Insights Into The Effect of Shelter Modification On Key Biochemical Aspects vis-a-vis the Performance of Sahiwal Zebu Cows Reared in Hot Arid Ambience

doi:10.21203/rs.3.rs-888843/v1

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Insights Into The Effect of Shelter Modification On Key Biochemical Aspects vis-a-vis the Performance of Sahiwal Zebu Cows Reared in Hot Arid Ambience

https://doi.org/10.21203/rs.3.rs-888843/v1

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This study was undertaken to evaluate the effect of shelter modifications in the form of floor alteration and heat stress amelioration aids on the biochemical aspects and productive performance of Sahiwal zebu cows. 24 healthy Sahiwal cows in their second or third parity were randomly assigned to four groups (G1, G2, G3, and G4) having 6 cows each and were studied for duration of 150 days from June to November. G1 acted as control without any shelter modification, while G2 cows were housed in stalls with rubber mat covered floors, G3 cows were provided with cooling fans along with water sprinkling twice a day, and G4 cows were housed in stalls combining rubber mat floors with cooling fans and water sprinkling twice a day. This study revealed a significant (p<0.05) effect of shelter modification on milk yield, though no significant effect on milk composition was found. Among blood biochemical parameters, serum cholesterol and cortisol levels registered a significant (p<0.05) effect of shelter modification. The use of heat amelioration aids with, and without rubber mat floors positively influenced the productive and biochemical aspects of Sahiwal cows. Such strategies can be utilized to reduce stress on animals and help in maintaining their production.

Animal Science

Sahiwal

dairy cows

flooring

shelter

rubber mat

cortisol

milk yield

biochemical

production performance

India is home to an assortment of livestock species, ranging from large bovids like cattle, buffalo, and yaks, to smaller species like goats, sheep, and pigs. The country alone accounts for 37.28 %of global cattle, 21.23 %of global buffalo, 26.40 %of global goat and 12.17 %of global sheep population (FAOSTAT, 2020). This livestock richness is one of the key reasons of the nation emerging as a global giant in milk production. However, the majority of animals are still reared in unorganized set up, which translates into low productivity per animal compared to the developed country counterparts. Livestock rearing still holds the key to livelihood security of a large rural mass, especially in the state like Rajasthan which has got substantial area under the Great Thar desert that massively constraints agriculture (Department of animal husbandry, Rajasthan). The nation is going through a phase of climate change resulting in increased episodes of heat stress in northern India (Shukla 2003), this poses a serious challenge to the sustainability of livestock rearing. Climate change coupled with the ever-increasing demand for animal source food owing to changing food habits warrants significanttransformation in the livestock sector to meet these challenges.

The recent past has seen a shift in the dairy production systems of the country from the traditional extensive set up to a largely industrial set up characterized by intensification. However, the intensification of dairy production systems comes with its own set of challenges. Studies from countries across globe, over the years, have highlighted the issues associated with intensive production, especially with regards to animal comfort and subsequent welfare (Chikwanda and Muchenje 2017; Brscic et al. 2015). The type of intensification and housing systems are defined by the prevailing agroclimatic conditions and availability of construction materials. In Indian set up, mostly tie stalls or loose housing systems are prevalent in dairy production owing to the small herd size. Even in loose housing systems, the resting paddocks and key buildings like milking and feeding areas have largely concrete floor. Concrete floor being hard and abrasive, has been associated with discomfort of cows often predisposing to lameness, and mastitis (Islam et al. 2020; Upadhyay et al. 2015). Both lameness and mastitis are known adversaries of productivity of cows.

The earlier stated facts warrant a closer look at the various dairy production systems prevalent in the country, which will throw crucial insights into the advantages and limitations of different systems. This will help to devise production systems in the form of housing and its aspects best suited to a particular agroclimatic set up. Furthermore, studies delineating the effects of varied flooring and heat stress amelioration strategies is significantly lacking in the animals of hot arid region of Bikaner. The study area falls in the great Thar Desert, which is characterized by wide diurnal fluctuations in ambient temperature, which makes the animals reared in this set up the model candidates for heat stress studies. Taking cognizance of all these facts, the present study investigated the effects of concrete floor and modifications to the floor, with and without heat stress amelioration strategies on the biochemical aspects along with the productive and reproductive parameters of Sahiwal zebu cows reared in hot arid ambience.

