May 2017 Field day Soil nutrient management project Report to stakeholders Backtrack Dairies Analysing where we are Where to from here

Soil nutrient management in dairy farming systems Thanks To DairyNZ AGMARDT Ballance Healthy Soils Hills Laboratories Hydrocom Kiwi Fertilisers Paddock Vets Perry Laboratories Precision Tracking Individual farmers and rural business professionals Introduction information Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems SHOULD do some samples for soil microbes and soil carbon to 60cm depth, also rooting depth. Some soil type, same pasture, cowsheds the same, did everything as same as possible. Trying to compare the two farms. Also keeping the same stocking rate. Pivot location would be good if could get on map. Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Backtrack Dairies – as at 10th May Whakapono Waiora Effective Area 155 210 Stocking Rate 3.1 3.0 Peak Cows 483 636 Treatment Kinsey-Albrecht Conventional Total MS/ha 1451 1365 Total MS/cow 466 451 Total N Applied 84 124 N Leaching 25 Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Milk Solids/Ha – as at 10th May Whakapono 1451 MS/ha (1500 MS/ha – projected) Waiora 1365 MS/ha (1423 MS/ha – projected) Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Milk Solids/Cow – as of 10th May Whakapono 466 kgMS/cow (481kgMS/cow – projected) Waiora 451 kgMS/cow (470 kgMS/cow – projected) Excluding calf milk Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Water Inputs over the last 3 seasons Whakapono 14/15 15/16 16/17 Rainfall 388 (from 24 Aug) 625 891 Irrigation 537 262 Total Water Inputs 1162 1153 Waiora 14/15 15/16 16/17 Rainfall 388 (from 24 Aug) 625 891 Irrigation 573 275 Total Water Inputs 1198 1166 Don’t have irrigation for 14/15 season – should be able to get from website? Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Whakapono Soil Temperature Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Waiora Soil Temperature Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Soil Moisture Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Whakapono – Pasture Cover vs N use Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Waiora – Pasture Cover vs N Use Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Fertiliser 16-17 N P K S Ca Mg Whakapono 84 35 90 116 522 64 Waiora 124 51 50 59 15-16 N P K S Ca Mg Whakapono 117 27 42 113 923 123 Waiora 160 37 67 94 90 Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Supplements Fed – Projected to end of Season Whakapono 749 kgDM/cow Waiora 644 kgDM/cow Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Soils Tests – Monitor Paddocks Hills Whakapono Waiora PH 6.3 6.2 Olsen P 14 16 S 19 11 K 6 8 Ca 9 10 Mg 29 17 Na 3 4 Kinsey Albrecht Whakapono Waiora PH 6.1 6.2 Total Exchange Capacity 11.4 10.7 Calcium % 64 71 Magnesium % 14 8 Potassium % 2.4 3.5 Sodium % 0.9 1.1 Kinsey Albrecht is base saturation % values All results are only for monitor paddocks Soil nutrient management in dairy farming systems

Overseer Nutrient Budgets Whakapono (kg/ha/yr)   N P K S Ca Mg Na Nutrients Added Fertiliser, lime and other 79 33 84 109 490 61 Rain/clover N Fixation 179 2 4 18 Irrigation 7 5 28 Supplements imported 50 8 6 Nutrients Removed As products 99 17 24 21 Exported effluent 1 As supplements To atmospheric 108 To water 25 0.7 140 35 Change in internal pools Plant material Organic pool 78 10 -20 Inorganic mineral -11 -2 -3 Inorganic soil pool 14 469 74 38 Waiora (kg/ha/yr)   N P K S Ca Mg Na Nutrients Added Fertiliser, lime and other 117 47 48 56 Rain/clover N Fixation 159 2 4 19 Irrigation 8 5 29 7 30 Supplements imported 6 17 3 1 Nutrients Removed As products 95 16 23 20 Exported effluent As supplements To atmospheric 105 To water 25 0.8 14 85 43 15 Change in internal pools Plant material -1 -2 Organic pool 88 12 -20 Inorganic mineral -16 -3 Inorganic soil pool 49 9 32 Measure leaching theoretically not physically Would like to do it physically if possible

