White grape pomace bale silage in dairy goat nutrition: productive, metabolic, and economic benefits of 15% dietary inclusion over a full lactation

1 Introduction

The urgent need to transform agri-food systems is increasingly evident due to rapid population growth, climate change, depletion of natural resources, and shifting economic conditions, all of which challenge global food security (Ishangulyyev et al., 2019; Benton et al., 2022). Ensuring consistent access to safe and nutritious food remains a central objective (Manners et al., 2020), particularly as projections indicate that the world population will reach nearly 10 billion by 2050, requiring a 70 % increase in agricultural output (Godfray et al., 2010; Fogarassy et al., 2020; FAO, 2024). This growth intensifies pressure on natural resources and arable land, heightening competition between livestock production and human food needs (Benoit and Mottet, 2023). Meanwhile, the agro-industrial sector generates large quantities of fibrous residues—around 57 million tonnes annually in the EU—representing a substantial loss of valuable biomass (Kilama et al., 2023; Malenica et al., 2022). Circular-economy approaches are therefore gaining prominence, promoting reuse, recycling, and by-product valorization to enhance sustainability (Islam and Zheng, 2025). Within this framework, incorporating plant-derived by-products into ruminant diets offers environmental and economic advantages, reducing feeding costs, supporting nutrient recycling, and supplying bioactive compounds. Evidence from grape pomace and other agro-industrial by-products shows that, when diets are properly formulated, animal performance and product quality are maintained, and economic feasibility is improved (Martins Flores et al., 2021; Monllor et al., 2023; Dentinho et al., 2023; Molosse et al., 2023; Baker et al., 2024).

Grape pomace represents the principal solid residue generated during winemaking. It is estimated that processing 100 kg of fresh grapes yields approximately 25 kg of this by-product (Taladrid et al., 2019), contributing to annual volumes that may reach up to 1,200 tons in major wine-producing regions (Bordiga et al., 2015) and roughly 260.000 tons worldwide. This material is particularly rich in grape-derived bioactive constituents—including flavonoids, tocopherols, antioxidants, and polyunsaturated fatty acids (Tangolar et al., 2011; Galanakis, 2012; Ovcharova et al., 2016; Harbeoui et al., 2017)—which have been associated with improved rumen function through modulation of the gut microbiota, mitigation of methane emissions, reduced proteolysis, and enhanced post-ruminal protein supply (Patra and Saxena, 2011). In functional terms, polyphenols can suppress methanogenic archaea, reduce protozoal activity, and shift fermentation toward pathways that use hydrogen more efficiently, collectively decreasing methane formation while stabilizing the rumen microbial ecosystem (Liu et al., 2026; Zhao et al., 2026). Beyond these effects, polyphenolic compounds are widely recognized for their strong antioxidant capacity, conferring protection against oxidative stress. They also exert several health-promoting actions, including anti-inflammatory, antibacterial, and anticoagulant properties, and contribute to improved vascular function (Nudda et al., 2015; Qiu et al., 2023).

Ruminants play a key role in closing nutrient cycles within circular food systems by converting low-value biomass, including agro-industrial by-products, into high-quality animal products. Through this unique capacity, they make a substantial contribution to global food security by supplying highly digestible, biologically valuable animal protein—an especially critical function in regions with limited agricultural resources and vulnerable food systems (Mottet et al., 2017). The balanced profile of essential amino acids in ruminant-derived milk and meat further underscores their nutritional relevance in human diets (Castillo et al., 2019). At present, ruminant meat and milk account for approximately 16 % of global protein intake and 8 % of total caloric consumption (FAO, 2023). Beyond their nutritional contribution, ruminants fulfil an important ecological function due to their natural adaptation to diets rich in fibrous material and slowly degradable bioactive compounds—features characteristic of many plant-derived by-products (Makkar, 2003; Frutos et al., 2004; Patra and Saxena, 2011). Goats, in particular, are browsing animals by nature (Hofmann, 1989; Launchbaugh and Walker, 2006) and exhibit a higher tolerance to tannins than sheep or cattle. This trait is largely attributed to their salivary proteins, which display strong affinity for tannin binding (Ventura-Cordero et al., 2017; Schmitt et al., 2020). Such physiological adaptations mitigate the antinutritional effects commonly observed in other species, including reduced feed intake and impaired rumen function (Silanikove et al., 1994; Correddu et al., 2020). However, only a limited number of studies have examined the effects of grape pomace in goats within this context.

