained. This analysis suggested that the synchrony of temperature and light cycles is important in promoting floral initiation. New features were incorporated into the phenology model that improved its predictive accuracy across seasons. Using both lab and field data, this study has revealed an important seasonal effect of night temperatures on flowering time. Further model adjustments to describe phytochrome (phy) mutants supported the findings and implicated phyB in the temporal gating of temperature-induced flowering. The improved phenology model was next linked to the clock gene circuit model. Simulation of clock mutants with different free-running periods highlighted the complex mechanism associated with daylength responses for the induction of flowering. Finally, the carbon assimilation and functional-structural growth modules were integrated to form the multi-component, whole-plant model. The integrated model was successfully validated with experimental data from a few genotypes grown in the laboratory. In conclusion, the model has the ability to predict the flowering time, leaf biomass and ecosystem exchange of plants grown under conditions of varying light intensity, temperature, CO2 level and photoperiod, though extensions of some model components to incorporate more biological details would be relevant. Nevertheless, this meso-scale model creates obvious application routes from molecular and cellular biology to crop improvement and biosphere management. It could provide a framework for whole-organism modelling to help address global issues such as food security and the energy crisis.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "Crop growth simulation modelling"

1

Mohanty, M. Crop growth simulation modelling and climate change. Jodhpur: Scientific Publishers, 2015.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
2

van, Laar H. H., ed. Modelling potential crop growth processes: Textbook with exercises. Dordrecht: Kluwer, 1993.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

van, Laar H. H., ed. Modelling potential crop growth processes: Textbook with exercises. Dordrecht: Kluwer Academic Publishers, 1994.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
4

Kar, Gouranga. Spectral properties analysis and crop growth simulation modelling in rice. Bhubaneswar: Water Technology Centre for Eastern Region, Indian Council of Agricultural Research, 2007.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
5

International, Potato Modeling Conference (2nd 1994 Wageningen Netherlands). Potato ecology and modelling of crops under conditions limiting growth. Dordrecht: Kluwer Academic Publishers, 1995.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
6

International Potato Modeling Conference (2nd 1994 Wageningen, Netherlands). Potato ecology and modelling of crops under conditions limiting growth. Dordrecht: Springer-Science+Business Media, 1995.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
7

Goudriaan, J., and H. H. Van Laar. Modelling Potential Crop Growth Processes. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-0750-1.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Pannangpetch, K. Introduction to simulation of crop growth on microcomputer. Khon Kaen, Thailand: Dept. of Agronomy, Faculty of Agriculture, Khon Kaen University, 1992.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
9

Bouman, B. A. M. Remote sensing subroutines in crop growth simulation models. Wageningen: DLO Research Institute for Agrobiology and Soil Fertiity, 1996.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
10

Kaandorp, Jaap A. Modelling growth forms of biological objects using fractals. Meppel, the Netherlands: Printed by Krips Repro, 1992.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Book chapters on the topic "Crop growth simulation modelling"

1

Fischer, R. A. "The Role of Crop Simulation Models in Wheat Agronomy." In Wheat Growth and Modelling, 237–55. Boston, MA: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4899-3665-3_23.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Van Oijen, M. "Simulation models of potato late blight." In Potato Ecology And modelling of crops under conditions limiting growth, 237–50. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-0051-9_15.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Fishman, Svetlana, and B. Bar-Yosef. "Simulation of nitrogen uptake from soil and partitioning in potato plants: model description and sensitivity analysis." In Potato Ecology And modelling of crops under conditions limiting growth, 147–66. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-0051-9_10.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Bhatia, Avnish Kumar. "Crop Growth Simulation Modeling." In Simulation Foundations, Methods and Applications, 315–32. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05657-9_15.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Weir, A. H., W. Day, and T. G. Sastry. "Using a Whole Crop Model." In Wheat Growth and Modelling, 339–55. Boston, MA: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4899-3665-3_31.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Goudriaan, J., and H. H. Van Laar. "Development and growth." In Modelling Potential Crop Growth Processes, 69–94. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-0750-1_5.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Goudriaan, J., and H. H. Van Laar. "The main seasonal growth pattern." In Modelling Potential Crop Growth Processes, 7–28. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-0750-1_2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Biscoe, P. V., and V. B. A. Willington. "Crop Physiological Studies in Relation to Mathematical Models." In Wheat Growth and Modelling, 257–69. Boston, MA: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4899-3665-3_24.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Goudriaan, J., and H. H. Van Laar. "Introduction." In Modelling Potential Crop Growth Processes, 1–6. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-0750-1_1.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Goudriaan, J., and H. H. Van Laar. "Climatic factors." In Modelling Potential Crop Growth Processes, 29–49. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-0750-1_3.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Crop growth simulation modelling"

