Pty Limited ABN area of. Mark Harris Chris Minehan (02)

Transcription

1 RURAL MANAGEMENT STRATEGIES Pty Limited ABN AGRICULTURAL CONSULTANTS Southern Agribusiness Trial Extension Network GRDC Project Improving Nitrogen application decisions in cropping systems using Yield Prophet andd Plant Available Water Capacity mapping in the Barmedman area of southern NSW. Mark Harris Chris Minehan Rural Management Strategies Pty Limited Wagga Wagga, NSW (02) Report Date: February 2014

2 Executive Summary A paddock scale trial using farmer equipment was undertaken at Barmedman during the 2013 winter cropping season to demonstrate the use of Yield Prophet and plant available water capacity mapping to improve Nitrogen decision making in wheat. No effect of added Nitrogen was observed at the site in Managing Nitrogen using Yield Prophet and PAWC mapping added extra cost compared to the standard and Nil Urea treatments, however this method identified opportunities for cost saving through a better understanding of current Nitrogen and soil water. A decision making framework incorporating historical site performance was proposed as a method of further improving the Nitrogen decision making process. Questions arising from this information include: Does Zone management of Nitrogen improve profitability and reduce risk in both high yielding and low yielding situations? What are the implications in the following season to variable rate (VR) Nitrogen management? What is the effect of carryover Nitrogen? Can the same process be used for VR Nitrogen management in canola? Can the cost, time and effort of managing Nitrogen this way be reduced by extrapolating soil characterisation information across a landscape on similar soil types? Additional research is required to answer these questions.

3 1.0 Introduction Accurate and targeted allocation of resources is essential in modern farming systems. Nitrogen allocation has become the most costly and stressful decision that producers in continuous cropping systems face each year. Nitrogen fertiliser is often the largest single variable cost, commonly accounting for 30% of the variable cost of growing wheat and canola. Nitrogen decisions are made early in the growing season when yield outcomes are uncertain. Under-allocation of Nitrogen reduces yield and grain quality, while over-allocation adds unnecessary cost and can exacerbate moisture stress through excess vegetative growth. In paddocks with variable soil type and plant available water capacity (PAWC), the negative outcomes associated with under or over allocation can occur simultaneously. In most situations, Nitrogen application is reliant on rainfall for plant uptake, increasing risk, uncertainty and stress when rain is not assured. Decision support tools such as Yield Prophet have potential to improve the accuracy of Nitrogen allocation decisions by better matching Nitrogen to crop requirement based on predicted yield outcomes derived from local soil and weather information. Despite being available to producers and advisors for many years, the use of Yield Prophet has been limited due to perceived inaccuracies. An increasing number of producers have access to yield monitoring and mapping technology as well as the ability to apply variable rates of Nitrogen. To date, very few have been able to utilise this technology to improve decision making or management. The primary limitations have been deciding on which basis to differentiate between areas of the paddock and knowing how to manage those areas differently to increase productivity or reduce risk. This project aimed to demonstrate how Yield Prophet can be used to make Nitrogen decisions using accurate and targeted soil PAWC information for each soil type in a paddock. In southern NSW farming systems, soil PAWC is a major limitation to yield where nutrition, disease and weed competition are managed. EM38 surveys have been suggested as a method for creating soil PAWC maps of paddocks or farms and indeed, many producers have EM38 survey maps already. Mapping soil with an EM38 survey may determine the PAWC zone boundaries within the paddock. Soil characterisations obtained within each zone improve the fit of the Yield Prophet model to the soil type, allowing for more accurate decisions to be made. Rather than blanket applications of nitrogen which over-allocate some areas and under-allocate others, Yield Prophet should enable producers to more confidently match Nitrogen allocation to crop requirement. Nitrogen applications could be reduced on areas of low soil PAWC, reducing costs, while increasing Nitrogen applications on areas of high soil PAWC could increase yield and grain quality.