1. Experimental design

Twenty-four lactating Sahiwal cows, in their second or third parity, free from any anatomical or pathological conditions were selected from the cattle yard of Livestock research station (LRS), Kodamdesar, Bikaner, India. The cows were randomly assigned to four experimental groups: G1, G2, G3, and G4, with six cows per group, averaging similar cumulative milk yield at the start of the experiment. The G1 group acted as control and reared on concrete floor without any shelter modification, while the rest three groups were assigned to treatments as outlined in Table 1. Blood collection was carried out monthly from every individual of each group for estimation of biochemical parameters, and milk samples were collected fortnightly for analysis of production parameters.

Table 1

Experimental design
Groups	Treatments
G1 (n = 6)	Control, cows reared on floor made of concrete slabs
G2 (n = 6)	Cows reared on concrete floor covered with 25mm thick rubber mats in the covered area
G3 (n = 6)	Cows reared on concrete floor with provision of fans in the covered area and sprinkling of water twice daily at 11.00 AM and 3.00 PM.
G4 (n = 6)	Cows reared on concrete floor covered with 25 mm thick rubber mats with provision of fans in the covered area and sprinkling of water twice daily at 11.00 AM and 3.00 PM.

2. Recording of microclimatic variables inside shed

The meteorological variables, temperature, and relative humidity were recorded twice daily at morning and afternoon time points every fortnight in all four sheds. The THI was calculated from these variables as per the formula:

THI = (1.8 × Tdb + 32) − [(0.55 − 0.0055 × RH) × (1.8 × Tdb − 26)] (NRC, 1971)

Where, Tdb- dry bulb temperature in °C and RH is relative humidity (%).

3. Estimation of production parameters

The milk yield per group was recorded daily and averaged for a fortnight combining yields of all the individuals of every treatment group. The milk samples collected every fortnight during the study period were subjected to estimation of milk fat, protein, lactose, solids not fat (SNF), and total solids, in an automated milk analyser, Foss Milkoscan FT120.

4. Estimation of biochemical parameters

The blood samples collected in sterile vacutainers were kept in slanting position at room temperature for three hours for serum separation, followed by centrifugation at 3000 rpm for 15 minutes. The serum was collected in clean sterile 2 ml Eppendorf tubes, and kept refrigerated at -80°C till analysis. The samples were analysed for serum glucose, cholesterol, blood urea nitrogen (BUN), aspartate amino transferase (AST), and alanine amino transferase (ALT), using Idexx chemistry analyzer machine using vet test kits supplied by Idexx laboratories, as per procedure outlined by the manufacturer. While the serum cortisol level was measured using Bovine COR (Cortisol) ELISA Kit, Life Span Biosciences, following the manufacturer’s protocol.

Prevailing microclimate

The mean THI was found to be 78.81 ± 0.49 and 82.87 ± 0.12, 78.56 ± 0.19 and 82.66 ± 0.19, 76.81 ± 0.17 and 79.23 ± 0.17, and 76.78 ± 0.50 and 79.18 ± 0.11 during morning and afternoon periods for G1, G2, G3, and G4 shed, respectively. THI values were significantly higher (p < 0.05) in G1 and G2 groups as compared to G3 and G4 groups in morning as well as in the afternoon periods.

Production parameters

Data pertaining to the milk yield (Table 2) revealed the overall mean milk yield during the study period to be 5.32 ± 0.65, 5.63 ± 0.89, 6.71 ± 0.73, and 6.92 ± 0.7, in G1, G2, G3, and G4 groups, respectively. The milk yield differed significantly (p < 0.05) between the control and treatment groups G3, and G4, while no significant difference in milk yield was evident between G2 and G1 groups. The G3 and G4 groups maintained significantly higher production throughout the study period, compared to G1. No significant difference was evident in milk fat percentage among the four groups. While the milk lactose percentage was significantly higher in G3 and G4 groups during the last three fortnights compared to G1, though the mean difference in milk lactose during study period was non-significant. The milk protein percentage was significantly higher in G2, G3, and G4 groups only during 150th day, compared to G1. Furthermore, the milk SNF and total solids were maintained at non-significantly higher level in G2, G3, and G4 group.

