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Article

Composition, Mineral and Fatty Acid Profiles of Milk from Goats Fed with Different Proportions of Broccoli and Artichoke Plant By-Products

by
Paula Monllor
1,
Gema Romero
1,
Alberto S. Atzori
2,
Carlos A. Sandoval-Castro
3,
Armín J. Ayala-Burgos
3,
Amparo Roca
1,
Esther Sendra
1 and
José Ramón Díaz
1,*
1
Departamento de Tecnología Agroalimentaria, Universidad Miguel Hernández de Elche, 03312 Alicante, Spain
2
Dipartimento di Agraria, Università degli Studi di Sassari, 07100 Sassari, Italy
3
Facultad de Medicina Veterinaria y Zootecnia, Universidad Autónoma de Yucatán, Mérida 97100, Mexico
*
Author to whom correspondence should be addressed.
Foods 2020, 9(6), 700; https://doi.org/10.3390/foods9060700
Submission received: 28 April 2020 / Revised: 27 May 2020 / Accepted: 28 May 2020 / Published: 1 June 2020
(This article belongs to the Special Issue Better Animal Feeding for Improving the Quality of Ruminant Meat and Dairy)
Versions Notes

Abstract

:
In the Mediterranean region, artichoke and broccoli are major crops with a high amount of by-products that can be used as alternative feedstuffs for ruminants, lowering feed costs and enhancing milk sustainability while reducing the environmental impact of dairy production. However, nutritional quality of milk needs to be assured under these production conditions and an optimal inclusion ratio of silages should be determined. This work aimed to evaluate the effect of three inclusion levels (25%, 40%, and 60%) of these silages (artichoke plant, AP, and broccoli by-product, BB) in goat diets on milk yield, composition, and mineral and fatty profiles. Treatments with 60% inclusion of AP and BB presented the lowest milk yield. No differences were found on the milk mineral profile. Inclusion of AP in the animals’ diet improved the milk lipid profile from the point of view of human health (AI, TI) compared to BB due to a lower saturated fatty acid content (C12:0, C14:0, and C16:0) and a higher concentration of polyunsaturated fatty acids (PUFA), especially vaccenic acid (C18:1 trans11) and rumenic acid (CLA cis9, trans11), without any differences with the control treatment.

1. Introduction

Regarding milk consumption worldwide, cow’s milk occupies first place, followed by buffalo and thirdly, that of goat [1], which continues to increase [2] due to its high level of calcium, phosphorus, and animal protein. In addition, goat milk has been classified as a substitute for cow’s milk in those people who suffer from some type of allergy to this food [3]. Goat’s milk is a source of nutrients in the human diet due to its content of Se and polyunsaturated fatty acids (PUFA), such as vaccenic and rumenic acid or CLA [4,5], which can influence the prevention of certain types of cancers and cardiovascular diseases [6,7]. The literature contains many studies of how diet affects the performance and quality of ruminant milk. Hilali et al. [8] and Cappucci et al. [9] found that the inclusion of agro-industrial and olive by-products in ewes’ diets enhanced milk fatty acid profile, with no effects on performance and milk macro-composition. On the other hand, Schulz et al. [10] observed changes in milk fatty acid profile in cows fed with red clover silage in comparison with maize silage. Finally, Monllor et al. [11] showed slight differences in fat and protein levels of milk from goats fed with artichoke by-products and an increase of Selenium and polyunsaturared fatty acid contents. The inclusion of agricultural by-products in ruminant diets does not have to affect the sensory quality of dairy products. Such is the case in Caputo et al. Ref. [12], who did not observe differences in the aromatic profile of milk and dairy products from cows fed with destoned olive cake.
It is necessary to enhance the sustainability of milk production and reduce the impact of animal feeding. The use of local resources, especially if recovered from by-products, may significantly enhance milk sustainability. Artichoke (Cynara scolymus L.) and broccoli (Brassica oleracea var. Italica) crops generate large quantities of by-products. According to Food and Agriculture Organization of the United Nations (FAO) [13], 1,505,328 t of artichoke and 25,984,758 t of broccoli were harvested worldwide in 2017. The artichoke plant is a waste, mainly formed of stems and leaves, and some unharvested inflorescences are left in the field after harvest of inflorescences for human consumption. This by-product has traditionally been used by grazing small ruminants or collected and brought to dairy farms [14]. The yield of green fodder in this crop is 11.1 t/ha [15], which, taking into account FAO’s cultivated area data [13] (2017) worldwide (122,390 ha), would result in an annual production of more than 1,300,000 t of available artichoke plant. According to Ros et al. [16], 29.5% of harvested broccoli is composed of stems and inflorescences that are not suitable for human consumption. Broccoli by-product is considered, from the point of view of animal feed, more as a concentrate than as a forage, due to its low fibre content and high protein level [17].
Agri-food by-products, whether coming from stubbles left in the field or the canning industry, constitute a supply of alternative forage for livestock, allowing the use of local resources and reducing feed costs without damaging animal performance and productivity, as long as the rations that include these feeds are balanced. The use of these by-products can also be a solution to minimise residues produced by the agro-food industry and thus reduce removal costs and emissions of polluting gases caused by uncontrolled fermentation of these agricultural wastes. In addition, the use of agro-food by-products reduces the land and supplies dedicated to the development of livestock feed, thus aiding the circular economy. However, the strong seasonality and high water content of these feeds limits their systematic use in animal feeding. Through lactic fermentation, the silage is able to conserve perishable products so that cellular respiration is suppressed, protein and vitamin degradation is prevented, and clostridial fermentation is avoided [18], reaching levels of safety that do not endanger the health of animals and do not compromise the hygienic-sanitary quality of milk or derived products.
Previous studies have shown that these by-product silages have the proper fermentative and nutritional conditions to become part of sheep and goat diets [14,19,20]. The references found in the literature about the effect of consuming these silage by-products on milk quality and composition, as well as on the health status of animals, are scarce [21,22,23]. None of these studies have been conducted in dairy goats, except Muelas et al. and Monllor et al. [11,24], where the effect of up to 25% inclusion of silage artichoke plant on the technological aptitude of milk was studied.
With the previous background, it is hypothesised that these by-products may be incorporated into the diet of lactating goats without detriment to their milk yield and quality. Therefore, the objective of this experiment is to study the effect of the inclusion of by-product silages (artichoke plant and broccoli by-product) in the ration of goats on milk production, macro-composition, and quality and determine the optimum level of inclusion in the ration among the three levels tested (25%, 40%, and 60%), with the aim of assuring milk nutritional quality within an integrative approach of enhanced sustainability of milk production.

2. Materials and Methods

2.1. Animals and Facilities

The animals used in this experiment were Murciano-Granadina lactating goats housed in the experimental and teaching farm of the Miguel Hernández University, Spain, with access to outdoor yards (2.30 m2/animal), free access to water, and enough feeding space for all animals (at least 35 cm/animal and 1.50 m2/animal as total indoor space) with a straw bed. As usual in the region, the animals were milked once a day (Casse milking parlour, 2 × 12 × 12, GEA, Germany) and fed twice a day, at 8:00 a.m. and 2:00 p.m. This study was approved by the Ethical Committee of Experimentation of the Miguel Hernández University (code UMH.DTA.GRM.01.15).

2.2. Experimental Design

On the fourth month of lactation, 63 lactating goats were selected (41.2 ± 7.15 kg, 2.25 ± 0.80 kg/day, 5.39 ± 0.48 Log cell/mL). The animals were divided into seven homogeneous groups regarding body weight (BW), daily milk yield, and somatic cell count (SCC).
A short-term experiment was conducted to study the effect of inclusion in the diet of two by-product silages (artichoke plant, AP, and broccoli by-product, BB), of which their composition and fermentation quality are shown in Table 1. They were included at three levels each (25%, 40%, and 60%, expressed on a dry matter basis of the total ration); thus, seven rations were tested: 25%, 40%, and 60% of artichoke plant silage (AP25, AP40, and PAP60, respectively), the same percentages of broccoli by-product silage (BB25, BB40 and BB60), and a control diet (C), which represents the conventional ration used to feed dairy goats (alfalfa hay and a mixture of grains). Diets were formulated according to the recommendations of Fernandez et al. Ref. [25], an average amount of 2.23 kg DM/day was offered, and the seven rations were isoenergetic and isoproteic. Table 2 shows the ingredient proportion and the chemical composition of each diet. Once the pre-experimental sampling was performed, the experiment lasted 4 weeks. In the first two weeks, each group of animals adapted to their diet. In the next two weeks, data on feed consumption, milk yield, and body weight were recorded and blood and milk samples from animals were collected weekly for subsequent laboratory analyses. Bulk milk samples were collected weekly and used to determine mineral and fatty acid profile concentrations.

