Circular Economy in Animal Nutrition: Feed Valorisation, Precision Livestock Farming, and Sustainability

Abstract

Livestock systems are expected to convert human-inedible biomass into animal-source food while reducing their environmental footprint, and the circular economy (CE) provides a framework for this transition. This review argues that the circular value of a feed resource depends less on its availability than on three conditions: the processing required before it can be fed safely, the controllability of its variability and hazards, and the comparability of the life cycle assessment (LCA) evidence for its environmental benefit. Accordingly, resources are classified as suitable for direct feed use (e.g., oilseed meals, distillery co-products, former foodstuffs), requiring biological or technological upgrading (e.g., solid-state fermented residues, insect meal, single-cell protein), or better suited to non-feed valorisation. Nutritional evidence, LCA findings, One Health hazards and regulatory constraints are compared across these classes, distinguishing LCA values reported by original studies from qualitative estimates. A Mediterranean case study on olive mill by-products and phytogenic additives in swine, largely conducted by the authors, is presented separately, with its limits of generalisation. Linkages and trade-offs with the Sustainable Development Goals are examined, and precision livestock farming is evaluated as a conditional enabler rather than a prerequisite. Research priorities are proposed.

1. Introduction

The global food system faces a paradox of enormous proportions: it must feed a projected population of 9.8 billion people by 2050—demanding a 50–70% increase in food production—while simultaneously operating within planetary boundaries that are already under severe stress [1]. The livestock sector is both a critical contributor to human food security and one of the most resource-intensive components of the agri-food system, accounting for approximately 14.5% of total anthropogenic greenhouse gas (GHG) emissions, consuming around 33% of all crop-based calories, and using 70% of agricultural land directly or indirectly [2]. Reconciling this dual role—essential food producer and environmental pressure source—requires systemic transformation rather than incremental efficiency gains.

The circular economy (CE) concept has emerged as one of the most compelling frameworks for achieving this transformation. Rooted in industrial ecology, biomimicry, and regenerative design, the CE replaces linear ‘take–make–dispose’ models with closed-loop material and nutrient flows [3]. In agri-food systems, this translates into a hierarchy of strategies: prevention of food waste; reuse of surplus food and by-products; recycling of nutrients through animal feeding and composting; and recovery of energy from unavoidable residuals [4]. Livestock, historically serving as the ‘upcyclers’ of agricultural co-products inedible or unpalatable to humans, are natural partners in CE agri-food design.

Yet modern intensive livestock systems have progressively diverged from this CE logic. Large-scale grain and oilseed production dedicated to feeding livestock—particularly soybeans cultivated on deforested Amazonian land and maize grown with synthetic nitrogen fertilisers—has eroded the efficiency and environmental advantage that livestock once provided by consuming low-grade biomass [5]. Re-embedding livestock in CE nutrient loops, by deliberately diverting agro-industrial by-products, food waste, insect meal, algae, and fermented substrates from wasteful disposal pathways into animal diets, represents both an environmental imperative and an economic opportunity [6].

Mediterranean countries have particular CE potential in animal nutrition: the olive oil industry alone generates millions of tonnes of olive mill waste annually [7], and the polyphenol-rich composition of these by-products makes them especially promising as functional feed ingredients. Studies by the present author group have examined solid-state fermentation of olive mill stone waste and related residues and their use in pig diets [8,9]; these studies are discussed as a delimited case study (Section 3.7) rather than as representative of the field.

Precision livestock farming (PLF)—the data-driven, sensor-enabled management of individual animals using IoT devices, artificial intelligence, and decision-support systems—is increasingly recognised as an important enabling technology for CE-compatible nutrition [10]. Real-time monitoring of feed intake, body condition, and environmental conditions can allow farmers to match nutrient supply to animal requirements with minimal waste, reduce risks associated with compositional variability in unconventional CE feed ingredients, and generate data that may support verification of CE performance outcomes for regulatory and market purposes.

The central argument of this review is that the circular value of a feed resource is determined less by its availability than by three conditions: (i) the processing route required before it can be fed safely; (ii) the degree to which its compositional variability and associated hazards can be controlled; and (iii) whether its claimed environmental benefit is supported by LCA evidence that is comparable in functional unit and system boundary. To make this argument operational, CE-aligned resources are grouped into three classes. Class A comprises materials suitable for direct incorporation into compound feed after conventional processing (e.g., oilseed meals, cereal and distillery co-products, molasses, former foodstuffs). Class B comprises substrates that require biological or technological upgrading before they become nutritionally or hygienically acceptable feed ingredients (e.g., lignocellulosic residues upgraded by solid-state fermentation, insect meal reared on organic side-streams, single-cell protein and microalgae). Class C comprises residual streams for which non-feed valorisation (e.g., anaerobic digestion, acidogenic fermentation, composting) is more appropriate; these contribute to the circular bioeconomy without producing feed ingredients. Drawing on the authors’ experience with feeding trials in commercial pig herds, the review also identifies where experimental evidence stops short of conclusions that can be generalised across species, feedstocks and production systems, and treats PLF as a conditional enabler rather than a prerequisite for circular feeding.

This review provides a comprehensive, multidisciplinary synthesis of the current evidence base for CE-based animal nutrition. Section 2 establishes the conceptual and regulatory framework. Section 3 evaluates CE feed ingredient categories according to the classification above, presents the authors’ Mediterranean case study separately (Section 3.7), and discusses category-specific limitations. Section 4 examines sustainability assessment, including LCA and One Health hazards. Section 5 analyses linkages and trade-offs between CE-based animal nutrition and the UN SDGs. Section 6 evaluates PLF as an enabling technology. Section 7 addresses future challenges, and Section 8 provides conclusions.

Review Scope and Methodological Approach

This article is conceived as a narrative, evidence-integrative review rather than a formal systematic review, reflecting the breadth of an inherently interdisciplinary subject that spans animal nutrition, fermentation biotechnology, environmental life cycle assessment, digital agriculture, and sustainable development policy. A structured literature-search approach was nevertheless used to improve transparency and reproducibility. The review should therefore be interpreted as a structured narrative synthesis rather than a PRISMA-compliant systematic review [11,12].

Literature was identified through structured searches of PubMed, Scopus, and Web of Science, covering publications from 2014 to 2026, combined with a citation-chaining (‘snowballing’) step in which the reference lists of key studies and prior reviews were examined to capture foundational or highly cited works that a keyword search alone might miss. The core conceptual search terms combined (i) circular-economy vocabulary (‘circular economy’, ‘CE’, ‘upcycling’, ‘by-product valorisation’, ‘bioeconomy’); (ii) animal nutrition and target-ingredient terms (‘animal nutrition’, ‘livestock feed’, ‘swine’, ‘poultry’, ‘ruminant’, ‘olive mill waste’, ‘insect meal’, ‘microalgae’, ‘single-cell protein’, ‘solid-state fermentation’); and (iii) enabling-technology and outcome terms (‘precision livestock farming’, ‘life cycle assessment’, ‘sustainable development goals’), joined with Boolean operators (AND/OR) and adapted to the syntax of each database. To improve interpretation of heterogeneous evidence, findings were considered according to evidence type and maturity: (i) independent replicated animal or farm studies; (ii) single animal/farm studies or validated modelling/LCA studies; (iii) laboratory or in vitro evidence; and (iv) conceptual, policy, or exploratory evidence. Quantitative comparisons are interpreted cautiously where functional units, system boundaries, allocation procedures, animal species, or production systems differ.

Across the three databases, the search and citation-chaining process retrieved approximately 340 records. After removal of approximately 55 duplicates, approximately 285 records were screened by title and abstract, of which approximately 75 were excluded as out of scope. Approximately 210 records underwent full-text assessment; of these, approximately 139 were excluded because they lacked an animal nutrition or livestock feeding component, did not report primary data, LCA results or policy analysis relevant to the review, or duplicated evidence already represented by a more complete source. Of the remaining 71 eligible sources, six further studies by the author group were not cited, to limit self-citation (see below), so that the reference list comprises 65 sources: 53 peer-reviewed articles, reviews and proceedings papers, and 12 policy, regulatory or institutional documents. Two ISO standards on LCA methodology, cited in Section 4.1, are additionally included in the reference list. Of these, the six studies of the Mediterranean case (five by the author group, including one review, and one independent study [13]) are summarised in Section 3.8, and the LCA synthesis in Section 4.1 draws on 12 sources. The screening process is summarised in Supplementary Figure S1. These figures are approximate, reflecting the narrative rather than systematic nature of the review, and are not intended as a formally auditable PRISMA count.

Inclusion criteria comprised peer-reviewed primary research and review articles published in English that reported empirical data, life cycle assessment findings, or policy analysis directly relevant to CE-aligned feed ingredients, PLF technologies, or the SDG dimensions of animal nutrition; regulatory texts and UN policy documents were included where they defined the governing framework discussed in Section 2.3. Non-peer-reviewed sources, conference abstracts without full text, and studies addressing CE principles without any animal nutrition or livestock feeding component were excluded. Given the narrative rather than systematic design, we did not apply formal risk-of-bias scoring; instead, we qualitatively assessed each primary study for the clarity of its experimental or analytical design, the transparency of its reported methodology, and its relevance to the CE–animal nutrition nexus.

Given the direct involvement of several authors of this review in the primary research examined in Section 3.1, Section 3.2, Section 3.3, Section 3.4, Section 3.5, Section 3.6, Section 3.7, Section 3.8 and Section 4.3 [8,9,14,15,16], these studies were subjected to the same inclusion criteria and are presented alongside, and cross-checked against, the independent international literature rather than being treated as a privileged evidence stream; readers should note this potential source of emphasis when interpreting the relative weight given to Mediterranean olive by-product and Greek swine-production case studies throughout the review. To keep self-citation to a minimum, only one study per stage of the case study is cited, and related studies by the group on other substrates, formulations and species are not cited. In quantitative terms, five of the 67 references (approximately 7%) involve one or more authors of this article; the study by Gerasopoulos et al. [13] was conducted by an independent group and is not counted among them. To limit this emphasis, the authors’ studies are cited in Section 5 and Section 6 only where they add information not available from independent sources, and general conclusions are based on independent evidence wherever it exists.

During the preparation of this review, generative artificial intelligence tools (Claude, Anthropic, Claude Opus 5.5; ChatGPT, OpenAI, GPT-4o, May 2024 version) were used to assist in organising the literature corpus and in rendering figures from data and conceptual structures defined by the authors. The authors reviewed and edited all outputs, checked all figures against the cited source data, and take full responsibility for the content of this publication.

2. Conceptual and Regulatory Framework

2.1. Definitions, Principles, and Hierarchy

The Ellen MacArthur Foundation defines the circular economy as ‘an economic system aimed at eliminating waste and the continual use of resources through reuse, sharing, repair, refurbishment, remanufacturing, and recycling to create a closed-loop system, minimising the use of resource inputs and the creation of waste, pollution and carbon emissions’ [3]. Applied to agri-food, the CE framework overlaps substantially with, but is broader than, bioeconomy thinking: it encompasses not only biological materials but also water, packaging, energy, and inorganic nutrients such as phosphorus and potassium.

Three nested principles underpin the CE: (i) design out waste and pollution from systems from the outset; (ii) keep products and materials in use at their highest value for as long as possible; and (iii) regenerate natural systems through nutrient cycling and land restoration [3]. For animal nutrition, these map, respectively, to: (i) diverting agro-industrial residues, food waste, and surplus biomass from landfill, incineration, or anaerobic digestion into animal feed; (ii) extending the productive lifespan of nutrients by incorporating them into feed formulations that can be repeatedly cycled through animal metabolism and manure back to cropland; and (iii) using precision manure application and regenerative grazing to restore soil organic matter and biodiversity [17].

2.2. Livestock as CE Converters: The Upcycling Paradigm

Livestock have historically been the ‘waste managers’ of agrarian societies, consuming crop residues, kitchen scraps, and processing by-products that humans could not or would not eat. In doing so, they converted low-grade biomass into nutrient-dense foods—milk, meat, eggs—while simultaneously producing manure that fertilised the land from which the crops were grown, completing a virtuous CE cycle [5,18]. Wilkinson [18] proposed a ‘net food production’ lens for evaluating livestock CE value: species and production systems that convert human-inedible biomass into human-edible protein make a net positive contribution to food security; those that consume more human-edible protein than they produce represent a net competitive burden. Integrating high proportions of CE-derived, human-inedible feed materials into livestock rations is therefore both an environmental and a food security strategy.

Critically, closing the CE loop also requires managing livestock outputs efficiently. Nitrogen and phosphorus in animal manure represent the ‘recovered resources’ of the CE system. Precise quantification of manure nutrient output—enabled by PLF monitoring technologies—allows optimal field application of manure as a substitute for synthetic fertilisers, recovering embedded nutrients and reducing the energy-intensive Haber–Bosch synthesis of nitrogen fertilisers [19]. Innovative downstream technologies—struvite precipitation, biogas production, digestate valorisation—further extend the CE loop at the farm and landscape scale [20].

The convergence of circularity with animal and public health is increasingly framed as a One Health imperative rather than a purely environmental one. Shurson and Urriola [21] argue that sustainable swine feeding programmes require the simultaneous optimisation of nutrient-use efficiency, animal and human health, and socio-economic outcomes, and that circular feeding strategies—sourcing by-products, upcycling food waste, and precision-formulating diets—cannot be evaluated on environmental metrics alone without also accounting for feed safety, zoonotic risk, and antimicrobial stewardship. This multi-objective framing is directly compatible with, and reinforces, the CE hierarchy described above, and is revisited in Section 4.3 and Section 7.7 of this review.

