A meta-analytical evaluation of the effects of high-salt water intake on beef cattle

Abstract

Adequate drinking water is essential to maintain acceptable production levels in beef cattle operations. In the context of global climate change, the water scarcity forecasted for the future is a growing concern and it would determine an increase in the use of poorer quality water by the agricultural sector in many parts of the world. However, consumption of high-salt water by cattle has consequences often overlooked. A meta-analysis was carried out to assess the impact of utilizing high-salt water on dry matter (DMI) and water intake (WI), and performance in beef cattle. The dataset was collected from 25 studies, which were conducted between 1960 and 2020. Within the dataset, the water quality was divided into three categories according to the ratio of sulfates (SO4) or sodium chloride (NaCl) to total dissolved solids (TDS): 1) TDS = all studies included (average SO4:TDS = 0.4); 2) NaCl = considered studies in which water salinity was dominated by NaCl (average SO4:TDS = 0.1); and 3) SO₄ = considered studies in which water salinity was dominated by SO₄ (average SO₄:TDS = 0.8). Results showed that DMI and WI were negatively affected by high-salt water consumption, although the magnitude of the effect is dependent on the type of salt dissolved in the water. There was a quadratic effect (P < 0.01) for the WI vs. TDS, WI vs. NaCl, DMI vs. TDS, and DMI vs. NaCl, and a linear effect (P < 0.01) for WI vs. SO₄ and WI vs. SO₄. Average daily gain (ADG) and feed efficiency (FE) were quadratically (P < 0.01) affected by high-salt water, respectively. This study revealed significant negative effects of high-salt water drinking on beef cattle WI, DMI, and performance. However, the negative effects are exacerbated when cattle drink high-sulfate water when compared with high-chloride water. To the best of our knowledge, this is the first approach to evaluate animal response to high-salt water consumption and could be included in the development of future beef cattle models to account for the impact of water quality on intake and performance. In addition, this meta-analysis highlights the need for research on management strategies to mitigate the negative effects of high-salt water in cattle.

Introduction

It is predicted that in the coming years the world population will increase significantly (FAO, 2011), leading to an increase in food demand of nearly 70% over the next 40 yr (Molden et al., 2007). To sustain this growth, the finite natural resources (water and land) that support primary food production are going to be under increasing pressure. In this scenario, the agricultural sector must face the challenge of increasing food production with resources that are increasingly scarce and vulnerable to the processes of degradation and climate change (Behnassi et al., 2014; Jiménez Cisneros et al., 2014).

Ruminants play a vital role in meeting the demand for food, due to their ability to transform resources of low nutritional value (e.g., forage and agroindustrial byproducts) into animal protein of high biological value for humans. However, even though livestock products provide a third of the protein consumed around the world, it is at the cost of using a third of the water that agriculture uses worldwide (Herrero et al., 2009).

In the future, animal production sustainability will depend to a large extent on the efficient administration of water resources due to global climate change increases water scarcity in quantity and quality (Legesse et al., 2017). Consequently, with an increase in the demand for animal products, improving the water productivity for livestock use is crucial (Descheemaeker et al., 2010).

After oxygen, water is considered the most important nutrient for the growth, digestion, metabolism, lactation, and reproduction of ruminants (NASEM, 2016). In mammals, about 99% of all the body’s molecules are composed of water (Macfarlane and Howard, 1972). Since food and water consumption are directly related (Utley et al., 1970; Bond et al., 1975), adequate supply of good quality water is essential to avoid detrimental effects on animal health and productivity (Meyer et al., 2004; Kume et al., 2010). However, the water scarcity forecasted for the future would determine an increase in the use of low-quality water (e.g., high-salt water) for livestock production.

Water quality is a general term used to describe the physical, bacteriological, and chemical properties that determine the aptitude of a drinking water source for a given purpose. In the case of water intended for animal consumption, excess salts (mainly chlorides and sulfates [SO₄]) often limit animal production in different parts of the world. At present, the effort directed to the development of basic research for the generation of knowledge on ways and mechanisms to allow a more efficient use of high salt water is scarce, possibly due to the fact that it has traditionally been considered a resource of little value, easily available and renewable (Brew et al., 2011; NASEM, 2016).