Soil nutrient management in dairy farming systems Pasture Quality Ave for Season Whakapono Waiora DM % 16.8 ME (MJ/KgDM) 12.4 12.2 Protein % 26.3 26.2 NDF % 37.4 39.3 Soluble Sugars % 10.8 10.4 Whakapono – S6 Waiora – N8 Lactating cow needs about 18% crude protein. High at 21-22 for environmental purposes as more is leached John king measure brix shows slightly higher on whakapono Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Pasture DM% Soil nutrient management in dairy farming systems

Clover content – 3 seasons Whakapono Waiora 4% 7% 10% History of sampling method Soil nutrient management in dairy farming systems

Effect of farm system on clover content 27% Whakapono Waiora 12% 10% Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems % of Farm Mown % mown of farm – Whakapono = 63% Waiora = 116% Whakapono –Total area pre mown –69.1ha = 44.6%. Area cut for silage = 28.3ha =18.3 % Waiora Total area pre mown –154ha =73%. Area cut for silage = 90ha =43% Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Animal Health – Down Cows Whakapono Waiora % of Cows at Calving time 4% 7% % of Cows Pre Calving 1% % of Cows Post Calving 3% 5% % of Cows rest of season 2% Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Animal Health – Lame cows Whakapono = 14% Waiora = 15% Lame cows pivots over tracks on whakapono and larger herd size. Could be the difference in clover content Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Animal Health - Mastitis Whakapono = 10% Waiora = 12% Mastitis cases per month Put in SCC either on this graph or separate Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Animal Health - SCC Whakapono = 158 Waiora = 165 Mastitis cases per month Put in SCC either on this graph or separate Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Whakapono Milk Urea Average = 25 Last season average was 26 Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Waiora Milk Urea Average = 23.8 Average last season = 24 Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Trace Elements Results  Copper (ref range8-25umol L)   Mar-14 Nov-14 Mar-15 Dec-15 Apr-16 Nov-16 Apr-17 Waiora 13 13.17 13.2 14.75 10.75 12.62 12.67 Whakapono 9.75 12.25 12.8 12.5 10 13.33  Selenium (ref range 600 + nmol/ L) 610 900 768 836.3 837.5 773 985 845 647.5 738 976.7 715 555 1078  B12 (ref range 300 + pmol/ l) 302 391.67 384 322.5 366.3 293 286 295 310 266 258.3 285 351 265  Iodine (ref range 45 - 60 ug/l) 26.2 35 25 35.67 29.88 34 52.17 23 29 24.2 30.17 28.33 36 54.83 Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Cow Condition Whakapono Pre Calving Pre Mating Summer Autumn Average CS 4.9 4.6 4.5 % < 4.0 1 5 8 3.5 % < 4.5 33 45 39 % > 5.0 21 11 7 13 Waiora Pre Calving Pre Mating Summer Autumn Average CS 4.9 4.7 4.5 4.4 % < 4.0 1 3 8 6 % < 4.5 4 22 45 49 % > 5.0 23 12 9 Put in updated logo Pre calving – July Pre Mating – Sep Summer – Feb Autumn - May Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Reproductive Performance   Whakapono Waiora 3 week Submission Rate 91% 87% Non-cyclers 9% 13% AI length 7 weeks Mating length 10 weeks % Early Calvers (Aug calving) 62% 57% % Late Calvers (Sep Calving) 25% 31% Empty Rate 15% Reproductive performance – info Waiora cows mated 624 Whakapono 481 cows mated Doesn’t include CO’s Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Reproductive Performance   Whakapono Waiora 3 week Submission Rate 91% 87% Non-cyclers 9% 13% AI length 7 weeks Mating length 10 weeks % Early Calvers (Aug calving) 62% 57% % Late Calvers (Sep Calving) 25% 31% Empty Rate 15% Reproductive performance – info Waiora cows mated 624 Whakapono 481 cows mated Doesn’t include CO’s Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Reproductive Performance Analysis Whakapono Waiora No of cows available to be mated 481 624 % of Late Calvers 20 24 % of cows over 8 yrs 13 15 % of Heifers and R3’s 37 38 % of cows in low condition 4 % of cows losing condition 31 Old cows above 8 yrs old Soil nutrient management in dairy farming systems

