on farm tools - western dairy management conference

On-Farm Tools ForMonitoring Feeding

& ProductionBy Greg Bethard By Sandy Stokes

Technical Services Specialist Extension Dairy SpecialistMonsanto Dairy Business Texas A&M University

Route 2, Box 395 Route 2 Box 1Wytheville, VA 24382 Stephenville, TX 76401

540-637-6501 254-968-4144fax 540-637-6503 fax 254-965-3759

[email protected] [email protected]

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Many industries incorporate variousprocess controls as part of their dailymanagement practices. On dairies,process control or on-farm evaluation

tools have typically occurred in conjunction withDHIA testing, or through forage testing and rationformulation. These tools provide meaningful datafor management decisions, but they are generallyused on an individual cow basis (monthly DHIAtesting) or occur infrequently (forage testing andration formulation). For many dairies, individualdata may be costly or difficult to obtain, andmonthly data may be insufficient for routine man-agement decisions.

This paper will focus on inexpensive but timelymethods of monitoring production, efficiency, andfeeding on large dairy operations. Two broad areaswill be addressed: feeding management tools andproduction monitoring tools. Emphasis will be onmanaging groups on a daily or weekly basis withrelatively inexpensive and simple tools.

Feeding Management ControlsRation & Particle Size Evaluation. Dairy herds

under modern management schemes have thecapability to average over 30,000 lbs milk per cowper year. Top dairy producers and nutritionists con-tinually challenge cows to achieve ever higher lev-els of milk production. High producing cowsrequire higher intakes of an energy dense ration tosupport today’s levels of production. Since energyintake is a function of energy density and dry mat-ter intake, nutritionists struggle to maximize drymatter intake and energy density while maintainingeffective fiber and rumen health.

Formulating energy dense rations often requireshigh levels of grain or byproducts. Inadequate for-age intake can result from a high grain diet fed toan early lactation animal with low dry matterintake. Normally, nutritionists think of supplyingminimum quantities of fiber (ADF or NDF) to pro-mote rumination and saliva production. However,

particle size of the feed, along with fiber content,will dictate the quantity of chewing and saliva pro-duced. “Effective fiber” is a term used to describethe ability of a feed to promote chewing activityand saliva production.

Particle size may be marginal when rations in-clude processed forages and by-product feeds, orwhen rations are over-mixed. Reduction in particlesize may alter the physical nature of fiber, reducingits ability to stimulate rumination and saliva flow,hence reducing effective fiber. Mertens (1997) cal-culated a physical effectiveness fiber (pef) factor forNDF of various feeds. The pef factors for alfalfa haywere 0.82 (long), 0.77 (coarsely chopped), 0.72(medium chopped), 0.60 (finely chopped), and0.54 (ground or pelleted). If a sample of alfalfa haytested 45% NDF, it would have 34.7% effectiveNDF if coarsely chopped (45% x 0.77) and 27% iffinely chopped. Effects of inadequate effective fiberin lactation rations include: acidosis (subacute oracute), erratic dry matter intakes, decreased milkyields, lowered milk fat production, and healthproblems (laminitis, ketosis, displaced abomasum).

Data throughout the literature and field observa-tions strongly support the concept of adequate par-ticle size. For purposes of brevity, one study evalu-ating particle size will be discussed. Grant and co-workers at the University of Nebraska and the U.SDairy Forage Research Center in Wisconsin evalu-ated the effects of alfalfa hay particle size on pro-duction and rumen health of Holstein cows. Onetrial in the study evaluated three particle sizes ofalfalfa hay, which was the sole forage. All hay wasground in a tub grinder with various screens toachieve fine (0.24” screen) or coarse (3” screen)particle length. An intermediate particle length wasachieved by mixing equal parts of the fine andcoarse hay. Results from the study are in Table 2.On paper, the three diets were similar. Dry matterintake and actual milk yield were also similar forthe three treatments. However, due to particle sizedifferences, there were differences in all remaining

Western Dairy Management Conference • Apr i l 8-10, 1999 • Las Vegas , Nevada

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On-Farm Tools For MonitoringFeeding & Production

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Monitoring Feeding & Production... (continued from page 115)

parameters. The optimum particle size dietappeared to be the medium. Cows receiving thisdiet had the highest and most efficiently producedfat corrected milk yield. Chewing activity, milk fatpercent, acetate:propionate, and rumen pH allincreased as particle size increased. This dataclearly demonstrates that particle size, either toogreat or too small, can impact milk production andrumen health.