In the context of the background described, the objective of this review was to conduct a meta-analysis of the relationships among types and increasing level of dissolved salts in drinking water and voluntary feed and water intake as well as animal performance in beef cattle. To the best of our knowledge, this study represents the first attempt to review and generalize the effects of high-salt water on intake and performance in beef cattle by a meta-analytical evaluation of current published research.

Materials and Methods

Data collection

We conducted a systematic scientific literature search to collect a dataset for evaluating the effects of high-salt water consumption on dry matter intake (DMI), water intake (WI), average daily gain (ADG), and feed efficiency (FE) in beef cattle. The search was limited to in vivo studies with cattle. The studies were identified using electronic research databases of published literature (Scopus, Google Scholar, and Science Direct). Examples of keywords used in combination were “cattle,” “ruminant,” “steer,” “cow,” “saline water,” “salt water,” “sulfate,” “sulfur,” “sodium chloride,” “total dissolved solid,” “intake,” “performance,” and “gain.” The criteria for each study to be incorporated in the dataset were that at least one of the variables concerned was reported along with a detailed description of animal, diet formulation, water quality, and statistical design. When it was not reported, composition of diet ingredients was estimated from NASEM (2016). A total of 25 studies published from 1960 to 2020 were selected for this meta-analysis (Supplementary Appendix). Details of the specific studies are presented in Table 1.

Table 1.

General review of the studies used in the meta-analysis to evaluate the effects of high-salt water in the performance of beef cattle

Study	Country	Experimental design	Diet composition	Forage level in diet, %	Water Source1	Water Quality, g/L2	Category	Breed	Initial BW3, kg
Weeth et al., 1960	USA	Change—Over	Chopped alfalfa hay	100	A	0.1 to 20.0	Heifer	Hereford	218
Weeth and Haverland, 1961	USA	Change—Over	Chopped alfalfa hay	100	A	12.6 to 17.6	Heifer	Hereford	185
Weeth and Lesperance, 1965	USA	Change—Over	Grass hay	100	A	0.1 to 10.0	Heifer	Hereford	232
Weeth et al., 1968	USA	Latin square	Grass hay	100	A	0.2 to 6.7	Heifer	Hereford	220 to 253
Weeth and Hunter, 1971	USA	Latin square	Mixed grass hay	100	A	0.1 to 6.0	Heifer	Hereford	256
Weeth and Capps, 1972	USA	Latin square	Mixed grass hay	100	A	0.1 to 2.8	Heifer	Hereford	240
Digesti and Weeth, 1976	USA	Split-plot	Grass hay, protein pellet	86	A	0.4 to 2.8	Heifer	Hereford × Angus	165
Dixon and Milligan, 1983	Canada	Latin square	Mature grass hay	100	A	1.5 to 10.0	Steer	Charolais crossbred	309 to 343
Saul and Flinn, 1985	Australia	Completely ranzomized	Pasture hay	100	A	0.2 to 11.0	Heifer	Hereford	223
Ray, 1989	USA	Completely ranzomized	Ground alfalfa hay, dry-rolled wheat, molasses	50 to 100	A	1.3 to 6.0	Steer	Crossbred	170
Katting et al., 1992	USA	Split plot	Alfalfa hay, mature grass hay	100	A	0.4 to 2.3	Steer	Holstein	234
Sager and Casagrande, 1998	Argentina	Completely ranzomized	Alfalfa hay, grass hay	100	N	1.6 to 5.5	Calf	Angus	106
Loneragan et al., 2001	USA	Randomized block	Steam-flaked corn, alfalfa haylage, wheat midds, corn silage	17	N	0.1 to 2.0	Steer	Crossbred	304
Patterson et al., 2002	USA	Randomized block	Grass hay, wheat middlings	53	N	1 to 6.2	Steer	Crossbred	317
Patterson et al., 2003	USA	Randomized block	Grass hay, wheat middlings	55	N	1.2 to 7.3	Steer	Crossbred	290
Zimmerman, 2003	Canada	Latin square	Orchardgrass hay	100	A	0 to 2.9	Heifer	Angus	372
Ward and Patterson, 2004	USA	Randomized block	Grass hay, wheat middlings	55	A	0.4 to 3.8	Steer	Crossbred	334
Johnson et al., 2004	USA	Randomized block	Warm-season shortgrasses, cool-season midgrasses	100	N	1.0 to 7.3	Steer	Crossbred	285
Grout et al., 2006	Canada	Latin square	Orchardgrass hay	100	A	1.8 to 4.8	Heifer	Angus	345
Cammack et al., 2010	USA	Randomized block	Chopped crested wheatgrass, wheat middlings pellet	50	A	0.6 to 3.6	Steer	Crossbred	318
Sexson et al., 2010	USA	Completely ranzomized	Corn silage, wheat silage, steam flaked corn, alfalfa hay	10	N	0.8 to 2.5	Steer	Crossbred	339
Visscher et al., 2013	Germany	Latin square	Hay cobs, hay, barley, soybean meal	70	A	0.1 to 10.0	Bull	Holstein-Friesian	219
López et al., 2014	Argentina	Change—Over	Tropical grass hay, soybean meal	75 to 100	A	0.8 to 6.5	Steer	Braford crossbred	375
Alves et al., 2017	Brazil	Completely randomized	Buffel grass hay, soybean meal, ground maize	50	A	0.6 to 8.3	Heifer	Red Sindhi	200
Penner et al., 2020	Canada	Randomized block	Barley silage, barley grain, wheat screening pellet, pea straw	63	A	0.8 to 5.6	Heifer	Hereford crossbred	445

