CC BY
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Ukrainian Journal of Ecology
UkrainianJournal of Ecology, 2018, 8(1), 51-56. doi: 10.15421/2017_186
ORIGINAL ARTICLE
Variation in dietary cation-anion differences (DCAD) of feed ingredients in relation to milk fever disease in dairy cattle
Ghaid Al-Rabadi, Marwan Al-Hijazeen
Department of Animal Production, Faculty of Agriculture, Mutah University Al-Karak, 61710, Jordan, E-mail:ghaid78@yahoo. com Submitted: 07.12.2017. Accepted: 15.01.2018
Milk fever is an important disease that affect lactating cow due to the shortage of calcium circulation after parturition. Incidence of milk fever can be minimized by changing diet acidity/alkalinity before parturition to enhance Ca release of bone, and minimizing it excretion through several regulatory mechanisms. However, cow's regulatory mechanisms are inadequate in its ability to satisfy the increased metabolic requirement of calcium. Many formulas have been suggested in literature for calculating Dietary Cation-Anion Differences (DCAD) in attempts to acidify diets to minimize the incidence of milk fever. Thus, selection of feed ingredients, and used formula (DCAD below 0 mEq/kg) are important when formulating diet to reach appropriate acidification of the cows' blood. The aim of current study is to characterize and to measure DCAD of different feed ingredients (Listed in: National Research Council (NRC, 2001)) using the most used equations reported in the literature which are highly correlated with the incidence of milk fever. Tabulated DCAD values showed that the ability of most forages to cause acidification of the cow is not possible and few feed ingredients possessed mild-strong acidic effect. However, using ingredients with acidic effect have nutritional and economic limitations especially in dairy diets. This screening study showed that mostly used feed ingredients in Jordan possess alkaline effect. The magnitude of DCAD1 ((Na++ K+) + (Cl-)), DCAD2 ((Na++ K+) + (Cl-+ S-2)) and DCAD3 ((Na++ K+) + (Cl-+ 0.6S-2)) of different feed ingredients mainly used in Jordan ranged from 93.5 - 592.7 mEq/kg, 31.2 - 349.5 mEq/kg, and 56.1 - 446.8 mEq/kg, respectively. Thus, incorporation of acidifying ingredients is necessary when feeding dry cows without compromising feed intake when cows fed under Jordanian conditions. Several nutritional strategies have been suggested to acidify complete diet, and positively enhance Ca releasing from bones to decrease the possibility occurring milk fever in dairy cows.
Key words: dietary cation-anion difference; milk fever; cattle; feed ingredients
Introduction
Milk fever (hypocalcaemia) is considered as a serious disease in dairy cattle, and it occurs when cows are unable to compensate for the high demand in Ca required for milk production and satisfy its own needs after parturition (Charbonneau et al., 2006). Dairy cattle responses at this period by triggering endocrine and physiological changes that involves stimulating the secretion of parathyroid hormone and afterwards increase the concentration of 1, 25 (OH)2D3 (Thilsing-Hansen et al., 2002). Consequently, parathyroid hormone directly stimulates renal reabsorption mechanisms for calcium to minimize the losses through urination, and will stimulate processes to enhance intestinal absorption of calcium, and mobilization of calcium from bone (NRC 2001). However, cow's regulatory mechanisms are limited in its ability to satisfy the increased metabolic requirement by the rate, by which calcium can be mobilized from bone reserves (DeGaris & Lean, 2009). This condition has been reported to be more pronounced in older cows, and in cows fed on alkalogenic diets, and thus make them more exposed to the risk of milk fever (Ramberge et al., 1984).
Nutritionist attempts to lower DCAD (Dietary Cation-Anion Difference) in cows before calving to trigger physiological mechanism that induce compensated metabolic acidosis condition (Thilsing-Hansen et al., 2002). Cows compensate metabolic acidosis by regulating calcium elimination from the body through increasing urinary excretion of acids (Vagnoni & Oetzel, 1998), maintaining blood pH by bone accepting hydrogen ion in replace of Ca (Lemann et al., 2003) and retaining calcium in blood by reducing its excretion in urine (Charbonneau et al., 2006). Consequently, these regulatory mechanisms enhance more calcium to be retained in the blood. Many formulas have been suggested in literature for calculating DCAD for different feed ingredients and complete diets for dairy cows. Using the preferred equation ((Na++ K+) + (Cl-+ S-2)) by many nutritionists, it is common to attempt to bring DCAD less than zero mEq/kg diet (NRC, 2001). To achieve this DCAD level, extra intake of anionic salt must be fed for at least 10 days before birth (Thilsing-Hansen et al., 2002). However, feeding anionic salts have been associated with low dry mater intake because of its low palatability (Goff & Horst, 1997). Reduction of feed intake and negative energy balance just before calving is undesirable and may lead to risk of ketosis and fatty liver syndrome. Thus,
careful selection of feed ingredients is important when formulating diet to reach appropriate acidification of the cow with minimal usage of anionic salts especially in farms with limited feed ingredient choices such as Jordan.
