Starch digestion in the rumen, small intestine, and hind gut of dairy cows – A meta-analysis

Animal Feed Science and Technology 192 (2014) 1–14

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Starch digestion in the rumen, small intestine, and hind gut of dairy cows – A meta-analysis A. Moharrery 1 , M. Larsen, M.R. Weisbjerg ∗ Department of Animal Science, Aarhus University, Foulum, DK-8830 Tjele, Denmark

a r t i c l e

i n f o

Article history: Received 7 May 2013 Received in revised form 28 February 2014 Accepted 3 March 2014

Keywords: Starch Digestibility Dairy cows Meta-analysis Rumen Small intestine

a b s t r a c t The aim of the present study was to provide mechanistic prediction equations for starch digestibility in the rumen, small intestine, hind gut and total tract by conducting a metaanalysis of available data on starch digestion in lactating dairy cows. Data for starch digestion was extracted from 66 publications on in vivo experiments with 290 dietary treatments involving lactating dairy cows, 284 with total tract starch digestibility (dSTtt), and 184 with rumen (dSTru), 55 with small intestinal (dSTsi) and 58 with hind gut starch digestibility (dSThg). The major starch sources were corn (n = 158), corn silage (n = 151), barley (n = 55), wheat (n = 46) and sorghum (n = 23). The meta-analysis of starch digestion was conducted by multiple regression analysis. For groups of starch sources, wheat showed highest and NaOH treated barley lowest dSTtt. dSTtt was affected by starch source but not starch intake. Highest dSTru was found for wheat. dSTru decreased as the amount of starch consumed increased and starch source affected dSTru. Post rumen, dSTsi was positively, but not significantly, correlated with the dSTru, however starch source affected the dSTsi. Further, dSThg was positively correlated to the dSTsi (and dSTru), and estimation of dSThg was not improved by including starch source in the model. This indicates that highly digestible starch sources have high digestibilities in all digestive compartments, and that there is limited compensatory starch digestion in the lower tract for starch sources with low ruminal starch digestibility. The following approach is proposed as a model for prediction of starch digestion in each compartment for the gastrointestinal tract. Rumen: prediction equation based on rates of starch degradation of individual starch sources, eventually feed groups. The impact of starch intake level on rumen starch digestibility found in this study would probably be partly accounted for if the model includes a feed intake dependent rate of passage. The small intestinal digestibility of ruminal escape starch is predicted using starch source specific (or groups) digestibility coefficients. Hind gut digestibility of small intestinal escape starch is predicted using a 1. order regression equation based on ruminal starch escape. © 2014 Elsevier B.V. All rights reserved.

Abbreviations: BW, body weight; CNCPS, Cornell Net Carbohydrate and Protein Systems; CP, crude protein; d, day; DFe, degrees of freedom for the error term; DM, dry matter; DMI, dry matter intake; dST, starch digestibility; dSTtt, total tract starch digestibility; dSTru, rumen starch digestibility; dSTsi, small intestinal starch digestibility; dSThg, hind gut starch digestibility; EE, ether extract; eq, equation; GLM, general linear model; kd, rate of degradation; kp, rate of passage; MP, metabolisable protein; NDF, neutral detergent fibre; NE, net energy; NEL, net energy for lactation; NorFor, the Nordic feed evaluation system; P, probability; RMSE, root mean square error; SD, standard deviation; SI, small intestine; SSe, sums of squares for the residuals; STentering, starch entering each compartment; STprop, proportion of total starch intake. ∗ Corresponding author. Tel.: +45 8715 8046; fax: +45 8715 6076. E-mail address: [email protected] (M.R. Weisbjerg). 1 Present address: Animal Science Department, Agricultural College, Shahrekord University, P.O. Box 115, Shahrekord, Iran. http://dx.doi.org/10.1016/j.anifeedsci.2014.03.001 0377-8401/© 2014 Elsevier B.V. All rights reserved.

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A. Moharrery et al. / Animal Feed Science and Technology 192 (2014) 1–14

1. Introduction State of the art feed evaluation systems use a mechanistic and preferably a non-linear approach to calculate the feeding value of the diet as a whole, and hence, do not utilise constant NE and MP values for each feedstuff. Examples of such feed evaluation systems are the Nordic feed evaluation system NorFor (Volden, 2011) and the North American models NRC 2001 (National Research Council, 2001) and the CNCPS model (Fox et al., 1992). Precise prediction of starch digestion in various compartments of the digestive tract is important for several reasons: (1) ruminal digested starch is a major source of energy for both the ruminal microbes and the host animal, (2) in some systems, the negative correlation between ruminal starch and NDF digestion is modelled (Volden and Larsen, 2011), (3) the energetic efficiency of small intestinally digested starch is higher as compared with ruminal and hind gut fermentation (Harmon and McLeod, 2001), and (4) microbial organic matter synthesis from fermentation of starch in the hind gut is lost in faeces. Several reviews and coherent attempts to model starch digestion in dairy cows are available (Nocek and Tamminga, 1991; Offner and Sauvant, 2004; Reynolds et al., 1997; Reynolds, 2006; Mills et al., 1999a,b; Patton et al., 2012). However, most of these reviews and models consider post-ruminal digestion as one compartment. Offner and Sauvant (2004) modelled prediction equations for the three major compartments of the digestive tract, e.g. rumen, small intestine and hind gut using a data base including data from both growing cattle and dairy cows. In the review of Harmon et al. (2004), only data from growing cattle was used and this showed a large variation in observed small intestinal digestion of starch that might pertain to difficulties in obtaining representative ileal samples and maintaining ileal cannulas in growing animals. Small intestinal digestibilities of starch measured in vivo with lactating dairy cows are not commonly published, but during the last decade a number of studies have been published. The aim of the present study was to model prediction equations for starch digestion in the three major compartments of the digestive tract by meta-analysis using available published data with lactating dairy cows. A multiple regression approach was used that allowed modelling of feedstuff specific parameters using experimental treatments where starch originates from more than one source.

