Enhancing Sheep Vitality Through Diverse Pastures and Seaweed-Based Bio-Stimulants: Effects on Performance, Health, and Product Quality

Abstract

This on-farm study explored the effects of diverse pasture systems and seaweed-based bio-stimulants (AgriSea NZ Seaweed Products, Paeroa, New Zealand) on sheep performance, metabolic health, milk composition, and carcass characteristics. A 3 × 2 factorial design was used to compare three pasture systems; ryegrass-white clover (RW), a 23-species diverse mix (DI), and functionally diverse strip swards (ST), with (SW) or without (CO) a seaweed-based bio-stimulant. Ninety pregnant ewes were stratified by live weight and allocated across six treatment groups (15 ewes per treatment). Lambing occurred on treatment paddocks. At weaning, 90 lambs (15 per treatment) were selected based on body weight and sex balance to continue through to finishing. Pasture chemical composition differed among treatments: ST had lower fibre (neutral detergent fibre, NDF; acid detergent fibre, ADF) than RW and DI, while SW increased dry matter digestibility (DMD) and metabolisable energy (ME), and reduced NDF and ADF (p < 0.05). Strip pastures improved lamb average daily gain (ADG) by 17% from lambing to weaning compared to DI, and by 14% from weaning to finishing compared to RW (p < 0.05). Seaweed-based bio-stimulant treatment enhanced lamb ADG by up to 12% and improved carcass traits, including loin and shoulder yields (p < 0.05). Ewes and lambs on seaweed-treated pastures exhibited lower serum non-esterified fatty acid (NEFA) concentrations (p < 0.05), indicating better energy balance. Milk from ST and/or SW treated ewes had elevated omega-6 fatty acids and essential amino acids, suggesting enhanced nutritional value. These findings demonstrate that combining botanical diversity with natural bio-stimulants can improve animal growth, metabolic health, and product quality, offering a promising strategy for sustainable and welfare-oriented sheep production systems.

1. Introduction

As society progressively recognises the intricate connections between land, animals, and human health, there is a growing demand for alternative approaches to pastoral systems that prioritise animal welfare, vitality, and long-term sustainability [1,2,3,4,5,6,7,8]. In this context, vitality is defined as the ability to live, grow, and develop vigorously while maintaining good health, welfare, and well-being. Pasture-based livestock systems are increasingly being reimagined as vital components of regenerative agriculture, capable of enhancing soil health, nutrient cycling, and ruminant performance while reducing dependence on synthetic fertilisers and external inputs [1,2,8]. However, despite growing global interest, existing pasture systems often fail to meet these holistic targets, highlighting the need for integrated strategies that combine botanical diversity, bioactive-rich forages, and bio-stimulant-enhanced soil amendments to promote both animal vitality and ecosystem sustainability.

Recent research indicates that grazing diverse swards improves animal welfare and environmental health [9,10,11,12,13,14,15]. More specifically, plants (terrestrial or aquatic) with particular secondary chemical bioactive compounds (e.g., tannins, terpenoids, phenols, carotenoids, and antioxidants) reduce oxidative and physiological stress in grazing ruminants, while increasing animal performance and feed conversion efficiency [11,13,16,17,18,19,20,21]. For instance, diets containing seaweed and seaweed extracts combined with specific terrestrial plant extracts reduce stress in grazing cattle and sheep, enhancing hedonic and eudemonic well-being [11,22,23]. Being able to meet individual hedonic requirements and consume foods containing medicinal and prophylactic compounds, thereby improves health. Enhanced eudemonic and hedonic well-being coupled with better health may suggest that dietary diversity will improve not only animal welfare, but also well-being (mental state and health), and thereby vitality.

Moreover, the rhizosphere of diverse swards enhances soil microbiota and nutrient absorption by plants, increasing the mineral and medicinal phytochemistry contents of herbage, hypothetically, enhancing the nutraceutical value of pastures [24,25] and thereby livestock vitality. On the other hand, synthetic-fertiliser application jeopardises soil biodiversity by suppressing the role of bacteria and fungi in amplifying the decomposition of organic matter and humus. As organic matter decreases, the physical structure of soil changes, all of which reduces soil life and health [1,26,27,28]. These changes lead to modulations in various associated soil physiological processes, affecting plant phytochemical richness and thereby nourishment and nutrient supply to herbivores. Further, it is suggested that seaweed-based bioactive treatment to pastures can remediate such degradation by changes in the microbiome components of the soil and the plants that contribute to plant growth and phytochemical diversity of plant species [29,30,31].

While previous studies have highlighted the individual benefits of either diverse plant species or seaweed supplementation, few have investigated their combined or interactive effects under controlled grazing conditions. Diverse multispecies swards, particularly those including legumes, herbs, and forbs, have been associated with improved animal performance, enhanced antioxidant status, and reduced nitrogen excretion compared to conventional ryegrass-based pastures [11,17,32]. Additionally, functionally organised pasture systems, such as adjacent monoculture strips, have been shown to enhance intake consistency and nutrient partitioning by simplifying foraging behavior and offering functional plant separation [33,34]. Despite these promising results, the role of structured sward design in small ruminant systems remains underexplored [18,35]. Similarly, although seaweed-based bio-stimulants have been shown to improve plant growth, nutrient uptake, and soil microbial activity [30,36,37], most studies have focused on agronomic or soil-related outcomes rather than their direct effects on animal vitality. This study integrates structured pasture diversity with seaweed-based bio-stimulants to explore combined effects on sheep growth, metabolism, and product quality under commercial grazing conditions. This approach links pasture composition, metabolic indicators, milk composition, and carcass traits, providing insights into how pasture design and natural soil amendments influence productivity and product quality.

We hypothesised that grazing sheep on either a diverse multi-species sward or a functionally diverse sward treated with seaweed-based bio-stimulants would enhance growth performance, metabolic health, and product quality compared to conventional systems. Therefore, this study aimed to evaluate sheep vitality, defined by growth performance and metabolic indicators, in response to grazing on either a conventional ryegrass-white clover sward, a diverse multi-species sward (23 forage species), or a functionally diverse sward composed of five adjacent monoculture strips, each with or without the application of seaweed-based bio-stimulants.

2. Materials and Methods

The present study was conducted from September 2022 to March 2023 on a 10-hectare plot of Lincoln University Johnstone Memorial Laboratory Sheep Farm (43°38′37.1″ S, 172°26′56.3″ E), Christchurch, New Zealand.

Before starting the experiment, all pasture paddocks received a basal fertiliser mixture (diammonium phosphate, sulphur, urea). Each paddock (0.75 to 1.5 ha) was then split in half: one half received seaweed-based bio-stimulant treatments, while the other half remained untreated as a control. The seaweed-based bio-stimulants were supplied by AgriSea NZ Seaweed Ltd. (Paeroa, New Zealand) and included a combination of ‘Soil Nutrition’, ‘Ocean Nutrition’, and ‘Pasture Nutrition’ products. These products are produced via a proprietary cold-brew fermentation process using locally sourced New Zealand seaweed (Ecklonia radiata), which preserves bioactive compounds such as polysaccharides, polyphenols, laminarins, mannitol, natural plant-growth regulators, trace elements, and vitamins. The bio-stimulants were applied three times during the experimental period (October 2022, December 2022, and February 2023) at rates of 5 L/ha ‘Soil Nutrition’, 5 L/ha ‘Pasture Nutrition’, and 7 L/ha ‘Ocean Nutrition’ at each application, following the manufacturer’s guidelines.

A total of 90 pregnant ewes (69.68 ± 7.51 kg; range: 64.5–74.4 kg) were stratified by live weight and randomly allocated to six treatment groups (15 ewes per treatment) in a 3 × 2 factorial design. The treatments consisted of three pasture systems; ryegrass-white clover (RW), a diverse 23-species mix (DI), and a functionally diverse strip sward (ST), with or without a seaweed bio-stimulant (SW or CO, respectively), resulting in the groups RWCO, RWSW, DICO, DISW, STCO, and STSW (Figure 1). Lambing occurred directly on the assigned treatment paddocks, resulting in a total of 122 lambs, with 74 ewes (82%) delivering single lambs and 16 ewes (18%) producing twins. No triplet births were recorded. Ewes and their lambs remained in their assigned paddocks under consistent treatment conditions until weaning.