4 2.0 Objectives The broad objective of the project was to improve farm productivity and profitability through more targeted and strategic allocation of Nitrogen. More specific aims were to: Demonstrate the use of Yield Prophet and plant available water capacity (PAWC) mapping to make better Nitrogen application decisions; Quantify the economics of using Yield Prophet and PAWC mapping to improve Nitrogen decision making. 3.0 Methodology 3.1Trial design A co-operator was selected who had existing EM38 mapping, soil type variability, experience using GPS yield monitoring equipment and the ability to apply variable rate Nitrogen. The trial paddock was split into 3 zones based on EM38 survey data and three years of yield maps. Spatial analysis of EM38 survey data and yield maps determined the sites for soil characterisations. o Zone 1 (MG1) Red Sandy Loam o Zone 2 (MG2) Shallow Sand + paddock edges o Zone 3 (MG3) Sandy Clay MG1 MG3 MG2

5 3.2 Soil characterization and modelling Soil cores were taken post-harvest 2012 to assess crop lower limit (CLL), given almost no rainfall was received from August to December Soil moisture percentage was measured and used to create a soil characterisation for each zone. Yield Prophet profiles were created for each zone based on soil characterisation data (Figures 2, 3, 4). Starting soil moisture and Nitrogen were determined by soil coring prior to sowing (Table 1). Rainfall data was accessed from the closest weather station at Barmedman. This fed directly into the model. Figure 1. Collecting soil cores to determine crop lower limit (CLL) Starting PAW (mm) Starting Nitrogen (kg/ha) Zone 1 (MG1) Zone 2 (MG2) Zone 3 (MG3) Table 1. Starting soil water and starting soil Nitrogen

6 SOIL CHARACTERISATIONS MG1 Figure 2. Soil Characterisation for MG1 MG Ammonium Nitrogen mg/kg Nitrate Nitrogen mg/kg Organic Carbon % Conductivity ds/m ph Level (CaCl2) ph ph Level (H2O) ph Chloride mg/kg Moisture % Table 2. MG1 Soil data collected prior to sowing.

7 MG2 Figure 3. Soil Characterisation for MG2 MG Ammonium Nitrogen mg/kg Nitrate Nitrogen mg/kg Organic Carbon % Conductivity ds/m ph Level (CaCl2) ph ph Level (H2O) ph Chloride mg/kg Moisture % Table 3. MG2 Soil data collected prior to sowing

8 MG3 Figure 4. Soil Characterisation for MG3 MG Ammonium Nitrogen mg/kg Nitrate Nitrogen mg/kg Organic Carbon % Conductivity ds/m ph Level (CaCl2) ph ph Level (H2O) ph Chloride mg/kg Moisture % Table 4. MG3 Soil data collected prior to sowing

9 3.3 Treatment Allocation In July 2013 the Yield Prophet model was used to estimate the yield potential of each zone using measured soil Nitrogen, starting soil moisture and rainfall. Other crop information such as sowing time, variety and seeding rate were also entered into the model. Nitrogen rates were determined separately for each zone, based on Yield Prophet predictions using output from the Crop Report (Figure 5), Nitrogen Comparison Report (Figure 6) and Nitrogen Profitability Report (Figure 7) models. To compare with district practise, a standard Urea treatment of 100 kg/ha was included in strips across the paddock, encompassing each of the three variable rate (VR) zones. It was decided that in order to compare the VR treatments against the Standard treatments, that the total allocation of Urea should be equal across the paddock. This way the value of allocating Nitrogen differentially to zones could be more easily compared with blanket application. Based on the Crop Report, Nitrogen Comparison Report and Nitrogen Profitability Report model outputs from Yield Prophet, it was determined that the highest rate should be allocated to MG1, followed by MG3 and that each of these allocations was likely to provide greater returns than MG2. It was decided that the maximum amount of Urea to apply in any one zone would be 200 kg/ha Urea. As such, the maximum rate was applied to MG1, with the remaining Urea applied to MG3. VR Zones Urea Rate(kg/ha) MG1 200 MG2 0 MG3 175 Table 5. Nitrogen Treatments