Table 2

Production parameters of cows in different treatment groups
Parameters	Days	Treatments
Parameters	Days	G-1	G-2	G-3	G-4
Milk Yield	15	6.62 ± 0.85	6.31 ± 0.37	6.43 ± 0.66	7.02 ± 0.42
	30	6.69 ± 0.85	6.43 ± 0.78	8.31^* ±0.73	8.7^* ± 0.56
	45	6.26 ± 0.61	6.44 ± 1.02	7.53^* ± 0.55	7.75^*± 0.63
	60	6.25 ± 0.81	6.56 ± 1.09	7.61^*± 0.66	7.84^*± 0.8
	75	5.61 ± 0.75	6.04 ± 0.98	7.26^* ± 0.69	7.46^* ± 0.86
	90	4.99 ± 0.64	5.37 ± 1.06	6.94^* ± 0.82	7.11^* ± 0.81
	105	4.81 ± 0.65	5.22 ± 1.07	6.72^* ±0.83	6.91^* ± 0.85
	120	4.33 ± 0.72	5.09^*± 1.1	6.23^*± 0.88	6.42^* ± 0.89
	135	4.28 ± 0.58	4.76 ± 1.17	5.45^*± 0.91	5.55^*± 0.92
	150	3.55± 0.48	3.97 ± 1.16	4.54^* ± 0.96	4.67^* ± 0.92
	Mean	*5.32± 0.65**	*5.63 ± 0.89**	*6.71± 0.73**	*6.92± 0.7**
Milk Fat	15	2.77 ± 0.22	2.99 ± 0.6	3.21 ± 0.42	3.24 ± 0.2
	30	2.87 ± 0.21	3.15 ± 0.27	3.15 ± 0.38	3.37 ± 0.2
	45	2.9 ± 0.34	3.01 ± 0.24	3.69 ± 0.43	3.25 ± 0.19
	60	3.11 ± 0.27	3.06 ± 0.2	3.38 ± 0.22	3.57 ± 0.27
	75	3.19 ± 0.34	3.05 ± 0.21	3.56 ± 0.26	3.89 ± 0.35
	90	3.68 ± 0.29	4.04 ± 0.35	3.88 ± 0.36	4.42 ± 0.47
	105	3.88 ± 0.33	4.4 ± 0.32	4.3 ± 0.42	4.56 ± 0.46
	120	4.16 ± 0.36	4.63 ± 0.26	4.5 ± 0.31	4.71 ± 0.52
	135	4.17 ± 0.33	4.47 ± 0.29	4.49 ± 0.31	4.7 ± 0.5
	150	4.1 ± 0.31	4.4 ± 0.29	4.44 ± 0.29	4.7 ± 0.5
	Mean	3.43 ± 0.23	3.64 ± 0.24	3.8 ± 0.29	3.98 ± 0.29
Lactose	15	4.88 ± 0.16	4.85 ± 0.16	4.81 ± 0.23	5.1 ± 0.06
	30	4.88 ± 0.14	4.93 ± 0.09	4.9 ± 0.14	5.03 ± 0.05
	45	4.82 ± 0.19	5.14 ± 0.07	5.08 ± 0.05	5.11 ± 0.06
	60	4.86 ± 0.11	5.02 ± 0.06	4.9 ± 0.11	4.98 ± 0.09
	75	4.82 ± 0.15	5.02 ± 0.05	4.93 ± 0.08	4.92 ± 0.07
	90	4.71 ± 0.11	4.89 ± 0.05	4.82 ± 0.08	4.95 ± 0.06
	105	4.65 ± 0.08	4.8 ± 0.04	4.9^*± 0.07	4.96^*± 0.1
	120	4.68 ± 0.11	4.89 ± 0.05	4.89 ± 0.09	4.85 ± 0.14
	135	4.53 ± 0.09	4.7 ± 0.05	4.95^*± 0.09	4.99^*± 0.11
	150	4.52 ± 0.09	4.73 ± 0.04	5^*±0.08	4.98^*± 0.09
	Mean	4.75 ± 0.1	4.89 ± 0.05	4.9 ± 0.1	4.98 ± 0.07
