Animal Science

Evaluation of intake, productive performance and milk quality of cows grazing Brachiaria decumbens cv. Basilisk, with two grazing intensities during rainy season

J.J. Reyes^{1  *} 
http://orcid.org/0000-0002-9681-1187

Yordaine Ibarra¹ 

Ana Valeria Enríquez¹ 

Sara Rey¹ 
http://orcid.org/0000-0003-1668-2168

Verena Torres¹ 
http://orcid.org/0000-0002-7451-8748

¹Instituto de Ciencia Animal, C. Central km47½, San José de las Lajas, Mayabeque, Cuba

Abstract

A simulated grazing was developed with Brachiaria decumbens cv. Basilisk, to study the performance of dairy cows during rainy season in two grazing intensities: T1 = 75 and T2 = 150 LAU ha^-1 day^-1. Twenty Siboney crossbred cows were studied, between the second and third lactation, with 480 ± 8 kg of body weight (10 animals treatment^-1), grazing 15 hours a day. InfoStat statistical program, version 12.0, was used for data processing. T2 animals showed lower grass availability (P = 0.0072) and intake decrease (P = 0.0362) (24.35 vs. 17.57 and 12.77 vs. 11.33 kg DM animal^-1 day^-1 for availability and intake of animals of 75 and 150 LAU ha^-1 day^-1). No differences were reported in individual production per cow and dairy components. However, production per area increased (P = 0.0001) by 1.74 times in T2 with respect to T1 (3,279.99 and 5,722.71 kg of milk ha^-1 rainy season^-1, for T1 and T2, respectively). Production cost of a liter of milk increased by 11.8 % in the treatment with the lowest intensity (2.17 vs. 1.96 $ L^-1, for 75 and 150 LAU ha^-1 day^-1). Results indicate that animals from the treatment with 150 LAU ha^-1 day^-1 showed no differences in individual production, although they increased productivity per grazing area by 2,842.72 L, and decreased costs by 0.21 $ produced L^-1.

Keywords: intake; production; dairy quality; balance; cost

Dairy production systems in tropical areas show several alternatives. However, the most profitable is the use of grasses as food base. It is important to highlight that pastoral systems require a correct management due to its influence on morpho-physiological and productive performance (^{Merlo-Maydana et al. 2017}). Seasonal variations can decrease grass availability and quality, which can cause nutritional problems (^{Davis and Matamoros 2016}).

Productivity of grass-based systems has been demonstrated. Nevertheless, most of the research that supports this result is based on systems with high inputs (^{Roca-Fernández 2020}). Current tropical livestock requires exploitation systems with low input levels and ecologically acceptable, with which a better selection of pastures and forages is achieved, as well as breeds with greater capacity to adapt to the challenge posed by climate change in tropical areas (^{Sejian et al. 2015}).

Therefore, the objective of this study was to characterize the performance of Siboney crossbred cows, grazing Brachiaria decumbens cv. Basilisk, with two grazing intensities, during rainy season.

Materials and Methods

The research was developed in dairy A of the Institute of Animal Science (ICA, initials in Spanish) of the Republic of Cuba. This facility is located in San José de Las Lajas municipality, Mayabeque province. It is located at 22° 58’00” North and 82° 09’21” West at 92 m a.s.l. Mean general weather conditions, taken at ICA meteorological station, are characterized by 1,475 mm of annual precipitation and 80.20% of relative humidity.

An amount of 2.66 ha were used, with two years of exploitation, and 61.7% of coverage by Brachiaria decumbens cv. Basilisk, established on red ferralitic soil (^{Hernández et al. 2015}), with flat relief. The area was divided into 20 paddocks, 0.133 ha each.

Twenty Siboney crossbred cows were used in production, 125 ± 12 d of lactation, with a body weight of 486 ± 8.25 kg, between the second and third lactation. They were randomly divided into two groups (10 animals group^-1), taking into account milk production, lactation days and body weight.

The grassland was subjected to two grazing intensities (IP) T1 = 75 and T2 = 150 LAU ha^-1 d^-1. For T1, 13 fixed paddocks were used, with one occupation day paddock^-1, while for T2, seven paddocks were used, with two occupation days paddock^-1. Mean rest days in the period were 25.39 ± 0.28 and 33.28 ± 0.49, for T1 and T2, respectively (^{Reyes et al. 2019}).

