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Full-Text Articles in Physical Sciences and Mathematics

Climate Change And Mediterranean Seagrass Meadows: A Synopsis For Environmental Managers, G Pergent, H Bazairi, C N. Bianchi, C F. Boudouresque, M C. Buia, S Calvo, P Clabaut, M Harmelinvivien, M Angel Mateo, M Montefalcone, C Morri, S Orfanidis, C Pergentmartini, R Semroud, Oscar Serrano, T Thibaut, A Tomasello, M Verlaque Jan 2014

Climate Change And Mediterranean Seagrass Meadows: A Synopsis For Environmental Managers, G Pergent, H Bazairi, C N. Bianchi, C F. Boudouresque, M C. Buia, S Calvo, P Clabaut, M Harmelinvivien, M Angel Mateo, M Montefalcone, C Morri, S Orfanidis, C Pergentmartini, R Semroud, Oscar Serrano, T Thibaut, A Tomasello, M Verlaque

Research outputs 2014 to 2021

This synopsis focuses on the effects of climate change on Mediterranean seagrasses, and associated communities, and on the contribution of the main species, Posidonia oceanica, to the mitigation of climate change effects through sequestering carbon dioxide. Whilst the regression of seagrass meadows is well documented, generally linked to anthropogenic pressures, global warming could be a cause of new significant regression, notably linked to the introduction of exotic species, the rise of Sea-Surface Temperature (SST), and relative sea level. Seagrass communities could also be affected by climate change through the replacement of high structural complexity seagrass species by species of lower …


Soil Seed Banks Of Fringing Salt Lake Vegetation In Arid Western Australia - Density, Composition And Implications For Postmine Restoration Using Topsoil, Eddie J. Van Etten, Brett Neasham, Sarah Dalgleish Jan 2014

Soil Seed Banks Of Fringing Salt Lake Vegetation In Arid Western Australia - Density, Composition And Implications For Postmine Restoration Using Topsoil, Eddie J. Van Etten, Brett Neasham, Sarah Dalgleish

Research outputs 2014 to 2021

Although studies of seed banks in arid ecosystems are commonplace, they are lacking for the large arid zone of Western Australia. Across the six major plant communities fringing a large salt lake within this zone, topsoil (0-5 cm depth) was collected from 12 to 36 sites per community. Samples were dried, spread out on a bed of vermiculite in seedling trays and placed in a well-watered glasshouse to determine the readily germinable component of the soil seed bank. Subsamples of topsoil were treated with smoke water, hot water or flooding to help determine seed bank of species with dormancy mechanisms. …


Hierarchical Graphical Bayesian Models In Psychology, Guillermo Campitelli, Guillermo Macbeth Jan 2014

Hierarchical Graphical Bayesian Models In Psychology, Guillermo Campitelli, Guillermo Macbeth

Research outputs 2014 to 2021

The improvement of graphical methods in psychological research can promote their use and a better comprehension of their expressive power. The application of hierarchical Bayesian graphical models has recently become more frequent in psychological research. The aim of this contribution is to introduce suggestions for the improvement of hierarchical Bayesian graphical models in psychology. This novel set of suggestions stems from the description and comparison between two main approaches concerned with the use of plate notation and distribution pictograms. It is concluded that the combination of relevant aspects of both models might improve the use of powerful hierarchical Bayesian graphical …


Novel Image-Dependent Quality Assessment Measures, Asaad Hashim, Zahir Hussain Jan 2014

Novel Image-Dependent Quality Assessment Measures, Asaad Hashim, Zahir Hussain

Research outputs 2014 to 2021

The image is a 2D signal whose pixels are highly correlated in a 2D manner. Hence, using pixel by pixel error what we called previously Mean-Square Error, (MSE) is not an efficient way to compare two similar images (e.g., an original image and a compressed version of it). Due to this correlation, image comparison needs a correlative quality measure. It is clear that correlation between two signals gives an idea about the relation between samples of the two signals. Generally speaking, correlation is a measure of similarity between the two signals. An important step in image similarity was introduced by …


Windows Surface Rt Tablet Forensics, Asif Iqbal, Hanan Al Obaidli, Andrew Marrington, Andy Jones Jan 2014

Windows Surface Rt Tablet Forensics, Asif Iqbal, Hanan Al Obaidli, Andrew Marrington, Andy Jones

Research outputs 2014 to 2021

Small scale digital device forensics is particularly critical as a result of the mobility of these devices, leading to closer proximity to crimes as they occur when compared to computers. The Windows Surface tablet is one such device, combining tablet mobility with familiar Microsoft Windows productivity tools. This research considers the acquisition and forensic analysis of the Windows Surface RT tablet. We discuss the artifacts of both the Windows RT operating system and third-party applications. The contribution of this research is to provide a road map for the digital forensic examination of Windows Surface RT tablets.