Renna et al. (2023) found that including 60 g/kg DM of dried grape pomace in dairy goat diets of early-lactation does did not affect milk yield, gross milk components, or the main milk fatty acids. Likewise, in French Alpine dairy goats, Antunović et al. (2024) tested inclusion levels of 50 y 100 g/kg DM of grape seed cake and reported no significant effects on milk yield, its gross composition, or hematological and biochemical indicators. In contrast, these authors observed that the antioxidant activity of milk was improved. Subsequent studies by Galvez-Lopez et al. (2025b) and Gálvez-López et al. (2026) evaluated the inclusion grape pomace silage in the diets of Murciano-Granadina dairy goats during early-lactation. In the first experiment, Galvez-Lopez et al. (2025b) incorporated 50, 100, and 150 g/kg DM of white grape pomace silage into experimental diets and reported that even the highest inclusion level did not elicit adverse effects on productive performance, physiological status, or oxidative indicators. In a follow-up study, Gálvez-López et al. (2026) tested 60, 120, and 180 g/kg DM of red grape pomace silage, concluding that the intermediate level (120 g/kg DM) provided the most balanced and optimal dietary performance, with no relevant differences compared with the control diet, and the need to test the long-term effects along a full lactation period to corroborate that findings.

Against this background, this study evaluated the effects of incorporating 15% DM of ensiled white grape pomace (WGP) into the diet of dairy goats throughout an entire lactation. The assessment encompassed individual milk yield, milk gross composition (including somatic cell count), body weight, hematobiochemical profile, and oxidative and inflammatory biomarkers. Economic performance was also examined. The overarching aim was to determine whether ensiled white grape pomace can be used as an alternative feed ingredient in dairy-goat diets without impairing productive performance or physiological stability, while contributing to more sustainable feeding strategies.

2 Materials and methods

2.1 Animals and facilities

The trial was conducted at the teaching and experimental dairy goat facility of Miguel Hernández University in Spain. The study covered a full lactation cycle, beginning in late February and concluding in mid-September. The herd consisted of Murciano-Granadina dairy goats managed under a free-stall housing system. Animals were kept in straw-bedded pens, with each goat allocated 1.5 m² of effective floor area and 35 cm of linear space at the feeding barrier, and had continuous access to fresh water. Feeding was scheduled twice daily (09:00 and 15:00), and milking was performed once daily, immediately before the morning feeding using a milking parlor (Casse 2 × 12 × 12, GEA, Germany), following standard regional practices. This study was approved by the Office of Responsible Research at Miguel Hernández University (code UMH.DTA.JDS.04.22).

2.2 Experimental design

From an initial group of 80 goats, at five weeks postpartum stage of lactation, and fed a conventional diet (Control diet), 40 animals were selected based on parity, body weight (35.70 ± 5.84 kg), milk yield (2.26 ± 0.80 kg/day), and SCC (2.38 ± 0.53 log_10–10³ cells/mL). The animals were assigned to the 2 treatments (20 goats/treatment), ensuring a balance regarding parity, body weight, milk yield and SCC, and also distributed into 4 homogeneous batches (2 batches/treatment x 10 goats/batch) to record diet and water ingestion at batch level, ensuring balance across the selection criteria. Following a one-week adaptation period to their new batches when the animals were fed the control diet, a pre-experimental sampling (sampling 0) was conducted, including all the variables analyzed. After the pre-experimental sampling, the treatments started: Control (conventional diet without by-products), and 15-WGP (diet including 15% DM of WGP silage). After a two-week dietary adaptation period, five more samplings were performed at animal level —every six weeks—to assess individual body weight, milk yield, and milk gross composition. Physiometabolic status at animal level was monitored at three points across the lactation—early, mid, and late—through individual blood sampling, which was subsequently used for hematological and serum biochemical profiling. Feed and water intake were monitored biweekly at the batch level in two consecutive days. Figure 1 provides an overview of the experimental timeline.

The experimental diets were formulated according to the nutritional requirements of dairy goats producing 2.5 kg of milk per day, following the Murciano-Granadina breed guidelines of Fernandez et al. (2005). Rations were designed to be isoenergetic and isonitrogenous and were offered in fixed quantities twice daily, without ad libitum access. The feeding strategy combined a commercial pelleted concentrate —composed of maize, soybean meal, wheat, rice bran, barley, beet pulp, sunflower meal, beet molasses, and mineral supplements— with a forage base consisting of alfalfa hay and cereal straw. The ingredient composition, chemical characteristics, and daily feed allowance are detailed in Table 1.

Table 1. Ingredients and chemical composition of experimental diets.

15-WGP, diet with 15% DM of WGP silage; DM, Dry matter; FM, Fresh matter; OM, Organic matter; EE, Ether extract; CP, Crude protein; NDF, Neutral detergent fibre; ADF, Acid detergent fibre; ADL, Acid detergent lignin; GAE eq., gallic acid equivalent; ME, Metabolic energy: ¹(Jarrige et al., 1981); ²UFL, forage unit for lactation (INRA system), where 1 UFL = 7.11 MJ of net energy for lactation (NEL); IVDMD, In vitro dry matter digestibility; IVOMD, In vitro organic matter digestibility; IVNDFD, In vitro neutral detergent fibre digestibility; VFA, Volatile fatty acids. ¹Molar proportion of VFA (%).