Soil nutrient management in dairy farming systems Summary of Performance – Projected to end of season Whakapono Waiora Peak Cows 483 636 Stocking Rate (cows/ha) 3.1 3.0 Milk Solids/Cow 481 470 Milk Solids/ha 1500 1423 Nitrogen Applied 84 124 Supplements Offered (kg/cow) 749 644 Supplement made on Farm (kg/cow) 101 153 Irrigation Applied 262 275 Rainfall 891 Nitrogen Leaching 25 Deaths % 1.7 3.5 Culls % 9.1 9.0 Milk solids per cow does not include calf milk Soil nutrient management in dairy farming systems

Soil Nutrient Management in Dairy Farming Systems The New Zealand Institute for Plant & Food Research Limited Soil Nutrient Management in Dairy Farming Systems Prepared by: Abie Horrocks and Richard Gillespie

Soil Healthy soil continued capacity to sustain biological productivity and ecosystem function within land-use boundaries Soil resilience capability of a soil to return to its original state (recover) after being stressed or disturbed Why is soil organic matter (SOM) important to healthy and resilient soils? How does SOM contribute to a healthy soil? The questions that we might ask in this project are driven by SOM Impt to understand about SOM SOM important in both systems Let’s look at how SOM is impacted in the soil

Functions of organic matter in the soil Biological functions - energy for biological processes - reservoir of nutrients - contributes to resilience Functions of SOM Physical functions - improves structural stability - influences water retention - alters soil thermal properties - cation exchange capacity - buffers changes in pH - complexes cations Chemical functions Organic matter is a source of nutrients for microbial and biological processes i.e. SOM is a reservoir of nutrients but it’s the microbial activity that releases these nutrients and compounds. Basically SOM is energy for biological processes. The by product of biological processes contributes to chemical and physical properties of soil So we’re looking at the extent that differences in land management (nutrient management) affect soil physical, chemical and biological functions

SOM Contributes to a range of important soil properties Management can alter the amount and distribution of different types of organic matter Organic matter contributes positively to many soil properties Changes in soil organic carbon and associated physical properties can be slow Biological and chemical properties may be more responsive to changes in management but differences need to be tracked over time (due to inherent variability) SOM relationship in soil is complex

The comparison Two farms, similar/same soil type, balanced stock (age, condition, production, SR and BW), irrigated (SW monitored) Three focus paddocks identified from each farm Albrecht-Kinsey biological approach (South) vs a ‘best management practice’ conventional approach (North) System differences South: AK focus on balancing nutrients with more emphasis on Mg, Ca etc North: synthetic fertiliser The soil analysis measures the nutrients available to the plant from the soil by performing specific nutrient tests in a certain way Initially same rates of N on each system But different formulations (urea north vs AS south)

Methods Focus paddocks were chosen and paired, with as similar a cropping history as was possible. Crop history prior to conversion New paddock ID System Pairing 2008-09 2009-10 2010-11 North 3 Conventional A Triticale (cut and carry) Peas (seed) Feed wheat South 12 Biological Pasture (short term?) Milling wheat North 15 B information not available Ryecorn (winter grazed) South 19 Pasture/chicory mix Chicory North 22 south end C Clover South 26 Pasture? Wheat

Limitations Paddocks are not replication. At best, only observational comparison of the two management systems. Very limited stats (t test: 2 tailed distribution, paired) No reason why we can’t get good, useful information But need to bear in mind that it is observational and not replicated We can only say e.g. the biologically managed farm at site A was better/worse/different than the conventional farm at site B. Trends over time are best indicator that something is happening

Soil measurements 3 measurements per focus paddock for most of the measurements Each measurement site GPS plotted (reduces spatial variability) Aim is to monitor physical, chemical and biological changes over time for the two systems.