1

Todoroff, Pierre, Mickaël Mezino, Lionel Le Mézo, and Jean-Baptiste Laurent. "SHARP: An Online, Real-Time Sugarcane Harvest Prediction System based on Crop Growth Simulations and PLS Regression." In Modelling and Simulation. Calgary,AB,Canada: ACTAPRESS, 2013. http://dx.doi.org/10.2316/p.2013.802-026.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Gaetan, Louarn, Frak Ela, Combes Didier, and Escobar-Gutierrez Abraham. "Modelling variations in individual plant productivity within a stand: Comparison of top-down and bottom-up approaches in an alfalfa crop." In 2012 IEEE 4th International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA). IEEE, 2012. http://dx.doi.org/10.1109/pma.2012.6524843.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Jullien, Alexandra, Amélie Mathieu, Jean-Michel Allirand, Amelie Pinet, Philippe de Reffye, Bertrand Ney, and Paul-Henry Cournède. "Modelling of Branch and Flower Expansion in GreenLab Model to Account for the Whole Crop Cycle of Winter Oilseed Rape (Brassica napus L.)." In 2009 Third International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA). IEEE, 2009. http://dx.doi.org/10.1109/pma.2009.74.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

"A satellite-based crop-factor hydrological model for broad-scale estimates of irrigated area, crop-water-requirement and crop phenology." In 22nd International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2017. http://dx.doi.org/10.36334/modsim.2017.l4.weeks.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Nisperos, Saturnina Fabian, and Frederic D. McKenzie. "Assessing Crop Rotation Sustainability Using Analytical Hierarchy Process." In 32nd Conference on Modelling and Simulation. ECMS, 2018. http://dx.doi.org/10.7148/2018-0336.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

"Temperature increase and cotton crop phenology." In 20th International Congress on Modelling and Simulation (MODSIM2013). Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2013. http://dx.doi.org/10.36334/modsim.2013.b2.luo.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Hawick, K. A. "Spectral Analysis of Growth in Spatial Lotka-Volterra Models." In Modelling and Simulation. Calgary,AB,Canada: ACTAPRESS, 2010. http://dx.doi.org/10.2316/p.2010.685-030.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Radulescu, Marius, and Constanta Zoie Radulescu. "Simulation and Optimization for Crop Planning Under Risk." In 2013 8th EUROSIM Congress on Modelling and Simulation (EUROSIM). IEEE, 2013. http://dx.doi.org/10.1109/eurosim.2013.117.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Ashimov, Abdykappar A., Bahyt T. Sultanov, Zheksenbek M. Adilov, Yuriy V. Borovskiy, Dauren K. Suissinbayev, and Askar A. Ashimov. "Parametrical Regulation of Economic Growth based on the Jones Endogenous Model." In Modelling and Simulation. Calgary,AB,Canada: ACTAPRESS, 2011. http://dx.doi.org/10.2316/p.2011.735-038.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

"Towards measures of the eradicability of rain-splashed crop diseases." In 19th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2011. http://dx.doi.org/10.36334/modsim.2011.e16.bennett.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Crop growth simulation modelling"

1

Groenendijk, Piet, Hendrik Boogaard, Marius Heinen, J. G. Kroes, Iwan Supit, and Allard de Wit. Simulation nitrogen-limited crop growth with SWAP/WOFOST : process descriptions and user manual. Wageningen: Wageningen Environmental Research, 2016. http://dx.doi.org/10.18174/400458.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Dik, Pim, Fenny van Egmond, and Leandro Barbieri. Exploration of the simulation of crop growth and water holding capacity for regenerative agriculture : Soil Heroes Foundation - Hoeksche Waard case study. Wageningen: Wageningen Environmental Research, 2022. http://dx.doi.org/10.18174/582324.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

de Vries, Sander C. WFLOW_LINTUL: raster-based simulation of rice growth in the WFLOW/OpenStreams hydrological modelling platform : user manual and description of core model code. Wageningen: Wageningen Research (WR) business unit Agrosystems Research, 2018. http://dx.doi.org/10.18174/461276.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Lieth, J. Heiner, Michael Raviv, and David W. Burger. Effects of root zone temperature, oxygen concentration, and moisture content on actual vs. potential growth of greenhouse crops. United States Department of Agriculture, January 2006. http://dx.doi.org/10.32747/2006.7586547.bard.