Milk Protein	15	3.23 ± 0.12	3.17 ± 0.05	3.14 ± 0.13	3.18 ± 0.08
	30	3.25 ± 0.06	3.29 ± 0.05	3.22 ± 0.1	3.44 ± 0.11
	45	3.26 ± 0.05	3.36 ± 0.07	3.29 ± 0.13	3.51 ± 0.07
	60	3.25 ± 0.05	3.37 ± 0.06	3.39 ± 0.11	3.57 ± 0.09
	75	3.29 ± 0.07	3.37^*± 0.06	3.41*± 0.11	3.57^*± 0.09
	90	3.48 ± 0.15	3.76 ± 0.12	3.45 ± 0.11	3.45 ± 0.05
	105	3.51 ± 0.13	3.61 ± 0.11	3.54 ± 0.09	3.5 ± 0.06
	120	3.64 ± 0.17	3.82 ± 0.09	3.66 ± 0.11	3.84 ± 0.12
	135	3.44 ± 0.12	3.63 ± 0.11	3.71 ± 0.07	3.62 ± 0.06
	150	3.51 ± 0.11	3.7^*± 0.08	3.8^*± 0.07	3.58^*± 0.05
	Mean	3.37 ± 0.07	3.42 ± 0.09	3.43 ± 0.1	3.5 ± 0.06
Milk SNF	15	8.67 ± 0.13	8.72 ± 0.13	8.69 ± 0.21	8.74 ± 0.08
	30	8.62 ± 0.12	8.8 ± 0.11	8.74 ± 0.18	8.86 ± 0.08
	45	8.5 ± 0.16	8.74 ± 0.09	8.88*± 0.07	8.99*± 0.08
	60	8.55 ± 0.13	8.8 ± 0.08	8.82 ± 0.1	8.91*± 0.06
	75	8.44 ± 0.28	8.79 ± 0.07	8.77 ± 0.1	8.91 ± 0.09
	90	8.38 ± 0.23	8.84 ± 0.06*	8.93*± 0.07	8.97*± 0.07
	105	8.48 ± 0.24	8.82 ± 0.06	9 ± 0.05	8.95 ± 0.09
	120	8.56 ± 0.22	8.85 ± 0.08	9.02 ± 0.06	8.98 ± 0.11
	135	8.62 ± 0.18	9 ± 0.07	8.95 ± 0.05	8.85 ± 0.07
	150	8.63 ± 0.19	8.85 ± 0.08	8.9 ± 30.07	8.99 ± 0.09
	Mean	8.56 ± 0.14	8.8 ± 0.08	8.87 ± 0.09	8.92 ± 0.07
Total Solids	15	12.75 ± 0.37	12.63 ± 0.17	13.24 ± 0.44	13.23 ± 0.41
	30	12.72 ± 0.35	12.75 ± 0.15	13.18 ± 0.35	13.43 ± 0.42
	45	12.48 ± 0.37	12.75 ± 0.26	13.04 ± 0.29	13.42 ± 0.32
	60	12.49 ± 0.4	12.84 ± 0.27	13.13 ± 0.22	13.43 ± 0.32
	75	12.46 ± 0.43	13.03 ± 0.34	13.12 ± 0.23	13.31 ± 0.32
	90	12.52 ± 0.45	13.2 ± 0.35	13.41 ± .31	13.79^*± 0.3
	105	12.75 ± 0.49	13.46 ± 0.36	13.67 ± 0.32	13.89 ± 0.29
	120	13.14 ± 0.59	13.94 ± 0.45	14 ± 0.26	14.39 ± 0.38
	135	12.95 ± 0.58	13.82 ± 0.44	13.79 ± 0.25	14.17^*± 0.35
	150	12.77 ± 0.56	13.83 ± 0.39	13.71 ± 0.26	14.12^*± 0.39
	Mean	12.72 ± 0.42	13.19 ± 0.28	13.43 ± 0.28	13.71 ± 0.33
Note- mean bearing superscript ‘*’ differ significantly (p < 0.05)

