Driving Farm Innovation through Knowledge Transfer

Driving Farm Innovation 

through Knowledge Transfer 

Applying the learning from the Agricultural Innovation 

Support programme 

What are the implications for agricultural extension? 

Friday 23 October 2015 

09.00-16.00 

UCD, O’Brien Centre for Science 

Web link to Conference Papers will be 

circulated to all participants post-event.

Conference Programme 

09.00 Registration and walkabout / viewing of posters with research findings 

09.30 Conference Opening: Professor Gerry Boyle, Director, Teagasc 

09.45 Keynote address: Teagasc Advisor Christy Watson on the challenges and opportunities facing Farm Advisors 

10.15 SESSION 1 

Challenges and 

Opportunities to improve 

Farm management and 

Productivity 

11.00 Tea/Coffee 

Chair: Michael Brady, 

Agricultural Consultant 


Can we categorise Farmers 

towards a better meeting of 

their needs? 

Chair: Professor Joe Mannion, 

Retired Dean of Agriculture, 

UCD 


Can we reach out more 

effectively to the broader 

population of farmers? 

13.00 Lunch Break 

Chair: Mark Moore, 

Teagasc Communications 


How can we better support 

the next generation of young 

farmers? 

Chair: Austin Finn, 

Land Mobility Programme 

Manager, Macra na Feírme 

15.00 SESSION 5: 

How can we be more 

effective in securing Ireland’s 

Environmental Credentials? 

Chair: Dr Helen Sheridan, 

UCD 

15.45 Conference Close 

Teri Acheson 

based on her completed work on herd health 

planning 

Kaitlynn Glover 

based on her completed work on pig record 

keeping 

Sean Cooney 

based on his completed work on the use of 

performance recorded rams in the sheep sector 

Zerlina Pratt 

based on her completed study to identify 

categories of KT need among populations of 

farmers 

Eilish Burke 

based on her completed study on the KT needs 

of high profit dairy farmers 

James Dunne 

based on his completed study on the KT needs 

of drystock farmers at different levels of 

profitability 

Oisin Coakley 

based on his ongoing work on ‘hard to reach’ 

dairy farmers 

Owen Kehoe 

based on his completed study on the use of 

Local Radio in knowledge transfer 

Tomas Russell 

based on his ongoing research on farm 

succession and inheritance 

John Kelly 

based on his completed research on practical 

ways for Teagasc to engage with recent 

Agricultural College graduates from graduation 

to farm ownership 

Fergal Maguire 

based on his completed work on how to 

maintain commonage land in Co Wicklow in 

good agricultural and environmental condition 

Meabh O’Hagan 

based on her ongoing work on assessing 

farmers perception of green house gas (GHG) 

Emissions and effective KT interventions 

to support practice change and emissions 

reductions. 

Paul Newman 

based on his ongoing study of understanding 

the stage in the adoption process when farmers 

‘give up’ on grass measuring technology 

John Greaney 

based on his ongoing study of the use of farm 

financial tools by dairy farmers and advisors 

Q&A and Panel Discussion 

Conor Kavanagh 


dairy farmers 

Tom Deane 


drystock farmers 

Joanne Masterson 

based on their ongoing work on ‘hard to reach’ 

drystock farmers 


Sean Mannion 

based on his ongoing reseach on the key 

ingredients for effective KT Events for farmer 

learning and adoption 


Colm Doran 

based on his completed work on Moodle 

based online teaching and developing distance 

training models in horticulture 

Michael Keane 

based on his completed work on practical 

supports for the promotion and support of 

non-family farm partnerships in Irish dairy 

farms 


John Ryan 

on his ongoing work on Soil Fertility Knowledge 

Transfer initiatives to support achievement of 

high performance on farms 

Q&A and Panel Discussion

Improving farmer engagement in herd health planning and 

Teri Acheson Alan Renwick¹ 

biosecurity on beef farms through the BETTER farm programme 

Adam Woods² 

1.School of Agriculture and Food Science UCD, Belfield, Dublin 4. 

2.Teagasc Ballyhaise, Co. Cavan. 

Background / Context: Prevention and control of animal disease at farm level is of major importance in agriculture. Previous studies show 

deficiencies in herd health and biosecurity on Irish farms. This study offers the chance to increase farmers awareness to key methods that will help 

improve understanding and participation in this area. Working with the Teagasc/Irish farmers journal BETTER farm beef programme provides the best 

transfer tool for these improvements in the sector. 

Objectives 

‣ Establish current uptake of biocontainment 

(BC) and herd health 

(HH) practices at farm level 

‣ Explore the effectiveness of 

technology transfer through the 

BETTER farm programme 

‣ Identify ways to improve uptake of 

main BC and HH practices 

‣ Tailor make a method/model to 

improve knowledge transfer and 

thus provide recommendations to 

key stakeholders 

Sources of data 

Survey 

Booklet 

Methods of 

created 

data 

collection 

Survey 

Methodology 

Non BETTER farm discussion 

BETTER farm discussion groups 

groups 

(Study group) 

(Control group) 

18 groups (N=180) 18 groups (N=180) 

10 people selected 

(1 BETTER farm + 9 others) 

10 people selected 

Bio-containment and Vaccination 

Vaccination & 

Bio-containment practices booklet 

- 

Based on views of protocol 

Identify any changes since 

previous survey 

Key Findings (N=167) 

85% of respondents agreed that biosecurity and bio-containment 

are important in preventing disease outbreak at farm level. 

63% respondents have no HH plan in place currently. 

"Unnecessary as no previous cases“, is the main reason for not 

vaccinating: e.g. 42% respondents reported this for Lepto 

Skills such as booster vaccinations, correct timing and use of the 

correct equipment were identified as ‘poor’ by respondents 

Farmers with a HH plan had more BC practices in place. 

‘Good hygiene’ and ‘buying from herds with high HH status’ were 

identified as the most useful BC practices. 

Booklet (n=49): 

Utilisation of the booklet by farmers 

86% consulted the booklet at some stage during the study. 

Fluke & Worm (51%), clostridial diseases (43%) and calf pneumonia (41%) 

were selected as the top three sections of the booklet to be used. 

A positive outcome to the booklet was achieved, as moderate (40%) to large 

(24%) increase in awareness of BC and vaccinations was documented by 

farmers who used the booklet. 

32% felt it had increased their understanding of vaccines and simplified 

vaccination practice. . 

Key Conclusions 

Overall there is a positive approach to HH on beef farms in Ireland, however current practices in place did not match the optimal level 

that is needed to control and prevent disease spread. 

No significant difference in HH was found between the BETTER and non-BETTER farm groups, this indicated that although HH was a 

key component of the BETTER farm programme it had no impact on the level of uptake. 

A gap in the use of vaccination as a control method for disease spread was identified. This was principally due to a lack of clinical 

cases identified at farm level. 

Those with a HH plan in place were more pro-active with BC practices and vaccinations at farm level. 

The booklet was considered a beneficial knowledge transfer tool to have for sourcing information and for guidance when carrying out 

vaccinations. Overall it increased awareness of vaccinations and BC practices and encouraged uptake of practices at farm level. 

Masters in Agriculture Innovation Support - This project is funded by Teagasc under the Walsh Fellowship Scheme

Record Keeping in Irish Pig Production: Factors Affecting 

Enrolment in Teagasc PigSys/ePM Recording Programmes 

K. E. Glover 1,2* , J. Kinsella 1 , and C. Carroll 2 

1 

School of Agriculture and Food Science, University College Dublin, Belfield, Dublin 4, Ireland; 

2 

Pig Development Department, Teagasc Animal and Grassland Research and Innovation Centre, Moorepark, Fermoy, Co. Cork, Ireland; 

*kaitlynn.glover@gmail.com 

Context 

Market factors and policy-driven regulations in the pig sector have significantly altered the profile of the typical Irish pig farm 

over the last decade. Production technology developments have made the sector more productive, but management technologies 

have failed to keep pace. Among them, record keeping technologies have undergone little amendment, prompting the necessity 

for significant review. Coupled with a renewed international interest in knowledge transfer (KT), this study seeks to examine the 

advisory role in management technology adoption and use, and other factors affecting on-farm adoption of recording tools. 