2.3. Analysed Variables

The body weight of the animals (BW, kg) was recorded by weighing them on a scale (±100 g, APC, Baxtran, Vilamalla, Spain). The feed consumption was measured twice a week and calculated by the average of the difference of the feed offered and refused on dry matter basis. The chemical composition of the silages and diets was analysed as previously described by Monllor et al. [11]. Dry matter (DM, g/kg; method 930.5), 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 crude fibre (CF; g/kg DM; method 962.09) were determined following AOAC [27] procedures. Neutral detergent fibre (NDF, g/kg DM), acid detergent fibre (ADF, g/kg DM), and acid detergent lignin (ADL, g/kg DM) were analysed according to Van Soest et al. [28]. Total polyphenol content (TP, g/kg DM) was measured by the Folin-Ciocalteu method [29]. Volatile fatty acids (VFA, g/kg DM) (acetic, propionic, and butyric acid, also including lactic acid and ethanol) were determined by HPLC liquid chromatography (Agilent 1200, Santa Clara, CA, USA and Supelcogel C-610H column: 30 cm × 7.8 mm ID, Saint Louis, MO, USA), by Feng-Xia et al. [30] methodology. Apparent in vitro dry matter digestibility (IVDMD, g/kg DM) was measured according to Menke and Steingass [31]. Fatty acid profile analysis in diets was performed by direct methylation on the lyophilised samples, without prior extraction of the fat, according to Kramer et al. [32] and were identified by a gas chromatograph (GC-17A Shimadzu, Kyoto, Japan) coupled with a flame ionisation detector (FID) equipped with a capillary column (CP Sil 88 100 m × 0.25 mm internal diameter and 0.20 µm internal coverage, Agilent, Santa Clara, CA, USA). A mixture of fatty acid methylated esters (FAME;18912-1AMP, Sigma-Aldrich, Saint Louis, MO, USA) was used for identification of the fatty acids of the samples.
Dietary and milk minerals (Na, Mg, K, Ca, P, S, Se, Zn, Cu, Fe, and Mn) were determined by carrying out a previous digestion of the samples, according to González Arrojo et al. [6]. Microwave (MW) digestion unit Ethos Easy, Milestone (Milestone, Srl, Sorisole, Italy) equipped with a rotor for 10 TFM (chemically modified PTFE) vessels was used for sample mineralisation. The microwave program consisted of four phases (i) 5 min at 1000 W at temperatures from 100 to 60 °C; (ii) 10 min at 1000 W from 165 to 80 °C; (iii) 5 min at 1000 W from 180 to 120 °C; and, (iv) 5 min at 700 W from 180 to 120 °C. The ICP-MS (inductively coupled plasma mass spectrometry) instrument used in this study was an Agilent 7700× Octopole Reaction System (ORS) (Agilent Technologies, Tokyo, Japan). The ICP-MS operating conditions were optimised for the simultaneous determinations of all elements. ICP-MS standard solutions were prepared daily by appropriate dilution of stock standard 1000 mg/L for each element in 2% v/v Suprapur HNO3. An appropriate internal standard was also required for each analyte to correct physical and/or matrix interferences in ICP-MS.
The milk yield (kg/day) of every goat was determined during milking using a Lactocorder® device (Lactocorder, Balgach, Switzerland). This device collected a representative sample of 100 mL of milk at every milking of each animal for subsequent analysis. The macro-composition of milk (fat, protein, true protein, casein, whey protein, lactose, total solids, TS; non-fat total solids, NFTS; useful dry matter content, UDM, and ash; %) and urea content (mg/L) was determined by medium infrared spectroscopy equipment (MilkoScan™ FT2, Foss, Hillerød, Denmark). The SCC (103 cell/mL) was analysed by an electronic fluoro-optical method (DCC, DeLaval, Tumba, Sweden). Fat corrected milk yield (FCM) was calculated according to Gravert equation [33]: FCM (3.5%) = 0.433 × milk yield (kg/day) + 16.218 × fat milk yield (kg/day). Milk fatty acids were extracted by the Folch procedure, with some variations collected in Romeu-Nadal et al. [34] and were methylated following the Nudda et al. [35] method. The equipment, column, and FAME mix used for the identification of peaks of milk fatty acid profile were the same as for the diets. Atherogenicity index (AI) and thrombogenicity index (TI) were calculated according to Ulbricht and Southgate [36]. These indices provide important information because AI is related with the ability of lipids’ adhesion to immunological and circulatory system cells and TI indicates the tendency to form clots in blood vessels [8]. Desaturase indices (DI) for C14:0, C16:0, and C18:0 were calculated according to Lock and Garnsworthy [37].
In order to assess the effect of the diets on goats’ metabolism, blood samples were analysed. The same day as the milk sampling was performed, the fasting animals were bled and samples were collected for glucose, urea, and β-hydroxybutyrate (BHB) analysis. Blood samples were analysed with a glucose oxidase/peroxidase kit (Ref. 11503, Biosystems, Barcelona, Spain) for glucose (mg/dL), with a kinetic method (GN 10125, Gernon, Sant Joan Despí, Spain) for urea (mg/dL), and for the BHB (mmol/L), the Ranbut D-3-Hydroxybutyrate kit (RB 1007, Randox, Crumlin, UK) was used.

2.4. Calculations and Statistical Analysis

The SCC data were transformed into log10 scores before statistical analysis (LSCC).
BW, milk yield and macro-composition, SCC, and plasmatic profile data were performed using SAS GLIMMIX (SAS Institute Inc., Cary, NC, USA) with repeated measures, introducing the covariate of the data obtained in the pre-experimental sampling into the model and considering DIET, SAMPLING, and interaction DIET × SAMPLING as fixed effects, according to the following equation:
Y = µ + Di + Sj + DixSj + covY0 + Ak + e,
where Y is the dependent variable, µ is the intercept, Di is the fixed effect of the diet (i = C, AP25, AP40, AP60, BB25, BB40, BB60), Sj is the fixed effect of sampling (j = 1, 2, 3), DixSj is the interaction of diet with sampling, covY0 is the effect of the value of Y in sampling 0, Ak is the random effect of the animal, and e is the residual error. The covariance model with a lower value of the Akaike criterion (lower AIC and BIC) was used for each variable.
Milk mineral and fatty acid profile data were analysed using SAS GLM (SAS Institute Inc., Cary, NC, USA), introducing the covariate of the data obtained in the pre-experimental sampling into the model and considering DIET as a fixed effect. The level of acceptance for significance was 0.05.

3. Results

3.1. Diet Effects on Body Weight and Feed Consumption

Body weight is an indicator of the health status of the animal and optimising the inclusion of by-products involves assuring the proper health status of the goats. The treatments with the highest by-product inclusion showed a lower BW (40.2 and 38.7 kg in AP60 and BB60, respectively), while with the inclusion of 25% and 40%, no differences were observed compared to C (42.9 kg, Table 3). Sampling and interaction Treatment × Sampling also had a significant effect on BW as an increase (p < 0.001) was observed in sampling 2 in treatments with 40% of by-product (+1.9 and +2.4 kg in BB40 and AP40, respectively) and then in sampling 3, they descended again. Diets were offered in a similar amount but the goats in the different treatments showed different consumptions, with group C showing the highest (2.21 kg DM/day), whereas the lowest consumption was observed in groups BB40 (1.38 kg DM/day) and BB60 (1.27 kg DM/day) compared to the other treatments, which showed intermediate consumption (AP25: 1.52, AP40: 1.54, AP60: 1.57, and BB25: 1.65 kg DM/day).

3.2. Milk Yield, Macro-Composition, and SCC

A decrease in milk yield was observed as the percentage of inclusion of by-products increased (Table 3). C, AP25, and AP40 were the treatments with the highest milk daily yield (2.24, 2.15, and 2.14 kg/day, respectively; p < 0.001); BB60 was associated with the lowest yield (1.66 kg/day). A tendency to decrease FCM was also observed as the percentage of inclusion of the by-product in the diet increased. The highest yield was obtained in AP25, even without significant differences compared to C or other AP treatments; BB25 and BB40 did not show significant differences compared to C, AP40, and AP60, whereas BB60 showed the lowest value. The interaction among sampling and treatments was significant as the milk yield and FCM were only significantly reduced in AP25 and AP60 during the experiment, but remained stable in the rest of the treatments.
The diet had no significant effect on LSCC. An increase of + 0.28 Log cells/mL (p < 0.01) was observed in AP25 between samplings 2 and 3, so that sampling and interaction with treatment were significant.
As for the macro-composition of the milk shown in Table 3, the diet only had significant effects on fat (but also affected UDM and TS) and urea (Table 3). BB60 was the one with the highest fat value and T was the lowest. The significant interaction of the treatment with the sampling in fat, UDM, TS, whey protein, and lactose was due to specific increases or decreases in sampling 2 in AP40, which returned to similar values to the previous ones at sampling 3. Both the casein content of milk and NFTS were reduced in all treatments during the experiment (p < 0.001). The ash content increased 0.134 percentage units in AP25 at the end of the experiment, remaining stable in the rest of the treatments. Regarding the milk urea content, AP60 was the treatment that presented the highest level (641 mg/dL; p < 0.01) and BB60 the lowest (542 mg/dL).

