Progress report for SW21-927
Project Information
In 2019, there were over 3.6 million dairy cows in the western U.S. [1], making dairy a dominant sector of the region’s agriculture. Organic milk production is becoming more prevalent, with organic products increasing from 1.92% to 4.38%, of all milk products sold, between 2006 and 2013 [2]. Organic milk companies promote their product based upon the health and environmental benefits of pasture-raised milk [3], and require at least 120 grazing days per year for both lactating cows and replacement heifers [4]. However, milk production is 32% lower in dairies using 75-100% of pasture-based forage compared to those using 25% or less pasture forage [5]. Insufficient dry matter intake (DMI) of pasture by dairy cows is a major factor limiting milk production [6], and it has been observed that some dairy breeds are more efficient grazers than others [7-9]. Therefore, improved feed efficiency - the relative ability of a cow to convert feed into growth or milk, is increasingly important in pasture-based dairy systems [10, 11].
This proposal expands our previous Western SARE projects that evaluated how grass-legume pastures with different energy, protein, and condensed tannin (CT) levels affected beef steer and Jersey heifer growth performance (SW10-088 and SW17-046). Those studies found that forage characteristics only explained 50% of the variation in DMI and average daily gain (ADG) [12, 13]. Furthermore, producers on our research team asked about the influence of dairy breed on performance within their pasture-based systems. Thus, we propose to investigate the effects of dairy breed, pasture type, and breed-by-pasture type interactions on DMI, feed efficiency, and environmental and economic sustainability of heifers raised in pasture-based systems. A multi-disciplinary team will conduct this research at the Utah State University Lewiston Pasture Research Facility where replicated pastures of grass monoculture (MONO) or grass-birdsfoot trefoil (MIXED) are established. Four breeds of dairy heifers (Holstein, Jersey, Holstein/Jersey crossbreds, and 3-way Holstein/Montbeliarde/Viking Red crossbreds [i.e., ProCROSS]) will be compared as they rotationally graze pasture treatments (MONO vs MIXED) throughout the summer. Producer cooperators will provide dairy heifers and participate in DMI and forage evaluation of pastures on their dairies.
Outreach is a major component of the proposal with contributions from university extension and eOrganic. This program will integrate traditional outreach with electronic media and be guided by input from producer cooperators and similar stakeholders. The primary targeted audiences will be dairy producers, Extension educators, NRCS personnel, and other professionals who advise farmers/ranchers. Emphasis will be on providing opportunities to train these individuals in the local area, statewide, and across the western region.
These objectives are in direct response to stakeholder feedback and are expected to identify differences in feed efficiency. It is anticipated that some breeds will respond to both high quality (MIXED) and lesser quality (MONO) pastures, whereas, some breeds will respond only to high-quality pastures. At the end of the research, we expect to provide producers with solid scientific AND economic data on pasture-based dairy heifer development for a variety of pasture-types and dairy breeds.
RESEARCH OBJECTIVES
Our long-term goal is to enhance the sustainability of pasture-based dairy. The central hypothesis of the current proposal is that genetic background (“breed”) will have a significant influence on the physiological responses of dairy heifers grazing grass/birdsfoot trefoil (MIXED) or grass-only (MONO) pastures, and these differences will be reflected in measures of environmental and economic sustainability. Specific research objectives are:
1: Determine the influence of dairy breed on DMI and feed efficiency in heifers grazing either grass-monoculture or grass/birdsfoot trefoil mixed pastures. We hypothesize that DMI and feed efficiency will differ across breeds but will be greater in MIXED pastures compared to MONO pastures for all breeds. We also anticipate that some breeds will have greater feed efficiency relative to other breeds on lesser quality pastures.
2: Evaluate the influence of dairy breed on nutrient leaching when grazing either grass-monoculture or grass/birdsfoot trefoil mixed pastures. We hypothesize that animals grazing the pastures with the CT-containing birdsfoot trefoil (MIXED) will have improved nitrogen (N) utilization as measured by reduced N in groundwater leachate compared to those grazing grass monocultures, and that greater feed efficiency will be associated with greater N-utilization efficiency.
