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Introduction
Livestock systems are key to ameliorating poverty in developing countries (FAO, 2010). Although goat production systems have been put forward as a means for sustainable livelihoods in rural communities around the world (Daskiran et al., 2018) their productivity is generally low due to low quality and availability of feeds (Souza et al., 2017). Improving goat feed can enhance productivity, which is required to improve livelihoods (Makkar, 2016). High quality forages may have a positive impact on milk yield (Cabral et al., 2015) and, if home-grown, improve the efficiency of use of resources (Rao et al., 2015).
Sunflower (Helianthus annus), which is native to Mexico, is rich in lipids (Rodrigues-Gandra et al., 2017) and has been used to increase the fat content of diets. In goats, its use has resulted in increased milk protein content (Sanz-Sampelayo et al., 2007). As an alternative forage source, it may improve diet quality and productivity of dairy goats; which also needs to be assessed in economic terms.
Goat milk composition varies according to diet, mainly in terms of milk fat and protein content which, in turn, affects the characteristics of cheese (Chilliard et al., 2003; Sanz-Sampelayo et al., 2007). Organoleptic characteristics of cheese may be affected by the forage fed to the animal, particularly in fresh cheese (Coulon et al., 2004; Sanz-Sampelayo et al., 2007). Therefore, the objective of this study was to evaluate the effect of substituting corn straw with sunflower hay plus chickpea for dairy goats in terms of yield, chemical composition and sensory acceptability of cheese, as well as profitability.
Materials and methods
Ethical considerations
The experimental procedures with goats and work with the collaborating farmer followed guidelines accepted by Instituto de Ciencias Agropecuarias y Rurales (ICAR) of Universidad Autónoma del Estado de México and were institutionally approved (DICARN-1319).
Location of the study
An on-farm experiment following the participatory livestock technology development approach was undertaken in El Bajío region of central Mexico, located at 20° 12' 51" N and 100° 08' 19" W. El Bajío is the second-highest producer of goat milk in Mexico under semi-intensive and intensive systems.
Animals
A total of 28 dairy goats were randomly divided into two groups of 14 goats each (MZST and SFCP). Goats remained confined for the duration of the experiment in an open pen with a dirt floor, with water and a mineral and vitamin mix freely available at all times.
Diets
The MZST treatment was the conventional ration (as a control treatment) that included 200 g/goat/day of ground lucerne hay plus 400 g/goat/day of a concentrate with 18% CP prepared on the farm from a commercial concentrate with 22% CP (65% fresh weight), ground white corn grain (20% fresh weight), and ground sorghum grain (15% fresh weight). This diet had a roughage base of 600 g/goat/day of ground corn straw to produce 1.2 kg total on a fresh weight basis for the diet offered per goat.
The second treatment substituted corn straw with sunflower-chickpea ground hay (SFCP) at the same 600 g/goat/day as the forage base for this diet. Lucerne hay plus corn straw (MZST) or lucerne hay plus sunflower-chickpea hay (SFCP) were offered twice daily: half the ration in the morning and half in the afternoon. Lucerne hay and the treatment corn stover or sunflower-chickpea hay were provided separately but in the same trough as the lucerne hay. The concentrate was offered at milking.
This experiment was in the line of adaptive research - “an approach that characterizes the needs of farmers and then uses experiments in farmers’ fields to adapt a given technology to local conditions” (Flor et al., 2017), thereby enabling more rapid dissemination and adoption of results (Stroup et al., 1993).
Fresh cheese production
Experimental fresh cheese (white paste and pressed) was made by the collaborating farmer according to the usual practice in the study region. Milk was sieved and pasteurized at 75 °C and cooled to 35 °C when a commercial rennet (CUAMEX) was added. This mixture was left to set for 40 minutes, then cut into 1 cm cubes, and the whey removed. Salt at 20 g/L milk was added, the mass homogenized and placed in rings (500 g capacity), pressed (2.06 x 105 Pa) for 8 h and refrigerated at 4 °C for 24 h.
Chemical composition of cheese
Cheeses were weighed, a 500 g sample of cheese from each treatment was homogenized, and a 200 g subsample was kept at -20 °C until chemical analyses (Queiroga et al., 2013) for moisture, ash, protein, fat, and pH (AOAC, 1990).
