Embed Size (px)
Citation preview
grdc.com.au
PROFIT FROM PRECISION AGRICULTUREPREPARED BY PATRICK REDDEN AND ROYCE PITCHFORD (RURAL DIRECTIONS PTY LTD), AND KATE BURKE (THINK AGRI) PROJECT 9176123
SOUTHERN REGION DECEMBER 2018
> A SUMMARY OF CURRENT INFORMATION ON THE ECONOMIC VALUE OF PRECISION AGRICULTURE TOOLS IN THE GRDC SOUTHERN REGION
2 TABLE OF CONTENTS
TABLE OF CONTENTS
Disclaimer and acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4
About this publication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
More on farm business profit gain opportunities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7
PA Profit Pathways . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .8
Estimating value and contribution to profit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
Operational timeliness and PA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
A profit first, PA second approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Understanding your region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
A review of the economic value of PA applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
PA Profit Pathway 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
Improving PAWC-Soil pH and lime application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
Drainage mapping to address water logging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
Improving PAWC- Ripping dense or compacted subsoil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Improving PAWC- Soil structure amelioration with gypsum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
Improving PAWC- Soil structure amelioration with animal manure by surface application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Improving PAWC- Ameliorating water repellent sands via claying, delving, spading or inversion . . . . . . . . . . . . . . . . . . . . . . . 24
Autosteer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
PA Profit Pathway 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
Improved Phosphorous (P)management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
Improved Potassium (K) management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
Improved N management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
Estimating yield potential by understanding seasonal and spatial variation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
Fallow management of weeds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
Managing herbicide resistant or other difficult to control weed populations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
Streamlining crop monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
Future PA Profit Opportunities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
Tool box 1 – Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
Tool Box 2 – PA Technical information sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
Tool Box 3 – Is PA for me? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
References and further reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
DISCLAIMER AND ACKNOwLEDGEMENTS 3
DISCLAIMERGRDC: Any recommendations, suggestions or opinions contained in this publication do not necessarily represent the policy or views of the Grains Research and Development Corporation (GRDC). No person should act on the basis of the contents of this publication without first obtaining specific, independent professional advice.
The GRDC will not be liable for any loss, damage, cost or expense incurred or arising by reason of any person using or relying on the information in this publication.
The Company: This report has been produced by Rural Directions Pty Ltd (herein referred to as ‘the Company’) and associated consultants/ specialists. Whilst all due care has been taken in collecting, collating and interpreting information for this report, some omissions may have occurred. The statements and opinions contained in this report are given in good faith and in the belief that they are not false or misleading.
Neither the consultants nor the Company undertakes responsibility in any way whatsoever to any person in respect to the document, including any errors or omissions therein, arising through negligence or otherwise however caused.
This report is copyright. No part of it in any way may be by any means reproduced or stored in a retrieval system or transmitted without prior permission of the Company.
ACKNOwLEDGEMENTSThe authors would like to acknowledge the levy payers and GRDC for funding this work. We would also like to thank numerous contributors to this report for sharing their experience, insight and pointing us in the direction of research papers and information.
Of particular note is the Project Steering Committee for their input into structure, themes and content for the report, as well as review. The Steering Committee consists of Sam Trengove, Jess Koch, Andrew Whitlock, Brendan Williams, Daniel Harris, Rick Llewellyn and Randall Wilksch.
DISCLAIMER AND ACKNOwLEDGEMENTS
4 INTRODUCTION
Precision Agriculture (PA) is now part of grain growing vernacular. PA as previously defined by GRDC is simply:
• doing the right thing
• in the right place
• in the right way
• at the right time.
Site Specific Management (SSM) refers to PA applications for precise broadacre paddock management and most of the technologies featured here fit under that banner. The base technology required is a navigation guidance system, georeferencing of data, and software to enable georeferenced data to be interrogated and synthesised into a usable map or prescription (GRDC 2006).
Adoption of relatively simple applications such as auto steer and auto-section control are in the order of 80% across the region with higher rainfall areas closer to 70% and medium and low rainfall regions between 80 and 90% (Umbers 2017). The rate of adoption has been higher than other PA practices such as yield mapping (Lewellyn and Ouzman 2015).
Adoption of other applications have been much slower, even if clearly demonstrated to provide value. These include variable rate application of fertiliser or soil ameliorants on different soil types across a paddock, yield monitoring and yield mapping to aid decision making, and selective spot spraying of weeds.
The slow adoption is despite considerable investment by GRDC in the Precision Agriculture Initiative from 2006 to 2010 and continued work by specialist groups such as Society of Precision Agriculture Australia (SPAA), regional farming systems groups and expert consulting businesses.
Impediments to adoption cited by growers and advisers include:
• a lack of compatibility between hardware and software across different machinery
• the management time required to capture, process, and interpret data
• the disconnect between machinery and hardware suppliers and agronomic advisers in some districts
• the real or perceived capital cost to adopt the practice
• a lack of observability- i.e not clearly observing the benefits over the fence.
The perceived lack of robust and independent evidence quantifying the economic value of PA tools or PA across the whole farm is also cited as a significant barrier to adoption (GRDC 2017).
This comes at a time when grain yield achievement (Ya) relative (Yr) to water limited potential (Yw) is often below a reasonably expected Yr of 80% of Yw with considerable variation between and within regions (Hochman et al 2016). For example, a survey of 52 southern region paddocks in 2015 and 2016 found 62% of paddocks achieved yields below 80% of Yw (Lawes et al 2018).
Profit and return on capital achieved by grain growers is also highly variable with the upper 20% of farm businesses achieving returns far greater than the average return (Figure 1).
INTRODUCTION
INTRODUCTION 5
0.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
14.0%
SA Mid-North, Lower
Yorke Eyre
SA -VicMallee
Tasmaniangrain growing
NSW Central NSW SouthWest Slopes
VictorianHigh Rainfall
Southernregionalaverage
Return on equity Southern Australia
Top 20%
Average
FIGURE 1. Return on Equity for 100 farm businesses in Southern Australia (GRDC RDP00013 2016)
The consistent trend of substantial variation in both profit achievement and grain yield among growers in similar environments demonstrates the opportunity for many growers to improve their bottom line and move closer to enduring profits.
PA applications can improve yield and or reduce the cost of production, thereby having a positive influence on profit when applied in the appropriate situation.
This document summarises those situations where PA can value to the farm business through either a clear economic contribution or through harder to quantify factors such as ease of use or improved timeliness.
An evidence-based approach (Barends et al 2014), was undertaken to assess PA profit gain opportunities as follows:
1. Relevant information from published research and industry case studies was sourced critically evaluated and combined with
2. Industry knowledge, experience and recent data to ensure relevance in today’s crop production context, culminating in
3. A considered and practical appraisal of how PA can contribute to profit now and into the future.
6 ABOUT THIS PUBLICATION
This resource is for grain growers and their advisers who are asking:
How does Precision Agriculture (PA) improve farm business profit?We summarise the situations and technologies where PA has improved the profitability of cropping systems within GRDCs Southern Region (Tasmania, South Australia and Victoria).
Precision Agriculture can mean many things to many people and is often interlinked with terms such as digital agriculture, decision agriculture, big data, and agtech. The glossary in Tool Box 1 unpacks some of these terms. For the purposes of this report PA is taken to mean the actual change in practice, rather than the data associated with that change.
The focus is on assessing economic value and contribution to profit. This is not a ‘how to’ manual for Precision Agriculture Tools. Toolbox 2 lists several excellent technical reference materials.
This report forms the first output of ‘Assessing the economic value of precision agriculture tools for grain farming businesses in the Southern Region’. Subsequent outputs will include a management guideline, specific extension material with economic information for various PA applications, and a series of workshops on getting the most economic returns from PA adoption. These outputs will go into more depth on specific PA applications and economics.
The purpose of this publication and project is to focus on the relevant on-farm benefits of PA. Whilst there is further potential for supply chain, provenance, and environmental benefits from the adopting of other PA applications, these are not covered in this report and are beyond the scope of this project.
ABOUT THIS PUBLICATION
MORE ON FARM BUSINESS PROFIT GAIN OPPORTUNITIES 7
A recent GRDC funded analysis of 300 grain focused businesses across Australia between 2009 to 2013 identified common attributes among the most profitable business (GRDC RDP00013 2016). Gross margin optimisation; low-cost business model; risk management; and people and management were the four themes identified (Table 1). High performing businesses were strong in all four areas – simply being very strong at gross margin optimisation or having a lean business model was not enough.
Factors explaining the variation in financial returns include achievement of grain yield; management of both fixed and variable costs; efficient use of people, machinery and capital; the ability to withstand business shocks; considered and timely decision making; and implementation of operations.
Scale of operation and commodity price were poor explainers of performance, as was found in a similar study of Western Australian farms (Lawes and Kingwell 2012). While rainfall influenced grain yield in both studies, there was considerable variation among performance in similar districts, indicating the strong influence of farm management. Critically, the high performing business can be making more than double the returns of the average business.
PA must positively impact on at least one of the four profit drivers to consistently influence profit. There is also potential for an inappropriate focus on one profit driver to the detriment of others. For example, the pursuit of gross margin optimisation with high capital cost machinery can have a negative impact on the low-cost business model area, and result in poorer overall financial performance.
Another profit driver that is critical for successful implementation of PA is people and management. This is driven by having people with the right skills and motivation to implement PA accessible to the grower. This could be from within the farm team or through external service providers, but without the people element a strong economic impact from PA is unlikely.
TABLE 1. PROFIT DRIVERS IDENTIFIED FOR SOUTHERN REGION FROM A SURVEY OF 100 FARM BUSINESSES (GRDC RDP00013 2016)
PROFIT OPPORTUNITY KEY MANAGEMENT CONSIDERATIONS
Gross margin optimisation (cost effective production)
Enterprise choice
Crop rotation
Timeliness of operations
Sound agronomy driving high water use efficiency and yield
Variable costs control
Maximising quality
Low-cost business model (profit focus)
Overhead cost control
Labour efficiency
Machinery investment matched to business size
Finance costs actively managed
Risk management Able to withstand seasonal or other business shocks
People and management Getting things done in a timely manner and to a high standard
Clear and balanced decision making
Systems and processes to support work flow
MORE ON FARM BUSINESS PROFIT GAIN OPPORTUNITIES
8 PA PROFIT PATHwAYS
PA alone will not overcome the major management considerations associated with the key profit drivers outlined in Table 1. In other words, it will not make up for deficiencies in other areas of the business, such as high cost structure, or poor agronomy. Yet evidence does support PA leading to economic gain in three pathways outlined below.
It’s important to note that the contribution to profit will not be realised if the pathway to achieving the productivity gains compromises farm business cost structure. This can occur by over investment in machinery, increased labour, high cost of data acquisition, or compromised timeliness of key farm operations.
The three pathways identified that growers can take to improve profit with PA are:
Pathway 1. Strategic - Unlocking yield potential by cost effectively managing site specific soil constraints and/or enabling cost effective farming systems changes• Examples include variable rate lime and gypsum, more
precise drainage, subsoil amelioration, claying and delving planning
• Operations that are high cost are more targeted by only treating the responsive areas thus becoming economically viable
• PA is the enabler for the practice adoption and productivity uplift by identifying where to target large investment into capital projects
• PA also enables some strategic farming systems changes, that unlock multiple benefits beyond simply managing site specific soil constraints. For example, the adoption of inter-row sowing is a small change in itself, but could be the enabler of a controlled traffic farming (CTF)
• These projects often take more than one year to plan and implement, but have long term paybacks over many years, and can be transformative for the farm business.
The gains available here are generally of higher value than Tactical or Reactive categories
Pathway 2. Tactical - Achieving water limited yield potential in a cost-effective manner while managing production risk • Examples include variable rate P, N, K, S and seeding rate,
for site specific weed detection and control, on-row or inter-row sowing
• These tactics are often used each year with some minor refinements between seasons, but the same basic process is applied each year
• The gains are achieved by managing seasonal yield constraints and better managing between year variation, improved timeliness of operations and learning by doing (on farm test strips and trials to refine management approaches and facilitate adoption).
The gains available here are generally individually small but can collectively be significant.
PA PROFIT PATHwAYS
PA PROFIT PATHwAYS 9
Pathway 3. Reactive - Optimising quality and price and therefore increasing revenue• Responding quickly to unplanned seasonal events to
capture an opportunity or reduce a loss
• Examples include selective harvesting to manage frost damage, protein tracking to blend grain deliveries, patching out weedy or frosted areas for hay
• These applications are usually opportunistic and time sensitive and usually an added extra rather than the reason for implementing a PA practice.
Given their reactive nature, the gains here may be reduced if the extra labour or effort required exceeds the potential advantage.
Table 2 summarises typical constraints and opportunities that impact on profit in the GRDC Southern Region. These mostly relate to gross margin optimisation in the profit driver framework of Table 1.