2. Materials and methods 2.1. Description of database A literature search for publications reporting starch digestibilities in dairy cows was performed using online databases and manual search of reference lists in review papers. The literature search was not truncated for specific journals or publication language. In the present study, in vivo starch digestion data have been obtained from 66 publications comprising both digestibility trials and production trials where total tract digestibilities were determined (see reference Appendix 1. List of studies used for database). Selection criteria for inclusion of experiments were that data should be from lactating dairy cows, and publications should report at least total tract starch digestibility and information on the starch sources fed, and analysed starch should be used (not non-structural carbohydrates or equivalent). Observations with whole untreated grains were excluded. If starch content was not reported for individual feeds, table values for starch content from NorFor (2013) were used. Data were included in the database as experimental treatment means. Each treatment observation was average for treatment groups of 2–12 cows. The overall average number of cows per treatment was 4.9, but with higher number of cows for observations with only total tract digestibility (mean 5.8 cows/treatment mean, range 2–12) than for observations with rumen digestibility (mean 4.3 cows/treatment mean, range 2–8) or small intestinal digestibility (mean 3.3 cows/treatment mean, range 2–6). Out of the total 290 observations, breeds were Holstein (273), Norwegian red (13) and Dutch Frisian (4). Experimental treatments in the database (n = 290) covered a wide range of rations and production levels for lactating dairy cows (Table 1). Dry matter intake (DMI) ranged from 8.9 to 27.1 kg/day and the variation mainly reflected stage of lactation. Forage proportion of DMI averaged 482 g/kg DM and ranged from 290 to 770 g/kg DM. Dietary starch mainly originated from concentrates and averaged 277 g/kg DM ranging from 16 to 476 g/kg DM (Table 1). Starch intake, flow to the small intestine and hind gut, and to faeces were (mean ± SD) 5.89 ± 1.93, 1.92 ± 1.53, 0.44 ± 0.55 and 0.43 ± 0.39 kg/day, respectively, in the database. The average total tract starch digestibility was 931 ± 56 g/kg and ranged from 694 to 1000 g/kg. For each experimental treatment, the database included the source (name) of the two main concentrate and the two main forage starch sources, and the dietary inclusion of each. The proportion of the total starch intake from each of these four (or fewer if fewer were used) starch sources was calculated.

2.2. Calculations and statistical methods Most reported starch digestibilities could not be related to specific starch sources, as most experimental treatments included more than one starch source. The digestibility of starch from each specific starch source was therefore estimated by multiple regression analysis using the GLM procedure of SAS (version 9.3, SAS Institute Inc., Cary, NC) where the proportion of total starch intake from each specific starch source was included as regression variables.

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Table 1 Descriptive statistics of cows, diets, and starch digestibility in the data set. Variable

n

Mean

SD

Minimum

Cow characteristics Body weight, kg Days in milk Milk, kg/d

199 248 205

622 103 32.3

52 54 6.6

516 16 16.1

740 274 46.4

Dietary characteristics DMI, kg/d CP, g/kg DM EE, g/kg DM NDF, g/kg DM Starch, g/kg DM Forage, g/kg DM

290 290 57 282 290 290

20.8 171 47.7 316 277 482

3.6 23.1 18.1 48 70 98

8.9 84 16 200 16 290

27.1 296 84 458 476 770

Starch intakes and intestinal flows, kg/d 290 Intake Duodenal 184 58 Ileal Faecal 284 Digestibility, g/kg of entering starch 184 dSTru 55 dSTsi dSThg 58 284 dSTtt

5.89 1.92 0.44 0.43 681 606 555 931

1.93 1.53 0.55 0.39 185 206 199 56

0.31 0.14 0.02 0.00 224 114 81 694

Maximum

11.05 5.90 2.85 2.00 942 901 950 1000

DMI, dry matter intake; CP, crude protein; EE, ether extract; NDF, neutral detergent fibre; dSTru, rumen starch digestibility; dSTsi, small intestinal starch digestibility; dSThg, hind gut starch digestibility; dSTtt, total tract starch digestibility; SD, standard deviation.

In total, 21 starch source groups were included in the models for total tract starch digestibility, whereof the most abundant were: corn, corn silage (divided in high (>0.6) and low (<0.6) proportion of total starch intake), barley, wheat, sorghum, peas, and faba beans. Corn, barley, wheat, sorghum, peas, and faba beans included different physical and thermal treatments. The models used were: M1 : dST = ˛ + ˇ1 × STentering + ˇ2i × STpropi M2 : dST = ˛ + ˇ1 × STentering M3 : dST = ˛ + ˇ2i × STpropi where dST (g/kg entering) is the measured starch digestibility in each compartment of the digestive tract (rumen, small intestine, or hind gut) or in the total digestive tract; ˛ is the common intercept (g/kg entering); STentering is starch intake (kg/d, used for rumen and total tract digestibility) or proportionate escape starch from the rumen or the small intestine (g escape/kg intake); ˇ1 is the regression coefficient; STpropi is the proportion of total starch intake from the ith starch source; and ˇ2i is the vector with regression coefficients for the i = 1 to n starch source groups. The reduced models (M2 and M3) were tested against the full model (M1) using the following F test: F=

(SSeM2 − SSeM1 )/(DFeM2 − DFeM1 ) , SSeM1 /DFeM1

where SSe is the sums of squares for the residuals for the each model, here given for the reduction of M1 to M2, and DFe is the degrees of freedom for the error term. The H0 is that the reduced model do not increase SSe compared to the full model. Digestibilities of individual starch sources were estimated using M3 with NOINT. Rate of starch degradation in the rumen (kd) was calculated from estimated in vivo rumen starch digestibilities (dSTru) and assuming simple one compartment model: dSTru =

kd dSTru ↔ kd = kp · kd + kp 1000 − dSTru

The rate of passage for starch (kp) was estimated from the information in the database to be equivalent to the digestibilities and using Eq. (7.3) from Volden and Larsen (2011): kp = 2.504 + 0.1375 ·

DMI · 1000 − 0.02 · (100 − forage%), BW

where DMI, dry matter intake (kg/d); BW, body weight (kg) and Forage%, percent forage of total DMI and using 199 observations from the database where both DMI (mean 20.6 kg/d), live weight (mean 622 kg) and concentrate proportion (mean 514 g/kg total ration DM) were available.