Physical measurements: Penetration resistance:15 readings at 0-10 and 10-20cm depths. Measures soil density and represents compaction. Macroporosity and drained upper limit (DUL): 3 intact tension table cores to 7.5cm depth. Tension tables assess macroporosity as an indication of soils ability to drain efficiently. DUL gives field capacity (to determine water storage capacity). Aggregate stability: 3 spade squares to 15cm for aggregate stability. Indicative of physical structure and stability of soil under physical forces such as cultivation, rainfall and stock treading (affected by organic matter in system). Can determine water storage but need to know wilting point to calculate plant available water storage if can increase field capacity can increase water storage etc

Chemical and biological measurements 20 cores to 15 cm over paddock W sampling pattern Anaerobically mineralisable N: incubation process Total C and N. These N measurements will be indicative of available N under the two cropping systems. Hill Labs quick test (and S). Biological 3 ‘farmer spades’ 18 x 36 x 25cm. Earthworms, clover root weevil, porina, grass grub Effect of management on biological indicators may be direct or indirect. We will know starting point of soil N, N inputs and productivity So will be able to get a relative comparison of leaching potential But assume same rates of gaseous N losses and that we can get all inputs of N accurately from the biological products. AMN (anaerobically mineralisable N) is an estimate of the amount of plant available N likely to be released to the crop during the current season (incubation, corrected for ammonium in the non incubated soil). PMN is similar but is a longer incubation and represents what will be released over the season under optimal growing conditions. Is not same as mineral N ie N available to the plant now

Results: baseline fertility 2013 results (Hill Labs: Basic Soil + SO4-S) pH Olsen P S K Ca Mg Na North 3 Conventional 6 15 8 5 14 3 North 15 6.2 22 10 12 4 North 22 6.1 17 9 13 18.0 7.0 5.3 9.0 13.0 3.7 South 19 Biological 18 28 South 26 2 South 12 16 24 16.3 12.7 5.0 8.3 24.7 2.7 Individual paddock data presented Management changes already going >1y Some diffs at start of PFR monitoring

Results Results Baseline 2013 Year 1 2014 Year 2 2015 Year 3 2016 Conv Biol AMN (ug/g) 82.7 79.2 65.7 60.5 71.8 81.4 99.8 102.5 Soil moisture (%w/w) 24.7 25.0 29.9 30.8 30.9 31.5 32.3 Organic C (%) 2.7 2.9 2.8 3.0 Total N (%) 0.26 0.27 0.28 Soil pH 6.0 6.1 6.3 Olsen P (mg/L) 16.0 17.3 12.3 14.3 13.7 12.7 CEC (me/100g) 14.7 15.0 14.0 SO4-S (mg/kg) 10.7 11.0 11.3 22.0 K (MAF) 4.3 5.7 4.7 5.0 3.7 Ca (MAF) 8.7 8.3 7.3 9.7 Mg (MAF) 12.0 24.3 22.7 26.7 27.0 Na (MAF) 2.3 2.0 2.2 3.3 Average values presented Stats in 2016 report (t tests) AMN values 2016 high after dry winter. Take into account for fertiliser N management Convert ug/g to kg/ha. BD ->t soil/ha @1.2 g/ml 100 ug/g= 180 kg N/ha to 15 cm S differences Mg differences