The importance of adequate effective fiber hasgenerated an interest in developing an on-farm as-sessment of ration fiber effectiveness to ensure thathigh levels of performance are sustained whilemaintaining rumen health. Particle size separationattempts to identify the proportion of the rationwhich is effective in stimulating cud chewing andbuffer production from that which is rapidlydigestible. Many forage labs will analyze particlesize along with routine forage testing. For on-farmevaluation, NASCO’s Penn State Particle Size Sepa-rator (C15924N, Fort Atkinson, WI and Modesto,CA) is commonly used by nutritionists and veteri-narians.

The NASCO Penn State Particle Size Separatorquantifies particle size into three categories:<5/16”, 5/16-3/4”, and >3/4”. Particles less than5/16” are considered rapidly digested, and thosegreater than 3/4” are considered effective in stimu-lating cud chewing and buffer production. Thisseparator is simple, easy to use, and practical forroutine on-farm use. Guidelines for TMR and for-age particle size are in Table 1.

It is important to evaluate particle size at thebunk where cows are consuming feed. If inade-quate particle size is detected at the bunk, thecause may result from a number of factors. Finelychopped forages or inadequate ration forage arecommon causes. Harvesters with on-board kernelprocessors allow longer chop length for cornsilage. Another common cause of inadequate parti-cle size is over-mixing. Rippel and coworkers(1998) evaluated the effects of mixer type and mix-ing time on particle size distribution (usingNASCO’s Penn State Particle Size Separator) of ra-tions in north-central Texas (Table 3). There wereno significant differences between mixers and mix-ing time due to the tremendous variation in sam-ples. However, longer mixing times appeared toreduce the number of particles greater than 3/4”.

Field observations support this, suggesting thatover-mixing reduces particle size. Most profession-als recommend limiting mixing time to less than 5minutes, and avoiding mixing while loading.

Loading order is another consideration in reduc-ing particle size. Rippel et al. (1998) evaluated theeffects of mixing order for wheatlage (W), choppedalfalfa hay (A), and concentrate (C) on particle size(Table 4). The mixing orders evaluated were W-A-C, A-W-C, A-C-W, and W-C-A. When alfalfa wasthe first ingredient added to the mixer, coarse parti-cles >3/4” decreased and fine particles <5/16”increased. If particle size is limiting in a dairyration, altering the mixing order may help reduceparticle size reduction in the mixer.

One final consideration in evaluating particlesize is sorting. Cows often sort, selectively choos-ing portions of the TMR. Often coarser particleswith plenty of effective fiber are the least palatableportion of the ration. It is critical to evaluate theration that the cows are actually consuming.Another challenge is bunks that are not cleanedregularly. Fines can accumulate in the bunk if notcleaned routinely (daily preferred). This will resultin reduced particle size of what the cows are actu-ally consuming.

In general, western dairy rations with relativelylarge concentrations of alfalfa hay may not havethe particle size problems like other regions of thecountry. For regions such as the northeast that feedhigher levels of fermented, processed forages andlittle hay, particle size is more limiting (Table 5).However, all dairies can benefit from evaluatingand monitoring ration particle size.

Feed Inventory. Feed is the single largest operat-ing expense on dairy farms. Despite this fact, fewproducers track feed inventory closely to determineshrinkage and inventory discrepancies. Shrinkageon individual ingredients can vary from 0.5 to 20%(Dutton, 1998; Gaige, 1998). Excessive losses dueto scale errors, rodent or pest damage, wind,weather, etc. can be monitored and evaluated ifinventories are tracked.

Feed inventory tracking can help eliminate over-or under-feeding of ration ingredients. For variousreasons, feeders may not always feed the rationthey’ve been given. Many dairy producers andnutritionists can relate stories of a feeder notadding a particular ingredient because it was time


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consuming or difficult to load. Or, of a feederadding too much of an expensive ingredient,because such a small amount is needed. Unfortu-nately, these situations are often discovered wellafter the fact. By inventory tracking, these problemscan be discovered and addressed quickly. Oftenpoor milk production does not result from a poorration “on paper”, but rather from a deficiency infeeding management. Thus, although the formu-lated ration may be desirable, the ration actuallyconsumed may not be.