1. Objectives 

This study seeks to identify potential relationships between sociological and 

environmental factors and record keeping on Irish pig farms. The Teagasc 

PigSys recording system operates in an online platform (e-Profit Monitor) 

which stores and analyses quarterly data submitted by pig farmers to their 

Teagasc advisor. Utilising the Teagasc PigSys recording system as a basis of 

evaluation, three objectives are defined: 

• Identify information sources affecting on-farm management of Irish pig 

units 

• Assess information previously compiled through Teagasc PigSys system 

• Identify factors influencing record keeping (RK) on pig farms 

• Determine farmer-perceived outcomes of RK activities 

2. Methodology 

A.) Farm Visits 

• Qualitative assessment of Teagasc advisor-producer interaction 

» Standardised advisor questionnaire to assess farmer-advisor 

history and record keeping patterns 

» Observation of farmer-advisor interaction and relationship 

B.) Farmer Innovation Questionnaire (FIQ) 

• 328 commercial pig farms in Ireland 

» 189 active PigSys clients (c. 79,000 sows – 55%of Irish 

national herd) 

• 302 farmers – distributed questionnaires by post 

» 46% response rate (n=141) 

3. Preliminary Findings 

Farm location and farmer age did not feature as significantly associated with 

RK, but were significantly associated with technology use (home computer) 

and unit size (# of sows). 

• Average farmer age = 49 years 

• Average number of sows = 588 sows 

Figure 2: Relationship Between Teagasc Client Status and Type of Records Kept 

40.00% 

35.00% 

30.00% 

25.00% 

20.00% 

15.00% 

10.00% 

5.00% 

0.00% 

Teagasc advisory services were widely used (77% farmers) while ‘other’ 

advisory services were used by just 23% farmers. 

Teagasc client status was associated with the type of on-farm RK activities 

(p=0.012) with 58% of Teagasc clients reporting use of PigSys records. 

Farm Location 

Smartphone 

Smartphone 

€ tech 

investment 

Home Computer 

No 

# of sows 

Home 

Computer 

Farm 

Location 

Yes 

Farmer Age 

RK 

Smartphone 

Records not kept 

Written - record sheet 

Written - stockbook/diary 

Written first, computerised later 

Computerised - own format 

Computerised - database 

Combination 

n=141 where Not Teagasc clients = 38 

Teagasc Clients =103 

Teagasc 

Client 

Home Computer 

# of sows 

# of sows 

# of sows 

Farmer Age 

Home Computer 

Significantly associated Figure 2: Factors associated with on-farm RK activities from FIQ 2014. 

C.) Questionnaire Follow-on Interviews 

• Face-to-face interviews of 61 farmers who indicated willingness 

to participate with FIQ response 

• Qualitative, narrative data collection through semi-structured 

queries based on FIQ responses 

Empirical data and 

interviews with pig farm 

advisors assisted in the 

development of this 

study model, displaying 

factors which have the 

ability to affect on-farm 

RK activities. 

Clear, direct interaction 

Indirect interaction 

4. Conclusions 

Environmental 

Influence 

Market 

Structure 

Record 

Keeping 

Farmer 

Demographics 

Practical 

Assessment 

Enterprise 

Characteristics 

1. Advisor-producer interactions no longer fit within ‘Top-Down’ 

KT/advisory approach 

» Collaborative KT involving all stakeholders is preferred 

approach of Irish pig farmers 

» Farmer-advisor relationships valued highly, exhibit great 

trust and longevity for Teagasc advisors 

2. Efficient Teagasc advisory services are important to success of 

farm management /RK regime 

» Pig producers have little interaction with external advisory 

sources; just 1 in 4 utilised a non-Teagasc advisor 

» Difference in RK type undertaken by Teagasc clients and 

non-clients 

Figure 1: Irish Pig Production Record Keeping Study Model. 

3. Personal technology use similar across most Irish farms 

» Home computers more widespread than smartphones – 

reasons for technology use greatly varied 

» Expansion and innovation in technology is increasingly 

demanded among current technology users 

4. Varied motivations and influences to engage in on-farm RK 

» Many factors significantly intertwined; change in RK 

paradigm requires multifaceted approach (see Figure 2) 

This project is funded by Teagasc through the Walsh Fellowship Scheme.

An Assessment Of Irish Sheep Farmers Attitudes Towards The Use Of Genetically 

Evaluated Rams 

Sean Cooney 1 Dr. A. Fahey 2 Dr. M. Gorman 3 & M. Gottstein 4 

1,4 

Teagasc, Advisory & Training Office, Codrum, Macroom, Co. Cork 

2,3 

UCD, Belfield, Dublin 4 

Background / Context 

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The Teagasc Better Sheep Farm Programme has found that progeny from 

genetically evaluated rams were 2.5kg heavier at weaning and 2 weeks earlier to 

Z_sxZx6k7mdTK6gBEQ 

slaughter. We need to understand why sheep farmers are not using genetically 

evaluated rams. 

Objectives: 

Determine the factors that affect 

farmer’s decisions to purchase (and 

to continue to purchase) genetically 


The identification of these factors 

will help to design extension 

programmes to improve the adoption 

of genetic improvement technologies 

in the Irish sheep industry 

Methodology 

Survey of Teagasc sheep farmers 

(n=258) and a random sample of 

pedigree sheep breeders (n=80) to 

determine the factors influencing 

their attitudes towards the adoption 

and usage of genetically evaluated 

rams. 

Key Findings 

Factors influencing sheep farmer’s decisions to purchase 

genetically evaluated rams 

1. Farmers that did not have sheep handling facilities (sheep race) were less 

likely to purchase genetically evaluated rams (OR= 0.38,95% C.I = 0.22, 

0.68) 

2. Lowland sheep farmers were more likely to purchase a genetically evaluated 

ram with an OR of 3.50 (95%C.I = 1.93, 6.32) 

3. Farmers who were unaware of the Sheep Ireland genetic star rating system 

were less likely to purchase genetically evaluated ram (OR=0.16, 95% C.I 

0.03-0.75) 

4. Non-pedigree sheep farmers were less likely to purchase genetically 

Factors influencing sheep farmer’s decisions to continue 

purchasing genetically evaluated rams 

1. Farmers who are unaware of the star rating index are less likely to continue 

purchasing genetically evaluated rams (OR = 0.17, 95% C.I =0.04,0.62) 

2. Lowland sheep farmers are more likely to continue to purchasing genetically 

evaluated rams with an OR of 3.24 (95% C.I = 1.61, 6.52). 

3. Farmers that did not have a spouse with off farm employment were less likely 

to continue purchasing genetically evaluated rams with an (OR = 0.36, 95% 

C.I 0.18, 0.74) 

Conclusion 

Recommendations 

While the study found a low level of adoption, it also found a very high level 1. 

of awareness and interest among non-adoptees. Given the interest level 

among non-adoptees and the general satisfaction with the star rating 

Extend STAP incentive to encourage farmers to continue to purchase 

genetically evaluated rams and increase the chance that non adoptees 

would purchase these rams. 

system and that over half of those surveyed intended to performance 

record in the future it may be concluded that farmers are in the 

contemplation or persuasion stage of the technology adoption process. 

2. 

3. 

Data collection amongst specific hill flocks needs to be intensified to 

allow the upland farmers improve the quality of mountain breeds. 

As sheep farmers preferred source of information is from newspapers 

greater awareness of the benefits of this technology need to be 

1. Pedigree breeders were found to have higher levels of adoption. 

vigorously promoted in the farming press. 

2. Sheep farmers who had invested in sheep handling facilities were more 

likely to purchase genetically evaluated rams 

4. Extension agents could place greater emphasis on highlighting the 

correlation between using genetically evaluated rams and the increased 

3. The influence of STAP membership has yet to be evaluated but it 

appears to be positive. 

5. 

financial gains to be accrued. 

More focused research on the perceptions, attitudes, behaviour and life 

4. Limited availability of performance recorded black face mountain rams 

restricts the opportunity of upland farmers to purchase genetically 

stories of sheep farmers. 


