SPONSORED BY ALLTECH

K. MJOUN*

*K. Mjoun is with Alltech and is based in Brookings, S.D.

In modern dairy production, feed costs represent up to 60% of the total cost of producing milk. High feed costs call for continued improvement in feed efficiency in dairy cattle. Reliable and rapid feed analyses are therefore required to accurately assess the availability of energy and nutrients of feeds.

Unlike traditional methods to estimate digestibility (Tilley and Terry, 1963) which focus on end-point measurements, the in vitro fermentation model (IFM) is a dynamic in vitro gas production (IVGP) technique that uses an exhaustive approach to evaluate digestion kinetics and end products of ruminal fermentation. The IFM was developed with the goal to offer nutritionists and producers a practical diagnostic tool to evaluate, troubleshoot and propose solutions and strategies to potential issues.

IFM key parameters and applications

When a feed is incubated, dietary carbohydrates (CHO) are fermented to produce volatile fatty acids (VFA), gases and microbial biomass (MBM). Fermentation gases are continuously recorded using an automated system. A dual pool mathematical model is used to describe digestion kinetics of the fast and slow carbohydrate fractions present in the feed (Schofield and Pell, 1995). Fast pool gas production (FP) corresponds to rapidly fermented CHO (mainly sugars and organic acids, starch, pectin; some of available fiber can be present). Slow pool gas production (SP) consists of insoluble available fiber or slowly fermented CHO (mainly fiber; slow-degrading starch may be present).

It is important to note that these pools are only an approximation of the different components, which may break down at varying rates. The proportions of each component depend on the feedstuff — for example, ensiled feeds contain more organic acids; cereal grains contain starch; beet pulp, citrus pulp, soy hulls and alfalfa contain significant amounts of pectins. Grass hay, molasses and beet pulp contain large concentrations of sugars. The type of nutrient available to rumen microbes will affect the rate of degradation of the different pools and size and will also determine the type of organic acids produced during the fermentation and therefore the energy value of the feed.

Gas production, kinetics

The extent of gas production (TGP) and VFA production are indicators of dry matter digestion. As indicated earlier, the proportion of gas produced from fast and slow pools is affected by the type of ingredients and the amount of fermented feeds in a ration. Unbalanced pools need to be corrected by making adjustments to the inclusion rates of the individual feeds.

In ruminants, nutrient availability is determined by the extent of digestion and rates of degradation and passage in the rumen. Degradation rates exert significant influence on the extent of digestion; for example, a feed with a degradation rate of neutral detergent fiber (NDF) of 5%/hour as compared with 3%/hour will result in 10% units increase in NDF digestion. Effectively, this results in more feed intake and energy available for milk production. This is especially important for forages that largely contribute to the slow pool.

True dry matter digestibility (TDMD), microbial biomass and VFA net production reflect the efficiency of fermentation. Microbial biomass production is inversely related to TDMD and gas production stressing the need for a holistic evaluation of rumen fermentation so that feeds are not selected only based on their gas production profile. VFAs produced in the rumen contribute 50-75% of a cow's energy supply. Rumen VFA proportions provide valuable indication on how the dietary energy will be used by lactating cows. Acetic and butyric acids are lipogenic and contribute to milk fat synthesis while propionic acid is gluconeogenic and contributes to lactose synthesis and regulates milk secretion.

Relationships

A total of 160 samples of commercial lactation dairy TMR of known animal performance — milk yield, fat-corrected milk (FCM) and dry matter intake (DMI) — were evaluated using IFM. The majority of samples were from the U.S. and represents diets fed to high-producing dairy cows and includes a wide range of feedstuffs mainly based on corn and corn silage. Samples were from different stages of lactation with an average days in milk of 159 + 43 and milk yield of 79.8 + 13.1 lb., FCM of 75.5 + 11.8 and feed efficiency (FE; FCM/DMI) of 1.49 + 0.19. Large variation existed in the chemical composition of the samples, but the average of nutrient concentrations was typical of lactation diets. DM, CP, NDF, acid detergent fiber (ADF) and starch concentrations were 48 + 6.2, 17.5 + 1.56, 31.7 + 4.28, 19.45 + 3.17 and 25.9 + 4.48, respectively, on a DM basis.