10 Figure 5. Yield Prophet Crop Report Graph for MG1 Figure 6. Yield Prophet Nitrogen Comparison Report Graph for MG1

11 Figure 7. Yield Prophet Nitrogen Profitability Report Graph for MG1 3.4 Nitrogen Application Nitrogen treatments were applied on 5 August 2013 once the crop had reached GS31 in all three zones. Growth stages were estimated using the growth stage simulation function within Yield Prophet (Figure 8) and visually confirmed prior to spreading. Nitrogen was applied in the form of Urea using a variable rate spreader. 13mm of rainfall fell on the site over the days 7 and 8 August 2013.

12 Figure 8. Yield Prophet Growth Stage Simulations A variable rate Urea prescription map was created to ensure each zone received the designated amount of fertiliser. The Standard 100kg Urea treatment strips were built into the prescription map, encompassing all three zones. A Nil Urea strip was included for comparison

13 Figure 9. Nitrogen Treatments Treatment Strips were 48m wide, encompassing 2 spreading widths (24m) and 4 header widths (12m), allowing each strip to be harvestedd and analysed separately. Standard agronomic practise was used for alll other crop management. Variety Sowing Date Spitfire 16 th May 2013 Sowing Rate Fertiliserr at Sowing Knockdown Herbicide In-crop Herbicide kg/ha kg/ha MAPP L/ha Roundup CT L/ha Trifluralin 480 L/ha Amicide Advance ml/ha Lontrel g/ha Glean Rainfall 406 mm 242 mm 13 mm 46 mm January to December 2013 April to October and 8 August September 20133

14 4.0 Results The trial was harvested on 19 November 2013 with a yield monitor equipped header. Figure 10 shows yield variation within the trial paddock 1m x 1m plots were hand harvested for grain quality assessment on the same day. MG1 Urea Rate (kg/ha) Wheat Yield (t/ha) Protein (%) Screenings Grade Variable Rate AGP1 Standard Rate AUH2 Nil Urea AGP1 MG2 Variable Rate AGP1 Standard Rate AGP1 Nil Urea AGP1 MG3 Variable Rate AGP1 Standard Rate AGP1 Nil Urea AGP1 The number of hand harvested plots was too low to statistically analyse grain quality. Screenings were associated with broken grain, rather than small grains, possibly due to the sampling and testing process. Treatment Average Wheat Yield (t/ha) Variable Rate 3.26 Standard Rate 3.30 Nil 3.14 Zone Average Wheat Yield (t/ha) MG MG MG3 3.37

15 100kg 100kg NIL 100kg 100kg 100kg 100kg NIL 100kg 100kg 100kg 100kg NIL 100kg 100kg Figure 10. Yield Map including Nitrogen treatments

16 5.0 Economic Analysis Variable Rate Nitrogen Management Average Yield 3.26 t/ha Average Protein 9.8 % Ave Screenings 8.3 % Grade AGP1 $230 / tonne $750 / ha Less 100kg/ha $600/t $60 / ha Less Cost of VR management * $35 /ha $655 /ha * Includes EM38 survey, soil characterisation, soil coring/testing, yield prophet subscription. Assumes no additional machinery or software purchased Standard Nitrogen Management Average Yield 3.30 t/ha Average Protein 10.9 % Ave Screenings 7.6 % Grade AGP1 $230 / tonne $759 / ha Less 100kg/ha $600/t $60 / ha $699 /ha Nil Urea Average Yield 3.14 t/ha Average Protein 9.6 % Ave Screenings 8.3 % Grade AGP1 $230 / tonne $722 / ha $722 /ha Grain prices were based on the best cash price available at Barmedman Graincorp depot on the day of harvest.