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Fig. 1. Ruminal starch digestion vs. starch intake.

3. Results 3.1. Rumen The dSTru was highly variable, from 224 to 942 g/kg starch entering in the rumen (Table 1, Fig. 1). Both starch intake (P<0.05) and starch source (P<0.01) affected dSTru (Table 2). The full model including both starch intake and starch source (M1, Table 2) resulted in a negative slope of 14 g/kg per kg increase in daily starch intake. Estimates of dSTru for main individual starch sources are given in Table 4 based on estimates from M3 including NOINT. Estimates for dSTru were very high dSTru for pure starch from wheat, high dSTru (861–945 g/kg) for pure corn starch, barley, oat, corn silage (high) and wheat, and lower (619–773 g/kg) for legumes and NaOH treated wheat and barley, and lowest (574 g/kg) for corn. Corn silage high is corn silage observations where corn silage starch made up more than 600 g/kg ration starch.

3.2. Small intestine Mean dSTsi was 606 g/kg, ranging from 114 to 901 g/kg starch entering (Table 1, Fig. 2). The dSTsi was affected by starch source (P<0.01) but not by rumen escape (Table 3). The full model (M1) for dSTsi did not indicate any relationship between rumen starch escape and dSTsi as the negative regression coefficient was far from significant (P=0.7). The M1 could not be reduced to the simple model (M2) only including ruminal escape starch (P<0.01, Fig. 3). The M1 could be reduced to M3 including starch source but not ruminal escape starch. The dSTsi were very high (701–819) for oat, NaOH treated wheat, pure wheat starch, barley and corn silage high, and high (652–675 g/kg) for pure corn starch and wheat (Table 4). Corn showed medium (510 g/kg) dSTsi, whereas dSTsi for legumes and NaOH treated barley were very low (203–437 g/kg).

Table 2 Models predicting starch digestibility in rumen and total tract based on starch intake and starch source (M1), starch intake (M2), and starch source alone (M3). Model

Starch intake

SE

P (ˇ = / 0)

(g/kg)/(kg/d) Rumen, n = 184 M1) Intake + source M2) Intake M3) Source Total tract, n = 284 M1) Intake + source M2) Intake M3) Source

−14.0 −40.3

−0.1 −5.2

Intercept

SE

P (˛ = / 0)

Root MSE

M1 = / M2

(g/kg)

5.7 6.0

2.0 1.7

<0.01 <0.01

0.6 <0.01

P – model reductiona

902 See Table 4

35

962 See Table 4

11

<0.01

<0.01

Parameter estimates for starch sources not shown for M1 and M3, for M3 estimates are given in Table 4. a F-test for reduction of M1 to M2 or to M3. H0 : M2 or M3 do not differ from M1.

125 166 127

<0.01

52 56 52

<0.01

M1 = / M3

<0.05

NS

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Fig. 2. Small intestinal starch digestion vs. starch entering the compartment.

Table 3 Models predicting starch digestibility in small intestine and hind gut based on proportion escaping previous compartments and starch source (M1), on proportion of starch escaping previous compartments (M2), and starch source alone (M3). Model

Starch escape

SE

P (ˇ = / 0)

SE

P (˛ = / 0)

Root MSE

0.26 0.19

0.39 0.26

0.24 0.16

0.7 <0.01

0.04 <0.01

<0.01 <0.01

P – model reductiona M1 = / M2

(g/kg)

(g/kg)/(g/kg) Small intestine, n = 56 M1) Escape + source −0.10 M2) Escape −0.61 M3) Source Hind gut (SI escape), n = 59 −0.84 M1) Escape + source M2) Escape −0.78 M3) Source Hind gut (rumen escape), n = 56 M1) Escape + source −1.11 M2) Escape −0.83 M3) Source

Intercept

740 See Table 4

50

638 See Table 4

37

739 See Table 4

42

<0.01

<0.01

<0.01

161 191 159

<0.01

179 186 187

NS

153 163 184

NS

M1 = / M3

NS

<0.05

<0.01

Parameter estimates for starch sources not shown for M1 and M3, for M3 estimates are given in Table 4. a F-test for reduction of M1 to M2 or to M3. H0 : M2 or M3 do not differ from M1.

Fig. 3. Small intestinal digestibility vs. ruminal escape starch in proportion of intake. (- - - -, M2) dSTsi = 740 − 0.61 × (1000 − dSTru).

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Table 4 Digestibility of starch (dST, g/kg entering) from starch sources in different digestive compartments estimated using M3 (see Tables 2 and 3) and calculated rate of digestion kd. Starch source

Total tract n

Wheat starch Corn starch Wheat Oat Corn silageb Barley Faba beans Wheat NaOH Corn Peas Sorghum Barley NaOH

1 1 46 1 10 49 7 3 158 9 23 1

dSTtt 1021 1003 1002 989 962 959 952 933 916 909 905 839

kd (h−1 )

Rumen SE

n

74 74 16 54 21 10 25 43 8 22 12 52

1 1 29 7 6 47 7 3 75 6 13 1

dSTru 1064 861 945 918 909 870 773 705 574 747 619 670

SE 182 182 42 88 63 26 62 107 23 58 37 127

Small intestine n

–a 0.374 1.038 0.677 0.604c 0.404 0.206 0.144 0.081 0.178 0.098 0.123

1 1 4 1 2 16 7 1 15 5 1

Hind gut

dSTsi

SE

722 652 675 701 819 759 437 708 510 341 na 203

230 230 86 166 117 45 78 165 49 78

n 1 1 4 1 2 16 7 1 17 5

159

1

dSThg

SE

776 826 636 704 660 609 633 61 469 561 na 389

267 267 100 193 135 52 91 192 53 90 184

na: data was not available. a Infinite. b Observations where starch from corn silage contributes more than 60% of dietary starch. c kd would be 0.448 h−1 if estimated using a forage equation for passage rate from NorFor (Volden and Larsen, 2011).