¹A, water source artificially prepared by adding salt (NaCl, MgCl₂, CaCl₂, Na₂SO_4, K₂SO_4, MgSO₄) to tap water; N, natural water (ground, well or dam) source.

²TDS, total dissolved solids.

³BW, body weight.

There was a wide range of management, season, cattle characteristics (breed, body weight [BW], and sex), diet formulation, and water quality used among the studies within the dataset. However, only water quality was considered for the meta-analysis because of the reduced numbers of treatments for any other variable of classification. The number of means used in the meta-analysis was not the same for each response variable because not all studies reported all variables (Table 2). Within the dataset, the water quality was divided into three categories according to the ratio of SO₄ or sodium chloride (NaCl) to total dissolved solids (TDS): 1) TDS = all studies included (average SO₄:TDS = 0.4); 2) NaCl = considered studies in which water salinity was predominantly dominated by NaCl (average SO₄:TDS = 0.1); and 3) SO₄ = considered studies in which water salinity was predominantly dominated by SO₄ (average SO₄:TDS = 0.8).

Table 2.

Summary statistics of dry matter (DMI) and water (WI) intake, average daily gain (ADG), and feed efficiency (FE) data used in the meta-analysis to evaluate the effects of high-salt water in the performance of beef cattle

Item1	Mean	SD2	Minimum	Maximum	n 3
DMI, g/kg BW0,75	97.4	27.1	30.4	148.3	83
TDS	4.3	4.2	0.1	20.1
SO4:TDS	0.4	0.4	0.0	1.0
Animal BW, kg	261.4	85.1	106.0	494.0
DMI, g/kg BW0,75	92.0	24.8	30.4	145.7	47
NaCl	5.4	5.0	0.1	20.1
SO4:TDS	0.1	0.1	0.0	0.4
Animal BW, kg	252.4	87.7	165.0	494.0
DMI, g/kg BW0,75	104.5	28.6	33.0	148.3	36
SO4	3.0	2.2	0.1	7.3
SO4:TDS	0.7	0.2	0.4	1.0
Animal BW, kg	290.0	96.2	106.0	494.0
WI, g/kg BW0,75	465.7	153.7	156.0	904.6	105
TDS	4.1	4.0	0.0	20.1
SO4:TDS	0.4	0.4	0.0	1.0
Animal BW, kg	271.1	81.8	106.0	494.0
WI, g/kg BW0,75	480.8	165.9	171.8	904.6	53
NaCl	5.2	5.0	0.0	20.1
SO4:TDS	0.1	0.1	0.0	0.4
Animal BW, kg	263.8	83.6	165.0	494.0
WI, g/kg BW0,75	450.3	140.0	156.0	722.9	52
SO4	3.0	2.1	0.0	7.3
SO4:TDS	0.8	50.2	0.4	1.0
Animal BW, kg	298.3	89.3	106.0	494.0
ADG, g/kg BW0,75	10.1	11.1	−43.0	29.7	59
TDS	4.8	4.6	0.1	20.1
SO4:TDS	0.4	0.4	0.0	1.0
Animal BW, kg	267.2	80.8	165.0	494.0
FE, kg gain/kg DMI	0.1	0.2	−1.4	0.2	56
TDS	4.3	4.1	0.1	20.1
SO4:TDS	0.5	0.4	0.0	1.0
Animal BW, kg	270.3	82.4	165.0	494.0