Conclusionsij0ijkd]jj2kj-f2TTH 

Masters in Agricultural Innovation Support - This research has been funded under the Teagasc Walsh Fellowship Scheme

Number of Dairy Farmers 

Using the innovation-decision process to 

understand reasons for the low uptake of grass 

measuring technology on dairy farms 

P. Newman 1 , M. Moore 1 & D. O’Connor 2 

1 

Teagasc Headquarters Oak Park, Co. Carlow 

2 


Background 

Grazed grass is the cheapest feed source for milk production in Ireland (Teagasc, 2011). 

Ireland’s competitive advantage is the potential of its pastures to grow up to 16 t of grass 

DM/ha (O’Donovan et al., 2010). An increase in grass utilisation by 1 t/ha can increase net 

profit by €161/ha (Teagasc, 2015). Growth rates are seasonal with considerable variation 

observed between regions (Ramsbottom et al., 2015). Computer programmes are available 

to farmers as a grassland management decision support tool. However, only a minority of 

farmers currently use new grassland management technologies. 

Aim 

The aim of the research is to identify dairy farmers stage within the adoption process and to assess their 

reasons for adoption or non-adoption of grass measuring technology. 

Objectives 

Methodology 

• Collecting a survey of Teagasc dairy farmers in 

county Carlow to identify their stage within the 

innovation-decision process. 

• Evaluate their reasons for adoption or non-adoption 

of grass measuring technology. 

• Identify and compare key characteristics associated 

with each stage of the innovation-decision process. 

• Categorisation of non-adopters and development of 

more targeted and effective Knowledge Transfer 

initiatives 

Sources of Data 

Population: 121 (specialist dairy farms) 

Sample size: 92 (specialist dairy farms) 

Location: County Carlow 

Methods: Mixed methods (quantitative and 

qualitative) 

Methods of Data Collection 

• The use of a telephone survey to collect data 

for the study 

• Interview Teagasc and Industry experts 

Finding to Date 

Distribution of Respondents in the Stages of the Innovation-Decision Process 

Decision Stage 

60 

24% 

50 

50 50 50 50 

37% 

40 

45 

30 

38 38 

Continued Adoption 

Discontinuance 

Later Adoption 

Continued Rejection 

20 

18% 

10 

Farmers Surveyed 

Farmers Progression 

9 

0 

Knowledge Persuasion Decision Implementation 

21% 

Stages 

Conclusions 

• To increase the adoption rate of grass measuring technology and for it to be successfully implemented on dairy 

farms as a grassland management decision support tool, more support must be provided to farmers. 

• The formation of grassland discussion groups focused entirely on grassland management is one method to 

improve farmers skills and offer continued support. 

This project is funded by Teagasc through its Walsh Fellowship Scheme

An Analysis of the Use of Financial Planning Tools by Dairy Farmers and Advisors 

John Greaney², Dr. Michael Wallace¹, Mr. Fintan Phelan 


2. Teagasc, Moorepark, Co.Cork 

3. Teagasc Portlaoise, Co. Laois 


There is a view that a significant number of recent entrants to dairying still do not appreciate fully the importance of managing risk around farm development planning 

and cash flow management. They need to be more aware of the impact of capital development and volatility on cash flow, as well as understanding the true cost of 

producing a litre of milk and how they can manage the factors that influence this cost. 

Objectives 

• Review and evaluate existing farm planning tools and 

approaches that are available to farmers and advisors 

• Determine the extent to which financial planning tools are 

used to assist in the farmer’s decision making process 

• Examine the attitudes of farmers and advisors towards 

business planning and to determine the key influences, 

external sources of advice and intra-family responsibilities in 

relation to financial recording and planning within farm 

businesses 

• Make recommendations about the development of new 

modes and tools to assist advisors and farmers in preparing, 

reviewing and updating farm plans 

Cash Plan Programme 

• In 2014, the Department of Agriculture, Food and the Marine (DAFM) supported the ‘Cash Plan 

Programme 2014’, highlighting the importance of managing risk around farm development 

planning and cash flow management 

• The aim was to support new entrants into dairy farming (i.e. those who commenced supplying 

milk on or after 1 April 2008) to become familiar with the impact of capital development and 

volatility in cash flow, as well as understanding the true cost of producing a litre of milk 

• Eligible participants were entitled to a sum of €1,000 for satisfactory participation in the 

programme and completion of three relevant tasks: 

1. Complete ‘My Farm, My Plan- Planning for my Future’ strategic planning workbook 

2. Record the monthly cash flow for 2014 

3. Prepare a monthly cash flow budget for 2015 

Methodology 

Some Key Findings 

Financial Management 

. 

• Literature review 

• Survey of 80 farmers in Cork East who took part in the ‘Cash 

Plan Programme’. 55 of these farmers completed the course 

in full. 

• Interviews with key industry stakeholders: Banks, Processors, 

Accountants, Feed Companies, Solicitors, Irish Farmers 

Journal, Bord Bia. 

Farm Details: 

• Average No. Cows 96 

• Average Farm Size 147 acres 

• Average age 35 

• 40% farming in partnerships (family) 

• Average Milking Platform - 119acres 

• 46.25% rely on their spouse 

to keep farm records. 

• 50% have a farm office 

• 80% calculate their costs of 

production 

• Family proved to be the 

most influential factor when 

making major financial 

Workload 

decisions on the farm 

Farmer Questionnaire 

• Questioned on a one to one basis 

• 53 questions - both open and closed questions 

• 30% also working off farm 

• 85% of farms are a ‘one man show’ 

• 41.25% rely on family members to carry 

out daily tasks 

Future Plans 

• 58.75% intend on expanding 

• Structured around capturing a detailed account of the 

Education 

following: 

‣ Farm Details- general background 

• 28.75% went to 3 rd Level 

‣ Workload- Employment details, day-day running of farm 

Farm IT/Bus. Planning 

‣ Education- Qualifications or level of education received 

• Only 26.25% of farmers felt very 

‣ Farm IT- level of competency with computers 

comfortable using laptops/computers 

‣ Business Planning- familiarity with Bus. Tools 

• 51.25% found the Teagasc eProfit 

‣ Development and Investment- Level of investment/debt 

‣ Financial Management Tools and Practices- who carries 

out the financial management e.g. spouse 

‣ Future Plans- Increasing cow numbers etc… 

Monitor useful 

• 32.5% of respondents thought the 

workbook tool- My Farm My Plan 

to be of benefit to their business 

n=80 

Conclusions/Recommendations to Date 

• 60% of farmers surveyed approached Teagasc for advice before investing money in their business 

• 61.25% of the sample believed they benefitted from participating in the ‘Cash Plan Programme’ 

• There is scope there to run courses in the future with 68% of farmers expressing an interest in attending a number of annual training days again to help with 

cash flow budgeting/understanding finance/business planning 

• 31% of the farmers interested in additional training days would be wiling to pay for the training 

• 87.5% farmers restructured their debt over the last 5 years but huge levels of debt exist on farms in East Cork 

• For greater adoption of the Teagasc financial tools there must be further buy-in from the advisory staff 


Developing a Targeted Marketing Tool Through Farmer 

Categorisation to Enhance the Efficiency of Knowledge Transfer 

Z. Pratt 1 , D.O’Connor 2 & M.Moore 3 

1 Kildalton College, Piltown, Co. Kilkenny 

2 

Teagasc Headquarters, Oakpark, Co. Carlow 

3 


1. Background and Purpose of study 

Knowledge transfer is of paramount importance to future sustainability of agriculture. With a drop in 

advisor numbers in Teagasc by over 36% since 2007, there is a demand for a better alignment of farmer 

needs with extension services. Targets contained in the Food Harvest 2020 also mean adoption of better 

practice on farms if these goals are to be met. Categorising farmers into groups based on similar needs 

may help enhance knowledge transfer efficiency. 

