AU2018211337A1

AU2018211337A1 - Systems, methods, apparatus and user interfaces for processing agricultural commodities

Info

Publication number: AU2018211337A1
Application number: AU2018211337A
Authority: AU
Inventors: Oswald Forbes Norton
Original assignee: AG Centre Australia Pty Ltd
Current assignee: AG Centre Australia Pty Ltd
Priority date: 2017-08-04
Filing date: 2018-08-03
Publication date: 2019-02-21

Abstract

SYSTEMS, METHODS, APPARATUS AND USER INTERFACES FOR PROCESSING AGRICULTURAL COMMODITIES A system to process agricultural commodities comprises a computer memory storing pricing data in a master price grid related to the processing of agricultural commodities. The pricing data is received from a plurality of processors of agricultural commodities and/or feedlots. The master price grid stores the pricing data in a multidimensional master data structure for each processor and/or feedlot. The system comprises a computer processor in communication with the computer memory and an interface in communication with the computer processor to: receive a request from a producer of agricultural commodities for a comparison of pricing from a plurality of processors of agricultural commodities and/or feedlots for agricultural commodities the producer wishes to sell; and output the comparison of pricing from the plurality of processors of agricultural commodities and/or feedlots. The pricing comparison is generated by the computer processor based at least on the master price grid. Corresponding methods, apparatus, user interfaces and computer readable media are also disclosed.

Description

SYSTEMS, METHODS, APPARATUS AND USER INTERFACES FOR PROCESSING AGRICULTURAL COMMODITIES

FIELD OF THE INVENTION [001] The present invention relates to systems, methods, apparatus and user interfaces for processing agricultural commodities, and in particular processing livestock, such as, but not limited to cattle, sheep and goats.

BACKGROUND TO THE INVENTION [002] The processing of agricultural commodities, and in particular livestock, such as, but not limited to cattle, sheep and goats, is currently a time-consuming and complex procedure and as such it can problematic for producers to obtain a like-forlike price comparison. This may appear to be a relatively straightforward problem to address, but there are a range of factors that must be considered that present a number of significant hurdles.

[003] For example, livestock processors and feedlots typically generate and issue their own price grids which identify the price the particular processor or feedlot will pay based on a number of characteristics relating to the animals being processed and other factors relating to the feedlot procedure. Such characteristics include at least some of the following relating to animals: age, weight, dentition, fat grading, butt shape, sex, breed, premiums for features such as marbling, deductions for features such as bruising, meat or fat discolouration or other blemishes, the number of animals being processed in one sale, whether the animals are certified according to an applicable standard, e.g. Meat Standards Australia (MSA) in Australia, whether the animals are hormone growth promotant (HGP) free, animal feeding history, e.g. grass-fed, grain fed, condition of animal on arriving for processing and other factors, such as a location of the producer, location of the processor/feedlot and a destination market.

[004] Different processors and feedlots include the above characteristics or a subset thereof in their price grids and present the information in different formats and

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2018211337 03 Aug 2018 layouts. It can therefore be difficult for producers to accurately assess the grade their animals are likely to achieve once processed and therefore the price. To be able to compare price grids producers must request the grids from the processors/feedlots over the telephone, via email, facsimile or via an online request form. Furthermore, the information in the price grids changes regularly according to market conditions such that the time consuming process of sourcing the price grids must be repeated regularly even before the process of manually comparing the different grids can take place.

[005] The difficulties experienced by producers in accessing and accurately comparing price grids reduces the ability of producers to make better production and investment decisions. Processors and feedlots also experience inefficiencies in exchanging the necessary documentation with producers for each sale.

[006] In some countries, such as Australia, the aforementioned problems have resulted in the prospect of mandatory price reporting being introduced. Whilst this may address or ameliorate some of the aforementioned problems, other problems are likely to remain and significant costs to the industry would be incurred.

[007] Progress towards addressing at least some of the aforementioned problems has been made with initiatives such as:

Livestock Data Link (LDL), which is a web-based application that links slaughter data from the National Livestock Identification System (NLIS) and MSA databases with analytical tools, benchmarking reports and feedback. LDL allows supply chain participants to analyse carcass performance in terms of compliance to market specifications; and

Meat and Livestock Australia (MLA)’s Prices & Markets information and reporting tool, which is a web-based application that allows supply chain participants to analyse the aggregated pricing data of processors, feedlots and saleyards at a region level and in relation to broad livestock types.

[008] Partial solutions to at least one or more of the aforementioned problems, or alternatives are provided by the systems disclosed in the following patents and patent applications: US7181408, US7584136, US2008/0059330, AU2016201469 and AU2014307605. Nonetheless, each of the systems possesses one or more drawbacks and/or deficiencies that render such systems unsuitable for providing an

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2018211337 03 Aug 2018 adequate solution, particularly for processing livestock and/or particularly in Australia.

OBJECT OF THE INVENTION [009] An object of the present invention is to provide a system and/or a method and/or an apparatus for processing agricultural commodities, and in particular processing livestock, such as, but not limited to cattle, sheep and goats, and more particularly, processing livestock in Australia that addresses or at least ameliorates one or more of the aforementioned problems of the prior art and/or provides a useful commercial alternative to existing offerings.

SUMMARY OF THE INVENTION [0010] Embodiments of the present invention relate to systems, methods, apparatus and user interfaces for processing agricultural commodities, and in particular processing livestock, such as, but not limited to cattle, sheep and goats, and more particularly, to processing livestock in Australia.

[0011] Embodiments of the present invention relate to systems, methods, apparatus and user interfaces for providing feedback on agricultural commodities that have been processed, for example, to assist producers in improving their production and investment decision making processes.

[0012]According to one form, but not necessarily the broadest form, the present invention resides in a system to process agricultural commodities, the system comprising:

a computer memory storing pricing data in a master price grid related to the processing of agricultural commodities, said pricing data received from a plurality of processors of agricultural commodities and/or feedlots, said master price grid storing pricing data in a multidimensional master data structure for each processor/feedlot;

a computer processor in communication with the computer memory; and an interface in communication with the computer processor to:

receive a request from a producer of agricultural commodities for a comparison of pricing from a plurality of processors of agricultural

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2018211337 03 Aug 2018 commodities and/or feedlots for agricultural commodities the producer wishes to sell; and output the comparison of pricing from the plurality of processors of agricultural commodities;

wherein the comparison is generated by the computer processor based on the master price grid.