17 6.0 Discussion of Results There was no significant effect of applied Nitrogen on this site in 2013,, whether managed separately using Yield Prophet and PAWC mapping or applied as a blanket rate, when compared to the Nil treatment. This likely due to the starting soil Nitrogenn being adequate to achievee the water limited yield potential. Yield Prophet slightly overestimated thee yield potential of MG1 and MG3 and significantly underestimated the yield potential of MG2. These inaccuracies s appear to be associated with variation in rooting depth across the zones and can be manually altered to more closely reflect the situation. Using Yield Prophet and zone management did allow for a more analytical approach to Nitrogen management, with measured differences in starting soil water andd Nitrogen between zones from the beginning of the season. With hindsight there was an opportunity to reduce fertiliser costs based onn model predictions, however this opportunity was not considered for reasons discussed below. Yield Prophet Crop Reports generated in July 2013 for MG11 and MG33 indicated an 80% probability of achieving 3.2 t/ /ha, (the long term median wheat yield y of thee site), with existing Nitrogen and PAW. Figure 11. Crop Report generatedd 1 July 2013 for MG1 If the decision had been made, based onn the model output, that the long term median yield could be achieved without additional Nitrogen, significant cost c savingss could have been made.

18 Why was Nitrogen applied to MG1 and MG3 when there appeared to be adequate soil Nitrogen to exceed the long term median yield? The following factors influenced the decision to apply additional Nitrogen: Full moisture profile indicated by Yield Prophet (Figure 12). Strong seasonal forecast (80% chance of above median rainfall July to October predicted) General optimism amongst farmers and advisors, based on the seasonal forecast Fear of missing out on above average yields if the seasonal forecast was accurate. Desire to determine if upper yield predictions of the Yield Prophet model could be achieved in a large scale trial. Figure 12. Estimate of plant available water for MG1, 1 July 2013 Without a decision making framework, the decision maker is still tempted to consider the what if scenario of above average spring rainfall and soft finishing conditions. This has the potential to encourage higher inputs than are required. In order to reduce the temptation of over allocation in years like 2013, where adequate N is available for median yields to be achieved, a decision making framework that incorporates historical yield performance is proposed.

19 6.1 Proposed framework for Nitrogen decision making using Yield Prophet and PAWC Zones. Yield Prophet % Probability of achieving median yields with existing Nitrogen + Plant Available Water with additional Nitrogen Likelihood of yield response to additional Nitrogen / Action > 60 % LOW / Wait < 60 % < 60 % LOW / Wait, reassess < 60 % > 60 % HIGH / Go Comment Adequate Nitrogen and PAW PAW is likely to be the major limitation to yield Adequate PAW but inadequate Nitrogen By using the above framework for Nitrogen decision making, the reliance on long term forecasting or guessing future rainfall could be reduced. When managing zones independently the process would have to be followed for each management zone within a field to determine the requirement for additional Nitrogen. If Nitrogen is deemed to be required (scenario 3), the Nitrogen Profit Report and Nitrogen Comparison Report generated by Yield Prophet could be used to estimate required Nitrogen and application rates.

20 6.2 Economic Discussion In 2013 the use of Yield Prophet and PAWC mapping to manage Nitrogen was less profitable than the standard, blanket rate treatment. Both Nitrogen treatments were less profitable than the Nil Urea treatment. Even though the Nitrogen treatments increased yield compared with the Nil, the increases were not large enough to cover the expense of extra Urea. If the decision making framework outlined above had been implemented, no Urea would have been applied, a net saving of $25/ha. $60/ha Less $35/ha $25/ha Urea saving cost of managing Nitrogen using Yield Prophet and PAWC mapping Net benefit over blanket Urea application. This outcome was heavily influenced by seasonal and site conditions. If yield potential was higher or residual soil Nitrogen was lower, the economic outcomes may have been different. In the absence of deep drainage or denitrification it could be assumed that applied Nitrogen would be available to the following crop. The value of this additional soil Nitrogen depends on the amount of Nitrogen available in the Nil treatment, as well as the seasonal conditions the following year.

