Document Type : Research Paper
Extended Abstract
Introduction
Recent environmental concerns have increased interest in managing by-products from food and agriculture industries, particularly as options for animal feed (Tufarelli et al. 2013). Using agricultural by-products in animal nutrition not only reduces the environmental impact of these materials but also enhances their economic value and profitability (Malenica et al. 2023). This approach offers an efficient method for transforming lower-quality food materials into higher-quality products, such as meat, while simultaneously decreasing livestock dependence on feed that could otherwise serve as human food (Bampidis and Robinson 2006). Among these by-products, molasses and vinasses, derived from sugar beet and sugarcane processing, have shown potential for animal feeding applications (Gerimipour et al. 2019).
Molasses, a byproduct or final product of sugarcane or sugar beet processing, is obtained during the production of raw or refined sugars. This viscous liquid is characterized by a high concentration that impedes the complete crystallization of its sugar content through conventional methods. Molasses is widely recognized as a high-quality energy source and frequently incorporated into ruminant diets (Mordenti et al. 2021). Vinasses or stillage are byproducts of the anaerobic fermentation of molasses and contain elevated concentrations of salts and organic matter. This wastewater, which generates 10 to 18 L L-1 of ethanol, contaminates soil and surface water and poses a threat to aquatic ecosystems (Brito et al. 2024). Vinasses have high concentrations of potassium, calcium, magnesium, sulfur, and nitrogen. Furthermore, the amino acids present contribute to metabolic processes and activate the immune system in various species (Hidalgo et al. 2009) . The concentration of soluble carbohydrates in vinasses is lower than that in molasses, while its protein and ash content are higher. It has been documented that the organic acids present in vinasses enhance feed conversion ratio, increase growth rates, improve digestibility, and facilitate nutrient metabolism (Hidalgo et al. 2009). In a separate study, it was reported that a mixture of bagasse and vinasses, when used in the fattening of lambs, resulted in reduced feed consumption and increased weight gain, with no effect on carcass traits (López-Campos et al. 2011).
The incorporation of molasses and vinasses into livestock feed systems presents logistical challenges due to the need for storage, transportation, and handling infrastructure. However, integrating these by-products into lick blocks offers a practical solution by simplifying feeding protocols and enhancing feed cohesion. Multi-nutrient blocks (MNB) reduce reliance on commercial concentrates, lower costs, and ease competition for grain-based resources between livestock and humans (de Evan et al. 2020). Moreover, Iranian pastures often lack sufficient energy, protein, and minerals, highlighting the potential of MNB to meet livestock nutritional needs and promote sustainable practices. These seasonal deficiencies parallel feed scarcity issues faced across tropical and subtropical regions, where drought, poor pasture quality, and fluctuating grain prices repeatedly threaten small ruminant productivity. In this study, we hypothesize that using molasses and vinasses in MNB can significantly reduce the environmental impact of sheep production while maintaining animal health. We propose that these by-products require less land, water, and fertilizer than conventional feeds, lowering water and carbon footprints and improving land use efficiency, especially in water-scarce regions like Iran. Thus, we evaluated the impact of molasses and vinasses based MNB (MMNB and VMNB) on growth performance, blood metabolites, rumen parameters, and environmental sustainability in pregnant Mehraban ewes. Iran’s semi-arid sheep systems share key characteristics with livestock production landscapes in Africa, South Asia, and Latin America, where resource limitations and climate stressors are pronounced.
Material and methods
The present study was conducted in the rangelands and traditional livestock farming systems of Baghche village, located 25 kilometers from Hamedan, Iran. For this purpose, 60 Mehraban pregnant ewes (parity 1 to 4) with a mean body weight of 43 ± 3 kg were allocated to three experimental groups (20 replicates per group) using a completely randomized design. All experimental procedures involving animals were approved by the Research Ethics Committee of Bu-Ali Sina University (Approval No. 1680823) and complied with institutional guidelines for animal care and use. The experimental treatments consisted of: 1) a control group (pasture without MNB), 2) pasture supplemented with access to MMNB, and 3) pasture supplemented with access to VMNB. All animals were in phase of late pregnancy (i.e., 45-55 days to parturition). The MNBs were provided 300 g/sheep/day block twice daily: at 8:00 AM before the livestock were sent to graze and at 5:00 PM after their return from the pasture, over a 30-day period. An adaptation period of 10-day was considered before starting experimental periods. Based on the average age of the ewes, the MNBs were formulated in accordance with NRC (1985) standards. A diet was formulated theoretically (TC) to calculate environmental parameters, and was not subjected to in vivo evaluation using pregnant ewes (Table 1). To mitigate internal parasite infections, all ewes were orally administered albendazole tablets.
