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milling region is spread across several varying geographic and climate zones. Across these regions and within regional districts varietal differences in cane yield and CCS vary throughout a harvest season. Typically, across the Industry, the harvest window tends to start in mid-June and finish by mid-November, with a season length of approximately 20-24 weeks. However, in NSW the season runs to mid-December often due to prolonged periods of wet-weather. The increasing risk of rainfall-related harvest interruptions is a primary reason why industry is reluctant to have crushing seasons closer to the end of the calendar year. The extent to which rain stops harvesting depends not only on the amount of rain in any given period, but also on soil type, aspect, slope, temperature and the moisture content of the soil before the rain event. Rainfall is not uniform over a mill region and, therefore, harvesting interruptions to individual farms are also unpredictable. The time of year when a crop is harvested affects yield by imposing both crop age and seasonal factors on the crop. The yield of the following ratoon crop is affected by the seasonal conditions into which the new crop grows. McDonald, Wood and Muchow (1999) showed the importance of time of harvest and crop age on crop productivity and profitability. To fully understand the physiological effects of crop age and time of rationing on productivity, the effects of climate (temperature and radiation) on a well-managed crop (where no other factors limit growth) must be separated from other factors which limit growth. Lawes et al. (2004) analyses suggested that exploitation of regional spatial variation would improve productivity. Sugarcane growers have a lot of issues to consider simultaneously when planning harvest times for individual blocks on farms including variety, crop class, crop age, CCS, cane yield, soil type and micro-climates. Each blocks location within the farm also comes into the time of harvest decision due to factors such as flood risk and attractiveness to pests. Regional management differences such as varieties, irrigation, group rotations and mill throughput means that harvest planning processes also vary across regions, therefore an industry-wide method is not appropriate. Therefore, the sugar industry has developed harvest planning tools to better manage: variety selection, crop age and crop class management, harvester migration and trafficability in wet weather, risk management of harvest, and to plan for better accommodation of climate forecasting indicators. However, these systems have not been adopted by the industry as the most profitable option for the industry is also the one with the least equity at the farm and harvester group level. Mallee System Mallees are grown as permanent crops. It is expected that mallees will be harvested repeatedly on about three to seven year rotations, with the length of rotation determined by the harvest yield. The season of harvest combined with the soil profile (availability of soil moisture) will need to be managed so that mallees liable to be under severe moisture stress on shallow soils are only harvested in optimal conditions of spring and early summer. This is discussed in greater detail in section 1.4.3 and 1.4.4. 2.5.2 Harvest monitoring Sugar System Knowing how much cane remains to be harvested during a crushing season has always been an important task undertaken by mill field staff. The pre-season crop estimates form the basis of many facets of raw sugar manufacturing from marketing and logistics, planning mill start dates, cane 61
transport arrangements, harvest groups base daily loadings and harvesting schedules. Changes in farm estimates during the season often occur and will therefore affect many of those facets identified above. Traditionally, mills used a proportional re-estimating program to determine the amount of change in farm estimates. In its simplest form, this is the calculation of a ratio comparing the actual yield for an area of harvested cane against the original estimate for that same area and applying the calculated ratio to the remaining crop estimates for each farm. The sugar industry has been using GPS as a management tool to keep records of the location of various vehicles for a number of years. The first commercial GPS vehicle tracking system developed in Australia was the GEOSTAT locomotive tracking system developed by Tully Sugar Limited and GS Corporation in 1993 (Fuelling and Wright 1997). Developments in harvest management systems have seen the mounting of GPS on harvesters to monitor where harvesters have worked. Various harvester monitoring systems are currently in use with the main components comprising data logger, GPS and modem. Mackay Sugar developed a harvester monitoring system during the 2005 and 2006 seasons. MTData tracking and data logging units form the basis for the harvester performance and tracking system. A GPS tracking device records the position of the harvester and stores it in a data logger awaiting transfer to a central web site. The MTData units include elevator on/off and engine on/off digital inputs to allow the status of the machine to be determined. Crossley and Dines (2004) undertook trials to integrate harvester tracking with a mill-based spatial harvest recording system during the 2002 and 2003 seasons in the NSW mills. The hardware was a dedicated system assembled by Transcom, and consisted of a data logger, GPS and a CDMA modem. The data recorded by these units consisted of a series of positions of the harvester, and machine status at those times. Harvesters monitoring data was stored on the harvester for the day and uploaded to a central server each night. A customised GIS software application called CHOMP (Centralised Harvest Operations Management Program) was used to interpret the areas cut and maintain the paddock harvest status from a map interface (Beattie and Crossley 2006). Figure 2.10 illustrates GPS harvester tracking in a NSW harvested field. 62
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Sustainable Biomass Supply Chain fo
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Foreword This report provides an as
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include business development (new p
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Acknowledgments The authors would l
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4.1 Product Options and Supply Chai
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Table 4.2 Assessment of current val
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Figure 3.4 Tracked rigid self-prope
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Executive Summary What the report i
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• Biomass production potential of
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• As the Industry expands, the mo
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Harvesting, transport and storage s