TABLE 2. LIKELY SITUATIONS WHERE PA MAY CONTRIBUTE TO PROFIT
STRATEGIC TACTICAL REACTIVE
Unlocking yield potential by cost effectively managing site specific soil constraints and/or enabling cost effective farming systems changes
Achieving water limited yield potential in a cost-effective manner while managing production risk
Optimising quality and price and therefore increasing revenue
• Sodicity
• Salinity
• Acidity
• Non-wetting sand
• Compaction
• Soil density
• Soil texture
• Waterlogging
• Soil nutrition
• Matching yield potential to plant available water
• Crop monitoring
• Root disease management
• Fallow management of weeds
• In crop weed management
• Frost
• Heat stress
• Harvest management
• Patchy weed infestations
10 PA PROFIT PATHwAYS
ESTIMATING VALUE AND CONTRIBUTION TO PROFITQuantifying the economic value of PA is a challenge and the source of much debate. There are two main approaches that are used, and both have merit.
The ‘Partial Budget’ approach involves assessing the change in practice and returns due to that change (GRDC RDP00013 2015). This can be a combination of change in cost and/or change in revenue. This is the simplest method of assessing economic value from PA adoption but has some weaknesses in dealing with the different results that can be achieved in different seasons. That said, partial budgeting is a good conservative starting point.
Variation between seasons (temporal variation) is generally greater than spatial (proximal) variation within fields so understanding the probabilities of achieving a benefit based on seasonal volatility could further enhance the partial budgeting approach.
‘Whole Farm Analysis’ is favoured by some to examine the impact, probability and profitability of the management change at the whole farm level over time. Generally whole farm benefits are assumed to be greater than those calculated in partial budget.
The challenge in whole farm analysis is that often paddock scale benefits are simply multiplied up to a whole farm level. This may be over or understating the variability between paddocks across the farm. The scale of variability is inconsistent – even at a paddock level. Across a farm there will not necessarily be a uniform benefit from adopting PA. This can further add to the complexity of decision making for PA, compared to the more ‘one in all in’ adoption decisions that apply across a farm, such as a new variety or moving to no-till (Lawes and Robertson 2011).
Where possible, we summarise both the monetary value using Partial Budgeting and/ or Whole farm analysis and the indirect (non-monetary) value including a qualitative judgement on likelihood of contribution to profit.
PA implementation requires dedicated time and labour in excess of normal farm operations. This could be in the data collection and analysis phase, the machine setup and monitoring, or the investigation phase. Economic analysis of the benefit needs to recognise the value of the time and labour that has gone into the project, even if it is internal family labour.
Recognising the capital investment required for PA is also important when assessing its economic value. Grain farms are capital intensive businesses, and profitable deployment of capital is critical for financial success. The investment of capital comes with an opportunity cost and this needs to be reflected in the economic analysis of any capital investment for PA.
Depreciation of PA equipment is another consideration. The nature of PA equipment is that there is a continued evolution, innovation and improvement in the technology that underlies it. This increases the speed at which previously useful equipment is superseded and potentially rendered obsolete. Allocating a minimum of 15% depreciation rate when costing PA equipment will account for this (GRDC RDP00013 2015).
The capital cost of the PA component of machinery varies considerably. For older technology like autosteer, the cost of accessing the technology is effectively built into the price of a machine. This results in a very low capital investment to access the tool itself. Some of the reactive PA applications such as selective harvesting for frost may have no capital outlay. For other tools such as pH mapping accessing capital is often done through using a contractor to complete the task. An example of a capital-intensive application of PA is the purchase of an optical spot sprayer for managing summer fallows. For capital intensive PA applications, adoption is often limited by scale and the ability to spread the cost.
PA PROFIT PATHwAYS 11
OPERATIONAL TIMELINESS AND PATimeliness of all operations remains the major management related profit driver in the Southern Region, Timelly fallow management, earlier sowing and appropriate crop management all contribute to improving water use efficiency and yield (Robertson et al 2016). When PA improves timeliness it indirectly improves profitability.
PA can be an enabler for larger management units to increase work rate without sacrificing sound agronomy. As paddock sizes have increased to enable larger machinery to operate at greater field efficiency, PA is providing a means of continuing to treat different soil types or paddock history with integrity. Hence a grower can get more done without the potential missed opportunity of a blanket input approach.
Another improvement to timeliness can come in the form of strategic amelioration projects. Large capital inputs such as lime to treat acid soils, gypsum to treat sodicity, or clay spreading and delving on non-wetting sands are a substantial investment for a business, yet with large production gains possible. Adopting a PA approach to these projects will allow more efficient targeting of responsive areas.
For example, if the capital budget allows for 100ha of liming each year, a blanket approach may apply lime to 70ha of responsive soil types and 30ha of no response. Using PA to target 100ha of responsive soils each year effectively improves the timeliness of liming on 30ha, bringing forward the production benefits by a year on that area. For a 1,000ha farm this scenario would cover the whole farm in seven years rather than 10.
Further to this, the time period for reapplication could be increased by targeting problem areas with a more appropriate higher rate of lime the first time.
‘Precision Monitoring’ is an effective tool to reduce the risk of untimely monitoring constraining crop yield and profit. Thorough crop monitoring is critical to maximising water use efficiency by ensuring that in-season yield limitations are identified and addressed in a timely manner. Timeliness of crop monitoring can become a profit limiting factor as farm scale increases.
Understanding inherent spatial variability using data layers such as historic yield maps or imagery, or in season NDVI imagery can help growers and agronomists make better use of crop monitoring time. In season imagery can help target monitoring and sometimes provide an alert to an emerging issue before it is obvious at ground level in the paddock (e.g early stage N deficiency). When combined with ground truthing, earlier intervention may occur. Conversely, relying entirely on remote sensing of crop growth differences to identify anomalies and prompt action can be too late for early weed infestations or insect damage that can cap yield potential (and profit) in the crop establishment phase.
PA can have a negative impact on timeliness and therefore profit when it’s not implemented well. This can occur by:
• increasing complexity of an operation
• misplaced priorities (taking time to setup for the last 1% gain at the expense of getting the job done)
• creating a system that is heavily reliant on technology that is prone to greater downtime when things aren’t working.
The increasingly sophisticated electronics involved in farm machinery is taking much of the maintenance and repair away from the grower. The result is that problems can take longer and cost more to fix, whereas in times past growers were able to identify and rectify basic mechanical issues and get on with the job.
12 PA PROFIT PATHwAYS
ON-FARM LEARNINGA further indirect benefit from PA is the ability to conduct trials and test new approaches on an individual farm. This can be used in a multitude of ways from variety selection and fertiliser strategy, through to higher cost soil amelioration projects. The nature of PA also requires a level of curiosity into the underlying constraints in a paddock.
The process of exploring these constraints is a fantastic learning tool and can increase the rate of adoption of new practices. In this way there can be value in exploring spatial data to assist with identifying and solving a problem, even if it does not lead to a move to a more targeted or variable rate approach.
PA PROFIT PATHwAYS 13
A PROFIT FIRST, PA SECOND APPROACHThe financial gain from PA is best optimised by identifying the farm business profit opportunities first, then considering if a PA practice can help realise that opportunity more effectively. Table 3 explains the steps to that approach along with an example.
TABLE 3. THE PROFIT OPPORTUNITY FIRST APPROACH
STEPS TO IDENTIFYING PA PROFIT GAIN OPPORTUNITIES EXAMPLE
1. Understand profit gain opportunities for the farm business using the profit drivers framework (Table 1)
We have low pH soils limiting yield potential in some but not all areas on the farm
2. Does PA have a role in addressing those constraints? Soil types are variable within paddocks so variable rate application of lime could be an option
3. Determine the cost and benefit of implementing the PA practice using a partial budget approach
A partial budget analysis compares using PA or not, (e.g VR lime v Uniform spreading) to address the issue
4. Are there other benefits to consider? Lower liming costs will mean more paddocks can be amended in one season
5. Does the business have the capacity to usefully implement? The PA profit ready check list in Tool Box 3 is a good place to start
14 PA PROFIT PATHwAYS
The likelihood of PA effectively contributing to profit will vary for each individual farm business and each potential application due to the physical farm attributes, current equipment base, and seasonal, market and input price conditions. In other words, the odds of a PA application contributing to profit is very situational.
Paddock variability plays a major role in determining the economic benefits from PA adoption. If there is insufficient variability within a paddock, then there is unlikely to be a strong business case for the effort and expense of a site-specific approach to soil amelioration or crop nutrition. Paddock variability of 10 to 15% co-efficient of variation (CV) is often enough to expect a financial benefit from managing the variability while CV > 15% is considered highly likely to achieve a financial payback from managing the variability. The extent of variability required to warrant spatial management will also be dependent on crop type and value (Sauer et al 2013).
Data layers that contribute to an understanding of paddock variability include yield maps and remote images such as satellite derived NDVI maps and soil surveys as well as farmer knowledge.
Care is required when using any of these spatial variability maps as they require ground-truthing to ascertain the reason for the variability. Visual assessment of the crop, soil and tissue testing, and soil surveying can all be useful to determine the underlying cause of the variability. This investment in ground-truthing makes up part of the cost of implementing PA but is an important stage in the process.
The size of the cost or benefit to be realised will also influence how much variability is required to make a PA approach economically worthwhile. A high cost per hectare treatment such as claying requires relatively little variability to show a benefit from PA if it can be targeted more effectively. A relatively low-cost saving per hectare treatment such as site-specific spot spraying of weeds requires much higher levels of spatial variability to achieve an economic benefit. This also demonstrates why the relative economic gains to be made from the Strategic PA pathway tend to be larger than the Tactical PA pathway.
The benefit from smaller cost saving items is greater where the targeted intervention increases yield or prevents yield loss (Trengove 2018). An example of this using PA derived soil variability knowledge to inform where to apply lower rates of metribuzin on sandy soils and higher rates on heavier soils in the same paddock. The financial benefit comes from avoiding yield loss caused by metribuzin induced crop damage rather than the small savings in herbicide.
UNDERSTANDING YOUR REGION 15
The Southern Region has a diverse array of soil types, climates, and farming systems. The economic value and opportunity of PA tools for each farm business in the region will vary accordingly. This section looks at the broad issues affecting different zones within the region, and where PA is likely to have the highest impact on profit for each zone.
GRDC divides the Southern Region into three broad zones based on high, medium and low rainfall (Figure 3). These can then be split further into subregions based on soil type and landscape.
FIGURE 3. GRDC Southern Region and rainfall zones
Table 4 summarises the soil type and farming system attributes affecting grain yield in each zone and Table 5 summarises the most likely fit of PA applications in each zone. These tables were derived by identifying the highest and lowest impact opportunities for each region utilising the judgement and experience of the steering committee combined with available published evidence. It is not intended as an exhaustive list or definitive analysis. It aims to illustrate the degree of prevalence of an issue within a subregion rather than the complete presence or absence. This is intended as a quick reference guide to what may be impacting profit in your zone, so that the highest priorities can be recognised.