[0013] According to another form, but not necessarily the broadest form, the present invention resides in a method to process agricultural commodities, the method comprising:

storing in a computer memory pricing data related to the processing of agricultural commodities, said pricing data received from a plurality of processors of agricultural commodities or feedlots, said pricing data stored in a master price grid storing pricing data in a multidimensional master data structure for each processor/feedlot;

receiving via an interface in communication with a computer processor, the computer processor in communication with the computer memory, a request from a producer of agricultural commodities for a comparison of pricing from a plurality of processors of agricultural commodities or feedlots for agricultural commodities the producer wishes to sell;

generating by the computer processor a comparison of pricing from the plurality of processors of agricultural commodities or feedlots based on the master price grid; and outputting the comparison via the interface.

[0014]According to a further form, but not necessarily the broadest form, the present invention resides in an apparatus to process agricultural commodities, the apparatus comprising:

a computer memory storing pricing data in a master price grid related to the processing of agricultural commodities, said pricing data received from a plurality of processors of agricultural commodities or feedlots, said master price grid storing pricing data in a multidimensional master data structure for each processor/feedlot;

a computer processor in communication with the computer memory; and

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2018211337 03 Aug 2018 an interface in communication with the computer processor to:

receive a request from a producer of agricultural commodities for a comparison of pricing from a plurality of processors of agricultural commodities or feedlots for agricultural commodities the producer wishes to sell;

generate by the computer processor a comparison of pricing from the plurality of processors of agricultural commodities or feedlots based on the master price grid; and output the comparison via the interface.

[0015] According to a further form, but not necessarily the broadest form, the present invention resides in a computer readable medium having stored thereon instructions executable by a computer processor to cause:

storing in a computer memory pricing data related to the processing of agricultural commodities, said pricing data received from a plurality of processors of agricultural commodities or feedlots, said pricing data stored in a master price grid storing pricing data in a multidimensional master data structure for each processor;

generating by the computer processor a comparison of pricing from the plurality of processors of agricultural commodities based on the master price grid; and outputting the comparison via the interface.

[0016]According to yet another form, but not necessarily the broadest form, the present invention resides in a user interface to facilitate processing of agricultural commodities, the user interface comprising:

a plurality of fields to receive data relating to a request from a producer of agricultural commodities for a comparison of pricing from a plurality of processors of

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2018211337 03 Aug 2018 agricultural commodities or feedlots for agricultural commodities the producer wishes to sell; and a plurality of fields to output the comparison of pricing from the plurality of processors of agricultural commodities or feedlots;

wherein the comparison is generated by a computer processor based on a master price grid stored in a computer memory in communication with the computer processor, the master price grid storing pricing data in a multidimensional master data structure for each processor/feedlot, the pricing data related to the processing of agricultural commodities and received from a plurality of processors of agricultural commodities or feedlots.

[0017] Preferably, the multidimensional master data structure for each processor comprises a dimension for each grading parameter or metric usable for grading the agricultural commodity.

[0018] Suitably, a price grid input interface is provided which receives the pricing data from the processors/feedlots.

[0019] Preferably, the plurality of fields for receiving data comprises fields selected from the following: a field for freeform entry of data; a menu to receive one of a plurality of predetermined selections; a slider to receive an adjustable selection within a predetermined range.

[0020] Preferably, the data relates to grading parameters for grading the agricultural commodities.

[0021] Preferably, the comparison of pricing is optimised to assist the producer in making better decisions relating to commodity production including, but not limited to ranking the comparison in order of highest pricing for the producer or ranking in order of a selected grading parameter, such as fat depth, Hot Standard Carcase Weight (HSCW), butt shape etc.

[0022] Suitably, the comparison of pricing is generated based on one or more fixed or variable assumptions.

[0023] Suitably, the one or more variable assumptions are generated based on feedback data derived from one or more previous purchases by the respective processor of agricultural commodities and/or one or more previous sales by the respective producer of agricultural commodities.

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2018211337 03 Aug 2018 [0024] Suitably, a multidimensional feedback data file is generated comprising data for each commodity, such as each animal, such data optionally being grouped by a parameter relating to the sale, such as processor, location, dressing percentage, etc..

[0025] Suitably, the data for each animal in the feedback data file are linked to the sale and the price grid under which the sale was made via universally unique identifiers (UUIDs).

[0026] Further forms and/or features of the present invention will become apparent from the following detailed description.

BRIEF DESCRIPTION OF THE DRAWINGS [0027] Embodiments of the present invention will now be described with reference to the accompanying drawings, which are provided by way of example only and in which like reference numerals refer to like features. In the drawings:

[0028] FIG 1 shows a system according to an embodiment of the present invention; [0029] FIG 2 is an extract of a custom price grid input interface completed by a livestock processor for the input of non-MSA pricing data;

[0030] FIG 3 is an extract of a different custom price grid input interface from that shown in FIG 2 completed by the same livestock processor for the input of MSA pricing data;

[0031] FIG 3A shows another price grid input interface for feedlots;

[0032] FIG 4 is an example of a master price grid for livestock processors in Australia;

[0033] FIG 5 is an example of a master price grid for livestock feedlots in Australia; [0034] FIG 6 shows a subset of a multidimensional master data structure comprising just three dimensions of a master price grid;

[0035] FIG 7 illustrates the multiple dimensions of the master data structure of the master price grid for each processor;

[0036] FIG 8 illustrates the master price grid for multiple processors;

[0037] FIG 9 illustrates links between the data for each animal from the feedback data file, the sale and the price grid under which the sale was made;

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2018211337 03 Aug 2018 [0038] FIGS 10 and 11 are general flow diagrams illustrating methods of providing a comparison of pricing from a plurality of the processors of agricultural commodities or feedlots;

[0039] FIGS 10A and 11A show examples of the user interface receiving from the producer data relating to the processing of cattle to a feedlot and processor, respectively.