Full text
Abstract:
Soilless crop production in protected cultivation requires optimization of many environmental and plant variables. Variables of the root zone (rhizosphere) have always been difficult to characterize but have been studied extensively. In soilless production the opportunity exists to optimize these variables in relation to crop production. The project objectives were to model the relationship between biomass production and the rhizosphere variables: temperature, dissolved oxygen concentration and water availability by characterizing potential growth and how this translates to actual growth. As part of this we sought to improve of our understanding of root growth and rhizosphere processes by generating data on the effect of rhizosphere water status, temperature and dissolved oxygen on root growth, modeling potential and actual growth and by developing and calibrating models for various physical and chemical properties in soilless production systems. In particular we sought to use calorimetry to identify potential growth of the plants in relation to these rhizosphere variables. While we did experimental work on various crops, our main model system for the mathematical modeling work was greenhouse cut-flower rose production in soil-less cultivation. In support of this, our objective was the development of a Rose crop model. Specific to this project we sought to create submodels for the rhizosphere processes, integrate these into the rose crop simulation model which we had begun developing prior to the start of this project. We also sought to verify and validate any such models and where feasible create tools that growers could be used for production management. We made significant progress with regard to the use of microcalorimetry. At both locations (Israel and US) we demonstrated that specific growth rate for root and flower stem biomass production were sensitive to dissolved oxygen. Our work also identified that it is possible to identify optimal potential growth scenarios and that for greenhouse-grown rose the optimal root zone temperature for potential growth is around 17 C (substantially lower than is common in commercial greenhouses) while flower production growth potential was indifferent to a range as wide as 17-26C in the root zone. We had several set-backs that highlighted to us the fact that work needs to be done to identify when microcalorimetric research relates to instantaneous plant responses to the environment and when it relates to plant acclimation. One outcome of this research has been our determination that irrigation technology in soilless production systems needs to explicitly include optimization of oxygen in the root zone. Simply structuring the root zone to be “well aerated” is not the most optimal approach, but rather a minimum level. Our future work will focus on implementing direct control over dissolved oxygen in the root zone of soilless production systems.
APA, Harvard, Vancouver, ISO, and other styles
5

Crowley, David E., Dror Minz, and Yitzhak Hadar. Shaping Plant Beneficial Rhizosphere Communities. United States Department of Agriculture, July 2013. http://dx.doi.org/10.32747/2013.7594387.bard.

Full text
Abstract:
PGPR bacteria include taxonomically diverse bacterial species that function for improving plant mineral nutrition, stress tolerance, and disease suppression. A number of PGPR are being developed and commercialized as soil and seed inoculants, but to date, their interactions with resident bacterial populations are still poorly understood, and-almost nothing is known about the effects of soil management practices on their population size and activities. To this end, the original objectives of this research project were: 1) To examine microbial community interactions with plant-growth-promoting rhizobacteria (PGPR) and their plant hosts. 2) To explore the factors that affect PGPR population size and activity on plant root surfaces. In our original proposal, we initially prqposed the use oflow-resolution methods mainly involving the use of PCR-DGGE and PLFA profiles of community structure. However, early in the project we recognized that the methods for studying soil microbial communities were undergoing an exponential leap forward to much more high resolution methods using high-throughput sequencing. The application of these methods for studies on rhizosphere ecology thus became a central theme in these research project. Other related research by the US team focused on identifying PGPR bacterial strains and examining their effective population si~es that are required to enhance plant growth and on developing a simulation model that examines the process of root colonization. As summarized in the following report, we characterized the rhizosphere microbiome of four host plant species to determine the impact of the host (host signature effect) on resident versus active communities. Results of our studies showed a distinct plant host specific signature among wheat, maize, tomato and cucumber, based on the following three parameters: (I) each plant promoted the activity of a unique suite of soil bacterial populations; (2) significant variations were observed in the number and the degree of dominance of active populations; and (3)the level of contribution of active (rRNA-based) populations to the resident (DNA-based) community profiles. In the rhizoplane of all four plants a significant reduction of diversity was observed, relative to the bulk soil. Moreover, an increase in DNA-RNA correspondence indicated higher representation of active bacterial populations in the residing rhizoplane community. This research demonstrates that the host plant determines the bacterial community composition in its immediate vicinity, especially with respect to the active populations. Based on the studies from the US team, we suggest that the effective population size PGPR should be maintained at approximately 105 cells per gram of rhizosphere soil in the zone of elongation to obtain plant growth promotion effects, but emphasize that it is critical to also consider differences in the activity based on DNA-RNA correspondence. The results ofthis research provide fundamental new insight into the composition ofthe bacterial communities associated with plant roots, and the factors that affect their abundance and activity on root surfaces. Virtually all PGPR are multifunctional and may be expected to have diverse levels of activity with respect to production of plant growth hormones (regulation of root growth and architecture), suppression of stress ethylene (increased tolerance to drought and salinity), production of siderophores and antibiotics (disease suppression), and solubilization of phosphorus. The application of transcriptome methods pioneered in our research will ultimately lead to better understanding of how management practices such as use of compost and soil inoculants can be used to improve plant yields, stress tolerance, and disease resistance. As we look to the future, the use of metagenomic techniques combined with quantitative methods including microarrays, and quantitative peR methods that target specific genes should allow us to better classify, monitor, and manage the plant rhizosphere to improve crop yields in agricultural ecosystems. In addition, expression of several genes in rhizospheres of both cucumber and whet roots were identified, including mostly housekeeping genes. Denitrification, chemotaxis and motility genes were preferentially expressed in wheat while in cucumber roots bacterial genes involved in catalase, a large set of polysaccharide degradation and assimilatory sulfate reduction genes were preferentially expressed.
APA, Harvard, Vancouver, ISO, and other styles
6