2.3. Regulatory Context in the European Union

The EU has progressively built a regulatory architecture that increasingly supports CE-compatible animal nutrition. The Circular Economy Action Plan (2020) explicitly identifies the food system as a priority transition area and calls for measures to increase the use of agri-food by-products as animal feed [4]. The Farm-to-Fork Strategy (2020) sets 2030 targets of a 50% reduction in overall EU sales of antimicrobials for farmed animals and aquaculture, a reduction of nutrient losses by at least 50% and a reduction of fertiliser use by at least 20%, all of which favour feeding approaches that improve animal health and close nutrient loops [22]. Commission Regulation (EU) 2021/1372 re-authorised processed animal proteins (PAP) from non-ruminants—including insects—in pig and poultry diets [23]. Regulation (EU) 2023/1115 on deforestation-free supply chains creates indirect incentives to source feed from CE waste streams [24]. However, significant regulatory gaps persist, including heterogeneous national implementation of the Commission guidelines on the feed use of former foodstuffs, limited approval of insect species across all livestock categories, and no dedicated regulatory framework for SSF-upgraded agro-industrial by-products [25].

3. CE-Aligned Feed Ingredients: Classification and Evidence

The feed resources reviewed in this section differ less in their origin than in what must be done to them before they can be fed. Applying the classification introduced in Section 1, most oilseed meals, cereal, distillery and sugar-processing co-products, dried fruit and vegetable pulps and packaged former foodstuffs belong to Class A: they enter compound feed after conventional processing (drying, ensiling, unpacking, grinding) and are controlled through existing feed-quality systems. Olive cake straddles Classes A and B: it can be fed after drying and partial destoning, whereas stone-rich and lignified fractions require upgrading. Lignocellulosic residues upgraded by SSF, insect meal, microalgae and single-cell proteins belong to Class B, because their nutritional value and safety depend on a biological conversion step whose conditions must themselves be controlled. Seaweeds and phytogenic extracts are used as additives rather than bulk ingredients. Finally, Class C streams—very wet, perishable or contaminated residues, and the fractions remaining after feed use—are valorised through non-feed routes (Section 3.3). Because the evidence base, the hazards and the regulatory position differ between these classes, they are evaluated separately in Section 3.1, Section 3.2, Section 3.3, Section 3.4, Section 3.5, Section 3.6 and Section 3.9.

Table 1 provides a structured overview of the principal CE-aligned feed ingredient categories, their nutritional profiles, target species, CE benefits and class (A or B) as defined in Section 1.

Table 1. Principal CE-aligned feed ingredient categories, nutritional highlights, target livestock species, and CE benefits. SSF = solid-state fermentation; OMSW = olive mill stone waste; BSFL = black soldier fly larvae; DDGS = dried distillers’ grains with solubles; CP = crude protein. Class A = suitable for direct feed use after conventional processing; Class B = requires biological or technological upgrading before feed use; Class C streams (non-feed valorisation) are not listed (see Section 3.3). ↑ = increase; ↓ = decrease.

CE Feed Category	Example Ingredients	Nutritional Highlights	Target Species	CE Benefit/Key References
Olive mill by-products (A/B)	OMSW, olive cake, OMW	High polyphenols (hydroxytyrosol, oleuropein); antioxidant capacity enhanced by SSF	Pigs, poultry, small ruminants	Diverts potentially problematic by-product streams; valorises polyphenols; may reduce reliance on synthetic antioxidants [8,13]
Oilseed by-products (A)	Rapeseed meal, sunflower meal, palm kernel meal	25–40% CP; variable fibre; B vitamins and minerals	Pigs, poultry, ruminants, aquaculture	Reduces soybean imports; lowers deforestation pressure [26]
Cereal/distillery by-products (A)	DDGS, brewers’ spent grain (BSG), wheat bran	Energy + protein supplement; high digestible fibre for ruminants	Cattle, pigs, poultry, sheep	Valorises bioethanol/beer co-streams; reduces landfill burden [27]
Fruit & vegetable processing residues (A)	Tomato pomace, citrus pulp, apple pomace, grape marc	Fermentable fibre; lycopene, carotenoids, polyphenols; prebiotic properties	Ruminants, pigs, poultry	Diverts horticultural processing waste; may improve animal-product quality [28]
Molasses (A)	Sugarcane molasses, sugar beet molasses	High soluble sugars (45–65%); B vitamins; palatability enhancer	Cattle, sheep, pigs	CE 3R principle: by-product of sugar refining [29]
Former foodstuffs/Food waste (A)	Surplus bread, bakery waste, pasta, confectionery	Variable energy/protein, matching cereal–soy diets; cost-negative	Pigs, poultry	Diverts surplus food from landfill; catering waste excluded under EU law [30]
Insect meal (B)	BSFL (Hermetia illucens), mealworm (Tenebrio molitor)	40–45% CP; lauric acid; antimicrobial peptides; bioavailable minerals	Poultry, pigs, aquaculture	Bioconverts organic waste; replaces fishmeal/soybean meal [31,32]
Microalgae (B)	Spirulina (Arthrospira platensis), Chlorella vulgaris, Nannochloropsis spp.	50–70% CP; omega-3 (EPA, DHA); pigments (phycocyanin, astaxanthin)	Poultry, pigs, aquaculture, ruminants	Grown on CO2 + wastewater; no arable land [33]
Seaweeds/Macroalgae (additive)	Asparagopsis taxiformis, Laminaria spp., Ulva spp.	Iodine; bioactive polysaccharides; bromoform (antimethanogenic)	Ruminants, pigs, poultry	Reduces enteric CH4 yield by 45–80% (dose- and diet-dependent); ocean-based CE loop [34]
Single-cell proteins (SCP) (B)	Yeast, bacterial (Methylococcus), fungal SCP	40–60% CP; balanced amino acid profile; high digestibility	Aquaculture, poultry, pigs	Grown on agri-residues, biogas, CO2; decouples feed from land [35]
SSF-upgraded by-products (B)	Pistachio shell + OMSW + Lathyrus clymenum husks (SSF with Pleurotus ostreatus)	CP compositional upgrade confirmed in vitro [9]; in vivo antioxidant/redox benefit confirmed [8]; lignin/fibre response is substrate-dependent (↓ in OMSW mixtures, ↑ in Lathyrus mixtures) [9]	Pigs (weaned piglets)—in vivo trial [8]; substrate chemistry only, no animal trial, in [9]	Dual waste stream valorisation; fungal bioconversion [8,9]
Phytogenic feed additives (additive)	Curcumin, silymarin, olive leaf extracts, grape marc polyphenols	Antioxidant, anti-inflammatory, hepatoprotective; mycotoxin risk mitigation	Pigs, poultry, ruminants	Sourced from plant-processing residues; CE-formulated additives [14]

Table 1. Principal CE-aligned feed ingredient categories, nutritional highlights, target livestock species, and CE benefits. SSF = solid-state fermentation; OMSW = olive mill stone waste; BSFL = black soldier fly larvae; DDGS = dried distillers’ grains with solubles; CP = crude protein. Class A = suitable for direct feed use after conventional processing; Class B = requires biological or technological upgrading before feed use; Class C streams (non-feed valorisation) are not listed (see Section 3.3). ↑ = increase; ↓ = decrease.

CE Feed Category	Example Ingredients	Nutritional Highlights	Target Species	CE Benefit/Key References
Olive mill by-products (A/B)	OMSW, olive cake, OMW	High polyphenols (hydroxytyrosol, oleuropein); antioxidant capacity enhanced by SSF	Pigs, poultry, small ruminants	Diverts potentially problematic by-product streams; valorises polyphenols; may reduce reliance on synthetic antioxidants [8,13]
Oilseed by-products (A)	Rapeseed meal, sunflower meal, palm kernel meal	25–40% CP; variable fibre; B vitamins and minerals	Pigs, poultry, ruminants, aquaculture	Reduces soybean imports; lowers deforestation pressure [26]
Cereal/distillery by-products (A)	DDGS, brewers’ spent grain (BSG), wheat bran	Energy + protein supplement; high digestible fibre for ruminants	Cattle, pigs, poultry, sheep	Valorises bioethanol/beer co-streams; reduces landfill burden [27]
Fruit & vegetable processing residues (A)	Tomato pomace, citrus pulp, apple pomace, grape marc	Fermentable fibre; lycopene, carotenoids, polyphenols; prebiotic properties	Ruminants, pigs, poultry	Diverts horticultural processing waste; may improve animal-product quality [28]
Molasses (A)	Sugarcane molasses, sugar beet molasses	High soluble sugars (45–65%); B vitamins; palatability enhancer	Cattle, sheep, pigs	CE 3R principle: by-product of sugar refining [29]
Former foodstuffs/Food waste (A)	Surplus bread, bakery waste, pasta, confectionery	Variable energy/protein, matching cereal–soy diets; cost-negative	Pigs, poultry	Diverts surplus food from landfill; catering waste excluded under EU law [30]
Insect meal (B)	BSFL (Hermetia illucens), mealworm (Tenebrio molitor)	40–45% CP; lauric acid; antimicrobial peptides; bioavailable minerals	Poultry, pigs, aquaculture	Bioconverts organic waste; replaces fishmeal/soybean meal [31,32]
Microalgae (B)	Spirulina (Arthrospira platensis), Chlorella vulgaris, Nannochloropsis spp.	50–70% CP; omega-3 (EPA, DHA); pigments (phycocyanin, astaxanthin)	Poultry, pigs, aquaculture, ruminants	Grown on CO2 + wastewater; no arable land [33]
Seaweeds/Macroalgae (additive)	Asparagopsis taxiformis, Laminaria spp., Ulva spp.	Iodine; bioactive polysaccharides; bromoform (antimethanogenic)	Ruminants, pigs, poultry	Reduces enteric CH4 yield by 45–80% (dose- and diet-dependent); ocean-based CE loop [34]
Single-cell proteins (SCP) (B)	Yeast, bacterial (Methylococcus), fungal SCP	40–60% CP; balanced amino acid profile; high digestibility	Aquaculture, poultry, pigs	Grown on agri-residues, biogas, CO2; decouples feed from land [35]
SSF-upgraded by-products (B)	Pistachio shell + OMSW + Lathyrus clymenum husks (SSF with Pleurotus ostreatus)	CP compositional upgrade confirmed in vitro [9]; in vivo antioxidant/redox benefit confirmed [8]; lignin/fibre response is substrate-dependent (↓ in OMSW mixtures, ↑ in Lathyrus mixtures) [9]	Pigs (weaned piglets)—in vivo trial [8]; substrate chemistry only, no animal trial, in [9]	Dual waste stream valorisation; fungal bioconversion [8,9]
Phytogenic feed additives (additive)	Curcumin, silymarin, olive leaf extracts, grape marc polyphenols	Antioxidant, anti-inflammatory, hepatoprotective; mycotoxin risk mitigation	Pigs, poultry, ruminants	Sourced from plant-processing residues; CE-formulated additives [14]

3.1. Olive Mill By-Products and Mediterranean Agro-Industrial Residues

Southern European olive oil production generates several million tonnes of solid and liquid by-products annually [7]. Olive mill stone waste (OMSW), olive cake, and olive mill wastewater (OMW) are characterised by high polyphenol content—particularly hydroxytyrosol, oleuropein, tyrosol, and caffeic acid—which confers potent antioxidant, anti-inflammatory, and antimicrobial properties but also creates environmental toxicity if improperly disposed [8,13]. Solid-state fermentation (SSF) with white-rot fungi, particularly Pleurotus ostreatus, can biotransform these by-products, increasing crude protein content and generating enzymatic activities, although the magnitude and even the direction of changes in lignin and other fibre fractions depend on the substrate mixture [9,36].

The liquid fraction of olive processing, OMW, presents a distinct valorisation pathway to the solid OMSW and cake fractions, since its very high polyphenol concentration and biological oxygen demand make it simultaneously the most environmentally hazardous and the most bioactive of the olive by-product streams. Papatsiros et al. (2023) [16] evaluated a natural polyphenolic extract derived from OMW in weaned piglets under commercial field conditions and reported significant reductions in post-weaning diarrhoea incidence and in circulating oxidative stress biomarkers relative to untreated controls, indicating that OMW-derived polyphenols retain functional bioactivity when delivered as a feed extract rather than as a solid fermented substrate. Together with the independent study of Gerasopoulos et al. [13], who reported improved redox status in piglets fed an OMW-derived polyphenolic by-product, these results indicate that both solid and liquid olive by-products can be considered for pig nutrition, although most trials have assessed redox and health biomarkers rather than commercial performance or economic outcomes.

Eliopoulos et al. (2024) [8] conducted a controlled trial with 200 weaned piglets fed a diet containing 50 g/kg of a SSF mixture of OMSW and Lathyrus clymenum husks for 40 days. The supplemented group showed improved blood antioxidant parameters (Table 2). Complementary research by Eliopoulos et al. (2022) [9] demonstrated that SSF of pistachio shell combined with OMSW using Pleurotus ostreatus increased the crude protein content of pistachio shell, a hard agricultural waste resistant to conventional feed processing, whereas lignin decreased in mixtures with OMSW but increased in mixtures with L. clymenum pericarp.