Setting Goals And Choosing Appropriate Reference Sites For Restoring Mine Pit Lakes As Aquatic Ecosystems: Case Study From South West Australia, Eddie J. Van Etten, Clint D. Mccullough, Mark A. Lund Jan 2014

Setting Goals And Choosing Appropriate Reference Sites For Restoring Mine Pit Lakes As Aquatic Ecosystems: Case Study From South West Australia, Eddie J. Van Etten, Clint D. Mccullough, Mark A. Lund

Research outputs 2014 to 2021

Pit lakes may form when open cut mining leaves a pit void behind that fills with ground and surface water. Often replacing terrestrial ecosystems that existed prior to mining, the pit lake may offer an alternative ecosystem with aquatic biodiversity values that can be realised through planned restoration. Restoration theory and mine closure regulatory requirements guides us toward restoring disturbed systems towards landscapes that are of regional value and relevance. However, how do we identify a restoration target for a novel aquatic habitat that did not exist prior to the new post-mining landscape? This paper presents a process of first …


Frequency Estimation Of Single-Tone Sinusoids Under Additive And Phase Noise, Asmaa Nazar Almoosawy, Zahir Hussain, Fadel A. Murad Jan 2014

Frequency Estimation Of Single-Tone Sinusoids Under Additive And Phase Noise, Asmaa Nazar Almoosawy, Zahir Hussain, Fadel A. Murad

Research outputs 2014 to 2021

We investigate the performance of main frequency estimation methods for a single-component complex sinusoid under complex additive white Gaussian noise (AWGN) as well as phase noise (PN). Two methods are under test: Maximum Likelihood (ML) method using Fast Fourier Transform (FFT), and the autocorrelation method (Corr). Simulation results showed that FFT-method has superior performance as compared to the Corr-method in the presence of additive white Gaussian noise (affecting the amplitude) and phase noise, with almost 20dB difference.


Education For Sustainability Through A Photography Competition, Rowena Scott Jan 2014

Education For Sustainability Through A Photography Competition, Rowena Scott

Research outputs 2014 to 2021

This article describes the development and history of a sustainability photography competition. From its simple beginnings as an environmental officer's idea, an environmental sustainability photography competition began in just one university. Now hosted by Australasian Campuses Towards Sustainability (ACTS), finalist entries are viewed on a public website gaining international attention. A purpose of this article is to demonstrate the diversity of views of sustainability by displaying the winning entries from 2013 and 2012. It is anticipated that readers may replicate these ideas in creative arts and across disciplines throughout primary, secondary and other higher education institutions, community groups and diverse …


Contrasting Biogeochemical Cycles Of Cobalt In The Surface Western Atlantic Ocean, Gabrial Dulaquais, Marie Boye, Rob Middag, Stephanis Owens, Viene Puigcorbe, Ken Buesseler, Pere Masque´, Hein J. De Baar, Xavier Carton Jan 2014

Contrasting Biogeochemical Cycles Of Cobalt In The Surface Western Atlantic Ocean, Gabrial Dulaquais, Marie Boye, Rob Middag, Stephanis Owens, Viene Puigcorbe, Ken Buesseler, Pere Masque´, Hein J. De Baar, Xavier Carton

Research outputs 2014 to 2021

Dissolved cobalt (DCo; 0.2μm; 10%) to the DCo stock of the mixed layer in the equatorial and north subtropical domains. Biotic and abiotic processes as well as the physical terms involved in the biogeochemical cycle of Co were defined and estimated. This allowed establishing the first global budget of DCo for the upper 100m in the western Atlantic. The biological DCo uptake flux was the dominant sink along the section, as reflected by the overall nutrient-type behavior of DCo. The regeneration varied widely within the different biogeochemical domains, accounting for 10% of the DCo-uptake rate in the subarctic gyre and …