UNDERSTANDING YOUR REGION
16 UNDERSTANDING YOUR REGION
TAB
LE 4
. DIS
TRIB
UTI
ON
OF
SOIL
TY
PE A
TTRI
BU
TES
AN
D S
OM
E M
AJO
R FA
CTO
RS K
NO
WN
TO
INFL
UEN
CE
GRA
IN Y
IELD
AC
ROSS
TH
E SO
UTH
ERN
REG
ION
RAIN
FALL
ZO
NE
SUB
REG
ION
PAW
SAN
DY
SO
ILS
AC
ID
SOIL
SA
LIN
ITY
SOD
ICIT
YW
ATER
LO
GG
ING
C
OM
PAC
TIO
NN
PKS
NU
TRIT
ION
FALL
OW
M
AN
AG
EMEN
TH
ERB
ICID
E RE
SIST
AN
CE
FRO
STH
EAT
STRE
SS
Low
Upp
er E
P
All z
ones
√
√
√
All z
ones
Al
l zon
es
√√
√
Wes
tern
EP
√
√
√
√
√
Upp
er N
orth
√√
√√
√
√√
√
SAVI
C N
Mal
lee
√
√√
√
√√
√
SAVi
c S
Mal
lee
√
√√
√
√√
√
Vic
C M
alle
e√
√
√
√√
√√
Med
ium
Low
er E
P√
√√
√√
√√
√
Cen
tral Y
P√
√
√
Low
er Y
P√
√
√√
Nor
ther
n YP
- M
id N
orth
√√
√√
√
√√
√
Wim
mer
a-Bo
rder
tow
n√
√
√√
√√
√√
SA U
pper
Sou
th E
ast
√√
√√
√
√√
√
Cen
tral V
ic
√√
√√
√√
√√
Nth
Cen
tral V
ic
√√
√
√√
√√
Hig
h
SA L
ower
Sou
th E
ast +
Ka
ngar
oo Is
land
√√
√√
√√
√
Sout
hern
Vic
√
√√
√√
√√
√
Nor
th E
ast V
ic s
lope
s
√√
√√
√√
√√
Tas
Gra
in
√
√√
√√
√
UNDERSTANDING YOUR REGION 17
TAB
LE 5
. SPE
CIF
IC P
A A
PPLI
CAT
ION
S TH
EIR
LIKE
LY C
ON
TRIB
UTI
ON
TO
PRO
FIT
AC
ROSS
TH
E RE
GIO
N B
ASE
D O
N S
UIT
AB
ILIT
Y A
ND
ARE
A A
FFEC
TED
(GRE
EN -
HIG
HLY
LIK
ELY;
Y
ELLO
W- S
OM
ETIM
ES L
IKEL
Y; O
RAN
GE
- LES
S LI
KELY
)
STRA
TEG
ICTA
CTI
CA
LRE
AC
TIV
E
RAIN
FALL
ZO
NE
SUB
REG
ION
Dra
inag
e m
appi
ng
Zone
d cl
ayin
g/
delv
ing
Zone
d rip
ping
/ sp
adin
g
Zone
man
agem
ent t
hrou
gh v
aria
ble
rate
ap
plic
atio
n of
:Ve
hicl
e au
tost
eer
Impl
emen
t st
eerin
g (P
rotra
kker
)
Com
pact
ion
man
agem
ent
with
CTF
Inte
r-ro
w o
r on
-row
so
win
g
Site
sp
ecifi
c w
eed
dete
ctio
n an
d co
ntro
l
Dec
isio
n su
ppor
t for
so
il &
crop
m
onito
ring
Map
ping
w
eeds
Prot
ein
Map
ping
Lim
eG
ypsu
mSe
edN
, P, K
, S
Low
Upp
er E
P
Wes
tern
EP
Upp
er N
orth
SAVI
C N
Mal
lee
SAVi
c S
Mal
lee
Vic
C M
alle
e
Med
ium
Low
er E
P
Cen
tral Y
P
Low
er Y
P
Nor
ther
n YP
- M
id N
orth
Wim
mer
a-Bo
rder
tow
n
SA U
pper
Sou
th
East
Cen
tral V
ic
Nth
Cen
tral V
ic
Hig
h
SA L
ower
Sou
th
East
+ K
anga
roo
Isla
nd
Sout
hern
Vic
Nor
th E
ast V
ic
slop
es
Tas
Gra
in
18 A REVIEw OF THE ECONOMIC VALUE OF PA APPLICATIONS
This section collates previously published economic studies. The criteria for inclusion were full accounting of costs including capital outlay, depreciation, labour and operational costs as described earlier. Previously reported benefits based on anecdotes are not included. We have focused on Strategic and Tactical pathways to profit. The reactive pathway by nature is more variable and situational and will be demonstrated later in this project through case studies.
A REVIEw OF THE ECONOMIC VALUE OF PA APPLICATIONS
A REVIEw OF THE ECONOMIC VALUE OF PA APPLICATIONS 19
PA P
ROFI
T PA
THW
AY 1
STRA
TEG
IC -
UN
LOC
KIN
G Y
IELD
PO
TEN
TIA
L BY
CO
ST E
FFEC
TIV
ELY
MA
NA
GIN
G S
ITE
SPEC
IFIC
SO
IL C
ON
STRA
INTS
PRO
FIT
OPP
ORT
UN
ITY
MO
ST L
IKEL
Y
APP
LIC
AB
LE
PLA
CES
IN
SOU
THER
N
ZON
E
AD
OPT
ION
STA
TUS
WH
AT’S
TH
E PA
VA
LUE
PRO
POSI
TIO
N?
REV
IEW
OF
ECO
NO
MIC
ST
UD
IES
WH
AT IN
FLU
ENC
ES S
UC
CES
S?
IMPR
OV
ING
PA
WC
-
SOIL
PH
AN
D L
IME
APP
LIC
ATIO
N
Low
Soi
l pH
ar
eas:
LRZ
Upp
er N
orth
MRZ
Low
er E
P
NYP
Mid
Nor
th
SA U
pper
SE
Cen
tral V
ic
Nth
Cen
tral V
ic
HRZ
SA L
ower
SE
+ KI
Vic
Sth
NE
Vic
slop
es
Tas
Gra
in
Impr
ovin
g PA
WC
an
d th
us c
rop
or
past
ure
prod
uctio
n by
incr
easi
ng s
oil p
H
abov
e 4.
8 (C
aCl2
) is
com
mon
pra
ctic
e
Lim
ing
acid
ic
soils
nee
ds to
be
mai
ntai
ned
and
pote
ntia
lly in
crea
sed
to
coun
tera
ct a
cidi
ficat
ion
over
tim
e
In S
A, V
R lim
ing
is
incr
easi
ng b
ut o
nly
acro
ss 6
% o
f sui
tabl
e ar
eas
thus
far (
Har
ding
et
al 2
018)
In V
ic, V
R lim
ing
adop
tion
is in
crea
sing
bu
t the
re is
sig
nific
ant
pote
ntia
l for
furth
er
adop
tion
• So
il pH
spa
tial v
aria
bilit
y is
map
ped
and
lime
is
appl
ied
at v
aryi
ng ra
tes
depe
ndin
g on
soi
l pH
re
spon
sive
ness
• As
a h
igh
capi
tal c
ost a
ctiv
ity, l
imin
g is
m
ore
cost
effe
ctiv
e th
roug
h ta
rget
ed z
one
man
agem
ent a
nd V
R
• Pr
ofit g
ains
com
e fro
m:
• un
lock
ing
yiel
d po
tent
ial b
y ad
dres
sing
so
il ac
idity
and
impr
ovin
g PA
WC
(e.g
15%
to
50%
yie
ld re
spon
se d
epen
ding
on
crop
ty
pe a
nd s
tarti
ng p
H in
SW
Vic
) (M
iller 2
015)
• m
ore
effici
ent a
lloca
tion
of e
xpen
ditu
re
incr
easi
ng m
argi
nal r
etur
n on
inve
stm
ent
and
redu
cing
the
payb
ack
perio
d
• ap
plyi
ng li
me
to a
reas
that
wou
ld n
ot h
ave
been
trea
ted
in th
e ab
senc
e of
spa
tial p
H
data
• Li
me
savi
ngs
of 3
0 to
75
% in
NE
and
SW V
ic,
with
10%
bei
ng re
quire
d to
cov
er th
e co
st o
f th
e m
appi
ng p
roce
ss
(Whi
tlock
201
5; S
PAA
2011)
• $
16-$
73/h
a fro
m li
me
savi
ngs
case
stu
dies
in
2016
(RD
P000
13a
2016
)
• O
liver
et a
l (20
10)
estim
ated
1 to
2 y
ear
payb
ack
perio
d fro
m V
R lim
ing
in W
A w
heat
bel
t w
hen
yiel
d re
spon
se to
lim
ing
was
incl
uded
in
the
anal
ysis
• Le
vel o
f var
iabi
lity
in s
oil p
H
and
lime
resp
onsi
vene
ss
acro
ss a
pad
dock
or f
arm
• W
ater
lim
ited
yiel
d po
tent
ial-
(Hig
her p
ay o
ffs in
hig
h ra
infa
ll zo
nes)
• C
ost a
nd a
cces
s to
lim
e pr
oduc
t. N
ot re
adily
ava
ilabl
e in
som
e ar
eas,
so
ther
e is
val
ue
allo
catin
g lim
ited
tonn
ages
to
the
mos
t res
pons
ive
parts
of
the
farm
• Ac
cess
to a
var
iabl
e ra
te
lime
spre
ader
(alth
ough
not
es
sent
ial)
20 A REVIEw OF THE ECONOMIC VALUE OF PA APPLICATIONS
PA P
ROFI
T PA
THW
AY 1
STRA
TEG
IC -
UN
LOC
KIN
G Y
IELD
PO
TEN
TIA
L BY
CO
ST E
FFEC
TIV
ELY
MA
NA
GIN
G S
ITE
SPEC
IFIC
SO
IL C
ON
STRA
INTS
PRO
FIT
OPP
ORT
UN
ITY
MO
ST L
IKEL
Y
APP
LIC
AB
LE
PLA
CES
IN
SOU
THER
N
ZON
E
AD
OPT
ION
STA
TUS
WH
AT’S
TH
E PA
VA
LUE
PRO
POSI
TIO
N?
REV
IEW
OF
ECO
NO
MIC
ST
UD
IES
WH
AT IN
FLU
ENC
ES S
UC
CES
S?
DRA
INA
GE
MA
PPIN
G T
O
AD
DRE
SS W
ATER
LO
GG
ING
Hig
h Ra
infa
ll re
gion
s an
d lo
w-
lyin
g ar
eas
pron
e to
wat
er lo
ggin
g in
Med
ium
Ra
infa
ll zo
nes
MRZ
Low
er E
P
Wim
mer
a-Bo
rder
tow
n
Cen
tral V
ic
HRZ
SA L
ower
SE
+ KI
Vic
Sth
NE
Vic
slop
es
Tas
Gra
in
Seve
ral c
omm
erci
al P
A pr
ovid
ers
parti
cula
rly
thos
e se
rvic
ing
the
HRZ
, pro
vide
dr
aina
ge m
anag
emen
t ad
vice
bas
ed o
n PA
te
chno
logy
in S
outh
ern
and
NE
Vict
oria
and
in
Tasm
ania
and
SE
Sout
h Au
stra
lia
• Pa
ddoc
k ar
eas
pron
e to
cro
p lo
ss th
roug
h w
ater
inun
datio
n ar
e re
clai
med
thro
ugh
data
de
rived
and
wel
l-pla
nned
dra
inag
e
• El
evat
ion
map
s an
d w
ater
mov
emen
t si
mul
atio
n ar
e us
ed to
pla
n eff
ectiv
e dr
aina
ge
or d
iver
t wat
er b
efor
e in
reac
hes
low
lyin
g ar
eas
• As
an
ofte
n-hi
gh c
apita
l cos
t act
ivity
, ben
efits
ar
e de
rived
from
allo
catin
g co
sts
effec
tivel
y an
d en
surin
g m
axim
um re
turn
on
inve
stm
ent
• Pr
ofit g
ains
com
e fro
m:
• un
lock
ing
yiel
d po
tent
ial o
f are
as p
rone
to
inun
datio
n w
ater
logg
ing
• in
crea
sed
traffi
cabi
lity
impr
ovin
g tim
elin
ess
of o
pera
tions
• m
ore
effici
ent a
lloca
tion
of e
xpen
ditu
re
(by
putti
ng th
e dr
ains
in th
e rig
ht s
pots
) in
crea
sing
mar
gina
l ret
urn
on in
vest
men
t an
d re
duci
ng th
e pa
ybac
k pe
riod
• re
mov
ing
the
need
for r
aise
d be
ds in
som
e si
tuat
ions
, red
ucin
g ca
pita
l cos
ts
• m
ore
effici
ent f
ertil
iser
use
thro
ugh
less
de
nitri
ficat
ion
loss
es (W
hitlo
ck a
nd T
orpy
20
17)
No
publ
ishe
d ec
onom
ic
stud
ies
wer
e fo
und
• Th
e re
lativ
e ar
ea o
f pro
duct
ive
land
pro
ne to
inun
datio
n an
d w
ater
logg
ing
• Th
e fre
quen
cy o
f whi
ch
inun
datio
n oc
curs
• C
ost o
f acq
uirin
g dr
aina
ge
sim
ulat
ion
and
cost
of d
rain
age
wor
ks
A REVIEw OF THE ECONOMIC VALUE OF PA APPLICATIONS 21
PA P
ROFI
T PA
THW
AY 1
STRA
TEG
IC -
UN
LOC
KIN
G Y
IELD
PO
TEN
TIA
L BY
CO
ST E
FFEC
TIV
ELY
MA
NA
GIN
G S
ITE
SPEC
IFIC
SO
IL C
ON
STRA
INTS
PRO
FIT
OPP
ORT
UN
ITY
MO
ST L
IKEL
Y
APP
LIC
AB
LE
PLA
CES
IN
SOU
THER
N
ZON
E
AD
OPT
ION
STA
TUS
WH
AT’S
TH
E PA
VA
LUE
PRO
POSI
TIO
NRE
VIE
W O
F EC
ON
OM
IC
STU
DIE
SW
HAT
INFL
UEN
CES
SU
CC
ESS?