Lambs were weaned at 80 ± 8.65 days of age with an average live weight of 34.98 ± 5.7 kg. Because lambing produced more than 15 lambs per treatment (122 lambs from 90 ewes), 15 lambs from each treatment group were randomly selected for the post-weaning to finishing phase. For twin-bearing ewes, one lamb was randomly chosen to avoid maternal bias, while all single-born lambs were included. Following this random selection, minor adjustments were made to ensure balanced sex ratios (female to male approximately 1:1; 47:43) and comparable average live weights across treatment groups. The initial lamb-weaning weight was included as a covariate in the statistical models to account for any residual differences among treatment groups. Selected lambs remained in their respective treatment paddocks (15 lambs per paddock; 90 in total) through to finishing, while all ewes and unselected lambs were removed post-weaning. Throughout the study, lambs were managed without mixing between treatment groups to preserve treatment integrity. The lamb was considered the experimental unit.

2.1. Pasture Design and Grazing Management

The pasture swards were managed under a rotational grazing system, with animals moving between paddocks based on pasture availability (pre-grazing targets ~2200–2500 kg DM/ha) and target post-grazing residuals (~1500 kg DM/ha). Muti-forage choice was a forage mix consisting of 23 species (Appendix A 

Table A2. Representative forage species used in the 23-species diverse pasture system.

Forage Type	Cultivar/Name	Functional Role
Perennial Ryegrass	Legion AR1	High-energy grass
Perennial Ryegrass	Mohaka AR1	High-energy grass
Tall Fescue	Hummer TF	Drought-tolerant grass
Meadow Fescue	Oakdon MF	Palatable, cool-season grass
Prairie Grass	Atom Prairiegrass	High-quality forage, winter-active
Cocksfoot	Savvy Cocksfoot	Drought-tolerant, persistent grass
Timothy	Timothy	Highly palatable grass
Red Clover	Relish R/C	Nitrogen fixation, protein source
White Clover	Brace W/C	Nitrogen fixation, ground cover
White Clover	Tribute W/C	Nitrogen fixation, ground cover
White Clover	Nomad W/C	Nitrogen fixation, ground cover
Crimson Clover	Crimson Clover	Quick nitrogen fix, autumn growth
Lotus	Etanin Lotus	Tannin-containing legume
Lucerne	Titan5 Lucerne	High- protein legume
Balansa Clover	Viper Balansa	Annual legume, nitrogen fixation
Strawberry Clover	Strawberry Clover	Salt-tolerant, nitrogen fixing legume
Chicory	Choice Chicory	Antioxidant-rich herb
Plantain	Ecotain Plantain	Anti-inflammatory, mineral-rich
Forage Rape	Mainstar Rape	Fast-growing brassica
Lupin	Lupins	High-protein legume
Radish	Radish	Soil conditioning, deep rooting
Vetch	Vetch	Nitrogen fixation, winter-active legume
Persian Clover	Resal Persian	Soft-leaved, autumn/winter legume

), and the functionally diverse choice was five equal-sized adjacent monoculture strips of plantain (Plantago lanceolata), ryegrass (Lolium perenne), chicory (Chicorium intybus), lucerne (Medicago sativa), and red clover (Trifolium pratense) (Appendix A 

Table A1. Representative forage species used in the functionally diverse strip-pasture system.

Forage Type	Botanical Name	Function
Plantain	Plantago lanceolata	Anti-inflammatory
Chicory	Cichorium intybus	Antioxidant-rich
Lucerne	Medicago sativa	Protein-rich legume
Red Clover	Trifolium pratense	Nitrogen fixation
Perennial Ryegrass	Lolium perenne	High energy grass

).

Pasture dry matter mass (kg DM/ha) was estimated by a rising plate meter in RW paddocks and by quadrate cuts (0.2 m²) in DI and ST paddocks. Rather than using a set stocking rate (SR), RW paddocks were allocated weekly grazing areas containing twice as much forage mass as DI and ST paddocks, based on the post-grazing residuals from the previous week. This was enacted because many of the species sown in the DI and ST paddocks can achieve much greater forage utilisation than the ryegrass paddocks [38,39,40]. Accordingly, RW paddocks were targeted to allocate 7.0 kg DM/day compared to 3.5 kg DM/day per lamb for DI and ST paddocks. Although individual feed intake per lamb was not directly measured or estimated, grazing allocations were based on recommended daily dry matter intake (DMI) guidelines for ewe-lamb pairs and post-weaning lambs [41], and residuals were managed to ensure unrestricted forage availability. Once grazing was initiated the paddocks were not irrigated, but irrigators were set up once animals moved to another fresh-pasture paddock.

2.2. Pasture Sampling and Analysis

Pasture samples were collected once per season (spring, summer, and autumn) from each treatment paddock, approximately four weeks after each application of the seaweed bio-stimulants. Pre-grazing samples were collected from >25 random locations within each treatment paddock and composited into duplicate samples per paddock. Samples were placed in paper bags and transported to the laboratory within 30–60 min of collection. Each composite sample was thoroughly mixed; one subsample was oven-dried at 60–65 °C for 48–72 h to a constant weight to determine dry matter (DM) content while the other subsample was freeze-dried, ground to pass through a 1 mm sieve and analysed for chemical composition using near-infrared spectrophotometry (NIRS). Standard NIRS calibrations were used to estimate crude protein (CP), neutral detergent fibre (NDF), acid detergent fibre (ADF), water-soluble carbohydrates (WSC), dry matter digestibility (DMD), and metabolisable energy (ME) following the Association of Official Analytical Chemists (AOAC) methods.

2.3. Liveweight Measurements and Blood Sampling for Metabolic Profiles

Live weights (LW) were measured at fortnightly intervals for both ewes and lambs from lambing until weaning, and subsequently for lambs alone from weaning to the end of the finishing phase. Average daily weight gain (ADG; g/day) was then calculated as the slope from regressing LW. Blood samples were collected from ewes at 72.24 ± 7.83 days postpartum (near weaning) and from lambs at 189.58 ± 8.51 days of age (finishing stage). Blood samples were collected in the morning by jugular venipuncture into sodium heparin and EDTA vacutainer tubes (Greiner Bio-One, Stonehouse, UK). After clotting for 2 h at room temperature, serum was then separated by centrifugation at 3000× g for 10 min. The serum was thereafter stored at −20 °C until the assay.

Serum concentrations of urea, non-esterified fatty acids (NEFA), and total antioxidant status (TAS) were measured using commercial kits (Randox Laboratories, Antrim, UK) on a semi-automated biochemical analyser (Chem 7, 340–670 nm, Erba Diagnostics Mannheim, Germany) at 37 °C. Randox calibration serum (catalog no. CAL2351) was used as daily quality control. Inter-assay coefficients of variations for NEFA and Urea were <4% and 8%, respectively. The minimum detectable levels for urea and NEFA were 0.1 mmol/L and 0.072 mmol/L, respectively, according to the manufacturer’s instructions [42].

2.4. Milk Analyses and Carcass-Traits Evaluation

Milk samples were collected from ewes at 72.24 ± 7.83 days postpartum, close to the weaning period. Ewes were hand-milked following a brief separation from their lambs. Milk samples were freeze-dried and analysed for amino-acid composition using high-performance liquid chromatography (HPLC) and for fatty-acid profiles using gas chromatography (GC), with results expressed as milligrams per gram (mg/g) of dried milk. Milk volume was not recorded, as it was not feasible to estimate yield accurately due to variation in litter size (single vs. twin lambs) and continuous suckling under ad libitum nursing. However, because fatty acid values were standardised per gram of dried sample, this approach enabled reliable comparisons across treatments without requiring total milk-yield estimation.

At the end of the finishing phase, lambs were slaughtered at a commercial abattoir operated by Alliance Group Ltd. (Timaru, South Island, New Zealand). Standard industry protocols were followed for slaughter and carcass processing. Post-chilling, individual carcass data were collected, including cold carcass weight and the yields of leg, loin, and shoulder cuts. Primal cut yields were recorded using calibrated commercial grading systems employed by Alliance, combining automated yield scanners and manual verification by trained personnel. All cut yields were expressed as percentages of cold carcass weight, and data were provided as individual carcass reports for each lamb. These values were used to evaluate treatment effects on carcass composition.

2.5. Statistical Analyses

All statistical analyses were conducted using SAS 9.4 (SAS Institute Inc., Cary, NC, USA). Data were first checked for normal distribution using the Kolmogorov–Smirnov test and q-q plots. Repeated measures linear mixed models (PROC MIXED) were used to evaluate average daily gain (ADG) in ewes (from lambing to weaning) and lambs (from lambing to weaning and from weaning to finishing). These models included pasture type, seaweed bio-stimulant treatment, their interaction, and time as fixed effects, with the individual animal as the subject of repeated (time) measurements. Body weight at baseline (initial ewe or lamb weight) was included as a covariate to account for initial variation in body condition. Least squares means were used to compare treatment groups, with significance defined at p < 0.05.