¹TDS, total dissolved solids; SO₄:TDS, ratio of sulfates to total dissolved solids; BW, body weight.

²SD, standard deviation.

³n, number of data points included.

Prior to the analysis, feed and water intake data reported in the studies as kg/d, L/d, and % of BW were converted to be expressed as a common unit (g/kg BW^0.75). The concentration of salt in the water was expressed as g/L of TDS. In some studies, FE (kg gain/ kg DMI) were calculated as the ratio between BW gain and dry matter intake.

Statistical analyses

All data were analyzed by the Mixed procedure of SAS (SAS Inst. Inc., Cary, NC), using the meta-analytical techniques recommended by St-Pierre (2001) and Sauvant et al. (2008). The following full model was used for the analysis:

$${\displaystyle \begin{array}{l}{\displaystyle {\mathrm{y}}_{\mathrm{i}\mathrm{j}}={\mathrm{B}}_0+{\mathrm{B}}_1\mathrm{T}\mathrm{D}{\mathrm{S}}_{\mathrm{i}\mathrm{j}}+{\mathrm{B}}_2\mathrm{T}\mathrm{D}{{\mathrm{S}}^2}_{\mathrm{i}\mathrm{j}}+{\beta }_{\mathrm{i}}\mathrm{T}\mathrm{D}{\mathrm{S}}_{\mathrm{i}\mathrm{j}}+{\mathrm{s}}_{\mathrm{i}}+{\epsilon }_{\mathrm{i}\mathrm{j}}}\end{array}}$$

where y_ij is the response variable for the jth observation of the ith study, B ₀ is the overall intercept, B ₁ is the overall regression coefficient of Y on TDS, B ₂ is the overall quadratic regression coefficient of Y on TDS, TDS_ij is the total dissolved solids in water for the jth observation of the ith study, β _i is the random effect of study on the regression coefficient of Y on TDS, s_i is the random effect of the ith study, and ε _ij is the residual error. Thus, B ₀ + B ₁TDS_ij + B ₂TDS²_ij is the fixed effect part of the model, and β _iTDS_ij + s_i + ε _ij is the random effect part of the model. The variance–covariance matrix of the random factors was declared as variance components.

For all statistical analyses, the number of replicates (animals or pens) in each experiment was used to weight the means (Jayanegara et al., 2012). The WEIGHT statement of PROC MIXED was used to include the weighting variable in the model.

To determine the best fit for the relationship between each dependent variable and TDS, SO₄ or NaCl concentration, the bias-corrected Akaike’s information (AICC) and Bayesian’s information criteria (BIC) were used. The equations with the smallest AICC and BIC were chosen to describe the relationship between the variables. Another criterion used to select models was the significance of the parameters. For graphical representation of meta-analysis results, observations were adjusted to take into account the random effect of study before being plotted, as suggested by St-Pierre (2001).

