Insights from the Grain and Graze program
Insights from the Grain and Graze program
Author: Cam Nicholson (Nicon Rural Services, Geelong) | Date: 21 Feb 2017
Take home message
- The feed sources in a mixed farming operation (pasture, winter crops, stubble, summer fodder) are more variable than pasture and greater skill is required to match feed supply with animal demand.
- The pasture component in a crop rotation can be used successfully to control weeds, build nitrogen (N) and improve soil conditions, but there are pitfalls.
- Mixed farming reduces downside risk compared to straight cropping, but usually lowers the chances of making very big profits.
- Integration and diversity created by mixed farming produce a level of complexity that requires sophisticated decision making, including an understanding of the social dynamics.
Background
Livestock numbers on farms in the traditional mixed farming areas of Australia have been in decline since the 1990s, although in the past few years, these numbers have stabilised and are now on the increase (Bell et al. 2014). The reasons for the fall are a combination of commodity prices, the adoption of full stubble retention, operator frustration with the competition for time and resources between crop and livestock and the rapid technological advances in cropping compared to the animal system. However, with major improvements in livestock and wool prices, a questioning of the ‘no till means no livestock’ philosophy, the emerging challenges with weeds and organic matter decline and the desire by growers to increase on-farm diversity to manage risk, mean there is renewed interest in re-introducing or expanding livestock on grain farms.
Unfortunately, decades of giving livestock the ‘poor cousin’ status has meant infrastructure has degraded or been removed and skills lost with generational change. New knowledge created in the livestock industry in the past 20 years is unfamiliar to many growers and advisers. A 2013 survey of 93 farm advisers indicated their confidence to advise clients on the use of the whole farm feedbase and adjusting stocking rates was only 6.8 out of 10, much lower than their confidence with other practices such as stubble management, crop rotations and integrated weed management (Roberts, 2013).
The Grain and Graze program has been operating during this declining and now emerging resurgence in livestock, running from 2003 to 2016 across large parts of the mixed farming zones of Australia. The program started through a collaboration of the GRDC, Meat and Livestock Australia, Australian Wool Innovation and the now defunct Land and Water Australia. The second phase from 2009 to 2013 involved the GRDC in partnership with the Department of Agriculture and the final smaller extension phase only involved the GRDC (2014 to 2016).
This paper attempts to summarise the take home messages from two of the key study areas from the Southern Region of the Grain and Graze mixed farming program. These areas are (i) growing and utilising various feed sources — the feedbase, and (ii) managing a mixed farming system — the social dynamic. It is not a complete summary of the work undertaken in Grain and Graze and readers are encouraged to visit the Grain and Graze website for more information (Grain and Graze website).
Managing feed sources
A lot is known about what animals need to reach certain levels of performance and the consequences if these benchmarks are not reached. Matching the right quantity and quality of feed to animal demand is an ongoing challenge even for single enterprise livestock graziers. In a mixed farming operation, there are different sources of varying quality and quantity feed at different times of the year (Figure 1). Making best use of these different sources can be challenging because of the variability of feed quantity and quality.
Figure 1. Likely availability of different feed sources during the year (lighter grey represents less reliability).
Considerable work was undertaken in the Grain and Graze program to appreciate the opportunities presented by these additional feed sources and how they can be utilised while minimising any downside impacts.
Winter crops
A major focus has been on grazing winter crops and is summarised in the Grazing Cropped Land booklet (Nicholson et al. 2016). Most work has been on cereals, especially wheat and barley.
Information was collected on the dry matter production (Figure 2) at different times of sowing and the herbage quality (Figure 3).
Figure 2. Range in dry matter (kg/ha) for wheat and barley trials at different sowing times for low rainfall (left, n=48) and high rainfall (right, n=149) environments across Southern and Western Australia. Dot represents the average, box the 25% to 75% range and the ends of the tails the extremes.
Figure 3. Range in metabolisable energy (left) and protein (right) for wheat and barley trials at different growth stages (n=125). Error bar is one standard deviation.
A common fear of growers and agronomists is the impact grazing may have on grain yield (Creelman et al. 2015). Measurements comparing grain yields with and without defoliation up to growth stage 30 (GS30) over a 10 year period showed both decreases and increases in grain production (Figure 4). These results were from multiple varieties, grazing regimes and sowing dates. More than half resulted in difference in grain yield from grazing of between -250kg/ha and +250kg/ha.