Magnesium

Sulphur

Physical measurements Baseline 2013 Year 1 2014 Year 2 2015 Year 3 2016 Conv Biol 0-10 cm penetration resistance (MPa) 2.2 1.7 1.6 1.2 1.3 10-20 cm penetration resistance (MPa) 2.0 2.1 2.5 1.9 1.8 0-7.5 cm DUL moisture content (% v/v @ -10kPa) 40.5 40.8 44.3 43.9 43.5 42.4 42.2 0-7.5 cm Macro Porosity (% v/v @ -10kPa) 8.3 8.9 10.5 9.7 11.0 13.1 14.9 Aggregate stability (mm, MWD) 1.5 Aggregate stability (% >1 mm) 66 56 59 78 80 77 83 PR measurements: Good to very good for PP. >2.5 is concerning and can affect production 10-20cm note lower PR on Bio. Why? Deeper roots. Or fertiliser practice can affect. Stimulate microbes -> exudates, mucilaginous polysaccharides ->changes in soil phys characteristics Liming (Ca) can help soil structure DUL= FC. Ability of the soil to hold water Macro porosity: pore space >75um by volume. Link to water holding capacity and moisture release Can see higher values but not of concern. In desired range for PP. Dairy survey Lismore soils range 3-60% average 28% Trend to increase over time in both systems with higher values in Biol Earthworms have an effect on macro porosity. Maybe microbes causing changes too Agg Stab: 2 variates shown strongly linked. Nothing of concern, typical of dairy farm PP MWD <1.5 mm is concerning. Can see 2.8 in PP ungrazed under fencelines with 90% >1mm

Biological measurements Baseline 2013 Year 1 2014 Year 2 2015 Year 3 2016 Conv Biol Earthworms per m2 452 562 1144 1822 977 1349 1009 1577 Grass grubs per m2 9 32 6 20 42 12 72 Clover root weevil adult per m2 208 236 2 Clover root weevil larvae per m2 - 276 227 155 205 315 328 Porina per m2 4 >250 ew/m2 considered good. Numbers could be affected by grazing rotation and timing of weather and monitoring and activity....also putting cows on after rain vs time to drain at another paddock etc. +ve change to bio system Grass grub numbers concerning on south farm. Noted some GG patches when clipping autumn dissections Higher under bio Clover root weevil differences probably seasonal. Porina numbers on south farm concerning

Pasture composition Seasonal sampling: spring, summer, autumn in each focus pdk Sample pre grazing, close to grazing Sample paddock in W shape Clip to as close to ground level, approx. every 20 m (~35-40 clips) Mix and subsample Dissection Grass Clover Weed Dead Plus other desirable species Chicory Plantain

Pasture composition Previously shown the data points that make up this average plot fro grass and clover Difficult to see trends over time So simplified with line graph Consistently showing separation btwn the 2 management systems Bio has less grass and more clover than conv Only time that sig t <0.05 showed was grass% April 2016 Usually lots of noise in data to make up average so little significance Dead content. Similar btwn systems Function of mgt which is very good and targeted (sometimes JC targets higher residuals) Dead usually low in spring, inc over summer, reduces in autumn 2016/17 boil 9.5 conv 11.8

Conclusions It is anticipated that over time differences in farm management may result in changes to pasture composition and soil quality. It is also anticipated that there will be seasonal fluxes of soil structural condition in the focus paddocks, with the primary drivers for this being organic matter returns and moisture content at time of grazing. Overall the two sites are mostly consistent, especially in terms of physical soil parameters. Monitoring changes in soil quality in response to management may take longer to detect. Earthworms (although inherently variable), readily available sulphur and soil magnesium trends are emerging (all higher on the biological side). One of the focus paddocks under biological management had consistently higher clover content compared to the other focus paddocks (where there was no detectable difference in clover proportion). This is normalising. Pasture composition response to management Biological (where less fertiliser N is applied) Grass 8% down, clover 9% up (mean 2016/17)

Thank you! www.plantandfood.com The New Zealand Institute for Plant & Food Research Limited Thank you! www.plantandfood.com

Soil Nutrient Management Project May, 2017 Jeremy Savage MacFarlane rural business

The Landscape, May 2017: Fonterra announced a milk price forecast of $4.25/kgMS. Focus on low cost production. Opportunity to “cashflow” down turn by selling replacement heifers. Low stocking rate, low costs structure.