3: Ascertain the influence of dairy breed on the economic sustainability of pasture-based heifer development. We hypothesize that heifer breed/pasture type combinations with relatively greater feed efficiency will have greater annual net financial impact and reduced payback period.
EDUCATION OBJECTIVES
As part of our long-term goal to enhance the sustainability of pasture-based dairy, we will implement an innovative and impactful multi-faceted extension/outreach program on the production and environmental benefits of pasture-based dairy heifer development. Pasture-based milk production is a fast-growing segment of agriculture in the Intermountain West and this project will bridge the gap in urgently needed information regarding breed and pasture-type differences. We have devised a solid research plan that will generate a wealth of highly novel data across a very broad and multidisciplinary research spectrum. The results from this study will be of value to the scientific and pasture-based dairy farming communities in general, but our research/outreach effort is designed to translate this information to make a real difference to individual dairy farmers and their families throughout the Intermountain West. Specific education objectives are:
1: Implement an innovative and impactful multi-faceted extension/outreach program for producers and professionals in the local area, statewide, and across the western region on the production, environmental, and economic benefits of grass/legume grazing for pasture-based dairy production systems.
2: Create and pilot the Intermountain Regional Dairy Grazing School.
3: Produce and publish scholarly and educational products.
See attached pdf for a picture of the Excel Gantt chart that will be used for this research project.
Cooperators
- - Producer
- - Producer
- (Researcher)
- (Educator)
- (Researcher)
- (Researcher)
- - Producer
Research
The central hypothesis of the current proposal is that genetic background (“breed”) will have a significant influence on the physiological responses of dairy heifers grazing grass/birdsfoot trefoil (MIXED) or grass-only (MONO) pastures, and these differences will be reflected in measures of environmental and economic sustainability.
OBJECTIVES
Our long-term goal is to enhance the sustainability of pasture-based dairy. The central hypothesis of the current proposal is that genetic background (“breed”) will have a significant influence on the physiological responses of dairy heifers grazing grass/birdsfoot trefoil (MIXED) or grass-only (MONO) pastures, and these differences will be reflected in measures of environmental and economic sustainability. Specific objectives are:
1: Determine the influence of dairy breed on DMI and feed efficiency in heifers grazing either grass-monoculture or grass/birdsfoot trefoil mixed pastures. We hypothesize that DMI and feed efficiency will differ across breeds but will be greater in MIXED pastures compared to MONO pastures for all breeds. We also anticipate that some breeds will have greater feed efficiency relative to other breeds on lesser quality pastures.
2: Evaluate the influence of dairy breed on nutrient leaching when grazing either grass-monoculture or grass/birdsfoot trefoil mixed pastures. We hypothesize that animals grazing the pastures with the CT-containing birdsfoot trefoil (MIXED) will have improved nitrogen (N) utilization as measured by reduced N in groundwater leachate compared to those grazing grass monocultures, and that greater feed efficiency will be associated with greater N-utilization efficiency.
3: Ascertain the influence of dairy breed on the economic sustainability of pasture-based heifer development. We hypothesize that heifer breed/pasture type combinations with relatively greater feed efficiency will have greater annual net financial impact and reduced payback period.
METHODS AND MATERIALS
Objective 1. Determine the influence of dairy breed on DMI and feed efficiency:
Updated pasture treatments, grazing, and dry matter intake (DMI) and feed efficiency (FE) methods used are described below and in detail in Greenland, M.S.; Waldron, B.L.; Isom, S.C.; Fonnesbeck, S.D.; Peel, M.D.; Rood, K.A.; Thornton, K.J.; Miller, R.L.; Hadfield, J.A.; Henderson, B., et al. Dry matter intake and feed efficiency of heifers from 4 dairy breed types grazing organic grass and grass-birdsfoot trefoil mixed pastures. J Dairy Sci 2023, 106, 3918-3931, doi:10.3168/jds.2022-22858.