The white grape pomace silage (WGP) included in the experimental diet originated from the quality-assessment trials of this agro-industrial residue conducted by Galvez-Lopez et al. (2025a). The material had been stored in sealed commercial plastic bales for 180 days (approximate weight: 300 kg; pH 3.9; DM 43%). Its average nutritional profile —43% dry matter, 6.3% ether extract, 12.2% crude protein, 40.6% neutral detergent fiber, and 33.7% acid detergent fiber— characterizes WGP as a fibrous feed ingredient providing a moderate energy contribution within ruminant diets.

2.3 Variables analyzed

Chemical and nutritional characterization of the experimental diets (Table 1) was determined using standard analytical procedures (AOAC, 1999). Samples were pre-dried at 60 °C for 48 h, ground in the laboratory to a particle size of <1 mm, and analyzed for: dry matter (DM, g/kg; method 930.15), organic matter (OM, g/kg DM; method 942.05), ether extract (EE, g/kg DM; method 920.39), crude protein (CP, g/kg DM; method 984.13), and total sugars (g/kg DM; method 974.06). Fiber fractions —neutral detergent fiber (NDF), acid detergent fiber (ADF), and acid detergent lignin (ADL)— were determined according to the methods described by Van Soest et al. (1991). Starch content was measured using the polarimetric technique of Ewers (ISO, 1997). Total polyphenol content (PT, expressed as g gallic acid equivalents/kg DM) was analyzed using the Folin-Ciocalteu method following the methodology of Kim et al. (2003). Mineral content in the diets was determined after acid digestion of the samples, using an Inductively Coupled Plasma Mass Spectrometer (ICP-MS; Agilent 7700x, Santa Clara, CA, USA) following the protocol of González-Arrojo et al. (2016).

Apparent in vitro dry matter digestibility (IVDMD, g/kg DM) was assessed using the method of Menke and Steingass (1988), incorporating slight adjustments recommended by Yáñez-Ruiz et al. (2016). Neutral detergent fiber degradability (IVDNDF, g/kg DM) was calculated from the digested residue according to Van Soest et al. (1991). The proportion of volatile fatty acids (VFAs, g/kg DM) —acetate, propionate, butyrate, isobutyrate— was quantified using High-Performance Liquid Chromatography (HPLC; Agilent 1200, Santa Clara, CA, USA) equipped with a Supelcogel C610H column (30 cm × 7.8 mm ID; Saint Louis, MO, USA), following the analytical procedure described by Feng-Xia et al. (2013).

At each sampling point, goats were individually weighed using a high-precision scale integrated into the handling chute (Accurex RX Fox, Gram Group, Barcelona, Spain; ± 100 g accuracy) to monitor changes in body weight (kg) throughout the study. Daily milk yield (kg/day) was recorded for each animal using a Lactocorder^® device (Lactocorder, Balgach, Switzerland). Milk macrocomposition —including fat, crude protein, lactose, useful dry matter (UDM), non-fat dry matter (NFDM), and milk urea— was analyzed using mid-infrared spectroscopy (CombiFossTM 7 DC, Foss, Hillerød, Denmark). Somatic cell count (SCC, 10³ cells/mL) was determined via flow cytometry (CombiFossTM 7 DC, Foss, Hillerød, Denmark). Fat-Corrected Milk (FCM 3.5%) was calculated following Gravert (1987): FCM (3.5%) = 0.433 × milk yield (kg/day) + 16.218 × fat yield (kg/day). Fat and Protein-Corrected Milk (FPCM) was estimated using CVB (2008): FPCM = milk yield (kg/day) × (0.337 + 0.116 × Fat (%) + 0.06 × Protein (%)).

Feed intake (FMI and DMI) and water intake (WI) were monitored at the batch level every two weeks, over two consecutive days, yielding three measurement replicates for each sampling point. Feed intake was calculated as the difference between the quantities of feed offered and refused, expressed on both a fresh matter (FM) and dry matter (DM) basis. To determine DM content, representative samples of offered and refused feed were dried at 105 °C for 48 hours. Water intake was measured by difference using individual water meters (Fenix Hidroconta -SV-RTK E4^® Flow Systems-, Murcia, Spain) installed in each pen.