Figure 4. Change in cereal grain yield (kg/ha) due to grazing for wheat, barley, oats and triticale (n=187).
Multiple factors are believed to contribute to the range in responses including variety selection, crop growth stage and residual biomass left at the end of grazing, length of time between grazing and anthesis and post grazing conditions (moisture and heat). Key guidelines to emerge for grazing winter crops to minimise yield loss are presented (Table 1).
Recommendation | Reasoning |
|---|---|
Sow winter varieties early (March-April), on opportunistic soil moisture. | Earlier sowing increases likely dry matter production, providing the opportunity for earlier grazing and longer periods of biomass recovery. |
Graze earlier (June-July) rather than later. | The time and environmental conditions between the end of grazing and anthesis have a major influence on grain yield. The longer this recovery period the better. |
‘Clip graze’ in lower rainfall or moisture stress years. | Retaining some leaf area reduces the amount of new biomass that needs to be regrown after grazing but before anthesis. |
Complete grazing before GS30. | Grazing after GS30 may remove elongating grain ears. |
Match variety to the growing environment. | Grazing will also delay maturity and with long season varieties may expose ripening crops to heat and moisture stress. |
Other important findings from the grazing winter crop work include:
- Canola established at a ‘traditional’ late autumn sowing time and then grazed in winter commonly incurred significant yield losses compared to ungrazed canola. Early autumn, summer or even spring sowing appears to provide a more suitable dual purpose canola grazing opportunity.
- Stubble will be reduced after grazing, even when defoliated at the early vegetative growth stage.
- Grazing resulted in visual changes to the soil surface, but no changes to subsequent water infiltration, soil water storage or crop yields. Grazed soils had a remarkable ability to ‘repair’ themselves.
- Grazing does not necessarily increase weeds, however, weed free paddocks are the safest to graze. Experiments showed weeds increased, stayed the same or decreased as a result of grazing, but there was no consistent reason for the change.
Crop stubbles
Winter crop stubbles can provide a valuable source of feed, primarily from residual grain and green shoots from shot grain and weeds. Standing straw and trash have much lower quality (energy and protein) which are below maintenance requirements for all classes of livestock. Therefore, animal weight gain is directly linked to the amount of grain and green material in the stubble (assuming no supplementary feeding).
Improved efficiency of harvest machinery means not all crop paddocks have grazing value and only those with sufficient high energy material should be grazed, otherwise sowing and herbicide efficacy problems can be created with livestock lying over standing straw. Experiments indicate there needs to be at least 40kg/ha of residual grain or 40kg/ha of green material for a sheep to maintain or gain weight (although the gain is difficult to predict). Below these values, animals lose weight, irrespective of how much straw or leaf trash remains.
A simple guide to help assess the amount of grain in a stubble is presented (Table 2) along with photos of different levels of green materials (Figure 5).
Number of cereal grains/0.1m2 and approx. quantity of grain/ha | Number of cereal green shoots/0.1m2 and approx. quantity of green/ha as dry matter | ||
|---|---|---|---|
Grains counted (number/0.1 m2) | Equivalent quantity of grain (kg/ha) | Green shoots counted (number / 0.1m2) | Equivalent quantity of DM (kg/ha) |
6 | 20 | 7 | 20 |
13 | 40 | 14 | 40 |
20 | 60 | 21 | 60 |
26 | 80 | 28 | 80 |
The equivalent of 40kg/ha for crop legumes is approximately four grain per quadrat for lupins, two for field peas and chickpeas and one for faba beans.
Figure 5. Indication of green shoot material available for grazing.
Other critical points when grazing stubble:
- Grazing should be conducted to retain between 50% and 70% groundcover so as to avoid wind erosion or decrease water infiltration.
- In medium and low rainfall areas, removing green material in stubbles is recommended to conserve soil moisture, therefore only the residual grain should be considered as having grazing value.
