EFFECTS OF TRANSIENT VARIATION OF SILAGE DRY MATTER CONCENTRATION ON LACTATING DAIRY COWS

Transcription

1 EFFECTS OF TRANSIENT VARIATION OF SILAGE DRY MATTER CONCENTRATION ON LACTATING DAIRY COWS A Thesis Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University By Lucien Reiter McBeth, B.S. Graduate Program in Animal Sciences The Ohio State University 2012 Thesis Committee: Dr. William P. Weiss, Advisor Dr. Normand St-Pierre Dr. Kristy M. Daniels

2 Copyright by Lucien Reiter McBeth 2012 i

3 ABSTRACT Transient changes in silage dry matter (DM) concentration, if unaccounted for, will cause a diet to become unbalanced. We hypothesized that a transient decrease in silage DM concentration would have a negative effect on dry matter intake (DMI), milk yield and composition, and nutrient digestibility. Holstein cows (24) at an average of 116 days in milk were used in 8 replicated 3 3 Latin squares with 21-d periods. The treatments were 1) control, 2) unbalanced, and 3) balanced. The control diet was formulated to have a consistent forage:concentrate (F:C) of 55:45 on a DM basis throughout the period. The unbalanced and balanced diets were the same as the control diet for most of the period except during two 3-d bouts when water was added to the silage (simulating a rain event) to cause a 10%-unit decrease in silage DM concentration. During the bouts, the unbalanced diet was the same as control diet on an as-fed basis, but the F:C decreased to 49:51 DM basis, which reduced diet DM concentration (66.2 vs. 63.9%) and forage-ndf concentration (23.6 vs. 21.0%), and increased starch concentration (28.4 vs. 30.4%). The balanced treatment corrected for the change in silage DM concentration by an increase in wet silage inclusion to rebalance the F:C to 55:45 DM basis. Over the 21-d period, treatment did not affect DMI (24.0 kg/d). Milk production was greater for ii

4 the unbalanced treatment than control (39.3 vs kg/d). DMI for the unbalanced treatment was less on one day only (d 12), and was greater on the day following both bouts (d 6 and 15). As-fed intake of both change treatments was increased during the bouts to maintain DMI, but took 1 d to respond during and after the bouts. Milk production of the unbalanced treatment was not less than the control treatment on any day, and was increased during and after the first bout (d 5 and 6). Milk production was less for the balanced treatment on d 14 when compared to the control treatment. DM and NDF digestibility were not affected by the treatments (65.9% and 55.4%, respectively). Milk fat concentration was lower for the balanced treatment (3.41 vs. 3.33%) and milk protein was greater for the unbalanced treatment (2.78 vs. 2.80%) when compared to the control treatment. Milk fat increased (3.35 vs. 3.48%) and milk protein decreased (2.82% vs. 2.79%) for the unbalanced treatment during the wet bouts. Overall, a large decrease in silage DM% (10%-unit) over short term bouts (with or without TMR adjustment) had only minor effects on DMI, milk yield and composition. Therefore, with a dry alfalfa silage-based diet, adjusting for transient changes in silage DM was not necessary. iii

5 ACKNOWLEDGEMENTS I would like to thank Bill Weiss for his advising. Thank you for taking the time to answer my many questions, even the answers that were just restating the question for me to answer myself. Also, not many students have an advisor who takes time out of their busy schedules to help collect manure. Statistics were a foreign language that I learned to appreciate thanks to Normand St-Pierre, for that I thank you. Thank you Kristy Daniels for your teaching and advising throughout my time here. Thanks are also due to Donna Wyatt, Juan Testa, and the farm crew. Donna, life in the lab is really easy when you have someone to coach you through all the assays, rather than start from scratch. Juan, thank you for being out at the barn with me every morning during the digestion trials and sample collections, as well as completing the glamorous job of drying and grinding. Farm crew, thank you for handling all of the day-to-day chores required in conducting a cow trial. Thank you to my family and friends. Without all of you, I would not be in the position that I am in today. I cannot express my thanks for that. iv

6 VITA January 21, Born - Normal, IL B.S. Animal Science University of Minnesota St. Paul, MN present...graduate Research Associate Ohio State University Wooster, OH PUBLICATIONS McBeth, L.R., W.P. Weiss, and N.R. St-Pierre Effects of Variable Dietary Fat Concentrations on Lactating Dairy Cows. Page 166 in Proceedings of the Tri-State Dairy Nutrition Conference. Fort Wayne, IN (Abstr.). McBeth, L.R., W.P. Weiss, N.R. St-Pierre Effects of Transient Silage DM Concentration Variation on Dairy Cows. Page 140 in Proceedings of the Tri-State Dairy Nutrition Conference. Fort Wayne, IN. (Abstr.). McBeth, L.R., W.P. Weiss, N.R. St-Pierre Effects of Transient Silage DM Concentration Variation on Dairy Cows. J. Dairy Sci. 95:234 (Abstr.). Weiss, W.P., D.E. Shoemaker, L.R. McBeth, P. Yoder, N.R. St-Pierre Within Farm Variation in Nutrient Composition of Feeds. Pages in Proceedings of the Tri-State Dairy Nutrition Conference. Fort Wayne, IN. v

7 Weiss, W.P., D.E. Shoemaker, L.R. McBeth, and N. R. St-Pierre Effects of Oscillating Dietary Concentrations of Unsaturated and Total Long Chain Fatty Acids on Lactating Dairy Cows. J. Dairy Sci (Submitted). Major Field: Animal Sciences FIELDS OF STUDY vi

8 TABLE OF CONTENTS Abstract...ii Acknowledgements...iv Vita...v List of Tables...viii List of Figures...x Chapters: 1. Literature Review Introduction Materials and Methods Results and Discussion...26 List of References...66 Appendix...75 vii