The animals grazed during the evening-night hours, from 5:00 p.m. until 3:30 a.m., and in the morning from 6:30 to 11:00 a.m., for an average of 15 hours a day. The rest of the time, they stayed in shadow units, all together. They had water and mineral salts at will. They received 0.4 kg of supplement after the third produced liter, according to initial production, divided into two milkings. They were also offered 0.06 kg of mineral mixture cow^-1 d^-1.

To meet the objectives of this research, the following measurements were made:

• Grass intake. It was determined by the offer minus the rejection. Grass availability was estimated in each rotation, at the entrance and exit of animals, according to the method described by ^{Haydock and Shaw (1975)}. Cutting height was 10 cm from the soil. Between 80 and 100 observations ha^-1 were taken.

• Milk production. It was analyzed in the last five days of each rotation. It was individually measured, at each milking, using the Alfa Laval graduated flask.

• Milk quality. Samples of 50 mL were taken per cow at each weighing of the day during the last five days of each rotation. Percentages of fat, protein, lactose, non-fat solids (NFS) and total solids (TS) were determined by means of a Milkco Scan minus-6 infrared equipment, FOSS brand.

The rotational food balance was carried out using CALRAC program (^{Roche et al. 1999}).

To calculate the cost of a liter of milk (cuban pesos), items of the different expenses incurred in the production process were taken (^{Gavelán 2017}): depreciation of facilities and equipment $978.44, pasture depreciation $661.1/ha, salary $325.00/person/month, supplements $1.63/kg FM, salts $0.35/kg, other 5 % of expenses and 30 % of indirect expenses.

The statistical analysis used for measurements of individual milk production, fat and protein percentage, was the multiplicative model with the effect of lactation curve. In cases where the multiplicative model did not fit, the analysis of covariance was used, in which lactation days were considered as a concomitant variable. For the rest of measurements, analysis of variance was applied, according to a completely randomized design. InfoStat statistical program, version 12.0 (^{Di Rienzo et al. 2012}) was used and ^{Duncan test (1955)} was applied to establish differences between means.

Results and Discussion

Reports of the study, under the same availability conditions (kg DM ha^-1 rotation^-1), indicated that pasture areas with grazing intensity of 150 LAU ha^-1d^-1 increased by 39.9 %, in relation to the intensity of 75 LAU ha^-1d^-1 (^{Reyes et al. 2019}). However, the animals of the treatment with the highest grazing intensity showed less availability (P=0.0072) in 23.7 % and lower grass intake (P=0.0362) in 11.3 %, with respect to those of the treatment with low intensity (table 1).

Table 1 Performance of the availability, animal intake and use of Brachiaria decumbens cv. Basilisk, with two grazing intensities 

Grazing intensity	Grass, kg DM animal^-1 d^-1		Use, %
	Availability	Intake
75 LAU ha^-1 d^-1	24.35	12.77	52.44
150 LAU ha^-1 d^-1	18.57	11.33	61.03
±SE	1.36	0.78	0.93
Sign.	P=0.0072	P=0.0362	P=0.0001

The effect of the increase in grazing intensity led to higher (P = 0.0001) pasture use in 16.4% (table 1). However, reports of ^{Reategui et al. (2019)}, who studied low (1000) and high grazing pressures in Brachiaria decumbens (1,500 kg LW/100 kg DM), concluded that proportion of leaves is proportional to the initial availability per pasture hectare, regardless of pressure grazing, and therefore, proportion of leaves increases intake.

Intake values for 75 and 150 LAU ha^-1 d^-1 of grazing intensity represented 3.04 and 2.72 % of the body weight of cows, respectively. These figures were in the range reported in the references, which is between 2.85 and 3.2 % (^{Bargos 2008} and ^{Mojica-Rodríguez et al. 2017}), and which may vary according to the characteristics of cows, pasture quality and supplementation level of the concentrate (^{Delagarde 2019}).

Mean production of liters of milk per cow showed no contrasts among the studied grazing intensities. Animals of the lowest intensity treatment produced, on average, 8.73 L cow^-1 d^-1, against the 8.38 L cow^-1 d^-1 of the group with the highest intensity (table 2).