[0040] FIG 12 shows an example of a user interface outputting the comparison of pricing from the plurality of processors of agricultural commodities or feedlots;

[0041] FIG 12A shows another example of a user interface outputting the comparison of pricing from a plurality of feedlots;

[0042] FIG 13 illustrates further inputs receivable from a producer of agricultural commodities that can be analysed by the computer processor in calculating the comparison of pricing;

[0043]FIGS 14 to 18 are general flow diagrams illustrating methods of facilitating a transaction of agricultural commodities between a producer and a processor or feedlot;

[0044] FIGS 19 and 20 are general flow diagrams relating to the generation of feedback data; and [0045] FIGS 21 to 23 show examples of feedback data.

[0046] It will be appreciated that the accompanying drawings may not have been drawn to scale and/or some features may have been distorted and/or omitted and/or may be schematic for the sake of clarity.

DETAILED DESCRIPTION OF THE INVENTION [0047] Embodiments of the present invention relate to systems, methods, apparatus and user interfaces for processing agricultural commodities, and in particular for processing livestock, such as, but not limited to cattle, sheep and goats, and more particularly, to processing livestock in Australia. However, embodiments of the present invention are applicable to processing other agricultural commodities and processing agricultural commodities in other countries. Embodiments of the present invention relate to systems, methods, apparatus and user interfaces for providing feedback on agricultural commodities that have been processed, for example, to assist producers in improving their agricultural commodities.

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2018211337 03 Aug 2018 [0048] Referring to FIG 1, a system 100 to process agricultural commodities according to some embodiments of the present invention comprises a computing device 101, such as a server, comprising a computer memory 102 comprising a computer readable medium 104 storing pricing data 106 in a master price grid 108 related to the processing of agricultural commodities. The pricing data 106 is received from a plurality of processors of agricultural commodities or feedlots. The master price grid 108 stores pricing data in a multidimensional master data structure for each processor of agricultural commodities or feedlots and the master data structure is described in further detail hereinafter. The system 100 comprises a computer processor 110 in communication with the computer memory 102. The computer processor 110 and the computer memory 102 can be in the same computing device, such as computing device 101, or in different devices, such as multiple computing devices, e.g. servers in the same or separate locations. The system 100 comprises an interface 112, such as a graphical user interface output on a display of a computing device 114, such as a laptop or desktop computer, tablet or mobile phone, in communication with the computer processor 110, for example via a communications network 116.

[0049] The interface 112 receives a request from a producer of agricultural commodities for a comparison of pricing from a plurality of the processors of agricultural commodities for agricultural commodities the producer wishes to sell. Hence, computing device 114 can be that of a producer. The computer processor 110 generates the comparison of pricing based on the master price grid 108 and the interface 112 outputs the comparison of pricing from the plurality of processors of agricultural commodities or feedlots. It will be appreciated that multiple producers of agricultural commodities can access the system 100 simultaneously via their respective computing devices 114 and submit and receive requests for a comparison of pricing from a plurality of the processors of agricultural commodities or feedlots for agricultural commodities the respective producers wish to sell.

[0050] For the systems, methods, apparatus and user interfaces of the present invention to operate, the pricing for processing agricultural commodities must be obtained from the processors/feedlots. According to some embodiments, this is achieved by providing processors/feedlots with a price grid input interface 118 which receives the pricing data from the processors/feedlots. With reference to FIG 1, price grid input interface 118 is output on a display of a computing device 120, of the

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2018211337 03 Aug 2018 processors/feedlots, such as a laptop or desktop computer, tablet or mobile phone, in communication with the computer processor 110, for example via the communications network 116.

[0051] According to some embodiments, a custom price grid input interface is provided to larger processors/feedlots and a standard price grid input interface is provided to smaller processors/feedlots. The custom price grid input interface accommodates the larger number of grading parameters or metrics for larger processors/feedlots that typically process a wider range of agricultural commodities for both domestic and international customers. Smaller processors/feedlots typically process a narrower range of agricultural commodities for smaller, less diverse markets.

[0052] FIGS 2 and 3 show two examples of extracts of custom price grid input interfaces completed by a processor of livestock. FIGS 2 and 3 show examples of pricing data relating to different grading parameters for grading agricultural commodities in the form of livestock. FIG 2 shows an extract of a custom price grid input interface 200 for a processor showing prices for different weights of livestock, such as 400-426kg, 350-400kg, 275-350kg, etc. for non-MSA heifers that have been grass fed according to the following grading parameters: fat quantity; dentition (no. of teeth); and butt shape. FIG 3 shows an extract of a custom price grid input interface 300 for the same processor showing prices for different weights of livestock, such as 400-426kg, 350-400kg, 275-350kg, etc. that have been grass fed, and according to the same grading parameters as FIG 2, but with the additional universal premium of whether the livestock are angus.

[0053] FIG 3A shows another example of a price grid input interface for feedlots which has been completed with sample figures. The price grid input interface comprises a plurality of fields, such as drop down menus or free text entry fields, for receiving pricing data from feedlots including, but not limited to a price grid number, date validity ranges for the price grid, delivery date ranges, weight ranges, dentition ranges, sex, breed, tropical breed content ranges, market options, a price per kg, weighing limitations or conditions, such as weighed after overnight curfew or a specified shrinkage percentage based on a transportation distance range. There is also an option to upload a file containing the feedlot’s price grid, such as in pdf format. The pricing data is then submitted to and received by computing device 101.

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2018211337 03 Aug 2018 [0054] The standard price grid input interface will be made available to each smaller processors/feedlots. Nonetheless, the standard price grid input interface is still quite complex since it contains all aspects of pricing grids from a wide range of smaller processors/feedlots and all of the pricing parameters they take into account for their pricing.

[0055] The data from the price grid input interfaces for the processors/feedlots are stored in one or more master price grids. FIG 4 shows an example of a master price grid 400 in the form of a table for processors of livestock in Australia and FIG 5 shows an example of a master price grid 500 in the form of a table for feedlots for livestock in Australia.