This Mediterranean, olive-focused evidence base is consistent with, and reinforced by, independent international work on SSF-based feed upcycling. Sun et al. (2024) [37] reviewed bioprocessing routes—including SSF—for upcycling agro-industrial and food wastes into high-nutritional-value animal feed at a global scale, concluding that fermentation-based upgrading is among the most broadly applicable strategies for closing feed-sector nutrient loops regardless of substrate origin, while Šelo et al. (2021) [36] provide a comprehensive independent review of SSF valorisation of lignocellulosic agro-food residues more broadly, corroborating the substrate-selection and process-parameter principles (moisture, particle size, inoculum) that underlie the Mediterranean case studies reviewed above. These independent reviews support the general feasibility of SSF-based upgrading, but they also show that outcomes depend on substrate, strain and process conditions and that in vivo, scale-up and economic data remain scarce; the Mediterranean results should therefore be regarded as substrate-specific until independently replicated.

3.2. Oilseed Meal By-Products

The global oilseed crushing industry generates protein-rich meal constituting the primary plant-protein ingredient in livestock feeds worldwide. Soybean meal is the dominant protein ingredient worldwide, and part of its production is linked to tropical deforestation [5]. Rapeseed meal (32–38% CP) and sunflower meal (28–35% CP) from European oilseed crushing represent major Class A alternatives [26]; the environmental benefit of replacing imported soybean meal with locally produced meals depends largely on how land-use change is accounted for, and published estimates are not directly comparable [38,39].

3.3. Cereal Processing, Distillery, and Fruit Processing By-Products

Dried distillers’ grains with solubles (DDGS), brewers’ spent grain (BSG), tomato pomace, citrus pulp, apple pomace, and grape marc represent abundant CE feed materials generated by the food and beverage processing industries. DDGS contains approximately 27–30% crude protein and high digestible phosphorus; grape marc is rich in anthocyanins and other polyphenols, and fruit and vegetable co-products such as citrus pulp, tomato pomace and grape pomace have been used as functional ingredients to modify the fatty acid profile or oxidative stability of animal products [28]. Molasses—containing 45–65% total sugars—serves as a palatable energy supplement and illustrates the CE 3R principle (reduce, reuse, recycle) applied to sugar refining waste [27,29].

Not every food-industry residue should be directed to feed. Streams that are highly perishable, too dilute, chemically unsuitable or of uncertain safety (Class C) are often better valorised through non-feed routes that still contribute to the circular bioeconomy. Beyond SSF, which aims to improve the nutritional properties of a feed substrate, other fermentation-based routes target different bioproducts: acidogenic fermentation of food-industry by-products, for example, converts carbohydrate-rich residues into volatile fatty acids that can serve as precursors for biopolymers and other bio-based chemicals [40], while anaerobic digestion recovers energy and a nutrient-rich digestate [20]. These routes do not produce feed ingredients, but they compete for the same residues; the choice between feed and non-feed valorisation should therefore be based on the nutritional value, safety and local demand for each stream rather than on a default preference for feed use (see also Section 5.6).

3.4. Food Waste and Former Foodstuffs

Approximately 1.3 billion tonnes of food is lost or wasted globally each year [41]. Converting food waste and former foodstuffs into animal feed is consistently identified as one of the highest-value options in the food waste hierarchy [4]. Life cycle studies indicate that converting food waste into pig feed generally has lower environmental impacts than conventional feed production and alternative waste treatments, but the results depend strongly on the processing technology (e.g., heat treatment and drying) and on the avoided-disposal credits assumed [42]. A modelling analysis by zu Ermgassen et al. [30] estimated that, if heat-treated food waste (swill) were legally fed to pigs in the EU, as in Japan and South Korea, the land use of EU pork production could be reduced by about one fifth (approximately 1.8 million ha).

A review by the author group [15] grouped food-industry by-products for pig diets by principal nutrient contribution (energy-, protein- or fibre-dense) and identified batch-to-batch compositional variability, year-round supply logistics and heterogeneous national interpretation of EU former-foodstuff legislation as the main barriers to wider adoption (Section 2.3, Section 7.1 and Section 7.2).

3.5. Insect Meal, Microalgae, Seaweeds, and Single-Cell Proteins

Black soldier fly larvae (BSFL, Hermetia illucens) can bioconvert food waste and agro-industrial residues into biomass containing 40–45% crude protein and 25–35% ether extract, with antimicrobial peptides that modulate gut microbiota [31,32]. Microalgae—including Spirulina, Chlorella, and Nannochloropsis—provide 50–70% CP and can be cultivated on CO₂ and nutrient-rich wastewater effluents, effectively acting as tertiary wastewater treatment organisms [33]. The red seaweed Asparagopsis taxiformis fed at 0.25% and 0.5% of organic matter intake for 147 days reduced enteric methane yield in beef steers by 45% and 68%, respectively, across diets, and by up to 80% on a low-forage diet [34]. Single-cell proteins produced by fermentation of yeast, bacteria, or fungi on agricultural residues or biogas can reach 40–60% CP and largely decouple protein supply from arable land use [35].

3.6. Phytogenic Feed Additives and Mycotoxin Management from CE Sources

Phytogenic feed additives sourced from agro-industrial by-products represent a rapidly expanding CE category. Curcumin is isolated from turmeric rhizomes and processing residues; silymarin from milk thistle seeds and marc; hydroxytyrosol and oleuropein from olive leaves and OMW; and resveratrol from grape marc.

Papatsiros et al. (2024) [14] evaluated a multi-component mycotoxin detoxifier—formulated with clay minerals, curcumin, silymarin, yeast cell wall, and hydrolysed yeast—in 300 weaned piglets challenged with fumonisin-contaminated feed across two independent commercial farm trials. The treated group showed significantly reduced plasma TBARS and CARBs and increased total antioxidant capacity at 45 and 70 days of age, alongside improved average daily gain and feed conversion ratio.

These findings are corroborated by independent trials outside the author group’s own network. Raj et al. (2025) [43] evaluated a comparable multi-component mycotoxin-detoxifying agent in weaned pigs under combined dietary exposure to deoxynivalenol and zearalenone, reporting improved health and performance outcomes consistent in direction with those reported in [14], despite differing formulations, mycotoxin challenges, and research groups. More broadly, Biswas and Kim (2024) [44] reviewed the evidence base for phytogenic feed additives as dietary enhancements in swine and poultry and concluded that antioxidant, antimicrobial, and growth-promoting benefits are consistently reported across formulations and production systems, though inclusion-rate standardisation and mechanism-of-action data remain comparatively limited. These independent sources support the generalisability of the CE-sourced phytogenic strategies discussed in this section beyond the specific formulations and farms studied by the author group.

3.7. A Mediterranean Case Study: Cumulative Evidence-Building from Fermentation Chemistry to Farm Systems

The studies summarised in Section 3.1, Section 3.4 and Section 3.6 form a coherent case study conducted by an overlapping author group spanning the University of Thessaly, the Hellenic Agricultural Organization-Demeter, and the Agricultural University of Athens. This programme traces a three-stage translational arc (Figure 1): (1) ingredient-level bioconversion, in which solid-state fermentation of olive mill stone waste and other agro-industrial residues using Pleurotus ostreatus increases crude protein and enriches bioactive polyphenol fractions [8,9]; (2) controlled and field animal trials, in which these SSF-upgraded substrates or related phytogenic additives improve antioxidant status and reduce oxidative stress markers in weaned piglets [8,14,16]; and (3) a systems-level review of food-industry by-products in pig diets and their environmental footprint [15]. This progression is presented as one illustration of cumulative evidence-building, not as representative of the wider field.

Figure 1. The Mediterranean case study follows a three-stage translational sequence: laboratory bioprocessing of agro-industrial residues, animal trials under commercial conditions, and a systems-level review. Evidence tiers follow Section Review Scope and Methodological Approach. Sources: Stage 1, Eliopoulos et al. (2022) [9]; Stage 2, Eliopoulos et al. (2024) [8], Papatsiros et al. (2023) [16], Papatsiros et al. (2024) [14] and the independent study of Gerasopoulos et al. (2015) [13]; Stage 3, Papatsiros et al. (2025) [15]. Outcomes not yet assessed are shown in the lower panel. ↑ = increase; ↓ = decrease; horizontal arrows between panels indicate the sequence of stages.

Three limitations bound what this case study can support. First, most animal trials measured redox and health biomarkers over relatively short periods, and only one reported growth performance; none has yet assessed carcass quality, economic return or the environmental footprint of an SSF-upgraded ingredient under commercial conditions. Second, the SSF studies were conducted at laboratory scale with specific substrate ratios and a single fungal species, and the compositional response—particularly of lignin—differed between substrate mixtures [9]; the results cannot therefore be transferred to other feedstocks without testing. Third, the animal trials were conducted on Greek farms by overlapping teams, so independent, multi-site replication is lacking. Accordingly, the case study is used here to illustrate how evidence can be built from ingredient to farm level, whereas the general conclusions of this review on CE feed ingredients rest on the independent literature summarised in Section 3.1, Section 3.2, Section 3.3, Section 3.4, Section 3.5, Section 3.6 and Section 4.

3.8. Summary of the Primary Studies of the Mediterranean Case Study

Across CE feed categories, evidence maturity is heterogeneous. Commercially established co-products have a substantially larger practical evidence base than emerging ingredients such as SCP, microalgae, seaweeds, and some SSF-derived substrates. Claims concerning environmental benefits, health effects, or scalability should therefore be interpreted according to the maturity and independence of the supporting evidence.

Table 2 consolidates the design, scale, and principal quantitative findings of the primary studies of the case study (five by the author group and one independent study [13]) discussed narratively across Section 3.1, Section 3.4 and Section 3.6. Readers should note that the p-values reported in this table derive from single-study analyses without stated correction for multiple comparisons across simultaneously tested biomarkers, and that arm-level sample sizes and standardised effect sizes beyond the reported p-values are not uniformly available in the underlying publications; findings should be interpreted with this in mind.

Table 2. Summary of the design, scale, and principal quantitative findings of the primary studies by the author group underpinning the translational case study of Section 3.7. FRSA = free radical scavenging activity; GSH = reduced glutathione; ADG = average daily gain; FCR = feed conversion ratio. Arrows indicate the direction of the reported effect in the treatment group relative to control. An Evidence Tier column, classifying each study against the four-tier evidence-maturity framework defined in Section Review Scope and Methodological Approach (Tier I: independent replicated studies; Tier II: single field/animal-farm studies; Tier III: laboratory/in vitro evidence; Tier IV: systems-level narrative synthesis), is included. Gerasopoulos et al. [13] is an independent study and is not co-authored by the present authors.

Study (Ref.)	Design/Scale	Principal Findings	CE Relevance	Evidence Tier
Eliopoulos et al. 2024 [8]	Controlled trial; 200 weaned piglets; 50 g/kg SSF OMSW + Lathyrus clymenum husks; 40 days	↓ TBARS (p = 0.049); ↓ protein carbonyls (p = 0.012); ↑ FRSA (p = 0.005); ↑ GSH (p = 0.040); ↑ catalase (p = 0.012)	SSF-upgraded olive by-product safely improves antioxidant status in pigs	Tier II—single field/animal-farm study
Gerasopoulos et al. 2015 [13] (independent group)	Piglet feeding trial with OMW polyphenolic by-product	Improved redox status in blood and tissues	Direct valorisation of liquid olive by-product as feed	Tier II—single field/animal-farm study
Eliopoulos et al. 2022 [9]	SSF of pistachio shell (PS) mixed with olive mill stone waste (OMSW, 10–20% w/w) OR Lathyrus clymenum pericarp (LP, 20–50% w/w), inoculated with Pleurotus ostreatus, 21-day incubation	↑ crude protein (up to +33.87%, 20% LP+PS); cellulose ↑ in all mixtures (+13–17%); lignin ↓ in PS+OMSW mixtures (up to −14.22%) but ↑ in PS+LP mixtures (+11 to +38%); β-glucans markedly ↑ (up to ~480-fold in 100% PS)	Dual waste-stream valorisation via fungal bioconversion; note lignin/anti-nutritional response is substrate-specific, not uniformly reduced	Tier III—laboratory/in vitro (substrate chemistry only)
Papatsiros et al. 2023 [16]	Field trial; weaned piglets; OMW-derived polyphenolic extract	↓ post-weaning diarrhoea incidence; ↓ oxidative stress biomarkers	OMW polyphenols retain bioactivity as a liquid feed extract	Tier II—single field/animal-farm study
Papatsiros et al. 2024 [14]	Two-farm field trial; 300 weaned piglets; fumonisin challenge	↓ plasma TBARS/CARBs; ↑ total antioxidant capacity; ↑ ADG; improved FCR	CE-formulated mycotoxin detoxifier protects growth performance	Tier II—two-farm trial by the same group (not independently replicated)
Papatsiros et al. 2025 [15]	Systematic narrative review; pig diets across production cycle	Feed-sector carbon footprint reduction with quality-assured by-product diets	Synthesises food-industry by-product use at systems level	Tier IV—systems-level narrative synthesis

Table 2. Summary of the design, scale, and principal quantitative findings of the primary studies by the author group underpinning the translational case study of Section 3.7. FRSA = free radical scavenging activity; GSH = reduced glutathione; ADG = average daily gain; FCR = feed conversion ratio. Arrows indicate the direction of the reported effect in the treatment group relative to control. An Evidence Tier column, classifying each study against the four-tier evidence-maturity framework defined in Section Review Scope and Methodological Approach (Tier I: independent replicated studies; Tier II: single field/animal-farm studies; Tier III: laboratory/in vitro evidence; Tier IV: systems-level narrative synthesis), is included. Gerasopoulos et al. [13] is an independent study and is not co-authored by the present authors.