3.3. Hind gut The dSThg averaged 555 g/kg, ranging from 81 to 950 g/kg starch entering (Table 1, Fig. 4), but when calculated as proportion of starch intake it only averaged 52.3 g/kg of starch intake. The dSThg was examined both based on rumen and small intestinal escape (Table 3). Models based on rumen escape resulted in the lowest RMSE, indicating that rumen escape better than small intestinal escape predicted dSThg. Based on rumen escape, escape (P<0.01) but not starch source affected dSThg. The reduced model (M2) based on rumen escape showed that dSThg decreased with 0.83 g/kg for each g/kg increase in rumen escape (Fig. 5). The dSThg for individual starch sources (M3 with NOINT) ranged from 61 for NaOH treated wheat to 826 g/kg for pure corn starch (Table 4). 3.4. Total tract Intake of starch varied from 0.3 to 11.0 kg/day among diets and dSTtt averaged 931 g/kg ranging from 694 to 1000 g/kg (Table 1, Fig. 6). Starch source affected dSTtt (P<0.01; Table 2), whereas starch intake level did not affect dSTtt. The full model (M1, Table 2) indicated that starch intake did not affect dSTtt, which was confirmed when tested against the reduced M3 not including starch intake. Test against M2 showed that omitting starch sources from the model resulted in a poorer prediction (P<0.01).

Fig. 4. Hind gut starch digestion vs. starch entering the compartment.

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Fig. 5. Hind gut digestibility vs. ruminal escape starch in proportion of intake. (- - - -, M2) dSThg = 739 − 0.83 × (1000 − dSTru).

The dSTtt for main individual starch sources are given in Table 4 based on estimates from M3 but including NOINT option. Starch sources in Table 4 are sorted according to declining dSTtt. Pure starches from wheat and corn, and wheat and oat were all fully (>989 g/kg) digested. Only NaOH treated barley with 839 g/kg showed dSTtt below 900 g/kg. 3.5. Rate of digestion Mean calculated fractional rate of passage for the observations in the database was 0.0604 h−1 . In Table 4 rates of rumen starch digestion are given calculated on basis of the estimated rumen digestibilities and the passage rate of 0.0604 h−1 . Calculated rate of digestion was lowest for corn with 0.081 h−1 , and were high for barley with 0.404 h−1 , and very high for corn silage high, oat and wheat ranging from 0.604 to 1.038 h−1 . 3.6. Sensitivity test To check whether the omission of experiment in the analysis might have skewed estimated digestibilities presented in Table 4, a sensitivity test was performed, using a subdataset where the respective starch source made up more than 95% of total ration starch (dominant starch source). Out of the 12 starch sources given in Table 4, 10 for dSTru, 8 for dSTsi, and 10 for dSTtt had observations where the respective starch source was fed as dominant starch source. For the subdataset, mean dSTru were similar (within ±5 percent-units range) to the full dataset for 6 out of 10 starch sources. Exceptions were, measured vs. Table 4 values (g/kg), respectively, Faba beans 720 vs. 773, Wheat NaOH 565 vs. 705, Corn 692 vs. 574, and sorghum 677 vs. 619. For dSTsi, mean dSTsi were similar (within ±5 percent-units range) to the in Table 4 estimated values

Fig. 6. Total tract starch digestion vs. starch intake.

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for 5 out of 8 observations where the respective starch source was fed as dominant starch source. Exceptions were, measured vs. Table 4 values (g/kg), respectively; Faba beans 550 vs. 437, Corn 410 vs. 510, and Peas 215 vs. 341. For dSTtt, mean dSTtt all were similar (within ±3 percent-units range) to the in Table 4 estimated values. 3.7. Other factors The database included information which was not included in the models used in Tables 2–4. The effect of dry matter (DM), crude protein (CP) and NDF intake and CP and NDF proportion of DM was tested by inclusion in the full model (M1). Generally, these factors did not affect starch digestibility, only rumen starch digestibility seemed to be negatively affected by increased DM and NDF intake (data not shown). Further, effects of physical structure and heat treatment were initially tested, however data balance did not allow for conclusive statements for the present dataset and approach (data not shown). 4. Discussion Rations fed to lactating dairy cows normally contain starch from several starch sources, and accordingly, many starch digestibility measurements on productive lactating cows have been performed with rations containing starch from more than one source, precluding assessment of starch digestibility for individual starch sources. The aim of the present study was to assess both the effect of starch source and the effect of starch intake or escape on starch digestibility in the different parts of the digestive tract. Therefore, we have chosen an approach which allowed use of all available digestion trials where starch digestibility had been measured, by building a data base including, together with starch digestibility, both starch source and the proportion of the total starch intake originating from each starch source. The disadvantage of this approach was that it resulted in an unbalanced data set, whereas the advantage was that it allowed use of all available digestibility measurements. If experiments with only one dominant starch source had been selected, number of observations would have been seriously reduced. In the present data set only 26% of the observations had one major starch source accounting for more than 90% of total starch, and in only 53% of the observations one major starch source accounted for more than 70% of total starch. The major consequence of the unbalanced nature of the dataset was that the possibility for taking the effect of experiment into account became difficult as starch source and experiment often was partly or completely confounded. Indeed, state of the art meta-analysis considers experiment as a random factor (St-Pierre, 2001), but inclusion of experiment in the analysis resulted in estimated starch digestibilities for some starch sources which were not in accordance with the majority of the observations for the respective starch source. Thus, we decided to perform the analysis without taking the effect of experiment into account and therefore both within and between experiment observations were considered as independent. The sensitivity test showed, that for Faba beans the derived models seemed to overestimate rumen, and underestimate small intestinal digestibility, whereas the opposite was seen for corn. This reversing pattern could indicate problems in obtaining representative samples from the duodenal cannula, as discussed by Jensen et al. (2005). Further, observations where specific starch sources were dominant starch source might not be representative for all observations including the respective starch source, as treatments which alter digestibility of starch like, e.g. heat treatment might have higher occurrence for observations where a starch source is dominant. For whole grains like NaOH treated wheat the deviation were probably due to variable efficiency of NaOH treatment. Thus, the internal validation showed that the values in Table 4 are in the right biological range, and deviating values were still within the range of digestibilities found in experiments with cattle (Axe et al., 1987; Harmon et al., 2004). 4.1. Ruminal digestion of starch Increased starch intake reduced dSTru with 14 g/kg per kg increase in starch intake. This negative effect of starch intake was probably partly due to a positive correlation between starch and DM intake, and in agreement with Firkins et al. (2001) who reported a decrease of 12 g/kg in digestibility of non-fibre carbohydrates per kg increase in DMI. Increased rumen passage rate with increased DMI is well accepted and introduced in several feed evaluation systems as e.g. NorFor (Volden, 2011), and with increased passage rate the digestibility of starch in the rumen is expected to decrease. Offner and Sauvant (2004) found that accounting for DMI highly increased accuracy of prediction of dSTru. In contrast, Patton et al. (2012) reported no indication of an effect of DMI (across all diets) on dSTru, however increased starch intake decreased dSTru from 750 g/kg at low starch intake to a plateau of 600 g/kg for starch consumption above 4 kg per day (Patton et al., 2012). It is well known that digestibility, both total and in different compartments of the digestive tract, can vary considerable between starch sources (Mills et al., 1999a; Offner and Sauvant, 2004; Larsen et al., 2009). Rumen degradability varied from full digestibility for purified wheat starch to 574 g/kg for corn. The ranking and levels of the obtained dSTru are comparable with results collected by Nocek and Tamminga (1991), whereas dSTru reported by Patton et al. (2012) were surprisingly lower and out of the range we had seen in our database. As an example Patton et al. (2012) report dSTru to be 690 g/kg for barley, where data in our database averaged 889 ranging from 850 to 915 g/kg for 12 observations where barley starch had made up more than 95% of total starch intake. Generally, the ranking tells that purified starch, starch from wheat, barley and oat, and starch in corn silage have high dSTru, whereas mature corn, sorghum and legume seeds have low dSTru.