Metabolic parameters (NEFA, urea, and TAS) were analysed using general linear models (PROC GLM), with pasture type, seaweed bio-stimulant treatment, and their interaction included as fixed effects. Individual animal ID was treated as a random factor to account for variability among animals. For each metabolite, thresholds from published reference ranges (upper and lower threshold values for ewe and lamb, as shown in

Table 1. Upper and lower concentration thresholds for serum metabolites in ewes and lambs.

Metabolite	Optimum Concentration of Metabolites				Reference/s
	Ewes		Lambs
	Lower Threshold	Upper Threshold	Lower Threshold	Upper Threshold
NEFA (mmol/L)	0.1	0.6	0.1	0.5	[43]
Urea (mmol/L)	3	10	3	10	[43]
TAS (mmol/L)	0.5	1.5	0.3	1.0	[44]

NEFA non-esterified fatty acids; TAS total antioxidant status.

) were used to categorise values as low, normal, or high.

To evaluate treatment effects on milk composition, separate general linear models were constructed for each amino acid and fatty acid. Fixed effects included pasture, seaweed bio-stimulant treatment, and their interaction, while ewe ID was included as a random factor to account for repeated measures within animals. Treatment differences were identified based on least squares means with pairwise comparisons.

Carcass characteristics, including cold carcass weight and primal-cut yields, were analysed using general linear models with pasture, fertiliser, and their interaction as fixed effects. Post hoc comparisons were conducted to determine treatment effects on individual cut yields.

3. Results

The outcomes of this study demonstrate how pasture diversity and seaweed-based bio-stimulant treatments influenced ewe and lamb performance, metabolic health, milk quality, and carcass characteristics. Statistically significant effects were observed across several production and physiological parameters, particularly in relation to pasture type and seaweed bio-stimulants treatment. For clarity and ease of interpretation, the results are presented in the following order: 1. ewe performance and metabolic indicators and ewe milk composition (amino acids and fatty acids), and then 2. lamb performance and metabolic indicators and lamb-carcass characteristics.

3.1. Pasture Composition

The effects of pasture type and SW treatment on pasture nutritive value are shown in

Table 2. Pasture chemical composition across pasture and fertiliser treatments from a 3 × 2 factorial design.

	Treatments						Pasture Factor			Fertilizer Factor		p Value
Factor	DISW	DICO	RWSW	RWCO	STSW	STCO	DI	RW	ST	SW	CO	Pas	Fert	Inter	SEM
CP (%DM)	21.94	21.38	23.53	22.63	23.07	23.34	21.66	23.08	23.20	22.85	22.45	0.112	0.528	0.729	0.75
WSC (%DM)	13.89	12.35	14.22	14.13	14.63	14.10	13.12b	14.18 a	14.37 a	14.25	13.53	0.05	0.112	0.377	0.62
NDF (%DM)	39.01	42.20	38.23	40.22	25.50	30.37	40.60 b	39.22 a	27.94 a	34.24 b	37.60 a	<0.001	0.05	0.783	2.05
ADF (%DM)	23.72	25.07	22.44	22.92	19.99	21.39	24.40 a	22.53 b	20.69 c	21.95 b	23.13 a	0.001	0.05	0.867	0.75
DMD (%)	76.42	74.98	79.33	78.28	78.98	77.36	75.70 b	78.80 b	78.17 a	78.24 a	76.87 b	0.002	0.028	0.909	0.69
ME (MJ/kg DM)	11.48	11.27	11.88	11.77	11.70	11.52	11.38 b	11.83 a	11.61 a	11.69 a	11.32 b	0.001	0.025	0.818	0.08

Treatments: RW: conventional ryegrass-white clover pasture; DI: diverse 23-species pasture; ST: functionally diverse strip pasture; SW: seaweed bio-stimulant treatment; CO: seaweed bio-stimulant untreated control; CP: crude protein; WSC: water-soluble carbohydrates; NDF: neutral detergent fibre; ADF: acid detergent fibre; DMD: dry matter digestibility; ME: metabolisable energy. Pas: pasture; Fert: fertiliser; Inter: pasture × fertiliser interaction; SEM: standard error; ^a,b,c means with different superscripts within rows are significantly different (p < 0.05) from each other.

. Strip and RW pastures had lower ADF and higher WSC, DMD, and ME compared with DI pastures (p < 0.05). Seaweed bio-stimulants application increased ME and DMD and reduced NDF and ADF compared with CO (p < 0.05).

3.2. Ewe Performances

3.2.1. Average Daily Gain (ADG) of Ewes, from Lambing to Weaning

Ewe average daily gain from lambing to weaning was significantly influenced by both pasture type and fertiliser treatment (p < 0.05), while pasture × fertiliser interaction, and time were not significant (p > 0.05). Among pasture types, ewes grazing on ST pastures achieved the highest weight gain (69.68 ± 8.47 g/day), which was significantly higher than those on DI pastures (−2.05 ± 8.47 g/day; p < 0.0001) and also greater than those on RW pastures (52.77 ± 8.47 g/day;

Table 3. Ewe average daily gain (ADG) and metabolic profiles from the lambing to weaning stage, across pasture and fertiliser treatments from a 3 × 2 factorial design.

	Treatments						Pasture Factor			Fert Factor		p Value
Factor	DISW	DICO	RWSW	RWCO	STSW	STCO	DI	RW	ST	SW	CO	Pas	Fert	Inter	SEM
ADG (g/d)	−3.79	−0.31	89.1	16.5	89.3	50.1	−2.05 b	52.77 a	69.68 a	58.2 a	22.07 b	0.002	0.034	0.190	8.47
NEFA (mmol/L)	0.469	0.787	0.69	1.141	0.431	0.728	0.628 b	0.915 a	0.579 b	0.530 b	0.885 a	0.022	0.001	0.804	0.058
Urea (mmol/L)	9.429	8.272	7.67	7.284	8.316	8.563	8.851 a	7.477 b	8.439 a	8.472	8.039	0.022	0.287	0.368	0.211
TAS (mmol/L)	1.078	1.062	0.996	1.03	1.015	0.998	1.070	1.013	1.006	1.029	1.030	0.211	0.992	0.758	0.015

Treatments: RW: conventional ryegrass-white clover pasture; DI: diverse 23-species pasture; ST: functionally diverse strip pasture; SW: seaweed bio-stimulant treatment; CO: seaweed bio-stimulant untreated control; ADG: average daily gain (grams/day); NEFA: non-esterified fatty acids (mmol/L); Urea: blood urea concentration (mmol/L); TAS: total antioxidant status (mmol/L); Pas: pasture; Fert: fertiliser; Inter: interaction, SEM: standard error; ^a,b means with different superscripts within rows are significantly different (p < 0.05) from each other.

). Further, ewes receiving SW had a higher ADG (58.2 ± 8.47 g/day) compared to those under CO (22.07 ± 8.47 g/day; p = 0.034). Among the pasture × fertiliser combinations, STSW ewes achieved the highest average daily gain (89.3 ± 8.47 g/day), followed by RWSW (89.1 ± 8.47 g/day). In contrast, DISW and DICO showed the lowest performance, with negative weight gains (−3.79 ± 8.47 g/day and −0.31 ± 8.47 g/day, respectively).

3.2.2. Metabolic Performances of Ewes, from Lambing to Weaning

Ewe NEFA concentrations were significantly affected by both pasture type (p = 0.022) and fertiliser treatment (p = 0.001), while their interaction was not significant (p = 0.804; Table 3). Ewes grazing on RW exhibited the highest NEFA levels (0.915 mmol/L), followed by those on DI (0.628 mmol/L) and ST (0.579 mmol/L) pastures. Across SW application, NEFA concentrations were lower in ewes managed under the SW (0.530 mmol/L) compared to those under CO (0.885 mmol/L). Figure 2 further supports this finding, showing a higher proportion of ewes in the ‘high NEFA’ category under CO compared to SW, particularly in RWCO and DICO, while ewes grazing on STSW had the highest proportion falling within the ‘normal’ NEFA range.