Study (Ref.)	Design/Scale	Principal Findings	CE Relevance	Evidence Tier
Eliopoulos et al. 2024 [8]	Controlled trial; 200 weaned piglets; 50 g/kg SSF OMSW + Lathyrus clymenum husks; 40 days	↓ TBARS (p = 0.049); ↓ protein carbonyls (p = 0.012); ↑ FRSA (p = 0.005); ↑ GSH (p = 0.040); ↑ catalase (p = 0.012)	SSF-upgraded olive by-product safely improves antioxidant status in pigs	Tier II—single field/animal-farm study
Gerasopoulos et al. 2015 [13] (independent group)	Piglet feeding trial with OMW polyphenolic by-product	Improved redox status in blood and tissues	Direct valorisation of liquid olive by-product as feed	Tier II—single field/animal-farm study
Eliopoulos et al. 2022 [9]	SSF of pistachio shell (PS) mixed with olive mill stone waste (OMSW, 10–20% w/w) OR Lathyrus clymenum pericarp (LP, 20–50% w/w), inoculated with Pleurotus ostreatus, 21-day incubation	↑ crude protein (up to +33.87%, 20% LP+PS); cellulose ↑ in all mixtures (+13–17%); lignin ↓ in PS+OMSW mixtures (up to −14.22%) but ↑ in PS+LP mixtures (+11 to +38%); β-glucans markedly ↑ (up to ~480-fold in 100% PS)	Dual waste-stream valorisation via fungal bioconversion; note lignin/anti-nutritional response is substrate-specific, not uniformly reduced	Tier III—laboratory/in vitro (substrate chemistry only)
Papatsiros et al. 2023 [16]	Field trial; weaned piglets; OMW-derived polyphenolic extract	↓ post-weaning diarrhoea incidence; ↓ oxidative stress biomarkers	OMW polyphenols retain bioactivity as a liquid feed extract	Tier II—single field/animal-farm study
Papatsiros et al. 2024 [14]	Two-farm field trial; 300 weaned piglets; fumonisin challenge	↓ plasma TBARS/CARBs; ↑ total antioxidant capacity; ↑ ADG; improved FCR	CE-formulated mycotoxin detoxifier protects growth performance	Tier II—two-farm trial by the same group (not independently replicated)
Papatsiros et al. 2025 [15]	Systematic narrative review; pig diets across production cycle	Feed-sector carbon footprint reduction with quality-assured by-product diets	Synthesises food-industry by-product use at systems level	Tier IV—systems-level narrative synthesis

3.9. Limitations and Critical Considerations of CE-Aligned Feed Ingredients

The preceding sections have emphasised the nutritional and environmental promise of CE-aligned feed ingredients; a balanced assessment, however, requires equal attention to the practical limitations that currently constrain their routine use. Compositional variability is the most pervasive constraint: agro-industrial by-products, food waste streams, and SSF-upgraded substrates can vary substantially in nutrient content between batches, seasons, and suppliers, complicating precise ration formulation and creating a persistent risk of under- or over-supplementation relative to animal requirements. Storage stability is a related concern, since several CE materials—particularly OMW-derived polyphenolic extracts, insect meal, and moist food waste fractions—are prone to oxidative or microbial degradation if not adequately processed and stored, which can erode both nutritional value and safety over time. Microbial and chemical contamination risk is non-trivial for former foodstuffs and catering-derived materials in particular, requiring dedicated quality-assurance protocols that are not yet standardised across the sector. Seasonal and geographic availability further constrains several CE streams—olive by-products, grape marc, and certain fruit-processing residues are strongly seasonal—so that year-round diet formulation typically requires either storage infrastructure or a diversified portfolio of complementary by-products. Economic feasibility remains uncertain for smaller processors, since the capital costs of SSF bioreactors, drying, or pelleting infrastructure may not be recovered at low throughput volumes. Finally, farmer acceptance and regulatory uncertainty—particularly around former foodstuff legislation and the approval status of some SSF-upgraded materials—continue to slow commercial adoption even where the underlying nutritional and environmental case is strong.

These constraints do not apply equally to all categories. For conventional agro-industrial co-products (Class A; e.g., oilseed meals, DDGS, dried pulps), the main challenges are batch-to-batch nutrient variability, anti-nutritional factors and mycotoxin carry-over, which can largely be managed with existing feed-quality systems: supplier specifications, routine proximate and mycotoxin analysis, and NIR calibration. Heterogeneous food waste streams and former foodstuffs pose additional hazards—packaging residues, pathogen contamination, animal by-product content and highly variable fat and salt concentrations—so their use depends on source segregation, validated heat treatment, HACCP-based controls and traceability back to the generating site, within the limits of EU animal by-product legislation [15,30]. Biologically upgraded materials (Class B; SSF products, insect meal, SCP) additionally require control of the conversion process itself: safety of the substrate, identity of the strain or species, residual substrate and microbial metabolites, accumulation of heavy metals (in insects) and stable end-product composition, for which standardised specifications and approval routes are still being developed [32,36,37]. Table 3 therefore distinguishes advantages and limitations by category, and the corresponding One Health hazards are summarised in Section 4.3.

Table 3 summarises the principal advantages and limitations of the main CE feed ingredient categories reviewed in Section 3, to support a more critical, balanced reading of the evidence presented above.

Table 3. Principal advantages and limitations of the main CE-aligned feed ingredient categories reviewed in Section 3, provided to support a balanced, critical reading of the evidence. BSFL = black soldier fly larvae; SCP = single-cell protein; SSF = solid-state fermentation; OMSW = olive mill stone waste; OMW = olive mill wastewater.

CE Feed Category	Principal Advantages	Principal Limitations
Olive mill by-products (OMSW, OMW)	High polyphenol/antioxidant content; large regional volumes; SSF markedly improves protein and reduces anti-nutritional factors	Strongly seasonal; OMW highly variable in polyphenol concentration; SSF requires dedicated bioprocessing infrastructure [8,9,13]
Oilseed meals	Established supply chains; well-characterised nutrient profiles; direct soybean-meal substitution	Regional production volumes limited relative to global soybean meal demand; glucosinolate/anti-nutritional factors in some meals [38,39]
Cereal/distillery/fruit by-products	High volumes; established use in ruminant diets; valorises brewing/ethanol co-streams	High moisture content complicates storage/transport; variable fibre digestibility across batches [7,27,29]
Former foodstuffs/food waste	Very large volumes; cost-negative; diverts landfill-bound material	Batch-to-batch nutrient variability; contamination risk; heterogeneous national regulatory interpretation [15,30,42]
Insect meal (BSFL, mealworm)	High-quality protein; bioconverts otherwise unusable organic waste; low land footprint	Production costs remain above conventional protein sources at scale; limited approved species/inclusion levels [25,31,32]
Microalgae/SCP	No arable land requirement; can be grown on waste CO2/effluents; high protein density	High production costs; limited commercial-scale fermentation capacity; taste/palatability constraints in some species [33,35]
Seaweeds (antimethanogenic)	Very large enteric methane reductions at low inclusion	Bromoform residue and iodine-toxicity concerns; cultivation/supply chains still immature at commercial scale [34]
SSF-upgraded by-products	Converts recalcitrant lignocellulosic waste into functional feed; redox/antioxidant benefit reported in one piglet trial	Requires dedicated fungal bioprocessing infrastructure; process standardisation across substrates still developing [8,9]
Phytogenic feed additives	Antioxidant/anti-inflammatory potential; possible contribution to antimicrobial stewardship; mycotoxin-risk mitigation	Inclusion-rate standardisation and mechanism-of-action data still limited; sourcing consistency varies by supplier [14,43,44]

Table 3. Principal advantages and limitations of the main CE-aligned feed ingredient categories reviewed in Section 3, provided to support a balanced, critical reading of the evidence. BSFL = black soldier fly larvae; SCP = single-cell protein; SSF = solid-state fermentation; OMSW = olive mill stone waste; OMW = olive mill wastewater.

CE Feed Category	Principal Advantages	Principal Limitations
Olive mill by-products (OMSW, OMW)	High polyphenol/antioxidant content; large regional volumes; SSF markedly improves protein and reduces anti-nutritional factors	Strongly seasonal; OMW highly variable in polyphenol concentration; SSF requires dedicated bioprocessing infrastructure [8,9,13]
Oilseed meals	Established supply chains; well-characterised nutrient profiles; direct soybean-meal substitution	Regional production volumes limited relative to global soybean meal demand; glucosinolate/anti-nutritional factors in some meals [38,39]
Cereal/distillery/fruit by-products	High volumes; established use in ruminant diets; valorises brewing/ethanol co-streams	High moisture content complicates storage/transport; variable fibre digestibility across batches [7,27,29]
Former foodstuffs/food waste	Very large volumes; cost-negative; diverts landfill-bound material	Batch-to-batch nutrient variability; contamination risk; heterogeneous national regulatory interpretation [15,30,42]
Insect meal (BSFL, mealworm)	High-quality protein; bioconverts otherwise unusable organic waste; low land footprint	Production costs remain above conventional protein sources at scale; limited approved species/inclusion levels [25,31,32]
Microalgae/SCP	No arable land requirement; can be grown on waste CO2/effluents; high protein density	High production costs; limited commercial-scale fermentation capacity; taste/palatability constraints in some species [33,35]
Seaweeds (antimethanogenic)	Very large enteric methane reductions at low inclusion	Bromoform residue and iodine-toxicity concerns; cultivation/supply chains still immature at commercial scale [34]
SSF-upgraded by-products	Converts recalcitrant lignocellulosic waste into functional feed; redox/antioxidant benefit reported in one piglet trial	Requires dedicated fungal bioprocessing infrastructure; process standardisation across substrates still developing [8,9]
Phytogenic feed additives	Antioxidant/anti-inflammatory potential; possible contribution to antimicrobial stewardship; mycotoxin-risk mitigation	Inclusion-rate standardisation and mechanism-of-action data still limited; sourcing consistency varies by supplier [14,43,44]

4. Sustainability Assessment of CE-Based Animal Nutrition

4.1. Life Cycle Assessment: Evidence Base

Life cycle assessment (LCA) is the ISO-standardised methodology (ISO 14040/14044 [45,46]) for quantifying environmental impacts across the entire product life cycle. Table 4 synthesises the key LCA findings for CE feed ingredients reviewed in this article. The most frequently reported impact category is global warming potential (GWP), but the direction and size of the effect differ between categories. For insect meal, land use is consistently lower than for soybean meal, whereas GWP and energy use can be higher, depending mainly on the rearing substrate and on the energy used for climate control and drying [31]. For food waste converted into pig feed, most LCAs report lower impacts than for conventional feed, provided that energy-intensive drying is avoided and avoided-disposal credits are included [30,42]. For SCP and microalgae, results depend largely on the energy source and are not reported in a directly comparable form in the sources reviewed here [33,35]. Asparagopsis supplementation reduced enteric methane yield in beef steers by 45–68% across diets and by up to 80% on a low-forage diet, but whole-diet GWP was not assessed [34].

These figures should be interpreted with appropriate caution regarding the methodological assumptions underlying them. LCA outcomes for CE feed ingredients are sensitive to the allocation method used to partition environmental burdens between a primary product and its by-product (economic, mass, or system-expansion allocation can shift reported impacts substantially for the same physical process); to the system boundary chosen (farm-gate versus full life-cycle, and whether avoided-disposal credits for diverted waste streams are included); and to regional differences in baseline energy mix, transport distance, and land-use reference scenarios, which mean that a GWP reduction reported for one country or production system may not transfer directly to another. Readers should therefore treat the ranges reported in Table 4 as indicative of direction and approximate magnitude rather than as precise, universally applicable coefficients. In Table 4, values reported directly by the cited studies are distinguished from qualitative statements, and numerical ranges that could not be traced to an original LCA have been removed. Figure 2 shows only directly reported values and is intended for qualitative orientation, not for quantitative comparison.

Figure 2. Environmental evidence map for circular feed strategies. Panel (A) summarises the qualitative direction of feed-ingredient LCA findings for land use and GWP; Panel (B) shows farm- or product-level environmental outcomes reported under different functional units and system boundaries; Panel (C) shows the reduction in enteric methane yield with Asparagopsis taxiformis. Only values reported directly by the cited studies are shown; they derive from heterogeneous studies and are intended for qualitative contextualisation rather than direct quantitative comparison. Sources: Panel (A), van Huis and Oonincx (2017) [31], Pikaar et al. (2018) [35], Pereira et al. (2022) [33], Siddique et al. (2024) [42], zu Ermgassen et al. (2016) [30], van Zanten et al. (2016) [38] and FEFAC (2022) [39]; Panel (B), zu Ermgassen et al. (2016) [30] and McNicol et al. (2024) [47]; Panel (C), Roque et al. (2021) [34].