Fasting blood samples were obtained at three predefined stages of the trial —early, mid, and late lactation (Figure 1)— with collections performed at 08:00 h. Samples were collected from the jugular vein using an Eclipse™ needle (BD Vacutainer, Franklin Lakes, NJ, USA) and stored in three test tubes (BD Vacutainer, Franklin Lakes, NJ, USA), according to the intended analysis: EDTA K2 (4 mL) for hematological analysis, Serum CAT (10 mL) with clot activator for serum biochemical profile assessment, and LH Lithium Heparin (10 mL) for oxidative status evaluation. Hematology was determined using an Element HT5 analyzer (SCIL VET, Tudela, Spain) calibrated for a female goat: white blood cells (WBC), lymphocites (LYM), monocytes (MON), neutrofiles (NEU), red blood cells (RBC), hemoglobine (HGB), hematocrit (HCT) were analyzed, and the ratios neutrofiles/limphocites (NLR), and monocites/lymphocites (MLR) were calculated. Serum biochemical profile was analyzed using the rapid diagnostic disk “Diagnostic II” for Element RC3X (SCIL VET, Tudela, Spain); the analytes measured comprised: alkaline phosphatase (ALP), gamma-glutamyl transferase (GGT), amylase (AMY), lipase (LYPA), blood urea nitrogen (BUN) creatinine (CREA), urea, total protein (TP), globulin (GLOB), albumin (ALB), glucose (GLU), cholesterol (CHOL), Ca, P. Oxidative status was evaluated using total antioxidant capacity assay —ABTS (Leite et al., 2011) and FRAP (Oyaizu, 1986)—. Specific antioxidant capacity was determined by measuring superoxide dismutase (SOD) activity assay (DetectX^® Superoxide Dismutase Activity Kit, Arbor Assays, Ann Arbor, MI, USA). Serum amyloid-A (SAA), an acute-phase protein, was quantified as an inflammatory biomarker using a species-specific commercial ELISA kit (GOAT-SAA, FineTest™).

The cost of WGP silage, including its processing and ensiling, is substantially lower (120.9 €/t DM; Galvez-Lopez et al., 2025a than that of conventional forages commonly used in ruminant diets, such as alfalfa hay (240 €/t DM, according to price records from the Lonja de Cereales de Albacete, 2026). Considering the cost advantage introduced by incorporating WGP silage into the diet, along with the observed milk production performance (UDM) and the market price of fat- and protein-corrected milk (€/FPCM), the economic performance of the feeding strategy was assessed.

2.4 Statistical analysis

The SCC values were transformed into base-ten logarithms for statistical analysis. The statistical evaluation of variables measured at the individual level was conducted using a mixed linear model (PROC GLIMMIX, SAS v9.4, 2024), considering the effect of the covariate (data at the pre-experimental sampling), diet, sampling, the interaction (diet × sampling), and batch nested within diet, according to the following equation:

Y = µ + Di + Sj + Di × Sj + covY0 + Bk(Di) + Ak + e

where Y is the dependent variable, µ is the intercept, D_i represents the fixed effect of diet (i = Control and 15-WGP), S_j is the fixed effect of sampling (j = 1, 2, 3, 4, 5), D_i × S_j represents the interaction between diet and sampling (10 levels), covY₀ accounts for the effect of Y in the pre-experimental sampling, B_k(Di) is the batch nested within diet.

For variables analyzed on blood/plasma/serum samples, the model included the fixed effects of diet (D_i, i = 2 levels), sampling (S_j, 3 levels, j = 1, 3, 5), their interaction (D_i × S_j, 6 levels), covY₀ accounts for the effect of Y in the pre-experimental sampling, and batch(diet).

For both scenarios, the animal was considered a random effect (A_k), and e represents the residual error. A compound symmetry covariance structure was employed to account for the correlation of repeated measures, based on the lowest AIC and BIC values.

For variables measured at the batch level (WI, DMI, FMI), a general linear model (PROC GLM, SAS v9.4, 2024) was used, considering the effect of diet, sampling, and the interaction, according to the following equation:

Y = μ + Di + Tk + (Di × Tk) + e

where Y is the dependent variable, μ is the intercept, D_i represents the fixed effect of diet (i = Control and15-WGP), T_k is the fixed effect of sampling (k = 0, 1, 2, 3, 4, 5), D_i × T_k represents the interaction between both effects (12 levels), and e is the residual error.

Least squares means were calculated to interpret differences between levels of the fixed effects. The null hypothesis was rejected at P < 0.05, indicating statistically significant differences between levels.

Model assumptions were evaluated through residual diagnostics (normality and homogeneity of variance) prior to analysis.

3 Results

3.1 Feed intake, body weight, milk yield and quality

The inclusion of WGP silage did not lead to significant differences in most variables related to productive performance (Table 2). Body weight did not differ between the Control and 15-WGP groups, and both showed a similar increasing trend as the trial progressed (Figure 2A). Average daily DMI was 2.01 ± 0.01 kg DM/day for the Control diet and 2.04 ± 0.01 kg DM/day for the 15-WGP diet. Throughout the feeding trial, DMI remained comparable between treatments except at the final sampling point, when goats receiving the 15-WGP diet exhibited a significantly lower DMI (1.53 ± 0.04 kg DM/day) than the Control group (1.69 ± 0.04 kg DM/day) (Figure 2B). On the other hand, FMI was significantly higher in the 15-WGP group (2.39 ± 0.02 kg FM/day) compared with the Control group (2.20 ± 0.02 kg FM/day) from sampling 1 to sampling 4, with both treatments converging to similar values at the end of the study (Figure 2C). Dietary treatment produced the opposite pattern for water intake: goats fed the 15-WGP diet consumed significantly less water on average (5.79 ± 0.07 L/day) than those in the Control group (6.16 ± 0.07 L/day) (Table 2).