Winter fodders
Unlike a grazier, winter pastures in a cropping rotation are commonly grown for reasons other than just feed. Most commonly fodder is used to assist in weed control before the next cropping phase, to add biological nitrogen (N) and to improve overall soil condition. Maximising fodder production for livestock is therefore only one of a number of possible objectives. When these objectives are combined with a grower’s affinity towards and access to livestock, the fodder phase length they want, preparedness to resow each year and the potential ‘weed’ problem created in the subsequent crop, it creates a massive number of possible winter pasture options. There is no single ‘right’ answer.
The most suitable option for a grower will need to be formulated on a case by case basis, taking into account the relative importance of multiple objectives and other considerations as previously described. To assist with these considerations, the advantages and disadvantages for different legume and grass winter pastures tested in the Grain and Graze program are presented (Tables 3 and 4).
Other key observations worth highlighting:
- There was a very large variability in overall fodder production from year to year. While annual production differences were anticipated because of seasons, the range was 0.5 to 12t/ha. In general, grass fodder grew more dry matter of similar quality than legumes grown at the same time.
- Annual ryegrass can be dramatically reduced (to <10%) after two years of a pasture phase if seed set can be prevented. However, it is essential to control late germinating annual ryegrass (October-November) that grows when applied herbicides are no longer effective. In contrast, wild radish remains problematic, with no reduction in plant numbers recorded after many years of a fodder phase.
- Growing fodder legumes does not guarantee an accumulation of soil N and where accumulation does occur, it may be lower than the common rules of thumb of approx. 20kg of shoot N/t dry matter (Peoples et al. 2013). Measurements of total soil N accumulation under legumes ranged from 0 to 150kg/ha. There are multiple reasons why sub-optimal fixation may occur (legume species, rhizobia efficiency, residual soil N), but one suggestion is the residual effect of common cropping herbicides, especially group B (Martin Barbetti, pers comm Nov 2016).
- Lucerne was the least beneficial fodder break crop in the 500mm+ rainfall areas because overall dry matter production was less than other fodder legumes. It captured most soil N so the next crop started from very low N levels and the release of organic N was much slower compared to other legumes (peaked about year 3). In addition, lucerne dried the soil profile more than other legumes, which resulted in a greater soil moisture deficit if winter rainfall after removal was below average.
- Crops sown in years after a legume break that receive below average growing season rainfall can be oversupplied by the mineralised soil N, leading to higher grain screenings.
Attributes | Annual fodder legumes (arrowleaf, Persian, balansa, sub clover, medic) | Annual pulses (peas, beans) | Perennial legumes (lucerne) | |||
|---|---|---|---|---|---|---|
Advantages | Disadvantages | Advantages | Disadvantages | Advantages | Disadvantages | |
Feed quantity | Generally grows less dry matter than grasses | Generally grows more dry matter than fodder legumes | Out of season growth if summer rainfall occurs | Slow to establish and reach maximum production (usually year 2) | ||
Sub clover may grow less in first year while building the seed bank | Quick to establish and achieve ground cover | Annual production less than most other species | ||||
Winter growth may be slow especially if not sown early | ||||||
Feed quality for grazing | High quality feed when vegetative, usually better than grasses but not cereals or canola | Out of season high quality feed if rainfall occurs | Grazing lush lucerne can create digestive issues such as bloat, red gut | |||
Grazing | Provides in-season grazing | Cannot be grazed in the vegetative stage | Can provide out of season grazing if rainfall occurs | |||
Seeding | Can sow same species year on year | May need to be re-sown each year — depending on species or if seed set is compromised by weed seed set control | Unable to sow same crop year on year | Only sown once | ||
Carryover seed/removal | May create a ‘weed’ problem when in the next cropping phase. | Unlikely to cause a ‘weed’ issue in subsequent crops | No carryover seed | Established lucerne can be hard to kill | ||
Disease break | Provides an effective grass disease break | Provides an effective grass disease break | Builds pulse disease population | Provides an effective grass disease break | ||
Nitrogen | Provides N but amount depends on effective nodulation | Unable to control mineralised N release | Provides N but amount depends on effective nodulation | Unable to control mineralised N release | Provides N but amount depends on effective nodulation | Very effective at scavenging any residual soil N |