Sensory assessment
Cheese acceptability was assessed using a 1-to-5-point score, following Agudelo-López et al., 2019) on a five-point scale test, as follows: 1: I do not like it; 2: I like it a little; 3: I do not like nor dislike; 4: I like it, and 5: I like it very much.
Cheese was cut into 2-cm cubes (approximately 20 g), randomly coded, placed on white plates (Kondyli et al., 2016), and allowed to come to room temperature (18 ± 2 °C). Cheese was assessed in four sessions by 20 panelists (between 45 and 65 years of age) who were familiar with this type of cheese. Panel conformation followed methods described by Mehaia, 2002 and Moneeb et al., 2019.
Cheese assessment followed the four phases described by Castro et al., 2014: visual, mixed (touch and taste), olfactory, and mouth. Wheat bread and water were available for the panelists to cleanse their palates between tastings. The sensory appraisal was conducted in a white room at 21 to 23 °C, with artificial illumination, at noon time, on tables without divisions. The characteristics assessed were appearance, texture, color, flavor, odor, and overall acceptability, following Mehaia (2002).
Analysis of texture profile
The texture profile of cheese was assessed from 2 cm3 cheese cubes using a texturometer (Stable Micro Systems, Godalming, Surrey, UK) with two cyclic compressions in a cylindrical steel probe (40 mm in diameter) at 2.0 mm/sec, with 4.0 mm rupture distance and 0.05 N force. The characteristics assessed were hardness, cohesiveness, adhesiveness (in Newtons), and elasticity (in mm) (Chen et al., 1979).
Statistical analyses
ANOVA (Minitab 14 statistical software) was used to analyze the chemical composition variables of cheese following a completely randomized design with the following model:
Where µ= general mean, t= effect of treatment (i = 1, 2) and e= residual variation. Mean comparisons among treatments were conducted with a Student “t” test.
ANOVA was also used for the sensory appraisal, as described by Mehaia (2002). Differences were significant at p<0.05.
Economic performance
Partial budgets were calculated for the duration of the experiment and used to determine costs and returns, considering only feed costs with results expressed in US dollars as previously reported (Prospero-Bernal et al. 2017). The variables used were the cost of ingredients to calculate total feed cost as well as total milk yield (from Sainz-Ramírez et al., unpublished) and cheese production. Total income and margin over feed costs were also calculated from the selling price.
Results
No statistical differences were found (p=0.215) between treatments in regard to milk fat used for the cheese, being 33.8 g/kg for MZST and 34.5 g/kg for SFCP; although there were differences (p<0.05) between treatments for protein (33.2 g/kg for MZST and 34.5 g/kg for SFCP; Sainz-Ramírez et al., unpublished).
The MZST diet contained 143.69 g crude protein/kg DM and 28.43 g ether extract (lipids)/kg DM, whilst the SFCPT diet contained 211.95 g crude protein/kg DM and 113.72 g ether extract/kg DM (Sainz-Ramírez et al., unpublished).
Cheese yield and chemical composition
Cheese yield (kg/10 kg milk) was significantly (p<0.001) higher for the experimental SFCP ration, with 12% greater yield (Table 1).
Table 1 Fresh cheese yield and chemical composition.
| N | MZST | SFCP | SEM | P-value | |
|---|---|---|---|---|---|
| Cheese yield (kg/10 kg milk) | 30 | 1.25 | 1.40 | 0.07 | 0.001 |
| Moisture (%) | 30 | 55.21 | 54.89 | 0.03 | 0.001 |
| Fat (%) | 30 | 22.20 | 24.63 | 0.23 | 0.051 |
| Protein (%) | 30 | 22.84 | 24.85 | 0.28 | 0.001 |
| Ash (%) | 30 | 27.8 | 28.1 | 0.22 | 0.001 |
| pH | 30 | 5.67 | 5.80 | 0.16 | 0.001 |
MZST: Concentrate + Lucerne hay + Corn straw; SFCP: Concentrate + Lucerne hay + Sunflower-chickpea hay; SEM: Standard error of the mean.
Moisture content was lower in cheese from the SFCP treatment; but protein, ash, and pH were significantly (p<0.05) higher in SFCP than the conventional MZST ration.
Texture profile
Cheese hardness in SFCP was almost 10% higher (p<0.05) than cheese from MZST, with no differences (p>0.05) for elasticity, cohesiveness, and adhesivity (Table 2).