Serum biochemical parameters

The data related to biochemical aspects has been presented in Table 3. The mean ALT and AST levels did not differ significantly among the control and treatment groups during the course of this study. Though the ALT and AST levels were non-significantly lower in the G2, G3, and G4 groups from 90 days onwards compared to control cows. Similarly, there was non-significant difference in glucose levels, with G4 group having highest levels, cows of G2, G3, and G4 groups maintained higher glucose levels compared to control G1 cows. The overall mean serum total protein level (g/dl) was 8.11 ± 0.25 8.07 ± 0.19, 7.89 ± 0.21 and 7.65 ± 0.2 in G1, G2, G3, and G4 cows, respectively, showing non-significant effect of shelter modification. On the other hand, the serum BUN did not register any significant changes in the cows of control and treatment groups during the course of this study. Furthermore, the serum cholesterol (mg/dl) revealed a significant effect of shelter modification with cows having significantly (p < 0.05) higher cholesterol level from 30th day to 150th day, the G3 group also maintained significantly higher cholesterol level during 30th, 60th and 90th day followed by a decline during 120th and 150th day.

Table 3

Blood biochemical parameters of cows in different treatment groups
	(Days)	Group-1 (G-1)	Group-2 G-2)	Group-3 (G-3)	Group-4 (G-4)
ALT	0	55 ± 6.75	60.84 ± 5.75	57.34 ± 5.16	45.34 ± 4.57
	30	51.75 ± 8.51	62.5 ± 5.49	49.5 ± 5.58	45 ± 4.75
	60	51.17 ± 5.72	54.84 ± 4.02	51.67 ± 4.22	47.67 3.82
	90	52.17 ± 4.28	50.84 ± 3.39	50.67 ± 3.32	45.5 ± 2.46
	120	53.5 ± 4.75	49.67 ± 5.7	53 ± 3.36	49.84 ± 5.02
	150	55.5 ± 4.52	43.84 ± 3.42	50.84 ± 3.52	46.5 ± 4.62
	Mean	52.7 ± 5.27	52.34 ± 2.86	51.14 ± 2.94	46.9 ± 3.12
AST	0	73 ± 9.1	81 ± 6.3	92.17 ± 13.44	89.34 ± 11.52
	30	71.84 ± 4.4	90.17 ± 4.93	75.84 ± 10.87	81.67 ± 10.38
	60	76.3 ± 42.95	78.67 ± 3.87	73.5 ± 7.23	75.5 ± 6.52
	90	72.84 ± 3.19	68.17 ± 2.76	71.84 ± 5.28	69.34 ± 3.05
	120	73.5 ± 5.52	61.67 ± 4.18^*	61.17 ± 4.88^*	62.17 ± 3.08^*
	150	76.17 ± 2.86	62.84 ± 2.65^*	64.34 ± 3.74^*	63.67 ± 2.53^*
	Mean	74.14 ± 2.74	72.3 ± 4.41	69.34 ± 5.83	70.47 ± 1.65
Glucose	0	56.89 ± 1.7	57.19 ± 1.61	59.96 ± 1.3	60.72 ± 1.31
	30	56.46 ± 1.32	55.43 ± 0.96	60.47 ± 1.65	61.34 ± 2.05
	60	56.21 ± 1.48	56.36 ± 1.15	60.58 ± 1.72	62.67 ± 2.53
	90	58.69 ± 1.97	57.24 ± 1.06	59.61 ± 1.38	61.6 ± 1.77
	120	58.56 ± 2.02	61.24 ± 1.84	58.77 ± 1.35	60.32 ± 2.22
	150	59.68 ± 1.91	63.87 ± 2.28	60.1 ± 1.24	58.02 ± 2.55
	Mean	57.92 ± 1.62	58.83 ± 1.25	59.91 ± 1.13	60.79 ± 2
Serum total protein	0	8.17 ± 0.26	8.32 ± 0.24	7.99 ± 0.24	8.3 ± 0.18
	30	8.27 ± 0.23	8.25 ± 0.25	8.27 ± 0.4	7.79 ± 0.36
	60	8.15 ± 0.16	8.1 ± 0.28	7.99 ± 0.25	7.8 ± 0.27
	90	8.07 ± 0.29	7.95 ± 0.19	7.8 ± 0.23	7.69 ± 0.15
	120	8 ± 0.33	7.97 ± 0.16	7.74 ± 0.16	7.52 ± 0.15
	150	8.07 ± 0.27	8.09 ± 0.14	7.65 ± 0.19	7.47 ± 0.18
	Mean	8.11 ± 0.25	8.07± 0.19	7.89± 0.21	7.65 ± 0.2
Cholesterol	0	138 ± 9.13	131 ± 9.16	149.67 ± 9.48	141.67 ± 9.14
	30	131.17 ± 9.63	131.5 ± 9.42	152.84^*± 9.99	165.67^*± 10.7
	60	132 ± 9.09	128.84 ± 10.72	159.34^*± 9.46	173.67^*± 10.19
	90	136.5 ± 8.85	131.67 ± 9.57	167.5^*± 9.57	160.5^*± 8.48
	120	137.67 ± 8.66	132.17 ± 9.79	148.5 ± 7.79	166.34^*± 8.83
	150	137.17 ± 8.37	136.5 ± 9.42	149 ± 9.37	166.84^*± 8.9
	Mean	134.9 ± 9.01	132.14 ± 9.89	154.44± 8.58	162.4 ± 9.55
BUN	0	16.5 ± 1.73	19.84 ± 1.89	20.02 ± 1.97	17.17 ± 2.21
	30	18.34 ± 2.26	19.84 ± 0.75	19.84 ± 2.12	20.34 ± 0.84
	60	18.56 ± 2.22	18 ± 0.58	20.17 ± 1.19	18.67 ± 0.71
	90	18.81 ± 1.77	19 ± 0.26	18.47 ± 1.47	17.67 ± 1.05
	120	19.36 ± 1.73	17.5 ± 1.06	16.5 ± 1.02	17.84 ± 1.33
	150	19.67 ± 1.89	17.34 ± 0.76	16.17 ± 0.98	16.17 ± 1.11
	Mean	18.54 ± 1.71	18.34 ± 0.4	18.17 ± 1.22	18.14 ± 0.81
Cortisol	0	25.5 ± 0.24	24.99 ± 0.15	24.54 ± 0.26	24.76 ± 0.09
	30	25.37 ± 0.22	23.71 ± 0.17	21.81 ± 0.21	19.48^*±0.24
	60	25.44 ± 0.19	23.18 ± 0.24	21.17^*±0.43	18.41^*±0.12
	90	25.2 ± 0.15	22.77 ± 0.2	20.59^*±0.41	17.22^*±0.39
	120	25.1 ± 0.19	22.24 ± 0.2	19.31^*±0.35	16.15^*±0.28
	150	24.84 ± 0.26	21.89 ± 0.25	17.97^*±0.47	15.84^*±0.24
	Mean	*25.24±0.19**	*23.13±0.17**	*20.9±0.26**	*18.64±0.11**
Note- mean bearing superscript ‘*’ differ significantly (p < 0.05)