Provides rapid mineralisation from dry matter | Provides rapid mineralisation from dry matter | Release of N over many (3+) years | No rapid release of N because of large tough roots that have to break down. Sub optimal soil N may occur in the first year after removal | |||
Herbicides | Provides some alternative pre and post emergent herbicide options | Some herbicides may affect N fixation | Provides some alternative pre and post emergent herbicide options | Some herbicides may affect N fixation | Provides some alternative pre and post emergent herbicide options | Some herbicides may affect N fixation |
Green manure | Can be green or brown manured effectively | Can be green or brown manured effectively | Difficult to manure | |||
Fodder conservation | Higher quality fodder, usually of better quality than grasses or cereals | Limited fodder conservation options | Good quality fodder | |||
Post spring grazing | Nutritious carryover feed | Grazing can result in reduced ground cover | Nutritious carryover feed | Grazing can result in reduced ground cover | Retains quality late into the season. Possible if rainfall occurs out of season | |
Soil moisture | Dries soil profile similar to cereal crop | Dries soil profile similar to cereal crop | Dries soil profile more aggressively than other fodders, so may compromise soil moisture in a below average season | |||
Attributes | Annual grasses (annual ryegrass, oats, barley, wheat) | Perennial grasses (perennial ryegrass, phalaris) | ||
|---|---|---|---|---|
Advantages | Disadvantages | Advantages | Disadvantages | |
Feed quantity | Generally greater dry matter than legumes | Out of season feed if there is summer rainfall | Slower to establish in first year with maximum production in years 2+ | |
Rapid early season dry matter (more than legumes) | Annual production similar to other species | |||
Rapid recovery after grazing | ||||
Feed quality | High quality feed when vegetative | Feed quality declines rapidly when plants become reproductive | Will provide some high quality green pick with out of season rainfall | Good quality feed when vegetative but usually less than other species |
Grazing | Provides early in season grazing | Provides whole season grazing | ||
Seeding | Need to be re-sown each year | Only sown once | ||
Carryover seed/removal | Any carryover seed likely to germinate early next season so easy to control | Any carryover seed likely to germinate early next season so easy to control | ||
Disease break | Provides a host to grass specific diseases | |||
Nitrogen | No N | No N | ||
Herbicides | Limited alternative pre and post emergent herbicides | Limited alternative pre and post emergent herbicides for other grasses | ||
Green manure | Can be manured | Difficult to manure | ||
Fodder conservation | Good quality fodder but usually poorer quality than legumes | Good quality fodder but usually poorer quality than legumes | ||
Post spring grazing | Limited carryover feed | Retains quality late into the season. Possible if rainfall occurs out of season | ||
Soil moisture | Dries soil profile similar to legume crop or typical crop rotation | Dries soil profile more than a legume crop or typical crop rotation but less than lucerne | ||
Summer fodders
Summer fodder crops have lost favour with many advisers and growers. The findings that retained soil moisture on fallows increases water use efficiency and that the gains in grain yield outweighed keeping the weeds for summer stock feed (Hunt, 2013) meant there was no incentive to include a summer water using plant. This thinking was widely adopted across Southern Australia, including the high rainfall zone (HRZ). However, work from Grain and Graze showed the need to conserve soil moisture was not applicable in areas of higher winter rainfall. In these areas, the soil type results in high evaporative losses of soil moisture over summer through capillary rise, even without any plants actively growing and with reasonable amounts of retained stubble (approx. 4t/ha). In addition, the limited water holding capacity of most soils in the HRZ, combined with the high probability of winter rainfall exceeding the soil water holding capacity, meant stored summer rainfall was on limited value to the next winter crop and in some cases led to more rapid waterlogging the next winter (Creelman, 2016).
Eight trials in the HRZ clearly illustrated there was no impact of growing a summer fodder for grazing on the subsequent winter crop, although grazing did significantly reduce the available soil N at the time the winter crop was sown (Nicholson, 2015a).
These insights, combined with the release of canola with a strong vernalisation requirement, enabled out of season sowing of a brassica to be used for grazing over summer, followed by locking up the grazed plants to take through as a traditional winter crop for harvest. The quality of the canola dry matter was comparable to other fodder brassicas, with dry matter typically between 0.5t/ha and 4t/ha depending on summer rainfall. Subsequent grain yields compared to conventional sowing of canola in late autumn have proved equal if not better (GRDC, 2016). Significantly earlier sowing of wheat with strong vernalisation requirements is also being tried.