IMPR
OV
ING
PA
WC
-
RIPP
ING
DEN
SE
OR
CO
MPA
CTE
D
SUB
SOIL
Sand
y or
poo
rly
stru
ctur
ed d
uple
x so
ils w
ithin
:
LRZ
Upp
er E
P
Wes
tern
EP
Upp
er N
orth
SA/V
ic N
,S,C
M
alle
e
MRZ
Low
er E
P
Cen
tral Y
P
Low
er Y
P
NYP
Mid
Nor
th
SA U
pper
SE
Cen
tral V
ic
Nth
Cen
tral V
ic
HRZ
SA L
ower
SE
+ KI
Vic
Sth
NE
Vic
slop
es
Tas
Gra
in
Ripp
ing
to o
pen
up
subs
oils
has
bee
n sp
orad
ical
ly a
dopt
ed
thro
ugho
ut th
e de
cade
s (S
ale
et a
l 20
16)
Ripp
ing
is u
sed
to
redu
ce c
ompa
ctio
n in
san
dy s
oils
; red
uce
hard
pan
in d
uple
x so
ils a
nd to
faci
litat
e ro
ot g
row
th in
den
se
subs
oils
with
var
ied
leve
ls o
f suc
cess
(Sal
e et
al 2
016)
Ove
rall
adop
tion
is
rela
tivel
y lo
w
• So
il ty
pe v
aria
bilit
y, cl
ay c
onte
nt a
nd d
epth
to
cla
y is
map
ped
to id
entif
y ar
eas
that
may
re
spon
d to
ripp
ing.
Iden
tify
area
s co
ntai
ning
to
xic
leve
ls o
f Bor
on, S
odiu
m, C
hlor
ide
or
Alum
iniu
m, t
hat m
ay n
eed
to b
e av
oide
d so
as
not t
o br
ing
toxi
c so
il to
the
surfa
ce
• Pr
ofit g
ains
com
e fro
m:
• un
lock
ing
yiel
d po
tent
ial a
nd im
prov
ing
PAW
C th
roug
h in
crea
sed
root
ing
dept
h in
th
e m
ost c
ost-e
ffect
ive
man
ner p
ossi
ble
• m
ore
effici
ent a
lloca
tion
of e
xpen
ditu
re
incr
easi
ng m
argi
nal r
etur
n on
inve
stm
ent
and
redu
cing
the
payb
ack
perio
d
• re
duce
d ris
k of
brin
ging
pro
blem
soi
ls to
th
e su
rface
by
treat
ing
inap
prop
riate
are
as
Whi
le s
tudi
es h
ave
dem
onst
rate
d th
e ec
onom
ic im
pact
of r
ippi
ng
appl
icat
ion
per s
e in
san
dy
soils
(Hal
l 201
7); n
o st
udie
s re
porti
ng th
e ec
onom
ics
of
usin
g PA
to ta
rget
dip
ping
de
pth
and
area
wer
e fo
und
• C
ost o
f dat
a la
yers
• Ac
cess
to e
quip
men
t or s
kille
d co
ntra
ctor
s to
car
ry o
ut ri
ppin
g
• C
ost o
f am
elio
ratio
n re
lativ
e to
yie
ld p
oten
tial a
nd in
com
e ga
ins
- pay
back
is s
horte
r w
here
the
yiel
d ga
p is
the
grea
test
, ofte
n in
hig
her r
ainf
all
zone
s
• C
ompl
icat
ed re
latio
nshi
ps
exis
t bet
wee
n th
e so
il su
rvey
fa
ctor
s an
d id
entif
ying
re
spon
sive
soi
ls. C
are
need
s to
be
take
n in
terp
retin
g da
ta
and
a pi
lot a
ppro
ach
is u
sefu
l be
fore
full
scal
e re
med
iatio
n is
un
derta
ken
• In
crea
sing
the
leng
th o
f ben
efit
by a
void
ing
re-c
ompa
ctio
n
22 A REVIEw OF THE ECONOMIC VALUE OF PA APPLICATIONS
PA P
ROFI
T PA
THW
AY 1
STRA
TEG
IC -
UN
LOC
KIN
G Y
IELD
PO
TEN
TIA
L BY
CO
ST E
FFEC
TIV
ELY
MA
NA
GIN
G S
ITE
SPEC
IFIC
SO
IL C
ON
STRA
INTS
PRO
FIT
OPP
ORT
UN
ITY
MO
ST L
IKEL
Y
APP
LIC
AB
LE
PLA
CES
IN
SOU
THER
N
ZON
E
AD
OPT
ION
STA
TUS
WH
AT’S
TH
E PA
VA
LUE
PRO
POSI
TIO
N?
REV
IEW
OF
ECO
NO
MIC
ST
UD
IES
WH
AT IN
FLU
ENC
ES S
UC
CES
S?
IMPR
OV
ING
PA
WC
-
SOIL
STR
UC
TURE
A
MEL
IORA
TIO
N
WIT
H G
YPS
UM
Area
s w
here
so
dici
ty is
a
cons
train
t with
in
LRZ
Upp
er E
P
Wes
tern
EP
Upp
er N
orth
SA/V
ic N
,S,C
M
alle
e
MRZ
Low
er E
P
NYP
Mid
Nor
th
SA U
pper
SE
Cen
tral V
ic
Nth
Cen
tral V
ic
HRZ
SA L
ower
SE
+ KI
Vic
Sth
NE
Vic
slop
es
Tas
Gra
in
Incr
easi
ng P
AWC
and
tra
ffica
bilit
y th
roug
h th
e ap
plic
atio
n of
gyp
sum
is
com
mon
pra
ctic
e fo
r hi
gh d
ensi
ty, d
ispe
rsiv
e cl
ay-b
ased
soi
ls, m
any
whi
ch a
re s
odic
(Sal
e et
al 2
016)
Varia
ble
rate
ap
plic
atio
n of
gyp
sum
is
kno
wn
to o
ccur
in
Nor
ther
n Vi
ctor
ia a
nd
sout
hern
NSW
but
the
exte
nt o
f ado
ptio
n ac
ross
the
regi
on is
un
know
n
• Sp
atia
l var
iabi
lity
of s
oil t
ype
and
gyps
um
resp
onsi
vene
ss is
map
ped,
and
gyp
sum
is
appl
ied
at v
aryi
ng ra
tes
to a
men
d so
dici
ty
or d
ispe
rsiv
enes
s du
e to
low
Ca
rela
tive
to
mag
nesi
um
• As
a h
igh
capi
tal c
ost a
ctiv
ity, g
ypsu
m
appl
icat
ion
is m
ore
cost
effe
ctiv
e th
roug
h ta
rget
ed z
one
man
agem
ent a
nd V
R
• Ea
rly s
easo
n N
DVI
map
s ca
n be
a u
sefu
l in
dica
tor o
f sod
ic to
psoi
l if p
oor c
rop
emer
genc
e or
vig
our i
s re
late
d to
sod
icity
• Pr
ofit g
ains
com
e fro
m:
• un
lock
ing
yiel
d po
tent
ial b
y re
duci
ng s
oil
sodi
city
and
impr
ovin
g PA
WC
• in
crea
sed
traffi
cabi
lity
and
impr
ovin
g tim
elin
ess
of o
pera
tions
• m
ore
effici
ent a
lloca
tion
of e
xpen
ditu
re
incr
easi
ng m
argi
nal r
etur
n on
inve
stm
ent
and
redu
cing
the
payb
ack
perio
d
Stud
ies
repo
rting
on
the
econ
omic
s of
usi
ng P
A fo
r soi
l am
elio
ratio
n w
ith
gyps
um w
ere
not f
ound
• Le
vel o
f var
iabi
lity
in s
odic
ity
or s
oil d
ispe
rsiv
enes
s ac
ross
a
padd
ock
or fa
rm
• C
ost a
nd a
cces
s to
gyp
sum
pr
oduc
t. It
is n
ot re
adily
av
aila
ble
in s
ome
area
s,
so th
ere
is v
alue
allo
catin
g lim
ited
tonn
ages
to th
e m
ost
resp
onsi
ve p
arts
of t
he fa
rm
• Ac
cess
to a
var
iabl
e ra
te
gyps
um s
prea
der
A REVIEw OF THE ECONOMIC VALUE OF PA APPLICATIONS 23
PA P
ROFI
T PA
THW
AY 1
STRA
TEG
IC -
UN
LOC
KIN
G Y
IELD
PO
TEN
TIA
L BY
CO
ST E
FFEC
TIV
ELY
MA
NA
GIN
G S
ITE
SPEC
IFIC
SO
IL C
ON
STRA
INTS
PRO
FIT
OPP
ORT
UN
ITY
MO
ST L
IKEL
Y
APP
LIC
AB
LE
PLA
CES
IN
SOU
THER
N
ZON
E
AD
OPT
ION
STA
TUS
WH
AT’S
TH
E PA
VA
LUE
PRO
POSI
TIO
N?
REV
IEW
OF
ECO
NO
MIC
ST
UD
IES
WH
AT IN
FLU
ENC
ES S
UC
CES
S?
IMPR
OV
ING
PA
WC
-
SOIL
STR
UC
TURE
A
MEL
IORA
TIO
N
WIT
H A
NIM
AL
MA
NU
RE B
Y
SURF
AC
E A
PPLI
CAT
ION
Area
s w
here
so
dici
ty is
a
cons
train
t, an
d m
anur
e is
av
aila
ble
with
in
LRZ
Upp
er E
P
Wes
tern
EP
Upp
er N
orth
SA/V
ic N
,S,C
M
alle
e
MRZ
Low
er E
P
NYP
Mid
Nor
th
SA U
pper
SE
Cen
tral V
ic
Nth
Cen
tral V
ic
HRZ
SA L
ower
SE
+ KI
Vic
Sth
NE
Vic
slop
es
Tas
Gra
in
Surfa
ce a
pplic
atio
n of
ani
mal
man
ure
can
incr
ease
PAW
C
and
traffi
cabi
lity
in
high
den
sity
cla
y so
ils (A
rmst
rong
et a
l 20
07;2
015)
Ado
ptio
n is
rest
ricte
d by
hig
h to
nnag
es
requ
ired
and
subs
eque
nt c
ost o
f fre
ight
and
han
dlin
g
Is in
crea
sing
in
popu
larit
y in
nor
ther
n an
d so
uthe
rn V
icto
ria
on d
uple
x so
ils
• Sp
atia
l var
iabi
lity
of s
oil t
ype
and
resp
onsi
ve
to m
anur
e is
map
ped
and
man
ure
is
appl
ied
at v
aryi
ng ra
tes
to a
men
d so
dici
ty
or d
ispe
rsiv
enes
s du
e to
low
Ca
rela
tive
to
Mag
nesi
um o
r hig
h N
a%
• As
a h
igh
capi
tal c
ost a
ctiv
ity, m
anur
e ap
plic
atio
n is
mor
e co
st e
ffect
ive
thro
ugh
targ
eted
zon
e m
anag
emen
t and
VR
• Pr
ofit g
ains
com
e fro
m:
• un
lock
ing
yiel
d po
tent
ial b
y re
duci
ng s
oil
sodi
city
and
impr
ovin
g PA
WC
• in
crea
sed
traffi
cabi
lity
impr
ovin
g tim
elin
ess
of o
pera
tions
• m
ore
effici
ent a
lloca
tion
of e
xpen
ditu
re
incr
easi
ng m
argi
nal r
etur
n on
inve
stm
ent
and
redu
cing
the
payb
ack
perio
d
• Th
ere
may
als
o be
a n
utrie
nt re
spon
se in
so
me
year
s (C
eles
tina
et a
l 201
8)
Stud
ies
spec
ifica
lly
repo
rting
on
the
econ
omic
s of
usi
ng P
A fo
r soi
l am
elio
ratio
n w
ith
anim
al m
anur
e w
ere
not
foun
d
• Le
vel o
f var
iabi
lity
in s
odic
ity
or s
oil d
ispe
rsiv
enes
s ac
ross
a
padd
ock
or fa
rm
• C
ost a
nd a
cces
s to
man
ure
prod
uct.
Not
read
ily a
vaila
ble
in s
ome
area
s, s
o th
ere
is v
alue
al
loca
ting
limite
d to
nnag
es to
th
e m
ost r
espo
nsiv
e pa
rts o
f th
e fa
rm
• Ac
cess
to a
var
iabl
e ra
te
man
ure
spre
ader
24 A REVIEw OF THE ECONOMIC VALUE OF PA APPLICATIONS
PA P
ROFI
T PA
THW
AY 1
STRA
TEG
IC -
UN
LOC
KIN
G Y
IELD
PO
TEN
TIA
L BY
CO
ST E
FFEC
TIV
ELY
MA
NA
GIN
G S
ITE
SPEC
IFIC
SO
IL C
ON
STRA
INTS
PRO
FIT
OPP
ORT
UN
ITY
MO
ST L
IKEL
Y
APP
LIC
AB
LE
PLA
CES
IN
SOU
THER
N
ZON
E
AD
OPT
ION
STA
TUS
WH
AT’S
TH
E PA
VA
LUE
PRO
POSI
TIO
N?