2. Objectives 

1. Evaluate current farmer characteristics used in Client 

Relationship Management (CRM) systems in Teagasc 

2. Identify the most appropriate characteristics to develop a 

categorisation tool of farmers in Teagasc 

3. Provide recommendations on the use and further 

development of a categorisation tool of farming clients in 

Teagasc 


• Selection of 120 farmers from Electoral Divisions in Carlow 

• Identification of most suitable criteria for categorisation based 

on review of existing literature 

• Data collection on specific characteristics of Teagasc farmers 

• Analysis of characteristics of clients to determine their 

association 

with best practice adoption 

• Interviews with advisors on behavioural traits of farmers 

4. Key Findings 

Fig.1.Carlow Electoral Divisions 

• Teagasc do not have a specific CRM system 

• Teagasc CIMS (Client Information Management 

e.g. 

System) 

contains only basic information on individual farmers 

enterprise size, enterprise type 

Insights from the literature: 

 

 

Farm size and farmer age were determinants of the 

variation in technical efficiency (Wilson et al, 2013) 

Farm type important in farmer categorisation (Funk et 

al, 1988) 

Marital 

Status 

Farm Size 

Characterist 

ics 

Associated 

with 

Adoption of 

Best 

Practices 

Discussion 

Group 

Involveme 

nt 

Teagasc Advisor Interview Findings 

• Advisors expressed their view of the positive relationship 

between younger farmers and the adoption of best practice 

• Believed farm size had an influence on a farmer’s decision to 

adopt best practice 

• Advisors recommended inclusion of education as an aid to 

determine farmer’s adoption of best practices 

• Recommendations made to incorporate attitudes and 

Farm 

Type 

behaviours of farmers when constructing categorisation tool 

in future research 

5. Conclusions 

6. Recommendations 

• Teagasc CRM is primarily a financial tool 

• Age did not have a statistical association with the adoption 

of best practice 

• Marital status of farmers, presence of children, type of 

enterprise and discussion group involvement have 

association with adoption of best practices 

• Future studies should include behavioural characteristics to 

gain a better understanding of farmer KT needs 


• Details of characteristics of non-Teagasc farming clients 

should be included in the categorisation tool 

Masters in Innovation and Support Programme 2013-2015- Funded by Teagasc Walsh Fellowship Scheme

An assessment of the knowledge transfer supports required by high 

profitability dairy farmers 

Eilish Burke¹,² Dr. Monica Gorman,¹ Mr. John Maher² , Dr. Karina Pierce¹ 

1. School of Agriculture and Food Science UCD, Belfield, Dublin 4. 

2. Teagasc, Moorepark, Fermoy, Co.Cork. 

Aim: Identify the priority knowledge transfer (KT) supports required by high profitability dairy farmers (HPDF) 

Background 

Amongst Ireland’s dairy farmers, some are achieving high levels of profitability. How this is being achieved is of interest 

to the Irish dairy industry, including other dairy farmers. Furthermore, changes in the Irish dairy sector following milk 

quota abolition this year has the potential to bring about new challenges for dairy farmers. Consequently, to address 

these changes in the dairy landscape, future KT tools & supports may need modification. Therefore, the future KT 

requirements of HPDF must be assessed to understand their requirements, to allow Teagasc and the wider industry to 

allocate resources more effectively to meet their needs in the undefined future of milk production in a non-quota 

environment. 

Methodology 

Objectives 

• To determine how HPDF are so profitable 

–Technically 

–Financially 

–Socially. 

• To establish how HPDF use the AKIS 

system 

• To gain a clear understanding of priority 

KT needs of HPDF 

• To make recommendations for the industry 

as a whole on prioritisation of use of 

resources for HPDF 

Technically 

Key Findings 

Financially 

Socially 

4.AI usage 

1.eProfit Monitor 

5.Grazing plan 

2.ICBF information 

6.Breeding plan 

system 

3.Grass recording 

programmes 

Conclusion 

‣ The main focus for HPDF is to progress their farm business through the adoption of different farm business structures 

‣ There is a distinct shift in KT focus among HPDF from technical to more organisational skills in the future 

‣ To fulfil future KT needs HPDF will require increased reliance on a range of actors within the AKIS 

‣ This study should be continued to further investigate/develop different KT tools & supports to meet the future requirements of 

HPDF 

This project is funded through Teagasc Walsh Fellowship Programme: MAgrSc Agricultural Innovation Support 2013-2015

This project is funded by Teagasc through its Walsh Fellowship Scheme 

The influence of knowledge transfer uptake on the profitability of beef farms and the knowledge transfer 

requirements of beef farms with varying levels of profitability 

¹ ²James Dunne, ²Dr. Bridget Lynch ³Pearse Kelly 

Teagasc Advisory Office, Mellows Campus, Athenry, Co. Galway. ¹ 

School of Agriculture and Food Science UCD, Belfield, Dublin 4. ² 

Teagasc Grange, Dunsany, Co. Meath. ³ 

Project Aim 

‣ To evaluate and document the relationship and influence KT and innovation uptake has on the profitability of beef farms 

‣ What KT and innovation measures farmers feel they require and what they would be willing to adopt at farm level 

Background 

‣ 100,000 herds involved in beef farming nationally (CSO, 2012) 

‣ Irish beef sector accounts for 30% of value of Irish agricultural 

outputs (Bord Bia 2015) 

‣ Proportion of economically viable dry stock farms remains low, at 

about 15% and 22% for cattle rearing farms and non breeding 

farms respectively (NFS, 2015) 

‣ Huge variability in the level of profits made from beef farming 

(Teagasc, 2015) 

Project objectives 

‣ Identify the current economic performance levels on Galway/Clare 

beef farms and distinguish why performance on these beef farms 

varies 

‣ Identify the relationship between KT uptake and overall profitability of 

the enterprise 

‣ Identify farmers’ attitudes towards change and adoption of new 

practices and what have been the barriers in adopting new practices in 

the past 

‣ Determine across differing farm profitabilities what farmers feel they 

require to progress and what KT/innovation practices they would be 

willing to implement 

Methodology 

‣ Galway/Clare Advisory Region 

‣ Mixed methods study 

‣ Analysis of 2012 & 2013 ePM dataset 

‣ Top 10 , Average 10 and Bottom 10 

Farmers Selected on Gross margin 

‣ Semi-structured one to one interviews 

(n=30) 

Key Findings (One to One Interview) 

‣ The number of good farming practices completed on farm are 

higher as you move from the bottom performers through to the 

Key Findings (2012 & 2013 ePM Data) 

top performers, showing a direct relationship between KT 

uptake and profitability 

Farmer Profitability Category (Av. 2012 & 2013 ePM) 

Top 10 Average 10 Bottom 10 Top v Bottom 

‣ The main limitations in the adoption of new practices differed 

greatly within each group; land availability and farm 

Stocking Rate 

LU/ha 

1.66 1.238 1.11 + 0.58 

infrastructure were seen as the biggest limitations in the top 

performers vs. motivation and lack of profitability in the bottom 

performing group 

Gross 

Output 

1513 761 554 + 959 

‣ Farmers have identified extension priorities they feel they need 

€/ha 

to improve profitability; 

Total Variable 

Costs €/ha 

Liveweight 

(kg LW/ha) 

Gross Margin 

€/ha 

696 552 745 - 49 

624 371 261 + 363 

817 208 -191 + 1008 

‣ A separate KT model for each level of farmer 

‣ More one to one contact with advisors 

‣ Continuation of Better Farm Programme 

References 

‣ Bord Bia, 2015. Factsheet on the Irish Agriculture and Food & Drink Sector 

‣ Central Statistics Office, 2012. Census of Agriculture 2010, Final Results. 

‣ Department of Agriculture Fisher’s and Food (DAFF) (2010), in Food Harvest 2020 A vision for Irish Agri-food 

and fisheries, Irish Department of Agriculture, Food and Fisher’s. 

‣ National farm survey, (2015). Available at:: 

http://www.teagasc.ie/publications/2015/3646/The_viability_of_the_Irish_farming_sector_in_2014_Teagasc.pdf 

‣ Teagasc, 2015. e-Profit Monitor analysis Drystock Farms 2014.