An Information-Theoretic Image Quality Measure: Comparison With Statistical Similarity, Asmhan F. Hassan, Dong Cailin, Zahir M. Hussain Jan 2014

An Information-Theoretic Image Quality Measure: Comparison With Statistical Similarity, Asmhan F. Hassan, Dong Cailin, Zahir M. Hussain

Research outputs 2014 to 2021

We present an information-theoretic approach for structural similarity for assessing gray scale image quality. The structural similarity measure SSIM, proposed in 2004, has been successflly used and verfied. SSIM is based on statistical similarity between the two images. However, SSIM can produce confusing results in some cases where it may give a non-trivial amount of similarity for two different images. Also, SSIM cannot perform well (in detecting similarity or dissimilarity) at low peak signal to noise ratio (PSNR). In this study, we present a novel image similarity measure, HSSIM, by using information - theoretic technique based on joint histogram. The …


A Critical Review Of Habitat Use By Feral Cats And Key Directions For Future Research And Management, Tim S. Doherty, Andrew J. Bengsen, Robert A. Davis Jan 2014

A Critical Review Of Habitat Use By Feral Cats And Key Directions For Future Research And Management, Tim S. Doherty, Andrew J. Bengsen, Robert A. Davis

Research outputs 2014 to 2021

Feral cats (Felis catus) have a wide global distribution and cause significant damage to native fauna. Reducing their impacts requires an understanding of how they use habitat and which parts of the landscape should be the focus of management. We reviewed 27 experimental and observational studies conducted around the world over the last 35 years that aimed to examine habitat use by feral and unowned cats. Our aims were to: (1) summarise the current body of literature on habitat use by feral and unowned cats in the context of applicable ecological theory (i.e. habitat selection, foraging theory); (2) develop testable …


Modelling And Analysis On Noisy Financial Time Series, Jinsong Leng Jan 2014

Modelling And Analysis On Noisy Financial Time Series, Jinsong Leng

Research outputs 2014 to 2021

Building the prediction model(s) from the historical time series has attracted many researchers in last few decades. For example, the traders of hedge funds and experts in agriculture are demanding the precise models to make the prediction of the possible trends and cycles. Even though many statistical or machine learning (ML) models have been proposed, however, there are no universal solutions available to resolve such particular prob-lem. In this paper, the powerful forward-backward non-linear filter and wavelet-based denoising method are introduced to remove the high level of noise embedded in financial time series. With the filtered time series, the statistical …


What Do Elevated Background Contaminant Concentrations Mean For Amd Risk Assessment And Management In Western Australia?, Clinton D. Mccullough, J. J Pearce Jan 2014

What Do Elevated Background Contaminant Concentrations Mean For Amd Risk Assessment And Management In Western Australia?, Clinton D. Mccullough, J. J Pearce

Research outputs 2014 to 2021

Water quality contaminants include a range of naturally occurring chemicals that can cause degradation of aquatic ecosystem water values when concentration ranges exceed biological tolerances. Both acid and metalliferous drainage (AMD) and acid sulfate soil (ASS) can increase contaminant concentrations through reduced pH and increased solute concentrations especially of toxic metals and metalloids. Water quality guideline criteria are typically used to maintain existing end use value objectives when managing AMD/ASS-affected waters. However, surface and ground waters of catchments comprising mining resources often show elevated solute concentrations in baseline conditions due to their unique geologies. From an AMD and ASS risk …


Mobile Applications For Indian Agriculture Sector: A Case Study, Pratik Shah, Niketa Gandhi, Leisa Armstrong Jan 2014

Mobile Applications For Indian Agriculture Sector: A Case Study, Pratik Shah, Niketa Gandhi, Leisa Armstrong

Research outputs 2014 to 2021

Government, private agencies and the general public are often interested in the decisions made by the Indian farmers as they have large influences beyond the farm boundary. Over many years, the process of adoption of new technologies and policies in the Indian agricultural sector has received considerable academic attention highlighting the role of many social, financial and other influences on their decision making. The Indian government and other development agencies promote income generating projects as a way of encouraging growth through increased agricultural production and the protection of the natural resource base. The impact of new technology to economic growth …


Geospatial Data Pre-Processing On Watershed Datasets: A Gis Approach, Sreedhar Nallan, Leisa Armstrong, Barry Croke, Amiya K. Tripathy Jan 2014

Geospatial Data Pre-Processing On Watershed Datasets: A Gis Approach, Sreedhar Nallan, Leisa Armstrong, Barry Croke, Amiya K. Tripathy

Research outputs 2014 to 2021

Spatial data mining helps to identify interesting patterns from the spatial data sets. However, geo spatial data requires substantial data pre-processing before data can be interrogated further using data mining techniques. Multi-dimensional spatial data has been used to explain the spatial analysis and SOLAP for pre-processing data. This paper examines some of the methods for pre-processing of the data using Arc GIS 10.2 and Spatial Analyst with a case study dataset of a watershed.


