Agriculture Victoria’s unique distribution channel for nutrient balances

Gemma Heemskerk 1, Hayden Lewis 2, Andrew McAllister 2 , Cameron Gourley 3, Muhammad Islam4

1 Agriculture Research, Department of Economic Development, Jobs, Transport and Resources, Agriculture Victoria, 32 Lincoln Square North, Carlton Victoria 3053. Website: http://farmbuild.github.io/farmbuild/ Email: Gemma.Heemskerk@ecodev.vic.gov.au
2 Agriculture Research, Department of Economic Development, Jobs, Transport and Resources, Agriculture Victoria, 255 Ferguson Road, Tatura Victoria 3616. Email: Andy.McAllister@ecodev.vic.gov.au; Hayden.Lewis@ecodev.vic.gov.au
3 Agriculture Research, Department of Economic Development, Jobs, Transport and Resources, Agriculture Victoria, 1301 Hazeldean Road, Ellinbank Victoria 3821. Email: Cameron.Gourley@ecodev.vic.gov.au
4 Agriculture Research, Department of Economic Development, Jobs, Transport and Resources, Agriculture Victoria, Cnr Taylor St and Midland Hwy, Epsom Victoria 3551.  Email: Muhammad.Islam@ecodev.vic.gov.au

Abstract

Victorian agriculture faces significant challenges to meet the demands of growing markets and continue to deliver production gains, while also demonstrating responsible management of resources.  Nutrient resources are a key management consideration for Victorian agriculture.  Translation of our science into practical, everyday decision support is achieved with FarmBuild that delivers algorithms, calculators, and key agricultural datasets as freely available online functions.

 

Agriculture industry service providers and software developers can utilise FarmBuild web services, Application Programming Interfaces (APIs), integrated data sources and open source JavaScript API sample code, to build their own digital tools.  This will enable providers to support their own clients, and be customised for their specific needs. Whole farm nutrient balance models, as well as farm mapping and soil information, are currently available as on-line FarmBuild functions.

 

FarmBuild is a unique distribution channel for Agriculture Victoria’s science.  Decades of scientific research and data collation to understand whole farm nutrient balances is being delivered as web services and API’s.  This allows third-party users to integrate this science into their own digital tools with free and open access via GitHub.  Providing third-party users the opportunity to embrace the significant advances in digital technology, together with access to the best and current science for Victorian agriculture, will encourage evidence-based decision making on-farm.

Economies of scale in farms and environmental inequalities through the lenses of nitrogen fertilizer use: Concept development

Luciano B. Mendes & Wilfried Winiwarter

International Institute of Applied Systems Analysis, Schlossplatz 1, Laxenburg, A-2361, Austria, www.iiasa.ac.at, mendes@iiasa.ac.at, winiwart@iiasa.ac.at

Abstract

In this paper, we develop the framework of a system dynamics-based model for future studying the equity of resource distribution in rural areas, at a country scale and farm resolution. Our main hypothesis for conceptual development of the model is the following: the unequal spatial distribution of N fertilizer availability and use within a country might be linked to an unbalanced distribution of income to farms (in terms of farm size, i.e. economies of scale), which at the same time, might lead to exacerbated pollution.  In such a context, our target variables are: nitrogen fertilizer use, farm size (both in land area and herd size) and emissions of NH3, N2O and CH4, all disaggregated in a per-country basis. The Causal Loop Diagram (CLD) approach was used for this study, for visual representation of our ‘model concept’ on how target and intermediate variables are related. In order to allow future calibration and/or validation of the dynamic model, all variables utilized in construction of the CLD are commonly used indicators of social and rural development, economies of scale at farm level and environmental impacts. The representation of our model into a CLD revealed that a more sophisticated representation of wealth distribution in farms may be needed to extend beyond trivial outcomes in modelling effects of N fertilizer use.