Table 2. Main productive performance traits: least squares means (± SEM) by diet, and effects considered in the statistical model (P-value).

15-WGP, 15% DM of WGP silage; UDM, useful dry matter (% fat + %protein); FPCM, Fat and Protein-Corrected Milk; UFL, forage unit for lactation (INRA system), where 1 UFL = 7.11 MJ of net energy for lactation (NEL); LSCC, Log₁₀ somatic cells count; SEM, Standard error mean; P-values are reported for significant effects; ns, not significant (P > 0.05).

^a,bDifferent letters in the same row indicate significant differences by diet.

Regarding milk yield (MY), FCM and FPCM, no significant differences were detected between diets (Table 2). All three variables declined significantly and similarly in both dietary treatments as lactation progressed (Figures 3A–C). Crude protein content remained stable throughout lactation, with no significant differences between dietary treatments (Figure 4B). Milk lactose content was similar between groups and decreased significantly from early to mid-lactation (Figure 4C). Milk fat content increased significantly toward the end of lactation in both treatments; however, during the late lactation (samplings 4 and 5), 15-WGP milk fat content was significantly higher than the Control milk fat content (Figure 4A). UDM followed the same pattern as milk fat content (Figure 4D). Accordingly, feed efficiency (FPCM/UFL) was significantly higher in the 15-WGP diet compared with the Control diet during late lactation (samplings 4 and 5) (Figure 3D).

Milk urea content and LSCC were significantly affected by diet. WGP-15 milk urea content was significantly lower (602.04 ± 10.8 mg/L) than Control milk urea content (648.76 ± 10.8 mg/L). Conversely, milk from the Control goats exhibited lower LSCC (2.50 ± 0.09–10³ cells/mL) than milk from the 15-WGP goats (2.76± 0.09–10³ cells/mL) (Table 2).

3.2 Hemogram, serum biochemical profile, and oxidative stress

As shown in Table 3, the inclusion of WGP silage did not result in a significant effect on the hemogram. Regarding the serum biochemical profile, only CHOL was significantly affected by dietary WGP inclusion. Goats fed the 15-WGP diet exhibited a significantly higher CHOL (120.31 ± 4.18 mg/dL) than the Control goats (101.12 ± 4.18 mg/dL) (Table 4).

Table 3. Hemogram: least squares means (± SEM) by diet, and effects considered in the statistical model (P-value).

15-WGP, 15% DM of WGP silage; WBC, white blood cells; LYM, lymphocytes; MON, monocytes; NEU, neutrophils; RLN, lymphocyte-neutrophil ratio; RLM, lymphocyte-monocyte ratio; RBC, red blood cells; HGB, hemoglobin; HCT, haematocrit; SEM, Standard error mean; P-values are reported for significant effects; ns, not significant (P > 0.05).

Table 4. Serum biochemical profile: least squares means (± SEM) by diet, and effects considered in the statistical model (P-value).

15-WGP, 15% DM of WGP silage; ALP, alkaline phosphatase; GGT, gamma-glutamyl transferase; AMY, amylase; LYPA, lipase; BUN, blood urea nitrogen; CREA, creatinine; TP, total protein; GLOB, globulins; ALB, albumin; GLU, glucose; CHOL, cholesterol; SEM, Standard error mean; P-values are reported for significant effects; ns, not significant (P > 0.05).

^{a, b}Different letters in the same row indicate a significant difference by diet.

The 15-WGP diet significantly increased plasma antioxidant capacity, as evidenced by the ABTS assay (15-WGP: 0.24 ± 0.00 Trolox eq./mL; Control: 0.22 ± 0.00 Trolox eq./mL) and by the specific SOD activity assay (15-WGP: 0.76 ± 0.02 U/mL; Control: 0.70 ± 0.02 U/mL). In contrast, no significant differences between diets were observed in oxidative status assessed through reduction power (FRAP assay) or in the inflammatory biomarker SAA (Table 5).

Table 5. Oxidative and inflammatory biomarkers: least squares means (± SEM) by diet, and effects considered in the statistical model (P-value).

15-WGP, 15% DM of WGP silage; ABTS, 2.2′-azino-bis(3-ethylbenzothiazoline-6-sulfonate) reduction power; FRAP, Ferric Reducing Antioxidant Power; SOD, Superoxide Dismutase; SAA, serum amyloid-A; SEM, Standard error mean; P-values are reported for significant effects; ns, not significant (P > 0.05).

mg Trolox eq./mL; ²U/mL; ³µg/mL.