The long term disease, N and weed implications still need to be understood, however the approach provides an exciting way to change the thinking of utilising a dual purpose crop.
Managing a mixed farming system
Bell and Moore (2012) identified seven logical reasons why growers chose to operate both cropping and livestock.
These were:
- Risk mitigation (cropping and livestock income is not directly correlated).
- Exploiting spatial variability (land capability variation).
- Efficient resource allocation (labour, land, machinery, capital).
- Management focus (where skills and expertise lie).
- Management agility (ability to make tactical changes in season between enterprises).
- Production complementarities (reduced input costs or increased efficiencies), and
- Resource maintenance (soil fertility and stability, etc.).
Growers intuitively understand these reasons. However, growers make decisions based on more than just logical reasons. The Grain and Graze program invested considerable resources in understanding the ‘social dynamic’ and decision making issues that challenge or reinforce the logic of mixed farming. Some of these insights are discussed.
Complexity in mixed farming
Diversification and increasing integration between enterprises in a mixed farming system increase complexity. As more elements are added to the farming business, identifying the variables, interactions and trade-offs becomes more difficult. Informed decisions require more brain power and organisation, more technical knowledge and skills and even then it is hard to consider all possible elements. In addition, the decisions are also influenced by a range of social objectives and constraints such as business goals, personal preference and values that go beyond the biophysical considerations and calculations (RMCG 2006). The Grain and Graze program describes the logical and social dynamic as the head, heart and gut influences on decision making (Nicholson et al. 2015).
Some suggested tactics advisers can employ to help growers work through the complexity inherent in a mixed farming system are presented (Table 5).
Suggestion | Reasoning |
|---|---|
Find out their past experiences with an issue | Most growers learn by building on past experiences (that is why many appear conservative to new ideas). Unless you appreciate these experiences (good or bad), it is difficult to know how to frame any proposal or recommendation. |
Ask what they like and dislike about a proposal you present | Suggestions that do not align with a grower’s goals, values and beliefs will be rejected. This can only be found out by asking. Questions about the likes and dislikes of something tangible (your recommendations) is a good way to surface the ‘heart’ issues. |
Trust a grower’s intuition | Intuition or ‘gut feel’ is used to fill the knowledge gaps in complex decisions. We do not always have the facts but following your gut is a sound way to go in the absence of data. |
Encourage them to ‘tell stories’ | Talking things through often helps people ‘make sense’ of a situation and leads to insights about the ‘soft’ issues that are influencing a decision. |
Value failures | It is said we often learn more from our failures than our successes. Most extension material and case studies focus on the success with inspiring stories, however the mistakes and poor results can often be more insightful. |
Linked to the head, heart and gut influences is grower temperament. Temperament is the combination of the mental, physical and emotional traits of a person that influences what they do. It shapes how they learn and communicate, make decisions and address risk. Ground breaking work on the temperament type of growers (Strachan, 2011) showed most growers do not immediately recognise patterns and synergies in complex systems, so may struggle with integrating crops and livestock fully.
The ability of an adviser to identify a client’s temperament and then tailor messages to suit the individual is an extremely valuable skill. Information on the different temperament types, how to pick this in a client and then how the messages should be adapted is discussed in another paper at this update (Picking clients’ temperament and modifying your message accordingly to improve uptake) and also in other resources (Nicholson and Long, 2015).
Complex decision making
Just because we make decisions all the time does not mean we are good at making them. Decision making is a skill, underpinned by knowledge and awareness of inherent biases and emotion that individuals carry (Long, 2012). Being a skill, it also implies that there are steps or processes that can be followed to guide a complex decision in a logical way. This means decision making can be learnt, practised and refined.
The farm decision making booklet (Nicholson et al. 2015) provides many suggestions on ways to improve decision making. An example of one simple decision making process, in this case to decide whether to graze a winter crop or not, is provided (Table 6).