3.3. Milk Mineral Content

Milk mineral profile is shown in Table 4. Only significant differences in the Mn concentration due to dietary treatment were observed, although of small magnitude. AP40 was the treatment that presented the highest level of Mn (0.233 mg/kg DM; p < 0.05), followed by BB25 (0.222 mg/kg DM), whereas BB40 was the treatment showing the lowest value (0.185 mg/kg DM). These differences between treatments are not considered biologically relevant because the greatest of them, which was between AP40 and BB40, was only 0.048 mg/kg DM.

3.4. Milk Fatty Acid Profile

Regarding the milk fatty acid profile (Table 5), some significant variations were observed, although they were quantitatively limited. Regarding the content of vaccenic acid (C18:1t11), it was observed that this was higher (p < 0.001) in the AP treatments, without differences compared to C. There was a higher concentration of linoleic acid (C18:2n6) in AP60 (2.53%; p < 0.001); however, it was at C where a higher level of other C18: 2 isomers was observed. An increase (p < 0.001) of α-linolenic acid (C18:3n3) was observed as the level of AP inclusion in the ration was higher and AP60 presented a higher level (0.242%). AP treatments were also those with the highest content (p < 0.01) in rumenic acid (CLA c9, t11), although subsequently no significant differences were found in the sum of isomers of CLA (conjugated linoleic acid) between treatments, except of BB60, of which their content was the smallest of all. Table 6 shows that as the percentage of AP inclusion increased, so did the PUFA content, and AP60 was the treatment with the highest content (p < 0.001) compared to all the BB treatments, without differences from C or the rest of the AP treatments. AP60 presented the highest levels (p < 0.001) of n3 (0.275%) and n6 (2.79%) fatty acids, the latter without differences compared to C or the other AP treatments. It also achieved the lowest (p < 0.001) ratio n6/n3 obtained together with BB60 (10.3 and 12.3, respectively). Regarding the lipid quality indices related to human health (AI and TI), AP40 and AP60 were the ones with the lowest value (p < 0.001) and therefore, were healthier. Regarding the desaturation indices of the myristic (DI14), palmitic (DI16), and stearic (DI18) fatty acids, the differences found between treatments were of small magnitude. BB60 was the one with the highest value in DI14 and DI18 (0.012% and 2.08%, respectively; p < 0.001) and AP60 presented a higher value of DI16 (0.061%; p < 0.01).

3.5. Plasma Metabolic Profile

Regarding the plasma metabolic profile (Table 7), it was observed that the greater the inclusion of BB in the diet, the higher the glucose level (49.5 and 50.0 mg/dL in BB40 and BB60; p < 0.001), although the differences were of small magnitude (42.5 mg/dL in BB25). Regarding urea, C and AP had a higher content (p < 0.001), while the BB treatments obtained lower levels and BB60 showed the lowest (33.2 mg/dL). The level of BHB was higher in treatments that included less by-product, such as AP25, AP40, and BB25, while it was lower in treatments that included more BB (0.299 and 0.304 mmol/L in BB40 and BB60, respectively; p < 0.001). There was significant interaction of treatment with sampling in the three variables due to the different behaviour throughout the experiment between treatments: Glucose increased (p < 0.001) with the progress of the experiment in all treatments except BB60; blood urea was reduced (p < 0.001) at sampling 2 in BB25 and BB40 and increased at sampling 3 in BB25, BB40, and BB60; BHB increased (p < 0.01) at the end of the experiment in BB25, BB60, and AP60, while in C, BB40, AP25, and AP40 remained stable.

4. Discussion

4.1. Diet Effects on Body Weight and Feed Consumption

One of the factors that affects the total volume of the diet and its consumption by livestock is the moisture content, as Jackson and Forbes [38] pointed out. This effect is especially important in the short term as herbivores are able to progressively modify the volume of the rumen to increase the speed of transit of the digesta [39], so in the long term, this effect would have less influence. In this experiment, carried out in the short term, diet C was the one presenting the highest DM content and feed consumption (2.21 kg DM/day). On the contrary, diets BB40 and BB60 contained a greater amount of water and were bulkier and presented less consumption. In addition, diets with silage showed higher concentrations of VFA and other substances resulting from fermentation. The presence of propionic acid in BB60 (4.79 g/kg DM), as well as a higher concentration of ammonia N in both BB40 and BB60, also occurred in treatments with lower consumption due to the depressing effect on feed consumption demonstrated by Baumont [40]. The feed consumption of the BB treatments was superior to those found by Meneses [41] (0.508 kg DM/day) in Murciano-Granadina castrated males, whose ration incorporated 55% of BB silage. All BW values were normal for the Murciano-Granadina breed [42,43]. The greatest reduction in BW was in BB60, as well as the greatest reduction in feed consumption (1.27 kg DM/day and 38.7 kg).

4.2. Milk Yield, Macro-Composition, and SCC

The treatments that presented a higher feed consumption were those that had a higher milk yield. The values obtained are similar to the yield obtained with the equation proposed by León et al. Ref. [44] for the modelling of the Murciano-Granadina lactation curve, which stands at 1.93 kg/day between the fourth and fifth lactation months, which is where the animals used in this experiment were located. The highest percentage of fat in BB60 (4.59%) was probably due to a concentration effect (being the treatment with the lowest yield) and its highest content in acetic acid (37.8 g/kg DM, triple the rest) in the diet, which is an extra-lipogenic nutrient precursor of fat synthesis. Van Knegsel et al. [45] observed similar effects in dairy cows when part of the corn in the diet was replaced by beet pulp. Due to a higher fat concentration in BB60, UDM and TS also reached the highest values in this treatment (8.03% and 12.9%, respectively), exceeding C by almost a percentage point. The urea level of all treatments was found to be within the optimal range for goats recommended by the Interprofessional Dairy Laboratory of Castilla-La Mancha (LILCAM), which is between 500 and 700 mg/L. The differences found in the milk urea content can be explained by the different levels of feed consumption of the treatments. BB60 presented less feed consumption, in particular refusing part of the offered BB, which probably induced lower total protein intake and lower levels of milk urea, as Jimeno et al. [46] noticed.

4.3. Milk Mineral Content

The macromineral values correspond to those found by Mellado and García [47] in goat crossings. The composition of the diet of animals largely determines the concentrations of minerals in milk [48]. As there were no large differences in the content of the different minerals in the diets, no significant differences were subsequently observed in the milk of the different treatments, which is important for the technological aptitude of the milk, given the relevance of Ca and P in the setting and development of the microstructure of cheese [49], the main destination of goat’s milk. Only the Mn had a higher concentration in AP40 (0.233 mg/kg DM), although with such tight differences that they are not biologically relevant.

4.4. Milk Fatty Acid Profile

The milk of animals fed with AP60 had a higher content of n3 fatty acids, which caused a lower n6/n3 ratio, which is positive for the prevention of coronary and cardiovascular diseases [50]. On the other hand, C, AP25, AP40, and AP60, of which their diets had the highest levels of PUFA, were the treatments with milk richest in vaccenic, rumenic, and PUFA, as reported by Collomb et al. [51], who observed differences in the PUFA and vaccenic content in the milk of cows fed with high mountain pastures and in lowland plains because the plants that made up the mountain meadows had a higher concentration of PUFA.
Another factor that could influence the increase of PUFA in AP treatments was the slightly higher content of total polyphenols (TP) in the diet, although lower than that of BB60. However, the lower feed consumption of BB60 could mean that the total TP intake does not reach those of the AP treatments. Several studies have demonstrated the inhibitory action of dietary polyphenols on ruminal biohydrogenation of PUFA, without detrimental effects on milk yield and composition, due to interference with microbial flora [52,53,54,55]. These effects have also been observed in sheep with small amounts in the diet of by-products rich in TP [56,57]. Cappucci et al. Ref. [9] also observed how after increasing the TP content of the diet of Comisana sheep by including different levels of olive by-product, the concentration of linoleic (C18:2n6) and α-linolenic (C18:3n3) in milk was increased.
As a result of a lower milk content of C12:0, C14:0, C16:0, and C18:0, AP40 and AP60 had the lowest levels of AI and TI, so the milk of these animals would be of higher quality in terms of human health [42]. The values obtained from AI in all the treatments of this study are below those found by Molina-Alcaide et al. Ref. [42] in Murciano goats fed with conventional ration supplemented with feed blocks of olive by-products. The desaturation indices obtained in this experiment are similar to those provided by Baldin et al. Ref. [58] in a study in goats that received a dietary CLA supplement.

4.5. Plasma Metabolic Profile

Despite the differences found in the metabolic profile of the different treatments, glucose, urea, and BHB levels remained within the ranges considered optimal for goats [59], except for the urea value in BB60, which was slightly lower. As Friggens et al. [60] observed in goats’ performance, the level of BHB was generally low and particularly in those treatments showing lower feed consumption (BB40 and BB60) because goats, as lactating animals, adapt their milk yield to the level of feed intake, as seen in Table 3. This reduces the metabolic load and allows them to maintain adequate body reserves turnover. Due to the strong relationship between plasma and milk urea content [61], the lower levels of blood urea were found in the same treatments with the lowest values of milk urea.