^a,bDifferent letters in the same row indicate a significant difference by diet.

3.3 Economic performance of the feeding strategy

Regarding the economic outcomes (Table 6), the largest difference relative to the Control group was observed in feeding cost, with WGP inclusion reducing expenses by 12 €/goat and period. A smaller but favorable difference of 4.07 €/goat and period was also recorded in milk revenue for the 15-WGP diet. Overall, incorporating 15% DM WGP silage resulted in a net economic benefit of 16 €/goat over an 8-month lactation period.

Table 6. Economic outcomes of incorporating white grape pomace silage (WGP 15% DM) into the diet of Murciano-Granadina dairy goats over an 8-month lactation period (€/goat).

UDM, useful dry matter (% fat + %protein); FPCM, Fat and Protein-Corrected Milk; *(Control result - 15-WGP result).

4 Discussion

In the present experiment, DMI and milk yield in goats fed the 15-WGP diet did not differ from those observed in the Control group, which represents a positive outcome from a herd-management perspective. Maintaining both intake and milk production indicates that incorporating WGP at 15% DM does not compromise the core productive performance of Murciano-Granadina goats. The values obtained for DMI and milk yield were aligned with the expected performance of this breed during lactation (Fernandez et al., 2005; MAPA, 2026). Comparable milk yields for Murciano-Granadina goats under similar lactation periods have also been reported by Fernández et al. (2002), Monllor et al. (2020) and Monllor et al. (2023). The DMI were consistent with previous reports under comparable physiological conditions (Fernandez et al., 2005; Ibáñez et al., 2016), reinforcing the notion that WGP inclusion at 15% DM does not impair productive performance. Although Martins Flores et al. (2020) described a dose-dependent reduction in intake when increasing the inclusion levels of grape pomace silage (20%, 37.5% and 50% DM) in lambs, our findings suggest that a 15% DM inclusion represents a moderate level of WGP silage that does not adversely affect dry matter intake in lactating goats. In line with these observations, Moate et al. (2020) reported a clear trade-off when the inclusion of grape pomace in bovine diets was doubled relative to the level used in the present study (333 g/kg DM), achieving an approximate 15% reduction in enteric CH₄ emissions but at the cost of a 10% decline in productive performance. Goats, being natural browsers, exhibit a higher tolerance to dietary tannins than sheep or cattle, largely due to their salivary proteins, which show strong affinity for tannin binding (Hofmann, 1989; Launchbaugh and Walker, 2006; Schmitt et al., 2020).

The parallel pattern observed in DMI between goats fed both diets was mirrored in body weight, with mean body weight not differing significantly between groups. Furthermore, the trajectory of body-weight change throughout lactation was similar in both treatments. This pattern aligns with the typical physiology of lactating goats, which gradually regain weight and body condition after kidding and continue gaining weight as the subsequent pregnancy advances, preceding the next lactation cycle (Widiyono et al., 2020; Chaves et al., 2024). The higher feed efficiency observed in WGP-15 goats, reflected primarily in their increased milk fat content despite similar feed intake, may indicate an improved metabolic utilization of the diet following a prolonged adaptation period. This interpretation is supported by the greater production of VFAs in the WGP-15 diet, determined by in vitro digestion, as these ruminal fermentation end-products—primarily acetate and butyrate—are absorbed across the rumen wall and constitute the main energy source for ruminants, thereby contributing directly to milk fat synthesis (Bauman and Griinari, 2001; Mahboubi et al., 2026). Moreover, the enhanced in vitro NDF digestibility (IVNDFD) observed in the WGP-15 diet may further support this interpretation, as greater fiber degradation likely increased the supply of fermentation-derived energy available for milk-fat synthesis (Van Soest, 1994a; Chilliard et al., 2003), without increasing feed intake. The delayed appearance of this effect likely reflects a necessarily long period of continuous intake, reflecting the gradual adaptation of rumen microbial populations to the dietary change (Weimer, 1998; Ricci et al., 2022). Such adaptation is required for the stabilization of fermentative function and, consequently, for an efficient provision of fermentation-derived energy to the host (Van Soest, 1994a; Newbold and Ramos-Morales, 2019). This interpretation could be further strengthened by a rumen-liquid microbiota analysis in goats consuming the WGP diet, which would help clarify the microbial shifts underlying the observed response.

Previous studies have reported productive performance outcomes in line with these evidences when incorporating 60 g/kg DM of dried grape pomace, up to 100 g/kg DM of grape seed cake, 120 g/kg DM of red grape pomace silage, or 150 g/kg DM of white grape pomace silage (Renna et al., 2023; Antunović et al., 2024; Gálvez-López et al., 2026; Galvez-Lopez et al., 2025b respectively). However, all these experiments were conducted over short periods and during early lactation. Therefore, the results of the present research —carried out over a full lactation cycle— highlight the potential of WGP silage as an alternative feed ingredient that can partially replace conventional forages without compromising key production traits. The stability of productive responses at 15% DM inclusion suggests that Murciano-Granadina goats can efficiently adapt to diets incorporating moderate levels of polyphenol-rich agro-industrial by-products, supporting their use within circular feeding strategies.