Table 2 Performance of the variables and milk production in animals that consume Brachiaria decumbens cv. Basilisk, with two grazing intensities 

Indicators	Grazing intensity (LAU ha^-1 d^-1)		± SE
	75	150
Fat, %	3.79	3.99	0.20
Protein, %	3.27	3.29	0.07
Lactose, %	4.92	4.93	0.11
Non fatty solids, %	9.28	9.37	0.12
Total solids, %	12.90	13.10	0.25
Milk, kg cow^-1 d^-1	8.73	8.38	0.41

The studied dairy components did not differ among treatments, 3.79 and 3.99, 3.27 and 3.29, 4.92 and 4.93, 9.28 and 9.37 and 12.9 and 13.1% for fat, protein, lactose, non fatty solids and total solids in the milk of the animals subjected to 75 and 150 LAU ha^-1 d^-1, respectively. They remained within the normal ranges for the breed (^{FAO 2018}) and were similar to those reported by ^{Urbano et al. (2004)} in grazing systems with pastures of this same species.

The best pastures, with fertilization levels of 250 kg N/ha/year, allowed milk productions in the order of 8 to 11 kg cow^-1 d^-1. With the use of protein banks, with trees in 30 % of the area, productions of 10.1 kg cow^-1 d^-1 have been reported (^{Milera et al. 2014}).

When relating the volume of milk produced by the animals in treatments T1 and T2 per total grazing area used, it was found that grazing favors (P = 0.0001) the treatment of 150 LAU ha^-1 d^-1 in 1.74 times with respect to that of 75 LAU ha^-1, 3,279.99 and 5,722.71 kg of milk ha^-1 rainy season^-1, respectively (figure 1).

Figure 1 Total milk production (kg of milk ha^-1 rainy season^-1) 

These productions per area are lower than those reported by ^{Guiot (2017)}, who referred between 6,300 and 8,800 kg of milk ha^-1 rainy season^-1, with hybrid mulatto I and mulatto II grass, respectively, but with the inclusion of nitrogen fertilizers, at a rate of 150 kg N ha^-1 year^-1.

Nutrient balance (table 3) showed that for the animals of 75 LAU ha^-1 d^-1, the offered diet covered the requirements. However, when grazing intensity was doubled, there were deficiencies in total dry matter and energy intake, because animals decreased their pasture intake (table 1) due to the greater grazing pressure to which they were subjected (offers of 3.82 and 5.01 kg DM 100 kg LW^-1, for 150 and 75 LAU ha^-1 d^-1, respectively). This reduces the possibility of selection and leads to consuming fractions of grass with fewer nutrients.

Table 3 Retrospective feeding balance of cow performance, according to grazing intensity 

	Food	Intake DM, kg	ME, MJ	CP, g	Ca, g	P, g
75 LAU ha^-1 d^-1	Grass	12.77	109.47	1113.16	40.86	22.98
	Supplements	1.97	21.42	315.18	9.92	6.90
	Salts	0.06	0.00	0.00	7.51	6.48
	Diet contribution d^-1	14.8	130.89	1428.34	58.29	36.36
	Requirements d^-1		123.42	1091.00	55.60	34.70
	Covered requirements, %		106.05	130.92	104.84	104.84
150 LAU ha^-1 d^-1	Grass	11.33	95.23	920.99	36.25	20.39
	Supplements	1.85	20.11	296.01	9.31	6.45
	Salts	0.06	0.00	0.00	7.51	6.48
	Diet contribution d^-1	13.24	115.34	1217.00	53.07	33.32
	Requirements d^-1		121.72	1084.84	55.20	34.60
	Covered requirements, %		94.76	112.18	96.14	96.31

The previous may be caused by the best use of pastures (61.03%), performed by the animals subjected to 150 LAU ha^-1 d^-1 (table 1). This was superior to 47.83% of mean grass leaves, the most nutritious fraction in 23.9% more crude protein than stems, under this management (^{Reyes et al. 2019}). Therefore, animals consumed grass fractions of lower quality and digestibility (^{Low 2015}).

Under tropical grazing conditions, poor quality of pastures, low in crude protein and high in fiber, limits productivity of dairy cattle, so it is suggested that legumes, tree and shrub species have demonstrated to be a viable nutritional strategy for animal supplementation (^{Cardona-Iglesias et al. 2016} and ^{Arias-Gamboa et al. 2018}).