Urea concentrations in ewes were significantly influenced by pasture type (p = 0.022), but not by fertiliser (p = 0.287) or their interaction (p = 0.368; Table 3). The highest urea concentrations were found in ewes grazing on DI pastures (8.85 mmol/L), followed by ST (8.44 mmol/L) and RW (7.48 mmol/L). Figure 3 supports this interpretation, showing that most ewes across all treatments maintained urea levels within the ‘normal’ range, with some increase in ‘low’ urea proportions in RW pastures, particularly under CO management.

3.2.3. Amino-Acid Composition of Ewe Milk

Milk from ewes grazing on pastures under CO had higher levels of glutamic acid (67.11 mg/g) and aspartic acid (21.87 mg/g) compared to those treated with SW (60.46 and 19.87 mg/g, respectively; p < 0.05;

Table 4. Amino acid composition (mg/g of dried milk sample) in ewe milk across six grazing on treatments from a 3 × 2 factorial design.

	Treatments						Pasture Factor			Fert Factor		p Value
AA Category	DISW	DICO	RWSW	RWCO	STSW	STCO	DI	RW	ST	SW	CO	Pas	Fert	Inter	SEM
Aspartic acid	19.68	20.65	20.17	20.41	19.75	24.54	20.16	20.29	22.15	19.87 b	21.87 a	0.21	0.05	0.15	0.54
Glutamic acid	59.07	63.56	63.03	62.20	59.28	75.58	61.32	62.62	67.43	60.46 b	67.11 a	0.26	0.04	0.09	1.70
Cysteine	2.10	2.33	2.33	2.11	2.22	2.63	2.22	2.22	2.43	2.22	2.36	0.72	0.56	0.56	0.12
Serine	13.00	13.79	13.75	13.89	14.33	15.57	13.39	13.82	14.95	13.69	14.41	0.14	0.27	0.78	0.33
Histidine	7.30	7.69	7.83	7.79	7.54	8.85	7.50	7.81	8.20	7.56	8.11	0.15	0.28	0.79	0.23
Glycine	4.94	5.15	5.28	5.26	5.64	5.78	5.05	5.27	5.71	5.29	5.40	0.11	0.66	0.94	0.13
Threonine	10.52	11.25	11.44	11.06	11.35	12.64	10.89	11.25	12.00	11.10	11.65	0.37	0.40	0.56	0.32
Arginine	9.23	9.61	9.63	9.78	9.94	11.22	9.42	9.70	10.58	9.60	10.20	0.14	0.22	0.61	0.25
Alanine	9.38	9.86	9.76	9.85	9.88	11.44	9.62	9.81	10.66	9.67	10.39	0.14	0.12	0.38	0.23
Taurine	0.47	0.50	0.50	0.59	0.41	0.42	0.49 ac	0.54 a	0.41 bc	0.46	0.50	0.04	0.32	0.61	0.02
Tyrosine	10.33	10.95	10.77	10.66	10.77	12.78	10.64	10.71	11.78	10.62	11.46	0.18	0.13	0.28	0.28
Valine	15.14	15.94	15.71	15.75	15.71	18.30	15.54	15.73	17.01	15.52	16.66	0.23	0.13	0.36	0.38
Methionine	6.41	7.08	6.85	6.97	6.71	7.69	6.75	6.91	7.20	6.66	7.25	0.59	0.11	0.62	0.18
Phenylalanine	12.33	13.21	13.99	13.11	12.91	14.94	12.77	13.55	13.93	13.08	13.75	0.38	0.33	0.23	0.35
Isoleucine	12.35	13.09	12.99	13.06	12.69	15.02	12.72	13.03	13.86	12.68	13.72	0.29	0.09	0.30	0.31
Lysine	24.04	25.46	25.01	24.06	26.87	28.09	24.75	24.53	27.48	25.31	25.87	0.23	0.72	0.79	0.76
Leucine	23.98	25.76	25.33	26.08	25.32	28.58	24.87	25.70	26.95	24.88	26.81	0.35	0.10	0.68	0.58
Proline	22.61	28.55	25.37	24.08	38.96	32.28	25.58	24.73	35.62	28.98	28.30	0.16	0.89	0.59	2.52

Treatments: RW: ryegrass-white clover; DI: diverse 23-species; ST: strip pasture; SW: seaweed bio-stimulant; CO: no seaweed bio-stimulant; amino acids are expressed as mg/g of dried milk sample; Pas: pasture; Fert: fertiliser; Inter: interaction, SEM: standard error; ^a,b,c means with different superscripts within rows are significantly different (p < 0.05) from each other.

). Taurine levels were significantly higher in milk from RW treated groups (0.54 mg/g) than in DI (0.49 mg/g), with the lowest concentrations found in ewes grazing on the ST (0.41 mg/g). While most other amino acids showed no significant treatment effects, numerical trends suggest that ewes on ST pastures tended to have higher total amino-acid concentrations, particularly for proline, valine, and lysine, indicating a potential qualitative benefit of functional pasture diversity.

3.2.4. Fatty-Acid Composition of Ewe Milk

Analysis of ewe-milk fatty-acid profiles revealed several significant effects of both pasture type and fertiliser treatment, and their interactions (

Table 5. Individual fatty-acid composition (mg/g of dried milk sample) in ewe milk across six pasture × fertiliser treatments from a 3 × 2 factorial design.