A Survey Of Image Processing Techniques For Agriculture, Lalit Saxena, Leisa Armstrong Jan 2014

A Survey Of Image Processing Techniques For Agriculture, Lalit Saxena, Leisa Armstrong

Research outputs 2014 to 2021

Computer technologies have been shown to improve agricultural productivity in a number of ways. One technique which is emerging as a useful tool is image processing. This paper presents a short survey on using image processing techniques to assist researchers and farmers to improve agricultural practices. Image processing has been used to assist with precision agriculture practices, weed and herbicide technologies, monitoring plant growth and plant nutrition management. This paper highlights the future potential for image processing for different agricultural industry contexts.


Genetic Algorithm With Logistic Regression For Prediction Of Progression To Alzheimer's Disease, Piers Johnson, Luke Vandewater, William Wilson, Paul Maruff, Greg Savage, Petra Graham, Lance S. Macaulay, Kathryn A. Ellis, Cassandra Szoeke, Ralph N. Martins, Christopher Rowe, Colin L. Masters, David Ames, Ping Zhang Jan 2014

Genetic Algorithm With Logistic Regression For Prediction Of Progression To Alzheimer's Disease, Piers Johnson, Luke Vandewater, William Wilson, Paul Maruff, Greg Savage, Petra Graham, Lance S. Macaulay, Kathryn A. Ellis, Cassandra Szoeke, Ralph N. Martins, Christopher Rowe, Colin L. Masters, David Ames, Ping Zhang

Research outputs 2014 to 2021

Assessment of risk and early diagnosis of Alzheimer's disease (AD) is a key to its prevention or slowing the progression of the disease. Previous research on risk factors for AD typically utilizes statistical comparison tests or stepwise selection with regression models. Outcomes of these methods tend to emphasize single risk factors rather than a combination of risk factors. However, a combination of factors, rather than any one alone, is likely to affect disease development. Genetic algorithms (GA) can be useful and efficient for searching a combination of variables for the best achievement (eg. accuracy of diagnosis), especially when the search …


Small To Medium Enterprise Cyber Security Awareness: An Initial Survey Of Western Australian Business, Craig Valli, Ian C. Martinus, Michael N. Johnstone Jan 2014

Small To Medium Enterprise Cyber Security Awareness: An Initial Survey Of Western Australian Business, Craig Valli, Ian C. Martinus, Michael N. Johnstone

Research outputs 2014 to 2021

Small to Medium Enterprises (SMEs) represent a large proportion of a nation’s business activity. There are studies and reports reporting the threat to business from cyber security issues resulting in computer hacking that achieve system penetration and information compromise. Very few are focussed on SMEs. Even fewer are focussed on directly surveying the actual SMEs themselves and attempts to improve SME outcomes with respect to cyber security. This paper represents research in progress that outlines an approach being undertaken in Western Australia with SMEs in the northwest metropolitan region of Perth, specifically within the large local government catchments of Joondalup …


Tego - A Framework For Adversarial Planning, Daniel Ashlock, Philip Hingston Jan 2014

Tego - A Framework For Adversarial Planning, Daniel Ashlock, Philip Hingston

Research outputs 2014 to 2021

This study establishes a framework called ∗-Tego for a situation in which two agents are each given a set of players for a competitive game. Each agent places their players in an order. Players on each side at the same position in the order play one another, with the agent's score being the sum of their player's scores. The planning agents are permitted to simultaneous reorder their players in each of several stages. The reordering is termed competitive replanning. The resulting framework is scalable by changing the number of players and the complexity of the replanning process. The framework is …