- (link to the paper here: Dry matter intake and feed efficiency of heifers from 4 dairy breed types grazing organic grass and grass-birdsfoot trefoil mixed pastures - ScienceDirect)
Pasture Treatments: This experiment was conducted at the Utah State University Intermountain Pasture Research Farm (41°57'01.85" N, 111°52'15.75" W, elev. 1,369 m, 46 cm annual precipitation and 56.1 precipitation d/year) located near Lewiston, Cache County, UT, USA. The soils at the site are a Kidman Fine Sandy Loam and Lewiston Fine Sandy Loam (both are Coarse-loamy, mixed, superactive, mesic Calcic Haploxerolls). This semiarid Central Great Basin region of the western USA is characterized by hot, dry summers with most of the annual precipitation as snowfall. The precipitation from winter-time snowfall is stored in reservoirs and used for irrigated crop production (Utah Climate Center, 2018).
The study utilized previously established pastureland described by Rose et al. (2021; SW17-046). For this study, fencing was arranged on this established pastureland to accommodate three randomized complete blocks of a 4 × 2 factorial design with 4 levels of dairy breed-type and 2 levels of pasture-type [i.e., grass monoculture (MONO) and grass-BFT mixture (MIXED)]. This pastureland had been established with endophyte-free tall fescue (‘Fawn’, TF), meadow bromegrass (‘Cache’, MB), high-sugar orchardgrass (‘Quickdraw’, OG), and high-sugar perennial ryegrass (‘Amazon’, PR) in grass monocultures or as binary mixtures with BFT (‘Pardee’). Within each of three blocks, our 8 (i.e., four MONO and four MIXED) pastures (on average 0.42 ha each) were established by fencing perpendicular across the existing grass monoculture and grass-BFT strips such that each MONO pasture included all grasses, and each MIXED pasture included all grass-BFT combinations. Each of the 8 pastures were further divided evenly into 10 paddocks with a single strand of charged poly-wire.
The pastures had been managed using organic dairy grazing protocols since 2015, so no treatments received commercial fertilizer or any pesticides. However, approved organic sources of nitrogen were applied. Prior to the current study in 2017 and 2018, Chilean nitrate (sodium nitrate, 15-0-2, N-P-K; SQM) was applied at 91 and 28 kg N/ha for monocultures and mixtures respectively. In 2019, Chilean nitrate was applied at 28 kg N/ha in April to all treatments (both MONO and MIXED). In 2020 and 2021, Chilean nitrate was not available, so Nature Safe (feather, meat, and blood meal, 13-0-0 N-P-K; Darling Ingredients Inc. Irving, TX) was applied at 33 kg N/ha in April to all treatments. Pastures were sprinkler irrigated every 14 d from mid-May to September such that they received 7.6 cm of total water/irrigation period (i.e., precipitation + irrigation; ~100% grass evapotranspiration replacement).
Heifer Grazing: For each of 3 grazing seasons (2019, 2020, and 2021), groups of 4 pre-pubertal dairy heifers (e.g., testers) from each of 4 dairy breed-types were considered an experimental unit and were randomly allocated to each pasture (Total testers = 288 heifers = 24 experimental units/year [i.e., 3 blocks × 4 breed-types × 2 pasture-types] × 4 heifers × 3 years). The 4 breed-types of dairy heifers used in this experiment were Jersey, Holstein, Holstein-Jersey crossbreds, and three-breed rotational crossbreds of Montbéliarde-Swedish Red-Holstein (in the 2019 and 2021 season) or of Montbéliarde-Viking Red-Holstein (in 2020, this crossbred with Viking Red is also marketed as ProCross© by Coopex Montbeliarde, Roulans, France and Viking Genetics, Randers, Denmark). The heifers were leased from various commercial dairies in Utah and Southern Idaho and returned to their owners at the end of the summer grazing. Heifers were on average 7.4 ± 0.8 months old and 32% mature body weight (BW) at the beginning of the trial. Animals were cared for in accordance with the guidelines of the Institutional Animal Care and Use Committee at Utah State University (IACUC protocol #10063).