9 LIST OF TABLES 1. Nutrient composition of the silages Ingredient composition of the diets Nutrient composition of the diets Effects of a 3-d bout of wet silage on particle size selection by cows Effects of two 3-d bouts of wet silage on production variables over a 21-d period Effects of a 3-d bout of wet silage on apparent nutrient digestibility Effects of a 3-d bout of wet silage on apparent water balance Effects of a 3-d bout of wet silage on nitrogen balance Effects of two 3-d bouts of wet silage on milk composition variables over a 21-d period Effects of two 3-d bouts of wet silage on milk composition variables within a 21-d period, non-change vs. bout Effects of two 3-d bouts of wet silage on milk fatty acid variables over a 21-d period Effects of two 3-d bouts of wet silage on milk fatty acid index variables over a 21-d period Effects of two 3-d bouts of wet silage on milk fatty acid index variables within a 21-d period, non-change vs. bout...58 viii

10 A.1 Long chain fatty acid composition of the ingredients...76 A.2 Long chain fatty acid composition of the diets...77 A.3 Effects of two 3-d bouts of wet silage on milk fatty acids within a 21-d period, non-change vs. bout...78 A.4 Variance Components...80 A.5 Variance Components...81 ix

11 LIST OF FIGURES 1. Silage DM over time Forage inclusion (66% Alfalfa Silage, 33% Corn Silage, DM-basis), relative to period day, expressed as a percent of diet DM (A) and as-fed (B) Effects of two 3-d bouts of wet silage on daily dry matter intake (A) and daily dry matter intake deviation from the control treatment (B) over a 21-d period Effects of two 3-d bouts of wet silage on daily as-fed intake (A) and daily as-fed intake deviation from the control treatment (B) over a 21-d period Effects of two 3-d bouts of wet silage on daily milk production (A) and daily milk production deviation from the control treatment (B) over a 21-d period Effects of two 3-d bouts of wet silage on sample day milk fat% (A) and sample day milk fat% deviation from the control treatment (B) over a 21-d period Effects of two 3-d bouts of wet silage on sampling day milk protein% (A) and sampling day milk protein% deviation from the control treatment (B) over a 21-d period...65 x

12 CHAPTER 1 LITERATURE REVIEW MILK FAT DEPRESSION Milk fat depression is when milk fat yield is decreased while yields of milk and other milk components may remained unchanged (Bauman and Griinari, 2001). Milk fat is a large component of milk and milk is often priced on a component basis. Because of this component pricing, milk fat depression is very costly to the producer. Milk fat depression is a problem on commercial dairy farms and has been observed since at least 1845 (Van Soest, 1994). While dietary recommendations for carbohydrate balancing and unsaturated fat concentrations have been given (NRC, 2001), the underlying cause is still unknown. The goal of this literature review is to give an understanding of milk fat depression and how it relates to the hypothesis of the overall thesis. Topics to be discussed include milk fat composition and synthesis, causes of milk fat depression, and enzyme inhibitions. 1

13 Milk Fat Composition and Synthesis Milk fat is primarily composed of triacylglycerides (96-98%) and small amounts of mono- and di-acylglycerides (0.02%), and non-esterified free fatty acids (0.22%) (Jensen, 2002). While the fatty acid profile of the triacylglycerides is diverse, the most abundant fatty acids are saturated fatty acids of chain lengths of 4 to 18 carbons, cis-9 C18:1, trans- 18:1 isomers, and linoleic acid (Jensen, 2002). There are three sources for these fatty acids: diet, body fat, and mammary gland de novo synthesis. Lipolysis of adipose tissue releases non-esterified fatty acids (NEFA) into blood. These NEFA are either taken up by the mammary gland directly or taken up by the liver and oxidized or packaged into lipoproteins. Typically, fatty acids from lipolysis account for <10% of fatty acids in milk (Bauman and Griinari, 2003). This contribution is lower during neutral energy status (i.e. less lipolysis), and progressively greater as the animal enters into a more negative energy status (i.e. increased lipolysis). Lipolysis is important because too many long chain fatty acids in the mammary gland can be a problem, as is discussed later. Fatty acids absorbed in the small intestine are large contributors to milk fatty acids. These fatty acids are used as NEFA or packaged in the liver into very low-density lipoproteins (VLDL) and chylomicrons. Fatty acids >C16 and approximately 50% of C16 fatty acids originate directly from dietary sources. Work in rodents show that VLDL receptor protein is an essential protein which anchors the VLDL and chylomicrons to the mammary membrane (Tancken et al., 2001). When the VLDL or chylomicron is anchored to the basal membrane of the 2

14 mammary epithelium, lipoprotein lipase releases the fatty acids as non-esterified fatty acids. From there, these NEFA are re-esterified onto glycerol to form triacylglycerides in the mammary gland and are eventually released from mammary epithelial cells as milk fat globules in the milk. Mammary epithelial cells synthesize short- and medium-chain fatty acids. These de novo synthesized fatty acids account for all C4:0 to C14:0 fatty acids and approximately 50% of C16 fatty acids. Fatty acid synthase is a dimer polypeptide of 6 enzymes and is responsible for the synthesis of fatty acids (Barber et al., 1997). Fatty acid synthase condenses malonyl-coa (created by acetyl-coa carboxylase) with either acetyl-coa or butyryl-coa. Fatty acid extension proceeds through β-carbon reduction with malonyl-coa (from the reaction of acetyl-coa carboxylase and acetyl-coa). Ruminant fatty acid synthase is capable of synthesizing fatty acids from C6:0 to C16:0, which results in milk fat with short- and medium-chain fatty acids. A portion of medium- and long-chain fatty acids are desaturated in the mammary gland by stearoyl-coa desaturase, also known as Δ 9 -desaturase. Stearoyl-CoA desaturase inserts a cis double bond between the 9th and 10th carbons of a fatty acid, and cannot desaturate monenes with double bonds between Δ8 and Δ10 (Mahfouz et al., 1980). Stearoyl-CoA desaturase activity is integral for maintenance of milk fluidity during storage and ejection from the mammary gland (Timmen and Patton, 1988). Preformed and de novo synthesized fatty acids are packaged into triacylglycerides. Fatty acids are attached to a glycerol backbone through the 3