Cloud Security Meets Telemedicine, Michael N. Johnstone Jan 2014

Cloud Security Meets Telemedicine, Michael N. Johnstone

Research outputs 2014 to 2021

Medical systems are potentially one domain where security is seen as an impediment to patient care and not as an essential part of a system. This is an issue for safety-critical systems where reliability and trust are essential for successful operation. Cloud computing services offer a seamless means to allow medical data to be transferred from patient to medical specialist, whilst maintaining security requirements. This paper uses a case study to investigate the use of cloud computing in a mobile application to assist with diagnostics for patients with Parkinson Disease. It was found that the developers of the app ignored …


Local And Semi-Global Feature-Correlative Techniques For Face Recognition, Asaad Noori Hashim, Zahir Hussain Jan 2014

Local And Semi-Global Feature-Correlative Techniques For Face Recognition, Asaad Noori Hashim, Zahir Hussain

Research outputs 2014 to 2021

Face recognition is an interesting field of computer vision with many commercial and scientific applications. It is considered as a very hot topic and challenging problem at the moment. Many methods and techniques have been proposed and applied for this purpose, such as neural networks, PCA, Gabor filtering, etc. Each approach has its weaknesses as well as its points of strength. This paper introduces a highly efficient method for the recognition of human faces in digital images using a new feature extraction method that combines the global and local information in different views (poses) of facial images. Feature extraction techniques …


An Information-Theoretic Measure For Face Recognition: Comparison With Structural Similarity, Asmhan Flieh Hassan, Zahir Hussain, Dong Cai-Lin Jan 2014

An Information-Theoretic Measure For Face Recognition: Comparison With Structural Similarity, Asmhan Flieh Hassan, Zahir Hussain, Dong Cai-Lin

Research outputs 2014 to 2021

Automatic recognition of people faces is a challenging problem that has received significant attention from signal processing researchers in recent years. This is due to its several applications in different fields, including security and forensic analysis. Despite this attention, face recognition is still one among the most challenging problems. Up to this moment, there is no technique that provides a reliable solution to all situations. In this paper a novel technique for face recognition is presented. This technique, which is called ISSIM, is derived from our recently published information - theoretic similarity measure HSSIM, which was based on joint histogram. …


A Genetic Algorithm-Based Feature Selection, Oluleye H. Babatunde, Leisa Armstrong, Jinsong Leng, Dean Diepeveen Jan 2014

A Genetic Algorithm-Based Feature Selection, Oluleye H. Babatunde, Leisa Armstrong, Jinsong Leng, Dean Diepeveen

Research outputs 2014 to 2021

This article details the exploration and application of Genetic Algorithm (GA) for feature selection. Particularly a binary GA was used for dimensionality reduction to enhance the performance of the concerned classifiers. In this work, hundred (100) features were extracted from set of images found in the Flavia dataset (a publicly available dataset). The extracted features are Zernike Moments (ZM), Fourier Descriptors (FD), Lengendre Moments (LM), Hu 7 Moments (Hu7M), Texture Properties (TP) and Geometrical Properties (GP). The main contributions of this article are (1) detailed documentation of the GA Toolbox in MATLAB and (2) the development of a GA-based feature …


Editorial - The Changing Face Of Ehealth Security, Patricia Williams, Lizzie Coles-Kemp Jan 2014

Editorial - The Changing Face Of Ehealth Security, Patricia Williams, Lizzie Coles-Kemp

Research outputs 2014 to 2021

No abstract provided.


Why Penetration Testing Is A Limited Use Choice For Sound Cyber Security Practice, Craig Valli, Andrew J. Woodward, Peter Hannay, Michael N. Johnstone Jan 2014

Why Penetration Testing Is A Limited Use Choice For Sound Cyber Security Practice, Craig Valli, Andrew J. Woodward, Peter Hannay, Michael N. Johnstone

Research outputs 2014 to 2021

Penetration testing of networks is a process that is overused when demonstrating or evaluating the cyber security posture of an organisation. Most penetration testing is not aligned with the actual intent of the testing, but rather is driven by a management directive of wanting to be seen to be addressing the issue of cyber security. The use of penetration testing is commonly a reaction to an adverse audit outcome or as a result of being penetrated in the first place. Penetration testing used in this fashion delivers little or no value to the organisation being tested for a number of …


Application Of Cellular Neural Networks And Naive Bayes Classifier In Agriculture, Oluleye H. Babatunde, Leisa Armstrong, Jinsong Leng, Dean Diepeveen Jan 2014