Table 2 Sensory assessment of goat milk cheese.
| Treatments | Hardness (N) | Elasticity (mm) | Cohesiveness (N) | Adhesivity (N) |
|---|---|---|---|---|
| MZST | 19.22 | 0.82 | 0.71 | -0.17 |
| SFCP | 21.04 | 0.84 | 0.74 | -0.19 |
| SEM | 0.34 | 0.03 | 0.03 | 0.04 |
| P- value | 0.001 | 0.165 | 0.238 | 0.149 |
MZST: Concentrate + Lucerne hay + Corn straw; SFCP: Concentrate + Lucerne hay + Sunflower-chickpea hay; SEM: Standard error of the mean. N: Newton.
Sensory appraisal of fresh goat-milk cheese
In terms of texture and odor, cheese from the SFCP had higher (p<0.05) scores than cheese from the MZST, but in terms of flavor and overall acceptance, cheese from MZST had higher (p<0.05) scores than cheese from the SFCP treatment (Table 3).
Table 3 Texture assessment of goat milk cheese.
| N | MZST | SFCP | SEM | P-value | |
|---|---|---|---|---|---|
| Appearance | 4.40 | 4.20 | 0.22 | 0.176 | |
| Texture | 30 | 4.00 | 4.45 | 0.28 | 0.020 |
| Color | 30 | 4.25 | 4.40 | 0.20 | 0.324 |
| Odor | 30 | 2.85 | 3.20 | 0.27 | 0.019 |
| Flavor | 30 | 3.95 | 3.45 | 0.26 | 0.001 |
| Overall acceptability | 30 | 4.25 | 3.60 | 0.28 | 0.001 |
MZST: Concentrate + Lucerne hay + Corn straw; SFCP: Concentrate + Lucerne hay + Sunflower-chickpea hay; SEM: Standard error of the mean.
Economic performance
The feed item with the highest cost was the concentrate supplement, which represented nearly 60% of total feeding costs (Table 4).
Sunflower-chickpea hay was 30% more expensive than corn straw, but once included in rations SFCP ration was only 5% more expensive than the MZST ration since the cost of the base forage is diluted given the high cost of the concentrate supplement.
This was offset by the higher milk yields in the SFCP treatment, which generated 10% higher income from milk sales, representing 20% higher margin over feeding costs.
Table 4 Feeding costs and returns in US$ (unless otherwise stated) for the duration of the experiment.
| Item | MZST | SFCP |
|---|---|---|
| Concentrate supplement | 251.33 | 251.33 |
| Lucerne hay | 122.52 | 122.52 |
| Corn Straw | 51.84 | 0.00 |
| Sunflower-chickpea hay | 0.00 | 74.46 |
| Total feeding cost | 425.69 | 448.31 |
| Milk production (kg) | 407.40 | 449.4 |
| Milk selling price (US$/kg) | 1.59 | 1.59 |
| Income from milk sales | 647.56 | 714.32 |
| Margin over feeding costs | 221.88 | 266.01 |
| Feeding costs/kg milk | 1.04 | 1.00 |
| Income/Feeding costs ratio | 1.52 | 1.59 |
| Cheese production costs | 1,732.98 | 2,141.03 |
| Cheese production (kg) | 50.92 | 62.91 |
| Cheese selling price (US$/kg) | 41.14 | 41.14 |
| Income from cheese sales | 2,095.05 | 2,588.36 |
| Margin over production costs of cheese | 362.08 | 447.33 |
MZST: Concentrate + Lucerne hay + Corn straw; SFCP: Concentrate + Lucerne hay + Sunflower-chickpea hay.
Regarding cheese, the SFCP treatment resulted in 24% higher cheese production, resulting in a similar 24% higher income and margin over feeding costs compared to the conventional MZST ration.
Discussion
Feeding dairy goats with hay obtained from sunflower intercropped with chickpea led to higher animal performance compared to the conventional diet based on corn straw, highlighting the prospects for improving productivity of these systems as put forward by Rao et al. (2015) and Makkar (2016).
Yield and chemical composition of fresh goat cheese
Chemical composition of cheese in terms of fat, protein and ash was similar to reports by Ramírez-Lopez and Vélez-Ruiz (2016), Acevedo et al. (2018), Santos-Lavelle et al. (2018), and Pedregosa-Cabrero et al. (2020) for fresh cheese from goat milk.