The objectives of this study were: to compare alkalinity/acidity of feed ingredients using different DCAD equations mostly used in literature; to screen acidic feed ingredients that have potential to reduce the incident of milk fever in cows fed under Jordanian conditions.
Materials and methods
Dietary Cation-anion Differences was calculated based on the strong ion model that are mostly used in literature (DeGaris & Lean, 2009). These equations are selected in this study based on meta-analysis studies that showed strong ion models are correlated and predicted milk fever incidence (Charbonneau et al., 2006; Lean et al., 2006). The following equation was used to calculate mil-equivalent of each ion:
( % ioninfeed x 10000 x Valence)
mEq =---:-—-
Atomic weight
Strong ion models used to calculate DCAD of feed ingredients mostly used in dairy cattle nutrition listed in NRC (2001) are as the following:
DCAD1(mEq/kg) = (Na+(mEq/kg) + K+(mEq/kg)) - (Cl-(mEq/kg))
DCAD2 (mEq/kg) = (Na+(mEq/kg) + K+(mEq/kg)) - (Cl-(mEq/kg) + S-(mEq/kg))
DACD3 (mEq/kg) = (Na+(mEq/kg) + K+(mEq/kg)) - (Cl"(mEq/kg) + 0.6S-(mEq/kg))
Results and discussion
Table 1 shows a list of feed ingredients, and their calculated dietary DCAD (mEq/kg) using different equations. Tabulated values of DCAD shown in table 1 can provide a useful tool of nutritionist to calculate DCAD of complete feed and to compare DCAD of different feed ingredients when macro mineral analysis of different feed ingredient is not analyzed. Although minerals are considered the most variable of the nutrients commonly determined in feed ingredients (Berger, 1996), using stochastic programming in feed formulation software can provides assurance of meeting the requirement of animals to a great probability when the variation in nutrient concentration is known (Peña et al., 2009). For the same feed ingredient listed in table 1 and as expected, using DCAD values was highest for DCAD1 and it was the lowest for DCAD2 (because of including the acidifying sulfur in the equation) and was intermediate for DCAD3 (because of including fraction of sulfur). The coefficient 0.6 was included in DCAD3 based on the proportional efficiency of sulfate salts lowering urine pH in contrast to Cl salts (Goff et al., 2004). Until now, the suitable equation form used to predicate the incidence of milk fever is still unclear. However, DeGaris & Lean (2009) concluded that both DCAD2 and DCAD3 equations were equivalent in predicting milk fever risk although table 1 shows big differences between DCAD2 and DCAD3 for many same feed ingredients. This difference between DCAD2 and DCAD3 is critical when interpreting the results as nutritionists are looking for a narrow DCAD when formulating diets for dairy cattle during dry period to reduce the risk of milk fever incidence. For instance, a meta-analysis study obtained from twenty-two published studies showed that reducing dietary DCAD3 from +300 to 0 mEq/kg in non-lactating dairy cows reduced dietary dry matter intake by 11.3%, reduced the incidence of milk fever by 13.2% (from 16.4 to 3.2%) and urine pH from 8.09 to 7.01 (Charbonneau et al., 2006).
Table 1. List of feed ingredients and their calculated dietary cation-anion difference (DCAD) (mEq/kg, dry basis) using strong ion model equations.