Table 4. Summary of LCA findings for principal CE-aligned feed ingredients and strategies. GWP = global warming potential (kg CO₂-eq); FCR = feed conversion ratio; DDGS = dried distillers’ grains with solubles; PLF = precision livestock farming. GWP reductions are relative to the conventional baseline ingredient replaced. The Functional Unit/System Boundary column reports the basis on which each estimate was calculated in the cited source(s); rows differ in functional unit, system boundary, and allocation method (see Section 4.1) and should therefore not be compared directly as if equivalent. “Reported” denotes a value taken directly from the cited study; “qualitative” denotes that the cited sources do not provide a directly comparable quantitative estimate.

CE Ingredient/Strategy	Conventional Baseline Replaced	GWP Reduction (Reported/Estimated; Not Necessarily Comparable)	Functional Unit/System Boundary	Other Environmental Impacts & Notes	Key LCA Refs
BSFL meal	Soybean meal/fishmeal	Qualitative: land use lower, but GWP and energy use may exceed those of soybean meal depending on rearing substrate and energy source	Per kg protein; varies between studies	Lower land use; other impacts substrate-dependent	[31]
Single-cell protein (SCP)	Soybean meal/fishmeal	Qualitative: strongly dependent on energy source; no directly comparable value in the cited sources	Varies between studies	Very low arable land requirement	[33,35]
Processed food waste (pig feed)	Conventional cereal–soy diet	Qualitative: generally lower than conventional feed; dependent on processing energy and avoided-disposal credits	Varies; inclusion of avoided-disposal credits is decisive	Avoided landfill or incineration	[42]
Microalgae (Spirulina, Chlorella)	Fishmeal/synthetic amino acids	Qualitative: dependent on cultivation system and energy source	Varies between studies	N & P recovery from effluents; no arable land	[33,35]
Seaweed (Asparagopsis taxiformis)	Conventional ruminant diet	Reported: enteric CH4 yield −45 to −68% across diets, up to −80% on a low-forage diet; whole-diet GWP not assessed	Per kg DMI (CH4 yield); enteric emissions only; no full-diet LCA/GWP reported	Marine cultivation; minimal freshwater use	[34]
Olive mill by-products (OMSW + SSF)	Synthetic antioxidants/soy protein	Qualitative only: avoids OMSW landfill/incineration	Qualitative; no formal LCA functional unit reported	Reduces oxidative waste disposal burden; Mediterranean land-use benefit	[7,8,9]
Rapeseed/sunflower meal	Imported soybean meal	Qualitative: depends mainly on land-use change accounting	Varies between studies	Land use shift from deforested areas; reduced transport emissions	[38,39]
Heat-treated food waste (swill), scenario	Wheat/maize in pig diet	Reported: land use of EU pork −20% (≈1.8 Mha) if heat-treated food waste were permitted as feed; GWP not reported	EU pork production; scenario model	Land-sparing scenario	[30]
Precision feeding (PLF-optimised)	Standard phase feeding	Reported: up to −6.8% farm-level GHG and up to −12.0% GHG/kg deadweight in modelled beef systems	Per farm and per kg deadweight; modelled beef systems	Reduced nutrient waste; improved FCR; enables CE ingredient use	[47]

Table 4. Summary of LCA findings for principal CE-aligned feed ingredients and strategies. GWP = global warming potential (kg CO₂-eq); FCR = feed conversion ratio; DDGS = dried distillers’ grains with solubles; PLF = precision livestock farming. GWP reductions are relative to the conventional baseline ingredient replaced. The Functional Unit/System Boundary column reports the basis on which each estimate was calculated in the cited source(s); rows differ in functional unit, system boundary, and allocation method (see Section 4.1) and should therefore not be compared directly as if equivalent. “Reported” denotes a value taken directly from the cited study; “qualitative” denotes that the cited sources do not provide a directly comparable quantitative estimate.

CE Ingredient/Strategy	Conventional Baseline Replaced	GWP Reduction (Reported/Estimated; Not Necessarily Comparable)	Functional Unit/System Boundary	Other Environmental Impacts & Notes	Key LCA Refs
BSFL meal	Soybean meal/fishmeal	Qualitative: land use lower, but GWP and energy use may exceed those of soybean meal depending on rearing substrate and energy source	Per kg protein; varies between studies	Lower land use; other impacts substrate-dependent	[31]
Single-cell protein (SCP)	Soybean meal/fishmeal	Qualitative: strongly dependent on energy source; no directly comparable value in the cited sources	Varies between studies	Very low arable land requirement	[33,35]
Processed food waste (pig feed)	Conventional cereal–soy diet	Qualitative: generally lower than conventional feed; dependent on processing energy and avoided-disposal credits	Varies; inclusion of avoided-disposal credits is decisive	Avoided landfill or incineration	[42]
Microalgae (Spirulina, Chlorella)	Fishmeal/synthetic amino acids	Qualitative: dependent on cultivation system and energy source	Varies between studies	N & P recovery from effluents; no arable land	[33,35]
Seaweed (Asparagopsis taxiformis)	Conventional ruminant diet	Reported: enteric CH4 yield −45 to −68% across diets, up to −80% on a low-forage diet; whole-diet GWP not assessed	Per kg DMI (CH4 yield); enteric emissions only; no full-diet LCA/GWP reported	Marine cultivation; minimal freshwater use	[34]
Olive mill by-products (OMSW + SSF)	Synthetic antioxidants/soy protein	Qualitative only: avoids OMSW landfill/incineration	Qualitative; no formal LCA functional unit reported	Reduces oxidative waste disposal burden; Mediterranean land-use benefit	[7,8,9]
Rapeseed/sunflower meal	Imported soybean meal	Qualitative: depends mainly on land-use change accounting	Varies between studies	Land use shift from deforested areas; reduced transport emissions	[38,39]
Heat-treated food waste (swill), scenario	Wheat/maize in pig diet	Reported: land use of EU pork −20% (≈1.8 Mha) if heat-treated food waste were permitted as feed; GWP not reported	EU pork production; scenario model	Land-sparing scenario	[30]
Precision feeding (PLF-optimised)	Standard phase feeding	Reported: up to −6.8% farm-level GHG and up to −12.0% GHG/kg deadweight in modelled beef systems	Per farm and per kg deadweight; modelled beef systems	Reduced nutrient waste; improved FCR; enables CE ingredient use	[47]

4.2. Land Use, Biodiversity, and Economic Sustainability

Land-use change is the most potent driver of biodiversity loss globally, and livestock feed production—particularly soybean cultivation on deforested tropical land—is the single largest contributor. LCA studies indicate that insect meal requires substantially less land per kg of protein than soybean meal; SCP produced on renewable energy uses virtually no arable land; and food waste valorisation as pig feed ‘spares’ the land that would otherwise have grown the displaced conventional ingredient [30,31,35]. Farm-level economic evidence remains limited: one EU-wide analysis examined how alternative feeding strategies relate to total factor productivity growth in pig farming [48], but cost savings attributable specifically to CE feed ingredients have rarely been quantified. For SSF-processed olive mill by-products, no economic assessment is yet available, and potential savings from avoided OMSW disposal remain to be quantified.

4.3. Animal Health, Welfare, and One Health

CE-derived phytogenic additives can be incorporated safely into pig diets while actively improving antioxidant status, reducing mycotoxin-induced oxidative stress, and supporting growth performance under commercial field conditions [14,43,44]. The One Health framework demands systematic surveillance of CE feed materials for antimicrobial resistance gene dissemination, zoonotic pathogen contamination, heavy metal accumulation, and microplastic contamination—each representing a research priority for the next decade [49]. Table 5 summarises these hazards according to their current evidence level, the CE feed streams of greatest concern, and available mitigation measures, distinguishing established risks from emerging or plausible ones rather than presenting all four hazard categories as equally well-substantiated.

Table 5. One Health hazard-evidence-mitigation framework for CE-aligned animal feed ingredients. Evidence levels distinguish hazards with established causal evidence from those that are emerging, plausible, or context-dependent; AMR dissemination through CE feed streams is presented as an emerging risk area requiring further surveillance rather than an established causal pathway. Microplastic contamination is listed as an emerging concern for which feed-specific evidence is still scarce.

Hazard	Evidence Level	High-Risk CE Streams	Mitigation
Pathogens (e.g., Salmonella, Listeria)	Established	Food waste, former foodstuffs	Heat treatment; HACCP-based processing controls [49]
Mycotoxins	Established	Cereal by-products, agro-industrial residues	Routine analytical testing; phytogenic detoxifiers [14,43]
Antimicrobial resistance (AMR) gene dissemination	Emerging/plausible	Food waste, manure-derived inputs	Microbiological surveillance; further research needed before causal claims [49]
Heavy metal accumulation	Context-dependent	Marine-derived materials, industrial by-products, insects reared on contaminated substrates	Analytical monitoring; sourcing controls [32,49]
Microplastic contamination	Emerging/plausible	Marine-derived materials (seaweed, fishmeal alternatives)	Source control; analytical method development and testing

Table 5. One Health hazard-evidence-mitigation framework for CE-aligned animal feed ingredients. Evidence levels distinguish hazards with established causal evidence from those that are emerging, plausible, or context-dependent; AMR dissemination through CE feed streams is presented as an emerging risk area requiring further surveillance rather than an established causal pathway. Microplastic contamination is listed as an emerging concern for which feed-specific evidence is still scarce.

Hazard	Evidence Level	High-Risk CE Streams	Mitigation
Pathogens (e.g., Salmonella, Listeria)	Established	Food waste, former foodstuffs	Heat treatment; HACCP-based processing controls [49]
Mycotoxins	Established	Cereal by-products, agro-industrial residues	Routine analytical testing; phytogenic detoxifiers [14,43]
Antimicrobial resistance (AMR) gene dissemination	Emerging/plausible	Food waste, manure-derived inputs	Microbiological surveillance; further research needed before causal claims [49]
Heavy metal accumulation	Context-dependent	Marine-derived materials, industrial by-products, insects reared on contaminated substrates	Analytical monitoring; sourcing controls [32,49]
Microplastic contamination	Emerging/plausible	Marine-derived materials (seaweed, fishmeal alternatives)	Source control; analytical method development and testing

Shurson and Urriola [21] argue that circular swine feeding strategies should be formally evaluated against a multi-objective scorecard spanning nutrient-use efficiency, animal and human health, and socio-economic viability simultaneously, rather than sequentially.

5. CE-Based Animal Nutrition and the Sustainable Development Goals

The 17 Sustainable Development Goals (SDGs), adopted by the United Nations in 2015 as part of the 2030 Agenda for Sustainable Development, provide the overarching normative framework within which the transition to CE-based animal nutrition must be evaluated [50]. The SDGs are explicitly designed as an integrated, indivisible system: progress in one goal generates co-benefits in others. The intersection of CE principles with animal nutrition can be linked to up to 12 of the 17 SDGs, although many of these linkages are indirect or conditional (Table 6) [51,52].

Figure 3 depicts the closed-loop flow of the CE in animal nutrition, showing how agro-industrial by-products, food waste, novel proteins (insects, SCP, algae), and PLF-enabled manure management interact to close nutrient cycles. Figure 4 presents the SDG linkage matrix, mapping four CE-AN strategy categories against 12 SDGs. Table 6 provides a detailed breakdown of mechanisms, evidence, and specific SDG target codes.

Figure 3. Circular economy in animal nutrition: from waste valorisation to nutrient loop closure. Feed resources are grouped as Class A (direct feed use), Class B (upgrading required) and Class C (non-feed valorisation). Class A and B resources enter animal nutrition, with precision livestock farming as a conditional tool where ingredient variability is high; animal-source foods are produced, and manure, digestate and compost return nutrients to cropland and feed-crop production.

Figure 4. Linkage of circular economy-based animal nutrition strategies with selected Sustainable Development Goals. Filled circles indicate direct contributions; open circles indicate indirect or conditional contributions; dashes indicate no specific linkage to the four strategy categories; SDG 17 is treated as a cross-cutting partnership linkage (Table 6). Assignments were revised to match the linkage strengths in Table 6. Linkages are indicative and should be interpreted alongside the evidence and caveats in Table 6.

5.1. SDG 1 (No Poverty) and SDG 2 (Zero Hunger)

By valorising biomass streams that would otherwise be discarded, CE feeding systems enhance the productive efficiency of livestock without competing with human food supplies. McAllister et al. (2025) [51] demonstrate that circular bioeconomy livestock systems support SDG 2 by transforming inedible biomass from non-arable lands, processing co-products, and food-loss streams into nutrient-dense ASF. For smallholder systems in low- and middle-income countries, locally available CE feed ingredients can reduce feed costs and improve livestock productivity, although evidence from these systems lies largely outside the scope of this review. The creation of CE feed ingredient value chains—through collection logistics, SSF processing, and quality assurance services—also generates new rural employment and income opportunities, contributing to SDG 1 poverty reduction [48,51].

5.2. SDG 3 (Good Health and Well-Being)

SDG 3 is supported through three CE-animal nutrition pathways. First, improved animal health through CE-derived phytogenic antioxidants and mycotoxin-detoxifying agents [43,44] may reduce the clinical burden of production disease and, potentially, therapeutic antimicrobial use, although a reduction in antimicrobial use has not been directly demonstrated for these additives. Second, CE feed additives rich in bioactive compounds (omega-3 fatty acids from algae, polyphenols from olive-derived additives, carotenoids from fruit pomace) can improve the human health credentials of meat, milk, and eggs [33]. Third, by reducing mycotoxin contamination in feed through multi-component CE-formulated detoxifiers, CE nutrition approaches may reduce mycotoxin carry-over into ASF, although carry-over into edible tissues has rarely been measured.