Results and Discussion

A description of the dataset utilized in the analysis is shown in Table 2. Water quality reported covered a broad range of TDS, well above the maximum thresholds recommended (Table 3). Figure 1 shows the frequency distribution of TDS and SO₄ contents for the meta-analytical dataset. Although a high frequency of observations for TDS and SO₄ contents is in the range of 0.5 to 6 and 0 to 1, respectively, the distribution of the levels suggests that the dataset used allows representing the potential response on intake and animal performance to high levels of salt in water commonly found in beef cattle systems.

Table 3.

Maximum recommended values for total dissolved solids (TDS), sodium chloride (NaCl), and sulfates (SO₄) in beef cattle drinking water

Item	g/L	Comments
TDS	7.0	These waters should not be fed to cattle. Health problems and/or poor production will results
	> 10.0	Unsafe. Should not be used as a source of water
NaCl	7.0–10.0	Water intake increased. Reduced animal growth
	20.0	Toxic. Severe anorexia, weight loss, lethargy and physical collapse
SO4	2.5	Cattle can tolerate these water for short periods. Performance of grazing cattle may not be affected
	> 4.0	Unsafe. Not recommended for use under any conditions

¹Adapted from NRC (2005) and NASEM (2016).

Figure 1.

Frequency plot shows the distribution of (a) total dissolved solids (TDS) and (b) sulfates (SO₄) contents in water in the dataset. The dashed lines indicate the maximum safe concentration of TDS and SO₄ for all classes of beef cattle (NASEM, 2016). n = number of data points included; SD = standard deviation.

The chemical characteristics of the diets are shown in Table 4. There were large differences between minimum and maximum values of neutral detergent fiber (NDF) and crude protein (CP) concentration, which is explained by the forage-based diets used in most studies. However, only two studies reported a level of forage inclusion below 50% of the total diet DM.

Table 4.

Summary statistics of dietary composition for dry matter intake (DMI), water intake (WI), average daily gain (ADG), and feed efficiency (FE) data used in the meta-analysis to evaluate the effects of high-salt water in the performance of beef cattle

Item1	Mean	SD2	Minimum	Maximum	n 3
DMI					26
DM, %	87.59	9.6	48.90	94.90
CP, %	12.92	2.9	7.00	17.00
NDF, %	54.26	20.6	13.97	81.80
WI					32
DM, %	85.95	14.7	25.00	96.20
CP, %	12.73	2.8	7.00	17.00
NDF, %	55.46	18.8	13.97	81.80
ADG					16
DM, %	82.01	19.0	25.00	94.90
CP, %	13.85	1.9	10.58	17.00
NDF, %	45.30	19.2	13.97	67.60
FE					16
DM, %	86.07	11.4	48.90	94.90
CP, %	13.74	2.0	10.58	17.00
NDF, %	44.38	19.0	13.97	67.60

¹DM, dry matter; CP, crude protein; NDF, neutral detergent fiber.

²SD, standard deviation.

³n, number of data points included.

Figures 2 and 3 show the adjusted observations and Table 5 shows the equations for evaluating the effects of high-salt water consumption on the analyzed response variables. All equations were selected based on their goodness of fit and showed a quadratic effect (P < 0.01), with the exception of DMI vs. SO₄, WI vs. SO₄, which showed a significant linear effect (P < 0.01).

Figure 2.

Influence of high-salt water on dry matter intake (DMI) and water intake (WI) in beef cattle using equations from the meta-analytical results: (a) DMI vs. TDS, (b) DMI vs. NaCl, (c) DMI vs. SO4, (d) WI vs. TDS, (e) WI vs. NaCl, and (f) WI vs. SO4. TDS = total dissolved solids, NaCl= sodium chloride, SO4 = sulfates.

Figure 3.

Influence of high-salt water on average daily gain (ADG) and feed efficiency (FE) in beef cattle using equations from the meta-analytical results: (a) ADG vs. TDS and (b) FE vs TDS. TDS = total dissolved solids.

Table 5.