	Treatments						Pasture Factor			Fert Factor		p Value
FA (mg/g)	DISW	DICO	RWSW	RWCO	STSW	STCO	DI	RW	ST	SW	CO	Pas	Fert	Inter	SEM
C4:0	7.56	6.89	7.18	5.92	7.72	6.06	7.22	6.55	6.89	7.49 a	6.29 b	0.45	0.01	0.64	0.23
C6:0	9.85	8.66	8.30	6.42	9.45	7.77	9.25 a	7.36 b	8.61 a	9.20 a	7.62 b	0.005	0.001	0.81	0.27
C7:0	0.14	0.12	0.12	0.09	0.13	0.12	0.13	0.11	0.13	0.13 a	0.11 b	0.07	0.04	0.58	0.00
C8:0	12.43	10.91	9.62	7.35	11.04	9.77	11.7 a	8.49 b	10.4 a	11.03 a	9.34 b	0.0002	0.004	0.74	0.35
C9:0	0.27	0.23	0.22	0.17	0.25	0.24	0.25 a	0.19 b	0.25 a	0.25	0.22	0.03	0.16	0.55	0.01
C10:0	49.21	42.03	36.78	26.39	45.44	43.24	45.6 a	31.6 b	44.3 a	43.81 a	37.22 b	<0.001	0.01	0.40	1.62
C10:1	1.07 a	0.66 b	0.70 b	0.64 b	1.08 a	0.88 c	0.87 a	0.67 b	0.98 a	0.95 a	0.73 b	<0.001	<0.0001	0.02	0.04
C11:0	0.46	0.41	0.36	0.27	0.42	0.47	0.43 a	0.32 b	0.45 a	0.42	0.38	0.02	0.38	0.30	0.02
C12:0	26.53	23.38	19.77	14.67	24.77	26.25	24.9 a	17.2 b	25.5 a	23.69	21.43	0.002	0.17	0.24	0.99
C13:0	0.41	0.39	0.42	0.32	0.39	0.41	0.40	0.37	0.40	0.40	0.37	0.56	0.21	0.22	0.01
C13:0 anteiso	0.28 a	0.16 bc	0.15 b	0.13 b	0.18 b	0.24 ac	0.22 a	0.14 b	0.21 a	0.20	0.18	0.01	0.26	0.02	0.01
C13:0 iso	0.10 b	0.13 ac	0.14 a	0.11 bc	0.09 b	0.08 b	0.12 a	0.13 a	0.09 b	0.11	0.11	0.004	0.84	0.04	0.01
C14:0	54.85	50.56	51.85	40.84	61.69	54.64	52.7 ac	46.3 bc	58.2 a	56.13 a	48.68 b	0.04	0.05	0.75	1.96
C14:0 iso	0.47 b	0.50 b	0.61 a	0.43 b	0.44 b	0.51 b	0.49	0.52	0.47	0.51	0.48	0.42	0.40	0.01	0.02
C14:1 c9	0.65	0.44	0.46	0.41	0.87	0.71	0.54 b	0.43 b	0.79 a	0.66 a	0.52 b	<0.001	0.02	0.53	0.04
C15:0	4.60 bc	4.67 bc	5.47 a	4.09 b	5.37 ac	4.88 ac	4.63	4.78	5.12	5.14 a	4.55 b	0.22	0.01	0.04	0.13
C15:0 anteiso	2.74	2.65	3.13	2.23	2.94	2.70	2.69	2.68	2.82	2.94 a	2.52 b	0.68	0.01	0.06	0.08
C15:0 iso	1.04 bc	1.39 a	1.40 a	1.22 ac	1.03 bc	0.92 b	1.21 a	1.31 a	0.97 b	1.15	1.18	0.001	0.74	0.01	0.04
C16:0	118.05	104.80	115.61	91.44	143.58	119.17	111 ac	103 bc	131 a	125.7 a	105.14 b	0.05	0.03	0.85	4.95
C16:0 iso	0.97 ac	1.10 a	1.16 a	0.88 bc	1.11 a	1.11 a	1.03	1.02	1.11	1.08	1.03	0.48	0.40	0.04	0.03
C16:1 c7	1.80	2.03	2.04	1.66	1.79	1.83	1.92	1.85	1.81	1.88	1.84	0.72	0.75	0.08	0.05
C16:1 c9	2.67	2.38	2.28	1.66	3.72	2.96	2.53 ac	1.97 bc	3.34 a	2.89	2.33	0.01	0.11	0.85	0.19
C16:1 t9	1.30	1.36	1.47	1.11	0.96	1.27	1.33	1.29	1.12	1.25	1.25	0.53	1.00	0.26	0.08
C17:0	2.08	2.37	2.80	2.46	2.22	2.08	2.23 b	2.63 a	2.15 b	2.37	2.30	0.02	0.65	0.19	0.08
C17:0 anteiso	2.22	2.10	2.28	1.84	2.49	2.10	2.16	2.06	2.29	2.33 a	2.01 b	0.15	0.001	0.36	0.06
C17:0 iso	1.42 b	1.93 ac	1.93 ac	1.73 bc	1.65 bc	1.34 b	1.68 ac	1.83 a	1.4 c	1.67	1.67	0.02	0.98	0.002	0.06
C17:1	0.93	1.07	1.07	0.83	1.09	0.93	1.00	0.95	1.01	1.03	0.94	0.84	0.36	0.23	0.05
C18: t11	18.42	18.94	21.94	14.74	13.20	13.79	18.68	18.34	13.49	17.86	15.83	0.11	0.36	0.26	1.14
C18:0	44.73	58.57	63.13	60.88	34.06	24.74	51.6 a	62.0 a	29.4 b	47.31	48.06	<0.0001	0.89	0.20	3.35
C18:1 c11	1.40 bc	1.67 a	1.57 a	1.11 c	1.41 bc	1.39 bc	1.53	1.34	1.40	1.46	1.39	0.36	0.55	0.04	0.06
C18:1 c12	0.59	0.53	0.41	0.44	0.71	0.70	0.56 b	0.42 c	0.70 a	0.57	0.56	<0.001	0.85	0.86	0.03
C18:1 c13	0.60	0.54	0.50	0.43	0.64	0.66	0.57 a	0.47 b	0.65 a	0.58	0.54	<0.001	0.27	0.53	0.02
C18:1 c14/t16	2.11	2.21	2.07	2.02	1.86	1.78	2.16	2.05	1.82	2.01	2.00	0.26	0.95	0.90	0.08
C18:1 c6	1.80	1.65	1.47	1.31	1.79	1.86	1.72 a	1.39 b	1.83 a	1.69	1.61	0.01	0.51	0.66	0.06
C18:1 c9	65.46	69.66	82.36	80.78	60.45	45.94	67.5 b	81.5 a	53.2 c	69.42	65.46	<0.001	0.38	0.22	2.84
C18:1 t10	1.04	0.89	0.76	0.70	1.19	1.35	0.96 b	0.73 b	1.27 a	1.00	0.98	<0.001	0.50	0.21	0.05
C18:1 t15/c10	1.25	1.19	1.04	1.01	1.13	1.10	1.22	1.03	1.11	1.14	1.10	0.37	0.74	0.99	0.05
C18:1 t5–8	0.82	0.76	0.76	0.59	0.82	0.81	0.79	0.67	0.81	0.80	0.72	0.14	0.18	0.53	0.03
C18:1 t9	0.90	0.84	0.96	0.76	0.84	0.86	0.87	0.86	0.85	0.90	0.82	0.96	0.09	0.19	0.02
C18:2 c9 t12	1.92	1.64	1.72	1.52	1.90	1.84	1.78	1.62	1.87	1.85	1.67	0.24	0.14	0.75	0.06
C18:2 c9 t13	0.74	0.72	0.60	0.58	0.73	0.74	0.73	0.59	0.73	0.69	0.68	0.16	0.87	0.98	0.03
C18:2 c9,12	4.18	3.85	3.74	3.44	5.70	5.89	4.02 b	3.59 b	5.80 a	4.54	4.39	0.003	0.77	0.90	0.28
C18:2 t9 c12	0.68	0.57	0.57	0.57	0.67	0.60	0.62	0.57	0.64	0.64	0.58	0.41	0.19	0.58	0.02
C18:2 t9,12	0.69 ac	0.65 ac	0.88 a	0.46 bc	0.51 bc	0.54 bc	0.67	0.67	0.52	0.69 a	0.55 b	0.19	0.06	0.04	0.04
C18:3 c6,9,12	0.18	0.14	0.15	0.14	0.20	0.20	0.16 b	0.14 b	0.20 a	0.17	0.16	<.001	0.14	0.12	0.01
C18:3 c9,12,15	4.61	4.17	3.94	4.36	4.93	5.09	4.39	4.15	5.01	4.49	4.54	0.52	0.95	0.85	0.30
C19:0	4.68	3.96	5.38	2.96	3.92	4.25	4.32	4.17	4.09	4.66	3.72	0.92	0.06	0.07	0.25
C19:1	0.31	0.32	0.41	0.32	0.26	0.26	0.31 b	0.37 a	0.26 c	0.33	0.30	<0.001	0.24	0.09	0.01
C20:0	0.48	0.53	0.70	0.62	0.49	0.36	0.51 b	0.66 a	0.43 b	0.56	0.51	<0.001	0.26	0.29	0.03
C20:1 c11	0.11	0.13	0.13	0.10	0.13	0.13	0.12	0.11	0.13	0.13	0.12	0.45	0.36	0.15	0.01
C20:1 c8	0.58	0.47	0.56	0.32	0.55	0.52	0.53	0.44	0.53	0.56 a	0.44 b	0.27	0.02	0.28	0.03
C20:2 c11,14	0.05	0.06	0.04	0.06	0.08	0.09	0.05 b	0.05 b	0.08 a	0.06	0.07	0.02	0.26	0.91	0.01
C20:3 c11,14,17	0.07	0.07	0.08	0.14	0.08	0.08	0.07	0.11	0.08	0.07	0.09	0.29	0.34	0.46	0.01
C20:3 c8,11,14	0.06	0.06	0.07	0.07	0.08	0.09	0.06 b	0.07 bc	0.08 ac	0.07	0.07	0.002	0.67	0.73	0.00
C20:4 c5,8,11,14	0.27	0.27	0.31	0.24	0.38	0.32	0.27 b	0.28 b	0.35 a	0.32	0.28	0.02	0.08	0.56	0.01
C20:4 c8,11,14,17	0.12	0.13	0.10	0.10	0.16	0.11	0.13	0.10	0.13	0.12	0.11	0.10	0.30	0.32	0.01
C20:5 c5,8,11,14,17	0.33	0.34	0.34	0.35	0.34	0.30	0.33	0.34	0.32	0.34	0.33	0.64	0.72	0.60	0.01
CLA c9 t11	8.26	7.25	8.98	6.80	7.60	7.25	7.76	7.89	7.43	8.28	7.10	0.90	0.17	0.67	0.41
C22:0	0.33	0.34	0.42	0.42	0.38	0.28	0.33	0.42	0.33	0.38	0.35	0.09	0.38	0.44	0.02
C22:1 c13	0.06	0.07	0.08	0.06	0.06	0.06	0.07	0.07	0.06	0.07	0.07	0.65	0.87	0.13	0.00
C22:5 c7,10,13,16,19	0.67	0.70	0.78	0.71	0.70	0.62	0.68	0.75	0.66	0.71	0.68	0.43	0.50	0.69	0.03
C22:6_c4,7,10,13,16,19	0.29	0.30	0.33	0.33	0.34	0.28	0.30	0.33	0.31	0.32	0.30	0.75	0.64	0.71	0.02
C23:0	0.25	0.21	0.26	0.29	0.26	0.20	0.23	0.27	0.23	0.25	0.23	0.33	0.49	0.42	0.01
C24:0	0.17	0.17	0.22	0.22	0.18	0.15	0.17	0.22	0.17	0.19	0.18	0.12	0.59	0.74	0.01
C24_1_c15	0.06	0.05	0.07	0.06	0.05	0.04	0.06	0.06	0.04	0.06	0.05	0.06	0.27	0.97	0.00
C26:0	0.13	0.10	0.16	0.15	0.10	0.07	0.12 b	0.15 a	0.08 c	0.13 a	0.11 b	<0.001	0.05	0.78	0.01

Treatments: RW: ryegrass-white clover; DI: diverse 23-species; ST: strip pasture; SW: seaweed bio-stimulant; CO: no seaweed bio-stimulant; fatty acids (FA) are expressed as mg/g of dried milk sample. Pas: pasture main effect; Fert: fertiliser main effect; Inter: pasture × fertiliser interaction, SEM: standard error; ^a,b,c means with different superscripts within rows are significantly different (p < 0.05) from each other.