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Modern feed evaluation systems like NorFor (Volden, 2011) and CNCPS (Fox et al., 1992) predict dSTru using estimates for rumen fractional rates of degradation (kd) and for fractional rates of passage combined in a simple one pool model. Therefore estimates of kd are essential. Traditionally in situ or in vitro data have been used to parameterise the models, and NorFor (Volden and Larsen, 2011) rely on in situ data. However, as found by Tothi et al. (2003) and by Offner and Sauvant (2004) use of in situ kd estimates seems to underestimate dSTru for slowly degradable starch and overestimate dSTru for rapidly degradable starch. In the present study, alternatively, the kd was estimated by backwards calculation assuming passage behaviour as for concentrate in NorFor. This enabled estimation of kd’s which fit with the in vivo measured dSTru. The estimated kd varied from 0.081 h−1 for corn to 1.038 h−1 for wheat, and with similar ranking as for dSTru mentioned above. Patton et al. (2012) estimated ‘revised’ kd for rumen starch degradation and got values around 0.15 h−1 for wheat and barley, 0.10 h−1 for corn, and only 0.05 h−1 for corn silage, all considerable lower than those obtained in the present study, concurrent with the lower dSTru found by Patton et al. (2012) as discussed above. However, the kd values found for barley and corn in the present study are comparable with results obtained using rumen evacuation (Tothi et al., 2003) and with values in feed tables like NorFor (2013). Passage rates used by Patton et al. (2012) were based on those proposed by Offner and Sauvant (2004), and they result in slightly (0.066 h−1 ) higher passage rates for concentrate than the NorFor equation used in the present study when compared on the present data set, and differences in passage estimation will therefore only explain little of the deviation. However, the kd estimates are based on first order passage kinetics, and results from Tothi et al. (2003) and a review by Huhtanen and Sveinbjörnsson (2006) indicate that starch passage deviate from first order passage kinetics. This could question the used approach to estimate kd, however when the model (e.g. NorFor) where the kd data are used also rely on first order kinetics, an eventual bias in the kd estimates will be counteracted when used. The present kd values were all estimated using a passage rate prediction based on a concentrate equation which resulted in a mean fractional passage rate of 0.0604 h−1 . This resulted in similar conditions for estimations for all shown feedstuffs; however for corn silage it could be discussed whether a forage equation should have been used. Use of the NorFor equation for starch from forages (Volden and Larsen, 2011) would have resulted in a fractional passage rate of 0.0448 h−1 and a kd for corn silage of 0.448 h−1 instead of 0.604 h−1 . However, starch from kernels in whole crop cereal silages should be expected to have a rumen passage similar to concentrates, therefore the high estimate for kd (0.61 h−1 ) is likely the best estimate for rate of starch degradation in corn silage. However, to the best of our knowledge no studies have compared starch passage from whole crop silage with mature grains. 4.2. Small intestinal starch digestion Potential limiting factors for small intestinal starch digestion have been discussed for decades (Owens et al., 1986; Nocek and Tamminga, 1991; Harmon et al., 2004; Reynolds, 2006). The current data set provided no indications of an upper limit to starch digestion in the small intestine, as the amount of starch digested in the small intestine continuously increased with increasing amounts of starch entering the small intestine (Fig. 2). This is in line with other reviews of starch digestion in growing cattle (Owens et al., 1986; Harmon et al., 2004) and dairy cows (Nocek and Tamminga, 1991; Mills et al., 1999b). Indeed, there are substantial variations in the amount of starch digested in the small intestine at equal starch inflows. Thus, dSTsi of ruminal escape starch varies and relating the small intestinal digestibility to ruminal escape starch in proportion of starch intake (Fig. 3) shows no clear relationship. Previously, such a clear relationship have been observed for dairy cows (Nocek and Tamminga, 1991) and for beef cattle (Offner and Sauvant, 2004); however, the current analysis for lactating dairy cows using the greater amount of data now available show that decreasing dSTsi with increasing ruminal escape is confounded with starch source. Hence, the model including only starch source was as good in explaining the observed variation in dSTsi as the full model also including proportionate ruminal escape starch. Compared to using starch source specific digestibility coefficients, it would indeed be simpler to develop a starch digestion model using a simple prediction equation for dSTsi of ruminal escape starch like the M2 in the present equivalent to that proposed by Nocek and Tamminga (1991), but this would induce a great bias for some starch sources. For example, the M2 would predict the dSTsi of corn starch to 480 g/kg entering reasonably close to the estimated 510 ± 49 g/kg entering using M3 (Table 4). However, the comparison for peas give 586 g/kg entering using M2 compared to 341 g/kg entering using M3. The quantitative importance of this overprediction of dSTsi for peas would equate to 123 g/d of starch in diet containing 200 g/kg DM of peas fed at 20 kg DM/d, equivalent to approximately 1.2 MJ/d of NEL (Volden and Nielsen, 2011). Similarly, the M2 would under-predict the dSTsi of ruminal escape starch from sources in fact having high dSTsi. It could be argued that these under- and over-predictions are of minor importance on a whole diet basis, but the importance would be greater when evaluating the relative economic value of feedstuffs when composing concentrate mixes in the feed industry. These large starch source dependent variations delineates the necessity of including information on each starch source with respect to dSTsi in feed evaluation systems in order to obtain robust and accurate prediction of starch digestion. Treatment means for various processing methods were pooled within starch source in the analysis; however, this does not negate the need for use of dSTsi coefficients specified with respect to processing method actually applied to respective starch sources. As such, the dataset comprise variation in particle size obtained by grinding or rolling of corn, cereals and legumes that were found to greatly influence dSTsi (Rémond et al., 2004; Larsen et al., 2009). It is interesting to note the low dSTsi (Table 4) as compared to monogastrics in general (Bach Knudsen and Jørgensen, 2001) and in particular for corn starch where the dSTsi has been observed to 96.2% in pigs (Bird et al., 2007). It could be speculated that this would be caused by a lower accessibility of ruminal escape starch as rumen microbes have degraded the