15 glycerol-3 phosphate pathway. Fatty acids are not randomly attached to the glycerol backbone and show specificity for location based on length and saturation. Long chain fatty acids (C 18 ) are primarily located at the sn-1 location, short- to medium-chain fatty acids (C8:0 to C16:0) primarily located at the sn-2 location, and short chain fatty acids (C4:0 to C8:0) and cis-9, C18:1 primarily located at the sn-3 location (Jensen, 2002). Location of fatty acids with low melting points at the sn-3 location is thought to be important to maintain milk fluidity (Jensen, 2002). Causes of Milk Fat Depression Milk fat depression is a complex condition with many possible and proven causes. Not all milk fat depression is caused by the same factors. Associated or proven causal factors include precursor deficiencies, nutrient partitioning, carbohydrate imbalances (i.e. ruminal acidosis, both acute and subacute), and high concentration of unsaturated fat in the diet. Precursor Deficiencies Milk fat depression is commonly associated with a change in ruminal volatile fatty acid pattern due to a change in diet (high grain/low forage, or low effective fiber), resulting in less acetate and more propionate. Acetate is considered lipogenic and propionate glucogenic. Therefore, a deficiency in acetate could lead to a decrease in milk fat. However, a summary of research by Davis and Brown (1970) showed that supplemental acetate to milk fat depressing diets was inconsistent in recovering milk fat. In addition, the amount of acetate required for milk fat synthesis is much less than normally produced in the rumen. 4

16 With an average short chain fatty acid concentration in milk fat of 40.75% and an average short chain fatty acid length of approximately 12 carbons and molar weight of 200g/mol (Jensen, 2002), and an average of 650 g milk fat yield (Davis, 1967), approximately 8 moles of acetate per day are required for de novo synthesis. This is approximately 28% of the normal total acetate produced per day and 29% of the acetate produced per day during high grain caused milk fat depression (Davis, 1967). Under most conditions, acetate is not a limiting factor in milk fat production. Nutrient Partitioning Nutrient partitioning can have an effect on milk fat depression. Intravenous infusions of trans-10, cis-12 CLA cause a positive energy balance, due to the only minor decrease in dry matter intake and major decrease in milk energy output (Harvatine et al., 2009). Intravenous infusions of trans-10, cis-12 CLA increase mrna expression of the subcutaneous adipocyte lipogenic enzymes and proteins lipoprotein lipase, fatty acid synthase, stearoyl-coa desaturase, fatty acid binding protein 4, regulators of lipid synthase sterolresponse element binding protein 1, thyroid hormone responsive spot 14, and peroxisome proliferator-activated receptor-γ (Harvatine et al., 2009). Feeding a supplement of fish and soybean oil (high polyunsaturated fatty acids) to cows, caused a positive energy balance similar to the previous study, also increased the subcutaneous adipocyte lipogenic enzymes lipoprotein lipase and stearoyl- CoA desaturase, and increased proteins involved in lipid droplet formation and diacylglycerol synthesis (Thering et al., 2009). Both of these papers showed that 5

17 milk fat depression is associated with increased lipogenesis in adipocytes, possibly causing a deficiency of substrate for the mammary gland. Neither of these papers show whether the change in gene regulation was due to the change in energy balance or because of a molecular effect of the trans-10, cis-12 CLA. It is unknown whether milk fat depression was caused by this deficiency in substrate, or the up-regulation of lipogenesis in adipocytes was caused by milk fat depression. Carbohydrate Imbalances Carbohydrate imbalances can cause ruminal acidosis. There are two forms of ruminal acidosis, acute- and subacute-acidosis. Acute acidosis is commonly associated with feedlot cattle, where high levels of corn and low levels of forage are fed, and can lead to lactate production causing acidosis without adjustment to the diet (Goad et al., 1998). Acute ruminal acidosis is uncommon in dairy cattle, as dairy cattle are usually fed higher levels of forage. Subacute ruminal acidosis is associated with inadequate intake of physically effective fiber (especially forage) and overconsumption of rapidly fermentable carbohydrates (such as starch), as well as feeding management (mixing, number of feedings, and feedstuff variability), and certain animal behaviors (sorting of ration, slug feeding, and number of meals) (Stone, 2004). Fiber, especially forage fiber and physically effective fiber, increase chewing and saliva production and dilute rapidly degradable carbohydrates in the rumen. Therefore, fiber is important in maintaining optimal rumen ph (Allen, 1997). Recommendations for dietary fiber and forage fiber are provided by the 2001 Dairy NRC. Decreasing dietary fiber 6

18 below these recommendations can decrease milk fat production (Clark and Armentano, 1993; Depies and Armentano, 1995; Yang and Beauchemin, 2007). Non-fiber carbohydrate and starch recommendations have a large range and recommended concentrations depend more on site and rate of digestibility and intake amounts rather than on dietary concentration. Replacing starch with nonforage fiber can increase milk fat in some cases (Weiss, 2012) but not in others (Ranathunga et al., 2010). Increasing ruminally degradable organic matter increases volatile fatty acid production (Allen, 1997). Without proper buffering (through chewing and saliva production) or proper ruminal mucosa adaptation, an increase in volatile fatty acid production causes a decrease in ruminal ph. Low rumen ph inhibits biohydrogenation of fatty acids in the rumen (Van Nevel and Demeyer, 1996; Troegeler-Meynadier et al., 2003). Therefore, proper carbohydrate balancing of the diet is important to prevent milk fat depression. Unsaturated Dietary Fat Fat is a nutrient found in most feedstuffs and sometimes fed as an ingredient. Fat has a high energy content and can be used as an energy source to complement starch diets to increase diet energy while maintaining rumen health. Common sources include corn oil (in corn, corn silage, and especially distillers' grains), other plant oil and oilseeds, tallow, and rumen inert fat. While saturated fat does not inhibit milk fat yield, polyunsaturated fat does. Abomasal infusion of predominantly C16:0, C18:0, and cis-9 C18:1, as well as butter fat (predominantly short-, medium-, and saturated-fatty acids) increases milk fat yield; however, infusions of poly-unsaturated fatty acids decreases milk fat yield 7