5.3. SDGs 6, 7, and 8 (Clean Water, Clean Energy, Decent Work)

SDG 6 is advanced by incorporating OMW and food processing effluents as CE feed ingredients or SSF substrates, diverting toxic high-strength liquid waste from water bodies and reducing livestock-driven eutrophication. Precision feeding systems further reduce nitrogen and phosphorus excretion per unit of animal product, supporting clean water targets [19]. SDG 7 is linked through SSF, a generally low-energy process compared with thermochemical treatment [36], and through biogas generation from manure and indigestible CE residuals [20]. SDG 8 is served by the new value chains and employment opportunities created in CE feed ingredient collection, insect rearing, SSF processing, and PLF service provision, although economic evidence specific to CE feed ingredients remains limited [48,53].

5.4. SDGs 9, 12, and 13 (Innovation, Responsible Consumption, Climate Action)

SDG 9 is expressed through the technological innovations enabling CE-compatible nutrition: PLF IoT ecosystems, AI-driven ration optimisation, SSF biotechnology, SCP fermentation, and digital twin modelling of CE feed scenarios [54,55,56]. SDG 12 is perhaps the most direct SDG expression of the CE principle: by substituting resource-intensive conventional feed ingredients with CE-derived by-products, the livestock sector demonstrates responsible production patterns at scale, as called for in the EU Circular Economy Action Plan [4]. SDG 13 is addressed mainly through enteric methane mitigation (reductions of 45–80% in methane yield with Asparagopsis, depending on dose and diet [34]), modelled GHG reductions of up to 6.8% at farm level and 12% per kg deadweight with PLF adoption in beef systems [47], and avoided land-use change when imported soybean meal is replaced [38]; for insect meal, a climate benefit has not been consistently demonstrated (Section 4.1) [31].

5.5. SDGs 14, 15, and 17 (Life Below Water, Life on Land, Partnerships)

SDG 14 is supported through reduced marine eutrophication—achieved via precision feeding that minimises phosphorus and nitrogen excretion—and through the sustainable cultivation of seaweeds and microalgae as CE feed ingredients that avoid overexploitation of natural fish stocks [33,34]. SDG 15 is served by the land-sparing potential of CE feed systems: replacing imported soybean meal with CE ingredients spares tropical forest and savanna from conversion, with modelled savings of about 1.8 million ha if heat-treated food waste were fed to EU pigs [30,38]. SDG 17 is embodied in the multi-stakeholder, transdisciplinary nature of CE animal nutrition research: the collaboration between veterinary science, food technology, agronomy, chemistry, data science, and policy, exemplified by initiatives such as the FAO LEAP Partnership [51], represents exactly the type of cross-sectoral partnership that SDG 17 calls for [39,51].

Table 6. Linkages between CE-based animal nutrition (CE-AN) strategies and the UN Sustainable Development Goals (SDGs). CE-AN = CE-based animal nutrition; PLF = precision livestock farming; OMW = olive mill wastewater; ASF = animal-source foods; GHG = greenhouse gas; AMR = antimicrobial resistance; NCDs = non-communicable diseases. The Linkage Strength column classifies each contribution as Direct, Indirect, or Potential/conditional, following the direct (●) versus indirect (○) distinction shown in Figure 4; classifications are indicative. These classifications were assigned by consensus among the author team based on the mechanisms and evidence cited in the corresponding row; no independent or blinded scoring procedure was used.

SDG	CE-AN Strategy	Mechanism/Contribution	Linkage Strength	Key Refs	Relevant SDG Targets
SDG 1 No Poverty	Local CE ingredient valorisation; reduced feed costs	Cheaper CE-based diets improve smallholder profitability; create rural employment	Indirect (economic pathway)	[48,51,53]	1.1, 1.2, 1.4—Reduce poverty; promote economic inclusion in rural communities
SDG 2 Zero Hunger	Upcycling inedible biomass (crop residues, by-products, food waste) into ASF	Converts waste biomass into high-quality animal protein without competing with human food crops	Conditional/direct contribution depends on feed source and land-use assumptions	[5,6,51]	2.1, 2.3, 2.4—End hunger; improve nutrition; sustainable food production
SDG 3 Good Health & Well-Being	CE phytogenic additives; mycotoxin detoxifiers; reduced antimicrobial use	CE-derived antioxidants (curcumin, silymarin, olive polyphenols) improve animal health; reduced AMR; lower mycotoxin carry-through to ASF	Indirect/conditional	[43,44,56]	3.4, 3.9, 3.d—Reduce NCDs; reduce AMR; strengthen health security
SDG 6 Clean Water & Sanitation	Valorisation of OMW and food effluents as feed; precision feeding reducing N/P excretion	Diverts high-strength liquid waste from water bodies; precision feeding can reduce N and P excretion	Indirect/conditional	[19,57]	6.3—Improve water quality; reduce pollution; halve untreated wastewater
SDG 7 Affordable & Clean Energy	SSF-upgraded CE substrates (low energy); biogas from manure/CE residuals	SSF is low-energy compared to thermochemical disposal; manure biogas generates renewable on-farm energy	Potential/conditional (depends on biogas uptake)	[20,36,58]	7.2, 7.3—Increase renewable energy share; improve energy efficiency
SDG 8 Decent Work & Economic Growth	CE feed ingredient value chains; insect rearing industry; SSF processing centres	New rural employment in CE ingredient collection, SSF, insect rearing, quality assurance	Indirect (economic pathway)	[32,48,53]	8.2, 8.3, 8.5—Higher productivity; productive employment; inclusive growth
SDG 9 Industry, Innovation & Infrastructure	PLF digital technologies; SSF biotechnology; SCP fermentation; AI-driven nutrition systems	CE-compatible PLF tools (IoT, AI, digital twins) drive agri-food innovation; new industrial pathways	Direct/indirect, depending on technology and implementation	[35,54,55,56]	9.4, 9.5—Upgrade industry for sustainability; enhance research and innovation
SDG 12 Responsible Consumption & Production	Full CE loop: by-product feed use, manure nutrient cycling, reduced synthetic inputs	Reduces material footprint of livestock; closes nutrient loops; enables responsible labelling	Direct	[4,38,39,57]	12.3, 12.5—Halve food waste; substantially reduce waste generation
SDG 13 Climate Action	Replacement of high-GWP feed ingredients; seaweed CH4 inhibition; PLF manure management	45–80% reduction in enteric CH4 yield (Asparagopsis; dose- and diet-dependent) [34]; up to 6.8% farm-level/12% product-level GHG reduction via PLF adoption in modelled beef systems [47]; climate benefit of insect meal not consistently demonstrated [31]	Conditional/direct where quantified climate benefits are demonstrated	[31,34,47]	13.1, 13.2, 13.3—Strengthen resilience; integrate climate measures
SDG 14 Life Below Water	Fishmeal replacement with CE alternatives; precision feeding reducing P/N excretion	Reduced marine eutrophication; sustainable algae/seaweed cultivation avoids overfishing	Indirect	[33,34,59]	14.1, 14.2—Reduce marine pollution; sustainably manage coastal ecosystems
SDG 15 Life on Land	Replacement of deforestation-linked soy with local CE ingredients; agroecological manure cycling	Land sparing: ≈1.8 Mha in EU pork production if heat-treated food waste were used as feed [30]; enhanced soil health	Indirect/conditional	[6,30,51]	15.1, 15.2, 15.3—Protect terrestrial ecosystems; halt deforestation
SDG 17 Partnerships for the Goals	Multidisciplinary consortia; FAO LEAP; FEFAC Circular Feed; EU Horizon partnerships	Cross-sector research	Direct	[39,51]	17.6, 17.14, 17.17—Multi-stakeholder partnerships; policy coherence

Table 6. Linkages between CE-based animal nutrition (CE-AN) strategies and the UN Sustainable Development Goals (SDGs). CE-AN = CE-based animal nutrition; PLF = precision livestock farming; OMW = olive mill wastewater; ASF = animal-source foods; GHG = greenhouse gas; AMR = antimicrobial resistance; NCDs = non-communicable diseases. The Linkage Strength column classifies each contribution as Direct, Indirect, or Potential/conditional, following the direct (●) versus indirect (○) distinction shown in Figure 4; classifications are indicative. These classifications were assigned by consensus among the author team based on the mechanisms and evidence cited in the corresponding row; no independent or blinded scoring procedure was used.

SDG	CE-AN Strategy	Mechanism/Contribution	Linkage Strength	Key Refs	Relevant SDG Targets
SDG 1 No Poverty	Local CE ingredient valorisation; reduced feed costs	Cheaper CE-based diets improve smallholder profitability; create rural employment	Indirect (economic pathway)	[48,51,53]	1.1, 1.2, 1.4—Reduce poverty; promote economic inclusion in rural communities
SDG 2 Zero Hunger	Upcycling inedible biomass (crop residues, by-products, food waste) into ASF	Converts waste biomass into high-quality animal protein without competing with human food crops	Conditional/direct contribution depends on feed source and land-use assumptions	[5,6,51]	2.1, 2.3, 2.4—End hunger; improve nutrition; sustainable food production
SDG 3 Good Health & Well-Being	CE phytogenic additives; mycotoxin detoxifiers; reduced antimicrobial use	CE-derived antioxidants (curcumin, silymarin, olive polyphenols) improve animal health; reduced AMR; lower mycotoxin carry-through to ASF	Indirect/conditional	[43,44,56]	3.4, 3.9, 3.d—Reduce NCDs; reduce AMR; strengthen health security
SDG 6 Clean Water & Sanitation	Valorisation of OMW and food effluents as feed; precision feeding reducing N/P excretion	Diverts high-strength liquid waste from water bodies; precision feeding can reduce N and P excretion	Indirect/conditional	[19,57]	6.3—Improve water quality; reduce pollution; halve untreated wastewater
SDG 7 Affordable & Clean Energy	SSF-upgraded CE substrates (low energy); biogas from manure/CE residuals	SSF is low-energy compared to thermochemical disposal; manure biogas generates renewable on-farm energy	Potential/conditional (depends on biogas uptake)	[20,36,58]	7.2, 7.3—Increase renewable energy share; improve energy efficiency
SDG 8 Decent Work & Economic Growth	CE feed ingredient value chains; insect rearing industry; SSF processing centres	New rural employment in CE ingredient collection, SSF, insect rearing, quality assurance	Indirect (economic pathway)	[32,48,53]	8.2, 8.3, 8.5—Higher productivity; productive employment; inclusive growth
SDG 9 Industry, Innovation & Infrastructure	PLF digital technologies; SSF biotechnology; SCP fermentation; AI-driven nutrition systems	CE-compatible PLF tools (IoT, AI, digital twins) drive agri-food innovation; new industrial pathways	Direct/indirect, depending on technology and implementation	[35,54,55,56]	9.4, 9.5—Upgrade industry for sustainability; enhance research and innovation
SDG 12 Responsible Consumption & Production	Full CE loop: by-product feed use, manure nutrient cycling, reduced synthetic inputs	Reduces material footprint of livestock; closes nutrient loops; enables responsible labelling	Direct	[4,38,39,57]	12.3, 12.5—Halve food waste; substantially reduce waste generation
SDG 13 Climate Action	Replacement of high-GWP feed ingredients; seaweed CH4 inhibition; PLF manure management	45–80% reduction in enteric CH4 yield (Asparagopsis; dose- and diet-dependent) [34]; up to 6.8% farm-level/12% product-level GHG reduction via PLF adoption in modelled beef systems [47]; climate benefit of insect meal not consistently demonstrated [31]	Conditional/direct where quantified climate benefits are demonstrated	[31,34,47]	13.1, 13.2, 13.3—Strengthen resilience; integrate climate measures
SDG 14 Life Below Water	Fishmeal replacement with CE alternatives; precision feeding reducing P/N excretion	Reduced marine eutrophication; sustainable algae/seaweed cultivation avoids overfishing	Indirect	[33,34,59]	14.1, 14.2—Reduce marine pollution; sustainably manage coastal ecosystems
SDG 15 Life on Land	Replacement of deforestation-linked soy with local CE ingredients; agroecological manure cycling	Land sparing: ≈1.8 Mha in EU pork production if heat-treated food waste were used as feed [30]; enhanced soil health	Indirect/conditional	[6,30,51]	15.1, 15.2, 15.3—Protect terrestrial ecosystems; halt deforestation
SDG 17 Partnerships for the Goals	Multidisciplinary consortia; FAO LEAP; FEFAC Circular Feed; EU Horizon partnerships	Cross-sector research	Direct	[39,51]	17.6, 17.14, 17.17—Multi-stakeholder partnerships; policy coherence

5.6. Potential Trade-Offs Among SDGs

The preceding subsections have emphasised synergies between CE-based animal nutrition and the SDGs, but the relationship is not uniformly positive, and a balanced assessment should acknowledge genuine trade-offs. Productivity-oriented CE strategies that increase animal-source food output to advance SDG 2 (Zero Hunger) can, if pursued without land-use safeguards, increase absolute livestock numbers and associated grazing or feed-crop area, creating tension with SDG 15 (Life on Land) and biodiversity objectives, particularly where CE ingredient availability is not the binding constraint on herd size. Similarly, the pursuit of SDG 8 (Decent Work) through new CE value chains—insect rearing, SSF processing, collection logistics—can conflict with SDG 12 (Responsible Consumption and Production) if the resulting infrastructure itself has a significant material and energy footprint that offsets the waste-diversion benefit; this underscores the importance of the LCA system-boundary caveats discussed in Section 4.1. The SDG 6 (Clean Water) benefit of diverting OMW and food-processing effluent into feed use can, in principle, compete with SDG 7 (Affordable and Clean Energy) uses of the same waste stream, such as anaerobic digestion for biogas, since a given tonne of by-product can generally only be allocated to one valorisation pathway. Recognising these trade-offs does not undermine the overall case for CE-based animal nutrition made in this review, but it does argue against treating SDG alignment as an automatic, cost-free co-benefit; policy and investment decisions should be informed by context-specific analysis of which SDG objectives are prioritised locally, and by explicit acknowledgement of the second-order effects identified here.