REV
IEW
OF
ECO
NO
MIC
ST
UD
IES
WH
AT IN
FLU
ENC
ES S
UC
CES
S?
IMPR
OV
ING
PA
WC
-
AM
ELIO
RATI
NG
W
ATER
RE
PELL
ENT
SAN
DS
VIA
C
LAY
ING
, D
ELV
ING
, SP
AD
ING
OR
INV
ERSI
ON
Area
s of
non
-w
ettin
g so
il w
ithin
:
LRZ
Upp
er E
P
Wes
tern
EP
Upp
er N
orth
SA/V
ic N
,S,C
M
alle
e
MRZ
Low
er E
P
Cen
tral Y
P
Low
er Y
P
NYP
Mid
Nor
th
SA U
pper
SE
Wim
mer
a-
Bord
erto
wn
HRZ
SA L
ower
SE
+ KI
Firs
t ado
pted
in th
e 19
90s
in S
E SA
and
far
wes
tern
Vic
toria
, cla
y sp
read
ing
and
delv
ing
per s
e ha
ve b
een
used
to
impr
ove
non-
wet
ting
(wat
er re
pelle
nt) s
ands
fo
r man
y ye
ars.
The
re
rem
ain
furth
er a
reas
to
trea
t acr
oss
the
sout
hern
regi
on
Ther
e ha
s be
en li
mite
d ad
optio
n of
PA
tool
s fo
r map
ping
to im
prov
e effi
cien
cy o
f cla
y sp
read
ing
and
delv
ing
• Sp
atia
l var
iabi
lity
of s
oil t
ype
incl
udin
g lo
catio
n an
d de
pth
of c
lay
is m
appe
d fro
m E
M o
r ga
mm
a ra
diom
etric
sur
veys
• Sp
adin
g, c
lay
spre
adin
g an
d cl
ay d
elvi
ng
zone
s ar
e id
entifi
ed
• D
elvi
ng is
che
aper
than
cla
y sp
read
ing,
and
re
sults
in s
igni
fican
t sav
ings
• N
ew d
elvi
ng te
chno
logy
can
adj
ust d
epth
ba
sed
on a
pre
scrip
tion,
ena
blin
g ‘V
R de
lvin
g’
• Pr
ofit g
ains
com
e fro
m:
• un
lock
ing
yiel
d po
tent
ial a
nd im
prov
ing
PAW
C in
the
mos
t cos
t-effe
ctiv
e m
anne
r po
ssib
le
• im
prov
ing
crop
com
petit
ive
abilit
y ag
ains
t w
eeds
• m
ore
effici
ent a
lloca
tion
of e
xpen
ditu
re
incr
easi
ng m
argi
nal r
etur
n on
inve
stm
ent
and
redu
cing
the
payb
ack
perio
d
• m
ore
even
wet
ting
aids
pat
ch m
anag
emen
t of
wee
ds th
roug
h cr
op c
ompe
titio
n
Littl
e da
ta is
ava
ilabl
e on
th
e ec
onom
ic c
ontri
butio
n of
PA
to th
is p
ract
ice
• C
ost o
f dat
a la
yers
• Ac
cess
to e
quip
men
t or s
kille
d co
ntra
ctor
s to
car
ry o
ut c
layi
ng/
delv
ing
• C
ost o
f am
elio
ratio
n re
lativ
e to
Yie
ld p
oten
tial a
nd in
com
e ga
ins
-pay
back
is s
horte
r in
high
er ra
infa
ll zo
nes
• C
ompl
icat
ed re
latio
nshi
ps
exis
t bet
wee
n th
e so
il su
rvey
fa
ctor
s an
d id
entif
ying
re
spon
sive
soi
ls. C
are
need
s to
be
take
n in
terp
retin
g da
ta
and
a pi
lot a
ppro
ach
is u
sefu
l be
fore
full
scal
e re
med
iatio
n is
un
derta
ken
A REVIEw OF THE ECONOMIC VALUE OF PA APPLICATIONS 25
PA P
ROFI
T PA
THW
AY 1
STRA
TEG
IC -
UN
LOC
KIN
G Y
IELD
PO
TEN
TIA
L BY
EN
AB
LIN
G C
OST
EFF
ECTI
VE
FARM
ING
SYS
TEM
S C
HA
NG
E
PRO
FIT
OPP
ORT
UN
ITY
MO
ST L
IKEL
Y
APP
LIC
AB
LE
PLA
CES
IN
SOU
THER
N
ZON
E
AD
OPT
ION
STA
TUS
WH
AT’S
TH
E PA
VA
LUE
PRO
POSI
TIO
N?
REV
IEW
OF
ECO
NO
MIC
ST
UD
IES
WH
AT IN
FLU
ENC
ES S
UC
CES
S?
AU
TOST
EER
All r
egio
nsAd
optio
n is
gen
eral
ly
high
acr
oss
the
Sout
hern
Reg
ion,
with
hi
gher
rain
fall
area
s cl
ose
to 7
0% a
nd
med
ium
and
low
rain
fall
regi
ons
betw
een
80
and
90%
(Um
bers
201
7)
• Th
ere
is a
n in
itial
ben
efit o
n re
duce
d ov
erla
p an
d in
put s
avin
gs
• Se
cond
ly a
nd m
ore
sign
ifica
ntly
in th
e lo
ng
term
, ste
erin
g gu
idan
ce e
nabl
es d
efine
d fa
rmin
g sy
stem
s ch
ange
s (e
.g C
TF) a
nd
high
impa
ct “s
yste
ms
type
’’ in
tegr
ated
cro
p m
anag
emen
t pra
ctic
es th
at c
ontri
bute
to a
fle
xibl
e ad
aptiv
e ap
proa
ch to
opt
imis
ing
yiel
d po
tent
ial a
nd m
anag
ing
risk
• Ex
ampl
es o
f sys
tem
s ty
pe a
ctio
ns in
clud
e
• in
terro
w w
eed
cont
rol a
s pa
rt of
IWM
via
sh
ield
ed s
pray
ing
or in
terro
w c
ultiv
atio
n
• st
ubbl
e m
anag
emen
t thr
ough
inte
rrow
so
win
g (IR
S)
• tre
llisin
g of
lent
ils th
roug
h IR
S in
to s
tubb
le
and
impr
ovin
g ha
rves
tabi
lityo
• on
or n
ear r
ow s
owin
g to
cap
ture
moi
stur
e or
acc
ess
resi
dual
nut
rient
s
• IR
S to
redu
ce ro
ot d
isea
se ri
sk
• Su
ch a
ctio
ns w
iden
cro
p ch
oice
and
pro
vide
a
mor
e ro
bust
cro
p ro
tatio
n
• O
ther
gai
ns c
ome
from
incr
easi
ng w
orkr
ate
from
redu
ced
oper
ator
fatig
ue a
nd e
nabl
ing
nigh
t ope
ratio
ns
• O
verla
p sa
ving
s of
$2
-$16
/ha
have
bee
n re
cord
ed (S
PAA
2008
)
• Sy
stem
s ch
ange
s ar
e ve
ry d
ifficu
lt to
qua
ntify
• Eq
uipm
ent c
apab
le o
f au
tost
eer
• H
ighe
r inp
ut c
osts
per
ha
will
resu
lt in
gre
ater
sav
ings
from
ov
erla
p
• Pr
oact
ive
and
oppo
rtuni
stic
ap
proa
ch to
util
ise
prec
isio
n st
eerin
g fo
r a c
rop
man
agem
ent o
ppor
tuni
ties
as
they
em
erge
26 A REVIEw OF THE ECONOMIC VALUE OF PA APPLICATIONS
PA P
ROFI
T PA
THW
AY 1
STRA
TEG
IC -
UN
LOC
KIN
G Y
IELD
PO
TEN
TIA
L BY
EN
AB
LIN
G C
OST
EFF
ECTI
VE
FARM
ING
SYS
TEM
S C
HA
NG
ES
PRO
FIT
OPP
ORT
UN
ITY
MO
ST L
IKEL
Y
APP
LIC
AB
LE
PLA
CES
IN
SOU
THER
N
ZON
E
AD
OPT
ION
STA
TUS
WH
AT’S
TH
E PA
VA
LUE
PRO
POSI
TIO
N?
REV
IEW
OF
ECO
NO
MIC
ST
UD
IES
WH
AT IN
FLU
ENC
ES S
UC
CES
S?
IMPR
OV
ING
TR
AFF
ICA
BIL
ITY
A
ND
MO
ISTU
RE
INFI
LTRA
TIO
N
WIT
H C
TF
All r
egio
nsC
ontro
lled
traffi
c fa
rmin
g is
incr
easi
ng
acro
ss th
e re
gion
but
re
mai
ns lo
w. A
dopt
ion
leve
ls ra
nge
from
5-
50%
by
subr
egio
n in
20
16 (U
mbe
rs 2
017)
• Pr
ecis
ion
use
of tr
affic
acro
ss a
pad
dock
to
redu
ce c
ompa
ctio
n an
d im
prov
e tra
ffica
bilit
y
• Pr
eser
vatio
n of
ben
efit f
rom
oth
er a
mel
iora
tion
tool
s su
ch a
s rip
ping
• Pr
ofit g
ain
com
es fr
om in
crea
sed
yiel
d fro
m
impr
oved
moi
stur
e in
filtra
tion,
redu
cing
run
off,
incr
ease
d po
rosi
ty a
nd im
prov
ed w
ork
rate
s an
d tim
elin
ess
whe
n co
nditi
ons
are
wet
• A
void
of e
cono
mic
dat
a fo
r the
Sou
ther
n re
gion
• In
WA
$36/
ha a
ssum
ing
5% y
ield
gai
n w
ith
2 ye
ar p
ayba
ck fo
r $2
00K
mac
hine
ry
inve
stm
ent (
King
wel
l an
d Fu
chsb
ichl
er 2
011)
• Pa
ybac
k pe
riod
is h
ighl
y de
pend
ent o
n ca
pita
l in
vest
ed, e
xpec
ted
yiel
d in
crea
se a
nd lo
catio
n (s
oil t
ype
and
yiel
d po
tent
ial)
(Bla
ckw
ell e
t al
201
6)
• So
il ty
pes
with
an
abilit
y to
sto
re la
rge
amou
nts
of
moi
stur
e
• Eq
uipm
ent t
hat i
s al
read
y pa
rtly
alig
ned
for C
TF (t
o re
duce
cap
ital o
utla
y)
• Th
e ba
se le
vel o
f ran
dom
tra
ffic
occu
rring
on
the
padd
ock
whi
ch d
eter
min
es
the
rela
tive
bene
fit
rem
aini
ng
A REVIEw OF THE ECONOMIC VALUE OF PA APPLICATIONS 27
PA P
ROFI
T PA
THW
AY 2
TAC
TIC
AL
- AC
HIE
VIN
G W
ATER
LIM
ITED
YIE
LD P
OTE
NTI
AL
IN A
CO
ST-E
FFEC
TIV
E M
AN
NER
WH
ILE
MA
NA
GIN
G P
ROD
UC
TIO
N R
ISK
PRO
FIT
OPP
ORT
UN
ITY
MO
ST L
IKEL
Y
APP
LIC
AB
LE
PLA
CES
IN
SOU
THER
N
ZON
E
AD
OPT
ION
STA
TUS
WH
AT’S
TH
E PA
VA
LUE
PRO
POSI
TIO
N?
REV
IEW
OF
ECO
NO
MIC
ST
UD
IES
WH
AT IN
FLU
ENC
ES S
UC
CES
S?
IMPR
OV
ED
PHO
SPH
ORO
US
(P)M
AN
AG
EMEN
T
Anyw
here
in
the
regi
on
with
eno
ugh
varia
bilit
y.