19 (Kadegowda et al., 2008). This effect of polyunsaturated fatty acids results from an inhibition of de novo synthesis and biohydrogenation. Inclusion of plant oils and oilseeds decreases de novo synthesis of medium chain fatty acids (Chilliard et al., 2009). In addition to the decrease in de novo synthesis, feeding high levels of poly-unsaturated fatty acids decreases biohydrogenation, with the isomerization step (see below) being rate-limiting (Troegeler-Myenadier et al., 2003). Enzyme Inhibition Ruminal Biohydrogenation Inhibition The dietary fat in typical ruminant diets is high in linoleic acid (from corn and oilseeds) and linolenic acid (from grass and legume forages). Ruminant adipose and milk fat are composed of much less polyunsaturated fat than what is found in normal diets, with as much as 93% biohydrogenation of linoleic acid (Shorland et al., 1955). Unsaturated fatty acids are toxic to bacterial growth (Kemp et al., 1984) and biohydrogenation removes this toxic effect. Bacteria in the rumen of dairy cattle biohydrogenate unsaturated fatty acids to saturated fatty acids, producing various trans- fatty acids as intermediates (Bauman and Griinari, 2001). The biohydrogenation process occurs in 3 steps: lipolysis, isomerization, and biohydrogenation. Lipolysis is required to release free fatty acids from plant triacylglycerides, and is often thought to be the rate-limiting step in biohydrogenation (Harfoot and Hazelwood, 1997). Following lipolysis, the free fatty acids are isomerized (Jenkins et al., 2008). Isomerization of linoleic and linolenic acid leads to the many different trans- fatty acids that are found in 8

20 ruminant fats. The last step in the biohydrogenation process is the biohydrogenation of the fatty acid. During normal rumen conditions, trans-11 C18:1 is the predominant trans- isomer produced during this biohydrogenation pathway of linoleic acid to stearic acid. During milk fat depression, the pathway for microbial biohydrogenation of linoleic acid is altered and trans-10, cis-12 CLA and trans-10 C18:1 are both produced as the intermediates. Few species of microorganisms in the rumen are capable of biohydrogenation; they are grouped into two groups, A and B (Harfoot and Hazelwood, 1997). Group A is responsible for the first biohydrogenation of linoleic acid to vaccenic acid (trans- 11, C18:1); while Group B is responsible for completing the biohydrogenation to stearic acid (C18:0). Goup B organisms are more sensitive to the toxic effects of long-chain poly-unsaturated fatty acids, and therefore cause the biohydrogenation pathway to bottleneck at the trans-, C18:1 isomers if they are suppressed (Kemp and Lander, 1984). Biohydrogenation intermediates can pass out of the rumen freely or be absorbed by protozoa and pass out of the rumen (Yanez-Ruiz et al., 2006). Some of these biohydrogenation intermediates have been shown to inhibit de novo milk fat synthesis and milk fat secretion. Mammary Gland Enzyme Inhibition During milk fat depression, de novo synthesis of milk fatty acids is inhibited. Abomasaly infused trans-10, cis-12 CLA inhibited de novo synthesis and therefore milk fat production, with a 42% and 44% decrease in milk fat percentage and yield, respectively (Baumgard et al., 2000). Trans-10, cis-12 CLA abomasal infusion causes an exponential decrease in milk fat concentration 9

21 (Shingfield and Griinari, 2007). When milk fat depressing diets (high polyunsaturated fatty acids or carbohydrate imbalances) are fed (Piperova et al., 2000; Ahnadi et al., 2002; Peterson et al., 2003), or trans-10, cis-12 CLA infused abomasaly (Baumgard et al., 2002) or intravenously (Harvatine and Bauman, 2006), C4:0 to C16:0 output is decreased 30-59%. In addition to the decreased de novo synthesis, decreases in fatty acid synthase and acetyl-coa carboxylase mrna are observed, implying enzyme decreases as well. However, trans-10, cis-12 CLA alone cannot explain milk fat depression in all cases (Shingfield and Griinari, 2007). In addition to trans-10, cis-12 CLA, infusions of trans-9, cis-11 CLA and cis-10, trans-12 CLA inhibit milk fat yield (Sæbo et al., 2005; Perfield et al., 2007). A meta-analysis of studies with increasing supply of duodenal C18 shows a maximum C18 yield in milk of 52% of total fatty acids (Glasser et al., 2008). After this 52% threshold is reached, milk fat yield is limited by C4 to C16 yield. Abomasal infusions of fats with equal amounts of long chain fatty acid, but increasing amounts of short- and medium-chain fatty acids increases milk fat yield (Kadegowda et al.,2008). These last two studies demonstrate that shortand medium-chain fatty acids may have regulatory effects on milk fat production. High amounts of long chain fatty acids can not only inhibit de novo synthesis but also inhibit stearoyl-coa desaturase and acyltransferase activity. Stearoyl-CoA desaturase mrna and activity are both decreased during carbohydrate imbalance (Peterson et al., 2003), abomasal infusion of trans-10, cis-12 CLA (Baumgard et al., 2002), and intravenous infusion of trans-10, cis-12 CLA (Harvatine and Bauman, 2006). In addition, glycerol phosphate 10