5. Conclusions

The findings of this study highlighted that a threshold level of AP or BB inclusion in dairy goat diets, without negative effects on milk yield, composition, mineral and fatty acid profile, as well as metabolic status of the animals, would be 40% of the dietary dry matter.
The inclusion of artichoke plant and broccoli by-product silages in high doses (60%) caused lower feed consumption and lower milk yield. Inclusion at 60% of AP and BB increased the milk TS, although not enough to compensate for the reduced yield, resulting in lower FCM in the case of BB60. No differences were found regarding the milk mineral profile. Inclusion of the artichoke plant silage in the animals’ diet improved the milk lipid profile from the point of view of human health (AI, TI) compared to broccoli silage, due to a lower SFA content (C12:0, C14:0, and C16:0) and a higher concentration of PUFA, especially vaccenic acid (C18:1 trans11) and rumenic acid (CLA cis9, trans11), without any differences compared to the control treatment. Regarding sanitary status, the plasma metabolic profile in broccoli treatments reflects that goats ate grains and alfalfa, whereas broccoli was the last ingredient, impairing its consumption, especially at the high concentration (60%). In addition, the diets that included 60% of by-product silages caused a reduction in BW.

Author Contributions

Conceptualisation, G.R. and J.R.D.; Data curation, G.R., A.J.A.-B., and J.R.D.; Methodology, P.M., G.R., A.R., E.S., and J.R.D.; Resources, G.R.; Writing—original draft, P.M.; Writing—review & editing, G.R., A.S.A., C.A.S.-C., E.S., and J.R.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research received funding from the Spanish Ministry of Economy, Industry and Competitiveness and the European Regional Development Fund, grant number AGL2015-64518-R (MINECO/FEDER, UE). Paula Monllor was funded by an FPU grant (Reference number: FPU14/06058) from the Spanish Ministry of Education.

Acknowledgments

Aprovertia S.L., a technology-based company of Miguel Hernández University of Elche, provided the facilities for manufacturing the silages.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of the data; in the writing of the manuscript, or in the decision to publish the results.