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most accessible part. However, dSTsi of native corn starch obtained with post-ruminal infusion have not provided support for this (Kreikemeier et al., 1991; Kreikemeier and Harmon, 1995). Few studies of bovine ␣-amylase are available and Clary et al. (1968) did not observe major differences in species specific ␣-amylases to degrade various starches in vitro. This could point towards a general inhibition of pancreatic ␣-amylase in the bovine small intestine; however, further investigations are needed to elucidate the mechanisms behind. Overall, the present work provided no evidence of a limited capacity for small intestinal starch digestion of up to 2 kg/d, which would cover by far most practical feeding situations. Most of the observed variation in dSTsi of ruminal escape starch could be attributed to information of used starch sources. Thus, inclusion of a starch source specific parameter, i.e. digestibility coefficient, is necessary in mechanistic feed evaluation systems to obtain robust and accurate prediction of the quantitative small intestinal starch digestion. 4.3. Starch digestion in the hind gut It was expected that the hind gut would offer a possibility for compensatory digestion of starch with low digestibility in the rumen or small intestine. Indeed more starch is digested in the hind gut with increased small intestinal escape (Fig. 5) and the regression coefficient indicates an average dSThg of 434 g/kg entering. This value for lactating dairy cattle is in reasonable agreement with the coefficients of 440 and 494 g/kg entering estimated for growing cattle by Harmon et al. (2004) and Offner and Sauvant (2004), respectively. However, the dSThg of small intestinal escape starch decreased with increased proportion of starch escaping the small intestine (Table 3). Thus, the picture of compensatory hind gut digestion of starch is not clear as this collection of data indicate similar overall ranking of starch sources with respect to starch digestibility in each compartment of the digestive tract (Table 4). The prediction of dSThg did not improve using a model including starch source neither when based on small intestinal escape nor on ruminal escape starch. The reason for this is likely that the effect of starch source is difficult to assess when starch flows becomes small as is the case for hind gut inflow. Thus, we propose to predict dSThg using a simple 1. Order regression equation for all starch escaping the small intestine, but basing the equation on ruminal escape starch as this gave the lowest RMSE (Table 3, Fig. 5). 4.4. Total tract starch digestion Total tract starch digestibilities were generally high and close to 1000 g/kg (Fig. 6). The full model (M1) showed no tendency for an effect of starch intake on dSTtt, which was confirmed by the model test. In the simple model M2 excluding source a decrease of 5 g/kg per kg increase in starch intake was shown, which can only be explained large intake with some low digestible starch sources, as also Fig. 6 indicate. Offner and Sauvant (2004) included in situ effective degradability of starch in their model for total tract starch digestibility, probably explaining similar variation as source do in the present study. Further, Offner and Sauvant (2004) included DM intake, whereas neither DM nor starch intake was found significant in the present study. 4.5. Starch sources It is well known that digestibility, both in the total tract and in different compartments of the digestive tract, can vary considerable among starch sources (Mills et al., 1999a; Offner and Sauvant, 2004; Larsen et al., 2009). Estimates in the present study confirmed this, and overall the ranking for total tract was mirrored in the ranking for the rumen, small intestinal and hind gut compartments, telling that the overall positive correlation found between total tract and all compartments digestibilities also was true for individual starch sources. Purified starch from wheat and corn was estimated to be fully digestible. This agree with the general assumption that it is normally not the structure of the starch itself but more the surrounding protein matrix which affect starch digestibility, and thereby starch digestibility can be affected by heat treatment (Keetels, 1995; Eliasson and Gudmundsson, 1996), chemical treatment (Oke and Loerch, 1991; Ortega-Cerrilla et al., 1999) and by the physical structure of the starch source when fed (French, 1973). Wheat and oat were highly digestible in both the total tract and in the rumen, small intestine and hind gut, whereas corn silage and barley were slightly lower. Corn silage in Table 4 only comprised observations where corn silage starch made up more than 600 g/kg total ration starch. There were two reasons for subdividing corn silage observations into high and low (above and below 600 g/kg total ration starch). First, this makes the estimates in Table 4 more similar across feedstuffs. Next, estimates for corn silage including all observations were low especially for rumen digestibility compared to the estimates obtained for the group of high corn silage inclusion, and also compared to experiments with corn silage as the sole starch source (Jensen et al., 2005). The reason for this apparent confounding between proportion of total ration starch and digestibility estimates for corn silage for total and especially rumen digestibility is unknown, but might be due to increased maturity and lack of kernel cracker during harvest in some of the corn silages used in experiments with low inclusion. Starch from corn and sorghum had low digestibilities in total tract and in rumen, small intestine, and hind gut in accordance with Herrera-Saldana et al. (1990b). NaOH treated wheat and barley differed considerable in starch digestibility. NaOH