Adop
tion
of V
R P
varie
s w
idel
y ac
ross
th
e re
gion
. In
dune
/sw
ale
land
sys
tem
s w
here
var
iabi
lity
is
easi
ly s
een
adop
tion
leve
ls a
re a
s hi
gh a
s 70
% in
the
Vic
Mal
lee
(GRD
C 2
016)
. Low
er
adop
tion
regi
ons
such
as
Wim
mer
a w
ere
less
th
an 3
3%
• Va
riabi
lity
in s
oil t
ype
and
P st
atus
is m
appe
d an
d P
rate
zon
es a
re d
eriv
ed
• Yi
eld
map
s, p
revi
ous
ND
VI m
aps,
soi
l tes
ting
and
soil
surv
ey m
etho
ds c
an a
ll be
use
d to
de
fine
zone
s
• Pr
ofit g
ains
com
e fro
m:
• m
ore
effici
ent a
lloca
tion
of e
xpen
ditu
re
incr
easi
ng m
argi
nal r
etur
n on
inve
stm
ent
• po
tent
ial y
ield
resp
onse
in s
ome
zone
s
• Va
riabl
e co
st s
avin
gs
of -$
5 to
$13
/ha
(RD
P000
13 2
015)
• Va
riabl
e co
st s
avin
gs
of $
5-$1
0/ha
(McC
allu
m
2008
)
• Va
riabl
e co
st s
avin
gs o
f $7
/ha
(Rob
erts
on e
t al
2007
)
• Pr
ofit g
ains
from
yie
ld
resp
onse
s ar
e no
t in
clud
ed in
the
abov
e an
alys
es
• C
ost o
f dat
a la
yers
to d
efine
zo
nes
• Su
ffici
ent v
aria
bilit
y w
ithin
the
padd
ock
to d
rive
resp
onse
s
• C
lear
ly d
efine
d zo
nes
• VR
Cap
able
equ
ipm
ent
• H
igh
ferti
liser
pric
es in
crea
ses
likel
ihoo
d of
a re
turn
from
VR
appl
icat
ion
• So
il ty
pes
that
are
hig
hly
P re
spon
sive
are
mor
e lik
ely
to
prov
ide
an e
cono
mic
gai
n
IMPR
OV
ED
POTA
SSIU
M (K
) M
AN
AG
EMEN
T
LRZ
SA/V
ic N
, Mal
lee
MRZ
Low
er E
P
SA-M
id N
orth
SA U
pper
SE
Wim
mer
a-
Bord
erto
wn
HRZ
SA L
ower
SE
+ KI
Vic
Sth
NE
Vic
slop
es
Tas
Gra
in
Ligh
tly te
xtur
ed
acid
ic s
oils
can
be
defic
ient
in K
. Var
iabl
e ra
te a
pplic
atio
n of
K
ferti
liser
occ
urs
to
a lim
ited
exte
nt in
so
uthe
rn V
icto
ria
Ther
e is
gen
eral
ly lo
w
adop
tion
of u
tilis
ing
gam
ma
radi
omet
ry
to d
etec
ting
spat
ial
varia
tion
of p
otas
sium
in
Eas
tern
Aus
tralia
n
• So
il ty
pe v
aria
bilit
y is
map
ped
and
diffe
renc
es
in K
may
occ
ur
• G
reat
er p
reci
sion
in K
map
ping
is p
ossi
ble
usin
g vi
a ga
mm
a ra
diom
etry
(Won
g et
al 1
999)
• K
ferti
liser
is a
pplie
d at
var
iabl
e ra
tes
acco
rdin
g to
yie
ld re
spon
sive
ness
• Pr
ofit g
ains
com
e fro
m:
• m
ore
effici
ent a
lloca
tion
of e
xpen
ditu
re
incr
easi
ng m
argi
nal r
etur
n on
inve
stm
ent
• un
lock
ing
yiel
d po
tent
ial i
n K
defic
ient
zo
nes
that
may
not
hav
e be
en tr
eate
d if
unifo
rm K
app
licat
ion
was
the
only
opt
ion
• C
ost -
bene
fit s
tudi
es
of P
A to
defi
ne a
nd
man
age
K va
riabi
lity
wer
e no
t fou
nd. (
Seve
ral
stud
ies
lum
ped
VR N
P
K to
geth
er w
ithou
t di
ssec
ting
whe
re th
e be
nefit
was
der
ived
fro
m)
• C
ost o
f soi
l sur
veys
to d
efine
zo
nes
• Su
ffici
ent v
aria
bilit
y w
ithin
the
padd
ock
to d
rive
resp
onse
s
• C
lear
ly d
efine
d zo
nes
• VR
Cap
able
equ
ipm
ent
• H
igh
ferti
liser
pric
es in
crea
se
likel
ihoo
d of
a re
turn
from
VR
appl
icat
ion
28 A REVIEw OF THE ECONOMIC VALUE OF PA APPLICATIONS
PA P
ROFI
T PA
THW
AY 2
TAC
TIC
AL
- AC
HIE
VIN
G W
ATER
LIM
ITED
YIE
LD P
OTE
NTI
AL
IN A
CO
ST-E
FFEC
TIV
E M
AN
NER
WH
ILE
MA
NA
GIN
G P
ROD
UC
TIO
N R
ISK
PRO
FIT
OPP
ORT
UN
ITY
MO
ST L
IKEL
Y
APP
LIC
AB
LE
PLA
CES
IN
SOU
THER
N
ZON
E
AD
OPT
ION
STA
TUS
WH
AT’S
TH
E PA
VA
LUE
PRO
POSI
TIO
N?
REV
IEW
OF
ECO
NO
MIC
ST
UD
IES
WH
AT IN
FLU
ENC
ES S
UC
CES
S?
IMPR
OV
ED N
M
AN
AG
EMEN
TAn
ywhe
re in
th
e re
gion
with
en
ough
var
iabi
lity
Adop
tion
of V
R N
va
ries
wid
ely
acro
ss
the
regi
on. I
n du
ne/
swal
e la
nd s
yste
ms
whe
re v
aria
bilit
y is
ea
sily
see
n ad
optio
n le
vels
are
hig
her t
han
in m
ore
visi
bly
unifo
rm
land
type
s
As th
e co
st o
f lab
an
alys
is d
ecre
ases
m
ore
inte
nsiv
e gr
id
sam
plin
g m
ay in
crea
se
adop
tion
of V
R fe
rtilis
er
• D
istin
ct N
man
agem
ent z
ones
are
der
ived
fro
m a
rang
e of
dat
a la
yers
(e.g
yie
ld m
aps,
pr
evio
us N
DVI
map
s, o
ptic
al s
enso
rs, s
oil
test
ing
and
soil
surv
ey m
etho
ds c
an a
ll be
us
ed to
defi
ne z
ones
)
• N
app
licat
ion
stra
tegy
(tim
ing
and
rate
) is
tailo
red
to e
ach
zone
acc
ordi
ng y
ield
pot
entia
l an
d so
il N
sta
tus
• Pr
ofit g
ains
com
e fro
m:
• m
ore
effici
ent a
lloca
tion
of N
ferti
liser
ex
pend
iture
and
gre
ater
mar
gina
l ret
urn
on
inve
stm
ent
• pr
evio
usly
unr
ealis
ed y
ield
pot
entia
l on
high
er y
ield
pot
entia
l zon
es in
favo
urab
le
year
s
• re
duce
d ris
k of
hay
ing
off o
n lo
wer
yie
ld
pote
ntia
l are
as in
drie
r yea
rs
• po
ssib
ly im
prov
ed g
rain
qua
lity
thro
ugh
prot
ein
man
ipul
atio
n
Payb
ack
from
incr
ease
d yi
eld
of $
8/ha
(RD
P000
13
2015
)
This
hig
hlig
hts
that
VR
nitr
ogen
is h
ighl
y ap
plic
able
to p
addo
cks
with
hig
h sp
atia
l var
iabi
lity
in o
rder
to m
axim
ise
yiel
d an
d/or
RO
I in
indi
vidu
al
padd
ock
zone
• Th
e ab
ility
to c
ombi
ne s
easo
nal
clim
ate
fore
cast
ing
info
rmat
ion
and
plan
t ava
ilabl
e w
ater
sta
tus
into
pot
entia
l yie
ld e
stim
atio
n fo
r eac
h m
anag
emen
t zon
e
• Se
ason
al v
aria
bilit
y of
nitr
ogen
de
man
d is
ofte
n gr
eate
r th
an s
patia
l var
iabi
lity
– se
e es
timat
ing
yiel
d po
tent
ial
• VR
cap
able
equ
ipm
ent
A REVIEw OF THE ECONOMIC VALUE OF PA APPLICATIONS 29
PA P
ROFI
T PA
THW
AY 2
TAC
TIC
AL
- AC
HIE
VIN
G W
ATER
LIM
ITED
YIE
LD P
OTE
NTI
AL
IN A
CO
ST-E
FFEC
TIV
E M
AN
NER
WH
ILE
MA
NA
GIN
G P
ROD
UC
TIO
N R
ISK
PRO
FIT
OPP
ORT
UN
ITY
MO
ST L
IKEL
Y
APP
LIC
AB
LE
PLA
CES
IN
SOU
THER
N
ZON
E
AD
OPT
ION
STA
TUS
WH
AT’S
TH
E PA
VA
LUE
PRO
POSI
TIO
N?
REV
IEW
OF
ECO
NO
MIC
ST
UD
IES
WH
AT IN
FLU
ENC
ES S
UC
CES
S?
ESTI
MAT
ING
YIE
LD
POTE
NTI
AL
BY
UN
DER
STA
ND
ING
SE
ASO
NA
L A
ND
SPA
TIA
L VA
RIAT
ION
Has
regi
on w
ide
appl
icat
ion
Adop
tion
of z
one
base
d pl
ant a
vaila
ble
wat
er m
onito
ring
and
yiel
d es
timat
ion
is th
ough
t to
be lo
w
acro
ss th
e re
gion
Prac
tical
inco
rpor
atio
n of
like
ly s
easo
nal
outc
omes
bas
ed
on p
revi
ous
year
s pe
rform
ance
usi
ng P
A to
ols
is lo
w
• So
il PA
WC
is m
appe
d fro
m a
rang
e of
dat
a la
yers
(yie
ld m
aps,
ND
VI ,E
M s
urve
y) a
nd
man
agem
ent z
ones
are
defi
ned
• H
isto
rical
dat
a is
use
d to
und
erst
and
yiel
d pe
rform
ance
in v
aryi
ng s
easo
nal v
aria
tion
• C
urre
nt s
easo
n yi
eld
rang
e is
est
imat
ed u
sing
re
al ti
me
ND
VI a
nd P
AW s
tatu
s re
lativ
e to
hi
stor
ical
dat
a
• Yi
eld
rang
e is
refin
ed u
sing
with
Sea
sona
l C
limat
e in
form
atio
n
• Pr
ofit c
omes
from
:
• im
prov
ed li
kelih
ood
of R
OI f
rom
N o
r fu
ngic
ide
• Im
prov
ed ri
sk m
anag
emen
t in
gene
ral a
nd
incr
ease
d co
nfide
nce
in m
anag
ing
grai
n sa
les
and
insu
ranc
e po
sitio
ns
No
stud
ies
wer
e fo
und
that
sp
ecifi
cally
mea
sure
d th
e m
argi
nal b
enefi
t of t
he P
A co
ntrib
utio
n to
man
agin
g se
ason
al a
nd s
patia
l va
riatio
n in
yie
ld p
oten
tial
• U
nder
stan
ding
the
likel
y pe
rform
ance
of z
ones
rela
tive
to s
easo
nal c
ondi
tions
• In
corp
orat
ion
with
clim
ate
driv
er a
nd s
easo
nal f
orec
ast
deci
sion
sup
port
• Th
orou
gh k
now
ledg
e of
soi
l N
supp
ly in
eac
h m
anag
emen
t zo
ne e
ach
seas
on
30 A REVIEw OF THE ECONOMIC VALUE OF PA APPLICATIONS
PA P
ROFI
T PA
THW
AY 2
TAC
TIC
AL
- AC
HIE
VIN
G W
ATER
LIM
ITED
YIE
LD P
OTE
NTI
AL
IN A
CO
ST-E
FFEC
TIV
E M
AN
NER
WH
ILE
MA
NA
GIN
G P
ROD
UC
TIO
N R
ISK
PRO
FIT
OPP
ORT
UN
ITY
MO
ST L
IKEL
Y
APP
LIC
AB
LE
PLA
CES
IN
SOU
THER
N
ZON
E
AD
OPT
ION
STA
TUS
WH
AT’S
TH
E PA
VA
LUE
PRO
POSI
TIO
N?
REV
IEW
OF
ECO
NO
MIC
ST
UD
IES
WH
AT IN
FLU
ENC
ES S
UC
CES
S?
FALL
OW
M
AN
AG
EMEN
T O
F W
EED
S
Has
regi
on w
ide
appl
icat
ion
Fallo
w m
anag
emen
t ha
s be
en a
driv
er o
f im
prov
ed w
ater
use
effi
cien
cy in
the
past
de
cade
Mor
e re
cent
ly th
e ab
ility
of o
ptic
al s
enso
r sp
rayi
ng te
chno
logy
to
pre
cise
ly ta
rget
w
eeds
in a
pad
dock
ha
s be
com
e av
aila
ble.