). Pasture type significantly influenced milk concentrations of several short-chain and medium-chain saturated fatty acids, including C6:0, C8:0, C9:0, C10:0, C11:0, C12:0, as well as C14:1c9, C16:1c9, and C18:1c12 (p < 0.05). These differences reflect the role of pasture composition in modulating de novo fatty-acid synthesis in the mammary gland. Notably, strip (ST) and diverse (DI) pastures generally enhanced concentrations of beneficial unsaturated fatty acids compared to ryegrass-based (RW) pastures, as shown by higher values for C18:1c12, C18:1c13, and C18:1 c6 fatty acids.

Fertiliser treatment also had significant effects on several fatty acids, with seaweed bio-stimulants increasing the concentrations of saturated fatty acids (C4:0, C6:0, C8:0, C10:0, C14:0, C16:0) as well as unsaturated fatty acids (C18:2 t9,12, C20:1 c8; p < 0.05). Among fatty-acid grouped categories (

Table 6. Grouped fatty-acid categories (e.g., saturated, unsaturated, chain length, and omega classes) in ewe milk (mg/g of dried sample) across six pasture × fertiliser treatments from a 3 × 2 factorial design.

	Treatments						Pasture Factor			Fertiliser Factor		p Value
FA Category (mg/g)	DISW	DICO	RWSW	RWCO	STSW	STCO	DI	RW	ST	SW	CO	Pas	Fert	Inter	SEM
MUFA	103.9	107.85	123.1	111.04	94.55	79.76	105.86 c	117.06 ac	87.15 b	107.17	99.55	0.0004	0.18	0.34	3.35
PUFA	22.80	20.56	22.22	19.40	24.03	23.73	21.68	20.81	23.88	23.01	21.23	0.24	0.24	0.77	0.75
Saturated	346.4	329.26	339.5	274.4	361.82	314.12	337.83	307.01	337.97	349.26 a	305.95 b	0.27	0.019	0.53	9.31
SC	7.56	6.89	7.18	5.92	7.72	6.06	7.22	6.55	6.89	7.49 a	6.29 b	0.45	0.009	0.64	0.23
MC	99.96	86.41	75.87	56.00	92.60	88.74	93.19 a	65.93 b	90.67 a	89.48 a	77.05 b	<0.0001	0.013	0.40	3.15
LC	363.9	362.74	399.8	341.15	378.41	321.41	363.35	370.50	349.93	380.74 a	341.78 b	0.65	0.04	0.35	9.39
VLC	1.88	1.93	2.28	2.16	2.01	1.62	1.90 ac	2.22 a	1.82 bc	2.06	1.90	0.12	0.35	0.54	0.08
Omega-3	5.97	5.56	5.46	5.87	6.37	6.36	5.77	5.66	6.37	5.93	5.93	0.68	1.00	0.89	0.33
Omega-6	4.71	4.33	4.25	3.85	6.43	6.57	4.52 b	4.05 b	6.50 a	5.13	4.92	0.002	0.70	0.90	0.30

Treatments: RW: ryegrass-white clover; DI: diverse 23-species; ST: strip pasture; SW: seaweed bio-stimulant; CO: no seaweed bio-stimulant; Fatty acid groups are expressed as mg/g of dried milk sample; MUFA: monounsaturated fatty acids; PUFA: polyunsaturated fatty acids; Omega-3 and Omega-6: polyunsaturated fatty acid families Pas: pasture; fert: fertiliser; inter: interaction, SEM: standard error; MUFA: monounsaturated fatty acids; PUFA: polyunsaturated fatty acids; FA: fatty acids; SC: short chain; MC: medium chain; LC: long chain; VLC: very long chain; ^a,b,c means with different superscripts within rows are significantly different (p < 0.05) from each other.

), significant pasture effects were observed for monounsaturated fatty acids (MUFA), medium-chain fatty acids, very long-chain fatty acids, and omega-6 fatty acids (p < 0.05). Ryegrass-clover pastures produced the highest MUFA content (117.06 mg/g), whereas ST pastures significantly increased omega-6 concentrations (6.50 mg/g). Seaweed application resulted in higher saturated (349.26 mg/g) and long-chain fatty acids concentrations (380.74 mg/g), compared to CO (305.95 and 341.78 mg/g, respectively; p < 0.05).

3.3. Lamb Performances

3.3.1. Average Daily Gain of Lambs, from Lambing to Weaning

The average daily gain of lambs from lambing to weaning was significantly influenced by both pasture type and the application of seaweed-based bio-stimulants (p = 0.008;

Table 7. Lamb average daily gain (ADG; grams/day) and metabolic profiles from the lambing to weaning stage, weaning to finishing, across pasture and fertiliser treatments from a 3 × 2 factorial design.

	Treatments						Pasture Factor			Fert Factor		p value
Factor	DISW	DICO	RWSW	RWCO	STSW	STCO	DI	RW	ST	SW	CO	Pas	Fert	Inter	SEM
ADG (lambing-Weaning; g/d)	345.1	297.5	384.9	324.7	380.8	370.1	321.3 b	354.8 a	375.4 a	370.2 a	330.8 b	0.008	0.008	0.328	6.99
ADG (Weaning-finishing; g/d)	203.4	193.9	188.4	186.5	221.9	205.6	198.6 b	187.4 b	213.7 a	204.5	195.3	0.007	0.198	0.676	3.72
NEFA (mmol/L)	0.370	0.761	0.606	0.715	0.494	0.610	0.566	0.660	0.552	0.490 b	0.695 a	0.346	0.003	0.145	0.035
Urea (mmol/L)	7.937	8.998	7.461	7.267	8.418	9.036	8.468 a	7.364 b	8.727 a	7.939	8.434	0.022	0.236	0.458	0.217
TAS (mmol/L)	0.895	0.866	0.813	0.771	0.883	0.886	0.881 a	0.792 b	0.885 a	0.864	0.841	0.015	0.425	0.800	0.014

Treatments: RW: ryegrass-white clover; DI: diverse 23-species; ST: strip pasture; SW: seaweed bio-stimulant; CO: no seaweed bio-stimulant; ADG: average daily gain (grams/day); NEFA: non-esterified fatty acids (mmol/L); Urea: blood urea concentration (mmol/L); TAS: total antioxidant status (mmol/L); Pas: pasture; fert: fertiliser; inter: pasture × fertiliser interaction, SEM: standard error; ^a,b means with different superscripts within rows are significantly different (p < 0.05) from each other.

). Time also had a highly significant effect (p < 0.0001), while no significant interaction was observed between pasture and fertiliser (p = 0.328). Lambs grazing on ST exhibited the highest ADG (375.4 ± 6.99 g/day), which was 17% greater than lambs grazing on DI (0.321 ± 6.99 g/day; p = 0.002) and numerically higher (6%) than those grazing on RW (354.8 ± 6.99 g/day). Across all pasture types, lambs receiving SW exhibited a 12% higher ADG (370.2 ± 6.99 g/day) compared to those managed under CO (330.8 ± 6.99 g/day; p= 0.008). Among the pasture × fertiliser combinations, lambs grazing on STSW achieved the highest ADG (380.8 ± 6.99 g/day), which was 28% higher than lambs grazing on DICO (297.5 ± 6.99 g/day; p < 0.001).