Ingredient *DCAD1 **DCAD2 ***DCAD3
1 Alfalfa 466.3 304.1 369.0
2 Almond hulls 670.3 645.3 655.3
3 Apple pomace 195.6 152.0 169.4
4 Bakery byproduct meal 82.1 -5.2 29.7
5 Bread wastes 163.4 57.4 99.8
6 Cereal by product 146.4 84.0 109.0
7 Cookie by product 75.0 -6.1 26.3
8 Barley grain rolled 115.2 40.4 70.3
10 Barley silage headed 474.9 368.9 411.3
11 Beet sugar pulp 329.6 142.5 217.3
12 Bermudagrass Costal, hay, early
head 345.3 45.9 165.7
13 Bermudagrass titfon-85, hay, 3-4
wk growth 266.6 29.6 124.4
14 Blood meal, ring dried 165.3 -315.0 -122.9
15 Blood meal, batch dried 165.3 -315.0 -122.9
16 Brewer grains, wet 125.5 -111.5 -16.7
17 Brewer grains, dried 90.7 -115.1 -32.8
19 Canola Meal, mech, extracted 379.8 -75.6 106.6
21 Citrus pulp dried 284.8 222.5 247.4
23 Corn distiller grains with solubles,
dried 338.5 64.0 173.8
24 Corn Gluten feed, dried 373.5 99.1 208.8
25 Corn gluten meal, dried 108.4 -428.1 -213.5
26 Corn grains cracked 93.5 31.2 56.1
27 Corn grains, ground, dry 93.5 31.2 56.1
28 Corn grain, steam-flacked 93.5 31.2 56.1
29 Corn grain, rolled, high moisture 100.2 37.8 62.8
30 Corn grain, ground, high moisture 100.2 37.8 62.8
31 Corn grain and cob, ground 118.6 56.2 81.2
32 Corn grain and cob, high moisture 107.4 51.2 73.7
33 Corn Hominy 185.9 111.0 140.9
34 Corn silage immature <25% DM 252.2 164.9 199.8
35 Corn silage, normal 32-38% DM 229.4 142.1 177.0
36 Corn silage, Mature >40% DM 237.7 175.3 200.3
37 Cotton seed with lint 280.8 137.3 194.7
38 Cotton seed hulls 288.4 244.8 262.2
39 Cotton seed meal, solvent, 41 % CP 430.1 180.6 280.4
40 Fats and oil, Calcium Soaps 0.0 0.0 0.0
45 Feathers meal 159.0 -708.1 -361.3
46 Feathers meal with some viscera 46.3 -1045.3 -608.7
47 Fish byproducts Anchovy, meal,
mech 394.0 -92.6 102.1
48 Fish byproducts Menhaden, meal,
mech 259.4 -464.2 -174.7
49 Grasses, cool season, pasture
intensively managed 710.0 585.3 635.2
50 Grasses, cool season, hay, all
samples 390.4 259.4 311.8
51 Grasses, cool season, hay,
immature<55% NDF 551.8 402.1 462.0
52 Grasses, cool season, hay, Mid-
maturity 55-60% NDF 320.0 170.3 230.2
53 Grasses, cool season, hay mature
>60% NDF 326.3 220.3 262.7
54 Grasses, cool season, silage 482.3 351.4 403.8
55 Grasses, cool season, silage
immature <55% NDF 628.1 497.1 549.5
56 Grasses, cool season, silage mid-
maturity 55-60% NDF 543.7 412.7 465.1
57 Grasses, cool season, Silage
mature>60 NDF 389.6 264.9 314.8
58 Grass-legume mixture, hay,
immature < 51% NDF 528.1 353.4 423.3
59 Grass-legume mixture, hay, mid
maturity 51-57% NDF 413.7 245.3 312.7
60 Grass-legume mixture, hay,
mature>0.57 %NDF 377.7 196.8 269.2
61 Grass-legume mixture, silage,
immature <51% NDF 540.9 372.4 439.8
62 Grass-legume mixture, silage mid-
maturity 51-51% NDF 552.6 396.6 459.0
63 Grass-legume mixture, silage
mature > 57% 431.6 412.8 420.3
64 Grass-legume mixture (12-15% hemicellulose) hay, immature<
47% NDF 672.0 503.6 570.9
65 Grass-legume mixture, hay, mid
maturity 47-53% NDF 652.9 503.2 563.0
66 Grass-legume mixture, hay,
mature >53% NDF 314.9 140.2 210.1
67 Grass-legume mixture, silage
immature < 47% NDF 244.2 144.4 184.3
68 Grass-legume mixture, silage, mid
maturity 47-53% NDF 410.2 248.0 312.9
69 Grass-legume mixture, silage,
mature < 53% NDF 552.5 359.2 436.5
70 Grass-legume mixture (10-13.5% hemicellulose) hay, immature<
44% NDF 460.1 335.4 385.3
71 Grass-legume mixture, hay, mid
maturity 44-50% NDF 511.9 349.8 414.6
72 Grass-legume mixture, hay,
mature>50% NDF 515.4 353.2 418.1
73 Grass-legume mixture, silage
immature< 44% NDF 589.5 389.9 469.8
74 Grass-legume mixture, silage, mid
maturity 44-50% NDF 571.6 415.7 478.1
75 Grass-legume mixture, silage, >
50% NDF 552.2 390.0 454.9
76 Legume forage, pasture,
intensively managed 656.0 462.7 540.0
77 Legume forage, hay, all samples 442.6 286.7 349.1
78 Legume forage, hay,
immature<40% NDF 512.6 306.8 389.1
79 Legume forage, hay, mid maturity
44-46% NDF 463.2 269.8 347.2
80 Legume forage, hay, mature, >
46% NDF 482.0 338.5 395.9
81 Legume forage, silage, all samples 585.2 435.5 495.4
82 Legume forage, silage, immature, <
40% NDF 632.8 445.7 520.5
83 Legume forage, silage, mid
maturity, 40-46 % NDF 603.9 429.2 499.1
84 Legume forage, silage, mature, >
46% NDF 607.3 432.6 502.5
86 Meat meal 340.5 22.4 149.6
87 Meat and bone 445.6 202.3 299.6
91 Oat hay, headed 353.0 265.6 300.6
92 Oats silage, headed 465.5 347.0 394.4
93 Pea nut meal, solvent 322.4 122.8 202.7
94 Potato by product meal 325.5 256.9 284.3
95 Rice bran 389.2 270.7 318.1
96 Rye, annual, silage 622.1 497.3 547.2
98 Sorghum grain, dry rolled 107.6 39.0 66.5
99 Sorghum grain, steamed flacked 107.6 39.0 66.5
100 Sorghum silage 287.0 212.2 242.1
101 Sorghum hay, Sudan type 289.4 208.3 240.8
102 Sorghum silage, Sudan type 512.3 418.8 456.2
103 Soybean hulls 376.4 301.6 331.5
104 Soybean meal expellers, 45% CP 531.4 319.3 404.1
106 soybean meal, solvent, 44% CP 548.5 261.5 376.3
107 Soybean meal, solvent, 48% CP 592.7 349.5 446.8
108 Soybean seed, whole 502.0 308.6 386.0
109 Soybean seed, whole roasted 496.3 296.7 376.6
111 Sunflower meal, solvent 367.2 123.9 221.2
115 Wheat bran 309.8 178.9 231.3
116 Wheat grain, rolled 101.2 7.6 45.1
117 Wheat hay, headed 356.2 275.1 307.6
118 Wheat middling 337.8 225.5 270.4
119 Wheat silage, early headed 379.4 273.4 315.8
120 Wheat straw 279.4 210.7 238.2
121 Whey wet, cattle 778.3 61.0 347.9
*DCAD 1 = (Na++K+) - (Cl-), **DCAD2 = (Na++K+) - ■ (Cl"+S">, ***DACD3 = (Na++K+) - (Cl-+0.6S">
Urinary pH is considered as a practical mentoring measurement to metabolic acidosis to reduce the incidence of milk fever during dry period (Goff et al., 2004). Forage ingredients are relatively low in energy content and considered the recommended feed ingredients for feeding dairy cattle during the dry period. In the three used DCAD equations, all forage feed ingredients did not show any negative DCAD (i.e. acid inducing effect) (Table 1). Thus, the ability of forage to cause acidification of the cow is not possible. However, few feed ingredient possessed mild-strong metabolic acidosis effect based on DCAD2 equation (such as bread wastes (-5.2 mEq/kg), cookie by product (-6.1 mEq/kg), blood meal derived product (-315.0 mEq/kg), dried and wet brewer grains (-111.5 and -115.1 mEq/kg, respectively), canola meal (-75.6 mEq/kg) , dried corn gluten meal (-428.1 mEq/kg), feather meal without (-708.1 mEq/kg) and with viscera (-1045.3 mEq/kg), fish by products (range from -92.6 and -464.2 mEq/kg)) and DCAD3 equation ( such as blood meal derived product (-122.9 mEq/kg) , dried and wet brewer grains (-16.7 and -32.8 mEq/kg, respectively), dried corn gluten meal (-213.5 mEq/kg), feather meal with viscera (-608.7 mEq/kg), and fish byproducts Menhaden (-174.7 mEq/kg).