Inventory tracking can also be beneficial in feed

pricing. Feeds that have high shrinkage should bediscounted when determining their value. Forexample, suppose that, through inventory tracking,it is determined that shrinkage for ground shelledcorn is 10%. If ground shelled corn is selling for$100/ton, what would the “true” cost be? If therewas zero shrinkage, the cost would be $100 for2000 lbs. With 10% shrinkage, the true cost isactually $100 for 1800 lbs. [2000 lbs x (100%-10%)], which equates to $111.11 actual cost perton [$100/1800 lbs x 2000 lbs]. Thus, the true costof $100/ton corn in this example is $111/ton.

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Tracking is beneficial to determine actual feedcosts.

There are several methods for tracking feedinventory. None of the methods are 100% accu-rate, and higher precision is attained over longertime frames. The easiest but least accurate methodis to simply inventory feeds on a regular basis andcompare to what was supposed to have been fed.This is the most common method employed ondairy farms.

Another method is to track inventory based onwhat was actually fed to cows. A spreadsheet suchas the one displayed in Figures 1-4 will do this, orsimilar software programs may be available thatperform similar tasks. Ration ingredient inclusion(as a percent of the ration on as-fed basis) must beentered for each group. Then, total weights of eachration fed must be entered daily. From these twonumbers, total lbs of each ingredient fed per day iscalculated. This can be subtracted from the currentinventory to keep a daily inventory of all feeds onthe dairy. In addition, daily feed intakes (includingrefusals) can be easily calculated.

The most sophisticated and costly method oftracking inventory is by using a computerized feed-ing management system. E-Z Feed (Valley Agricul-tural Software, Tulare, CA) is one well-knownexample of a computerized feeding managementsystem. These systems generally include a scaleinterface mounted on the feed truck or mix wagon,a hand-held portable computer (Palmtop), and soft-

ware. A properly programmed system that receivesaccurate information can provide valuable output.

Computerized feeding management systems aregenerally easy to use and manage. The managerkeeps rations in a computer in the office, thendownloads feeding information (ingredients andweights for each pen) to a hand-held portable com-puter which is transferred to the feed truck. Nopaper is given to the feeder. As the feeder initiatesthe first load, the scale interface displays the firstingredient (by name or numerical code), then thepounds to be added. As the feeder adds feed, thenumber displayed approaches zero. For example,suppose 1000 lbs of hay need to be added to amix. The scale display would show the feed (byname or number) then display “1000”. As feed wasadded, the “1000” would continually drop until itreached 0, then it would go negative. When thefeeder was done with hay, the system would moveto the next ingredient, again displaying the name ornumber for the feed and the amount to be fed. Thisprocess would continue until the mix is complete.The information could then be downloaded to theoffice computer for the manager to evaluate.

A computerized feeding management systemcan perform inventory tracking based on what isactually loaded in the wagon, providing an accu-rate estimation of inventory changes. One pro-ducer from Texas reported a 6% reduction in feedshrinkage from using one of these systems. In addi-tion, these systems allow a manager to track and


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evaluate feeders. Most systems will track how closea feeder comes to adding the correct quantity offeed. For example, suppose 100 lbs of flaked cornwere supposed to be added to the mix, but thefeeder actually added 105 lbs; for this load, thefeeder’s deviation would be 5% for flaked corn. Fora given day or feeding, deviations for each feedcan be determined for each feeder. Dairy managershave told the authors that top feeders stay within1% for concentrate ingredients. Poor feeders canbe eliminated quickly by monitoring deviations.

Most computerized feeding management sys-tems can also be used to determine dry matterintake (including refusals) by pen. By interfacingwith milk production data, powerful informationcan be generated. Some of these items are dis-

cussed later in the paper.

Production Management ToolsMilk Urea Nitrogen. Another tool that is gaining

popularity in evaluating the feeding program ondairy farms is milk urea nitrogen (MUN) testing. Itis one of the few on-farm tools that provides insightinto what is happening inside the cow. When pro-tein is fed to cows, it is either in the degradable orundegradable form. Degradable protein isdegraded in the rumen by the microbial popula-tion. Some of the degraded protein is converted toammonia, which is utilized by the rumen bacterialpopulation. However, when excess ammonia isproduced beyond the needs of the microbes, it isabsorbed across the rumen wall and into the blood


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stream. Once in the blood, ammonia is detoxifiedto urea in the liver. Urea can be recycled for use byrumen microbes, excreted in urine, or exported inmilk.