Application Of Cellular Neural Networks And Naive Bayes Classifier In Agriculture, Oluleye H. Babatunde, Leisa Armstrong, Jinsong Leng, Dean Diepeveen

Research outputs 2014 to 2021

This article describes the use of Cellular Neural Networks (a class of Ordinary Differential Equation (ODE)), Fourier Descriptors (FD) and NaiveBayes Classifier (NBC) for automatic identification of images of plant leaves. The novelty of this article is seen in the use of CNN for image segmentation and a combination FDs with NBC. The main advantage of the segmentation method is the computation speed compared with other edge operators such as canny, sobel, Laplacian of Gaussian (LoG). The results herein show the potential of the methods in this paper for examining different agricultural images and distinguishing between different crops and weeds …


A Network That Really Works - The Application Of Artificial Neural Networks To Improve Yield Predictions And Nitrogen Management In Western Australia, Jinsong Leng, Andreas Neuhaus, Leisa Armstrong Jan 2014

A Network That Really Works - The Application Of Artificial Neural Networks To Improve Yield Predictions And Nitrogen Management In Western Australia, Jinsong Leng, Andreas Neuhaus, Leisa Armstrong

Research outputs 2014 to 2021

Yield predictions are notorious for being difficult due to many interdependent factors such as rainfall, soil properties, plant health, plant density etc. This study is based upon the author’s previously published work and extends its findings by further investigating the best mathematical solution to this dilemma. Artificial intelligence (AI) techniques have been applied to a large set of soil, plant, rainfall, and yield data from CSBP’s field research trial program. Here we further differentiate by investigate two ANN techniques, a genetic algorithm with back propagation neural networks (GA-BP-NN) and a particle swarm optimization with back propagation neural networks (PSO-BP-NN). Results …


An Artificial Neural Network For Predicting Crops Yield In Nepal, Tirtha Ranjeet, Leisa Armstrong Jan 2014

An Artificial Neural Network For Predicting Crops Yield In Nepal, Tirtha Ranjeet, Leisa Armstrong

Research outputs 2014 to 2021

This paper examines the application of artificial neural networks (ANNs) for predicting crop yields for an agricultural region in Nepal. The neural network algorithm has become an effective data mining tool and the outcome produced by this algorithm is considered to be less error prone than other computer science techniques. The backpropagation algorithm which iteratively finds a suitable weight value is considered for computing the error derivative. Agricultural data was collected from thirteen years from paddy field cultivation in the Siraha district, an eastern region in Nepal, and used for this investigation of neural networks. Additionally, climatic parameters including rainfall, …


Decision Support System Data For Farmer Decision Making, Pornchai Taechatanasat, Leisa Armstrong Jan 2014

Decision Support System Data For Farmer Decision Making, Pornchai Taechatanasat, Leisa Armstrong

Research outputs 2014 to 2021

The capacity of farmers and agricultural scientists to be able to make in-season decisions is dependent on accurate climate, soil and plant data. This paper will provide a review of the types of environmental and crop data that can be collected by sensors which can used for decision support systems (DSS) or be further interrogated for real time data mining and analysis. This paper also presents a review of the data requirements for agricultural decision making by firstly reviewing decision support frameworks and agricultural DSSs, data acquisition, sensors for data acquisition and examples of data incorporation for agricultural DSSs.


Integrating Soil And Plant Tissue Tests And Using An Artificial Intelligence Method For Data Modelling Is Likely To Improve Decisions For In-Season Nitrogen Management, Andreas Neuhaus, Leisa Armstrong, Jinsong Leng, Dean Diepeveen, Geoff Anderson Jan 2014

Integrating Soil And Plant Tissue Tests And Using An Artificial Intelligence Method For Data Modelling Is Likely To Improve Decisions For In-Season Nitrogen Management, Andreas Neuhaus, Leisa Armstrong, Jinsong Leng, Dean Diepeveen, Geoff Anderson

Research outputs 2014 to 2021

This paper hypothesizes that there is value in combining soil, climate and plant tissue data to give more reliable advice on nitrogen top-ups in-season when compared with models that are currently available. The benefit of soil and climate data is to factor in N mineralisation and potential yield while plant test data is a more direct approach of yield estimates when considering firstly plant N uptake from the whole soil profile and secondly biomass (important yield component). Plant test data are closer to yield in time and space than soil test data, shortening the time period for any yield prognosis …