3.3.2. Average Daily Gain of Lambs, from Weaning to Finishing

The average daily gain of lambs from weaning to finishing was significantly influenced by pasture type (p = 0.007), while no significant effects were observed for fertiliser treatment or the pasture × fertiliser interaction (p > 0.05). Time remained highly significant (p < 0.0001), indicating consistent temporal trends in growth across treatments. Lambs grazing on ST achieved the highest ADG (213.7 ± 3.72 g/day), which was 14% higher than those on RW (187.4 ± 3.72 g/day; p = 0.002) and 8% higher than those on DI (198.6 ± 3.72 g/day; p = 0.068). Lambs on DI (198.6 ± 3.72 g/day) exhibited a 6% higher ADG compared to those on RW (187.4 ± 3.72 g/day), though the difference was not statistically significant (p = 0.218). Although fertiliser did not show a main effect, lambs receiving SW exhibited numerically higher ADG (204.5 ± 3.72 g/day) than those receiving CO (195.3 ± 3.72 g/day), aligning with patterns observed in earlier growth stages. Among pasture × fertiliser combinations, lambs grazing on STSW showed the highest growth rate (221.9 ± 3.72 g/day), which was 19% higher than lambs grazing on RWCO (186.5 ± 3.72 g/day; p = 0.008).

3.3.3. Metabolic Performances of Lambs, from Weaning to Finishing

Lamb NEFA concentrations during the weaning to finishing stage were significantly influenced by fertiliser treatment (p = 0.003), while pasture type and pasture × fertiliser interaction were not significant (p > 0.05; Table 7). Lambs managed under SW exhibited lower NEFA levels (0.490 mmol/L) compared to those under CO (0.695 mmol/L; p < 0.05). Among pasture types, lambs grazing on ST showed the lowest NEFA concentrations (0.552 mmol/L), followed by DI (0.566 mmol/L) and RW (0.660 mmol/L), though the differences were not statistically significant. These trends are reflected in Figure 4, where the proportion of lambs falling into the ‘high NEFA’ category was greatest under CO treatments, particularly RWCO and DICO, while the highest proportions of lambs in the ‘normal’ range were observed in STSW and DISW groups.

Urea concentrations were significantly affected by pasture type (p = 0.022), whereas fertiliser treatment (p = 0.236) and pasture × fertiliser interaction were not statistically significant (p > 0.05; Table 7). Lambs grazing on DI and ST pastures exhibited higher mean urea levels (8.47 and 8.73 mmol/L, respectively) than those on RW pastures (7.36 mmol/L). Despite these differences, urea levels remained within physiological norms across all treatments. As shown in Figure 5, the majority of lambs maintained urea concentrations within the ‘normal’ range, with minimal instances of elevated levels mostly observed under STCO and DICO treatments.

3.3.4. Lamb Carcass Traits

Lamb carcass traits, including cold carcass weight, visceral fat mass, and individual primal-cut yields, showed limited but notable treatment effects (

Table 8. Lamb meat cuts’ weights, collected across pasture and fertiliser treatments from a 3 × 2 factorial design.

	Treatments						Pasture Factor			Fert Factor		p Value
Factor	DISW	DICO	RWSW	RWCO	STSW	STCO	DI	RW	ST	SW	CO	Pas	Fert	Inter	SEM
Cold weight (kg)	23.38	23.65	23.90	23.71	25.23	22.41	23.52	23.81	23.82	24.17	23.26	0.93	0.20	0.16	0.36
Visceral gross (kg)	9.10	8.01	10.44	8.44	10.12	10.14	8.56	9.44	10.13	9.885	8.864	0.22	0.17	0.53	0.37
Leg yield	23.04	22.84	22.70	22.95	22.56	22.53	22.94	22.82	22.55	22.77	22.78	0.33	0.96	0.69	0.11
Loin yield	15.32 ac	15.65 ac	15.38 ac	15.66 ac	15.79 a	15.25 bc	15.48	15.52	15.52	15.50	15.52	0.96	0.88	0.02	0.07
Shoulder yield	16.72 b	17.17 bc	16.64 b	16.90 bc	17.43 ac	16.89 bc	16.95	16.77	17.16	16.93	16.99	0.18	0.74	0.05	0.08
Total yield	55.08	55.66	54.72	55.51	55.77	54.68	55.37	55.12	55.23	55.19	55.28	0.87	0.82	0.11	0.19

Treatments: RW: ryegrass-white clover; DI: diverse 23-species; ST: strip pasture; SW: seaweed bio-stimulant; CO: no seaweed bio-stimulant; Pas: pasture; fert: fertiliser; inter: pasture × fertiliser interaction, SEM: standard error; ^a,b,c means with different superscripts within rows are significantly different (p < 0.05) from each other.

). While pasture and fertiliser main effects were not statistically significant for most variables, significant effects were observed for the pasture × fertiliser interaction on loin yield (p = 0.02) and shoulder yield (p = 0.05). The highest loin yield was recorded in lambs from the STSW group (15.79%), which was significantly greater than that of STCO (15.25%) and numerically higher than all other treatment combinations. Similarly, shoulder yield was highest in STSW (17.43%) and lowest in RWSW (16.64%).

4. Discussion

This study demonstrated that pasture diversity and the use of seaweed-based bio-stimulants significantly influence key aspects of sheep production systems, including growth performance, metabolic status, milk nutritional quality, and carcass characteristics. The factorial design employed in our research enabled robust comparisons across pasture structure (RW vs. DI vs. ST) and fertilisation strategies (CO vs. SW). Overall, the ST pastures combined with SW treatments delivered the most consistent improvements in both ewe and lamb outcomes. Together with previous findings [39,45], these results strengthen the value of agroecological grazing systems that integrate plant diversity with biologically active seaweed amendments to enhance animal vitality and production efficiency. Therefore, such systems influence natural ecological processes for nutrient cycling, microbial symbiosis, and selective feeding to improve productivity while reducing synthetic inputs/fertilisers [11,35].

Pasture quality strongly influenced ewe and lamb metabolic responses and performance. The superior nutritive value (low NDF, low ADF, high ME, and DMD) of strip pastures supported greater energy supply, explaining higher ewe weight gain and lower NEFA concentrations, and greater lamb growth from lambing to weaning. Ryegrass pastures, while higher in energy and digestibility than diverse, supported lower lamb post-weaning ADG, suggesting lower forage intake compared to diverse pastures. Diverse pastures, despite lower energy density, still produce higher ADG during the lamb finishing-phase, likely due to higher voluntary intake and improved foraging opportunities from mixed species, as observed in previous studies [9,17,39]. Feed intake per lamb was not directly measured or estimated, which limits precise conclusions about feed efficiency. However, grazing-pasture allocations were designed to exceed recommended daily DMI, and residuals were managed to avoid feed restriction. Therefore, differences in growth performance likely reflect pasture quality (e.g., fibre, energy, and digestibility) and potential differences in voluntary intake, particularly for diverse pastures where lambs had greater foraging opportunities. Higher milk omega-6 fatty acids and amino-acid quality from ST and SW treatments may also have contributed to lamb growth and carcass deposition, aligning with previous evidence linking plant diversity and grass-fed systems to improved product quality [16]. Carcass yield advantages (loin and shoulder) in ST and DI pastures further support better nutrient partitioning.

4.1. Ewe Responses to Pasture Diversity and Seaweed Bio-Stimulants

Postpartum ewe performance varied particularly with pasture type. Ewes grazing on ST and RW pastures gained weight during the lambing to weaning, while those on DI pastures experienced net weight loss. This trend likely reflects the higher foraging complexity and energy cost associated with navigating a multi-species sward, which can reduce intake or impair nutrient synchronisation in the early postpartum period. Some researchers have previously reported that high-diversity swards may induce dietary conservatism or promote selective foraging behavior, especially during early lactation when energy demands are elevated [12,46]. In contrast, the functionally organised ST pasture system may have facilitated more predictable intake and nutrient absorption, enabled faster recovery, and supported lactation performance [12,17]. These results highlight that not just the number of species, but their functional arrangement plays a critical role in shaping animal performances.

Metabolic indicators strongly verified our findings on ewe performance. Ewes in the SW and DI groups exhibited significantly lower NEFA levels compared to those on CO, reflecting a more favorable energy balance and reduced reliance on body-fat reserves. Elevated NEFA concentrations in RWCO (1.14 mmol/L; normal range 0.1–0.6 mmol/L) suggest a state of metabolic stress and negative energy balance (NEB) common in early lactation and associated with higher disease risk and reproductive delays [47,48]. The reduction of NEFA concentrations under SW application compared to CO aligns with reports that bioactive compounds in AgriSea seaweed products including laminarins, fucoidans, and polyphenols enhance oxidative resilience and stabilise systemic metabolism in ruminants [22]. Further, field studies show that seaweed-based soil amendments indirectly improve animal energy status by boosting forage nutrient quality [30,31].