Monitoring the level of urea in milk can crudelyindicate ammonia production in the rumen.Causes of excess ammonia production are gener-ally two-fold: over-feeding protein or an imbalancein carbohydrate/protein availability in the rumen.High MUN’s can indicate overfeeding of protein,which is costly from an economic standpoint.Overfeeding protein also can deprive the cow ofneeded energy, as the process of forming urea is anenergy cost to the cow. High MUN’s resulting fromcarbohydrate/protein imbalances imply that rumenfunction is not efficient. Correcting the imbalancewill likely result in improved production andgreater efficiency. Data exist to suggest that highMUN’s may impair reproductive performance(Table 6).

What is the target MUN for high producingdairy herds? Most work suggests that the normalrange for MUN’s is 10-16 mg/dl. Hinders (1996)reported that 7 California herds averaged 13 and16 mg/dl for low and high groups, respectively.Intervention is generally considered when herdaverage values exceed 18 mg/dl. Milk urea nitro-gen data is most useful when used to evaluategroups or a herd, and values for an individual cowshould not be used as culling criteria.

MUN testing is only valuable if performed regu-larly. Establishing a baseline and then monitoringregularly will help identify ration problems quickly.Most DHIA labs offer testing on an individual cowbasis. However, monthly numbers may not providetimely information. Many producers have adoptedweekly programs, testing groups and not individu-als. Most DHIA labs will accept bulk tank or groupsamples for MUN analysis. Bulk tank testing isinappropriate if more than one ration is fed. Stringsamplers (available through some DHIA affiliates)provide a cheap and simple method of collectinggroup samples. Fat, protein, and SCC can be testedalong with MUN on a weekly basis using stringsamplers.

Flow Meters. Milk production is routinely moni-tored by calculating a herd average from the bulktank, by monthly DHIA testing, or by recordingdaily milk weights electronically in the parlor.

Although these traditional production monitoringmethods provide needed data, they have weak-nesses. Bulk tank data is too general for many man-agement decisions, particularly if more than oneration is fed or if cows are grouped by stage of lac-tation. Data collected monthly through DHIA test-ing may be insufficient for timely managementdecisions. Most producers desire weekly or dailyinformation to evaluate production and make

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timely and proactive management decisions. Prob-lems are also detected sooner with frequent moni-toring. Electronic parlor meters provide a wealth oftimely data, but are costly to install.

Monitoring production of groups is an ideal toolfor large dairies. It has several advantages over bulktank, DHIA, or daily electronic production moni-toring. It is relatively inexpensive for large dairies(about $3,000 - 7,000 investment in most cases),and can provide daily information. If cows aregrouped by stage of lactation, group productiondata can provide timely performance informationby stage of lactation. The fresh and early lactationpens are critical groups on the dairy, and daily pro-duction information can be invaluable in quicklydiscovering problems before they manifest.

Recently, dairy producers have begun using flowmeters to more frequently monitor milk productionof groups or strings. Flow meters that monitor flowof water and other liquids have been around formany years; adaptation of these flow meters to thedairy parlor allow the producer to monitor milkproduction on a daily basis. There is more thanone type of flow meter, and they can be installedby most milking equipment dealers.

Flow meters are generally installed near but pastthe receiver jar. Flow meters installed well past thereceiver jar near plate coolers or the bulk tank maybe less accurate due to the quantity of milk in thelines. A “basic” flow meter package has an LCDdisplay in the parlor. Milkers must record milkweights for the group from the display and manu-ally reset for the next group. Small printers are alsoavailable to print milk weights instead of manuallyrecording. A spreadsheet similar to the one dis-played in Figures 1-4 can be used to enter numbersand calculate daily averages. The most advancedsystems automatically record data into softwarethat interfaces with feed information.

A common question dairy producers have aboutflow meters is their accuracy. We monitored twolarge dairies in New Mexico to determine theaccuracy of flow meters versus milk that was sold.For a three month period, flow meter numbers onthese two dairies were within between 97.8 and103.8% of the milk sold for each month. Producersfound the information to be useful and valuable inmanaging their dairy.