Furthermore, goats fed the WGP-15 diet exhibited lower WI, a response that can be explained by the greater moisture supplied through the silage component of the ration, which also increased fresh-matter intake. According to Van Soest (1994b), feeds with high moisture content—such as silages and fresh forages—can partially meet the animals’ free-water requirements under temperate conditions. This mechanism becomes particularly relevant when animals experience heat stress or when access to drinking water is restricted (Van Soest, 1994c). In practical terms, the reduction of approximately 0.4 L of WI per goat per day represents a meaningful saving of a resource that is increasingly scarce in dry-climate regions, where water availability often limits livestock productivity. This aspect gains further importance in the broader context of resource competition, as livestock systems must increasingly share water with crop agriculture and other human uses, underscoring the need for efficient water use within integrated production frameworks (Wisser et al., 2024).

The reduction in milk urea observed in goats fed with WGP reflects a meaningful physiological adjustment, most likely linked to more efficient nitrogen utilization arising from improved alignment between rumen-degradable protein and fermentable carbohydrate supply. Even so, several mechanisms could underlie this response. Milk urea concentrations are largely governed by crude protein intake and the balance between dietary protein and energy (Bendelja et al., 2020). In this study, both diets were designed to provide equivalent amounts of energy and protein, thereby limiting the influence of these factors. Dietary NDF content, which increased with WGP inclusion (Criscioni and Fernández, 2016), is another variable known to affect milk urea. Bonanno et al. (2008) reported a negative correlation between NDF and milk urea under isoproteic conditions, offering a plausible explanation for the lower values detected in WGP_15 milk. Moreover, WGP contains substantial levels of tannins (Tangolar et al., 2011; Harbeoui et al., 2017), which can bind ruminal proteins and form complexes that reduce their ruminal degradation (Frutos et al., 2004; Patra and Saxena, 2011). This process decreases the production of ruminal ammonia (NH₃), with urea as the primary excretory product of this pathway (Makkar, 2003).

Although LSCC was statistically higher in the WGP-15 milk, this difference lacks biological relevance. The somatic cell counts observed in both groups reflect an optimal intramammary health status, remaining well below the critical threshold of 1,000 × 10³ cells/mL established for dairy goats in the literature (Paape et al., 2001; Podhorecká et al., 2021).

No diet-related effects were detected for hematological or serum biochemical parameters except for plasma cholesterol concentrations. Similarly, no alterations in hematological and biochemical profiles have been reported in small ruminants supplemented with grape-derived by-products. Alba et al. (2019) found no alterations in Lacaune sheep supplemented with 20 g/kg DM of grape pomace flour, and comparable results were described in French Alpine goats receiving 100 g/kg DM (Antunović et al., 2024) and in Saanen goats offered 150 g/kg DM (Badiee Baghsiyah et al., 2023). Plasma cholesterol concentrations were significantly higher in WGP-15 goats compared to the control group. This increment could be attributed to the lipid profile of the grape seeds, which are naturally rich in polyunsaturated fatty acids, particularly linoleic acid (Blasi et al., 2024; Galvez-Lopez et al., 2025a; Romero et al., 2025). In ruminants, an increased intestinal influx and absorption of long-chain fatty acids stimulate hepatic lipoprotein synthesis for lipid transport, consequently raising circulating total cholesterol levels (Delavaud et al., 2022). It is worth noting that despite this statistical increase, the values remained within the physiological reference ranges for dairy goats (80–130 mg/dL), indicating that the treatment did not compromise the animals’ metabolic health. Both hemogram and serum biochemical parameters remained within the established physiological reference intervals for dairy goats (Kaneko et al, 1997; Russell and Roussel, 2007; Merck Veterinary Manual, 2026).

Plasma oxidative-stress biomarkers showed clear improvements in the WGP-15 goats, as evidenced by higher ABTS radical-scavenging activity and greater specific antioxidant capacity reflected by SOD activity. In a short-term trial, Galvez-Lopez et al. (2025b) had already observed a slight upward tendency in ABTS and SOD toward the end of the period of study at the 10% and 15% DM of WGP inclusion, although the limited duration of that experiment may have constrained the full expression of antioxidant responses. In contrast, Antunović et al. (2024) reported increased SOD activity in dairy goats fed diets containing 5% and 10% grape seed cake over a 60-day period. Similarly, Alba et al. (2019) previously documented a comparable enhancement in sheep supplemented with 20 g/kg DM of grape pomace flour during a short 15-day feeding period. This antioxidant effect is attributed to the polyphenolic compounds present in grape pomace, which are widely recognized for their strong radical-scavenging capacity and their role in protecting tissues against oxidative stress (Tangolar et al., 2011; Galanakis, 2012; Ovcharova et al., 2016; Harbeoui et al., 2017).