Housing is one of the key determinants of animal comfort, and in turn the productivity and welfare of animals. This study was an attempt to evaluate the effect of housing modifications on the biochemical, productive, and reproductive aspects of milking Sahiwal cows reared in hot arid region of the Great Thar Desert. On expected lines, the mean THI values were close to 80 in all the groups, indicating heat stress on animals. Other researchers have also reported THI in the zone of stress for dairy cows in northern India during summer and hot humid seasons (Bhan et al. 2012). The sheds with heat amelioration devices in the form of fans and water sprinkling however maintained lower THI compared to G1 and G2. This corroborates with the earlier reports have also shown lower temperature concomitant with housing modification (Singh et al. 2014; Kumar et al. 2011; Chanpongsang et al. 2010 and Gaughan et al. 2010) who found significantly. Moreover, use of evaporative cooling in dairy barns lowered the THI by some points (Sinha et al. 2019; Bucklin et al. 2009).

Different housing modifications have been associated with improved performance of animals (Lowe, Lively and Gordon 2019). In our study, the cows housed in shelter provided with heat alleviating measures coupled with and without rubber mat flooring showed significantly better milk yield. Use of fogger with fans significantly improved the milk production of crossbred dairy cows (Sinha et al. 2019). Spraying water on animals reduces the heat load (Tresoldi et al. 2018) and negates the adverse impact of heat stress to some extent. Earlier studies in cows and buffaloes have also shown the animals housed with heat stress alleviation strategies to maintain higher production (Yadav et al. 2016; Ambulkar et al. 2011; Chanpongsang et al. 2010 and Agarwal 2004). However, cows reared on rubber mats alone without any heat alleviation strategies did not improve production, agreeing with the reports of Upadhyaya et al. (2015), Eicher et al. (2013) and Pempek and Botheras, (2009). Furthermore, the composition of milk in cows of different treatment groups did not show a significant difference in means of milk fat, protein, lactose, SNF and total solids during the study improved. However, the treatment groups with heat stress amelioration strategies showed a significant difference with higher milk lactose, and proteins during the last two or three fortnights. These findings are in accordance with the reports of Upadhyay et al. (2015), and Eicher et al. (2013) who noted no difference in milk composition of animals housed with or without rubber mat on floors. Though effect of heat amelioration strategies has been conflicting on milk composition, with Shiao et al. (2011), Smith et al. (2006) and Aggarwal, (2004) reporting no effect of cooling strategies on milk composition of cows and buffaloes, Seerapu et al. (2015) reported significant effect of cooling strategies on milk composition of Mehsana buffaloes. The trend in milk composition of treatment groups in this study indicates use of sustained cooling strategies overtime can bring about improved performance of animals.