[0056]The master price grid 400 shown in FIG 4 comprises multiple grading parameters or metrics and features of each parameter, such as whether the parameter is discrete or continuous, a datatype pertaining to the parameter, such as whether it is a string, an integer, a character or floating and a type of parameter, e.g. a price, a deduction or a cut off. FIG 4 also shows examples of each parameter. In the example shown in FIG 4, the grading parameters comprise cattle type, market, dentition, gender, liveweight, hot standard carcass weight (HSCW), fat depth, butt shape, bruising, boning group, meat colour, fat colour, MSA index range and specific processor grading groups.

[0057]The master price grid 500 shown in FIG 5 comprises multiple feedlot parameters or metrics and features of each parameter for feedlots. In the example shown in FIG 5, the parameters comprise breed, market, dentition, gender, liveweight and Tropical Breed Content.

[0058] The master price grids are multidimensional master data structures for each processor/feedlot and comprise a dimension for each pricing parameter. FIG 6 shows a subset of the multidimensional master data structure of a master price grid comprising just three dimensions - a specific processor, the grading parameter of HSCW and the grading parameter of fat depth. Each price in the multidimensional master data structure subset shown in FIG 6 represents the price offered by the specific processor for a hot standard carcass weight (HSCW) range in kg for a specific fat depth in mm. Each additional grading parameter or metric adds another dimension and multiple dimensions for each processor/feedlot can be visualised as shown in FIG 7.

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2018211337 03 Aug 2018 [0059] FIG 8 illustrates the master price grid for multiple processors of agricultural commodities, such as livestock processors. The master price grid for multiple livestock feedlots is illustrated in a similar manner, but is less complex given feedlots typically have fewer grading parameters/metrics.

[0060] In some embodiments, for processors/feedlots to which grading parameters/metrics do not apply, for example, where processors/feedlots do not deal in specific breeds of cattle, the corresponding entry in the master price grid is a null value. Hence, compilation of the master price grid is efficient, covers the full range of grading parameters for processors/feedlots and can be efficiently interrogated by the computer processor to obtain the comparison of pricing from a plurality of the processors of agricultural commodities relevant to, and optimised for, the agricultural commodities each producer wishes to sell.

[0061] In some embodiments, following delivery of the agricultural commodity to the processor/feedlot, such as an agreed number of a specific type of cattle, a feedback data file having a structure similar to the master price grid is populated by the processor/feedlot and uploaded to the computer memory 102, e.g. of a server, via a feedback user interface. The feedback data file is multidimensional in that it comprises data for each animal, such data being grouped by another dimension such as sale or timestamp.

[0062] In some embodiments, and with reference to FIG 9, the data for each animal from the feedback data file are linked to the sale and the price grid under which the sale was made. The links between the file are via universally unique identifiers (UUIDs) which allow for comparison of the feedback data with the quoted price, which is based on the master grid price dimensions.

[0063] Embodiments of the invention will now be described with reference to the diagrams shown in FIGS 10 to 23.

[0064]With reference to FIG 10, according to some embodiments, a method to process agricultural commodities comprises at step 1000 a producer of agricultural commodities logging into a website via the user interface 112 via their computing device 114. The user interface 112 can be in communication with the computing device 101, such as a server, comprising the computer processor 110, computer memory 102 comprising a computer readable medium 104 storing in the master price grid 108 the pricing data 106 received from a plurality of processors of agricultural commodities or feedlots. In some embodiments, the producer requires a

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2018211337 03 Aug 2018 valid commodity producer code that can be related to food safety and/or traceability, which can be issued to the producer by a relevant government authority. For example, in Australia, the commodity producer code can be a valid Property Identification Code (PIC), which is an eight-character code allocated by the Department of Primary Industries (DPI) or an equivalent authority in each state or territory to identify a livestock-producing property.

[0065] At step 1002, the method includes the user interface 112 receiving from the producer the location of the commodity, such as livestock, the producer wishes to sell, which may be in the form of a postcode, ZIP code, or location name.

[0066] At step 1004, the method includes the user interface 112 receiving from the producer the date the commodity is to be delivered, which can be entered via a calendar function module. The date can be a single date of delivery, multiple dates of delivery or a date range, such as a specific week.

[0067] At step 1006, the method includes the user interface 112 receiving from the producer where the commodity is to be delivered, such as a processor or a feedlot. [0068] At step 1008, the method includes the user interface 112 receiving from the producer a quantity of the commodity the producer wishes to sell, such as a number of head of cattle.

[0069]At step 1010, the method includes the user interface 112 receiving from the producer data relating to the commodity to be sold. In this example, the data at step 1010 relates to grading parameters for cattle that are to be delivered to a feedlot, such as, but not limited to the liveweight, breed, gender, dentition and other characteristics of the cattle, such as certifications or an ultimate geographical destination for the cattle.

[0070] FIG 10A illustrates an example of one embodiment of the user interface 112 receiving from the producer data relating to the processing of cattle to a feedlot in accordance with steps 1002-1010.

[0071]At step 1012, the method includes the user interface 112 receiving from the producer data relating to the commodity to be sold for cattle that are to be delivered to a livestock processor. In this example, as shown in FIG 11, the data also relates to grading parameters for cattle, which can include one or more of the parameters specified in step 1010 and/or additional grading parameters, such as, but not limited to an age of the cattle and/or a feed type. The user interface 112 can receive data from the producer relating to multiple sales or lots and each sale or lot can be

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2018211337 03 Aug 2018 separately identified, for example, via a separate tab displayed on the user interface 112.

[0072] FIG 11A illustrates an example of one embodiment of the user interface 112 receiving from the producer data relating to the processing of cattle to a processor in accordance with steps 1002-1006 and 1012.

[0073] The user interface 112 can comprise a plurality of fields for receiving the data relating to the commodity to be sold. The plurality of fields can comprise fields selected from the following: a field for freeform entry of data; a menu to receive one of a plurality of predetermined selections; a slider to receive an adjustable selection within a predetermined range; or other field type.

[0074] The method includes receiving via the interface 112 a request from a producer of agricultural commodities for a comparison of pricing from a plurality of processors of agricultural commodities or feedlots for the agricultural commodities the producer wishes to sell.