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Biomass processing, supply chain pl
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Key barriers to biomass industries
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Crop-Biomass Production Production
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Figure 1.1 The cropping and pasture
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Table 1.1 Mallee species used for p
Page 33 and 34: 1.1.4 Growth Cycle Mallee System Ma
Page 35 and 36: northern New South Wales (where it
Page 37 and 38: Almost 80% of the industry now cuts
Page 39 and 40: Bark has relatively high ash but as
Page 41 and 42: Carbon sinks Planting of mallees to
Page 43 and 44: Table 1.5(a) State Land area devote
Page 45 and 46: out the fluctuations in farm income
Page 47 and 48: Mallee system Most of the mallee bi
Page 49 and 50: inconclusive result may have been d
Page 51 and 52: For a sustainable woody crop indust
Page 53 and 54: changed significantly since they we
Page 55 and 56: Figure 2.2 Biosystems Engineering p
Page 57 and 58: Whole-of-crop harvesting represents
Page 59 and 60: During the last decade the harvesti
Page 61 and 62: single row, as this would improve t
Page 63 and 64: 2.2.2.2 Weight Sugar System The Aus
Page 65 and 66: Table 2.1 Harvester Comparison Tabl
Page 67 and 68: The quality of cut may be less impo
Page 69 and 70: ate than a 170 tonne/ha crop of sta
Page 71 and 72: Dry Leaf 6.1 - 3.5 17.0 58.9 53.2 T
Page 73 and 74: Bulk density will be a key consider
Page 75 and 76: Table 2.4 EM levels in cane supply
Page 77 and 78: L/T L/T 60 0.97 0.71 80 0.92 0.66 1
Page 79 and 80: Total 7.5-26 16.5 Mallee System The
Page 81 and 82: • waiting for mill delivery of em
Page 83: perhaps at 10 - 20 km intervals. Th
Page 87 and 88: contractors and growers, and the fa
Page 89 and 90: experience of the sugar industry wi
Page 91 and 92: Table 2.11 Alternative harvest paym
Page 93 and 94: onto the harvester. BR+F still send
Page 95 and 96: Repairs and maintenance 2.10 Capita
Page 97 and 98: Figure 2.14 and Table 2.14 describe
Page 99 and 100: Sichter et al. (2005)), harvest and
Page 101 and 102: Transport efficiencies may be possi
Page 103 and 104: 3. Transport and Storage Systems Tr
Page 105 and 106: same time, the potential problems o
Page 107 and 108: Figure 3.3 Articulated self-propell
Page 109 and 110: • The harvester will not have any
Page 111 and 112: Figure 3.7 Gross mass compared with
Page 113 and 114: external factors dramatically impac
Page 115 and 116: Figure 3.11 The effect of haulout t
Page 117 and 118: 3.3 Road Transport 3.3.1 Configurat
Page 119 and 120: Figure 3.15 shows an example of the
Page 121 and 122: Road distance one way < 20 km 70 km
Page 123 and 124: Haul distance is largely outside th
Page 125 and 126: 3.6 Recommendations The nature of t
Page 127 and 128: • The strategy offered lower tota
Page 129 and 130: sugarcane billets are such that wit
Page 131 and 132: • Transfer the whole tree product
Page 133 and 134: Figure 4.5(b) Energy balance of con
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2010). Table 4.2 presents a summary
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4.4.2 Activated charcoal Activated
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Nett Product Value ($/t) $475.00 $
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Table 4.9 presents an estimation of
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• Oil from leaf @ $2/kg • Synth
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• The mallee oil would be extract
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5. Industry and Business Structures
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is conducted into tariff levels on
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Bx is % brix in first expressed jui
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Hildebrand (2002) estimated that th
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also has a flow on effect to the sp
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Sugar Industry Illustrative Example
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with super size multi-lift bins ove
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farmer vs. harvester) is the next l
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6. Supply Chain Planning and Manage
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Figure 6.1 Building blocks of the s
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weighed against the costs of operat
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• There is close contact between
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6.4 Planning, Management Tools and
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• Harvest and transport logistics
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interface. The system allows users
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Case Study 6.2 - Model Application
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Relationships between sectors and p
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7. Supply Chain Modelling and Econo
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It was assumed that there was a fif
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Table 7.2 Scenario two capital equi
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Table 7.4 Fuel burn rates harvester
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Figure 7.5 Effect of capital equipm
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Figure 7.7 Effect of annual tonnes
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30 1.8 7.0 12.3 17.5 50 1.1 4.3 7.6
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8. Conclusions and Recommendations
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Biomass bulk density has a large im
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Vehicles used for infield haulout w
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This can be compared with harvest a
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While diversification can add value
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Appendix 1: Comparative Assessment
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and transport conditions. Billet le
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that cane production is the most pr
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on sugar only, other proceeds (mola
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References Agnew, J 2002. A Partici
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Enecon 2001. Integrated Tree Proces
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Keating, BA, Antony, G, Brennan, LE
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Ridge, DR and Linedale, AL, 1997. T
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Willcox, T, Hussey, B, Chapple, D a
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