Grazing was initiated on the same calendar date for all treatments, when most grasses had reached the E0 stem elongation stage (Moore et al., 1991) and were approximately 25 cm in height (e.g., mid-May). A fixed stocking rate of 4 heifers/pasture was used throughout the study; however, the 3 blocks had slight differences in size (0.47, 0.44, and 0.35 ha for block 1, 2, and 3 respectively) resulting in stocking rates of 8.5, 9.1, and 11.4 heifers/ha for blocks 1, 2, and 3, respectively. This stocking rate was predetermined based upon heifer utilization previously reported for this pastureland (Rose et al., 2021), and with the objective to ensure excess herbage (e.g., high herbage allowance) in order to emphasize the nutritive value effects on DMI and heifer performance (Baudracco et al., 2010, Sollenberger and Vanzant, 2011). There was no herbage target end-points for grazing a particular paddock. Rotational stocking was used with a set stocking period of 3.5 d, followed by a rest period of 31.5 d for each of the 10 paddocks, such that the entire rotation cycle was 35 d. There were 3 rotation cycles each year, thus, heifers were on pasture for a total of 105 d (11 May to 24 August 2020; 17 May to 30 August 2021). However, in 2019, heifers were on pasture for a total of 118 d (29 May to 24 September 2019), when due to excessive herbage growth all heifers in all treatments were moved to overflow pastures of the appropriate type (i.e. MONO or MIXED) towards the end of rotation 1 to allow the pastures to be mechanically harvested and allowed to regrow prior to beginning the regular second rotation.
Herbage Evaluation: Pre-grazing and post-grazing herbage samples were collected just prior to (pre-) and after (post-) heifer relocation to the next paddock, by hand-clipping two random quadrats (0.25 m2)/paddock to a stubble height of 3.8 cm. Post-grazing samples were taken adjacent to the pre-grazing samples unless the heifers defecated or laid on the area. Samples were put in separate paper bags and dried at 60°C for at least three d before being weighed to determine quadrat herbage mass. Pre- and post-grazing standing sward heights (cm) measured with a meter stick and compressed sward heights (cm) measured with a rising plate meter (RPM) were taken directly on each unclipped quadrat. At the same time, we found the mean of 30 RPM measurements taken in a ‘w’ pattern throughout each paddock (two 30-RPM-measurement means were taken in 2020 and 2021). Individual quadrat herbage mass measurements were regressed against respective RPM measurements, forcing a zero intercept as described by Dillard et al. (2016), to develop herbage mass prediction equations within each grass species and pasture-type (R2 for these regressions ranged from 0.80 to 0.89). Paddock-based pre- and post-grazing herbage mass were then predicted using these equations and the 30-RPM-measurement mean herbage height. In addition to pre- and post-grazing RPM measurements, one (2019) or two (2020 and 2021) 30-RPM measurement means (in the ‘w’ pattern) were taken at 24 and 48 h after grazing initiation in each paddock and fitted to their respective regression equations to determine herbage mass at these time points. After heifers finished grazing a paddock, excess herbage was mowed to a stubble height of 12 cm and clippings removed. In 2020, paddocks were mowed after all rotations, and in 2021, paddocks were mowed after rotations 1 and 2 (stubble height after rotation 3 was equal to or less than 12 cm). Immediately after mowing, a 30-RPM-measurement mean was taken in each paddock, followed by another at 24 h and 48 h after mowing. Herbage mass (HM) was estimated using these RPM measurements and the appropriate regression equation. Daily herbage accumulation (kg/ha per day) (e.g., regrowth) was then estimated as the increase in HM between these timepoints. In 2019, no regrowth RPM measurements were taken, so daily herbage accumulation was estimated as the mean of the 2020 and 2021 regrowth values on a pasture-type × rotation basis. Herbage allowance (HA) (kg of herbage/kg of BW) was calculated at the beginning of each rotation cycle. Estimates of potential grazing efficiency (i.e., the proportion of herbage assumed consumed by livestock compared with herbage that disappears due to other activities) as effected by herbage mass were calculated as in Rose et al. (2021) by inputting modified HA (on a per d basis) in a regression equation developed from the Allison et al. (1982) comparisons of herbage allowances and grazing efficiencies (i.e., grazing efficiency, % = 105.11 – 463.30 × modified HA; R2 = 0.93; Mean 92, StdDev 6.5, range 100 to 64).