Finally, from an economic standpoint, WGP silage offers a clear cost advantage, including its processing and ensiling, amounting to 120.9 €/t DM (Galvez-Lopez et al., 2025a), which is markedly lower than the price of conventional forages typically used in ruminant diets, such as alfalfa hay (240 €/t DM, Lonja de Cereales de Albacete, 2026). When this cost advantage is considered alongside the observed milk production performance (UDM) and the market price of fat- and protein-corrected milk (€/FPCM), the greatest economic divergence relative to the Control group arises from feeding costs, with WGP inclusion reducing expenses by 12 €/goat. A smaller yet positive difference of 4.07 €/goat was also noted in milk revenue for the 15-WGP diet. Overall, incorporating WGP silage at 15% DM generated a net economic gain of 16 €/goat over an 8-month lactation period. The livestock sector operates under increasing economic, environmental, and structural pressure, largely driven by the tightening availability of feed resources and the growing competition for raw materials. This scenario has led to a sustained rise in production costs that has not been matched by equivalent increases in farm-gate milk prices, progressively eroding profit margins. Because feed accounts for 55–65% of total operating costs in dairy systems—depending on the production model and level of intensification (Gocsik et al., 2025)—nutrition remains the most decisive factor for farm profitability, both through direct expenses and its influence on animal health and performance (Benton et al., 2022). Strategies that improve feed efficiency or incorporate alternative raw materials are therefore essential to simultaneously enhance economic sustainability and reduce environmental impact (Marques et al., 2022). In this context, the use of locally sourced agro-industrial by-products offers a practical means of lowering dependence on conventional feedstuffs, reducing ration costs and mitigating emissions associated with long-distance transport (Romero-Huelva et al., 2017). This aligns with the principles of sustainable production systems, particularly in the context of circular economy approaches to agri-food production.

From a practical standpoint, the feasibility of implementing WGP silage may vary across production systems. The bale-silage format offers clear advantages in terms of storage, handling, and on-farm distribution (Galvez-Lopez et al., 2025a), allowing its use both in intensive indoor dairy operations and in pasture-based systems where it can be delivered directly in the field. The main challenge lies in demonstrating to farmers the practical viability and consistent performance of this alternative feed resource for its regular inclusion in the diet. Nevertheless, once these logistical considerations are addressed, WGP silage represents a feasible and cost-effective option that can be readily integrated into diverse management systems, contributing to more resource-efficient and sustainable production practices.

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Footnotes

Edited by: Soumaya Boukrouh, Mohammed VI Polytechnic University, Morocco

Reviewed by: Naima Mahreen, National Institute for Biotechnology and Genetic Engineering, Pakistan

Eduardo Michelon do Nascimento, Federal University of the Recôncavo of Bahia, Brazil

Footnotes

ABTS, 2.2′-azino-bis(3-ethylbenzothiazoline-6-sulfonate); ADF, Acid Detergent Fiber; ADL, Acid Detergent Lignin; ALB, Albumin; ALP, Alkaline Phosphatase; AMY, Amylase; BW, Body Weight; BUN, Blood Urea Nitrogen; CHOL, Cholesterol; CP, Crude Protein; CREA, Creatinine; DM, Dry Matter; DMI, Dry Matter Intake; EE, Ether Extract; FCM, Fat-Corrected Milk; FM, Fresh Matter; FMI, Fresh Matter Intake; FPCM, Fat and Protein-Corrected Milk; FRAP, Ferric Reducing Antioxidant Power; GGT, Gamma-Glutamyl Transferase; GLOB, Globulin; GLU, Glucose; HCT, Hematocrit; HGB, Hemoglobin; IVDMD, In Vitro Dry Matter Digestibility; IVNDFD, In Vitro Neutral Detergent Fiber Digestibility; IVOMD, In Vitro Organic Matter Digestibility; LSCC, Log10 Somatic Cell Count; LYM, Lymphocytes; LYPA, Lipase; ME, Metabolizable Energy; NDF, Neutral Detergent Fiber; NFDM, Non-Fat Dry Matter; OM, Organic Matter; RBC, Red Blood Cells; RLN, Ratio Lymphocytes/Neutrophils; RLM, Ratio Lymphocytes/Monocytes; SAA , Serum Amyloid-A ; SCC, Somatic Cell Count; SEM, Standard Error of the Mean; SOD, Superoxide Dismutase; TP, Total Protein; UDM, Useful Dry Matter; VFA, Volatile Fatty Acids; WBC, White Blood Cells; WI, Water Intake; WGP, White Grape Pomace.