[0075] The method comprises generating by the computer processor 110 a comparison of pricing from the plurality of processors of agricultural commodities based on the master price grid 108 and outputting the comparison of pricing via the interface 112. An example of the comparison of pricing generated and output in accordance with an embodiment of the present invention is shown in FIG 12. The example in FIG 12 displays the pricing offered by six different livestock processors at their respective locations for 72 grass fed, HGP free steers having a dentition of 0-2 teeth from a producer in Dalby, Queensland showing both MSA and non-MSA price calculations. The price comparison also displays other grading parameters unique to individual processors that have been factored into the calculation, such as HCSW range, fat depth range, butt shape, meat colour, fat colour and/or boning group as applicable to each processor. A distance and associated transport cost to each of the processors is calculated by the computer processor 110 and displayed for each processor.

[0076] FIG 12A shows another example of the user interface 112 outputting a comparison of pricing from a plurality of feedlots based on the master price grid 108. In this example, the pricing comparisons are based on 50 head of Hereford steers having milk teeth and being HGP free to be transported from Tenterfield and designated for the EU market. A distance and associated transport cost to each of the feedlots is calculated by the computer processor 110 and displayed for each

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2018211337 03 Aug 2018 feedlot. Delivery date cut offs or date ranges, weight ranges, optionally with limitations such as an assumed shrinkage factor and a tropical breed content are displayed for each feedlot. A reference or link to the applicable pricing data, such as pricing grid #276, upon which the pricing has been calculated is displayed for each feedlot. A date until which the prices are valid is also displayed for each feedlot. [0077]According to some embodiments, the comparison of pricing is generated based on one or more fixed or variable assumptions. The example in FIG 12 includes the assumption for each processor that there is nil bruising. Other examples of assumptions include: an average fat depth for a producer’s livestock in a certain age and weight range is y mm; the producer’s commodity have received a specific score according to a particular grading parameter. The one or more variable assumptions can be generated based on feedback data derived from one or more previous purchases by the respective processor of agricultural commodities and/or one or more previous sales by the respective producer of agricultural commodities and factored into the price calculation through machine learning processes.

[0078]According to some embodiments, the comparison of pricing is optimised to assist the producer in making better decisions relating to commodity production. For example, the comparison can be ranked in order of highest pricing for the producer. Alternatively, the comparison can be ranked in order of one or more of the grading parameters, such as a fat depth, HCSW, butt shape etc..

[0079]The user interface 112 can comprise one or more fields for varying, adjusting or filtering the data relating to the commodity to be sold in real time to adjust the price comparisons in real time. In the examples shown in FIGS 12 and 12A, the user interface 112 comprises a slider to receive an adjustable selection within a predetermined range for the live weight of the livestock and a slider to adjust the fat depth of the livestock. The user interface 112 comprises a menu to receive one of a plurality of predetermined selections for the butt shape of the livestock. The user interface 112 comprises an adjustable field relating to transport costs including a number of trucks required to transport the quantity ofthe commodity to be sold and a cost per kilometre. Other adjustable grading parameters are shown in FIG 13. It will be appreciated that other fields and data can be adjusted which, once adjusted, can change the processors/feedlots displayed in the price comparison and/or the order of the processors/feedlots displayed.

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2018211337 03 Aug 2018 /OOSOJOnce the computer processor 110 receives the selection of the processor or feedlot from the computing device 114 of the producer via the user interface 112, the system of the present invention facilitates the transaction or sale of the commodity between the producer and the processor/feedlot, as illustrated in FIGS 14-18. According to some embodiments, the producer creates an account, or logs in if already created, such that producer details (company name, ABN, contact details and bank account details etc.) are received by the computer processor 110, as shown in FIG 14. With reference to FIG 15, a valid Property Identification Code (PIC) is entered and photos and/or videos of the cattle being sold are submitted by the producer and received by the computer processor 110. Contract terms between the processor/feedlot are also agreed upon and recorded by the computer processor 110. With reference to FIG 16, a summary of the sale information is generated by the computer processor 110 and upon receipt of a sale request submitted by the producer, confirmations of the consignment request are sent to both the producer and processor/feedlot, such as via email. The processor/feedlot can subsequently accept the consignment request in its submitted form, reject the consignment request with one or more reasons, accept the consignment request with amended or additional conditions, such as, but not limited to a different delivery date, a request for further information, such as more photos/videos or the like. The producer will receive notifications accordingly and can submit further information where requested. If the processor/feedlot ultimately accepts the consignment, with reference to FIG 17, confirmations are sent to both the processor/feedlot and the producer, which are displayed/viewable in their respective dashboards. The confirmations are tailored according to the processor, feedlot and producer. The producer subsequently submits the necessary documentation. Once the transaction process is complete, the commodity is delivered according to the transaction conditions to the processor/feedlot. All transactions and communications are recorded by the computer processor 110. It will be appreciated that the general flow diagrams in FIGS 14-18 illustrate one embodiment and according to other embodiments the steps may be performed in a different order. It will also be appreciated that some of the steps will be performed substantially simultaneously.

[0081]\Ntih reference to FIG 18, the producer can book transportation via the system

100 using the data submitted via the user interface 112. The data is submitted to a

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2018211337 03 Aug 2018 transport provider who can, via the system 100, accept the job, reject the job or accept the job with amended details, such as a different delivery date.

[0082] It will be appreciated that according to a further form, the present invention resides in an apparatus in the form of computing device 101 to process agricultural commodities, such as, but not limited to livestock. The apparatus comprises the computer memory 102 storing the pricing data 106 in the master price grid 108 related to the processing of agricultural commodities. The pricing data is received from the plurality of processors of agricultural commodities or feedlots, as described herein, and the master price grid 108 stores the pricing data in a multidimensional master data structure for each processor/feedlot. The computer processor 110 is in communication with the computer memory 102 and the interface 112 is in communication with the computer processor. As described herein, the computer processor 110 receives via the interface 112 a request from a producer of agricultural commodities for a comparison of pricing from a plurality of processors of agricultural commodities, for agricultural commodities the producer wishes to sell. The computer processor 110 generates a comparison of pricing from the plurality of processors of agricultural commodities based on the master price grid and outputs the comparison via the interface 112.