Spatial analysis of nitrogen strip trials in sugarcane

Anthony Webster1, Rob Bramley2

1 CSIRO Agriculture, McGregor Road, Smithfield, Qld, 4878, tony.webster@csiro.au

2 CSIRO Agriculture, Waite Campus, Urrbrae, SA, 5064

Abstract

Nitrogen losses from sugarcane farms pose a threat to the Great Barrier Reef. Applying differential rates of nitrogen within blocks is one proposed management practice to reduce this threat by matching nitrogen rates to crop demand at the within-block scale. Farmers need practical methods to determine the appropriate nitrogen rate to apply to differing yielding parts of their blocks when employing variable rate application. We implemented a nitrogen strip trial with rates of 37, 132, and 170 kg N/ha in a plant crop of sugarcane, in comparison to the farmers normal rate of 153 kg N/ha. The block was harvested with a yield monitor fitted harvester. From the resultant yield map, yield values were extracted every three metres along the centre line of each strip. Rolling groups of ten extracted yield values were compared for each test strip to an adjacent area that received the farmer’s normal application via a paired two tail t-test. Yield was found to be significantly different for portions of each test strip and the normal N application rate. This information, used in conjunction with the yield map, was able identify areas of the block where lower application of N could be justified. In different parts of the block each of 37, 132 and 153 kg N/ha would achieve maximum yield. The farmer could use this information to apply lower than normal rates to areas where these lower rates do not compromise yield. Applying N differentially at the within-block scale at rates that match crop demand would be the optimal strategy in this block, and will lead to reduced N losses to the Great Barrier Reef.

The ‘Dairy Nitrogen Fertiliser Advisor’ – a web-based tool to assist farmer decisions

Kerry Stott1, Bill Malcolm1 and Cameron Gourley2

1Agriculture Victoria, Parkville Centre, Department of Economic Development, Jobs, Transport and Resources, Carlton, Victoria 3053. kerry.stott@ecodev.vic.gov.au

2Agriculture Victoria, Ellinbank Centre, Department of Economic Development, Jobs, Transport and Resources, Ellinbank, Victoria 3821.

Abstract

Decisions about using N fertiliser rely typically on rules based on expected average pasture responses to N applied. Such rules are mute on the economic limit to N use. In this paper, a new web-based application called the ‘Dairy Nitrogen Fertiliser Advisor’ (the ‘N-Advisor’) is presented. The tool uses marginal analysis and profit-maximising principles to inform dairy farmers and their advisors when they are considering how much N to apply to a particular paddock for a particular grazing rotation. The tool embodies response functions that have been derived from nearly 6,000 data sets from experiments in pasture yield response to N undertaken across Australia over the past 40 years. The response functions exhibit the diminishing returns required for marginal economic analysis. Recommendations about nitrogen fertiliser based on information from using the N-Advisor derive from (i) the expected marginal product of a response function for a particular Australian state and season calibrated to the paddock in question, (ii) the cost of the fertiliser (as spread) and (iii) the value of the extra pasture consumed. The N-Advisor enables users to perform ‘what-if’ analyses, exploring the effect on the profit maximising level of N of changing the cost of N fertiliser, or changing the value of the dry matter consumed. The N-Advisor also enables risk associated with production outcomes to be considered. The production and profit information that can be estimated using the N-Advisor has sufficient rigour and relevance to add value to decisions dairy farmers make about applying N.

A calibrated model for predicting pasture yield response to nitrogenous fertiliser

Murray C Hannah, Cameron J P Gourley, Kohleth Chia, Ivor M Awty

Agriculture Research and Development Division, Ellinbank Centre, Department of Economic Development, Jobs, Transport and Resources, Ellinbank, VIC 3821, AUSTRALIA. Murray.Hannah@ecodev.vic.gov.au.

Abstract

The increasing use of nitrogen (N) fertiliser in pasture-based dairy systems is commensurate with a decline in N use efficiency and increase in N surplus. An improved ability to predict pasture yield response to applied N is a crucial first step in determining the production and economic benefits of N fertiliser inputs. Data and meta data on pasture yield response to N fertiliser were utilised from a database repository of Australian fertiliser trials. Despite the extent of the data, there was patchy availability of meta data, only two nitrogen rates applied in the majority of trials, skewed representation of states, regions and seasons, and likely selection biases arising from trial protocol. These data were analysed and a quantitative non-linear mixed effects model based upon the Mitscherlich function was developed. The model included fixed effects for state by season, phosphorus status and harvest type (initial or residual), and nested random effects for location and trial/sub-trial. The model may be useful in predicting pasture yield response to applied N fertiliser as a proportion of obtainable yield and can be scaled to absolute response using the fitted model estimates of maximal yield, classified by location and season and by P status and harvest type, or by specification of a target harvest yield.