Milk Solids total (To Fonterra) 254,672 232,430 340,295 298,737 Whakapono Waiora Season Act 2015/16 Rev 2016/17 Farm Effective Area 155 210 Stocking Rate 3.3 3.1 3.29 3.03 Nitrogen Use 117 84 160 124 Peak Cows Milked 506 483 690 636 Production Milk Solids total (To Fonterra) 254,672 232,430 340,295 298,737 Milk Solids per ha 1,643 1,500 1,620 1,423 Milk Solids per cow 503 481 493 470 Feeding Pasture Eaten per cow 4166 4043 4048 4061 Supplements Eaten per cow 764 739 683 628 Total Feed Eaten per cow 4930 4782 4731 4689 Pasture Eaten per ha 13.6 12.6 13.3 12.3 Feed Conv. Efficiency (on platform) 9.8 9.9 9.6 10.0 Silage Harvested per Ha 173 353 676 Total Feed Utilised per Ha 13.8 13.0

Whakapono Waiora

Observations 16/17 Production back in both systems 13 kgMS/cow. The low stocking rate created greater demands on management. Compounded by a difficult season, nutritional challenge from pastures in November. Wet, wet, wet April. Pasture quality was difficult to maintain with high growth rates, lower demand. Feed cover on conventional farm was too high in summer months. This would have dropped the palatability of pastures and per cow production

2 seasons of an advantage to Wairora of circa 23 kgMS/cow. Comparison of farm Programs 2 seasons of an advantage to Wairora of circa 23 kgMS/cow. Have had better tail end lactation curves Has been achieved by feeding more supplement per cow rather than growing and harvesting grass. Feed harvested (TDM/HA) is similar for both units. Management has struggled handling the nitrogen boosted grass on conventional program with the low stocking rates.

Key Physical Comparisons: waiora conv Whakapono Production per (kgMS/Ha) 1423 1500 Deaths & Losses 3% 1.40% Times Topped 73% 45% Metabolic Cases 54 26 Metabolic % 8% 5% Silage Made (T DM) 161 56 Supplement Use (kgDM/cow) 628 739

Gross Marginal Analysis: Waiora conv Whakapono Milk Income 1,792,422   Waiora conv Whakapono Milk Income 1,792,422 1,394,580 Silage on Hand @ $.28 / T DM 4,200 560 Capital Livestock (Deaths) @ $1600/hd 30,528 10,819.2 Total Revenue 1,827,150 1,405,959 8,701 9,071 Expenses Conservation(@ $120 / t) 19,328 92 6,752 44 Purchased Feeds 112,920 538 116,817 754 Fertiliser (excl spreading) 85,738 408 93,310 602 Topping @$75/ha 11,498 55 5,231 34 Animal Health& Breeding Downer Cow Treatment @ $104.75/hd 5,657 27 2,724 18 Dusting for Metabolics 2,460 12 Total Variable Expenses 237,600 224,834 1,131 1,451 Gross Margin per ha 7,569 7,620

Opportunities 17/18 Lift the stocking rate. Lift the per cow production back to previous levels. Easier pasture management Positive business.

Whakapono Waiora Season Act 2015/16 Rev 2016/17 Fore 2017/18 Effective Area 155 210 Stocking Rate 3.3 3.1 3.29 3.03 Nitrogen Use 117 84 100 160 124 Peak Cows Milked 506 483 512 690 636 Production Milk Solids total (To Fonterra) 254,672 232,430 252,000 340,295 298,737 345,000 Milk Solids per ha 1,643 1,500 1,626 1,620 1,423 Milk Solids per cow 503 481 492 493 470 500 Feeding Pasture Eaten per cow 4166 4043 4087 4048 4061 Supplements Eaten per cow 764 739 750 683 628 Total Feed Eaten per cow 4930 4782 4837 4731 4689 4798 Pasture Eaten per ha 13.6 12.6 13.5 13.3 12.3 Feed Conv. Efficiency (on platform) 9.8 9.9 9.6 10.0 Silage Harvested per Ha 173 353 676 Total Feed Utilised per Ha 13.8 13.0