22 acyltransferase and acylglycerol phosphate acyltransferase mrna and activity are reduced during carbohydrate imbalance (Peterson et al., 2003) and abomasal infusion of trans-10, cis-12 CLA (Baumgard et al., 2002) (not reported during intravenous infusions of trans-10, cis-12 CLA). When cis-9 C18:1 (important for the sn-3 location on triacylglycerides to keep a low melting point for milk fat to maintain fluidity) a decrease in secretion of milk fat from epithelial cells occurs (Loor and Herbein, 2003; Loor et al., 2005; Gama et al., 2008). However, temporary infusions of sterculic oil (oil extracted from the seeds of the Sterculia foetida tree) (Griinari et al., 2000), trans-9, trans-11 CLA (Perfield et al., 2007), and trans-10, trans-12 CLA (Gervais et al., 2009) decreases stearoyl-coa desaturase mrna with no effect on milk fat production. A second stearoyl-coa desaturase enzyme was recently found, stearoyl-coa desaturase 5 (Lengi and Corl, 2007). During trans-10, cis-12 CLA intravenous infusions, stearoyl-coa desaturase mrna is decreased, but not stearoyl-coa 5 mrna or desaturase index (Gervais et al., 2009). Therefore, the mammary gland may be able to adapt temporarily to decreases in stearoyl-coa desaturase function, but more work needs to be done. Summary Milk fat depression can be very costly to a dairy producer, and therefore much attention should be paid to prevent milk fat depression. This can be done through a well formulated and fed diet. Diets should be formulated to contain proper amounts of poly unsaturated fatty acids and carbohydrate balance to maintain optimal rumen ph and biohydrogenation. 11

23 A well formulated diet alone will not prevent milk fat depression in all instances. There are many factors that can cause a difference between the diet that is formulated and the one that is fed, including changes in forage particle size, feeding management, and changes in ingredients. These changes can be transient or long term. Much work has been done on what effects a long term change has on milk and milk fat production. However, little work has been done on transient changes. An example of a transient change would be a rainfall that causes a portion of the silage to become wet (i.e. reduced dry-matter concentration). A lower dry-matter inclusion of this silage will cause a decrease in forage fiber and a proportional increase in easily fermented starch in the diet. This decrease in proportion of dietary forage fiber to starch has been shown to cause milk fat depression when fed for a long period. However, a transient change has not been evaluated. We hypothesized that a temporary decrease in silage dry-matter concentration, left unaccounted for, will shift carbohydrate balance, which will cause milk fat depression and decrease milk production. The objectives of this project are to determine the effects of a transient change in silage DM concentration on intake and milk production and composition, and digestibility. 12

24 CHAPTER 2 INTRODUCTION Lactating dairy cattle use feedstuffs to meet their nutritional demands and maintain a healthy environment for microbes in the rumen. These needs can be met by feeding very specifically balanced total mixed ration (TMR). However, nutrient concentrations in feedstuffs can vary, substantially which can cause nutrient composition of the TMR to vary. Forages often comprise more than half the diet dry matter (DM) fed to lactating dairy cows (Shaver, 2004) and a change in forage could result in a large change in the composition of the TMR. Day-to-day variation in DM concentration of corn silages and hay silage on 8 dairy farms in Ohio had coefficients of variation (CV) and ranges of 5.3 and 7.3 percentage-units, and 8.5 and 12.2 percentage-units, respectively (Weiss et al., 2012). Variation in silage DM will alter the composition of the TMR, unless appropriate adjustments are made. TMR are formulated on a DM basis; however, an ingredients are included in the mixture on an as-fed basis. Should the DM concentration of the forage change, the total amount of forage DM added to the TMR would also change, possibly resulting in an unbalanced diet. A 10 percentage-unit decrease in 13

25 forage DM concentration could reduce the forage-neutral detergent fiber (NDF) in a diet by 10 to 15%. A decrease in silage DM concentration could affect the concentration of other nutrients as well (e.g. starch, protein, etc.). A change in silage DM concentration could affect dry matter intake (DMI) and ruminal health. The major potentially limiting factors of DMI in high producing dairy cattle are rumen fill and hepatic oxidation of fuels (such as propionate) (Allen, 2000). A decrease in silage DM concentration would cause a decrease in forage NDF concentration of the diet and an increase in DMI could be expected (i.e. less rumen fill). Conversely, a decrease in silage DM could cause an increase in starch concentration of the diet. Increased starch intake can cause an increase in the production of ruminal propionate which has a hypophagic effect in cattle (Elliot et al., 1985). Ruminal acidosis can be caused by an inadequate intake of effective fiber or an overconsumption of starch (Stone, 2004). Because a decrease in silage DM would cause a reduction in the amount of forage fiber fed and likely an increase in the proportion of starch in the diet, subacute ruminal acidosis could occur. Some understanding of what affects short term variation of nutrients have on dairy cattle exists. Variations in dietary fat concentration cause little short term differences in DMI or milk production (Weiss et al., 2012, submitted). A series of three abstracts reported that 1 to 3 d decreases in silage DM of 3-8%- units decreased short term DMI and milk production (Mertens & Berzaghi, 2009; Boyd & Mertens, 2010; Boyd & Mertens, 2011). 14

26 Large variations in silage DM concentration can occur and these changes in silage DM concentration can cause a transient change in the TMR, making it nutritionally unbalanced. We hypothesized that these temporary imbalances would decrease intake, milk production, and nutrient digestibility and alter milk fatty acid profiles. The objectives of this research were to determine whether any changes in intake, milk production and composition, digestibility, and milk fatty acid profile occur. 15