Addressing Heterogeneity of Maize Yield and Nitrogen Use Efficiency in India: Farm-specific Fertilizer Recommendation from the Nutrient Expert® Tool

Kaushik Majumdar1, Sudarshan Dutta1, T. Satyanarayana1, Hirak Banerjee2, Rupak Goswami3, Vishal Shahi1, Mirasol Pampolino4, M. L. Jat5 and Adrian Johnston6

1 International Plant Nutrition Institute-South Asia Program, Gurgaon, Haryana, India, 122016, www.ipni.net, kmajumdar@ipni.net ;

2 Bidhan Chandra Krishi Viswavidyalaya, Mohanpur, Nadia, West Bengal, India; 3 IRDM Faculty Centre, Ramakrishna Mission Vivekananda University, Kolkata, India, 700103; 4 International Plant Nutrition Institute-South East Asia Program, Los Banos, Philippines; 5 International Maize and Wheat Improvement Center, New Delhi, India; 6 International Plant Nutrition Institute, Saskatoon, CANADA S7N 3R3

Abstract

Maize is an important contributor to food security in India. It is grown in diversified environments, and under variable management practices. Increasing demand for maize from multiple sectors, and its resilience to abiotic and biotic stresses, have made it a choice crop among farmers. Appropriate fertilizer management is important for sustainably intensifying maize systems in India. However, smallholder farmers’ fertilizer management in maize is generally more perception-based than science-based due to lack of appropriate guidance. This often leads to imbalanced fertilizer application by the farmers, with loss of yield and large environmental footprint from fertilizer use. The current study uses a fertilizer recommendation tool, Nutrient Expert® for maize, to provide field specific fertilizer recommendations to farmers of two distinct maize growing ecologies of Eastern and Southern India. The on-farm results, comparing the Nutrient Expert® tool-based recommendation and existing farmers’ fertilizer practices, showed that fertilizer recommendation from the tool improved maize yield and nitrogen use efficiency as compared to existing farmers’ practices, irrespective of scale of investigation ranging from regions, cropping seasons within regions, and farm typologies within states in a region.

Evaluation of a new fertilizer recommendation approach to improve nitrogen use efficiency across small-holder farms in China

Ping He1, Xinpeng Xu2, Limin Chuan3, Adrian Johnston4

1 International Plant Nutrition Institute (IPNI) China Program, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing, 100081, china.ipni.net, phe@ipni.net

2Institute of Plant Nutrition and Resources, Beijing Academy of Agricultural and Forestry Sciences, Beijing, 100097

3 Institute of Information on Science and Technology, Beijing Academy of Agricultural and Forestry Sciences, Beijing, 100097

4 International Plant Nutrition Institute (IPNI), 102-411 Downey Road, Saskatoon, SK, Canada S7N4L8

Abstract

Low fertilizer use efficiency caused by over and imbalanced fertilization is the great challenge in intensified agricultural production systems in China. Therefore, it is necessary to develop a better nutrient management and fertilizer recommendation approach for small-holder farms in China.  This paper introduces a new fertilizer recommendation approach based on yield response and agronomic efficiency, which addresses all such concerns. The nutrient management principles were developed to consolidate the complex and knowledge intensive information into simple deliverable computer software named “Nutrient Expert” enabling local advisors rapidly implement this technology to ensure field specific guidelines for fertilizer recommendations. The software only requires information that can be easily provided by farmers or local expert. The user will get a guideline on fertilizer management (and more, such as recommended plant density, attainable yield, profit analysis, etc) that are tailored to his location and locally available fertilizer sources after answering a set of simple questions. Nutrient Expert advocates managing the 4R Nutrient Stewardship strategy adopted by the global fertilizer industry compatible with the economic, social and environmental goal of sustainable development. Multiple-site field validation demonstrated that the easily grasped new approach based on yield response and agronomic efficiency helps in strategizing appropriate management of nutrients leading to better yield, nitrogen use efficiency and environmental sustainability.