References

  1. Guo, M. Goat milk. In Encyclopedia of Food Sciences and Nutrition, 2nd ed.; Caballero, B., Finglas, P., Toldra, F., Eds.; Academic Press: Cambridge, MA, USA, 2003; pp. 2944–2949. [Google Scholar]
  2. Pulina, G.; Milán, M.; Lavín, M.; Theodoridis, A.; Morin, E.; Capote, J.; Thomas, D.; Francesconi, A.; Caja, G. Invited review: Current production trends, farm structures, and economics of the dairy sheep and goat sectors. J. Dairy Sci. 2018, 101, 6715–6729. [Google Scholar] [CrossRef] [Green Version]
  3. Turck, D. Cow’s milk and goat’s milk. World Rev. Nutr. Diet 2013, 108, 56–62. [Google Scholar] [PubMed]
  4. Chen, L.; Li, X.; Li, Z.; Deng, L. Analysis of 17 elements in cow, goat, buffalo, yak, and camel milk by inductively coupled plasma mass spectrometry (ICP-MS). RSC Adv. 2020, 10, 6736–6742. [Google Scholar] [CrossRef]
  5. Djordjevic, J.; Ledina, T.; Baltic, M.Z.; Trbovic, D.; Babic, M.; Bulajic, S. Fatty acid profile of milk. IOP Conf. Ser. Earth Environ. Sci. 2019, 333, 012057. [Google Scholar] [CrossRef]
  6. González-Arrojo, A.; Soldado, A.; Vicente, F.; Fernández Sánchez, M.L.; Sanz-Medel, A.; de la Roza-Delgado, B. Changes on levels of essential trace elements in selenium naturally enriched milk. J. Food Nutr. Res. 2016, 4, 303–308. [Google Scholar]
  7. Halmemies-Beauchet-Filleau, A.; Shingfield, K.; Simpura, I.; Kokkonen, T.J.; Jaakkola, S.; Toivonen, V.; Vanhatalo, A. Effect of incremental amounts of camelina oil on milk fatty acid composition in lactating cows fed diets based on a mixture of grass and red clover silage and concentrates containing camelina expeller. J. Dairy Sci. 2017, 100, 305–324. [Google Scholar] [CrossRef] [Green Version]
  8. Hilali, M.; Rischkowsky, B.; Iniguez, L.; Mayer, H.K.; Schreiner, M. Changes in the milk fatty acid profile of Awassi sheep in response to supplementation with agro-industrial by-products. Small Rumin. Res. 2018, 166, 93–100. [Google Scholar] [CrossRef]
  9. Cappucci, A.; Alves, S.P.; Bessa, R.J.; Buccioni, A.; Mannelli, F.; Pauselli, M.; Viti, C.; Pastorelli, R.; Roscini, V.; Serra, A.; et al. Effect of increasing amounts of olive crude phenolic concentrate in the diet of dairy ewes on rumen liquor and milk fatty acid composition. J. Dairy Sci. 2018, 101, 4992–5005. [Google Scholar] [CrossRef]
  10. Schulz, F.; Westreicher-Kristen, E.; Molkentin, J.; Knappstein, K.; Susenbeth, A. Effect of replacing maize silage with red clover silage in the diet on milk fatty acid composition in cows. J. Dairy Sci. 2018, 101, 7156–7167. [Google Scholar] [CrossRef] [Green Version]
  11. Monllor, P.; Romero, G.; Sendra, E.; Atzori, A.S.; Diaz, J.R. Short-term effect of the inclusion of silage Artichoke by-products in diets of dairy goats on milk quality. Animals 2020, 10, 339. [Google Scholar] [CrossRef] [Green Version]
  12. Caputo, A.R.; Morone, G.; Di Napoli, M.A.; Rufrano, D.; Sabia, E.; Paladino, F.; Sepe, L.; Claps, S. Effect of destoned olive cake on the aromatic profile of cows’ milk and dairy products: Comparison of two techniques for the headspace aroma profile analysis. Ital. J. Agron. 2015, 10, 15. [Google Scholar] [CrossRef]
  13. FAO. Food and Agriculture Organization of the United Nations. Available online: http://www.fao.org/faostat/en/#data/FO (accessed on 4 April 2019).
  14. Hernández, F.; Pulgar, M.A.; Cid, J.M.; Moreno, R.; Ocio, E. Nutritive assessment of artichoke crop residues (Cynara scolymus L): Sun dried leaves and whole plant silage. Arch. Zootec 1992, 41, 257–264. [Google Scholar]
  15. Wernli, C.; Thames, I. Utilization of fodder residue of artichoke (Cynara scolymus L.) as silage. I. Factors affecting its conservation. Av. Prod. Anim. 1989, 14, 79–89. [Google Scholar]
  16. Ros, M.; Pascual, J.A.; Ayuso, M.; Morales, A.B.; Miralles, J.R.; Solera, C. Estrategias Sostenibles para un Manejo Integral de los Residuos y Subproductos Orgánicos de la Industria Agroalimentaria. Proyecto Life+ Agrowaste; CEBAS-CSIC, CTC y AGRUPAL: Murcia, España, 2012. [Google Scholar]
  17. Wiedenhoeft, M.H.; Barton, B.A. Management and environment effects on brassica forage quality. Agron. J. 1907, 86, 227–232. [Google Scholar] [CrossRef]
  18. Shinners, K.J.; Wepner, A.D.; Muck, R.E.; Weimer, P.J. Aerobic and anaerobic storage of single-pass, chopped corn stover. BioEnergy Res. 2010, 4, 61–75. [Google Scholar] [CrossRef]
  19. Meneses, M.; Megías, M.D.; Madrid, J.; Martínez-Teruel, A.; Hernández, F.; Oliva, J. Evaluation of the phytosanitary, fermentative and nutritive characteristics of the silage made from crude artichoke (Cynara scolymus L.) by-product feeding for ruminants. Small Rumin. Res. 2007, 70, 292–296. [Google Scholar] [CrossRef]
  20. Monllor, P.; Muelas, R.; Roca, A.; Sendra, E.; Romero, G.; Díaz, J.R. Nutritive and fermentative evaluation of silages made from plant of artichoke and artichoke and broccoli by-product. In Proceedings of the XLII Nationas and XVIII International Congress of Spanish Society of Sheep and Goat Husbandry (SEOC), Salamanca, Spain, 20–22 September 2017; Spanish Society of Sheep and Goat Husbandry: Sevilla, Spain, 2017; pp. 139–145. [Google Scholar]
  21. Marsico, G.; Ragni, M.; Vicenti, A.; Jambrenghi, A.C.; Tateo, A.; Giannico, F.; Vonghia, G. The quality of meat from lambs and kids reared on feeds based on Artichoke (Cynara Scolymus L.) bracts. Acta Hortic. 2005, 681, 489–494. [Google Scholar] [CrossRef]
  22. Jaramillo, D.; Buffa, M.; Rodríguez, M.; Pérez-Baena, I.; Guamis, B.; Trujillo, A.-J. Effect of the inclusion of artichoke silage in the ration of lactating ewes on the properties of milk and cheese characteristics during ripening. J. Dairy Sci. 2010, 93, 1412–1419. [Google Scholar] [CrossRef] [Green Version]
  23. Salman, F.M.; El-Nomeary, Y.A.A.; Abedo, A.A.; Abd El-Rahman, H.H.; Mohamed, M.I.; Ahmed, S.M. Utilization of artichoke (Cynara scolymus) by-products in sheep feeding. Am.-Eurasian J. Agric. Environ. Sci. 2014, 14, 624–630. [Google Scholar]
  24. Muelas, R.; Monllor, P.; Romero, G.; Sayas-Barberá, E.; Navarro, C.; Diaz, J.R.; Sendra, E. Milk technological properties as affected by including Artichoke by-products silages in the diet of dairy goats. Foods 2017, 6, 112. [Google Scholar] [CrossRef] [Green Version]
  25. Fernández, C.; Sánchez-Séiquer, P.; Navarro, M.J.; Garcés, C. Modeling the voluntary dry matter intake in Murciano-Granadina dairy goats. In Sustainable Grazing, Nutritional Utilization and Quality of Sheep and Goat Products; Molina, A.E., Ben, S.H., Biala, K., Morand-Fehr, P., Eds.; CIHEAM: Zaragoza, Spain, 2005; pp. 395–399. [Google Scholar]
  26. INRA. Alimentation des Bovins, Ovins et Caprins; Jarrige, R., Ed.; INRA: Paris, France, 1988; p. 471. [Google Scholar]
  27. AOAC. Official Methods of Analysis, 16th ed.; Cunniff, P., Ed.; Association of Official Analytical Chemists: Washington, WA, USA, 1999. [Google Scholar]
  28. Van Soest, P.J.; Robertson, J.B.; Lewis, B.A. Methods for dietary neutral detergent fibre and nonstarch polysacacharides in relation to animal nutrition. J. Dairy Sci. 1991, 74, 3583–3597. [Google Scholar] [CrossRef]
  29. Kim, D.; Jeong, S.W.; Lee, C.Y. Antioxidant capacity of phenolic phytochemicals from various cultivars of plums. Food Chem. 2003, 81, 321–326. [Google Scholar] [CrossRef]
  30. Liu, F.-X.; Fu, S.-F.; Bi, X.-F.; Chen, F.; Liao, X.-J.; Hu, X.-S.; Wu, J. Physico-chemical and antioxidant properties of four mango (Mangifera indica L.) cultivars in China. Food Chem. 2013, 138, 396–405. [Google Scholar] [CrossRef] [PubMed]
  31. Menke, K.H.; Steingass, H. Estimation of the energetic feed value obtained from chemical analysis and in vitro gas production using rumen fluid. Anim. Res. 1988, 23, 103–116. [Google Scholar]
  32. Kramer, J.K.G.; Fellner, V.; Dugan, M.E.R.; Sauer, F.D.; Mossoba, M.M.; Yurawecz, M.P. Evaluating acid and base catalysts in the methylation of milk and rumen fatty acids with special emphasis on conjugated dienes and total trans fatty acids. Lipids 1997, 32, 1219–1228. [Google Scholar] [CrossRef]
  33. Gravert, H.O. Dairy Cattle Production; Elsevier Science: New York, NY, USA, 1987; p. 234. [Google Scholar]
  34. Romeu-Nadal, M.; Morera-Pons, S.; Casteltratamiento, A.I.; López-Sabater, M.C. Comparison of two methods for the extraction of fat from human milk. Anal. Chim. Acta 2004, 513, 457–461. [Google Scholar] [CrossRef]
  35. Nudda, A.; McGuire, M.; Battacone, G.; Pulina, G. Seasonal variation in conjugated linoleic acid and vaccenic acid in milk fat of sheep and its transfer to cheese and ricotta. J. Dairy Sci. 2005, 88, 1311–1319. [Google Scholar] [CrossRef] [Green Version]
  36. Ulbricht, T.; Southgate, D. Coronary heart disease: Seven dietary factors. Lancet 1991, 338, 985–992. [Google Scholar] [CrossRef]
  37. Lock, A.; Garnsworthy, P. Seasonal variation in milk conjugated linoleic acid and Δ9-desaturase activity in dairy cows. Livest. Prod. Sci. 2003, 79, 47–59. [Google Scholar] [CrossRef]
  38. Jackson, N.; Forbes, T.J. The voluntary intake by cattle of four silages differing in dry matter content. Anim. Sci. 1970, 12, 591–599. [Google Scholar] [CrossRef]
  39. Schettini, M.A.; Prigge, E.C.; Nestor, E.L. Influence of mass and volume of ruminal contents on voluntary intake and digesta passage of a forage diet in steers. J. Anim. Sci. 1999, 77, 1896–1904. [Google Scholar] [CrossRef] [PubMed]
  40. Baumont, R. Palatabilité et comportement alimentaire chez le ruminant. INRA Prod. Anim. 1996, 9, 349–358. [Google Scholar]
  41. Meneses, M. Evaluación Nutritiva y Fermentativa del Ensilado de dos Subproductos Agroindustriales, Brócoli (Brassica oleracea, L. var. Itálica) y Alcachofa (Cynara Scolymus, L) para su Empleo en la Alimentación Animal. Ph.D. Thesis, University of Murcia, Murcia, Spain, 2002. [Google Scholar]
  42. Molina-Alcaide, E.; Morales-García, E.; Martín-García, A.; Ben Salem, H.; Nefzaoui, A.; Sanz-Sampelayo, M.; Morales-García, Y.E. Effects of partial replacement of concentrate with feed blocks on nutrient utilization, microbial N flow, and milk yield and composition in goats. J. Dairy Sci. 2010, 93, 2076–2087. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Fernández, C.; Pérez-Baena, I.; Marti, J.; Palomares, J.; Jorro-Ripoll, J.; Segarra, J. Use of orange leaves as a replacement for alfalfa in energy and nitrogen partitioning, methane emissions and milk performance of murciano-granadina goats. Anim. Feed. Sci. Technol. 2019, 247, 103–111. [Google Scholar] [CrossRef]