Dried herbage samples were be ground to pass through a 1-mm screen using a Thomas Wiley Laboratory Model 4 mill (Arthur H Thomas Co, Swedesboro, NJ, USA), and scanned with a Foss XDS near-infrared reflectance spectroscopy (NIRS) instrument (Foss, Eden Prairie, MN, USA) to determine nutritive value of the feed on offer. The 2018 NIRS Forage and Feed Testing Consortium (Hillsboro WI, USA) equations were used to predict nutritive value, resulting in estimates of crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL), in vitro true digestibility (IVTD), NDF digestibility (NDFD), fatty acids (FA), water soluble carbohydrates (WSC), and ash. Net energy for maintenance (NEm) and net energy for gain (NEg) were calculated as as per Saha, et al. (2010) (e.g., using TDN; not ADF-based). In addition, the proportion of BFT and condensed tannin concentrations in each clipped sample was determined with NIRS using the methodology described by Rose et al. (2021).
Heifer performance and Dry-Matter Intake: All heifers were individually weighed at the beginning of the study, and after each 35-d rotation cycle to determine BW and ADG. The total BW of heifers in each experimental unit were recorded and converted to standard animal units (AU) to equalize all breed-type treatments over the grazing season and years. Standard AUs are defined as a heifer at 40% of mature BW for each breed-type, as determined by published growth charts and calculated on a metabolic weight basis (Allen et al., 2011). Apparent DMI was based upon herbage disappearance and estimated as the difference between pre-grazed and post-grazed HM (kg/ha) with adjustments made for both daily herbage accumulation and grazing efficiency as: DMI per grazing period = {[pregrazing HM = (daily herbage accumulation x 3.5 d of grazing)] - postgrazing HM} x grazing efficiency x paddock size. DMI was reported as daily DMI (i.e., divided by 3.5 days) per 100 kg of heifer BW and per AU. Daily NDF, net energy for maintenance (NEm), and net energy for gain (NEg) intake were estimated by multiplying DMI by the proportion of these nutritive components in the herbage. Lastly, grazing adaptation, or how quickly heifers responded to a new paddock and what happened as they stayed on that paddock, was estimated by calculating a grazing rate. Grazing rate (kg DMI/h) was calculated using the above DMI equation, except herbage disappearances were based on the intervals between 0, 24, 48, and 84 hours of grazing for each paddock (e.g., 0 to 24 h intake in kg DMI/h).
Feed Efficiency: Feed efficiency, the relative ability to convert nutrients into growth, was evaluated as FCE (ratio of weight gain to DMI), energy conversion (ratio of weight gain to NEm and NEg intake), and residual feed intake (RFI; the difference between actual intake and intake predicted from growth performance). Because DMI was not estimated for each individual heifer and heifer BW was only measured every 35 d, all feed efficiency estimates were based upon average performance of the four tester heifers in an experimental unit for each rotation of grazing. Feed conversion efficiency was estimated as BW change per rotation divided by the sum of daily DMI for that entire 35 d rotation. Higher numbers indicated better efficiency (Sainz and Paulino, 2004, Smith et al., 2010). Similarly, energy conversion was estimated by substituting NEm and NEg intake for DMI as the divisor. It is noted that FCE and energy conversion ratios cannot be corrected on an AU basis (e.g., because AU units cancel out when dividing) so are only reported on a per 100 kg BW basis.
Residual feed intake was estimated as the difference between actual intake and intake predicted based upon growth performance, with lower RFI values indicative of higher efficiency since the expected weight gain is obtained with less intake (Sainz and Paulino, 2004). Predicted DMI was determined by first creating separate multiple regression models for each year by regressing each experimental unit grazing rotation average DMI on corresponding ADG and mid-rotation BW0.75 (Williams et al., 2011, Waghorn et al., 2012). The models were then fit to each experimental unit × rotation × year data point as: Y = β0 + β1X1 + β2X2 + ε, where Y is expected DMI, β0 is the intercept and β1 and β2 are the partial regression coefficients from the regression models, X1 is observed mid-rotation metabolic BW (i.e., BW0.75), X2 is observed ADG, and ε is the residual error. Inasmuch as the beginning % mature BW (%MBW) for Holsteins were lower compared to the other three breed-types, this procedure (on an AU basis) was repeated using beginning %MBW and beginning %MBW2 as covariates in the regression equation similar to the use of heifer age by Williams et al. (2011). However, since AU already attempts to standardize differences among years and breed-types, the REG procedure of SAS (SAS Institute Inc., Cary, NC, USA) with the ‘BACKWARD’ selection option was used (i.e., fits the full model and then eliminates regression variables that do not contribute to the model, we used a conservative criterion of P=0.20) to reduce likelihood of over-fitting expected DMI models. Because RFI results varied depending upon whether on a 100 kg BW, AU, or AU with beginning %MBW covariate basis, all three estimates were reported.