Using The DataMany dairies gather the data that has been dis-

cussed in this paper - milk weights, dry matterintakes, and MUN’s. Although this data isrecorded, often little is done with it. This is surpris-ing, considering that feed is the largest expense andmilk accounts for the majority of gross revenue.Closely monitoring variables relating to milk andfeed (ration efficiency, dry matter intake, inventorycontrol, milk production) can greatly influence netfarm income. By developing an on-farm system forrecording and evaluating this data, information forroutine management decisions can be generated.Sophisticated systems are available commerciallythat generate much of this information.

A spreadsheet approach for generating informa-tion from data collected will be discussed here.Although spreadsheets lack some of the sophistica-tion of commercial systems, they are inexpensiveand easy to adapt to individual needs. For the pur-pose of discussion, spreadsheets are simple to fol-low and allow easy understanding of the informa-tion generated. Example outputs from the spread-sheet are in Figures 1-4. Inputs into the spreadsheetare as follows:

• Daily group milk weights from flow meter.• Daily feed truck weights delivered to each pen

including close-up and far-off dry cows.• Daily cow numbers for each pen.• Rations fed to each pen including close-up

and far-off dry cows. • Feed entering (purchased) or leaving (sold) the

dairy each day.• Costs and dry matter content for each feed

ingredient.• Weekly MUN for each pen. With the above information, the following can

be calculated on a daily basis for each pen orgroup:

– Daily milk production and dry matter intakeby pen and herd and for each milking shift.

– Daily feed costs/cow/day by pen and herd andfor each milking shift.

– Daily income over feed cost by pen and herdand for each milking shift.

– Daily feed:milk conversion by pen and herdand for each milking shift.

– Daily running inventory of feeds on the dairy.


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Notes

1. Dutton, C. 1998. Feed Shrink at Chaput FamilyFarms. In: Proceedings from the Dairy Feeding Sys-tems Management, Components, and NutrientsConference, NRAES-116.

2. Gaige, M. 1998. Shrivel the Shrink. In: DairyToday, Sept. 1998.

3. Lammers, B.P., D.R. Buckmaster, and A.J. Hein-richs. 1996a. A simple method for the analysis ofparticle sizes of forage and total mixed rations. J.Dairy Sci. 79:922.

4. Lammers, B., J. Heinrichs and D. Buckmaster.1996b. Method helps in determination of forage,TMR particle size requirements for cattle. Feed-stuffs 68:41:14.

5. Grant, R.J., V.F. Colenbrander, and D.R. Mertens.1990. Milk fat depression in dairy cows: Role ofparticle size of alfalfa hay. J. Dairy Sci. 73:1823.

6. Hinders. R. 1996. MUN indicates adequacy of pro-

tein, carbohydrates in milking cow rations. Feed-stuffs 68:20:11.

7. Heinrichs, J. 1996. Evaluating forages and TMRsusing the Penn State Particle Size Separator. PennState Cooperative Extension Service. DAS 96-20.

8. Mertens. D.R. 1997. Creating a system for meet-ing the fiber requirements of dairy cows. J. DairySci. 80:1463.

9. Rippel, C.M., E.R. Jordan, and S.R. Stokes. 1998.Evaluation of particle size distribution and rationuniformity in total mixed rations fed in North-cen-tral Texas. Prof. Anim. Sci. 14:44-50.

10. Staples, C.R., W.W. Thatcher, C.M. Garcia-Bojalil, and M.C. Lucy. 1992. Nutritional influ-ences on reproductive function. In: Large DairyHerd Management, ed. H. H. Van Horn and C. J.Wilcox.

References:

– Weekly MUN for each pen, the herd, and foreach milking shift.

The six items calculated above can be printed innumerical format or graphically displayed. Figures1-4 provides examples of data output. The spread-sheet also calculates daily feed inventory based onwhat was fed. Monitoring this data on a monthlyand weekly basis provides timely information formanagement decisions. This information will helpa manager quickly discover changes in such thingsas forage quality, labor problems in the parlor,feeding problems, and transition cow problems.

SummaryMany dairies have the ability to track and moni-

tor feed and milk production. However, too oftenthe data is underutilized. Considering the eco-nomic impact of this information, effective utiliza-tion is critically important. It is necessary to use aspreadsheet such as the once described here orobtaining commercial software to fully utilize thedata generated. Obtaining group information on adaily and weekly basis provides timely informationdairy producers need to make routine managementdecisions.

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Notes

on farm tools - western dairy management conference

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