  44. León, J.; Macciotta, N.P.; Gama, L.T.; Barba, C.; Delgado, J. Characterization of the lactation curve in Murciano-Granadina dairy goats. Small Rumin. Res. 2012, 107, 76–84. [Google Scholar] [CrossRef]
  45. Van Knegsel, A.T.; Brand, H.V.D.; Dijkstra, J.; Van Straalen, W.; Heetkamp, M.; Tamminga, S.; Kemp, B. Dietary energy source in dairy cows in early lactation: Energy partitioning and milk composition. J. Dairy Sci. 2007, 90, 1467–1476. [Google Scholar] [CrossRef] [Green Version]
  46. Jimeno, V.; Rebollar, P.G.; Castro, T. Nutrición y alimentación del caprino de leche en sistemas intensivos de explotación. In Proceedings of the Alimentación Práctica del Caprino de Leche en Sistemas Intensivos. XIX Curso de Especialización FEDNA, Madrid, Spain, 23–24 October 2003; pp. 155–178. [Google Scholar]
  47. Mellado, M.; García, J. Effects of abortion and stage of lactation on chemical composition and mineral content of goat milk from mixed-breed goat on rangeland. APCBEE Procedia 2014, 8, 1–5. [Google Scholar] [CrossRef] [Green Version]
  48. Rey-Crespo, F.; Miranda, M.; López-Alonso, M. Essential trace and toxic element concentrations in organic and conventional milk in NW Spain. Food Chem. Toxicol. 2013, 55, 513–518. [Google Scholar] [CrossRef]
  49. Pastorino, A.; Hansen, C.; McMahon, D. Effect of pH on the chemical composition and structure-function relationships of cheddar cheese. J. Dairy Sci. 2003, 86, 2751–2760. [Google Scholar] [CrossRef] [Green Version]
  50. Hu, F.B. Optimal diets for prevention of coronary heart disease. JAMA 2002, 288, 2569–2578. [Google Scholar] [CrossRef]
  51. Collomb, M.; Bisig, W.; Bütikofer, U.; Sieber, R.; Bregy, M.; Etter, L. Fatty acid composition of mountain milk from Switzerland: Comparison of organic and integrated farming systems. Int. Dairy J. 2008, 18, 976–982. [Google Scholar] [CrossRef]
  52. Castro-Carrera, T.; Toral, P.G.; Frutos, P.; McEwan, N.R.; Hervás, G.; Abecia, L.; Pinloche, E.; Girdwood, S.; Belenguer, A. Rumen bacterial community evaluated by 454 pyrosequencing and terminal restriction fragment length polymorphism analyses in dairy sheep fed marine algae. J. Dairy Sci. 2014, 97, 1661–1669. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Buccioni, A.; Pauselli, M.; Viti, C.; Minieri, S.; Pallara, G.; Roscini, V.; Rapaccini, S.; Trabalza-Marinucci, M.; Lupi, P.; Conte, G.; et al. Milk fatty acid composition, rumen microbial population, and animal performances in response to diets rich in linoleic acid supplemented with chestnut or quebracho tannins in dairy ewes. J. Dairy Sci. 2015, 98, 1145–1156. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  54. Costa, M.; Alves, S.P.; Cabo, Â.; Guerreiro, O.; Stilwell, G.; Dentinho, M.T.; Bessa, R.J.B. Modulation ofin vitrorumen biohydrogenation byCistus ladanifertannins compared with other tannin sources. J. Sci. Food Agric. 2016, 97, 629–635. [Google Scholar] [CrossRef] [PubMed]
  55. Correddu, F.; Fancello, F.; Chessa, L.; Atzori, A.; Pulina, G.; Nudda, A. Effects of supplementation with exhausted myrtle berries on rumen function of dairy sheep. Small Rumin. Res. 2019, 170, 51–61. [Google Scholar] [CrossRef]
  56. Nudda, A.; Correddu, F.; Atzori, A.; Marzano, A.; Battacone, G.; Nicolussi, P.; Bonelli, P.; Pulina, G. Whole exhausted berries of Myrtus communis L. supplied to dairy ewes: Effects on milk production traits and blood metabolites. Small Rumin. Res. 2017, 155, 33–38. [Google Scholar] [CrossRef]
  57. Nudda, A.; Buffa, G.; Atzori, A.S.; Cappai, M.G.; Caboni, P.; Fais, G.; Pulina, G. Small amounts of agro-industrial byproducts in dairy ewes diets affects milk production traits and hematological parameters. Anim. Feed. Sci. Technol. 2019, 251, 76–85. [Google Scholar] [CrossRef]
  58. Baldin, M.; Dresch, R.; De Souza, J.; Fernandes, D.; Gama, M.; Harvatine, K.; Oliveira, D. CLA induced milk fat depression reduced dry matter intake and improved energy balance in dairy goats. Small Rumin. Res. 2014, 116, 44–50. [Google Scholar] [CrossRef] [Green Version]
  59. Rivas, J.; Rossini, M.; Colmenares, O.; Salvador, A.; Morantes, M.; Valerio, D. Effect of feeding on the profile metabolic goats in canary in the tropics. In Proceedings of the 4th Simposium of the Latinomerican Asociation in Animal Science, Quevedo, Ecuador, 13–15 November 2014; pp. 125–132. [Google Scholar]
  60. Friggens, N.; Duvaux-Ponter, C.; Etienne, M.; Mary-Huard, T.; Schmidely, P. Characterizing individual differences in animal responses to a nutritional challenge: Toward improved robustness measures. J. Dairy Sci. 2016, 99, 2704–2718. [Google Scholar] [CrossRef]
  61. Bonanno, A.; Di Grigoli, A.; Di Trana, A.; Di Gregorio, P.; Tornambè, G.; Bellina, V.; Claps, S.; Maggio, G.; Todaro, M. Influence of fresh forage-based diets and αS1-casein (CSN1S1) genotype on nutrient intake and productive, metabolic, and hormonal responses in milking goats. J. Dairy Sci. 2013, 96, 2107–2117. [Google Scholar] [CrossRef]
Table
Table 1. Chemical composition (g/kg DM) and fermentation quality (g/kg DM) of silages included in experimental diets.
Table 1. Chemical composition (g/kg DM) and fermentation quality (g/kg DM) of silages included in experimental diets.
ItemBBAP
Chemical Composition
DM (g/kg of FM, as fed)154258
OM821828
CP17478.1
CF214296
NDF430571
ADF326374
ADL63.4108
EE32.134.6
TP6.734.96
VFA and Fermentative Metabolites
Lactate30.817.0
Acetate11735.2
Propionate14.6n.d.
Butyrate3.808.56
Ethanol14.63.25
Ammonia N1.650.149
BB: Broccoli by-product silage; AP: Artichoke plant silage; DM: Dry matter; FM: Fresh matter; OM: Organic matter; CP: Crude protein; CF: Crude fibre; NDF: Neutral detergent fibre; ADF: Acid detergent fibre; ADL: Acid detergent lignin; EE: Ether extract; TP: Total polyphenols; VFA: Volatile fatty acids; n.d.: Not detected.
Table
Table 2. Ingredients of experimental diets and their nutritional value.
Table 2. Ingredients of experimental diets and their nutritional value.
ItemDiets
CAP25AP40AP60BB25BB40BB60
Ingredients (g/100 g DM)
Alfalfa hay38.014.7--13.58.504.60
Oat16.015.013.08.035.026.526.6
Barley9.509.008.004.515.503.721.23
Corn9.088.438.004.355.163.601.19
Dried sugar beet pulp7.367.006.503.534.183.000.960
Sunflower meal3.363.123.001.612.001.330.440
Peas2.502.322.091.201.420.9900.330
Cottonseed2.502.322.091.201.420.9900.330
Soybean meal 44%4.006.0010.012.02.002.001.00
Corn DDGS3.003.002.501.382.001.140.380
Sunflower seeds2.001.742.401.001.070.7400.250
Beans1.251.161.050.6001.000.5000.160
Wheat1.000.7701.000.4000.4700.3300.110
Soy hulls0.4200.3900.3500.2000.2400.1600.050
Silage-25.040.060.025.040.060.0
kg DM offered/day/animal2.242.262.202.302.222.212.20
Chemical Composition
DM (g/kg FM)893554448361438334254
g/kg DM
OM935915901884916904885
CP162160163157162165169
CF195202196237180180183
NDF376391382432359355353
ADF243248239281225226231
ADL56.555.149.555.248.047.046.7
EE41.936.535.130.541.338.534.7
TP3.874.185.425.344.605.426.68
IVDMD715715710665780747757
1ME (Mcal/kg DM)2.372.302.292.192.392.362.29
VFA and Fermentative Metabolites (g/kg DM)
Lactaten.d.14.223.224.533.141.256.0
Acetaten.d.4.916.0411.915.111.037.8
Propionaten.d.n.d.n.d.n.d.2.63n.d.4.79
Butyraten.d.n.d.n.d.n.d.n.d.n.d.n.d.
Ethanoln.d.1.501.801.699.6412.523.2
Ammonia N 0.1660.6280.7411.013.994.267.73
Fatty Acids Profile (g/100 g Total Fatty Acids)
C6:00.0610.1090.4850.3520.0590.0250.498
C12:00.1830.2860.1510.0500.2420.3280.146
C14:00.4400.5020.4130.3570.5420.5390.465
C16:017.218.118.317.319.817.721.2
C16:1 c90.3000.3480.3690.3640.3740.3120.592
C18:03.253.082.933.632.963.342.76
C18:1 c926.425.122.831.330.134.321.9
C18:1 c111.061.111.331.122.002.233.74
C18:2n644.042.040.532.335.529.429.4
C18:3n34.074.796.756.435.798.1813.0
C20:00.4630.7570.8841.190.4930.6790.838
C20:1n90.3230.4080.3000.3360.4640.3860.423
C22:00.4570.5460.5190.9600.3930.7840.640
C24:00.3360.4930.3920.4110.3650.6000.652
SFA23.324.726.426.825.524.629.5
MUFA28.227.626.133.733.037.527.5
PUFA48.748.347.740.041.538.143.2
Mineral Profile
Na (g/kg DM)2.895.837.3412.12.375.285.09
Mg (g/kg DM)2.663.243.053.632.062.522.43
K (g/kg DM)13.514.314.117.817.819.430.1
Ca (g/kg DM)5.9010.811.217.05.628.917.49
P (g/kg DM)2.764.093.693.563.403.614.18
S (g/kg DM)2.893.453.063.783.404.276.58
Se (mg/kg DM)0.1980.1900.1500.2430.1830.1350.167
Zn (mg/kg DM)49.444.241.334.143.642.536.9
Cu (mg/kg DM)6.156.425.836.765.684.675.41
Fe (mg/kg DM)129414287460175161235
Mn (mg/kg DM)42.147.744.254.038.534.635.7
C: Control diet; AP: Diet that includes artichoke plant silage; BB: Diet that includes broccoli by-product silage; DM: Dry matter; FM: Fresh matter; OM: Organic matter; CP: Crude protein; CF: Crude fibre; NDF: Neutral detergent fibre; ADF: Acid detergent fibre; ADL: Acid detergent lignin; EE: Ether extract; TP: Total polyphenols; IVDMD: In vitro dry matter digestibility; ME: Metabolisable energy; VFA: volatile fatty acids; SFA: Saturated fatty acids; MUFA: Monounsaturated fatty acids; PUFA: Polyunsaturated fatty acids, n.d.: Not detected 1[26].
Table
Table 3. Body weight, milk yield, and composition and SCC, according to the effects considered.
Table 3. Body weight, milk yield, and composition and SCC, according to the effects considered.
VariableDietsSignificance
CAP25AP40AP60BB25BB40BB60SEMDietSamplingDiet x Sampling
BW (kg)42.9 a41.6 ab42.2 a40.2 bc41.9 ab41.9 ab38.7 c0.69*********
Milk yield (kg/day)2.24 a2.15 ab2.14 abc1.92 bcd1.90 cde1.76 de1.66 e0.090********
LSCC (Log10 cell/mL)5.535.675.585.685.545.825.680.109n.s****
FCM (3.5%; kg/day)2.31 ab2.42 a2.26 ab2.17 abc2.03 bc2.00 bc1.88 c0.120*****
Fat (%)3.76 b4.25 ab4.06 ab4.29 ab4.02 ab4.25 ab4.58 a0.218**n.s.*
Protein (%)3.393.423.523.393.343.343.420.088n.s.n.s.n.s.
UDM (%)7.15 b7.68 ab7.59 ab7.68 ab7.36 ab7.61 ab8.01 a0.275*n.s.*
True protein (%)3.163.183.273.153.113.113.180.078n.s.n.s.n.s.
Casein (%)2.682.692.762.662.652.652.720.061n.s.***n.s.
Whey protein (%)0.4700.4840.5070.4910.4560.4650.4740.024n.s.*****
Lactose (%)4.254.164.204.164.234.204.180.045n.s.*****