While NEFA was primarily reflected in the effects of fertiliser treatment, urea concentrations were significantly influenced by the pasture system. Ewes grazing on DI and ST pastures had the highest urea concentrations compared to RW. Although all values remained within physiological norms, elevated urea may suggest inefficient rumen nitrogen utilisation or an imbalance between degradable protein and fermentable energy [49]. It was also noted that heterogeneous pasture systems improve botanical diversity and provide functional metabolites, however, it can increase nitrogen excretion when grazing behavior results in selective intake of protein-rich legumes or forbs [13]. These findings suggest that forage functional arrangement and digestibility are as important as species richness in optimising metabolic performance [16,39]. Therefore, designing pasture systems that synchronise protein and energy availability, whether through pasture species composition or a functionally diverse arrangement, may therefore be key to minimising metabolic nitrogen losses while preserving the animal performance benefits of diverse swards.

Seaweed application affected some of the amino-acid profile of ewe milk, with lower concentrations of aspartic acid and glutamic acid compared with the control. These changes likely reflect shifts in rumen microbial activity and amino-acid metabolism induced by the bioactive compounds present in seaweed bio-stimulants, such as polyphenols and polysaccharides, which can influence nitrogen partitioning and microbial protein synthesis. Similar metabolic modulations have been observed when phytogenic extracts or fermented plant bio-actives have been incorporated into ruminant diets, where altered nitrogen utilisation and reduced oxidative stress pathways contributed to modified amino-acid availability and milk composition [23,50]. Strips pastures, regardless of bio-stimulants application, tended to support higher levels of key amino acids such as proline, serine, lysine, leucine, and valine, which are important for milk-protein synthesis and neonatal growth. However, taurine levels were significantly higher in RW pastures compared to ST and DI, suggesting a potential influence of conventionally managed pasture on sulphur amino-acid metabolism or hepatic conjugation processes. These results emphasised the potential of pasture management to enhance not only quantity but also the nutritional quality of milk, which could have downstream effects on lamb development and human-health applications, particularly neonatal growth [11,39].

Fatty-acid composition of ewe milk was also significantly affected by both pasture and fertiliser treatments. Strips and DI pastures enhanced beneficial unsaturated fatty acids (e.g., C14:1c9, C16:1c9, and C18:1c12) and improved amino-acid quality in milk compared with conventional ryegrass-clover pastures. This effect can be linked to secondary plant metabolites such as polyphenols, terpenoids, and condensed tannins, which are abundant in legumes (e.g., red clover, lucerne) and forbs (e.g., chicory, plantain). These compounds alter rumen microbial populations and reduce biohydrogenation of dietary polyunsaturated fatty acids, resulting in greater transfer of beneficial unsaturated fatty acids into milk and tissue lipids [51,52]. For example, chicory and plantain crops are rich in phenolic compounds and readily fermentable carbohydrates, which increase propionate production and lower rumen pH, creating an environment that favours incomplete biohydrogenation and an increased outflow of intermediates such as vaccenic and conjugated linoleic acids [38]. Thus, these findings demonstrate that diverse pasture systems with different forbs and legumes can enhance the unsaturated fatty-acid profile of ewe milk through the modulation of rumen lipid metabolism.

Milk from ewes grazing on ST and DI pastures contained higher proportions of short-chain and medium-chain fatty acids, which are synthesised de novo in the mammary gland and which are associated with enhanced energy supply and milk-fat quality. The application of SW further increased short-chain and long-chain fatty-acid concentrations (e.g.: C4:0, C8:0, C10:0, and C18:2 t9,12), suggesting improved mammary de novo fatty acid synthesis and also enhanced uptake of dietary polyunsaturated fatty acids. This may reflect the role of SW in improving soil-nutrient availability and stimulating plant-secondary metabolism, leading to pastures with higher energy and lipid precursors that support the synthesis of beneficial milk fatty acids [53]. Notably, omega-6 fatty acids were significantly higher in ST pastures (6.50 mg/g) compared with both RW (4.05 mg/g) and DI pastures (4.52 mg/g), indicating a significant shift in fatty-acid composition driven by pasture diversity. Such shifts likely arise from reduced rumen biohydrogenation of polyunsaturated lipids and enhanced outflow of beneficial intermediates, which has been associated with the presence of phenolic compounds and other secondary metabolites in botanically diverse and strip pastures [21,52]. These results suggest that both botanical diversity and biologically active soil amendments enhance not only milk-fat production but also its nutritional quality, including favorable chain-length distribution and balanced polyunsaturated fatty-acid composition.

4.2. Lamb Outcomes in Response to Pasture Systems and Bio-Stimulants

Lamb performance results, parallel to those observed in ewes, support the systemic influence of pasture diversity and the bio-stimulants supplementation strategy. From lambing to weaning and then from weaning to the finishing phase, lambs grazing on ST pastures consistently achieved the highest ADG. This consistent advantage likely reflects superior intake dynamics and nutrient delivery within the structured functional forage environment. Particularly, lambs in the STSW group outperformed all others, suggesting that early-life exposure to spatially and nutritionally diverse forages supplemented with natural seaweed bio-stimulants delivers benefits that persist through later growth stages. This aligns with the concept of metabolic programming, where early nutrition can program long-term physiological outcomes [17,54].

According to the lamb metabolic-profile testing, NEFA levels were significantly reduced in SW-treated lambs, suggesting reduced oxidative stress and improved energy status. Plasma urea concentrations were not affected by supplementation; however, pasture diversity in the ST and DI groups significantly influenced urea values, reflecting increased crude protein content or legume intake (e.g., red clover, lucerne) in those pastures. Despite elevated values, all remained within physiological ranges, and no negative associations with growth performance were observed. This suggests that lambs on diverse pastures were able to metabolise available nitrogen effectively, though synchronising protein and energy remains a critical goal in pasture design [13,16].

Carcass evaluations revealed subtle but meaningful treatment effects. While total carcass weight was not significantly different, the STSW group exhibited higher yields in economically valuable cuts, such as the loin and shoulder. This is especially relevant for farm profitability, as these cuts dominate premium market prices. The result likely reflects more balanced nutrient partitioning and improved muscle deposition, possibly shaped by consistent growth rates and forage quality. Previous work confirms that both maternal diet and early grazing experience can influence carcass composition and meat quality in offspring [39,55].

Collectively, these findings highlight the multidimensional benefits of integrating pasture diversity with biologically active organic fertilisation. These diverse systems not only enhance animal growth and metabolic health, but also improve milk-nutrient profiles and carcass characteristics, thereby increasing productivity and product value. The results provide strong support to agroecological livestock systems that prioritise biological complexity and ecological processes over synthetic inputs, paving the way for holistic and sustainable livestock production [32,39,56]. Future research should explore more deeply the mechanisms underlying these effects, including changes in rumen microbiota, nutrient-absorption dynamics, and endocrine responses. Further, long-term trials could explore the cumulative impacts of combining pasture diversity with biologically active organic fertilisation on soil-carbon sequestration, nutrient cycling, microbial diversity, and overall soil fertility. Importantly, on-farm economic assessments are needed to evaluate cost effectiveness and adoption potential under real-world conditions. With continued refinement, systems such as the STSW and DISW models hold promise as scalable, sustainable alternatives to conventional grazing models.

5. Conclusions

This study demonstrates that combining strips or diverse pastures with seaweed bio-stimulants can significantly enhance key performance indicators in sheep production. Strip pastures improved lamb ADG by 17% from lambing to weaning compared to DI, and by 14% from weaning to finishing compared to RW. Diverse multi-species swards exhibited comparable post-weaning growth to RW pastures, likely due to greater voluntary intake and foraging opportunities. The application of seaweed amendments further improved lamb growth during the pre-weaning phase by 12% overall, while also reducing NEFA in both ewes and lambs close to the weaning and finishing, respectively. Milk composition responded positively, with SW application increasing medium-chain and long-chain, and unsaturated fatty acids. These results confirm that strips and diverse pastures, particularly when combined with seaweed amendments, provided the most favorable outcomes for lamb growth, ewe-milk nutritional quality, and lamb carcass composition. These findings highlight the importance of pasture configuration and natural bio-stimulants in improving animal performance, moving beyond the conventional focus on forage species alone. Future research should assess the long-term ecological and economic viability of such systems to guide their broader adoption in sustainable livestock production.