27 CHAPTER 3 MATERIALS AND METHODS Cows, Diets and Production Trial Experimental Design All procedures involving animals were approved by the Ohio State University Institutional Animal Care and Use Committee. Twenty-four Holstein cows were blocked by parity (3 squares multiparous, 5 squares primiparous) and assigned to one of 6 treatment sequences in 8 orthogonally replicated 3 3 Latin squares. At the beginning of the experiment cows averaged 116 DIM (±23d). Cows were moved into tie stalls and fed the control diet for 10 d prior to the beginning of the first period. The treatments were: control, unbalanced, and balanced. The control diet was formulated to have a consistent forage:concentrate (F:C) of 55:45 (DMbasis) throughout the period. The forage consisted of 67% alfalfa silage and 33% corn silage on a DM basis (Table 1 and Figure 1). The unbalanced and balanced diets were the same as the control diet for most of the period, except during two separate 3-d bouts. During these bouts, a calculated amount of water was added to both silages to reduce silage DM by 10 percentage units. During the bouts, the unbalanced diet was the same as the control diet on an as-fed basis, but F:C differed on a DM-basis (49:51) (Figure 2B). The balanced diet 16

28 was corrected for the change in silage DM concentration by increasing silage inclusion (as-fed basis) to rebalance F:C to 55:45 (DM-basis) (Figure 2A). Ingredient composition of the diets is presented in Table 2. All three treatment nutrient profiles were identical for 15 of the 21 d periods (Table 3). Digestion Trial Experimental Design Before beginning the experiment, two squares of multiparous cows from the production trial were chosen for a simultaneous total collection digestion trial during the production trial. Collection periods were 4 d, and started the first day of the first bout of the production period. Cows were moved to individual tie stalls designed for total separation and collection of feces, urine, and milk. Apparent digestibilities of DM, organic matter (OM), neutral detergent fiber (NDF), starch, and nitrogen were calculated as nutrient intake minus fecal output divided by intake. Nitrogen balance was calculated as nitrogen intake minus total nitrogen output in feces, urine, and milk. Production Trial Sampling and Analysis Cows were fed a TMR once daily and DMI was measured daily. Cows were fed for a target of 5% feed refusal, and feed refusal averaged 6% of feed offered. Starting on d 14 of the first period, silages were sampled daily and measured for DM by drying overnight at 100⁰C. Before d 14, silage was sampled twice weekly and DM was measured. When the silage DM changed, the new asfed inclusion rates of ingredients to maintain the goal DM inclusion were calculated. If the new calculated as-fed inclusion rate of the forages differed by a 17

29 total of 1.5 percentage units (sum of the absolute differences in individual silages), inclusion amounts fed were adjusted. Separate silage and concentrate samples were obtained weekly and composited by period. Silages were dried at 55⁰C for 48h and then ground through 1 mm screen (Wiley Mill, Arthur A. Thomas, Philadelphia, PA). Concentrate samples were not dried or ground. Feed samples were analyzed for DM (100⁰C oven for 24h), NDF (Ankom 200 Fiber Analyzer, ANKOM Technology, Fairport, NY) with sodium sulfite and amylase (Sigma A3306, Sigma Diagnostics, St. Louis, MO), ash, crude protein (CP) (Kjeldahl N 6.25, AOAC , 2000), ADF (AOAC , 2000), sulfuric acid lignin (Robertson and Van Soest, 1981), neutral- and acid-detergent insoluble CP, starch (Weiss and Wyatt, 2000) and long chain fatty acids (LCFA) (Weiss and Wyatt, 2003). Samples were analyzed for 30-h in vitro-ndf digestibility and 4-h in vitro-starch digestibility by Cumberland Valley Analytical Services (Hagerstown, MD; Goering and Van Soest, 1970). Silage samples were dry-ashed and concentrate samples were acid digested, and analyses were conducted using inductively coupled plasma spectrograph (STAR Laboratory, OARDC, Wooster, OH). Feed refusals of cows on the unbalanced and balanced treatments were sampled once during each bout, and refusals from all cows were sampled once during the non-change phases and analyzed for DM. During the second bout of the third period, particle size of the original feed offering and feed present 5 h after feeding was analyzed using the Penn State Particle Separator. Sorting was evaluated by the dividing 18

30 proportion of mass on each screen (top screen, middle screen, or pan) at 0h divided by the proportion on that screen at 5h. Cows were milked twice daily and weights were recorded electronically at each milking. Milk samples were obtained twice weekly. Three milk samples during the non-change time periods and 3 samples during the bouts were taken. Composited milk samples (a.m. and p.m.) were analyzed for fat, true protein, lactose, (B2000 Infrared Analyzer, Bentley Instruments, Chaska, MN) and milk urea nitrogen (MUN) (Skalar SAN Plus segmented flow analyzer, Skalar, Inc., Norcross, GA) by DHI Cooperative, Inc. (Columbus, OH). Milk fat was removed from a subsample of the a.m. sample and milk fatty acid profile was determined using a two-step procedure for methylation (Jenkins, 2000) with separation by gas-liquid chromatography using a CP-SIL88 capillary column (100 m 0.25 mm 0.2 µm film thickness; Varian, Inc., Palo Alto, CA). Cows were weighed and body condition scored (BCS) at the beginning of the trial and at the end of each period. BCS were scored by three separate scorers each period. Body weight (BW) change and BCS change was calculated as the difference between the end of the period weight or score and the end of the previous period weight or score. Digestion Trial Sampling and Analysis Silages and concentrate were sampled and composited daily during the collection period. Feed refused by cows were weighed and 10% (by weight) was sampled daily and composited for the period. All feed and refusal samples were kept refrigerated during the trial and frozen after the trial before processing. 19

31 Silages and refusals were lyophilized and ground through a 1 mm screen (Wiley Mill, Arthur A. Thomas, Philadelphia, PA). Concentrates were neither dried nor ground. All feed and refusals were analyzed as described for the production trial. Milk, urine, and feces were weighed, and sampled daily. Milk, urine, and feces were sampled (0.1% of weight) and composited. Urine was collected into containers containing adequate 50% sulfuric acid (v/v) to maintain ph <5.0. All fecal, urine, and milk samples were kept refrigerated during the collection period. Fresh milk, urine and feces were analyzed for nitrogen using the Kjeldahl procedure (AOAC, , 2000). Feces were lyophilized, ground, and analyzed the same (except nitrogen) as the feed and refusals. Statistical Analysis One cow on the control treatment was removed during the first period due to injury and her data were discarded. This cow was replaced for the second and third periods, and this cow was not used in the digestion trial. One cow on the unbalanced treatment and one cow on the balanced treatment in the same block had their treatments accidentally switched during the first bout (digestion trial) of the second period. Therefore, the data from those two cow periods were discarded from the production trial. Data from those cow periods were retained in the digestion trial (coded for the treatment that the cows actually received), giving 2 observations per treatment for the second period, and the model was penalized accordingly. Three models were used to analyze data from this experiment. Data were analyzed using the MIXED Procedure of SAS (v9.3). 20

32 Intake and milk production and composition data were averaged over the period and used in the following model. The CV for milk yield, DMI, milk fat, and milk protein was calculated within cow over the 21 d of each period, and analyzed as an independent variable with the following model. Digestibility, BCS and BW data were also analyzed with the following model. A priori, treatment effects were partitioned into 2 contrasts: control vs. unbalanced and control vs. balanced. The model follows: Y ijkl = µ + T i + L j + c k(j) + P l + TL ij + TP il + LP jl + TLP ijl + e ijkl where: Y ijkl = observed dependent variable µ = overall population mean T i = fixed effect of treatment (2 df) L j = fixed effect of parity (1 df) c k(j) = random effect of cow(parity) (22 df) P l = fixed effect of period (2 df) TL ij = fixed effect of the interaction between treatment and parity (2 df) TP il = fixed effect of the interaction between treatment and period (4 df) LP jl = fixed effect of the interaction between parity and period (2 df) TLP ijl = fixed effect of the interaction between treatment, parity, and period (4 df) e ijkl = residual error (32 df) 21

33 Milk composition data were also divided into two phases (non-change and bout), averaged, and nested within period as a repeated measure. The compound symmetry covariance structure for the repeated measure of cow(bout) was used for most dependent variables because it yielded the smallest Bayesian information criterion. If convergence was not met, then the autoregressive order one covariance structure was used. A priori, treatment effects were partitioned into 5 contrasts: non-change vs. bout within each treatment (3 contrasts), control bout vs unbalanced bout, and control bout vs. balanced bout. The model follows: Y ijklm = µ + T i + L j + c k(j) + P l + B m + TL ij + TP il + TB im + LP jl + LB jm + PB lm + cp lk(j) + TLP ijl + TLB ijm + TBP ilm + LPB jlm + TLPB ijlm + e ijklm where: Y ijklm = observed dependent variable µ = overall population mean T i = fixed effect of treatment (2 df) L j = fixed effect of parity (1 df) c k(j) = random effect of cow(parity) (22 df) P l = fixed effect of period (2 df) B m = fixed effect of bout (normal or wet) (1 df) TL ij = fixed effect of the interaction between treatment and parity (2 df) TP il = fixed effect of the interaction between treatment and period (4 df) 22

34 TB im = fixed effect of the interaction between treatment and bout (2 df) LP jl = fixed effect of the interaction between parity and period (2 df) LB jm = fixed effect of the interaction between parity and bout (1 df) PB lm = fixed effect of the interaction between period and bout (2 df) cp lk(j) = random effect of the interaction between cow(parity) and period (44 df) TLP ijl = fixed effect of the interaction between treatment, parity, and period (4 df) TLB ijm = fixed effect of the interaction between treatment, parity, and bout (2 df) TPB ilm = fixed effect of the interaction between treatment, period, and bout (4 df) LPB klm = fixed effect of the interaction between parity, period, and bout (4 df) TLPB ijlm = fixed effect of the interaction between treatment, parity, period, and bout (8 df) e ijkl = residual error (82 df) Intake and milk production and composition (milk fat and protein concentration) data were analyzed with day as a repeated measure. Intake and milk production had 21 observations and milk composition had 6 observations per cow-period. The first order auto regressive structure was used for the repeated measure of day. The SLICE=DAY option of LSMEANS statement was 23

35 used to determine what (if any) days there was a significant treatment effect. A Fisher s protected LSD was then used to compare treatment means on the days where treatment effect was significant (p<0.10). The model follows: Y ijkl = µ + T i + D j + p k + c l + TD ij + Tpc ikl + e ijkl where: Y ijkl = observed dependent variable µ = overall population mean T i = fixed effect of treatment (2 df) D j = fixed effect of day (20 df for intake and milk production or 5 df for milk composition) p k = random effect of period (2 df) c l = random effect of cow (23 df) TD ij = fixed effect of the interaction between treatment and day (40 df for intake or milk production or 10 df for milk composition) Tpc ikl = random effect of the interaction between treatment, period, and cow (44 df) e ijkl = residual error (1709 or 374 df) Sorting data were analyzed with the following model. Normality of data was tested using the Shapiro-Wilk test in PROC UNIVARIATE, and all dependent variables were normally distributed. A priori, treatment effects were partitioned into 2 contrasts: control vs. unbalanced and control vs. balanced. The model follows: Y i = µ + T i + e i 24

36 where: Y i = observed dependent variable µ = overall population mean T i = fixed effect of treatment (2 df) e i = residual error (21 df) 25