TS (%)12.0 b12.5 ab12.4 ab12.4 ab12.2 ab12.4 ab12.9 a0.28***
NFTS (%)8.758.678.818.638.708.678.750.084n.s.***n.s.
Ash (%)0.6390.6150.6480.6250.6380.6270.6520.024n.s.n.s.*
Milk urea (mg/L)617 ab587 abc591 abc641 a558 bc588 abc542 c23.0**n.s.n.s.
C: Control diet; AP: Diet that includes artichoke plant silage; BB: Diet that includes broccoli by-product silage; 25, 40, and 60 inclusion level of by-product silage on dry matter basis %; SEM: Standard error mean; BW: Body weight; LSCC: Log10 somatic cell count; FCM: Fat corrected milk (3.5%); UDM: Useful dry matter content (fat + protein); TS: Total solids; NFTS: Non-fat total solids; abc: Least square means within a column having different superscripts differ significantly. * p < 0.05; ** p < 0.01; *** p < 0.001.
Table
Table 4. Milk mineral profile according to the effects considered.
Table 4. Milk mineral profile according to the effects considered.
MineralDiets
CAP25AP40AP60BB25BB40BB60SEMSignificance
Na (g/kg DM)2.592.402.232.362.532.412.680.113n.s.
Mg (g/kg DM)0.8880.8370.8350.9320.8840.8130.8530.047n.s.
K (g/kg DM)12.011.511.211.812.110.911.50.51n.s.
Ca (g/kg DM)8.857.568.648.818.077.857.810.495n.s.
P (g/kg DM)6.005.166.376.085.436.056.110.412n.s.
S (g/kg DM) 2.452.292.442.452.352.402.370.107n.s.
Se (mg/kg DM)0.1020.0950.1270.1170.0910.1050.0930.010n.s.
Zn (mg/kg DM)18.621.317.128.325.920.423.52.60n.s.
Cu (mg/kg DM)0.6970.5381.110.3970.3570.3820.4200.367n.s.
Fe (mg/kg DM)2.952.162.262.722.112.222.340.557n.s.
Mn (mg/kg DM)0.203 b0.198 b0.233 a0.201 b0.222 ab0.185 b0.192 b0.010*
C: Control diet; AP: Diet that includes artichoke plant silage; BB: Diet that includes broccoli by-product silage; 25, 40, and 60 inclusion level of by-product silage on dry matter basis %; SEM: Standard error mean. abc: Least square means within a column with different superscripts differ significantly. * p < 0.05.
Table
Table 5. Fatty acid composition (g/100 g total fatty acids) measured in milk according to the effects considered.
Table 5. Fatty acid composition (g/100 g total fatty acids) measured in milk according to the effects considered.
Fatty AcidDiets
CAP25AP40AP60BB25BB40BB60SEMSignificance
C4:02.212.662.532.572.532.622.670.586n.s.
C6:03.053.593.413.513.543.553.610.795n.s.
C7:00.052 ab0.060 ab0.070 ab0.046 b0.073 ab0.071 ab0.077 a0.024*
C8:04.114.574.674.324.644.774.280.981n.s.
C9:00.065 b0.077 ab0.095 a0.088 ab0.102 a0.102 a0.102 a0.023*
C10:013.215.014.714.515.615.615.33.03n.s.
C10:1 c90.0370.0400.0330.0360.0470.0360.0340.017n.s.
C11:00.197 ab0.171 bc0.186 abc0.157 c0.190 ab0.201 a0.193 ab0.022**
C12:03.23 a2.81 bc3.10 abc2.66 c3.11 abc3.31 ab2.93 abc0.274***
C12:1 c90.0320.0240.0350.0300.0390.0370.0240.012n.s.
iso C13:00.017 b0.016 b0.026 ab0.028 a0.027 a0.016 b0.019 ab0.008*
anteiso C13:00.0250.0250.0300.0300.0300.0310.0260.008n.s.
iso C14:00.055 b0.045 b0.060 b0.067 ab0.063 ab0.058 b0.084 a0.019**
C14:07.62 ab7.08 ab6.92 ab6.74 b7.59 ab7.56 ab7.76 a0.568*
iso C15:00.174 abcd0.130 b0.178 abc0.184 a0.163 abcd0.154 bc0.152 bcd0.021***
anteiso C15:00.226 a0.170 c0.208 ab0.223 a0.189 bc0.181 c0.181 c0.021***
C14:1 c90.073 bc0.062 c0.067 bc0.076 abc0.071 bc0.080 ab0.090 a0.011***
C15:00.652 bc0.524 d0.617 c0.753 ab0.675 bc0.717 b0.818 a0.066***
C15:10.070 a0.042 d0.048 cd0.064 ab0.055 bc0.061 ab0.055 bcd0.011***
iso C16:00.176 c0.147 d0.188 bc0.225 a0.178 c0.204 ab0.218 a0.022***
C16:021.5 ab22.3 ab20.4 ab20.5 b22.1 ab22.0 ab23.9 a1.67**
C16:1 t40.039 ab0.003 b0.040 ab0.070 a0.003 b0.024 ab0.048 ab0.049*
C16:1 t50.023 ab0.005 ab0.029 ab0.043 a0.000 b0.007 ab0.042 ab0.036*
C16:1 t6-70.1050.0890.1120.1390.0970.0600.0850.148n.s.
C16:1 t90.1930.1680.1870.1660.1880.1750.1370.114n.s.
C16:1 t100.0280.0020.0200.0130.0300.0070.0120.034n.s.
C16:1 t11-120.0120.0410.0230.0480.0190.0630.0410.037n.s.
C16:1 c70.2030.1820.2050.2040.1910.1780.1760.043n.s.
C16:1 c90.436 c0.449 bc0.491 bc0.542 ab0.482 bc0.475 bc0.617 a0.080**
C16:1 c100.029 ab0.000 b0.031 ab0.047 a0.000 b0.012 ab0.033 ab0.040*
C16:1 c110.0000.0020.0040.0060.0000.0030.0110.009n.s.
iso C17:00.249 ab0.234 ab0.275 a0.223 ab0.207 ab0.184 b0.165 b0.060**
anteiso C17:00.287 a0.218 bc0.263 ab0.293 a0.257 ab0.180 c0.282 a0.049***
C17:00.555 b0.485 b0.516 b0.703 a0.536 b0.541 b0.636 a0.058***
C17:1 c6-70.0400.0460.0500.0490.0410.0560.0340.018n.s.
C17:1 c80.000 b0.002 b0.000 b0.003 b0.002 b0.014 b0.035 a0.012***
C17:1 c90.104 b0.114 b0.121 b0.195 a0.119 b0.159 a0.215 a0.023***
isoC18:00.034 ab0.041 ab0.047 b0.047 ab0.034 b0.057 a0.053 ab0.013*
C18:014.1 a12.5 ab13.2 ab12.2 ab12.7 a11.8 ab9.9 b0.85***
C18:1 t40.068 ab0.085 a0.067 ab0.049 bc0.082 a0.043 c0.045 c0.016***
C18:1 t50.030 ab0.024 b0.031 ab0.033 ab0.038 a0.017 b0.026 ab0.011**
C18:1 t6-80.196 a0.166 abc0.180 ab0.134 d0.146 bcd0.171 abc0.123 cd0.027**
C18:1 t90.269 a0.271 ab0.245 abc0.234 bcd0.233 bcd0.213 abcd0.193 d0.028**
C18:1 t100.276 a0.235 ab0.230 ab0.205 b0.220 ab0.235 ab0.219 b0.047*
C18:1 t111.30 a1.33 a1.35 a1.25 ab0.98 bc0.95 c0.81 c0.169***
C18:1 t120.492 a0.471 a0.460 abc0.396 b0.383 bcd0.377 bcd0.317 d0.049***
C18:1 t13-140.0590.0000.0580.0000.0620.1140.0370.117n.s.
C18:1 c918.0 ab17.6 ab18.2 ab19.0 a16.3 b16.9 ab175 ab1.45*
C18:1 c110.043 ab0.055 ab0.038 ab0.005 b0.045 ab0.155 a0.052 ab0.121*
C18:1 c120.587 a0.565 abc0.581 a0.536 abc0.511 bc0.569 ab0.511c0.047**
C18:1 c130.1240.1160.1120.1150.1150.1190.1120.019n.s.
C18:1 c140.424 a0.395 ab0.375 ab0.326 b0.371 b0.365 b0.329 b0.040**
C18:1 c150.2060.1920.1950.2130.1980.2080.2090.028n.s.
C18:2 c9,t130.294 a0.229 abc0.246 ab0.188 c0.220 bc0.220 abc0.174 abc0.044**
C18:2 t8,c130.098 a0.084 ab0.083 ab0.089 ab0.074 b0.089 ab0.092 ab0.019*
C18:2 t9,120.0000.0000.0070.0570.0000.0000.0080.034n.s.
C18:2 c9,t120.154 a0.117 ab0.112 b0.104 b0.106 b0.107 b0.101 b0.031**
C18:2 t11,c150.011 ab0.004 b0.014 a0.017 a0.013 ab0.010 b0.017 a0.008**
C18:2n62.59 abcd2.40 ab2.42 ab2.53 a2.10 c2.26 bc1.98 bcd0.193***
C20:00.233 d0.267 bc0.280 b0.350 a0.237 cd0.241 cd0.225 d0.029***
C18:3n60.0250.0220.0270.0230.0150.0100.0190.014n.s.
C20:1 c90.012 ab0.010 b0.017 ab0.029 a0.000 b0.007 b0.008 b0.015**
C20:1 c110.0380.0500.0530.0490.0520.0530.0400.018n.s.
C18:3n30.183 b0.145 c0.152 bc0.242 a0.156 bc0.179 bc0.173 bc0.025***
CLA c9,t110.486 bc0.510 abc0.527 ab0.538 ab0.370 bc0.377 c0.344 bc0.064**
CLA t9,c110.044 b0.032 c0.038 bc0.058 a0.030 c0.032 c0.035 bc0.009***
CLA t10,c120.0240.0260.0290.0390.0130.0100.0240.024n.s.
CLA t12,140.0170.0120.0230.0250.0090.0060.0220.017n.s.
∑CLA0.528 a0.550 a0.549 a0.532 a0.529 a0.531 a0.482 b0.019***
C20:2n60.0330.0270.0380.0400.0440.0360.0340.015n.s.
C20:3n90.070 b0.061 b0.075 b0.116 a0.080 b0.060 b0.069 b0.017***
C22:00.0230.0270.0190.0250.0180.0210.0270.015n.s.
C20:3n30.000 b0.004 b0.013 b0.031 a0.000 b0.000 b0.000 b0.012***
C20:4n60.152 a0.126 b0.151 a0.165 a0.158 a0.146 ab0.153 a0.018***
C23:00.021 bc0.019 c0.030 abc0.047 a0.045 a0.029 abc0.038 ab0.015**
C20:4n30.0010.0010.0010.0010.0100.0010.0010.009n.s.
C22:2n60.000 c0.026 b0.001 c0.009 bc0.051 a0.023 b0.057 a0.015***
C24:00.0490.0310.0470.0730.1260.0360.0420.092n.s.
C: Control diet; AP: Diet that includes artichoke plant silage; BB: Diet that includes broccoli by-product silage; 25, 40, and 60 inclusion level of by-product silage on dry matter basis %; SEM: Standard error mean; abc: Least square means within a column having different superscripts differ significantly. * p < 0.05; ** p < 0.01; *** p < 0.001.
Table
Table 6. Grouped fatty acids (g/100 g total fatty acids) and indices related to cardiovascular health and desaturation activity in milk according to the effects considered.
Table 6. Grouped fatty acids (g/100 g total fatty acids) and indices related to cardiovascular health and desaturation activity in milk according to the effects considered.
VariableDiets
CAP25AP40AP60BB25BB40BB60SEMSignificance
SFA72.273.072.270.975.174.273.62.19n.s.
MUFA23.322.723.524.521.121.822.61.90n.s.
PUFA4.11 ab3.86 abc3.87 abc4.24 a3.40 d3.56 cd3.50 bcd0.335***
UFA27.426.627.428.724.525.426.12.21n.s.
SFA/UFA2.642.772.642.503.102.952.850.326n.s.
SCFA22.926.125.724.726.626.925.75.38n.s.
MCFA36.2 b35.6 b34.3 b34.8 b36.5 b36.6 b39.4 a2.79*
LCFA39.8 abc37.4 abc38.7 abc41.6 ab36.4 abc35.4 bc36.0 c2.88**
n30.182 b0.151 b0.164 b0.275 a0.157 b0.178 b0.174 b0.034***
n62.78 a2.55 abc2.60 ab2.79 a2.30 c2.44 bc2.18 bc0.218***
n6/n315.4 abc17.3 ab17.4 a10.3 d14.8 abc13.8 bc12.3 cd2.33***
AI2.11 b2.11 bc1.95 cd1.83 d2.37 a2.28 ab2.31 ab0.127***
TI3.32 b3.30 b3.09 cd2.94 d3.65 a3.39 b3.36 abc0.141***
DI C14:00.010 abc0.009 abc0.010 abc0.011 c0.009 abc0.011 bc0.012 a0.001***
DI C16:00.050 b0.044 b0.055 ab0.061 a0.044 b0.048 b0.050 ab0.009**
DI C18:01.55 bc1.72 bc1.67 b1.80 ab1.54 d1.75 bc2.08 a0.049***
C: Control diet; AP: Diet that includes artichoke plant silage; BB: Diet that includes broccoli by-product silage; 25, 40, and 60 inclusion level of by-product silage on dry matter basis %; SEM: Standard error mean; SFA: Saturated fatty acids; MUFA: Monounsaturated fatty acids; PUFA: Polyunsaturated fatty acids; UFA: Unsaturated fatty acids (MUFA + PUFA); SCFA: Short chain fatty acids (C6:0 a C10:0); MCFA: Medium chain fatty acids (C11:0 a C17:0); LCFA: Long chain fatty acids (C18:0 a C24:0); AI: Atherogenic index; TI: Thrombogenic index; DI: Desaturation index; abc: Least square means within a column having different superscripts differ significantly. * p < 0.05; ** p < 0.01; *** p < 0.001.
Table
Table 7. Plasmatic profile according to the effects considered.
Table 7. Plasmatic profile according to the effects considered.
VariableDietsSignificance
CAP25AP40AP60BB25BB40BB60SEMDietSamplingDiet x Sampling
Glucose (mg/dL)44.6 bc47.7 ab45.0 bc48.3 ab42.5 c49.5 a50.0 a1.52*********
Plasma urea (mg/dL)52.0 a50.7 a50.9 a49.2 a38.8 bc39.8 b33.2 c2.14********
BHB (mmol/L)0.336 bc0.522 a0.424 ab0.376 bc0.421 ab0.299 c0.304 c0.040***n.s.**
C: Control diet; AP: Diet that includes artichoke plant silage; BB: Diet that includes broccoli by-product silage; 25, 40, and 60 inclusion level of by-product silage on dry matter basis %; SEM: Standard error mean; BHB: β-hydroxybutyrate; abc: Least square means within a column having different superscripts differ significantly. ** p < 0.01; *** p < 0.001.