[0083] It will be appreciated that according to a further form, the present invention resides in the computer readable medium 104 having stored thereon instructions executable by the computer processor 110 to cause storing in the computer memory 102 pricing data 106 related to the processing of agricultural commodities. The pricing data 106 is received from the plurality of processors of agricultural commodities or feedlots and the pricing data is stored in the master price grid 108 storing pricing data in a multidimensional master data structure for each processor. The instructions executable by the computer processor 110 cause receiving via the interface 112 in communication with the computer processor 110, the computer processor in communication with the computer memory 102, a request from a producer of agricultural commodities for a comparison of pricing from a plurality of processors of agricultural commodities for agricultural commodities the producer wishes to sell. The instructions executable by the computer processor 110 cause generating by the computer processor 110 a comparison of pricing from the plurality of processors of agricultural commodities based on the master price grid 108 and outputting of the comparison via the interface 112.

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2018211337 03 Aug 2018 [0084] It will be further appreciated that according to a further form, the present invention resides in the user interface 112 to facilitate processing of agricultural commodities. As described herein, the user interface 112 comprises a plurality of fields to receive data relating to a request from a producer of agricultural commodities for a comparison of pricing from a plurality of processors of agricultural commodities or feedlots for agricultural commodities the producer wishes to sell. The user interface 112 comprises a plurality of fields to output the comparison of pricing from the plurality of processors of agricultural commodities. As described herein, the comparison is generated by the computer processor 110 based on the master price grid 108 stored in the computer memory 102 in communication with the computer processor 110. The master price grid 108 stores the pricing data 106 in a multidimensional master data structure for each processor, the pricing data related to the processing of agricultural commodities and received from a plurality of processors of agricultural commodities or feedlots.

[0085] With reference to FIGS 19-23, in some embodiments, following delivery of the agricultural commodity to the processor/feedlot and processing, a feedback data file having a structure similar to the master price grid is populated by data from the processor/feedlot. The data from processors can include a carcass feedback results table, a carcass feedback summary and a payment summary (e.g. a Recipient Created Tax Invoice (RCTI)). Similar data relevant to feedlots can be received from feedlots. In some embodiments, the data can be provided by the processor/feedlot in PDF format and uploaded to the computer memory 102, e.g. of a server, via a feedback user interface. The computer processor 11 can convert the data from the processor/feedlot into a multidimensional feedback data file that comprises data for each animal, grouped by any parameter, relating to the sale, such as processor, location, dressing percentage, etc.. The feedback data file can be provided to processors/feedlots, for example, for their respective dashboards on their user interfaces and can also be provided to the producer via email and/or via the dashboard on the user interface 112, or by other means.

[0086]As shown in FIG 20, the feedback data can include, for example, graphical representations of different prices per unit weight as percentages of the total consignment and/or a distribution of liveweight for the total consignment in four quartiles with an average.

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2018211337 03 Aug 2018 [0087]As shown in FIGS 21-23, the feedback data can include for example, graphical representations of one or more of the following: different prices per unit weight as percentages of the total consignment; a distribution of HSCW for the total consignment in four quartiles with an average; different butt shapes and related deductions; different fat depths and related deductions; deductions for bruise scores, total deductions expressed as a price per unit weight; compliance and noncompliance with accreditations and/or company requirements; plots of one commodity variable against another, such as, but not limited to price per unit weight against accreditation index, variation of average price per unit weight over time, variation of average dressing percentage over time, variation of average HSCW over time, variation of average price per unit weight deductions over time. Such feedback can be compiled into a document and sent to the producer and/or be visible on the producer’s feedback analytics dashboard on the user interface 112. The user interface 112 enables the producer, via their computing device 114, to conduct further analysis and manipulation of the feedback data.

[0088] Embodiments of the present invention utilise machine learning to analyse the data provided by the processors/feedlots to automatically generate recommendations for the producers to assist the producers in improving their commodities, such as improving the profitability of their livestock herd. Such recommendations can include, but are not limited to changes to breeding and/or feeding operations.

[0089] Hence, the present invention addresses or at least ameliorates one or more of the aforementioned problems by providing a system, method, apparatus, user interface and computer readable medium to process agricultural commodities, which utilises a master price grid which stores pricing data in a multidimensional master data structure that enables producers of agricultural commodities to easily obtain accurate price comparisons and feedback data from a plurality of processors of agricultural commodities and/or feedlots. The present invention avoids the need for producers to repeatedly obtain up to date pricing data from processors/feedlots and enables processors/feedlots to readily reach producers with the pricing data. Grading parameters can be adjusted in real time to obtain price comparisons in real time in an efficient and transparent manner, which also addresses concerns of various governing bodies in commodities industries. The present invention accommodates the wide range of grading parameters employed by different processors/feedlots but

3269217vl

2018211337 03 Aug 2018 enables a fair and transparent comparison to be calculated. Transport costs are also factored into the calculation and the structured feedback data provides valuable analysis of processed commodities to assist producers in improving their operations. The feedback can be tailored to each producer enabling producers to make more informed investment and production decisions to increase the quality and profitability of their commodities. Embodiments of the present invention can also integrate with and complement existing platforms.

[0090] In this specification, the terms “comprises”, “comprising” or similar terms are intended to mean a non-exclusive inclusion, such that an apparatus that comprises a list of elements does not include those elements solely, but may well include other elements not listed.

[0091] The reference to any prior art in this specification is not, and should not be taken as, an acknowledgement or any form of suggestion that the prior art forms part of the common general knowledge.

[0092] Throughout the specification the aim has been to describe the invention without limiting the invention to any one embodiment or specific collection of features. Persons skilled in the relevant art may realize variations from the specific embodiments that will nonetheless fall within the scope of the invention.