Critical factors | Conditions | Points | Maximum | My score |
|---|---|---|---|---|
Crop establishment date | Before April 15 | 3 | 3 | 2 |
April 15-May 15 | 2 | |||
After May 15 | 1 | |||
Plant not well anchored (pull out) | No plant loss | 3 | 3 | 3 |
10% plant loss | 2 | |||
> 10% plant loss | 0 | |||
When grazing has been completed | Before GS30 | 3 | 3 | 3 |
At GS30-GS32 | 2 | |||
> GS32 | 0 | |||
Residual dry matter after grazing | 'Clip' graze | 3 | 3 | 2 |
50% biomass removed | 2 | |||
None, grazed to white line | 1 | |||
Soil moisture at grazing | Full profile | 4 | 4 | 2 |
1/2 profile | 2 | |||
<25% profile | 0 | |||
Time to recover biomass before flowering | Sufficient time | 4 | 4 | 2 |
Borderline | 2 | |||
Insufficient time | 0 | |||
Agronomic conditions | No constraints | 3 | 3 | 3 |
Minor constraints | 2 | |||
Major constraints | 1 | |||
Next 3-month forecast | Above average | 4 | 4 | 2 |
Average | 2 | |||
Below average | 0 | |||
27 | 17 | |||
Decision | ||||
> 21 | Definitely graze crop (minimal or no expected loss of grain yield) | |||
21 to 15 | Will only graze crop if the livestock benefits are greater than anticipated crop losses | |||
< 15 | Will not graze the crop (significant expected loss of grain yield) | |||
In this example, where the crop is sown on 1 May, is well anchored at grazing, is 50% grazed before GS30, but is limited in soil moisture and recovery time after grazing because of variety choice and forecast, it scores only 17 out of 27. It would be recommended grazing only occurs if the livestock benefits will outweigh the potential yield loss.
This framework could be applied to any decision that has multiple elements. The critical factors, conditions, points and scoring decision can be adjusted to suit each individual.
Difficulty in quantifying the benefits
It is relatively simple to quantify the costs and returns from a single cropping enterprise and/or a livestock enterprise, however quantifying what is gained from diversification and integration is harder. Simple analysis is not appropriate and is misleading, but many of us persist with doing so because it is easy (and supports our bias).
Consider grazing crops as an example. Measuring the potential downside is relatively easy, namely a reduction in grain yield compared to ungrazed, however measuring the benefits is more difficult because of the requirement to determine the sometimes subtle gains to the farming operation from grazing, such as increased feed on offer because pastures are spelled, reduced supplementary feeding, increased lamb weight at birth and slightly higher ewe condition leading to higher milk production (Creelman, pers comm). The entwined factors are often long term and do not give a rapid result. For this reason, benefits are generally intuitive. Be prepared to ask and trust the intuitive benefits identified by the grower and value these on the positive side of the ledger.
Quantifying the risks
One of the main reasons growers run mixed farming operations is to manage risk. Australian growers operate in an environment which is many times more variable than that of their competitors in the developed world (Keogh, 2013). Given this variability, it is surprising few growers undertake analytical risk analysis before making a decision. Instead, and partly because the majority of information published and the decision support tools available make no representation of volatility or probability, growers default to their experience to inform the riskiness of an option (Nicholson, 2013). They know prices, yields and some costs can be highly variable, but also know that some commodities and production systems are more variable than others. In most circumstances, sheep will grow wool even in a poor season and there will be some value in livestock even in poor condition. However, a crop may fail completely.
Analysis of more than 40 mixed farming businesses conducted through the Grain and Graze program and detailed price analysis led to the following conclusions:
- Livestock are generally less risky than cropping. They reduce the possibility of making large losses, however, having livestock also reduces the chances of making large gains. There is this risk return trade off. Businesses that choose to remove livestock are generally running a higher risk but potentially, higher reward business.
- Most major crops (wheat, barley, canola) are strongly correlated with each other (R>0.75) but not with livestock (if anything are weakly negatively correlated). This means low grain prices do not necessarily mean low livestock prices.
- Major animal products (sheepmeat, beef, wool) are very weakly correlated (R<0.3), which means there is price diversification within livestock types.
- Everyone has a preferred risk position that can change over time. The right level of risk for one business might be different for the next and will change over time so be prepared to recalculate the level of risk.
Price correlations between any two commodities can easily be generated using the Grain and Graze Agprice guide (Grain and Graze Agprice website).