Other Heifer Data: All heifers were weighed, body condition scored, and had blood, fecal, and rumen samples drawn at the initiation of grazing, and at the end of every 35 day grazing cycle thereafter. Blood work will entail an assay for insulin-like growth factor 1 (IGF1; produced mainly by liver and is the primary mediator of GH production and release). Blood will be collected from the coccygeal vein into heparinized vacutainer tubes and stored on ice until processed. Blood samples will be analyzed for IGF-I in duplicate using the Human IGF-I Quantikine ELISA Kit (SG100; R&D Systems) by following manufacturer-recommended procedures [30,31]. Blood samples were taken from the jugular vein into red-top vacutainer tubes and then stored on ice before being divided into two subsamples with one subsample centrifuged to remove the serum. Serum was then stored in a -20°C freezer until assayed. The whole blood subsample was stored at 4°C until used for DNA extraction. In 2021, ear notches were used for DNA analysis Ear notches were taken from the heifers at the beginning of study. One ear from each heifer's ear was clipped resulting in an approximately 0.5 cm diameter circle of each ear tissue. Each ear notch was placed in a labeled tube and was stored at -20 until DNA extraction was performed.
Rumen fluid was collected seven days after weight collection days (i.e. on days 7, 42, 77, and 112) to avoid complications associated with animal fasting on the regular weighing and sample collection days. Rumen fluid samples were collected using an esophageal tub, with approximately 100 mL of fluid collected from each animal. Of this sample, 50 mL was placed directly (fluid and associated ingesta/particulate matter) into a 50 mL conical tube for microbiome analysis, while the rest was filtered to remove particulates and placed in another 50 ml conical tube. Both tubes were stored in -80°C freezer until needed. Excess rumen fluid was discarded, and instruments rinsed with clean water between each animal. Rumen ammonia and volatile fatty acids concentrations were determined. Rumen microbial DNA was isolated and sequenced.
Blood urea nitrogen was analyzed in triplicate for each animal using a commercially available kit that provided compatibility with bovine serum (Urea Nitrogen (BUN) Colorimetric Detection Kit; Thermo Fisher Scientific; Waltham, MA, USA). The included kit protocol was strictly followed. Briefly, 40 µL of serum was added to deionized water to create a 1:10 dilution. Using a provided Urea Nitrogen Standard, standard solutions were created according to the kit protocol with concentrations ranging from ten to zero mg/dL. Using the provided 96 well plate, 50 microliters of standards (in duplicate) and diluted serum samples (in triplicate) were placed into appropriate wells. Seventy-five microliters each of two color reagents (Reagent A and then Reagent B) were placed into all wells. Plates were then covered to protect from light and allowed to incubate at room temperature for 30 minutes. Plates were read using a SYNERGY H1 microplate reader (BIOTEK; Winooski, VT) and GEN 5 2.9 absorbance reading software at a wavelength of 450 nm. All three sample values for each animal were then averaged and that outcome became the heifer’s serum BUN value for that timepoint.
Fecal samples were refrigerated at 4° C after collection. All fecal floats were analyzed in our laboratory via the Wisconsin Sugar Flotation Method (University of Pennsylvania School of Veterinary Medicine, Dr. Thomas Nolan. Copyright 2006) within 48 hours of collection. Briefly, 10 ml of Sheather’s solution (3.72 M sucrose in water) was added to three grams of feces and mixed thoroughly. This mixture was then put through a strainer and the fluid portion was placed in a 15 ml tube and centrifuged for four minutes at 2008 x g. The test tube was then filled completely with Sheather’s solution and a cover slip was placed on the meniscus and left for five minutes. The cover slip was then removed and placed on a glass slide. Parasitic eggs were then counted as the slide was viewed under a microscope with a magnification of 100x.