3269217vl

Claims

2018211337 03 Aug 2018

1. A system to process agricultural commodities, the system comprising:

a computer memory storing pricing data in a master price grid related to the processing of agricultural commodities, said pricing data received from a plurality of processors of agricultural commodities and/or feedlots, said master price grid storing pricing data in a multidimensional master data structure for each processor/feedlot;

a computer processor in communication with the computer memory; and an interface in communication with the computer processor to:

receive a request from a producer of agricultural commodities for a comparison of pricing from a plurality of processors of agricultural commodities and/or feedlots for agricultural commodities the producer wishes to sell; and output the comparison of pricing from the plurality of processors of agricultural commodities and/or feedlots;

wherein the comparison is generated by the computer processor based on the master price grid.
2. A method to process agricultural commodities, the method comprising:

storing in a computer memory pricing data related to the processing of agricultural commodities, said pricing data received from a plurality of processors of agricultural commodities and/or feedlots, said pricing data stored in a master price grid storing pricing data in a multidimensional master data structure for each processor/feedlot;

receiving via an interface in communication with a computer processor, the computer processor in communication with the computer memory, a request from a producer of agricultural commodities for a comparison of pricing from a plurality of processors of agricultural commodities and/or feedlots for agricultural commodities the producer wishes to sell;

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2018211337 03 Aug 2018 generating by the computer processor a comparison of pricing from the plurality of processors of agricultural commodities and/or feedlots based on the master price grid; and outputting the comparison via the interface.
3. An apparatus to process agricultural commodities, the apparatus comprising:

a computer memory storing pricing data in a master price grid related to the processing of agricultural commodities, said pricing data received from a plurality of processors of agricultural commodities and/or feedlots, said master price grid storing pricing data in a multidimensional master data structure for each processor/feedlot;

a computer processor in communication with the computer memory; and an interface in communication with the computer processor to:

receive a request from a producer of agricultural commodities for a comparison of pricing from a plurality of processors of agricultural commodities and/or feedlots for agricultural commodities the producer wishes to sell;

generate by the computer processor a comparison of pricing from the plurality of processors of agricultural commodities and/or feedlots based on the master price grid; and output the comparison via the interface.
4. A computer readable medium having stored thereon instructions executable by a computer processor to cause:

storing in a computer memory pricing data related to the processing of agricultural commodities, said pricing data received from a plurality of processors of agricultural commodities and/or feedlots, said pricing data stored in a master price grid storing pricing data in a multidimensional master data structure for each processor/feedlot;

receiving via an interface in communication with a computer processor, the computer processor in communication with the computer memory, a request from a

3269217vl

2018211337 03 Aug 2018 producer of agricultural commodities for a comparison of pricing from a plurality of processors of agricultural commodities and/or feedlots for agricultural commodities the producer wishes to sell;

generating by the computer processor a comparison of pricing from the plurality of processors of agricultural commodities and/or feedlots based on the master price grid; and outputting the comparison via the interface.
5. A user interface to facilitate processing of agricultural commodities, the user interface comprising:

a plurality of fields to receive data relating to a request from a producer of agricultural commodities for a comparison of pricing from a plurality of processors of agricultural commodities and/or feedlots for agricultural commodities the producer wishes to sell; and a plurality of fields to output the comparison of pricing from the plurality of processors of agricultural commodities and/or feedlots;

wherein the comparison is generated by a computer processor based on a master price grid stored in a computer memory in communication with the computer processor, the master price grid storing pricing data in a multidimensional master data structure for each processor/feedlot, the pricing data related to the processing of agricultural commodities and received from a plurality of processors of agricultural commodities and/or feedlots.
6. The system of claim 1, method of claim 2, apparatus of claim 3, computer readable medium of claim 4 and/or user interface of claim 5, wherein the multidimensional master data structure for each processor comprises a dimension for each pricing parameter.
7. The user interface of claim 5 or 6, wherein the plurality of fields for receiving data comprises fields selected from the following: a field for freeform entry of data; a

3269217vl

2018211337 03 Aug 2018 menu to receive one of a plurality of predetermined selections; a slider to receive an adjustable selection within a predetermined range.
8. The system, method, apparatus, computer readable medium and/or user interface of any preceding claim, wherein the data relates to grading parameters for grading the agricultural commodities.
9. The system, method, apparatus, computer readable medium and/or user interface of any preceding claim, wherein the comparison of pricing is optimised to assist the producer in making better decisions relating to commodity production.
10. The system, method, apparatus, computer readable medium and/or user interface of claim 9, wherein the comparison of pricing is optimised by one of the following: ranking the comparison in order of highest pricing for the producer; ranking in order of a selected grading parameter.
11. The system, method, apparatus, computer readable medium and/or user interface of any preceding claim, wherein the comparison of pricing is generated based on one or more fixed or variable assumptions.
12. The system, method, apparatus, computer readable medium and/or user interface of claim 11, wherein the one or more variable assumptions are generated based on one or more of the following: feedback data derived from one or more previous purchases by the respective processor of agricultural commodities; one or more previous sales by the respective producer of agricultural commodities.
13. The system, method, apparatus, computer readable medium and/or user interface of any preceding claim, wherein a multidimensional feedback data file is generated comprising data for each commodity.
14. The system, method, apparatus, computer readable medium and/or user interface of claim 13, wherein the data for each commodity in the multidimensional feedback data file is generated for each animal, such data being grouped by a parameter relating to the sale.

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2018211337 03 Aug 2018
15. The system, method, apparatus, computer readable medium and/or user interface of any preceding claim, wherein the data for each animal in the feedback data file are linked to the sale and the price grid under which the sale was made via universally unique identifiers (UUIDs).
16. The system, method, apparatus, computer readable medium or user interface of any preceding claim, wherein a price grid input interface is provided which receives the pricing data from the processors/feedlots.

17. A user interface to facilitate processing of agricultural commodities, the user interface comprising:

a plurality of fields to output a comparison of pricing from a plurality of processors of agricultural commodities and/or feedlots for agricultural commodities a producer of agricultural commodities wishes to sell;

wherein the comparison is generated by a computer processor based on data received from the producer about the agricultural commodities the producer wishes to sell and a master price grid stored in a computer memory in communication with the computer processor, the master price grid storing pricing data in a multidimensional master data structure for each processor/feedlot, the pricing data related to the processing of agricultural commodities and received from a plurality of processors of agricultural commodities and/or feedlots.