Table 1. Ingredients and chemical composition of multi-nutrient blocks including molasses (MMNB) or vinasses (VMNB) for supplementation of pregnant Mehraban ewes
جدول 1- اجزا و ترکیبات شیمیایی بلوک های چند مغذی حاوی ملاس یا ویناس برای استفاده در تغذیه میش های آبستن مهربان
|
Ingredients (% DM) |
MMNB |
VMNB |
TC1 |
|
Tomato pulp |
16.9 |
19.0 |
- |
|
Rice Bran |
13.7 |
15.5 |
- |
|
Molasses |
36.2 |
0 |
- |
|
Vinasses |
0 |
26.5 |
- |
|
Waste Yeast2 |
0 |
7.6 |
- |
|
Barley grain |
- |
- |
19.1 |
|
Corn grain |
- |
- |
10.0 |
|
Wheat bran |
- |
- |
28.5 |
|
Soybean Meal |
23.5 |
21.7 |
34.1 |
|
Urea |
3.45 |
3.45 |
2.00 |
|
Salt |
3.45 |
3.45 |
3.45 |
|
Mineral and Vitamin Supplement |
2.8 |
2.8 |
2.8 |
|
Chemical Composition |
|
|
|
|
Metabolisable Eenergy (Mcal/Kg DM) |
2.68 |
2.60 |
2.62 |
|
Crude Protein (% DM) |
29.4 |
30.1 |
29.8 |
|
Calcium (% DM) |
1.31 |
1.33 |
1.32 |
|
Phosphorus (% DM) |
0.62 |
0.67 |
0.68 |
|
1. Theoretical concentrate formulated for calculation of some environmental and sustainability parameters. MMNB and VMNB were formulated to be approximately isonitrogenous and isoenergetic compared to TC 2. Waste yeast is dead yeast cells precipitated in bottom of fermentation tank of alcohol production |
|
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Measurements and Analyses
Chemical Analyses of Feed
The chemical composition of the feed was determined using established analytical methods. Dry matter (DM) and crude protein (CP), were measured according to the standard procedures outlined by the Association of Official Analytical Chemists (AOAC 1990). Throughout the experimental period, feed blocks were weighed daily and provided to the sheep. Body weights were recorded at 10-day intervals prior to morning feeding to assess growth and health responses to the experimental diets.
Blood parameters
Blood samples were collected from the jugular vein of all sheep on days 15 and 30 of the experiment to assess metabolic and oxidative stress markers. Samples were divided into two tubes: one containing EDTA anticoagulant for plasma separation and another for serum. The values of glucose, total protein, albumin, and urea were measured using commercial kits (Pars Azmoon, Iran) with an autoanalyzer. Antioxidant enzyme activity was determined using the RANSEL kit (Randox Laboratories, UK), while malondialdehyde (MDA) levels, an indicator of lipid peroxidation, were quantified using a modified method by Buege and Aust (1978).
Rumen fermentation analyses
Rumen fluid was collected and analyzed to assess fermentation parameters. Rumen fluid was transferred to 50 mL Falcon tubes and centrifuged at 5000 rpm for 20 minutes at 4°C. The supernatant was mixed with 2 N HCl at a 1:1 ratio, and ammonia nitrogen concentration was measured using the phenol-hypochlorite method (Broderick and Kang 1980). For recording protozoa number, at the end of the trial, rumen fluid was collected via an esophageal tube and fixed with 10% formaldehyde solution to preserve protozoa. Samples were stained with methylene blue and counted under a light microscope using a specialized counting slide, as outlined by Dehority (1993) .
Environmental and sustainability factors
To assess the environmental sustainability of the three diets MMNB, VMNB, and TC Ingredients were categorized into two groups based on their production origin. First, high-impact ingredients: Primary crops (e.g., barley grain, corn grain, soybean meal), which require significant land, water, and energy inputs for cultivation. Second, low-impact ingredients: agricultural by-products (e.g., tomato pulp, rice bran, molasses, vinasses, waste yeast, wheat bran) and minor additives (e.g., urea, salt, mineral supplements), which incur minimal additional environmental impact as they are residuals of other processes or have negligible contributions to the assessed metrics.
Environmental impact values were assigned using generalized estimates from agricultural literature: Water Footprint: 1000 L Kg-1 for primary crops and 100 L kg-1 for by-products (Mekonnen and Hoekstra 2011); Carbon Footprint: 0.75 kg CO₂e kg-1 for primary crops and 0.1 kg CO₂e kg-1 for by-products (Clune et al. 2017); Land Use: 1.5 m² kg-1 for primary crops and 0 m² kg-1 for by-products, assuming no additional land allocation for by-products (Nemecek et al. 2016).
For each diet, the proportion of high-impact ingredients was calculated, and the environmental impact was determined as a weighted sum of contributions from high-impact and low-impact ingredients per kilogram of feed. These estimates provide relative comparisons rather than absolute values, due to the absence of region-specific production data.
Statistical analysis
Data for blood parameters, which involved repeated measurements over time, were analyzed using the General Linear Model (PROC GLM) procedure in SAS 9.4 (SAS Institute Inc., Cary, NC, USA). In contrast, body weight and rumen parameters, measured only at a single time point, were analyzed using a standard completely randomized design (CRD) model
The statistical model for the repeated measures analysis was as follows:
Yijk = μ + Ti + Aj(i) + Dk + (T×D)ik + (A×D)jk + εijk
Where: Yijk = the response variable for the animal j in the treatment i on the day k, μ = overall mean, Ti = fixed effect of treatment i (Control, MMNB, VMNB), Aj(i) = random effect of animal j nested within treatment I, Dk = fixed effect of sampling day k, (T×D)ik = interaction effect between treatment i and day k, (A×D)jk = interaction between animal j and sampling day k and εijk = residual error. When interactions were not significant (P > 0.05), they were removed from the model and main effects were reported. All variables exhibited a normal distribution upon assessment for normality. Means were compared using Tukey’s HSD test at a significance level of α = 0.05 to identify significant differences among treatment groups.
Results
Body Weight Changes
As illustrated in Table 2, supplementation with molasses-vinasses lick blocks did not significantly affect (P > 0.05) body weight at any measured interval.