The fermentation profile reflected the variation in chemical composition (Table 1). Fast pool gas production averaged 63.3 + 9.6 mL/g DM with a range of 41-95, exposing the differences in the soluble CHO content among samples. The rate of degradation of fast pool averaged 20.0% + 4.02 reflecting the differences in fermentability of the ingredients. Average slow pool gas production and its corresponding rate of degradation (SPR) were 112.6 + 9.7 mL/g DM and 4.56 + 0.47%/hour, respectively.

Differences in slow pool gas kinetics can be explained by the quality of fiber mainly of forage origin in the diets. Estimated starch degradation rate averaged 10.69 + 1.30%/hour. True dry matter digestibility was variable among samples with an average of 79.1 + 3.17% (70.4-86.2%). Other parameters are shown in Table 1.

Depending on the parameter, 15-40% of the samples have suboptimal values for a synchronized fermentation. Most issues relate to the rates of digestion of the fast (starch) and slow pools with samples presenting either very "slow" fast pool rates, indicating a lack of fermentable CHO or the presence of slowly fermenting starch, or fast rates potentially indicating excess sugars and/or the presence of very fermentable starch. Such cases would present high acidosis risk. While most of the TMR analyzed had adequate fiber digestion (rates >4.6%/hour), more than 25% of the samples contained fiber that was slowly digested, which will impact feed intake and animal performance. Sourcing better quality forages and/or byproduct feeds should correct the problem. The majority of TMR analyzed were fairly digestible, but up to 25 % of the samples were poorly digested with low VFA and MBM production. Inversely, high digestibility feeds (>84%) can be indicative of poor feed efficiency and increased risk of acidosis because of the high volume of gases and VFA produced in the rumen. Strategies to slow down the fermentation by introducing straw in the diet, for example, and substituting the most fermentable feeds with ones with slow fermentation may be required to avoid ruminal upsets.

To explore potential relationships between the fermentation parameters and lactation performance. Samples were stratified into deciles (10% groups) based on milk yield. Correlation and multiple regression analyses were conducted with performance parameters (milk, FCM, DMI) analyzed as dependent variables while chemical and fermentation parameters were treated as independent variables. Milk production (FCM) was positively correlated (P < 0.05) with FP gas production (r = 0.63), SPR (r = 0.73), TGP (r = 0.91), starch degradation rate (r = 0.79), TDMD (r = 0.86), VFA (r = 0.63) and MBM calculated based on the level of DMI (r = 0.73). Similar correlation strengths were observed for DMI and feed efficiency. Of the dietary nutrient concentrations, only carbohydrate parameters were correlated with milk production (FCM) and DMI. Specifically, fiber (NDF, ADF, lignin) were negatively correlated with FCM, DMI, FE (r= -0.86 to -0.75), whereas starch, NFC and TDN were positively related to FCM, DMI and FE (r = 0.68-0.92).

The FCM can be predicted as FCM= -480.5 + 34.4 SPR + 1.57 TGP + 4.55 VFA; R-square = 0.95, demonstrating the importance of diet digestibility, fermentability and fiber digestion rate in defining milk production level. Feed intake was similarly predicted by DMI = -94.7 + 10.27 SPR + 0.58 TGP; R-square = 0.87). Among the chemical composition parameters, dietary TDN concentration explained 82.2% of the variation observed in milk yield. For DMI, NDF concentration explained 69% of the observed variation in DMI in agreement with Van Soest (1994). The IFM data show the potential for monitoring and improving the nutritive value of dairy rations through optimizing rumen efficiency.

Making the right interpretation

Rumen fermentation is a complex process in which end products of fermentation are produced in proportions that depend primarily on substrate availability and the efficiency of microbial growth. Digested feed, microbial biomass, VFA and gas production are the end products of fermentation. It is important to simultaneously take into consideration all those parameters and not to focus on a single metric when making conclusions and potential adjustments to a diet.

Find out more about this and other critical topics May 17-20 during Alltech REBELation, a conference of innovation, inspiration and revolution in agriculture. Join the conversation as we examine the next frontier in nutrition. Visit rebel.alltech.com to view the top-class speakers and register.

References

Pell, A.N., and P. Schofield. 1995. Measurement and kinetic analysis of the neutral detergent-soluble carbohydrate fraction of legumes and grasses .J. Anim. Sci. 73:3455-3463.

Tilley, J.M.A., and R.A. Terry. 1963. A two-stage technique for the in vitro digestion of in vitro digestion of forage crops. J. Brit. Grassland Soc. 18:104-11.

Van Soest, P.J. 1994. Nutritional Ecology of the Ruminant. Cornell University Press. Ithaca, N.Y. n