The high energy supply provided by the SFCP treatment increases microbial protein synthesis and propionate concentration in the rumen resulting in increased milk yield and protein content as reported by Hills et al. (2015) and Vicente et al. (2017), when including high-energy diets in dairy cows. High protein content in milk allows for greater K-casein hydrolysis, which increases the production of para-K-casein micelles and macro-peptides that, combined with calcium ions, produce a strong union between micelles and increase cheese yield (Guinee et al., 2006).
Fat and moisture content have an inverse relationship since low fat contents result in high water retention capacity (Kondyli et al., 2016). These effects were observed in the present study, despite the lack of maturity of cheese. Milk fat and protein also affect cheese pH since casein micelles increase the buffer capacity of milk (Deshwal et al., 2020); the pH of cheeses made with treatment SFCP was higher.
Texture profile
Texture in cheese is related to hardness and moisture content, which may be affected by milk composition and, eventually, by diet composition. Low moisture content in cheese results in high hardness (Queiroga et al., 2013). In the work herein reported, the SFCP treatment resulted in higher hardness score of cheese. On the other hand, fat content contributes to the development of aromas and flavors and does affect texture and color (Guinee y McSweeney, 2006). The high fat content of the SFCP cheese resulted in significant effects on these parameters. Acevedo et al. (2018) and Pedregosa-Cabrero et al. (2020) mentioned that low fat content in cheese reduces adhesivity, while high elasticity is obtained by high protein content.
Sensory appraisal of cheese
Delgado et al. (2011) mentioned that flavor in cheese depends on the lactose and lactate contents, the extent of lipolysis and proteolysis within the cheese; in cheese from goat milk, flavor is strongly related to the presence of ramified chain fatty acids. The lipolytic system in goat milk is specific and may be altered by dietary fat supplementation, where liberation of certain fatty acids may generate unpleasant flavors in cheese, such as rancid or oxidized flavors that are linked to lipolysis or bitter notes linked to proteolysis, particularly in fresh cheese (Raynal-Ljutovac et al., 2011). This situation was observed in the present study, where the SFCP treatment had four times higher lipid content than the MZST treatment (113.72 vs 28.43 ether extract g/kg DM), which might have affected the variables of sensory attributes assessed in cheese.
Changes in milk fat content may affect lipid oxidation in cheese, which affects acceptability and quality of dairy products (Mlambo and Mapiye, 2015). There was no significant difference (p=0.051) in the cheese fat content between treatments; however, the numerical increase in fat could have resulted in the observed differences in flavor and overall acceptability of cheese from MZST and SFCP.
In terms of pH, cheese from goat milk tends to be alkaline and has high buffering capacity compared to cheese from cow milk, particularly in fresh cheeses (Galina et al., 2007) where pH has a strong effect on cheese flavor, which is more intense as pH approaches 6.0 or higher (Sanz-Ceballos et al., 2009). In the present study, cheese pH values were below 6.0, which are adequate for fresh cheese. However, cheese from SFCP had a lower rating for flavor. Some research (Freitas and Malcata, 2000; Watkinson et al., 2001; Queiroga et al., 2013) has suggested that high acidity in cheese generates changes in cheese proteins and, therefore, in texture, resulting in softer cheese. In the present study, low pH and texture scores were found in MZST cheese.
Economic performance
Use of concentrates in dairy operations substantially increases feeding costs, making farms economically more vulnerable (Hanrahan et al., 2018). Therefore, determining feeding costs helps to identify the vulnerability of farms and influences decision-making (Hemme et al. 2014). In our experiment, the concentrate supplement represented the most expensive item in feeding costs. The slightly higher feeding cost of SFCP treatment was more than offset by the increased production, incomes and margins over feeding costs compared with the conventional MZST ration.
Rao et al. (2015), Makkar (2016), and Shikuku et al. (2016), among other researchers, have mentioned that permanence of farms relies on their capability to develop profitable feeding strategies that enhance productivity, with improved quality forages a key aspect. The experimental SFCP ration based on sunflower-chickpea hay meets that premise, being profitable and viable, as results have shown.
In conclusion, our results show that feeding dairy goats with a SFCP ration based on sunflower hay and chickpea has an effect on cheese composition, modifies its texture profile, and affects consumer acceptance. Cheese produced with SFCP has higher protein and ash content and better texture, smell and taste compared with MZST. Additionally, the SFCP treatment increased income from milk and cheese sale and, therefore, profit margins on feed costs compared to a conventional MZST diet based on corn straw.