Shani, Uri, Lynn Dudley, Alon Ben-Gal, Menachem Moshelion, and Yajun Wu. Root Conductance, Root-soil Interface Water Potential, Water and Ion Channel Function, and Tissue Expression Profile as Affected by Environmental Conditions. United States Department of Agriculture, October 2007. http://dx.doi.org/10.32747/2007.7592119.bard.

Full text
Abstract:
Constraints on water resources and the environment necessitate more efficient use of water. The key to efficient management is an understanding of the physical and physiological processes occurring in the soil-root hydraulic continuum.While both soil and plant leaf water potentials are well understood, modeled and measured, the root-soil interface where actual uptake processes occur has not been sufficiently studied. The water potential at the root-soil interface (yᵣₒₒₜ), determined by environmental conditions and by soil and plant hydraulic properties, serves as a boundary value in soil and plant uptake equations. In this work, we propose to 1) refine and implement a method for measuring yᵣₒₒₜ; 2) measure yᵣₒₒₜ, water uptake and root hydraulic conductivity for wild type tomato and Arabidopsis under varied q, K⁺, Na⁺ and Cl⁻ levels in the root zone; 3) verify the role of MIPs and ion channels response to q, K⁺ and Na⁺ levels in Arabidopsis and tomato; 4) study the relationships between yᵣₒₒₜ and root hydraulic conductivity for various crops representing important botanical and agricultural species, under conditions of varying soil types, water contents and salinity; and 5) integrate the above to water uptake term(s) to be implemented in models. We have made significant progress toward establishing the efficacy of the emittensiometer and on the molecular biology studies. We have added an additional method for measuring ψᵣₒₒₜ. High-frequency water application through the water source while the plant emerges and becomes established encourages roots to develop towards and into the water source itself. The yᵣₒₒₜ and yₛₒᵢₗ values reflected wetting and drying processes in the rhizosphere and in the bulk soil. Thus, yᵣₒₒₜ can be manipulated by changing irrigation level and frequency. An important and surprising finding resulting from the current research is the obtained yᵣₒₒₜ value. The yᵣₒₒₜ measured using the three different methods: emittensiometer, micro-tensiometer and MRI imaging in both sunflower, tomato and corn plants fell in the same range and were higher by one to three orders of magnitude from the values of -600 to -15,000 cm suggested in the literature. We have added additional information on the regulation of aquaporins and transporters at the transcript and protein levels, particularly under stress. Our preliminary results show that overexpression of one aquaporin gene in tomato dramatically increases its transpiration level (unpublished results). Based on this information, we started screening mutants for other aquaporin genes. During the feasibility testing year, we identified homozygous mutants for eight aquaporin genes, including six mutants for five of the PIP2 genes. Including the homozygous mutants directly available at the ABRC seed stock center, we now have mutants for 11 of the 19 aquaporin genes of interest. Currently, we are screening mutants for other aquaporin genes and ion transporter genes. Understanding plant water uptake under stress is essential for the further advancement of molecular plant stress tolerance work as well as for efficient use of water in agriculture. Virtually all of Israel’s agriculture and about 40% of US agriculture is made possible by irrigation. Both countries face increasing risk of water shortages as urban requirements grow. Both countries will have to find methods of protecting the soil resource while conserving water resources—goals that appear to be in direct conflict. The climate-plant-soil-water system is nonlinear with many feedback mechanisms. Conceptual plant uptake and growth models and mechanism-based computer-simulation models will be valuable tools in developing irrigation regimes and methods that maximize the efficiency of agricultural water. This proposal will contribute to the development of these models by providing critical information on water extraction by the plant that will result in improved predictions of both water requirements and crop yields. Plant water use and plant response to environmental conditions cannot possibly be understood by using the tools and language of a single scientific discipline. This proposal links the disciplines of soil physics and soil physical chemistry with plant physiology and molecular biology in order to correctly treat and understand the soil-plant interface in terms of integrated comprehension. Results from the project will contribute to a mechanistic understanding of the SPAC and will inspire continued multidisciplinary research.
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Crop growth simulation modelling' for particular source types:
Journal articles Dissertations / Theses Books
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography