Where credible R&D may arise in the pig sector
The sectors below are examples of areas in which a company might encounter a genuine scientific or technological uncertainty that warrants an R&D assessment.
| Opportunity area | Illustrative unresolved question | Suggested endpoints |
| ZnO-free post-weaning resilience | How can diet, hygiene, early-life data and environmental controls be integrated to reduce PWD risk on a defined farm type? | Faecal score, ETEC/diagnostic results, medication, mortality, removals, ADG, FCR, feed intake and cost. |
| Precision nutrition | Can an adaptive feeding system maintain FCR and carcass outcomes under ingredient/batch variability? | Intake, growth variance, FCR, carcass, nutrient excretion, cost and model accuracy. |
| Early health warning | Can multi-modal data identify clinically meaningful risk earlier than existing observation? | Lead time, sensitivity, specificity, false alerts, treatment timing, mortality and staff burden. |
| Robust sow, piglet and early-life pathway
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Can maternal nutrition, farrowing environment, early-life management and monitoring reduce mortality, weight variation or later health risk under commercial conditions?
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Survival, birth/weaning-weight distribution, health, welfare, medication, growth and lifetime efficiency. |
| Genetics and phenotype research | Can new phenotypes, selection methods or data models improve robustness, survival, feed efficiency, maternal performance or disease resilience beyond routine index use? | Repeatability, genetic/phenotypic associations, survival, productivity, welfare, health and environmental indicators. |
| Tail integrity and welfare | Can a transferable intervention be developed across genetics, group size, feeder access, enrichment and climate? | Tail lesions, behavioural events, interventions, growth, removals and repeatability. |
| Adaptive ventilation | Can room or pen-level control balance thermal comfort, gases, dust, energy and animal performance under variable conditions? | Temperature, humidity, ammonia, dust, behaviour, energy, growth and safe-failure response. |
| Low-emission manure systems | Can a process reduce emissions while maintaining nutrient value, biosecurity, safety and farm economics? | Ammonia/GHG, nutrient analysis, energy, corrosion, pathogens, uptime and unit cost. |
| Interoperable farm-to-processor data | Can permissioned feed, animal, climate, treatment, carcass, cost and assurance data be integrated reliably enough to change timely decisions? | Data completeness, error rate, decision time, traceability, user adoption, governance and commercial value. |
Building credible on-farm innovation
A well-designed commercial trial protects the business as well as the animals. It defines the unit of analysis pig, litter, pen, room, batch or farm, before choosing a metric. It identifies confounders such as health status, feed batch, stocking density, climate, season, staff practice and veterinary intervention. It also sets welfare and food-safety escalation rules before the programme begins.
The experimental question and counterfactual should be stated before selecting equipment, feed, treatment or technology. The appropriate design will depend on the hypothesis, biological system, operational constraints, welfare safeguards and available experimental unit. Where suitable, the programme may use contemporaneous controls, randomised blocks, crossover or stepped-wedge approaches. These methods are not requirements in every case; they are examples of ways to reduce bias and improve the decision value of commercial testing. Implementation fidelity should be recorded. This includes feed batch and dose, uptime, climate, stocking, operator action, health events, diagnostic context and deviations from protocol. Welfare, food-safety and veterinary escalation rules should be set in advance. Evidence should include negative results and abandoned approaches: they can be scientifically valuable and help demonstrate that the work involved genuine uncertainty rather than an inevitable implementation of established practice.
Practical Recommendation: Separate experimental work from routine production from the outset. Record the scientific or technical goal, uncertainty, method, trial allocation, failures, results, cost nexus, grants, IP ownership and responsibility for the work before the project becomes difficult to reconstruct.
| Stage gate | Key question | Evidence required |
| Problem proof | Is the loss or risk material? | Baseline data, affected batches/rooms, financial impact, welfare/health or environmental consequence. |
| Technical rationale | Why might the proposed solution work? | Scientific or engineering rationale, known limits, safety and welfare constraints, competitor/knowledge review. |
| Controlled efficacy | Does the intervention work under defined conditions? | Protocol, suitable comparison, pre-specified endpoints, records of deviations and failures. |
| System fit | Does it transfer across commercial variability? | Testing across batches, rooms, operators, seasons or sites, with implementation-fidelity records. |
| Value and verification | Is it scalable and auditable? | Welfare, health, environmental, labour and economic evidence, plus cost and documentation integrity. |
Evidence should include negative results and abandoned approaches. They are important both scientifically and in demonstrating that the work involved a genuine uncertainty rather than an inevitable implementation of established practice.