Terms and significance for each equation that best fit dry matter intake (DMI) and water intake (WI), average daily gain (ADG), and feed efficiency (FE) from total dissolved solids (TDS) in drinking water in beef cattle

Itema	Parameter estimatesb
	Intercept	SEintercept	P-value	X	SEx	P-value	X2	SEx2	P-value	AICC	BIC	RMSE	R 2
Equations for DMI, g/kg BW0.75
DMI vs. TDS	110.82	5.17	<0.01	−0.48	0.78	0.54	−0.21	0.05	<0.01	688.0	689.8	22.37	0.75
DMI vs. NaCl	105.67	7.10	<0.01	0.85	0.85	0.35	−0.28	0.05	<0.01	383.7	384.5	18.80	0.86
DMI vs. SO4	118.29	6.71	<0.01	−4.68	1.22	<0.01				303.4	304.1	24.80	0.52
Equations for WI, g/kg BW0.75
WI vs. TDS	474.53	29.51	<0.01	12.53	8.38	0.15	−1.75	0.66	0.01	1322.3	1325.7	226.49	0.33
WI vs. NaCl	441.09	40.14	<0.01	34.44	10.95	<0.01	−2.36	0.68	0.01	674.0	675.5	288.10	0.26
WI vs. SO4	545.08	36.20	<0.01	−25.81	6.23	<0.01				616.1	617.4	162.10	0.42
Equation for ADG, g/kg BW0.75
ADG vs. TDS	14.01	1.81	<0.01	0.60	0.38	0.14	−0.17	0.03	<0.01	375.2	376.9	7.04	0.93
Equation for FE, kg gain/kg BW0.75
FE vs. TDS	0.10	0.02	<0.01	0.03	0.01	<0.01	−0.01	<0.01	<0.01	−88.4	−86.8	0.13	0.95

¹TDS, total dissolved solid; NaCl, sodium chloride; SO₄, sulfates.

²SE, standard error; AICC, corrected Akaike information criterion; BIC, Bayesian information criterion; RMSE, root mean square error; R², coefficient of determination.

Although this meta-analysis was conducted to summarize the impact of providing high-salt water on beef cattle performance, it is important to note that WI and DMI are influenced by several factors (i.e., BW, physiological state, diet composition, and environmental conditions). Moreover, the relatively short exposure periods to high-salt water (less than 140 d) of all the analyzed studies are another factor to consider. Longer exposure periods can generate the development of adaptation processes and/or other physiological effects (e.g., secondary mineral deficiencies), which might alter the observed responses of beef cattle consuming high-salt water.

Voluntary feed intake and water quality

Meta-analyses results indicated that DMI was negatively affected by the ingestion of large amounts of salt through drinking water (DMI vs. TDS; P < 0.01), although the magnitude of the effect is dependent on the type of salt dissolved in the water. The quadratic effect (P < 0.01) of DMI vs. NaCl showed that DMI reaches a maximum value (e.g., 106.34 g DM/kg BW^0.75 for a steer of 250 kg BW) at a TDS concentration of 1.5 g/L, decreasing at greater TDS concentrations. Contrarily, the linear effect (P < 0.01) of the DMI vs. SO₄ showed that DMI decreases from the least to the greatest TDS concentrations. Goodness of fit was not improved (based on AICC and BIC values) when the quadratic effect was included in the equation for DMI vs. SO₄.

It is widely recognized that feed intake determines nutrients’ availability to meet the metabolic requirements, thus representing one of the main factors influencing animal production (Mertens, 1994; Allen, 1996; Roche et al., 2008). Crucially, DMI seems to be the first and most affected variable when cattle drink high-salt water, especially with high SO₄ concentration. This meta-analysis revealed that water within the range of 6 to 8 g/L TDS reduces DMI by 10% to 15% (DMI vs TDS model), but if SO₄ is the main salt dissolved in the water, only 3 g/L are needed to decrease DMI to the same magnitude (DMI vs. SO₄ model). Reductions greater than 30% in DMI are expected when TDS concentration increases above 12 g/L. The mechanisms by which salts (and especially SO₄) in drinking water affect feed intake have not been completely elucidated yet. However, it is known that a systemic hypertonicity can affect the brain feeding centers that regulate consumption in ruminants (Burgos et al., 2000; Masters et al., 2005; Allen, 2014). In addition, some authors have suggested that hydrogen sulfide (H₂S) produced by sulfate-reducing bacteria adversely affects ruminal motility, increasing retention time and ruminal digestibility (Bird, 1972; Kandylis, 1984; Drewnoski et al., 2014) and decreasing feed intake (Loneragan et al., 2001; Uwituze et al., 2011; Drewnoski and Hansen, 2013). Oxidative damage could also explain decreases in DMI when beef cattle drink high-sulfate water, because H₂S can induce toxicity by increasing the hepatocyte formation of reactive oxygen species (Truong et al., 2006). Kessler et al. (2013) reported changes in hepatic gene expression involved in inflammatory and immune responses in steers drinking high-sulfate water (3.6 g/L SO₄). These authors observed reductions of 9% in DMI compared with control treatment. These results are in agreement with the hepatic oxidation theory, which suggests that food intake is regulated by signals carried from the liver to brain (Allen et al., 2009). In summary, the understanding of how high-salt water consumption affects the complex and multifactorial mechanisms that regulate feed intake is still elusive, but it is critical to develop management decisions to improve DMI when cattle are drinking high-salt water.