Ad
optio
n ha
s be
en
rela
tivel
y st
rong
in th
e M
alle
e, w
hils
t oth
er
regi
ons
have
bee
n sl
ower
to ta
ke it
up
• O
ptic
al s
enso
rs (c
amer
a sp
ray
tech
nolo
gy)
cont
rol n
ozzl
e fu
nctio
n to
targ
et in
divi
dual
w
eeds
or g
reen
pat
ches
• Pr
ofit c
omes
from
:
• re
duce
d he
rbic
ide
cost
s
• im
prov
ed c
ontro
l of h
ard
to k
ill w
eeds
- hi
gher
her
bici
de ra
tes
can
affor
d to
be
used
on
a sm
all s
pray
are
a)
Incl
udin
g ca
pita
l cos
t re
sults
rang
ed fr
om
-$2/
ha to
$4/
ha fr
om
varia
ble
cost
s sa
ving
s ha
(R
DP0
0013
201
5)
• Th
e de
pend
ence
of t
he fa
rm
on fa
llow
wee
d co
ntro
l to
stor
e m
oist
ure
• C
ost o
f her
bici
de p
rogr
am
• Li
kelih
ood
of m
ultip
le s
pray
s in
a
give
n fa
llow
per
iod
• Ac
cess
ing
the
tech
nolo
gy in
a
low
cap
ital m
anne
r (sc
ale
or
cont
ract
ing)
A REVIEw OF THE ECONOMIC VALUE OF PA APPLICATIONS 31
PA P
ROFI
T PA
THW
AY 2
TAC
TIC
AL
- AC
HIE
VIN
G W
ATER
LIM
ITED
YIE
LD P
OTE
NTI
AL
IN A
CO
ST-E
FFEC
TIV
E M
AN
NER
WH
ILE
MA
NA
GIN
G P
ROD
UC
TIO
N R
ISK
PRO
FIT
OPP
ORT
UN
ITY
MO
ST L
IKEL
Y
APP
LIC
AB
LE
PLA
CES
IN
SOU
THER
N
ZON
E
AD
OPT
ION
STA
TUS
WH
AT’S
TH
E PA
VA
LUE
PRO
POSI
TIO
N?
REV
IEW
OF
ECO
NO
MIC
ST
UD
IES
WH
AT IN
FLU
ENC
ES S
UC
CES
S?
MA
NA
GIN
G
HER
BIC
IDE
RESI
STA
NT
OR
OTH
ER
DIF
FIC
ULT
TO
C
ON
TRO
L W
EED
PO
PULA
TIO
NS
Has
regi
on w
ide
appl
icat
ion
Her
bici
de re
sist
ance
is
a th
reat
in a
ll re
gion
s.
Ther
e is
rela
tivel
y lo
w
adop
tion
of P
A to
ols
for t
he p
urpo
se o
f m
anag
ing
herb
icid
e re
sist
ance
or h
ard
to c
ontro
l wee
d po
pula
tions
• RT
K ac
cura
te a
utos
teer
com
bine
d w
ith w
ide
row
s fa
cilit
ates
shi
elde
d sp
rayi
ng o
f non
-se
lect
ive
herb
icid
es in
som
e cr
ops
• M
appi
ng th
e po
pula
tions
of d
ifficu
lt to
kill
wee
ds u
sing
sen
sors
or N
DVI
map
s en
able
s ta
rget
ed a
pplic
atio
n of
hig
her c
ost h
erbi
cide
st
rate
gies
• Ec
onom
ic re
spon
ses
of p
atch
man
agem
ent
are
impa
cted
by
effica
cy, t
arge
t spe
cies
, cos
t of
her
bici
de, a
nd w
eed
dens
ity (T
reng
ove
2016
)
• PA
ena
bled
nov
el w
eed
cont
rol o
ptio
ns
redu
ces
the
impa
ct o
f wee
ds o
n cr
op ro
tatio
n an
d im
prov
es th
e ro
bust
ness
of t
he c
ropp
ing
sequ
ence
• Sa
ved
varia
ble
cost
s es
timat
ed to
sav
e $1
3/ha
with
shi
elde
d sp
rayi
ng (S
PAA
2011)
• Sa
ved
herb
icid
e co
sts
from
pat
ch
man
agem
ent v
arie
d fro
m $
5.42
-$15
.30/
ha
depe
ndin
g on
her
bici
de
appr
oach
(Tre
ngov
e 20
13)
• Im
porta
nt o
f her
bici
de
resi
stan
ce o
n pr
ofita
bilit
y
• Ab
ility
to in
tegr
ate
othe
r to
ols
to re
duce
relia
nce
on
herb
icid
es (s
trate
gy s
houl
dn’t
sole
ly fo
cus
on h
erbi
cide
s)
• St
able
loca
tion
of w
eed
patc
hes
betw
een
year
s
• Ab
ility
to a
ccur
atel
y de
velo
p a
wee
d m
ap. T
he b
enefi
t is
lost
is
esca
pes
pers
ist
• C
rop
type
s su
ited
to s
hiel
ded
spra
ying
(wid
e ro
w o
ptio
ns)
32 A REVIEw OF THE ECONOMIC VALUE OF PA APPLICATIONS
PA P
ROFI
T PA
THW
AY 2
TAC
TIC
AL
- AC
HIE
VIN
G W
ATER
LIM
ITED
YIE
LD P
OTE
NTI
AL
IN A
CO
ST-E
FFEC
TIV
E M
AN
NER
WH
ILE
MA
NA
GIN
G P
ROD
UC
TIO
N R
ISK
PRO
FIT
OPP
ORT
UN
ITY
MO
ST L
IKEL
Y
APP
LIC
AB
LE
PLA
CES
IN
SOU
THER
N
ZON
E
AD
OPT
ION
STA
TUS
WH
AT’S
TH
E PA
VA
LUE
PRO
POSI
TIO
N?
REV
IEW
OF
ECO
NO
MIC
ST
UD
IES
WH
AT IN
FLU
ENC
ES S
UC
CES
S?
STRE
AM
LIN
ING
C
ROP
MO
NIT
ORI
NG
All r
egio
ns
Adop
tion
of ta
rget
ed
crop
mon
itorin
g is
in
crea
sing
as
tool
s lik
e N
DVI
imag
ery
are
mor
e re
adily
ava
ilabl
e.
ther
e is
con
side
rabl
e op
portu
nity
for f
urth
er
adop
tion
as th
e tre
nd
for i
ncre
asin
g ar
ea
unde
r man
agem
ent
per f
arm
bus
ines
s
• La
rger
farm
s re
quire
effi
cien
t and
targ
eted
cr
op m
onito
ring
tech
niqu
es to
mon
itor c
rop
heal
th, m
oist
ure
stat
us, a
nd p
est a
nd w
eed
impa
cts
• U
sing
yie
ld m
aps,
ND
VI m
aps
or s
oil s
urve
ys
to id
entif
y or
qua
ntify
var
iabi
lity
in c
rop
to
targ
et m
onito
ring
• M
ore
effec
tive
use
of m
onito
ring
time
• Po
tent
ial t
o id
entif
y an
d tre
at p
robl
ems
and
oppo
rtuni
ties
earli
er
Anec
dota
l evi
denc
e bu
t no
pub
lishe
d ec
onom
ic
info
rmat
ion
foun
d
• Eff
ectiv
e gr
ound
trut
hing
of
issu
es
• Ti
mel
y de
liver
y of
imag
ery
at a
us
eful
reso
lutio
n
• N
ot s
olel
y re
lyin
g on
targ
eted
m
onito
ring
to e
nsur
e no
thin
g fa
lls th
roug
h th
e ga
ps
FUTURE PA PROFIT OPPORTUNITIES 33
PA is constantly evolving, and future opportunities will be defined by a combination of access to new technology, decreasing cost of existing technology, and the emergence of new challenges and opportunities within the farming system.
Llewellyn and Ouzman (2015) highlighted the broad adoption of early stage PA such as autosteer, with 79% and 74% adoption in SA and Victoria respectively (Tasmania was not surveyed). This had jumped significantly from approximately 30% in 2005 and demonstrates the increasing adoption of a technology as the cost decreases and it becomes embedded into existing equipment. This highlights that for current technology such as optical spot sprayers, which are relatively new and expensive, adoption should continue to increase as the cost of technology comes down over time.
There is also potential for evolution of new PA applications as new farming system challenges emerge. As an example, frost has become an increasingly important issue for many growers in the Southern Region in the past decade. This is prompting some to exploit elevation maps as a way of monitoring and subsequently managing frost damage spatially.
This highlights a need for growers to regularly review their position on individual PA tools and applications. Something that may have been deemed unviable 5 years ago may now have a clear financial benefit due to decreasing cost of the technology, or a change in the importance of the issue to their business.
The continued development of new sensing technology will undoubtedly influence PA in the future. As new sensing information emerges, it will provide huge value if it can be integrated to provide greater insight into crop production. When coupled with the increasing computing power available to analyse and interrogate data, more diagnostic and predictive tools will emerge. An example of this is the development of stress indices that can help to pinpoint what is going on in a crop. Whilst not commercial yet it is a matter of time before this information is available (Humpal et al 2018). If this information can be deployed spatially there are endless PA opportunities that could result.
Underlying almost all decision making in cropping is the need to better understand Plant Available Water Capacity (PAWC). There would be a substantial opportunity to improve decision making and profitability if a more granular and real time approach could be taken to understanding PAWC, and how full the profile is at any given time. Continued development of soil and plant sensors in this area would be of huge benefit, as this could provide a direct link to yield estimation.
Recently there has been a step change in the accessibility of low-cost (sometimes free), high resolution NDVI imagery that growers can access at any time on their tablet or computer. This will help to expose underlying paddock variability that is not always obvious, and this increased awareness will likely drive the development of new PA applications that aren’t currently known. The accessibility of this imagery is the key driver, as previously it was often yield maps that are only available at the end of the year that enabled growers to see just how variable their paddocks are.
The other advantage of this imagery is the ability to get relatively simple responsiveness strips done in a paddock to guide decision making and have an objective way of checking the response. This can improve nitrogen fertiliser decision making in particular, with the use of N rich or N absent strips. This will be exploited over the short term as the adoption of the use of the imagery increases. The technology already exists.
FUTURE PA PROFIT OPPORTUNITIES
34 CONCLUSIONS
The purpose of this report was to identify the ways that PA can improve profit for grain growers in the Southern Region. Taking a profit first, PA second approach, and focusing on the four primary profit drivers clearly illustrates the role PA can play in improving profit. That is – identify the constraints and opportunities for profit on your farm, and then consider if PA has a role in addressing them. Note though, that PA can negatively impact on profitability if poorly implemented, through increasing the business cost base, or delaying rather than improving timeliness of operations.
There are three broad pathways to profit from PA. It is recommended that growers first consider the opportunities for their business at the strategic level, as these are likely to have the greatest economic benefit. Tactical applications of PA can have merit, but generally enable smaller gains than the strategic pathway. There are also paddock situations where a reactive approach to PA can be useful to solve a problem that emerges suddenly, or in response to a seasonal challenge.
This report covers the range of applications and a very broad brush of their potential best fit throughout the region. There were few economic studies that could be applied broadly to the breadth of farm businesses across the region particularly given the high degree of variability between businesses even in the same subregion. Therefore, investment decisions in precision agriculture are best preceded by a thorough business case which includes a fully costed partial budget analysis at a minimum. This project will provide guidelines for such analyses in later publications.
This project will also be collecting some economic data on five specific PA applications as part of future outputs. This will go some way to addressing this economic data gap. The authors would also welcome contact from anyone with information that hasn’t been captured in this report but would be useful economic data for the project and industry.
CONCLUSIONS
TOOL BOx 1 – GLOSSARY 35
Derived from Whelan and Taylor (2010) and Leonard et al (2017).