Categorisation of Hard-to-Reach Dairy Farmers in Kerry with regards Soil Fertility: 

Views and Knowledge towards engaging with Knowledge Transfer 

3 

2 

1 

Oisín Coakley 1 , Doris Laepple , Tom O’Dwyer 

Teagasc/UCD MAgrSc Innovation Support Student (2014-16) 

School of Agriculture and Food Science, UCD, Belfield, Dublin 4 

Animal & Grassland Research and Innovation Centre Teagasc Moorepark 

2 

3 

Categorisation of farmers in groups has proven successful in previous research (Garforth and Rehman, 2006. Jansen et al 2010. Vanclay, 

2004. Wales Rural Observatory, 2011) 

• FH2020 targets - future milk output depends on the rate of structural change and productivity 

growth. Relative to other regions, the south has the greatest expansion capacity. (Laepple and 

Hennessy, 2012) 

• As the costs of production continue to increase it is essential to identify factors influencing 

farmers and advisors attitudes to new technologies 

• According to Doherty et al. (2013) 14% of farms have never conducted soil analysis 

Methodology 

• Informed definition & criteria of an HTRDF 

• Two stage sampling – 

• Adviser & Industry Survey (n=8) 

• In-depth Qualitative Interview (n=15) 

• Explore findings – identifying main themes & 

sensitizing concepts 

• Further categorise - into segments based on ways 

in which HTRDF’s receive & trust information on 

soil fertility 

< Literature Review > 

Research Objectives 

1. Define Hard To Reach Dairy Farmers 

2. Segment HTRDF’s into categories based 

on their views of engagement with services 

& current knowledge 

3. Identify where the HTR dairy farmer 

acquires information relating to soil 

fertility management practices 

Classification of clients (n=815) by 

adviser on a Scale of HTR (1) – (4) 

reached regarding Soil Fertility info 

HTR 

4. Key Findings to date 

Soil Fertility 

‣ HTRDFs: mostly very well versed in how to 

Age Classification of HTR farmer 

clients (n=203) identified by 

Advisers 

Young Farmer (40 in 

the 2010 Census of Agriculture (CSO, 2012) 

Early Findings: 

‣ Good soil fertility seen by HTRDFs as very important to their farm business, however most are conservatively applied 

‣ Barriers: Poor soil (applicability to own farm) & weather conditions, ownership/lease issues, lack of finance or stress 

‣ Incentive by initiative to conduct soil analysis in conjunction with Kerry-Agribusiness viewed positively 

‣ Some previously in discussion groups felt they were not as “vocal” or “confident” as others in the group 


Increasing engagement between Teagasc Advisory Services and 'hard to 

reach' dairy farmers in Co. Limerick 

Conor Kavanagh¹ Dr Jim Kinsella² 

Dr Tom O’Dwyer³ 

1. Teagasc/UCD MAgrSc Innovation Support Student (2014-2016) 2. School of Agriculture and Food Science UCD, Belfield, Dublin 4. 3.Teagasc, AGRI Centre, Moorepark, Fermoy, Co. Cork. 

Background 

Many farmers have low levels of engagement with the advisory services, improving 

the level of engagement using different strategies and tools, which are 

known to be beneficial must be implemented to be beneficial (Jansen, 2010). 

For the purpose of this study Hard to Reach (HTR) farmers are those farmers: 

with limited interaction with the farm advisory services due to a wide range of 

social, cultural and economic factors, often believed to be bound by trade, and 

suspicious of change, and therefore are the slowest to adopt a new idea or technology 

(Vanclay, 2004). 

In the case of Irish dairy farmers these low levels of engagement with the advisory 

services limits their access to information and innovation support at a 

time when the sector is evolving to meet new opportunities and demands. 

Key Findings 

Table 1: Distribution of HTR Dairy Farmers by self-rated performance in key areas of 

farm management (n=100) 

Aim, Objectives and Methods 

The study aims to understand why HTR dairy farmers in Limerick do not use 

certain available farm advisory services and to test a new knowledge transfer 

intervention which can increase their engagement with the advisory services. 

Objectives: 

1. To establish the reasons why HTR dairy farmers in Limerick use little or 

no farm advisory services which could benefit their farm businesses. 

2. To determine HTR dairy farmers’ advisory service needs and their opinion 

of the different advisory technologies. 

3. To identify extension methods that can increase the uptake of advisory support 

by HTR farmers. 

Table 2: Distribution of HTR Farmers by their self-rated level of needed improvement 

in key areas of farm management (n=100) 

Level of Improvement 

Needed 

Financial 

Management 

Grassland 

Management 

Stock 

Management 

People 

Management 

None 18 43 56 68 

Most important 56 26 15 3 

Second most important 23 22 16 16 

Third most important 2 9 11 7 

Fourth most important 1 0 2 5 

Figure 3: Distribution of HTR Farmers by Reasons given for lack of uptake of advisory 

services (n=74 as 26 farmers provided no reason) 

30 

25 

HTR dairy farmers were identified by Dairy Advisors in Co. Limerick based 

on the level of engagement and use of advisory services in 2015. The criteria for 

selection were: 

20 

15 

1. Actively milking cows in 2015 

2. Have no involvement in a dairy discussion group 

10 

3. Do not attend more than 2 dairy related events/ year (open days, farm walks, 

training courses, joint programme events etc.) 

5 

4. May be in contact with an adviser in relation to getting Single Farm Payments 

and possibly Nutrient Management Plans completed. 

5. Not using certain dairy related technologies that Teagasc dairy advisors promote, 

namely: Profit monitors, Grass measuring; and Breeding techniques. 

0 

Age Cost Time Not a true reflection of 

on farm happenings 

Too Complicated 

Methodology 

Conclusions and Recommendations 

 

Of the HTR farmers surveyed 30% were interested in increasing their engagement 

with Teagasc through attendance at workshops and or training days, indicating 

there is a market for advisory services. 

 

As age was the most commonly given reason for lack of engagement and use of 

farm advisory services (Figure 3), there is potential for more advisory services to 

support decisions on transferring the family farm, succession and inheritance. 

 

Time was the second most common reason behind the lack of engagement from labour 

intense farmers, recommendations from advisors and encouragement from 

neighbouring farmers to join discussion groups, could increase their engagement 

with Teagasc. 

 

The use of workshops and/or training days for knowledge transfer have been beneficial 

in the past. The 30% of HTR farmers willing to attend such events could 

improve their knowledge uptake, uptake of specific advisory technologies and 

over all engagement with the advisory service. 


Categorisation of hard to reach drystock farmers according to 

their aspirations, intentions and motivations 

1. Tom Deane , 2. Karen Keaveney , 3. Aidan Murray 

1.Teagasc/UCD MAgrSc Innovation Support Student (2014-2016) 

2. School of Agriculture and Food Science, UCD, Belfield, Dublin 4 

3. Teagasc Beef Specialist, Ballybofey, Co. Donegal 

Aim: To explore the perspectives of the ‘hard to reach’ farmers in the Roscommon/Longford advisory region in terms of how they utilise 

information that is available to them and what motivates them to utilise it. 

1. Background 

‣ Drystock farms (beef and sheep) account for 68% of 

all farms in Ireland (Renwick, 2013) 

‣ Food Harvest 2020 aims for a 20% increase in the 

value of Ireland’s beef and sheep sectors. 

‣ This is to be achieved through ‘enhance knowledge 

transfer to drive farm efficiencies’ 

3. Objectives of research 

1. Define what is meant by the term ‘hard to 

reach’ 

2. Identify the aspirations, intentions and 

motivations of the ‘hard to reach’ drystock 

farmers. 

3. Produce recommendations on how 

to reach these farmers with the 

aid of an effective categorisation system. 

4. Research questions 

1. What are the perspectives of ‘hard to reach’ 

drystock farmers? 

2. How can assumptions about ‘hard to reach’ drystock 

farmers be addressed in order to help understand 

the factors surrounding their uptake of potentially 

useful information? 

3. What is the best way to categorise ‘hard to reach’ 

drystock farmers according to their aspirations, 

intentions and motivations? 

What is a hard to reach farmer? 