Biochemical attributes are one of the crucial indicators of stress in animals. Both ALP and AST are considered as crucial enzymatic markers of heat stress. The mean ALP and AST did not differ significantly among treatment groups, however, both G3 and G4 groups with cooling strategies maintained lower ALT, consistent with earlier report in buffaloes (Vijayakumar et al. 2011). Furthermore, the AST level was significantly lower in all three treatment groups during the last two fortnights. Researchers have reported a significant increase in ALT activity in heat stressed animals (Pandey et al. 2013; Bhan et al. 2012; Abdelatif and Alameen 2012; Sharma and Kataria 2011). While Bhan et al. (2012) and Calmari et al. (2011) reported an increased AST activity in heat stressed animals. Our findings indicate a positive effect of cooling strategies on heat stress amelioration in G3 and G4 cows, which translated into lower ALT and AST activities in cows of these groups. There was significant effect of cooling strategies coupled with or without rubber mat floors on serum cholesterol levels. The higher cholesterol levels can be indicative of higher feed intake in these groups due to decreased heat load. However, no significant difference was evident in serum glucose, BUN, and total proteins among cows of different treatment groups, which concurs with earlier reports (Das et al. 2013; Kumar 2012; Vijayakumar et al. 2011). On the other hand, the serum cortisol level, an important indicator of stress (Indu et al. 2014) was significantly lower in G4 cows compared to other three groups, while control group had highest mean cortisol levels. This indicates lower stress in the animals of animals housed in shed provided with cooling devices, and in animals with rubber mat floor compared to cows housed in shed with concrete floor. Use of foggers coupled with fans resulted in lower blood cortisol levels in crossbred dairy cows (Sinha et al. 2019). Buffalo heifers maintained with heat stress amelioration strategies also had lower cortisol levels (Verma et al. 2016; Vijayakumar et al. 2011), while heat stressed animals maintained higher blood cortisol (Marai and Habeeb 2010; Dikmen et al. 2008).

Housing conditions directly impact the production and welfare of animals. Though the use of rubber mat alone did not reveal any significant effect on the studied parameters, cows reared in shelter with improved floor and cooling strategy had the best performance. This can indicate the burden of heat stress to mask the effect of using rubber mat flooring alone on improving the performance of animals. Overall, the use of heat amelioration strategies coupled with or without improved flooring during the stressful periods of summer and hot humid seasons can help reduce the stress on animals and help to maintain their productive performance.

Funding

The authors are thankful to the research grant received from RAJUVAS, Bikaner for carrying out this study.

Conflicts of interest/Competing interests

The authors have no conflict of interest to declare.

Availability of data and material The data generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Code availability Not applicable

Authors' contributions RA carried out the research work and finalized the manuscript, RM helped in manuscript drafting, and GG helped with data analysis, visualization and manuscript preparation. All authors approved the manuscript.

Ethics approval

All the work was conducted after approval from institutional animal ethics committee.

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Insights Into The Effect of Shelter Modification On Key Biochemical Aspects vis-a-vis the Performance of Sahiwal Zebu Cows Reared in Hot Arid Ambience

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Abstract

Introduction

Materials And Methods

1. Experimental design

2. Recording of microclimatic variables inside shed

3. Estimation of production parameters

4. Estimation of biochemical parameters

Results

Prevailing microclimate

Production parameters

Serum biochemical parameters

Discussion

Conclusion

Declarations

References

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