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wheat had low rumen digestibility, but high total and small intestinal digestibility indicating that it is a starch source with high potential for digestible by pass starch. NaOH barley contrarily was very low in small intestinal digestibility, similar to what has been found for chemical treated barley (Ortega-Cerrilla et al., 1999; Larsen et al., 2009). Legumes, especially the peas, were estimated to be low in dSTtt and dSTru, however the most pronouncing property was the very low dSTsi of all legumes, a characteristic also seen when small intestinal digestibility was examined using the mobile bag method (Ghoorchi et al., 2013). The low dSTsi of legumes is a major reason why starch source is needed for prediction of dSTsi.

4.6. CP intake and starch digestibility Starch and nitrogen metabolism are closely linked in the rumen as carbohydrate fermentation drive the microbial protein synthesis, and insufficient nitrogen may limit microbial growth (Herrera-Saldana et al., 1990a). In support of this latter statement Moharrery and Das (2001) found a positive correlation between amylolytic and proteolytic activities in the rumen. Further, there is some evidence for a positive effect on dSTsi in dairy cows of post rumen infusion of casein (Abramson et al., 2002,2005a,b) or supply with large amounts of rumen undegradable protein (Bruckental et al., 2002). In the present study, the effect of total CP intake on starch digestibility was examined and neither dSTru nor dSTsi were affected by CP intake, which indicate that starch digestion in dairy cows is robust to variation in CP supply.

5. Conclusion Based on the present dataset, rumen starch digestibility was dependent on both starch intake and starch source, whereas small intestinal starch digestibility was mainly dependent on starch source, and hind gut digestibility only dependent on pre-compartment starch escape. Total tract starch digestibility was mainly dependent on starch source. Consequently, we propose the following approach for a starch digestion submodel to be implemented in mechanistic feed evaluation systems: Rumen: prediction equation based on rates of starch degradation of individual starch sources, eventually feed groups. Such rates can be estimated as shown in Table 4. The impact of starch intake on rumen starch digestibility found in this study would probably be partly accounted for if the model includes a feed intake dependent rate of passage. Small intestine: prediction equation based on individual starch source specific (or groups) digestibility coefficients. Thus, the model has to track ruminal starch escape at an individual starch source level. Hind gut: 1. Order regression equation prediction hind gut digestibility of small intestinal escape starch as a function of ruminal starch escape.

Acknowledgements The project was funded by NorFor a.m.b.a. (Aarhus, Denmark) and by the Commission of the European Communities, FP7, KBB-2007-1.

Appendix 1. List of studies used as the dataset Akay, V., Jackson, Jr., J.A., 2001. Effects of NutriDense and waxy corn hybrids on the rumen fermentation, digestibility and lactational performance of dairy cow. J. Dairy Sci. 84, 1698–1706. Beckman, J.L., Weiss, W.P., 2005. Nutrient digestibility of diets with different fiber to starch ratios when fed to lactating dairy cows. J. Dairy Sci. 88, 1015–1023. Benchaar, C., Vernay, M., Bayourthe, C., Moncoulon, R., 1992. Effet de l’extrusion de la féverole (Vicia Faba) sur les flux intestinaux d’azote et d’amidon chez la vache laitière en production. Reprod. Nutr. Dev. 32, 265–275. Cameron, M.R., Klusmeyer, H., Lynch, J.L., Clark, J.H., Nelson, D.R., 1991. Effects of urea and starch on rumen fermentation, nutrient passage to the duodenum, and performance of cows. J. Dairy Sci. 74, 1321–1336. Cammell, S.B., Sutton, J.D., Beever, D.E., Humphries, D.J., Phipps, R.H., 2000. The effect of crop maturity on the nutritional value of maize silage for lactating dairy cows 1. Energy and nitrogen utilization. Anim. Sci. 71, 381–390. Chen, K.H., Huber, J.T., Theurer, C.B., Swingle, R.S., Simas, J., Chan, S.C., Wu, Z., Sullivan, J.L., 1994. Effect of steam flaking of corn and sorghum grains on performance of lactating cows. J. Dairy Sci. 77, 1038–1043. Cooke, K.M., Bernard, J.K., 2005. Effect of length of cut and kernel processing on use of corn silage by lactating dairy cows. J. Dairy Sci. 88, 310–316. Espindola, M.S., DePeters, E.J., Fadel, J.G., Zinn, R.A., Perez-Monti, H., 1997. Effects on nutrient digestion of wheat processing and method of tallow addition to the diets of lactating dairy cows. J. Dairy Sci. 80, 1160–1171. Foley, A.E., Hristov, A.N., Melgar, A., Ropp, J.K., Etter, R.P., Zaman, S., Hunt, C.W., Huber, K., Price, W.J., 2006. Effect of barley and its amylopectin content on ruminal fermentation and nitrogen utilization in lactating dairy cows. J. Dairy Sci. 89, 4321–4335.

