2015 Autumn - From Little Data Big Data Grow

Please note single Journal articles are not available in hard copy.

To download the free editorial articles click here

This catalog has no sub-catalogs.

Farm Policy Journal: Vol 12 No 1 2015 Autumn - Full Journal - From little data big data grow

Australian Farm Institute (2015), From little data big data grow, Farm Policy Journal, Vol. 12, No. 1 - Autumn Quarter, Surry Hills, Australia 
ISSN 1449–2210 (Print)
ISSN 1449–8812 (Web)

$60.50


FPJ1201B - Sonka, S (2015), Big Data: From Hype to Agricultural Tool

Sonka, S (215), Big Data: From Hype to Agricultural Tool, Farm Policy Journal, Vol. 12, No. 1, Autumn Quarter, pp. 1-9, Surry Hills, Australia

ISSN 1449–2210 (Print)

ISSN 1449–8812 (Web) 

Big data appears to be at the apex of its ‘hype cycle’, meaning that the media’s breathless and uncritical enthusiasm for this term may be starting to diminish. When technology innovations reach this point, they enter a phase where investment is driven more by serious, critical analysis than by the desire to ‘have the newest thing’. This paper explores the dynamics underlying big data’s business potential as it relates to the food and agricultural sector.
First, let’s recognise that adoption of information and communication technology (ICT) has been a nearly constant feature in agriculture, business and society for the last three decades. So what is different about big data?
•    Big data is much more a capability than a single entity. It is the capability to extract information and generate insights where previously it was economically, if not technically, impossible to do so.
•    Big data has three key dimensions – volume, velocity, and variety.
•    The introduction of low-cost, novel sensing technologies (eg drones, satellites, cell phones) is a major means by which data (never before available because of the high cost of data capture) now can be gathered.
•    Analytics, the ability to make sense of massive amounts of highly variable types of data, is a key source of the power of big data.
So, how might big data capabilities enter the food and agricultural sector?
•    Tracking consumers, both in terms of shopping and purchasing behaviours as well as perceptions extracted from social media, has been an active area of big data application. These capabilities also will be employed to optimise supply chains, extending to agricultural production.
•    Numerous research and development (R&D) initiatives are underway with a focus on greatly increasing the productivity of agricultural production. Today these R&D efforts tend to be concentrated on the underlying biology of crop and livestock production. What is different about these efforts is that they are occurring on the farm, not in the lab or the experimental plot.
As these linkages are formed, key strategic questions will need to be addressed, such as:
•    What value, if any, is created by employing big data tools to optimise performance among and between these many firms?
•    If value is created, what organisational structure in agriculture would facilitate effective initiation and operation of such systems? 

$12.10


FPJ1201D - Rowe, J & Banks, R (2015), Sheep Industry Productivity – the Role of Genomics and Digital Data

Rowe, J, Banks, R (2015), Sheep Industry Productivity – the Role of Genomics and Digital Data, Farm Policy Journal, Vol. 12, No. 1, Autumn Quarter, pp. 21-31, Surry Hills, Australia

ISSN 1449–2210 (Print)

ISSN 1449–8812 (Web) 

As the sheep industry moves from focusing on wool production as its primary economic driver to the current situation where both sheep meat and wool are of similar importance, the challenge to maintain genetic improvement is significantly more complex. Selection for increased wool income only needs to focus on fleece weight and fibre diameter. Both parameters are easily measured and highly heritable. However, balanced ‘sheep’ production involves selection for increased reproductive efficiency and improved carcase characteristics as well as continued selection for wool traits. The sheep industry also has to breed for resistance to parasite due to the need to stop mulesing and the increasing problem of worm resistance to chemical drenches.
This paper focuses on three initiatives that are contributing to transformation of the sheep industry: genomic technologies; data management and skills development. Genomic technologies enable fast and well-balanced genetic gain, particularly when difficult to measure traits such as reproduction, parasite resistance and carcase characteristics are so important. Prediction of breeding values, based on DNA analysis, relies on calibration using large numbers of animals measured for all traits of interest. Cost-effective measurement of phenotypic parameters is therefore essential for genomic technologies. The development of automated and semi-automated measurement of production and carcase characteristics, combined with wireless data transfer and cloud-based computing, provide complimentary technologies to support the development and use of genomics.
Efficient data capture and its effective use also underpins improved productivity through better management and value-based supply chain transactions. Targeted training and skills development is the third component required to ensure that the sheep industry exploits the transformative and interlinked technologies of genetics and digital data.