GLOSSARY
TERM DESCRIPTION
AgTech Popular term in the investment community to describe the digital technologies used in agriculture
Big data Computerised analytics systems that interrogate extremely large databases of information in order to identify particular trends and correlations
Coefficient of variation (CV)
A statistical measure of variability, involving the ratio of the standard deviation to the mean
Controlled traffic farming (CTF)
A farming system in which most or all wheeled traffic runs on a set of permanent tracks to restrict soil compaction
Decision agriculture Conclusion or action resulting from the application of knowledge and/or information that may be derived from digital agriculture
Digital agriculture Collection and analysis of data to improve both on and off-farm decision making leading to better business outcomes
EM38 A tool to measure electrical conductivity of water in the soil and the soil itself, which is influenced by the soil salt and water content, and the amount and type of clay in the soil. It can help to identify where important subsoil constraints may be present in paddocks and in assessing variation in the amount of soil water that can be available to plants
GNSS The standard generic term for satellite navigation systems that provide autonomous geo-spatial positioning with global coverage. GNSS allows small electronic receivers to determine their location (longitude, latitude, and altitude) using time signals transmitted along a line-of-sight by radio from satellites
Gamma radiometry The measurement of natural gamma ray emissions of radioactivity, primarily from the top 30 - 50cm of soil or rock. Often, this can provide information about the parent material of the soil that can be related to soil types across the region or paddock
Normalised difference vegetation index (NDVI)
A common method of analysing remotely sensed imagery for vegetation health, vigour and greenness. The index is created by subtracting the value of the red band of the imagery from that of the near infrared, and then dividing this by the sum of the red and near infrared bands. Red light is strongly absorbed for photosynthesis and near infrared light is strongly reflected in healthy plants, so a high index value relates to high health and greenness. The NDVI is the most commonly used vegetation index
Optical spot sprayer A spray system involving a sensor that detects the presence of a plant and automatically activates a valve to direct spray at the plant. Used in fallow situations
PAWC (plant available water capacity)
Proportion of soil water that is available to plants within rootzone
Precision Agriculture (PA)
Farming practices that involve precise spatial management using GPS technologies
Site specific crop management (SSCM)
A management system that considers the variability of crop and soil parameters to make decisions on the application of production inputs
Spatial variability The variation found in soil and crop parameters (e.g. soil pH, crop yield) across an area at a given time
Temporal variability The variation found in soil and crop parameters within a given area at different measurement times
TOOL BOx 1 – GLOSSARY
36 TOOL BOx 2 – PA TECHNICAL INFORMATION SOURCES
REPORTS AND REFERENCE MATERIAL
PA IN PRACTICE II www .grdc .com .au/PAinPractice2 A seasonal guide to PA applications
APPLYING PA – A REFERENCE GUIDE FOR THE MODERN PRACTITIONER
https://grdc .com .au/resources-and-publications/all-publications/bookshop/2013/11/applyingpa A practical guide to implementing PA
CALCULATING RETURN ON INVESTMENT FOR ON FARM TRIALS DIY PRECISION AGRICULTURE
https://grdc .com .au/__data/assets/pdf_file/0026/233945/diy-pa-calculating-roi-for-on-farm-trials .pdf .pdf
A guide to conducting on farm trials
UNIVERSITY OF SYDNEY PA MODULES
https://sydney .edu .au/agriculture/pal/publications_references/educational_resources .shtml
Technical reference material on the development and application of PA in the grains industry
TOOL BOx 2 – PA TECHNICAL INFORMATION SOURCES
TOOL BOx 3 – IS PA FOR ME? 37
Modified from GRDC RDP00013 2015
CHECKLIST FOR ASSESSING PA OPPORTUNITIES
1
Is there potential to improve water use efficiency and yield relative to climate limited potential via crop rotation, crop agronomy, and operational timeliness?
If yes, explore these first.
2How long has the PA product or application been around? Has it been robustly tested in a commercial environment?
More established PA products tend to be cheaper with greater capability.
3
Will the technology influence long term average crop yield?
Technologies which unlock yield potential and result in yield increases, with only a small to moderate increase in cost can deliver substantial net economic benefit.
4
Is the PA technology the most cost effective mechanism to achieve the outcome that I am striving for?
Sometimes there are other ways to achieve the same outcome. Select the simplest and most cost effective option to achieve a desired outcome wherever possible.
5
Have I undertaken a robust economic assessment of the opportunity to apply the technology? Did this analysis demonstrates a positive net benefit?
The range in net economic benefits can be substantial and is often very sensitive to the cost of purchasing the technology and the robustness of the assumptions made.
6
Do I understand how the benefit will be influenced by climatic variability between seasons? Do my assumptions accurately reflect the likely benefit or cost saving by taking a long term perspective which captures the influence of seasonal variability?
Some technologies have very different payoffs under different seasonal conditions. It is important that this difference is understood and captured in an economic analysis. Tools such as CliMate can be used to add rigour to assumptions around seasonality and the way in which it may influence the benefit.
7
Do I understand how my level of business scale influences the commercial feasibility of applying this technology?
A technology which is commercially feasible for one business may not pass the commercial feasibility test for a smaller scale business.
8
Have I used long term, decile 5 pricing rather than spot pricing when calculating the net economic benefit or a range of price scenarios?
Spot pricing can substantially influence the value of the possible benefit or cost saving and as a result can be misleading. This is particularly so when spot pricing is substantially different from the longer term average. This principle applies to both input cost prices and grain prices.
9
Can I access the skill set and capacity to manage the data capture and interpretation required for this PA application?
Most forms of PA require additional data capture, analysis, and preparation to realise the benefit. The impact on labour demand is also important when assessing the application of a PA technology.
10
Have I completed the economic assessment on the application of this technology without bias?
Personal bias can easily influence an economic assessment. Ensuring that the analysis is undertaken without bias results in more robust assessments.
TOOL BOx 3 – IS PA FOR ME?
38 REFERENCES AND FURTHER READING
Armstrong RD, Eagle C, Mattas V, Jarwal SD, (2007) Application of composted pig bedding on a vertosol and sodosol soil 1. Effect on crop growth and soil water. Australian Journal of experimental agriculture 47 689-699
Armstrong RD, Eagle C, Flood R, (2015) Improving grain yields on a sodic clay soil in a temperate medium rainfall cropping environment Crop and Pasture Science 66 492-505
Blackwell P, Hagan J, Davies S, Riethmuller G, Bakker D, Hall D, Knight Q, Lemon J, Yokwe S & Isbister B (2013) Pathways to more grain farming profit by CTF in WA https://grdc.com.au/resources-and-publications/grdc-update-papers/tab-content/grdc-update-papers/2013/04/pathways-to-more-grain-farming-profit-by-ctf-in-wa
Barends E, Rousseau DM, Briner RB (2014) Evidence-Based Management, The Basic Principles, Amsterdam, Center for Evidence-Based Management, Amsterdam.
Celestina C, Midwood J, Sherriff S, Trengove S, Hunt J, Tang C, Sale P and Franks A (2018) Crop yield responses to surface and subsoil applications of poultry litter and inorganic fertiliser in south-eastern Australia Crop and Pasture Science 69(3):303-316. 2018
Condon G and K (2016) Controlled traffic farming the costs and the benefits https://grdc.com.au/resources-and-publications/grdc-update-papers/tab-content/grdc-update-papers/2016/02/controlled-traffic-farming-the-costs-and-benefits
GRDC (2009) How to put precision agriculture into practice. Precision Agriculture Factsheet Grains Research and Development Corporation, Canberra
GRDC RDP00013 (2016), Project Report for The integration of technical data and profit drivers for more informed decisions, authored by Rural Directions Pty Ltd, Macquarie Franklin, Meridian Agriculture, Agripath, and Corporate Agriculture Australia
GRDC RDP00013 (2015), Output 8 – Potential trade-offs between scale and precision use of inputs, authored by Rural Directions Pty Ltd, Macquarie Franklin, Meridian Agriculture, Agripath, and Corporate Agriculture Australia
GRDC (2017) Southern Regional Annual Report: Regional Cropping solutions network 2016-2017
GRDC (2006) Precision Agriculture Manual Part 1: Precision Agriculture Manual – http://www .grdc .com .au/Resources/Publications/2006/08/PA-Manual-2006
Hall D (2017) Economic analysis of the impacts and management of subsoil constraints report https://www.agric.wa.gov.au/managing-soils/economic-analysis-impacts-and-management-subsoil-constraints-report
Harding A, I’Anson K, Hughes B, Masters B, Herrmann T, (2018), Advancement of precision soil pH mapping in South Australia, 2018 SPAA symposium
Hochman Z, Gobbett D, Horan H, Garcia JN (2016). Data rich yield gap analysis of wheat in Australia. Field Crops Research 197, 97-106.1
Humpal J, McCarthy C, Thomassen JA, Percy C (2018). Machine vision learning for crop disease and quality parameters, 2018 SPAA Symposium
Inchbold A, Whelan B, Baines P (2009) Making Money out of Precision Agriculture Results from the Riverine Plains Inc project Improving Winter Cropping Systems in the Riverine Plains Project funded by GRDC In collaboration with ACPA https://riverineplains.org.au/wp-content/uploads/2015/05/RPI-Making-Money-out-of-Precision-Agriculture-2009.pdf
Kingwell R and Fuchsbichler A (2011) The whole farm benefits of controlled traffic farming: An Australian appraisal, Agricultural Systems, Volume 104 Issue 7
REFERENCES AND FURTHER READING
REFERENCES AND FURTHER READING 39
Lawes R, Chen C and Van Rees H (2018). The National Paddock Survey — what causes the yield gap across Australian paddocks? GRDC Update Perth WA February 2108 https://grdc .com .au/resources-and-publications/grdc-update-papers/tab-content/grdc-update-papers/2018/02/the-national-paddock-survey-what-causes-the-yield-gap-across-australian-paddocks
Lawes RA and Kingwell RS (2012) A longitudinal examination of business performance indicators for drought-affected farms Agricultural Systems 106 94-101
Lawes RA and Robertson MJ (2011) Whole farm implications on the application of variable rate technology to every field, Field Crops Research 124 142-148
Leonard E (Ed), Rainbow R (Ed), Trindall J (Ed), Baker I, Barry S, Darragh L, Darnell R, George A, Heath R, Jakku E, Laurie A, Lamb D, Llewellyn R, Perrett E, Sanderson J, Skinner A, Stollery T, Wiseman L, Wood G and Zhang A (2017). Accelerating precision agriculture to decision agriculture: Enabling digital agriculture in Australia. Cotton Research and Development Corporation, Australia.
Llewellyn RS and Ouzman J (2015) Adoption of precision agriculture related practices: status, opportunities and the role of farm advisers CSIRO www.csiro.au
McCallum MH (2008 ) Farmer Case studies on the Economics of PA Technologies, Society of Precision Agriculture Australia www.spaa.com.au
Miller L (2015) Making better liming decisions https://grdc .com .au/resources-and-publications/grdc-update-papers/tab-content/grdc-update-papers/2015/03/making-better-liming-decisions
Oliver YM, Robertson MJ, Wong MTF (2010) European Journal of Agronomy 32 (1) 40-50
Robertson M, Carberry P and Brennan L (2007) The economic benefits of precision agriculture: case studies from Australian grain farms, CSIRO for GRDC
Robertson M, Kirkegaard J, Rebetzke G, Llewellyn R and Wark T (2016). Prospects for yield improvement in the Australian wheat industry: a perspective Food and Energy Security 2016, 5(2):107–122
Sale P, Armstrong R, Wilhelm N, Davenport D, Tavvakoli E, Dean G, Desboiles J, O’Leary G, Malcom B, Celestina C (2016) Scoping Review for GRDC Project DAV00149 Understanding the amelioration processes of the subsoil application of amendments in the Southern Region.
Sauer B, Wells T, Wells M, Neale T, Smart A, D’Emden, F (2013) Applying PA. A reference guide for the modern practitioner. Grains Research and Development Corporation, Canberra
Society of Precision Agriculture Australia (2008) PA in Practice, grain growers experience of using variable rate and other PA technologies. www.spaa.com.au
Society of Precision Agriculture Australia (2011) PA in Practice 2 Society of Precision Agriculture Australia. www.spaa.com.au
Trengove S (2013), Potential for Site Specific Management of Lolium Rigidum (Annual Ryegrass) in Southern Australia, University of Adelaide
Trengove S (2016) – Users Guide for Site Specific Weed Management, SAGIT (unpublished)
Trengove S (2018) Where does PA fit in the Upper North?, presented at Upper North Farming Systems group August 2018
Umbers A (2017) GRDC Farm Practices Survey Report 2016. Grains Research and Development Corporation, Canberra
Whitlock A (2015) pH Mapping and Variable Rate Lime – 50,000 plus Hectares of Experience https://grdc .com .au/resources-and-publications/grdc-update-papers/tab-content/grdc-update-papers/2015/08/ph-mapping-and-variable-rate-lime-50000-plus-hectares-of-experience
40 REFERENCES AND FURTHER READING
Whitlock A (2018) Utilising-spatial-data-for-within-paddock-soil-and-crop-management https://grdc .com .au/resources-and-publications/grdc-update-papers/tab-content/grdc-update-papers/2018/03/utilising-spatial-data-for-within-paddock-soil-and-crop-management
Whitlock A and Torpey B (2017) Using precision agriculture technologies for drainage solutions https://grdc .com .au/resources-and-publications/grdc-update-papers/tab-content/grdc-update-papers/2017/02/using-precision-agriculture-technologies-for-drainage-solutions
Whelan B and Taylor J (2010) PA Education and Training Modules for the Grains Industry. for the Australian Centre for Precision Agriculture, University of Sydney Grains Research and Development Corporation
Wong MTF, Asseng S, and Zhang H (2006), A flexible approach to managing variability in grain yield and nitrate leaching at within-field to farm scales Precision Agriculture Volume 7, Issue 6, pp 405–417 |
Wong MTF and Harper RJ (1999) Use of on-ground gamma-ray spectrometry to measure plant-available potassium and other topsoil attributes Soil Research, 37 (2) 267-278
grdc.com.au