In addition to the pasture grazing, three feedlot replicates of three heifers per breed were fed a TMR formulated for an ADG target of 0.8 kg/day, and feed offered and refused each day weighed to calculate TMR DMI (only in 2019 and 2020). Heifer growth, herbage physical and chemical characteristics, DMI, and feed efficiency data was analyzed using the Proc Mixed procedure of SAS, and the effects of dairy breed and pasture-type treatments and their interactions reported. Heifer growth and DMI comparisons will be made between pasture versus TMR treatments.
Objective 2. Evaluate the influence of dairy breed on nutrient leaching: Soil water (leachate) nitrogen will be monitored by means of 90-cm suction-cup lysimeters (below the root zone). Leachate will be collected every week during the growing season, and as much as possible throughout the early spring and late fall. The leachate will be analyzed for nitrate-nitrite concentration using QuickChem Method 10-107-04-1-C on the Lachat Auto-analyzer. Leachate concentration and volume will be used to determine total leachate N.
To monitor any potential buildup of soil nitrogen, soil samples to a depth of 30 cm will be collected prior to grazing, and in the fall after the growing season each year. To account for the variability that may result from grazing, ten soil cores will be taken in each plot and combined to make a composite soil sample. Composite soil samples will be analyzed for available nitrogen (NO3-N) using potassium chloride on the Lachat Auto-analyzer, QuickChem Method 10-107-04-1-C.
Nutrient cycling and N-use efficiency will be evaluated by studying the relationships between herbage N intake (Object. 1) with N loss in leachate and the soil (Object. 2) and fecal, urine urea, and blood urea N (data obtained separate from this proposal). Breed effect on N leaching and N-utilization efficiency when grazing grass monocultures vs grass-BFT mixtures will be determined and differences reported. Data will be analyzed using SAS PROC Mixed with Repeated Measures.
Objective 3. Ascertain the influence of dairy breed on the economic sustainability of pasture-based heifer development: Partial budgeting techniques will be used to determine the cost differences from each heifer development program. Costs associated with procuring and feeding the different breeds of heifers will be determined. These costs will be subdivided for each of the breeds according to pasture-type (MONO or MIXED) and TMR-fed. The cost of the TMR feeds will be based on the last 5-years average costs to minimize bias in yearly feed prices.
The partial budgets will be used to quantify the impact of heifer performance, under each pasture-type and TMR, on the economic value of the four breeds following the methodology described by Feuz, et al. [29]. The last 5-years prices will be used to value the dairy heifers. In brief, price comparisons for the value of an open heifer versus a bred heifer and for different weight heifers will be made. However, breeding and subsequent monitoring of conception rates of the tester heifers will not be part of this study. Rather, conception rates for the economic analysis will be based upon assumptions drawn from previously published results. Based upon previous results [28], a single-service conception rate using gender-sorted semen of 53% for the TMR-fed heifers will be assumed. As per current available literature [43], all pasture-fed heifers will be penalized a 5% conception rate decrease compared to TMR-fed heifers. Furthermore, as per Hayes, et al. [44] heifers on MONO treatments with lesser body weight gain compared to their respective MIXED cohorts will be penalized an additional 5% decrease in conception rate.
Ultimately, the partial budgets will be used to determine the most profitable breed/development method (i.e., pasture-type and TMR) of raising dairy heifers. Actual costs and revenue differences for each breed and alternative pasture-based program will be combined to determine the breed and program that offers the best net annual financial impact.
PROGRESS REPORT.
Progress and to-date results are reported by Objective. The most recent progress report appears first under each objective, with previous reports still included and designated by date. The latest tables and graphs are numbered consecutively beginning from the previous report. However, outdated tables and graphs may be replaced when noted with the published version once the research has been published.