Undertaking risk analysis simply involves understanding the possible range in values encountered and how often they may occur. It requires framing the odds of different results occurring.
A few tricks picked up in the Grain and Graze program when including risk in decisions:
- Identify the big risky variables. A risky variable is one you cannot predict the value at the start of the season. The big risky variables found are crop yields, prices, lambing percentage and supplementary feeding. Other risky variables such as wool cut and fertiliser price are small by comparison and just average values can be used.
- Frame the odds around each risky variable. This can be as simple as determining that a worst one year in five yield might be 1t/ha, the best one year in five yield is expected to be 6t/ha and the mid-point approx. 4t/ha. Use these three values in scenario calculations.
- Use known correlations to reduce the number of calculations. For example, if using a worst one year in five price for wheat, use a worst one year in five price for barley, because we know the two prices are correlated.
- Historic information can be a valuable source on which to base future odds. The three most valuable and easy to access sources of historic information are:
- Climate data, especially deciles (BOM website).
- Commodity prices, adjusted for inflation (Grain and Graze Agprice website)
- Historic client data from private advisers.
A wealth of historic data has also been found in the form of grower experience that is commonly ignored by advisers, agencies and the wider industry when framing the odds to analyse risk. Do not underestimate this source as our experience has been that it is remarkably accurate and importantly creates grower ownership in the result because it is their information that has been used.
The Grain and Graze program has developed two approaches that draw together the aspects of risk and decision making:
- Grower friendly risk analysis, using Excel based Monte Carlo simulation in combination to create whole farm profit distributions (Nicholson, 2015b). Using a short face-to-face interview, the growers identified the risky variables in their business and framed the odds largely using past experience and historic farm data. This proved to be a very useful way of quantifying profit risk and led to many valuable discussions.
- The crop decision game. This requires the user to respond to random rainfall, pest, disease and frost events on a monthly basis, by choosing the level of inputs such as soil testing, using Yield Prophet®, fertiliser, weed, pest and disease application. Choices are usually do nothing, low, medium or high cost, with the associated degrees of efficacy. Each choice has a cost that accumulates across the year to give a gross margin and whole farm profit.
Both tools are available by contacting the author.
Thinking outside the square — future mixed farming
The potential success of integrating livestock into a farming business will be limited if an ‘old world’ view of the role of livestock is applied. Livestock can be highly profitable if best practice is applied to their feeding, genetics and health. Different ownership and agistment models provide pathways for growers not wanting to own ‘the traditional flock of breeders’, but to still have livestock in their system (Grain and Graze, 2016). The sharing of infrastructure is being adopted by some innovative growers and virtual fencing, which for years has been the Holy Grail, is rapidly approaching commercialisation. The mandatory use of national livestock identification tags in some states will drive innovation and lead to the adoption of some exciting technology to rival the advances in the cropping industry.
Conclusion
A lot has been learnt in the Grain and Graze program about the feedbase opportunities arising from running livestock in a cropping operation. There are many potential benefits, but to realise these will require changes to the way we think about livestock (class of animals, ownership models, essential infrastructure) and the cropping operation (what and when to sow, when to graze and how to include fodders in a rotation). These are complex decisions.
The complexity means decisions are influenced not only by technical information but also intuition, experience and personal values. Advisers will need to build their skills around the ‘social dynamic’ associated with this complexity decision making. This includes appreciating and talking about the risks in various actions, adequately and fairly analysing the benefits and costs of a decision and understanding the temperament of their clients so information and discussion can be tailored to suit each personality. Learning decision making frameworks will be essential.
Useful resources
Grain and Graze website (an archive of all publications, tools and resources from the program since 2003).
References
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Acknowledgements
The research undertaken as part of this project is made possible by the significant contributions of growers through both trial cooperation and the support of the GRDC — the author would like to thank them for their continued support. The findings in this paper are the result of many years of research and investigation by many people involved in the Grain and Graze program from 2003 to 2013. There are too many people to mention. However, the program would not have been possible without the significant and ongoing contributions of growers through the long term support of the GRDC.
Contact details
Cam Nicholson
Nicon Rural Services
32 Stevens Street, Queenscliff Vic 3225
03 5258 3860
03 5258 1235
cam@niconrural.com.au
GRDC Project Code: SFS00028,