In Jordan, few ingredients choices are available to the producers for dairy cattle such as: corn silage, alfalfa, wheat straw, corn, barley, wheat bran, and soybean meal. Based on the three equations mostly used by nutritionist, the magnitude of DCAD1, DCAD2 and DCAD3 of different feed ingredients mainly used in Jordan ranged from 93.5 - 592.7 mEq/kg, 31.2 - 349.5 mEq/kg, and 56.1 - 446.8 mEq/kg, respectively. Forages are expected to be the dominant ingredients in dairy diet before calving (due to relatively lower energy demand for dry cow and their cheap prices). Feeding forages have been reported to increase the risk of milk fever due to high cations level (Barnouin & Chassagne, 1991). Furthermore, concentrate feeding to dry cow has been reported to make cow to lose appetite around calving and to absorb less calcium than is required (Allen & Davies 1981; Braak et al., 1986). As shown above, absence of ingredients that possess mild-strong metabolic acidosis effect in Jordan may expose dairy cattle to the risk of milk fever. To best of our knowledge, there are no statistics regarding clinical or subclinical milk fever occurrence in dairy cattle in Jordan. However, milk fever is reported to occur at the rate of 5-10% (Bushinsky, 1996) and can reach as 34% in individual herds (Houe et al., 2001). With limited feed ingredient choices available for feeding dairy cattle during dry period, feed ingredients (with minimal usage of anionic salts) that have mild-strong metabolic acidotic effect is required to reduce the incidence of milk fever. However, the few feed ingredients with mild-strong metabolic acidosis effect mentioned above are not available in Jordan (i.e. considered as industry byproducts or raw materials that does not existed in enough quantities). Furthermore, their inclusion in the diet may have some nutritional limitations that must be taken into consideration when formulating diet for dairy cattle before calving. For example, corn gluten meal is lack of lysine and the proportion metabolizable lysine is very low (Sauvant et al., 2004), thus, including large quantities of corn gluten meal to acidify complete diet before parturition may compromise utilization of metabolizable lysine in cattle. Including feather meal in cattle at high level has been reported to be associated with reducing intake (Leme et al., 1978). Blood meal has been reported to be lack in Sulphur-rich amino acids (Klemesrud et al., 2000) and isoleucine (Maiga et al., 1996). Feeding other mild-strong acidic feed ingredients such as bakery wastes, fish meal, brewer grains has been reported to possess some nutritional and cost constrains that limits their inclusion in feed (Stallings, 2009). Several nutritional strategies have been adapted to acidify complete diet to stimulate compensated metabolic acidosis in dairy cattle. Goff & Horst (1997) showed that feeding diets low in potassium and sodium is effective in reducing the risk of milk fever. Certain anionic salt has been reported to be more palatable than another anionic source. Sulfate salts have been reported to be more palatable than chloride salts (Goff & Horst, 1996). Between mostly used anionic salts, magnesium sulfate has been reported to be the most palatable and calcium chloride is the least palatable (Oetzel, 1991). However, chloride has been shown to possess larger acid activity (by 1.6 times) compared to sulfate (Goff et al., 2004). Commercially, adding sweetener to anionic salts is used to mask bad palatability of anionic salts. Combination of previous strategies can be used together to acidify diet. In theory, using binding agents that binds to cations and encapsulation of anionic salt can be potential alternatives to minimize the risk of milk fever. Further research must be conducted to investigate combined strategies to reduce incidence of milk fever.
Conclusions
Calculated DCAD values showed that the ability of most forage to cause acidification of the cow is not possible. However, few feed ingredients possessed mild-strong metabolic acidosis effect, but they have limitations when included in dairy diets during dry period. Several nutritional strategies have been suggested to acidify complete diet to stimulate compensated metabolic acidosis in dairy cattle raised under Jordanian conditions.
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Citation:
Ghaid Al-Rabadi, Marwan Al-Hijazeen (2018). Futorna Variation in dietary cation-anion differences (DCAD) of feed ingredients in relation to milk fever disease in dairy cattle. Ukrainian Journal of Ecology, 5(1), 51-56. | This work is licensed under a Creative Commons Attribution 4.0. License