Nitrogen decisions for cereal crops: a risky and personal business

Robert Farquharson1, Deli Chen1, Yong Li1, 2, De Li Liu3, Thiagarajah Ramilan1-4

1Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Parkville, Victoria 3010, Australia, bob.farquharson@unimelb.edu.au 

2Chinese Academy of Science, 52 Sanlihe Rd., Beijing, China (100864) 

3NSW Department of Primary Industries, Wagga Wagga Agricultural Research Institute, Wagga Wagga, NSW 2650, Australia 

4Massey University, Palmerston North 4474, New Zealand

Abstract

Cereal crops principally require Nitrogen (N) and water for growth. Fertiliser economics are important because of the cost at sowing with expectation of a financial return after harvest. The production economics framework can be used to develop information for ‘best’ fertiliser decisions. But the variability of yield responses for rainfed production systems means that fertiliser decisions are a risky business. How do farmers make such decisions, and can economics give any guidance? Simulated wheat yield responses to N fertiliser applications show tremendous variation between years or seasons. There are strong agronomic arguments for a Mitscherlich equation to represent yield responses. Plots of the 10th, 50th and 90th percentiles of yield response distributions show likely outcomes in ‘Poor’, ‘Medium’ and ‘Good’ seasons at four Australian locations. By adding the prices for Urea and wheat we predict that the ‘best’ decisions vary with location, soil, and (sometimes) season. We compare these predictions with typical grower fertiliser decisions.  Australian wheat growers understand the yield responses in their own paddocks and the relative prices, so they are making relevant short-term fertiliser decisions. These are subjective or personal decisions. Myanmar smallholders grow rice and maize in the Central Dry Zone, with relatively low levels of fertiliser and low crop yields. They have pre-existing poverty, high borrowing costs and are averse to risky outcomes. A Marginal Rate of Return (MRR) analysis with a hurdle rate of 100% is illustrated for the Australian locations, and this approach will be tested in Myanmar.

 

Fertcare® – moving toward more effective nitrogen use

Jeff Kraak1, Nick Drew

1 Fertilizer Australia, Locked Bag 916, Canberra ACT, 2601, www.fertilizer.com.au, jeff.kraak@fertilizer.org.au

Abstract

Fertilizers provide an effective way to replace valuable plant nutrients such as nitrogen (N) that are removed in crop and animal products. Environmental issues associated with nutrients are areas of policy focus and public debate. Excess nutrients moving from agricultural land can harm other eco systems. An example is the movement of N from agricultural land into the waters of the Great Barrier Reef.

The fertilizer industry has made a commitment to effectively manage environment issues by developing and delivering its’ product stewardship program, Fertcare®.  This program encourages effective use of fertilizers to optimise crop and pasture yield while managing offsite movement of nutrients.

With over 2,900 people trained, 300 Accredited Advisors and 80 Accu-Spread® contractor machines, Fertcare® is effective in communicating good practices in fertilizer use and reducing environment risks. Fertcare® provides assurance to government, consumers and farmers that sound practices are being followed, and the program integrates with nutrient management public policy.

Targeted regulation of nitrogen loads – a spatial modelling case study of a Danish catchment

Berit Hasler1, Line Blok Hansen1 , Maria Konrad 1 ,  Hans Estrup Andersen 2, Mette Termansen1

1 Aarhus University, Dept. of Environmental Sciences, Frederiksborgvej 399, DK-4000 Roskilde, Denmark.

2 Aarhus University, Dept. of Bioscience, Vejlsøvej 25, DK_8600 Silkeborg, Denmark

Abstract

Nutrient loads cause eutrophication, and the non-point character of this pollution problem has been studied for decades. Efforts have been made to reduce nutrient loads and eutrophication in both Europe and the US, but additional actions are required to achieve good water quality aimed for in water quality policies. Novel data describing the spatial relationships between biophysical, hydrological factors and agricultural production now enable modelling of the non-point pollution and the spatial configuration of costs to reduce these loads. Spatial data have been used to model and analyze the cost-effective choices of abatement measures taking the nonpoint and diffuse distribution of the loads of nitrogen to the sea into account. Applying a cost-minimization model at a fine spatial resolution, we identify spatially distributions of the cost-effective implementation of abatement measures. We conclude that spatially differentiated implementation of abatement measures reduce costs compared to uniform regulations, and that including detailed modelling of the spatial configuration of the nitrogen retention in targeting also enables a reduction of the costs of N abatement.