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Gozho, G.N., Hobin, M.R., Mutsvangwa, T., 2008. Interactions between barley grain processing and source of supplemental dietary fat on nitrogen metabolism and urea-nitrogen recycling in dairy cows. J. Dairy Sci. 91, 247–259. Gressley, T.F., Armentano, L.E., 2007. Effects of low rumen-degradable protein or abomasal fructan infusion on diet digestibility and urinary nitrogen excretion in lactating dairy cows. J. Dairy Sci. 90, 1340–1353. Guyton, A.D., 2002. Starch digestion and phosphorus excretion in lactating dairy cows. Thesis, Faculty of the Virginia Polytechnic Institute and State University, Blacksburg, Virginia. Harvatine, K.J., Allen, M.S., 2006. Effects of fatty acid supplements on ruminal and total tract nutrient digestion in lactating dairy cows. J. Dairy Sci. 89, 1092–1103. Herrera-Saldana, R., Gomez-Alarcon, R., Torabi, M., Huber, J.T., 1990. Influence of synchronizing protein and starch degradation in the rumen on nutrient utilization and microbial protein synthesis. J. Dairy Sci. 73, 142–148. Herrera-Saldana, R., Huber, J.T., 1989. Influence of varying protein and starch degradabilities on performance of lactating cows. J. Dairy Sci. 72, 1477–1483. Hindle, V.A., Vuuren van, A.M., Klop, A., Mathijssen-Kamman, A.A., van Gelder, A.H., Cone, J.W., 2005. Site and extent of starch degradation in the dairy cow – a comcomparison between in vivo, in situ and in vitro measurements. J. Anim. Physiol. Anim. Nutr. 89, 158–165. Ipharraguerre, I.R., Clark, J.H., Freeman, D.E., 2005. Varying protein and starch in the diet of dairy cows. I. Effects on ruminal fermentation and intestinal supply of nutrients J. Dairy Sci. 88, 2537–2555. Jensen, C., Weisbjerg, M.R., Nørgaard, P., Hvelplund, T., 2005. Effect of maize silage maturity on site of starch and NDF digestion in lactating dairy cows. Anim. Feed Sci. Technol. 118, 279–294. Jochmann, K., Lebzien, P., Daenicke, R., Flachowsky, G., 1999. Influence of corn maturity and lactic acid bacteriaduring ensilage on nutrient conversion in the dairy cow digestive tract. J. Anim. Physiol. Anim. Nutr. 82, 178–192. Joy, M.T., DePeters, E.J., Fadel, J.G., Zinn, R.A., 1997. Effects of corn processing on the site and extent of digestion in lactating cows. J. Dairy Sci. 80, 2087–2097. Klusmeyer, T.H., Lynch, J.L., Clark, J.H., Nelson, D.R., 1991. Effects of calcium salts of fatty acids and proportion of forage in diet on ruminal fermentation and nutrient flow to duodenum of cows. J. Dairy Sci. 74, 2220–2232. Klusmeyer, T.H., Lynch, G.L., Clark, J.H., Nelson, D.R., 1991. Effects of calcium salts of fatty acids and protein source on ruminal fermentation and nutrient flow to duodenum of cows. J. Dairy Sci. 74, 2206–2219. Klusmeyer, T.H., McCarthy, Jr., R.D., Clark, J.H., Nelson, D.R., 1990. Effects of source and amount of protein on ruminal fermentation and passage of nutrients to the small intestine of lactating cows. J. 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Digestion site of starch from cereals and legumes in lactating dairy cows. Anim. Feed Sci. Technol. 153, 236–248. Lechartier, C., Peyraud, J.L., 2010. The effects of forage proportion and rapidly degradable dry matter from concentrate on ruminal digestion in dairy cows fed corn silage-based diets with fixed neutral detergent fiber and starch contents. J. Dairy Sci. 93, 666–681. Le Liboux, S., Peyraud, J.L., 1998. Effect of forage particle size and intake level on fermentation patterns and sites and extent of digestion in dairy cows fed mixed diets. Anim. Feed Sci. Technol. 73, 131–150. Le Liboux, S., Peyraud, J.L., 1999. Effect of forage particle size and feeding frequency on fermentation patterns and sites and extent of digestion in dairy cows fed mixed diets. Anim. Feed Sci. Technol. 76, 297–319. Lopes, J.C., Shaver, R.D., Hoffman, P.C., Akins, M.S., Bertics, S.J., Gencoglu, H., Coors, J.G., 2009. Type of corn endosperm influences nutrient digestibility in lactating dairy cows. J. Dairy Sci. 92, 4541–4548. Lynch, J.L., Klusmeyer, T.H., Cameron, M.R., Clark, J.H., Nelson, D.R., 1993. Effects of somatotropin and duodenal infusion of amino acids on nutrient passage to duodenum and performance of dairy cows. J. Dairy Sci. 76, 1353–1364. Martin, C., Rouel, J., Jouany, J.P., Doreau, M., Chilliard, Y., 2008. Methane output and diet digestibility in response to feeding dairy cows crude linseed, extruded linseed, or linseed oil J. Anim. Sci. 86, 2642–2650. Maulfair, D.D., Fustini, M., Heinrichs, A.J., 2011. Effect of varying total mixed ration particle size on rumen digesta and fecal particle size and digestibility in lactating dairy cows. J. Dairy Sci. 94, 3527–3536. McCarthy, Jr., R.D., Klusmeyer, T.H., Vicini, J.L., Clark, J.H., Nelson, D.R., 1989. Effects of source of protein and carbohydrate on ruminal fermentation and passage of nutrients to the small intestine of lactating cows. J. Dairy Sci. 72, 2002–2016. McNiven, M.A., Weisbjerg, M.R., Hvelplund, T., 1995. Influence of roasting or sodium hydroxide treatment of barley on digestion in lactating cows. J. Dairy Sci. 78, 1106–1115. Oba, M., Allen, M.S., 2003. Effects of corn grain conservation method on ruminal digestion kinetics for lactating dairy cows at two dietary starch concentrations. J. Dairy Sci. 86,184–194.

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