‣ No agreed definition of the term in available literature 

‣ Farmers can be hard to reach with potentially useful 

information (Jansen, 2010) 

Research Findings on what a hard to reach farmer is: 

‣ Contact made but does not apply information provided 

‣ No desire to seek out and utilise technical information 

‣ Mainly interested in scheme work 

‣ Reluctant to change: ‘entrenched in their own ways’ 

5. Findings to date 

‣Hard to reach farmers largely depend on their farm advisors to notify and advise them about upcoming schemes as well as with relevant technical information. 

‣Those hard to reach farmers that have limited or no contact with a farm advisor or don’t actively seek information largely avoid joining farm schemes e.g. GLAS 

‣These farmers are highly influenced by their neighbours regarding the decisions they make in relation to schemes to join. 

‣Time restrictions arising from working off-farm mean many farmers do not have time to get involved with participatory forms of agricultural extension such as 

discussion group participation 

‣The majority (80%) of the hard to reach farmers interviewed had not completed any form of agricultural education which is limiting their access to information 

‣Most hard to reach farmers unclear as to how they can become involved, or increase their involvement with advisory services 


Background Methods Objectives 

• Identify why key K.T. 

• Teagasc – 45,000 

clients 

• 14,000 Discussion 

Group members 

• 18,733 Club Contract 

Clients 

• Potential to increase 

profitability and 

efficiency on Irish 

farms 

• Output from cattle & 

sheep sectors over 

past 5 years - €1.9 

billion 

Longford/Roscommon 

Advisory Region 

programmes may not be 

engaging with farmers 

• Identify where farmers 

source information on 

farm topics & what 

technologies are being 

adopted 

• Establish the impact of 

the BETTER Farm 

Programme in a local area 

• Establish what services 

need to be provided to 

increase and maintain the 

level of engagement with 

K.T. programmes 

• Identify the supports that 

are required by advisors 

in order to facilitate 

delivering K.T. 

programmes 

Key 

Findings 

Interviews: BETTER Farm impact 

• Advisor has influence on farmers in discussion groups 

• Reseeding & drainage practices adopted in satellite group 

and surrounding area 

• Farmers learn & get advice from BETTER Farm participant

Owen Keogh¹² Monica Gorman ¹ 

The Use of Local Radio in Knowledge Transfer 

Pat Clarke² 


2.Teagasc, Athenry 

Radio, as a mass media communicator, is one of the most effective in Ireland. Teagasc in Mayo has a well established 

relationship with Mid-West Radio on which it broadcasts a daily 5 minute programme (Farming Scene) and a weekly 10 

minute programme (Farming Matters) each Wednesday evening. Recognising the need for research and advisory services to 

stimulate farm innovation and technology adoption, can the potential of radio be further exploited? 

Objectives 

To identify characteristics for 

effective agricultural radio 

To profile & analyse the 

listenership and attitudes of 

farmers in Mayo for Teagasc radio 

programmes broadcast by Midwest 

Radio. 

To investigate and map the 

potential for increased agricultural 

radio in other regions. 

To assess the interest & potential 

for increased use of podcasts as a 

means of KT support. 

Methodology 

A mixed methodology approach was used with triangulation to 

validate the results. This included: 

• Literature Review 

• Face to face listenership survey of farmers in Mayo 

• Discussion Group meetings 

• Internal Focus Groups with Teagasc radio staff 

• Mapping agricultural radio countrywide 

• Elite Interviews with key informants in the research area 

• Podcasting the Teagasc newsletter and monitoring downloads 

Key Findings 

Farmer Survey Findings (N=127) 

81% of farmers surveyed listen to the ‘Farming Scene’ 

72% of the respondents listen to ‘Farming Matters’ with 23% listening every week. 

Details and deadlines for Events/schemes were the most popular subject with rural 

development next 

< 12% of farmers under 30 listened to the Farming Scene weekly while 43% of farmers over 50 

listened weekly 

Almost 70% of respondents said they would like to see a stronger focus on the experience of 

local farmers in the programmes 

Podcast of the Teagasc Newsletter 

• September 14 – May 15 total podcast hits = 6,322 

• Dairy podcasts were the most popular podcasts with 1,300 hits 

over the test period (September – December) 

• Podcast listenership increased hugely when coupled with social 

media promotion 

• 75% of farmers surveyed would welcome podcasts on the 

Teagasc website 

Other Research Findings 

• Farmer discussion group members said that radio would not have a direct influence on decisions but would trigger certain actions e.g. selling 

livestock, event attendance or farm scheme deadlines. 

• There is scope to develop agri-radio further – building on current agri programmes across local radio stations and with enthusiasm from 

Teagasc regional managers and staff. 

• A checklist of criteria for effective agricultural broadcasting was developed by Teagasc radio staff. Being well prepared and structured and 

knowing the audience were two of the key criteria. 

Conclusions: 

• There is a high awareness and a wide listenership to the farming programmes in Co Mayo, that extends beyond Teagasc clients. 

• Farmers use the information from radio programmes in a specific way – usually as a prompt for further research or a reminder for action. 

• Farmers appreciate information and news that are specific to their own local area and relate experiences of farmers in similar situations 

to theirs. 

• Radio could be further utilized in the specific area of promoting knowledge transfer events 

• The Teagasc Podcast experiment showed farming based podcasts as popular downloads particularly when promoted through social 

media. 


Key ingredients for effective farmer learning 

through knowledge transfer events 

Sean Mannion¹, Anne Markey², Mark Gibson³ 

1 Teagasc/UCD MAgrSc Innovation Support Student (2014-2016) 

2 School of Agriculture and Food Science, Agriculture and Food Science Centre University College Dublin Belfield, Dublin 4 

3 Knowledge Management & Communications Specialist Teagasc, Mellows Campus, Athenry, Co. Galway 

Project Aim 

•To determine the key ingredients for effective farmer learning through knowledge transfer events organised by Teagasc 

Background 

•In 2014 Teagasc carried out 991 Knowledge Transfer (KT) events, categorised as open days/Farm Walks/ Demonstrations (42% ) and 

Meetings/Seminars (58%) 

•The challenge and future direction of Teagasc is to improve and innovate knowledge transfer systems 

•There is a lot of research conducted by Teagasc with some 500 research staff, however technical research must be complemented by 

research into effective knowledge transfer systems 

To review current 

best practice used 

in the planning 

and 

implementation of 

KT events and 

farmer learning 

To establish 

key criteria 

for effective 

farmer 

learning 

through KT 

events 

To identify farmers 

knowledge, 

attitudes and 

practices with 

respect to Teagasc 

KT events 

Objectives 

Of 

Research 

To create 

a profile 

of Teagasc 

KT events 

To examine the 

attitudes and 

practices of 

Teagasc staff in 

planning and 

implementing 

KT events 

Exit-poll surveys & 

follow up interviews 

• Major Sheep Event 

(National) (N=181) 

Att.= 12,000 

• Major Dairy Event 

(National) (N=228) 

Att.= 15,000 

• Regional Sheep 

Events (N=71) 

Att.= 750 

• Regional Beef 

Events (N=49) 

Att.= 400 

• Regional Dairy 

Events (TBC) 

Study Location 

Event 

organisers 

• Key 

informative 

interviews 

• N = 3 

Event 

presenters 

Methodology 

• Semi 

Structured 

Questionnaire 

• N = 16 

Event attendees 

• Semi Structured 

Questionnaire 

(exit-poll) 

• N = 580 

• 97.7% stated that the event met or exceeded their expectations 

• Farmers who are not part of a discussion group learn more at events 

Event attendees 

• Semi Structured 

Interview 

• N = 10 

• 67% stated that there were no improvements that they would recommend to the way 

information was presented 

• Visually seeing a practice in action and being able to ask questions was regarded as 

being very important, and the preference for many farmers 

• According to respondents peer to peer communication is very important for learning 

• Greater attendance at discussion group approved events 

Expected Outputs: 

• Assist Teagasc building best practice for KT events 

within Sheep, Dairy and Beef enterprises 

• Provide insights for event organisers and presenters 

on how farmers learn best at KT events 

• Identify barriers for effective learning 

Key findings from event 

attendees: (529 surveys & 10 

Interviews) 