21 7.0 Implications The project outcome suggests that there is potential for managing Nitrogen separately across management zones within a paddock using Yield Prophet and PAWC mapping. In situations where Nitrogen is not the major limitation to yield, identifying this using Yield Prophet and PAWC mapping and avoiding unnecessary Nitrogen fertiliser applications would provide a cost saving. In situations where zones differ in Nitrogen requirement, the ability to assess and target Nitrogen applications has the potential to provide both increased yield and cost saving. A number of limitations to this management technique were identified throughout the project: Realistic model predictions require accurate soil data plus an understanding of how to manipulate the soil characterisation and the soil parameters within Yield Prophet to best match the paddock conditions. There remains a requirement to guess future rainfall or rely on medium term weather forecasting which can be unreliable. This can lead to overly optimistic assumptions and over-allocation of fertiliser. The development of a decision making framework that compares predicted yield to historical performance at a location has the potential to reduce the reliance on seasonal forecasting or speculation about possible future conditions. A framework such as this could reduce both the business risk and stress associated with matching Nitrogen allocation to yield potential. Questions arising from this information: Does Zone management of Nitrogen improve profitability and reduce risk in both high yielding and low yielding situations? What are the implications in the following season to variable rate (VR) Nitrogen management? What is the effect of carryover Nitrogen? Can the same process be used for VR Nitrogen management in canola? Can the cost, time and effort of managing Nitrogen this way be reduced by extrapolating soil characterisation information across a landscape on similar soil types? A follow on from this project has been funded by GRDC for the 2014 winter season to answer some of the above questions.

22 8.0 Recommendations The potential remains for improved Nitrogen decision making using Yield Prophet and PAWC mapping, despite this strategy being less profitable than the blanket application and the Nil Urea treatments in 2013 at this site. There was no benefit from applied Nitrogen at this site, regardless of treatment, due to seasonal conditions. Where Nitrogen is not the major limitation to yield, such as this site, using Yield Prophet and PAWC mapping will not increase yields. It can, however identify those situations where cost savings can be made by reducing Nitrogen fertiliser applications and hence reducing risk. When using Yield Prophet to help make Nitrogen application decisions it could be beneficial to use a decision making framework that incorporates historical yield results for the site. This may decrease the temptation for unreasonably optimistic assumptions, particularly when other outside influences are compounding the optimism. Benefits of the strategy - The process improves the understanding of soil parameters and soil variation across paddocks, farms and landscapes. - The measurement of starting soil moisture and starting soil Nitrogen improves the accuracy of yield prediction, even in the absence of Nitrogen application decisions made using Yield Prophet. - The process encourages a more strategic approach to resource allocation. Limitations - Model predictions are heavily reliant on accurate soil characterisation, rainfall and temperature data. Rainfall and temperature measurements need to be measured as close to the site as possible. - The Yield Prophet model predicts the maximum yield potential with the given parameters. It does not account for reductions in yield associated with frost, disease, weeds or pests. - There remains a requirement to speculate on future rainfall and temperature conditions. The usefulness of managing Nitrogen variably using Yield Prophet and PAWC mapping needs to be assessed further, under a range of seasonal conditions and with other crops such as canola and barley

23 APPENDIX 1 Planned Extension Activities Presentation of findings and conclusions to Temora Ag Bureau members at one of their meetings. Copy of this report to be distributed to: - Temora Ag Bureau s network of farmers and advisors - Rural Management Strategies Pty Limited s network of clients and advisors Copy of this report to be published on the Rural Management Strategies Pty Limited website.

24 APPENDIX 2 Barmedman Rainfall 2013

25 BARMEDMAN RAINFALL 2013 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1st nd rd th th th th th th th th th th th th th th th th th st nd rd th th th th th th th st Highest Daily Monthly Total Annual April October 242.6