Collaboration and funding routes
The appropriate route depends on the applicant, ownership of the project, project location, commercial pathway, research partner, aid basis, costs and the status of the relevant call. A primary producer, producer group, processor, agri-tech supplier and university may all play different roles in one programme. No route should be assumed to be open or eligible without checking current terms.
| Route | Potential use | Essential eligibility point |
| Enterprise Ireland Innovation Voucher | A focused technical question with an eligible knowledge provider. Standard vouchers are €10,000 and co-funded vouchers can be up to €20,000; scheme terms must be checked. | An incorporated pig business is not automatically eligible merely by incorporation; SME, client and scheme requirements apply. |
| Enterprise Ireland Innovation Partnership Programme | Company-led collaboration with an Irish research institute for a defined research project. | The programme is for qualifying Irish-based manufacturing or internationally traded services companies that meet the programme and agency-client requirements. |
| Enterprise Ireland RD&I Fund | Product, process, service and R&D-capability projects. | Confirm client status, aid basis, costs and current terms before commitment. |
| DAFM research and bioeconomy calls | Public research programmes and specific competitive calls. | Calls are periodic rather than a single permanent entitlement; cite the exact live or relevant call. |
| DAFM European Innovation Partnership Scheme | Farmer, adviser, scientist and expert collaboration to develop and demonstrate practical innovation. | Some calls are closed while others are time-limited; use only the current relevant call and deadline. |
| Horizon Europe Cluster 6 | Larger international research and innovation collaborations in food, agriculture, environment and climate. | Work programmes and calls are time-bound; verify the 2026–2027 work programme and Funding & Tenders call terms. |
Grants and tax credits should be designed together. Grant assistance can restrict the tax-credit base, and contracts should allocate project responsibility, background IP, project IP, data rights, publication rights, confidentiality and commercial use before work begins.
From project activity to innovation value
A good project should not end with a technical result. It should produce a decision-ready evidence package: the performance result, the welfare/health and safety outcome, the implementation requirements, the cost case, the data and claims method, the IP/data position, and the scale-up plan.
A practical first discussion
An Innovation Funding Review can map active and planned work, identify potential scientific or technological uncertainties, distinguish routine production from experimental activity, screen appropriate funding routes, consider grants and tax interactions, and identify documentation, contracting, IP and data gaps before investment decisions are finalised.
For technology developers, feed businesses, processors and producer groups, commercialisation also depends on whether the solution works beyond one pilot site. The relevant evidence may include usability, reliability, staff workflow, farm economics, buyer or processor requirements, data governance, maintenance, customer-support needs and the limits of any performance claim.
Possible IP-income consideration: Knowledge Development Box
The Knowledge Development Box (KDB ) is not a general innovation incentive. It may be relevant only where a company earns income from a usable qualifying asset that it created from qualifying R&D, subject to the detailed statutory conditions. Revenue identifies qualifying assets such as computer programmes, qualifying patents and specified certified patentable IP for qualifying small companies. [24] KDB, tax-credit, IP ownership and commercialisation planning should be considered together only with specialist tax and IP advice.
How can InnoFund help me?
InnoFund can support an integrated approach that starts with identifying the uncertainty and business case; maps the appropriate company, collaboration and cost structure; aligns R&D relief, grants and capital-support considerations; and builds the record needed to defend technical and financial decisions. The objective is not to label routine operations as R&D. It is to recognise and structure genuine innovation early enough to protect the evidence, funding and commercial value it creates. InnoFund works with hundreds of farms across the Republic of Ireland as Ireland’s premier Innovation Funding and Growth Partner with a proven expertise in Agricultural Science.
Does this apply to your business?
Three questions to ask before treating a pig-sector project as potential R&D Corporation Tax Credit
- Is the activity undertaken by, or for, a company within the charge to Irish corporation tax?
- Is there a material scientific or technological uncertainty, rather than only a commercial decision?
- Is the team conducting systematic investigative or experimental work to resolve that uncertainty?
If the answer is “YES” to the above, then you should review your R&D activities with a specialist.
Methodology and limitations
This paper draws on current Irish and EU primary-source material where available, including Revenue, DAFM, Teagasc, EPA, the European Commission/JRC, EMA, Animal Health Ireland and Enterprise Ireland. Scientific literature is used to explain the biological and operational context of PWD and pharmacological ZnO withdrawal. Programme, tax, legal, welfare, environmental and funding information changes over time and should be confirmed immediately before publication, investment, project commencement or claim submission.