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Editorial Note

There are 23 pages of drawings only

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102

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Processor Metrics Group Datatype Type Example Dataset Cattle type Discrete String Price Grass Fed, Grain Fed (100. 70,60 day) Market Discrete String Price Angus, Organic, PCAS, EU, HGP Free, Free Range Dentition Discrete Integer* Price 0 only, 0-2, 3-4, 5-6, 7, 8 Gender Discrete String Price Steer, Female, Bull Liveweight N/A N/A Price HSCW/52% HSCW Continuous Float Price 0-100,100-120,120-140,...,340+ P8 Fat Depth Discrete* Integer Price 0-5, 5-22, 23-32, 33-43, 43+ Butt Shape Discrete Character* Deduction A-C, D, E Bruising Discrete* Integer Deduction 0, 1-4 Boning Group Discrete* Integer Deduction 1-8, 9-11 Meat Colour Discrete String* Deduction 1A, 1B, 1C, 2, 3, ..., 1 Fat Colour Discrete Integer Deduction 0-9 MSA Index Range Discrete Continuous Cut-off 0-100 Scale, (e.g > 52.5 = MSA, ELSE Non-MSA) Nolans Grade Group Discrete String Deduction 1,2,3,4,5,6

FIG 4

Feedlot Metrics Group Datatype Type Example Dataset Breed Discrete String Price Angus. Angus X, Hereford, British Bred. Wagyu, Wagyu X, Other Market Discrete String Price Organic, PCAS, EU, HGP Free, Free Range Dentition Discrete Integer* Price 0 only, 0-2,3-4,5-6,1,8 Gender Discrete String Price Steer, Heifer, Cow Liveweight Continuous Float Price 0-100,100-120,120-140,..., 340+ Tropical Breed Content (TBC) Continuous Fioat Price 0-12.5%, 12.6-50%, 50.1-100%

FIG 5

Processor 1 HSCW (kg) 260 - 280 280.1 - 300 300.1 - 320 Fat Depth (mm) 14 $4.SO $5.00 $5.00 15 $4.90 $5.10 $5.10 16 $4.90 $5.10 $5.10

FIG 6

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saleuuid processoruuid ammaluuid HSCW Fat Depth ... Price sale 001 prooessorOOl cowO01 280 1G 1000 sale 001 prooessorOOl cow002 285 17 1100

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PIC Number

Producer selects PIC Number of property cattle are leaving.

k_2

Feedlot - Photos/videos Producer uploads photos/videos of cattle if * selling to a feedlot (5x photos and 1x video required per 50 cattle) which will be stored on the AgCentre platform

Contract particulars

Producer makes acknowledgements specific to each processor/feedlot contract. Teys example below:

• I have read and understood the terms and conditions of the Teys Australia Livestock Contract * I declare that I have read and understood the Teys Australia Vendor Animal Welfare Requirements and agree to abide these standards for all cattle consigned to Teys Australia.

• For grain fed cattle:

o Name of Feedlot o Feedlot AUSMEAT Accreditation number o Number of days on feed at time of delivery * For grass fed cattle -1/We declare that the animals have never been:

o confined to a pen for the purpose of intensive feeding;

o supplementary fed grain or grain by-products; and o treated with antibiotics.

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Confirmation PDF

TTca information and links to these PDFs will be contained on their in drwdual dashboards.

Processor Processors PDF also contains producer contact details.

Feedlot

Feedlot's PDF also contains:

• producer contact details; and • Finks to re-visit photos/videos

Both parties receive confirmation PDF. containing:

• inputs provided by producer:

• estimated price range and average price (with appropriate disclaimers); and • oonsig n m ent requ est number.

This data will also be mirrored cn their “My Sales' and “Detailed Sale infdrmatiDn' pages on their dashboards.

Producer

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co py of te rms and cond itions of processor! feedlot:

conta ct details of p ereon nominated from processor/feedlot;

* p rocessor/fee d lot g rid with highlighted section corresponding to their inputs: and details about how producer can submit related documents through Ag Centre (NVD, eDECs, EU-NVD, MSA,

NFAS, CVD etc) and guidelines on how to complete these documents.

Producer submits all required documents.

FIG 17 slaughtered at processor.

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Non-MSA Related Data

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HSCW (kg)

Distribution of HSCW for total consignment showing 4 quartiles and average.

Butt Shape showing deductions in increments from processor's grid expressed as % of total consignment (A-E).

PB Fat Depth showing deductions in increments from processors grid, expressed as % of total consignment (0-43+).

A ιΊ 0 OL , -°C X ³ \ 1411 Tt - IUC-

Bruise Score showing deductions in increments from processors grid, expressed as % of total consignment (0-9).

for each body expressed as % of total consignment

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FIG 21

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MSA Data

2018211337 03 Aug

ΜΞΑ&Γ

CoSpec'i

Ccmpfliant _L Not jcmpliant

MSA compliance expressed % of total consignment, as either:

- MSA compliant

- MSA and company specification compliant

- Not MSA compliant.

MSA Index

Distribution of MSA Index for total consignment showing (30-80 expressed to 2 decimal places).

Tjihto myMSA to review specifics of MSA data (i.e. to determine why certaii animals (topped out of MSA).

MSA Index MSA Index vs $ kg showing distribution and correlation.

FIG 22

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2018211337 03 Aug 2018

Comparison Against Producer Profile Data

I I I I I I I I

Time

Average Sikg compared across previous consignments (or the producers steers, heifers, cows and bulls.

no .c 35

1/1 Φ

L_ _

Q

O -

Time

Average dressing percentage compared across previous consignments for the producer's steers, heifers, cows and bulls.

Average HSCW compared across previous consignments for the producer's steers, heifers, cows and bulls.

Average S/kg deductions from total deductions from PS Fat Depth, Butt Shape and Bruising compared across previous consignments for the producers steers, heifers, cows and bulls.

My Feedback will also contain long term feedback κ of p roducer s data a c ros s all sales on Ag Centre's platform.

FIG 23

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