Low energy intake of tropical grasses is presented by the low and relatively variable digestibility of structural carbohydrates. However, ruminant animals have the ability to include these carbohydrates and use them in the form of energy for their productive needs, and they can also store excess energy in the form of fat for use during periods of deficit. Therefore, energy supplementation has an impact on better productive performance and milk quality (^{Bargos 2014}).

Regarding the study of expenses per items, during the period and treatment, table 4 shows that expenses of feeding for both grazing intensities represented, against total expenses, 29.5 and 27.4 % for 75 and 150 LAU ha^-1 d^-1, respectively. The cost of produced milk liter increased, approximately, by 11.8% in the lower intensity treatment (2.17 and 1.94 $ L^-1, for 75 and 150 LAU ha^-1 d^-1, respectively).

Table 4 Feasibility analysis of milk production in two grazing intensities 

Items	Grazing intensity, LAU ha^-1 d^-1
	75	150
Depreciation of facility and equipment	978.44	978.44
Depreciation of grass	1123.85	605.15
Supplements	2277.64	2307.21
Salts	12.81	12.81
Feeding expenses	3414.30	2925.17
Wages	3120.00	3120.00
Other expenses	1126.91	1053.54
Indirect expenses	2929.05	2604.69
Total expenses	11568.70	10681.84
Total milk production, kg	5325.30	5514.04
Production cost, $ kg^-1	2.17	1.94
Incomes for selling milk, $	22632.53	23986.07
Cost/benefit relationship	1.96	2.25

In the structure of milk production cost, the expenses of food represented the highest percentages, and were, approximately, 50% of total expenses in these farms. ^{Davis and Matamoros (2016)} reported higher utility per liter produced in grazing without supplementation, since the cost of supplements is between 40 and 45 % of feeding cost (^{Madriz 2017}). In addition, fresh grass is five times cheaper than preserved forages, such as silages, and, above all, it is cheaper than cereal-based concentrates.

Expenses of food purchase have a great influence on milk production costs. To reduce them and increase profitability of production, it is necessary to intensify food production in the unit itself (^{Martín and Rey 1998}).

Cost/benefit relationship, in both cases, is higher than unity. The treatment with the highest grazing intensity exceeds the lowest by 14.8%. However, both present a high cost/benefit relationship for the dairy sector: 1.96 vs. 2.25, for 75 and 150 LAU ha^-1 d^-1, respectively. This responds to the fact that only the rainy season was analyzed, moment in which feeding expenses are lower, because animals depend on grass.

Good quality grass-based feeding allows feeding costs to be managed between 42 and 60 % of gross income. There is an inversely proportional relationship between grass quality and supplementation cost. That is, the higher the quality of pasture, the lower the supplementation costs, thus reducing total feeding costs (^{Davis and Matamoros 2016}).

^{Salado (2012)} reported that milk yield of cows has a marked influence on production costs. ^{Martín and Rey (1998)}, when studying 16 production technologies, showed that as animal productivity increased, production costs decreased, increased labor productivity and increased profitability were manifested.

Results of this study indicate that animals subjected to the treatment of 75 LAU ha^-1 d^-1 had greater grass availability and had better intake. However, its use was lower. There were no differences in individual productions and in milk quality. However, per grazing area used, it increased 1.74 times with 150 LAU ha^-1 d^-1, compared to low intensity. Production costs of a liter of milk were between 2.17 and 1.94 $ L^-1, for 75 and 150 LAU ha^-1 d^-1, respectively.

Acknowledgements

The authors would like to thank the workers of dairy A of the Institute of Animal Science for the provided support, as well as to the technical staff of Biomathematics group of this institution.

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Received: October 04, 2018; Accepted: June 29, 2021

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Conflict of interest: The authors declare that there are no conflicts of interests among them

Author´s contribution: J.J. Reyes: Original idea, experimental design, data analysis, writing the manuscript. Yordaine Ibarra: Experimental design, data analysis, writing the manuscript. Ana V. Enríquez: Conducting the experiment data analysis, writing the manuscript. Sara Rey: Economical analysis, experimental design, writing the manuscript