• From 30 Counties 

• 85% are the main decision makers on their 

farm 

• 66% are/have been in a discussion group 

• 79 Ha is the average farm size 

• 71% are full time farming 

• 87% of attendees were

Decision Making by Farmers on Succession & 

Inheritance 

T. Russell 1,2 , J. Breen 2 , J. McDonnell 3 , K. Heanue 3 , M. Gorman 2 & P. Wims 2 

1 

Teagasc, Advisory & Training Office, Tullamore, Co. Offaly 

2 


3 

Farm Management & Rural Development Department, Teagasc , Oakpark, Carlow 

4 

Rural Economy & Development Programme, Teagasc Athenry, Galway 

Development of a “Guide to Succession & Farm Transfer” 

Rationale 

Aim 

• Currently in Ireland only 6.2% of farm holders under 

the age of 35 (CSO, 2012) 

• Succession & Inheritance are the main mechanisms 

for increasing the number of young farmers 

• Lack of information & support for agricultural 

advisors, farmers & successors on succession and 

inheritance (Results from this study to date) 

Develop a tool in the form of a book to support farmers 

in making decisions on succession and inheritance 

Objectives 

• Light, user friendly, graphical book 

• Self complete workbook 

• Deal with the emotional and interpersonal issues 

• Focus on succession 

• One of the main issues is the lack of communication 

and starting the conversation 

Method 

• Co-creation/Co-Design – The practice of developing systems, 

products, or services through collaboration with end users, 

managers, facilitators, and other stakeholders 

• Facilitated interactive consultation sessions 

• Experience & Knowledge of Stakeholders, Providers and End 

Users 

Result 

Through 8 chapters with information & self complete exercises this guide: 

1. Outlines the processes of Succession and Farm Transfer 

2. Outlines the profile of the farm 

3. Defines the profile of the farm family 

4. The steps of communicating with the family about the future of the farm 

5. Defines and takes the farmer through the steps in sharing management 

responsibility on the farm 

6. Outlines the next steps for the farmer to take when they have started the 

conversation and if they cant reach a decision 

7. Identifies the key professionals involved in the transfer of the farm and their key 

roles and responsibilities 

8. Provides a formal “Succession Plan” document for use by the farmer to outline the 

future plans for the farm business 

Acknowledgements 

References 

This research has been funded through the Teagasc Walsh 

Fellowship Scheme 

Central Statistics Office. (2012). Census of Agriculture 2010 – Final 

Results. Dublin: Stationary Office.

A Study of Communication Methods for Teagasc to Engage with Agricultural College 

Graduates from Graduation to Farm Ownership 

John W Kelly¹ Padraig Wims² Kevin Connolly³ 

1.Teagasc Ballyhaise Agricultural College ,Co. Cavan. 


3.Teagasc Coolshannagh, Co. Monaghan. 

1. Background / Context 

• Currently no existing method for Teagasc to keep in contact with Agricultural College Graduates. 

• It is important that Teagasc maintain contact with them until they assume management of their home farms. 

2. Objectives 

Population 


1. Identify what communication methods agricultural graduates would 

like from an extension organisation. 

2. Assess and identify the characteristics of recent agricultural college 

graduates and their experience of agricultural college. 

3. Develop and evaluate methods of communication for agricultural 

advisors to engage with agricultural college graduates. 

4. Evaluate contact between a Teagasc advisor and existing agricultural 

college students. 

All Level 6 Ag College graduates since 2008 

Sample 

Graduates from Ballyhaise Agricultural College since 2008 (n=464) 

Research Methods 

• A postal survey Ballyhaise Agricultural College graduates since 2008 (n=464) 

• Identified methods of communication to be used between graduates and 

Teagasc advisors. 

• Methods piloted with sample and evaluated to identify the most successful 

methods. 

• Evaluations of contact between students and advisors by a farm walk and 

guest lecture. 

4. Findings 

Survey of Ballyhaise Graduates 

(n=166) 

• 82% wanted to receive updates about 

the College farm 

• 60% of respondents were users of 

Facebook. 

• 77% wanted to engage with Teagasc 

Identified Methods of Communication 

• Monthly newsletter from Ballyhaise 

College 

• Text message updates to graduates about 

Ballyhaise College farm 

• Facebook group page for graduates 

• 86% wanted to attend events for recent 

graduates. 

Facebook Page 

• Received over 2000 likes during 

research 

• Video of Autumn grass management 

had over 1200 hits. 

• 43% of respondents checked into the 

Teagasc Ballyhaise Facebook page two 

– three times a week 

Newsletter 

• Circulated via email, Teagasc Website and college 

Facebook Page 

• Included farm management tips and enterprise 

performance from college farm 

• All respondents found the content interesting and 

94.3% wanted to continue receiving it. 

• 73% used the newsletter to measure their farm 

performance 

• 48.8% changed their farming practices as a result of 

its content 

Text Message 

• All respondents read the text 

messages 

• 93.6% had a smartphone. 

• 97.3% of respondents said that 

they would like to continue to 

receive text messages 

5. Key Conclusions 

Conclusions 

• Graduates were very interested in college farm updates and in 

maintaining contact with Teagasc. 

• Facebook proved to be the most efficient and interactive method. 

• Most graduates prefer to use electronic methods of communication. 

• Newsletter was found to be an excellent source of technical 

information. 


• Teagasc advisors need to be introduced to students while in college. 

• The advisory regions in Teagasc and advisors themselves with an interest 

in contacting graduates should also establish Facebook pages. 

• Graduates could be integrated into existing discussion groups. 

• Each college should consider developing their own newsletter. 


Moodle based online teaching – 

the potential for distance training models in horticulture 

Name: Colm Óg Doran 

Supervisors: Dr. Monica Gorman (UCD), Mr. John Mulhern (Teagasc) 


Moodle is a web-based learning platform used for course management and the sharing of 

course materials with students. It was adopted by Teagasc in 2008 

This study looked at how Moodle could be developed within a Teagasc college to support 

full-time courses and to examine how it could potentially support distance education. 

Objectives 

Assess the use of Moodle and its future 

potential in Teagasc Botanic Gardens; 

Identify how a module in horticulture 

can be adapted for online learning. 

Methodology 

‣ Observation of faculty use of Moodle in 

current teaching 

‣ Focus Group discussions 

‣ Survey with full-time students 

‣ Support students and faculty with Moodle 

use over 2014/15 term 

‣ Pesticide Application 3-day course 

‣ Pre-recorded classes uploaded as videos onto 

Moodle 

‣ Students learned theory independently 

‣ Practical instruction and examination delivered 

by College technicians 

‣ Evaluate progress 

In 2014, only 3% of students agreed that all 

teachers used Moodle effectively 

This rose to 25% in 2015 

92% of teachers were keen to explore how 

Moodle can be used to enhance and improve 

their teaching 

85% of teachers stated they had not received 

enough training in using Moodle 

R 

E 

S 

U 

L 

T 

S 

Students who took the online course performed 

similarly to students who had previously sat the 

traditional course 

Those who had the lowest level of prior 

education performed poorest in written 

assessments 

All students that took the course would consider 

doing another in an online format in the future 

Conclusions 

Improvements were made in the use of Moodle over the course of this study in the Botanic Gardens, 

However teachers need further support in their use of the technology to utilise Moodle fully. 

The Pesticide Application online course showed that short courses can be adapted for online delivery, 

But more research and evaluation into this potential must take place. 


Develop and Pilot a practical tool to support Non-Family Farm Partnerships in Irish Dairying 

Michael Keane 1 Dr. David Stead 2 Mr. Thomas Curran 3 

1. Teagasc Advisory Office Nenagh, Co. Tipperary 

2. School of Agriculture and Food Science UCD, Belfield, Dublin 4. 

3. Teagasc, Farm Management, REDP, Moorepark Fermoy. Co. Cork 

Background 

Defects in Irish farm structures such as small farm sizes, an elderly age profile of farmers and a lack of land mobility are hampering agricultural 

productivity. Farm partnerships have the capacity to deliver significant economic, social and cultural benefits to farmers. Hence the rationale of this 

study is to foster knowledge transfer (KT) and innovation by developing a KT tools to support non-family milk production partnerships (MPP’s). 