5.7. From Plausible Linkages to Measurable Contributions

Most linkages summarised in Table 6 and Figure 4 are inferred from mechanisms rather than measured: few of the studies reviewed report outcomes that map onto the official SDG indicators, and none evaluates several SDGs simultaneously for the same CE feeding intervention. Three steps would make SDG claims testable. First, each claim should be tied to a specific target and indicator of the global framework [50], for example, the food loss index (indicator 12.3.1) for diverted food-industry residues, the proportion of agricultural area under productive and sustainable agriculture (indicator 2.4.1) for farm-level adoption, and ambient water quality (indicator 6.3.2) for nutrient losses from precision feeding. Second, livestock-specific metrics already used in feed-efficiency and LCA research—human-edible feed conversion efficiency, land-use ratio, nitrogen surplus and GHG intensity per unit of product—could serve as intermediate indicators that connect farm data to these targets [18,38,52]. Third, because many contributions are conditional (Section 5.6), the counterfactual should be stated explicitly: the same residue contributes differently to SDGs 7, 12 and 13 depending on whether it is fed, digested or composted. Until such measurements are available, the SDG linkages presented here should be read as hypotheses for evaluation rather than as demonstrated co-benefits [51,52].

6. Precision Livestock Farming as an Enabling Technology

6.1. Conceptual Links Between PLF and CE

Precision livestock farming (PLF) refers to the systematic, continuous, and automated monitoring and management of individual animals or groups using advanced sensor technologies, data analytics, machine learning, and decision-support systems [10]. The alignment between PLF and CE can be substantial, particularly in systems where ingredient variability and continuous monitoring create a need for data-driven management: PLF reduces nutrient overfeeding (minimising nitrogen and phosphorus excretion), monitors feed intake to detect and prevent waste, enables precise deployment of variable CE ingredients, can generate data that support CE performance verification, and links livestock nutrition to agronomic nutrient management through manure monitoring [60]. Figure 5 summarises this data-to-action pathway and separates commercially validated tools from those still at research or pilot stage.

Figure 5. Precision livestock farming for circular feeding. (A) Steps from sensing to intervention and verification, separating tools already validated in commercial use from applications still at research or pilot stage for circular feed ingredients (Section 6.1). (B) Main barriers to implementation.

The maturity of these technologies differs considerably, and the distinction matters for CE applications. Technologies already validated and used commercially include electronic feeders that deliver individual or group-specific diets to growing pigs and dairy cows, automatic weighing systems, milk meters, accelerometer-based activity and rumination sensors, and NIR analysis of feeds and forages in feed mills and, increasingly, on farm [10,54,60,61]. Precision feeding of growing pigs in particular has been shown to reduce nitrogen and phosphorus excretion without impairing performance [60]. By contrast, most applications specific to circular feed ingredients—AI-based early warning of adverse responses to novel ingredients, digital twins for testing inclusion scenarios, continuous on-line sensing of slurry nutrients, and automated verification of methane-mitigating additives under commercial conditions—remain at the research or pilot stage, and their effectiveness in managing variable CE ingredients has not yet been demonstrated [55]. Three practical barriers recur. First, NIR and other spectroscopic methods require calibrations developed for each material; calibrations for unconventional by-products, food waste mixtures or SSF products are scarce, and their accuracy outside the calibration range is uncertain [61]. Second, data from feeders, sensors, laboratory analyses and farm-management software are rarely interoperable, which limits the integration needed for dynamic reformulation [55]. Third, the cost of monitoring is proportionally higher for variable ingredients, which require more frequent sampling and analysis, and it may outweigh the price advantage of the ingredient on small and medium-sized farms (Section 6.8). The examples in Section 6.2, Section 6.3, Section 6.4, Section 6.5, Section 6.6 and Section 6.7 and Table 7 should be read with this distinction in mind.

6.2. Real-Time Feed Monitoring and Precision Nutrition

Modern PLF feed monitoring systems employ weigh platforms, individual RFID-linked feeding stations, and near-infrared (NIR) spectroscopy to characterise feed intake and composition at near-real-time resolution. On-farm NIR analysis of incoming CE ingredient batches allows ration formulation to be adjusted dynamically—maintaining target amino acid and energy concentrations as ingredient composition fluctuates—without costly over-inclusion safety margins [61]. Precision nutrition tools for monogastric animals, based on dynamic nutrient requirement modelling, match dietary supply to the changing physiological requirements of individual animals across productive stages, minimising excretion of undigested nutrients [62].

6.3. IoT Ecosystems, Artificial Intelligence, and Digital Twins

Internet of Things (IoT) ecosystems on PLF farms integrate data from multiple sensor streams into centralised cloud platforms [54]. AI algorithms—including recurrent neural networks and gradient-boosting models—have been reported, mainly in research settings, to identify individual animals at risk of metabolic disorders or suboptimal feed utilisation days before clinical signs appear, enabling pre-emptive nutritional interventions. When CE feed ingredients are included in rations, AI monitoring of growth curves and health indicators could provide early warning of adverse responses and support rapid reformulation, although this has not yet been validated for CE ingredients [54]. Digital twin technology—virtual replicas of individual animals or farm systems that simulate biological processes using real-time data—enables farmers and nutritionists to evaluate CE feed inclusion scenarios in silico before committing to large-scale physical trials [55].

6.4. PLF-Enabled Monitoring of CE Feed Efficacy

PLF data streams—automatically recorded, continuous, and individual-level—provide the statistical substrate for powered, adequately replicated field studies of CE feed efficacy. Field trials of feed additives, which typically rely on periodic blood sampling and pen-level performance records [43], could be strengthened by automated, continuous performance monitoring. Automated body condition scoring (BCS) using 3D camera systems and machine-vision algorithms enables frequent, objective assessment of body reserve changes in response to dietary interventions without the labour cost and observer variability of manual scoring [63].

6.5. PLF for Manure and Nutrient Loop Closure

PLF sensors installed in slurry collection systems can measure total nitrogen, ammonium, phosphorus, and potassium continuously, enabling precision field application of manure as a substitute for synthetic fertiliser. Coupling PLF feed monitoring (quantifying nutrient intake) with PLF manure monitoring (quantifying nutrient excretion) delivers a complete nitrogen and phosphorus mass balance at the farm level—the foundation for CE accounting and regulatory compliance reporting [64]. GHG emission monitoring through PLF tools, particularly automated methane measurement systems, allows the antimethanogenic effects of feed additives to be quantified and, in principle, verified under commercial conditions [47,65].

6.6. PLF as a Joint Lever for Animal Welfare and Climate Mitigation

PLF can also help ensure that environmental optimisation does not compromise animal welfare, for instance, when by-product variability is not adequately monitored: the same sensor infrastructure—behavioural monitoring, environmental sensors and biometric tracking—can provide both welfare indicators and emission or resource-use data [54].

6.7. From Monitoring to Action: A CE-PLF Decision-Support Framework

Section 6.2, Section 6.3, Section 6.4, Section 6.5 and Section 6.6 describe the individual PLF technologies that generate the data needed to manage CE-inclusive diets safely and verify their sustainability benefits. Table 7 synthesises this material into a decision-oriented format, mapping specific CE-relevant management decisions to the PLF data sources that inform them, the indicative triggers or thresholds that would prompt action, and the realistic on-farm intervention that follows, together with the sections and references of this review from which each example is drawn. This format, adapted from a decision-support table structure recently applied to precision livestock farming in dairy sheep production [66], is intended to make the CE-PLF linkage concrete and actionable for farm advisors and nutritionists, rather than leaving it at the level of general principle.

Table 7. Illustrative decision-support framework linking CE-related animal nutrition decisions to PLF data sources, indicative triggers, and realistic on-farm interventions, with the corresponding sections and references of this review. BCS = body condition score; NIR = near-infrared spectroscopy; SSF = solid-state fermentation; OMSW = olive mill stone waste; SCP = single-cell protein; TBARS = thiobarbituric acid-reactive substances.

CE-Related Management Decision	PLF Data Source(s)	Illustrative Trigger/Threshold (Requires Farm-, Ingredient-, and System-Specific Validation)	Realistic On-Farm Intervention	Review Section/Key References
Safe inclusion-rate adjustment for a variable CE ingredient batch (e.g., SSF-OMSW, former foodstuffs)	On-farm NIR/portable spectroscopy of incoming batch; feed intake sensors	Example: batch composition deviates >10% from formulation target; threshold should be validated for the specific ingredient	Dynamic ration re-optimisation via PLF-linked feed software before next delivery	Section 6.2 and Section 7.2 [61]
Early detection of adverse response to a novel CE ingredient (insect meal, SCP, algae)	AI-based growth-curve and health-indicator monitoring; automated feed intake	Example: growth trajectory deviates for ≥2 consecutive days; operational threshold requires validation	Rapid reformulation or temporary reversion to conventional ingredient; veterinary review	Section 6.3 [54]
Verification of antioxidant/health benefit from phytogenic CE additive (curcumin, silymarin, olive polyphenols)	Periodic blood biomarker sampling combined with continuous PLF performance monitoring	TBARS or protein carbonyl levels fail to decline within expected trial window	Extend or adjust dosing protocol; cross-check additive batch quality	Section 3.6 and Section 6.4 [43,44]
Manure nutrient credit calculation for cropland application (closing the CE nutrient loop)	PLF slurry sensors (N, ammonium, P, K); PLF feed-intake nutrient balance	Continuous N/P mass balance available at farm level	Precision manure application replacing a calculated share of synthetic fertiliser	Section 6.5 [19,64]
Dosing verification of seaweed/phytogenic methane-mitigating additive	Automated enteric methane measurement systems	Example: CH4 reduction below the efficacy level established for the specific additive and production system	Re-dose or substitute additive; audit mixing and delivery equipment	Section 6.5 [65]
Welfare safeguarding when scaling a CE ingredient from pilot to commercial volume	Automated body-condition scoring (3D camera); behavioural/activity sensors	BCS or activity index falls outside a pre-defined, validated welfare reference range	Pause scale-up; revert to previous validated inclusion rate pending review	Section 6.4 and Section 6.6 [63]

Table 7. Illustrative decision-support framework linking CE-related animal nutrition decisions to PLF data sources, indicative triggers, and realistic on-farm interventions, with the corresponding sections and references of this review. BCS = body condition score; NIR = near-infrared spectroscopy; SSF = solid-state fermentation; OMSW = olive mill stone waste; SCP = single-cell protein; TBARS = thiobarbituric acid-reactive substances.

CE-Related Management Decision	PLF Data Source(s)	Illustrative Trigger/Threshold (Requires Farm-, Ingredient-, and System-Specific Validation)	Realistic On-Farm Intervention	Review Section/Key References
Safe inclusion-rate adjustment for a variable CE ingredient batch (e.g., SSF-OMSW, former foodstuffs)	On-farm NIR/portable spectroscopy of incoming batch; feed intake sensors	Example: batch composition deviates >10% from formulation target; threshold should be validated for the specific ingredient	Dynamic ration re-optimisation via PLF-linked feed software before next delivery	Section 6.2 and Section 7.2 [61]
Early detection of adverse response to a novel CE ingredient (insect meal, SCP, algae)	AI-based growth-curve and health-indicator monitoring; automated feed intake	Example: growth trajectory deviates for ≥2 consecutive days; operational threshold requires validation	Rapid reformulation or temporary reversion to conventional ingredient; veterinary review	Section 6.3 [54]
Verification of antioxidant/health benefit from phytogenic CE additive (curcumin, silymarin, olive polyphenols)	Periodic blood biomarker sampling combined with continuous PLF performance monitoring	TBARS or protein carbonyl levels fail to decline within expected trial window	Extend or adjust dosing protocol; cross-check additive batch quality	Section 3.6 and Section 6.4 [43,44]
Manure nutrient credit calculation for cropland application (closing the CE nutrient loop)	PLF slurry sensors (N, ammonium, P, K); PLF feed-intake nutrient balance	Continuous N/P mass balance available at farm level	Precision manure application replacing a calculated share of synthetic fertiliser	Section 6.5 [19,64]
Dosing verification of seaweed/phytogenic methane-mitigating additive	Automated enteric methane measurement systems	Example: CH4 reduction below the efficacy level established for the specific additive and production system	Re-dose or substitute additive; audit mixing and delivery equipment	Section 6.5 [65]
Welfare safeguarding when scaling a CE ingredient from pilot to commercial volume	Automated body-condition scoring (3D camera); behavioural/activity sensors	BCS or activity index falls outside a pre-defined, validated welfare reference range	Pause scale-up; revert to previous validated inclusion rate pending review	Section 6.4 and Section 6.6 [63]

6.8. Economic Barriers to PLF Adoption on Small and Medium-Sized Farms

The PLF-CE integration described throughout Section 6 presumes a level of sensor, connectivity, and data-analysis infrastructure that is not equally accessible across the sector. For small and medium-sized farms—which represent the majority of dairy sheep, small ruminant, and many pig operations in Mediterranean and other CE-relevant production systems—the upfront capital cost of PLF hardware (weigh platforms, RFID readers, NIR units, environmental sensors) is frequently the single largest barrier to adoption, compounded by the ongoing subscription and connectivity costs of cloud-based analytics platforms. Because the economic case for PLF-CE integration rests substantially on the value of the compositional and performance data it generates for verifying CE ingredient safety and sustainability claims (Section 6.2, Section 6.3, Section 6.4, Section 6.5, Section 6.6 and Section 6.7), smaller farms that cannot afford this infrastructure are effectively excluded from participating in the more data-intensive, higher-value CE feeding strategies, even where the underlying feed ingredients themselves are locally available and affordable. Shared-service and cooperative models—in which PLF hardware and analytical capacity are pooled across multiple smallholdings, or provided as a pay-per-use service by feed suppliers or veterinary practices—represent a promising route to decoupling PLF-enabled CE verification from individual farm capital constraints, though rigorous economic evaluation of such models specific to CE feeding contexts remains limited and is identified here as a priority for future research alongside the economic evidence gaps noted in Section 7.4.