Voluntary water intake and water quality

Water intake was affected by water quality similarly to DMI. There was a quadratic effect (P < 0.01) for the WI vs. TDS and WI vs. NaCl, and a linear effect (P < 0.01) for the WI vs. SO₄.

The effects of salt on WI had higher variability compared to DMI and were determined by the type of salt in the drinking water. For example, in the range of 6 to 8 g/L TDS, voluntary WI might be increased up to 25% or decreased up to 30% depending on whether soluble salt in the water are mainly chlorides (i.e., NaCl) or SO₄ (i.e., Na₂SO₄), respectively. Although it is known that water and feed consumption are normally strongly related (Ahlberg et al., 2018; Zanetti et al., 2019), some authors have reported that in certain circumstances this relationship can be affected (Arias and Mader, 2011; Sexson et al., 2012). For example, DMI normally decreases in response to increasing levels of salt in the drinking water, whereas WI varies according to the type of salt (Grout et al., 2006); therefore, the relationship between WI and DMI appears to be weak and inconsistent when cattle drink high-salt water. Similar to DMI, the mechanisms by which salts affect WI are not fully understood. However, SO₄ salts could reduce the hedonic characteristics of water due to its bitter taste, affecting water consumption (Weeth and Capps, 1972; Digesti and Weeth, 1976; Grout et al., 2006). Goatcher and Church (1970) concluded that cattle are more sensitive to bitter than salty flavors, which may help us to explain why SO₄ salts are more rejected at lower concentrations than chloride salts (Weeth and Hunter, 1971). Additionally, SO₄ salts may affect WI through H₂S toxicity, in a similar way as already discussed for DMI. Sodium chloride, on the other hand, is less toxic than SO₄ salts (NRC, 2005; Wright, 2007); thus, a common response observed in cattle drinking high-sodium chloride water is an increase in water consumption and urine output, the later enhancing salt excretion and contributing to maintain osmotic balance (Wilson and Dudzinski, 1973; Katting et al., 1992). The kidney plays a significant role in the process of maintaining water homeostasis (Sands, 2009). The increased WI of cattle drinking high-sodium chloride water may be explained by an elevation in the osmotic pressure of the body water (Fitzsimons, 1998; Lazartigues et al., 2008). In a literature review on the central control of osmotic homeostasis in mammals, Bourque (2008) provided evidence that extracellular fluid hyperosmolality promotes WI mediated by osmoreceptors located at the periphery and in the hypothalamus. However, there is a maximum concentration of salt that can be tolerated in drinking water, which depends largely on the animal’s ability to concentrate urine (Kay, 1997). It has been documented that cattle can tolerate up to 15 g of sodium chloride per liter of drinking water (Weeth et al., 1960). Concentrations above the tolerance threshold outweigh the homeostatic regulatory mechanisms, causing a decrease in WI, preventing excessive salt load in the body. In summary, high-salt WI regulation is a complex function mediated by physiological mechanisms with critical roles on preventing toxicity and maintaining body water homeostasis.