$12.10


FPJ1201E - Eastwood, C & Yule, I (2015), Challenges and Opportunities for Precision Dairy Farming in New Zealand

Eastwood, C, Yule, I (2015), Challenges and Opportunities for Precision Dairy Farming in New Zealand, Farm Policy Journal, Vol. 12, No. 1, Autumn Quarter, pp. 33-41, Surry Hills, Australia

ISSN 1449–2210 (Print)

ISSN 1449–8812 (Web) 

This study aimed to identify the key challenges and opportunities for New Zealand farmers using precision dairy technologies. A range of dairy farmers, researchers and service providers were interviewed using a semi-structured interview method. Interviews were recorded and subsequently transcribed for qualitative analysis. An open coding process was used to identify main themes across the case studies. The information gathered from the precision dairying community provided insights which were used to identify areas for future research and development. Findings from the study indicated that precision technologies had potential benefits for an industry with larger farms, scarce labour and increasing management complexity. A number of issues also existed around technology and management adaption, the level of information and communication technologies (ICT) skills, and engagement of farmers. There was also uncertainty around how to unlock potential benefits, some problems were identified around staff-technology interactions, and limited backup and after sales support from the service sector. The analysis identified eight key questions concerning farmer expectations and experiences with precision dairy technology, along with the role of service providers, and factors involved in successful and unsuccessful adoption. The questions were used to propose a research agenda based around five themes aimed at driving a coordinated precision dairy research program. These themes were:
•    Where does precision dairy technology fit in New Zealand dairy systems?
•    Are the New Zealand dairy farmers ready to adopt new technologies?
•    How can trust and confidence in new technologies be built while managing expectations?
•    What are the service sector roles around precision dairying?
•    Where does industry engagement meet private delivery in precision dairy farming?
The paper describes the processes used in the case study work as well as farmer feedback on their experiences. 

$12.10


FPJ1201F - Bennett, JM (2015), Agricultural Big Data: Utilisation to Discover the Unknown and Instigate Practice Change

Bennett, JM (2015), Agricultural Big Data: Utilisation to Discover the Unknown and Instigate Practice Change, Farm Policy Journal, Vol. 12, No. 1, Autumn Quarter, pp. 43-50, Surry Hills, Australia

ISSN 1449–2210 (Print)

ISSN 1449–8812 (Web) 

This short discussion paper considers the current agricultural extension shortfalls and considers how agricultural big data might be used to change the way unknown on-farm issues are identified and managed. The premise being that if unknown issues are brought to light on an individual basis, and potential solutions discussed within trusted networks, that this will enhance the incidence of practice change. Knowledge is discussed in terms of that which is known and that which is not, with the discussion focused on the use of data to help realise unknown knowledge and thus determine on-farm issues, as well as predict cause and effect. The paper draws on the concepts of big data and networked learning to provide a base model on which digital platforms might operate to provide efficiencies in the on-farm decision-making process, as well as enhance the power of those decisions.

$12.10


FPJ1201C - Poppe et al. (2015), A European Perspective on the Economics of Big Data

Poppe, K, Wolfert, S, Verdouw, C, Renwick, A (2015), A European Perspective on the Economics of Big Data, Farm Policy Journal, Vol. 12, No. 1, Autumn Quarter, pp. 11-19, Surry Hills, Australia

ISSN 1449–2210 (Print)

ISSN 1449–8812 (Web) 

Modern information-based technologies, such as self-driving tractors, GPS (global positioning systems), robot milking machines, automated egg production, drones, satellite data and social media, will change farm practices and agricultural structures and contribute to the prosperity and resilience of farming systems. Food chains will not only become much more data-driven but will also move away from a situation characterised by a low level of data integration. This will have a significant impact on such issues as sustainability, food safety, resource efficiency and waste reduction.
The economic and social effects of such developments are still to be explored. At first sight they could lead to more closely integrated supply chains that make the farmer act simply as a franchisee with limited freedom, but the opposite could be true. Farmers could be empowered due to greater transparency and easier options for direct sales in consumer food webs (using social media and smart solutions for the ‘last mile’ delivery). Therefore we can see conflicting pressures between the globalisation and localisation of supply chains.
As with previous technological developments, not all farmers will invest in new skills and where technologies are labour saving, farms will get bigger. Some farms or regions will become less competitive if the basic infrastructure (eg broadband internet or GPS systems) is lacking. Competition between advisors could increase, if they are able to serve farmers digitally. In addition, part of such value added activities may move from the most remote rural areas to regions with clusters of knowledge and could also become more international in nature.
A major issue is that information and communication technology (ICT), combined with higher food prices and demographic changes could fundamentally shift the competitive advantage from family farms to more industrial holdings, leading to radical structural change in agriculture.

$12.10


Purchase a
membership and gain
unlimited access to
our journal and
research library

LEARN MORE BECOME A MEMBER

Purchase our
latest report

READ MORE