7. Future Challenges and Research Priorities

Figure 6 provides an integrated overview of the priorities discussed throughout this section, presenting both the stage-wise decision pipeline that any candidate circular feed ingredient must pass through and the research priorities of this section by indicative time horizon (Table 8).

Figure 6. Roadmap for the development and implementation of circular feed ingredients. (A) Decision pathway from source identification to approval and uptake; ingredients that fail the safety assessment or cannot be upgraded are redirected to non-feed valorisation (Class C). (B) Research priorities by indicative time horizon, as in Table 8.

7.1. Regulatory Harmonisation and Policy Coherence

Priority regulatory actions include harmonisation of former foodstuff definitions and approval pathways across EU member states; extension of the positive insect species list to all livestock categories; establishment of a dedicated regulatory framework for SSF-upgraded agro-industrial by-products; continued scientific and regulatory evaluation of the EU restrictions governing catering waste and swill feeding to pigs, with animal-health and biosecurity safeguards as the primary considerations; and development of proportionate approval pathways for SCP and precision fermentation-derived feed proteins [25,39]. A harmonised EU policy framework for CE feed ingredients, while maintaining rigorous feed-safety requirements, could potentially facilitate market uptake and reduce regulatory fragmentation.

7.2. Compositional Variability, Quality Assurance, and Standardisation

CE-derived materials are inherently variable across batches, sources, and seasons, representing the most significant practical barrier to widespread adoption in precision-formulated diets. Addressing this requires: development of rapid, low-cost, on-farm analytical technologies (portable NIR, Raman spectroscopy, lab-on-chip biosensors) capable of characterising CE ingredient composition at delivery; construction of standardised CE feed ingredient composition databases with variability ranges and seasonal correction factors; and development of CE ingredient certification schemes that guarantee minimum nutritional quality while tolerating expected natural variability [61].

7.3. Digital Integration: CE Feed Management Within PLF Platforms

Key R&D priorities include: CE-specific modules within PLF platforms tracking by-product sourcing provenance, processing parameters, batch nutritional composition, and animal responses; algorithms for dynamic ration re-optimisation triggered by CE ingredient batch compositional changes; blockchain-enabled digital traceability systems connecting agro-industrial waste generators, feed processors, farms, and crop nutrient managers in a verified CE loop; and regulatory acceptance of digital CE documentation as legally valid evidence for feed safety compliance [56].

7.4. Scaling Up: Infrastructure, Investment, and Value Chain Development

Scaling CE feed interventions to commercial production requires reliable, geographically distributed supply chains ensuring year-round availability; investment in dedicated CE feed processing infrastructure (insect rearing facilities, SSF bioreactors, SCP fermenters, food waste heat-treatment plants); and financial instruments—EU CAP green payments, Horizon Europe funds, private venture capital—to bridge the ‘valley of death’ between proof-of-concept research and commercial deployment [53].

7.5. Consumer Acceptance and Market Communication

Consumer attitudes towards animal products from CE-based feeding systems are complex and context-dependent. Transparency about CE ingredient sourcing combined with clear communication of environmental benefits significantly increases acceptance [67]. Reframing CE materials as ‘recovered biomass resources’ or ‘upcycled feed ingredients’—and developing CE certification labels for animal products analogous to organic or welfare assurance schemes—could create market premiums that incentivise CE feeding adoption and signal CE practices to value-conscious consumers.

7.6. Climate Change Adaptation of CE Feeding Systems

Climate change will alter both the supply of CE feed materials—drought and heat reducing crop yields and agro-industrial output—and the nutritional requirements of livestock—heat stress increasing maintenance energy requirements and oxidative stress burden. CE feeding systems must be designed with adaptive flexibility: the capacity to switch between CE ingredient sources as availability changes, adjust nutrient densities and antioxidant supplementation in response to PLF sensor data, and incorporate heat-tolerant CE ingredients—such as polyphenol-rich phytogenic additives [44]—as standard components of summer feeding programmes.

7.7. One Health: AMR Surveillance, Pathogen Safety, and Contaminant Monitoring

Important One Health considerations that warrant systematic assessment in CE feed systems include: AMR gene dissemination through food waste-based feeds carrying resistant bacteria; zoonotic pathogen contamination risks in improperly treated food waste or insect-rearing substrates; heavy metal and persistent organic pollutant accumulation in marine algae and industrial by-products; and microplastic contamination of marine-derived CE ingredients. Systematic surveillance of these hazards, integration of One Health risk assessment into CE feed approval pathways, and development of validated analytical methods for novel CE-specific hazards should be considered research and policy priorities, with the level of concern determined by the specific feed stream, processing method, exposure pathway, and available evidence [49,59].

7.8. Towards an Integrated CE–PLF–One Health Research Agenda

The seven preceding research priorities are best pursued not as parallel, independent tracks but as a single integrated agenda. Regulatory harmonisation (Section 7.1) determines which CE ingredients may legally be used; compositional standardisation (Section 7.2) determines whether they can be used safely and predictably at scale; PLF digital integration (Section 7.3) provides the monitoring infrastructure that makes both possible in commercial practice; infrastructure investment (Section 7.4) determines whether adequate supply volumes can be sustained; consumer communication (Section 7.5) determines market demand; climate adaptation (Section 7.6) determines the resilience of ingredient supply under a changing climate; and One Health surveillance (Section 7.7) provides the safety backstop across all of the above. Integrated evidence of this kind, spanning ingredient chemistry, animal trials, farm-system analyses and PLF-enabled verification and evaluated against multiple objectives [21], is what regulators, investors and consumers will require before CE-based animal nutrition can move from pilot studies to commercial practice.

7.9. Research Priorities by Time Horizon

To support strategic planning by funders, policymakers, and research groups, Table 8 organises the eight research priorities discussed in Section 7.1, Section 7.2, Section 7.3, Section 7.4, Section 7.5, Section 7.6, Section 7.7 and Section 7.8 according to a short-, medium-, and long-term time horizon, reflecting the relative technical and regulatory maturity of each priority area.

Table 8. Research priorities identified in Section 7.1, Section 7.2, Section 7.3, Section 7.4, Section 7.5, Section 7.6, Section 7.7 and Section 7.8, organised by approximate time horizon to support strategic prioritisation by funders and policymakers.

Research Priority	Time Horizon	Rationale
Compositional variability & quality assurance (Section 7.2)	Short-term (1–3 yr)	Portable NIR/Raman technologies already exist; requires standardisation and database-building rather than new technology development
Digital integration of CE within PLF platforms (Section 7.3)	Short-term (1–3 yr)	Builds on existing PLF software architectures; primarily a data-schema and integration task
Consumer acceptance and market communication (Section 7.5)	Short-term (1–3 yr)	Communication and labelling interventions can be piloted and evaluated within short cycles
Regulatory harmonisation and policy coherence (Section 7.1)	Medium-term (3–7 yr)	Requires EU-level legislative processes and multi-member-state coordination
Scaling infrastructure and value-chain investment (Section 7.4)	Medium-term (3–7 yr)	Requires capital investment cycles and supply-chain maturation beyond pilot scale
One Health surveillance of CE-specific hazards (Section 7.7)	Medium-term (3–7 yr)	Requires development and validation of new analytical methods before routine surveillance is feasible
Climate change adaptation of CE feeding systems (Section 7.6)	Long-term (>10 yr)	Depends on the trajectory of climate change itself and on multi-year agronomic adaptation
Integrated CE–PLF–One Health research agenda (Section 7.8)	Long-term (>10 yr)	Depends on prior maturation of the shorter-term priorities above; represents the end-state integration goal

Table 8. Research priorities identified in Section 7.1, Section 7.2, Section 7.3, Section 7.4, Section 7.5, Section 7.6, Section 7.7 and Section 7.8, organised by approximate time horizon to support strategic prioritisation by funders and policymakers.

Research Priority	Time Horizon	Rationale
Compositional variability & quality assurance (Section 7.2)	Short-term (1–3 yr)	Portable NIR/Raman technologies already exist; requires standardisation and database-building rather than new technology development
Digital integration of CE within PLF platforms (Section 7.3)	Short-term (1–3 yr)	Builds on existing PLF software architectures; primarily a data-schema and integration task
Consumer acceptance and market communication (Section 7.5)	Short-term (1–3 yr)	Communication and labelling interventions can be piloted and evaluated within short cycles
Regulatory harmonisation and policy coherence (Section 7.1)	Medium-term (3–7 yr)	Requires EU-level legislative processes and multi-member-state coordination
Scaling infrastructure and value-chain investment (Section 7.4)	Medium-term (3–7 yr)	Requires capital investment cycles and supply-chain maturation beyond pilot scale
One Health surveillance of CE-specific hazards (Section 7.7)	Medium-term (3–7 yr)	Requires development and validation of new analytical methods before routine surveillance is feasible
Climate change adaptation of CE feeding systems (Section 7.6)	Long-term (>10 yr)	Depends on the trajectory of climate change itself and on multi-year agronomic adaptation
Integrated CE–PLF–One Health research agenda (Section 7.8)	Long-term (>10 yr)	Depends on prior maturation of the shorter-term priorities above; represents the end-state integration goal

8. Conclusions

The circular economy represents a paradigm shift for animal nutrition: from a sector characterised by linear resource consumption and waste generation to one that closes nutrient loops, valorises unavoidable by-products, and actively contributes to ecosystem regeneration. The evidence reviewed in this article indicates that CE-aligned feed ingredients—spanning agro-industrial residues, food waste, insect meal, microalgae, single-cell proteins, and fermented substrates—show considerable promise for meeting livestock nutrient requirements, although the depth and independence of the supporting evidence varies substantially by ingredient category and animal species. LCA evidence shows that environmental benefits are category-specific: lower land use is consistently reported for several novel proteins, whereas GWP benefits depend on processing energy, land-use accounting and system boundaries and have not been consistently demonstrated for insect meal (Section 4.1). The three-class distinction proposed here—materials for direct feed use, substrates requiring upgrading, and residual streams better suited to non-feed valorisation—clarifies that the circular contribution of a residue depends on the processing it requires, on the control of its variability and hazards, and on the comparability of the evidence for its environmental benefit.

The Mediterranean case study on olive mill by-products and phytogenic additives in swine illustrates how evidence can be built from ingredient chemistry to farm-level outcomes, but its findings are specific to the substrates, formulations and farms studied and require independent, multi-site replication before they can be generalised.

The analysis of SDG linkages indicates that CE-based animal nutrition can contribute to multiple sustainable development objectives, including food security (SDG 2), health-related outcomes (SDG 3), resource and water management (SDG 6), innovation (SDG 9), responsible consumption and production (SDG 12), climate action (SDG 13), ecosystem protection (SDGs 14 and 15), livelihoods (SDG 1 and SDG 8), and partnerships (SDG 17). These contributions are heterogeneous in strength and are frequently indirect, conditional, or dependent on local system characteristics, as detailed in Section 5.6 and Table 6.

For policymakers and industry stakeholders seeking an actionable summary, four take-home messages emerge from this review. First, CE-aligned feed ingredients show technical and nutritional promise across the major livestock species discussed here, with some categories (e.g., oilseed and cereal by-products, DDGS) already commercially established and others (e.g., insect meal, single-cell protein, seaweed) still constrained by regulatory, logistical, and economic barriers as well as by a narrower evidence base. Second, PLF is most useful where ingredient variability is high, but most CE-specific PLF applications have not yet been validated under commercial conditions; PLF should therefore be treated as a conditional enabler rather than a prerequisite, and its costs weighed against the value of the ingredient, particularly on small and medium-sized farms. Third, the environmental and SDG benefits of CE-based animal nutrition, while substantial, are not uniform or automatic: LCA assumptions, allocation methods, and potential SDG trade-offs (Section 4.1 and Section 5.6) must be made explicit in any policy or investment case rather than assumed. Fourth, closing the current gap between CE feed research and international independent replication—particularly for phytogenic additives and SSF-upgraded substrates—should be an explicit funding priority, both to strengthen the evidence base and to support the broader international adoption of the strategies reviewed here.