Animal performance and water quality

The meta-analysis of the data showed that water quality negatively affected ADG and FE of cattle. A quadratic (P < 0.01) effect was observed for both relationships (ADG vs. TDS and FE vs. TDS, respectively). According to the equation ADG vs. TDS, the maximum ADG would be achieved within the range 1.5 to 3.0 g/L of TDS in drinking water. Concentrations of TDS greater than 6 g/L produce a marked reduction in ADG. Similarly, the best FE would be within the range 2.0 to 4.0 g/L of TDS, strongly worsening as TDS concentrations increase thereafter. Thus, when TDS concentrations raise above 6 g/L, a decrease in FE greater than 20% would be expected.

As expected, the ADG was positively related to DMI (NASEM, 2016). Based on the negative effects of high-salt water on DMI, decreased performance should be expected in animals drinking high-salt water compared with those under the same production conditions but drinking high quality water. Moreover, the meta-analysis suggests that high-salt water could cause a more negative impact on ADG and FE than in DMI. In ruminants, there is evidence that increases in salt intake decrease energy efficiency (Arieli et al., 1989), due to increases in heat production (Rumpler and Johnson, 1987). It has been indicated that movement of ions (Na⁺/K⁺) through membranes accounts for about 20%–30% of the basal energy expenditure of animals (Baldwin et al., 1980; Milligan et al., 1985). High levels of NaCl in the body fluid compartments of sheep increase the maintenance energy expenditure, reducing the productive parameters of wethers (De Waal et al., 1989). Similar results have been reported for other mammal species. For instance, Osaka et al. (2001) reported an increase in whole body energy expenditure in rats due to changes in plasma osmolality following intestinal infusion of a hypertonic solution. Similarly, Coelho et al. (2006) observed increases in energy expenditure and decreases in body weight in rats fed high-salt diets. On the other hand, the ruminal H₂S gas produced as a consequence of high-sulfur intake, mainly on high-concentrate diets, can block cytochrome C oxidase, negatively altering the electron transport chain in mitochondria (Beauchamp et al., 1984). Because the mitochondria produce 90% of the cellular ATP, any damage on its metabolism leads to inefficient futile cycles in the cells and ATP depletion, reducing FE (Bottje and Carstens, 2009). Therefore, maintaining systemic osmotic balance is an energy costly process that can potentially reduce animal performance. Future research is needed for a better understanding of the metabolism of energy at cellular level under high-salt load in the body fluid compartments of ruminants.

Conclusion

The meta-analysis revealed the overall negative effects of high-salt water on water intake, dry matter, and performance on beef cattle. The effects are more negative when cattle drink high-sulfate water than when they drink high-chloride water. Moreover, the meta-analysis points out that high-salt water could cause a more negative impact on average daily gain and feed efficiency than on dry matter intake. On the other hand, the meta-analysis highlights knowledge gaps and research needs, to have a better understanding of the effect of high-salt water at different levels of organization (cell, tissue, organ, and organ systems). This knowledge is essential for developing management strategies to alleviate the negative effects of high-salt water on cattle and other livestock species. Moreover, since models of global climate change predict shortages in both water quantity and quality in the near future, major technological progress should be achieved to improve high-salt water use efficiency for sustainable livestock production systems, particularly in regions with increasing scarcity and variability in natural resources. Finally, to the best of our knowledge, this is the first approach that assesses the effect of water quality on feed and water intake as well as animal performance. The relationships described in this meta-analytical evaluation could be the first step for the development of future mechanistic models to predict animal response in beef cattle drinking water with increasing levels and different types of salt concentration.

Glossary

Abbreviations

ADG

average daily gain

AICC

bias-corrected Akaike’s information criterion

BIC

Bayesian’s information criterion

BW

body weight

CP

crude protein

DM

dry matter

DMI

dry matter intake

FE

feed efficiency

H₂S

hydrogen sulfide

NaCl

sodium chloride

NDF

neutral detergent fiber

RMSE

root mean square error

SO₄

sulfates

TDS

total dissolved solids

WI

water intake

Conflict of interest statement

The authors declare no real or perceived conflicts of interest.