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Monllor, P.; Romero, G.; Atzori, A.S.; Sandoval-Castro, C.A.; Ayala-Burgos, A.J.; Roca, A.; Sendra, E.; Díaz, J.R. Composition, Mineral and Fatty Acid Profiles of Milk from Goats Fed with Different Proportions of Broccoli and Artichoke Plant By-Products. Foods 2020, 9, 700. https://doi.org/10.3390/foods9060700

AMA Style

Monllor P, Romero G, Atzori AS, Sandoval-Castro CA, Ayala-Burgos AJ, Roca A, Sendra E, Díaz JR. Composition, Mineral and Fatty Acid Profiles of Milk from Goats Fed with Different Proportions of Broccoli and Artichoke Plant By-Products. Foods. 2020; 9(6):700. https://doi.org/10.3390/foods9060700

Chicago/Turabian Style

Monllor, Paula, Gema Romero, Alberto S. Atzori, Carlos A. Sandoval-Castro, Armín J. Ayala-Burgos, Amparo Roca, Esther Sendra, and José Ramón Díaz. 2020. "Composition, Mineral and Fatty Acid Profiles of Milk from Goats Fed with Different Proportions of Broccoli and Artichoke Plant By-Products" Foods 9, no. 6: 700. https://doi.org/10.3390/foods9060700

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