Objectives 

1. Review theoretical & empirical literatures on KT issues and 

MPP’s 

2. Review models of KT regarding collaborative farming 

Literature Review: 

reviewing 

knowledge transfer 

issues in 

agriculture 

nationally and 

internationally 

arrangements in Ireland, UK & USA 

3. Determine the KT needs & supports of farmers in MPP’s 

4. Develop & pilot a practical tool 

for farmers in MPP’s 

Piloting of the new 

KT tool on Teagasc 

farm structure 

specialists & 3 

farmers through 

semi-structured 

interviews / 

questionnaires 

Methodology 

Study population 

and sampling 

methods: 

Conducted semistructured 

interviews with a 

short questionnaire 

Some Key Findings 

• Limited literature on MPPs in Ireland, the awareness of and clarity on MPPs needs fuller evaluation & the concept of collaborative 

arrangements such as MPPs needs promotion to the wider farming community 

• Benefits of being in a non-family MPP; pooled resources (90%), access to additional milk quota (83%), farm efficiency (64%), better 

lifestyle (79%) 

• The mean age of a non-family MPP farmer was 47 years, average farm size was 124 ha, average herd size of 207 dairy cows in 2014 

• Graph shows the KT tools/supports that respondents requested to see developed 

• The most dominant KT tool desired was the profit share calculator (81%) 

• 3.5% of farmers in the UK are involved in Joint Ventures 

• KT Case Studies: Fresh Start initiative in the UK and Sharemilk in the USA 

• KT tools/supports developed in the UK and USA are adopted by young 

entrants and existing farmers although their success is generally limited 

Some Key Conclusions 

• By conducting a bottom-up approach to capture the experiences and knowledge of non-family MPP farmers led to the successful development of a 

new Teagasc profit share calculator 

• 9 other KT tools/supports were found from the interview/questionnaire, thus this study can provide foundations for further development of practical 

KT tools for MPPs in Ireland 

• Farm partnerships offer a mechanism for dairy expansion in the post quota era and can sustain farm viability in regard to volatile world markets 

• In the post quota era much more emphasis needs to be placed on promoting the lifestyle and labour benefits of being in a MPP 


Assessing farmers perceptions of greenhouse gas emissions and developing effective 

knowledge transfer interventions to support practice change and emissions reductions 

Méabh O’Hagan¹,² James Breen¹ Pat Murphy² 


2. Teagasc, Johnstown Castle, Co. Wexford. 

Background 

Concern regarding global warming and climate change has led to an increase in focus on greenhouse gas(GHG) emissions in recent years. Agriculture accounts for nearly 30% of Irelands GHG 

emissions. Food Harvest 2020 has set out a number of targets focusing on smart, green and sustainable growth in the production of food in Ireland which, if met, would lead to a further 

increase in emissions. However, EU leaders have set out ambitious targets for all EU member states to reduce GHG emissions by 40% versus 1990 levels by 2030. In order for Ireland to reach 

Food Harvest 2020 targets and the EUs emissions targets, there must be a significant uptake of GHG mitigating technologies in agriculture. 

Objectives 

1. To assess the current level of knowledge among Irish beef and dairy farmers with 

regards to agricultural GHG emissions. 

2. To identify which GHG mitigating technologies are most likely, and least likely to be 

adopted by Irish beef and dairy farmers. 

3. To identify the most effective method of roll-out for the Carbon Navigator tool, 

and provide Teagasc with recommendations on how to proceed with the roll-out. 

Methodology 

• Structured questionnaires were carried out with beef and dairy discussion group 

members to assess knowledge about GHG emissions. 

• A list of 11 mitigating technologies was provided and farmers were asked to rate these 

in order of preference. 

• Potential methods for roll-out of the Carbon Navigator tool will be evaluated through 

the use of focus groups. 

Carbon Navigator 

• A tool developed by Teagasc and Bord Bia to reduce 

greenhouse gas emissions from livestock production 

systems. 

• Online decision support system which evaluates the 

adoption of GHG mitigating technologies on a farm. 

• Rates farmer adoption of technologies against other 

farmers in the area. 

• Allows farmers to set targets and displays the resulting 

reduction in GHG emissions and the financial benefit to 

the farmer. 

Key Findings To Date 

Next Steps 

. 

Most popular mitigation 

technologies 

Dairy: - Extending of grazing 

season length 

. 

1. Identify discussion groups to test methods of Carbon 

Navigator roll-out and assign methods to each. 

Beef: - Improve live-weight gain 

- Slurry application in spring and in 

suitable weather conditions 

2. Identify farmers from these groups to participate in 

focus groups. 

Least popular mitigation 

technologies 

Dairy: - Dietary additives to 

reduce methane emissions 

- Planting of forestry/coppicing of 

trees, planting of hedgerows 

3. Hold focus groups to assess the effectiveness of each 

roll-out method. 

Graph 1. Respondent attitudes and opinions towards GHGs. 

Beef: - Use of urea treated to 

reduce emissions and losses to air. 

- Planting of forestry/coppicing of 

trees, planting of hedgerows 

4. Analyse the data gathered from these focus groups to 

identify most effective roll-out method. 

Key Conclusions to Date 

Conclusions 

• GHG emissions isn’t being included as a topic in many discussion groups. 

• Both dairy and beef farmers would be willing to use a tool like the Carbon 

Navigator. 

• More information may need to be made available on some of the less popular 

or less known mitigation technologies. 


• Include agricultural GHG emissions as a topic in all beef and dairy discussion 

groups. 

• Promote adoption of most popular mitigation technologies immediately. 

• Provide more information and support for least popular and lesser known 

mitigation technologies. 


A new nutrient management software tool: the 

view from farmers and advisors 

By: John Ryan Teagasc/UCD MAgrSc Innovation Support Student 

(2014-2016) 

Supervisors: Dr Paul Murphy, UCD and Tim Hyde, Teagasc 

Introduction 

• Productive soils are the foundation of any successful farming system, the interpretation of soil test results and the task 

of nutrient management planning(NMP) are two important elements in the correction of soil fertility. 

• Teagasc have recently launched a new nutrient management tool which will generate outputs for farmers such as easy 

to read farmer friendly land maps, along with updated soil reports and fertiliser plan layouts. 

• This study is assessing existing knowledge transfer (KT) soil fertility tools, and assessing how the new NMP on-line 

tool can be improved to increase the adoption of best practice in relation to soil fertility. 

Objectives 

• Assess farmer’s opinions on 

the new Soil Reports, 

Fertiliser Plans & Maps 

• Identify key changes needed 

so this new nutrient 

management software will 

have lasting benefits into the 

future 

Methods 

• Survey of beef and dairy farmers (25) 

• On-line survey of Teagasc staff (164). 

• Designed to gather opinions on current 

NMP tools and what changes they 

would like to see in future. 

Some Results to date 

Teagasc staff survey 

• Software should include option to pick the farmers preferred method of measurement e.g. Units/acre/ha, Kgs/acre/ha. etc. 

• ‘Lack of knowledge’ was outlined as the main barrier to farmers adopting soil fertility best practices by 67% of Teagasc 

respondents 

• Problem areas were identified in the soil test reports, summary sheets, fertiliser plans and in the new colour land management 

maps 

Farmer survey 

• Farmers were very pleased with new coloured maps detailing fertiliser, slurry and lime applications needed, while also 

suggesting improvements/changes they would like to see made to these. 

• Farmers want results presented in a non-scientific fashion(High/Medium/Low rather than “X” Mg/l) 

• Farmers want slurry calculations to be presented in gallons/acre/ha rather than cubic metres as it is now. 

• Only 56% of farmers knew the correct pH for grassland, while only 24% understood their soil analysis report fully. 

Conclusions to date 

•The new Teagasc nutrient management tools are good but there is room for further small improvements 

•Farmers knowledge on soil fertility needs to be improved, be it through soil fertility campaigns, newsletters or 

some other medium 

•Soil fertility needs to become the primary topic of discussion when trying to maximise grass growth

Driving Farm Innovation through Knowledge Transfer

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