37 CHAPTER 4 RESULTS AND DISCUSSION Diet Day-to-day variation in silage DM concentration is presented in Figure 1. CV and ranges were comparable to presented previously observed variations (7.4 vs. 8.5% CV, 13.3 vs percentage unit range for alfalfa silage; 4.2 vs. 5.3% CV, 6.3 vs. 7.3 percentage-unit range for corn silage) (Weiss et al., 2012) Nutrient composition of the diets is presented in Table 3. Diet DM concentration decreased during the bouts (66.2, 63.9, and 60.7 %DM, control, unbalanced, and balanced, respectively). Dietary NDF and forage-ndf decreased 1.6 and 2.6%-units, and starch increased 2.0%-units for the unbalanced treatment during the bouts. All nutrients, except dietary DM concentration, remained the same for the balanced and control treatments. Additionally, for all of the non-change phases of the period, all three treatments were fed the control diet. Concentrations of CP of the diets were lower than intended (14.8% of DM) because the CP of the alfalfa silage decreased. The low concentration of dietary CP probably did not limit milk production. Compared to a previous study with 14.4% CP, DMI (18.0 vs. 24.0) and milk yield (31.8 vs kg/d) of the current study were higher (Law et al., 2009). A meta-analysis assessing concentrations of dietary protein and performance of lactating dairy 26

38 cows predicted a milk yield of 30.2 kg/d (Ipharraguerre and Clark, 2005). Milk production was also greater than predicted by the NRC, 2001 based on DMI and 14.8% CP (32.5 kg predicted vs kg actual). In addition, cows gained weight (Table 5, discussed below) during the trial and had a positive N balance (Table 8, discussed below). Particle Selection Particle selection results are presented in Table 4. Selection for particles on the top- and middle-screens was less for the unbalanced treatment (P=0.01 and P=0.001, respectively) than for the control treatment. Selection for particles in the pan was greater for the unbalanced treatment (P=0.006) than for the control treatment. Selection for particles on the top screen was not different between the balanced and control treatments, but selection for the middle screen and pan followed the same pattern as the unbalanced treatment (P=0.001 and P=0.04, respectively). The unbalanced treatment increased selection for smaller particles at the expense of larger particles. This selection could add to the risk of a acidosis event (DeVries, et al., 2008), which could decrease DMI, milk production, milk fat%, and fiber digestibility, and change the milk fatty acid profile. The difference between the balanced and control treatments is water addition to the silage. Changes in diet DM concentrations (>10 percentage units) caused by water addition or by silage replacing dry hay decreased (Leonardi et al.,2005), increased (Miller-Cushon and DeVries, 2009), or had little effect (Felton and DeVries, 2010; Fish and DeVries, 2012) on selection for smaller 27

39 particles at the expense of larger particles. In the current study, the decrease of dietary DM (66.2 vs. 60.7% dietary DM) occurred with an increase in selection for smaller particles at the expense of larger particles in the balanced treatment. This change in dietary DM was smaller than in previous studies and occurred at a different dietary DM concentration than previous studies. In addition, the differences could be due to a difference in sampling times. In the previous studies, particle selection analysis was conducted on the feed refusals 24 h following feeding. In the current study, analysis was completed 5 hr after feeding. Particle selection is greatest at 5 hr after feeding (Maulfair et al., 2010). Because of limited amounts on the top screen ( %) large changes in selection index from minor changes in mass are possible. Therefore, interpretation of the results of the top screen should be done with caution. During the addition of water, silage was mixed in a horizontal paddle-type TMR mixer for approximately 5 minutes, and some particle size reduction could be expected. Silage was not mixed in a TMR mixer otherwise. However, little differences in particle size between the control and balanced treatment diets were observed (6.3 vs. 6.4% top screen, 39.7 vs. 41.2% middle screen, no statistical comparison). Particle sizing was completed during only one period (n=8 per treatment). Between cow variation and limited repeatability of results could also limit the interpretation of data. In addition, results are not expressed on a percent of DM-basis. Therefore, differing concentration of water in the material retained on each screen could also limit the interpretation of these data. 28

40 Period Intake Means of feed intake are presented in Table 5. Mean DMI was not affected by either change treatment when compared to the control treatment. Average day-to-day DMI variation (within cow) of the unbalanced treatment was not different when compared to the control treatment. However, day-to-day variation in DMI was increased for the balanced treatment when compared to the control treatment (P=0.0004). Increased dietary starch does not have a consistent effect on DMI; but, increasing ruminally degraded starch can decrease DMI (Allen, 2000). However, this did not occur, potentially because the increase in starch was not great enough or a change in site of starch digestion occurred (i.e., replacing corn silage starch with dry ground corn starch). An increase in DMI could also occur due to a decrease in forage-ndf concentration in the diet. A review by Allen (2000) showed that dietary forage- NDF concentration has a negative association with DMI. In the current study, both NDF and forage-ndf concentrations were decreased by the unbalanced treatment during the bouts; however, no increase in DMI was observed. This could be because the reduction in NDF and forage-ndf were not great enough or long enough to increase DMI, or the negative effects of starch on DMI counterbalanced an increase due to decreased forage-ndf concentration in the diet. In previous research reported in an abstract, 7 d mean DMI was not affected by 8 percentage-unit uncorrected for decrease in silage DM 29

41 concentration through water addition for 1 d (Mertens and Berzaghi, 2009). This is similar to the current study. Because DM concentration of the diet was not consistent across the period, as-fed intake patterns could be different from DMI intake patterns. Mean intake expressed as-fed of the unbalanced treatment was not different when compared to the control treatment, but was greater for the balanced treatment when compared to the control treatment (P=0.06). Average day-to-day as-fed intake variation (within cow) of the unbalanced treatment was not different when compared to the control treatment. However, day-to-day variation in as-fed intake of the balanced treatment was greater when compared to the control treatment (P=0.001). Because there was no difference in DMI, the increased asfed intake of the balanced treatment is most likely caused by increased water intake. Mean Milk Production Means for milk production are presented in Table 5. Mean milk production of the unbalanced treatment was greater than that of the control treatment (P=0.05). The mean milk production of the balanced treatment was not different when compared to the control treatment. Average day-to-day milk production variation (within cow) of both change treatments was not different when compared to the control treatment. The increase in milk production of the unbalanced treatment could be caused by an increase in dietary energy. 30