Notable revisions in the January 2024 report:
- A new 'Milestone Table' has been added that gives anticipated completion dates for each component within each objective.
- With the near completion of Objective 1, the Methods and Materials of objective 1 have been completely revised to reflect what happened. In addition, a 'Lessons Learned' section for each sub-component nearing completion within the progress report.
- Shortly after the initiation of this research, results from our previous Western SARE project (SW17-046) indicated that insulin-like growth factor 1 (IGF1) was primarily affected by differences in the amount of time each heifer was fasted prior to weighing and blood collection (12 to 18 hours depending upon when they crossed the squeeze chute). Therefore, we replaced this assay with an ammonia concentration in the rumen fluid assay that had been shown to be related to diet. The Materials and Methods have been updated to reflect this change using
strikethroughto show text that no longer applies and italics to show the new text.
- Though the primary aim proposed in objective 1 was to investigate DMI and feed efficiency, the complexity and labor involved in a grazing study necessitates getting all the information possible from the livestock samples we were collecting. Thus, though blood urea nitrogen (BUN), fecal egg count (FEC), rumen microbiome analysis, and heifer genome analysis were not part of the original proposal for SW21-97, we were able to leverage the blood, rumen, and fecal samples from SW21-927 to get these extra data sets. These additional investigations are now in our Objective 1 progress report and are being used to help complete two additional M.S. theses in the USU Animal, Dairy and Veterinary Sciences Dept (for a total of four M.S. theses from this research project). These expanded datasets and research goals will give us a better overall picture of the effects of breed and pasture-type on growth performance. It should be noted that the rumen ammonia and VFA concentration results (which replaced the IGF1 assay) have been combined with the microbiome data and comprise one M.S. thesis. This combined and expanded data set will help us have a better understanding of livestock performance variation when grazing different pastures. The heifer genome analysis which comprises the other additional M.S. thesis, will provide preliminary data on how genetic variation within and among breeds affects dairy heifer growth performance when grazing different types of pastures.
- The blood (BUN and genomic DNA), fecal samples (FEC), rumen fluid, and ear-notch (genomic DNA) sampling, processing, and analysis have been added to the Materials and Methods using the italics and strikethrough as described previously.
- Review of the previous report resulted in some confusion about breeding and conception rate data used for the economic analysis. This proposal never intended to follow these tester heifers through the breeding and conception phase. Instead, we proposed to use previously published data to make assumptions about how these pastures would affect conception rate. This is the same methodology we used in one of our publications from a previous WSARE project SW17-046 (The effects of organic grass and grass-birdsfoot trefoil pastures on Jersey heifer development: Heifer growth, performance, and economic impact - ScienceDirect).
- This has been clarified in the Materials and Methods section using the italics and strikethrough as described previously.
Milestone Table for SW21-927: Dry Matter Intake and Feed Efficiency of Four Dairy Breeds in a Pasture-Based Heifer Development Program.
|
Objective/sub-objective |
Milestone |
Status |
Anticipated Completed Date |
Team Lead |
|
1. Determine the influence of dairy breed on DMI and feed efficiency |
|
|
|
|
|
a. Heifer growth performance |
Field data collected for 3 yrs (e.g., body wt, body condition score, rumen samples) |
Completed |
September 2021 |
Isom |
|
|
Ammonia and VFA in rumen fluid assay |
Completed |
December 2021 |
|
|
|
Growth and rumen fluid statistical analyses |
Completed |
October 2023 |
|
|
|
Manuscript |
Ongoing |
March 2024 |
|
|
|
eOrganic webinar |
|
June 2024 |
|
|
|
Fact sheet |
|
August 2024 |
|
|
|
|
|
|
|
|
b. DMI and feed efficiency (FE) |
Field data collected for 3 yrs (e.g., herbage samples collected) |
Completed |
September 2021 |
Waldron |
|
|
Forage quality analysis |
Completed |
January 2022 |
|
|
|
DMI and FE calculations |
Completed |
January 2022 |
|
|
|
DMI and FE statistical analyses |
Completed |
February 2022 |
|
|
|
DMI and FE Manuscript |
Published |
January 2023 |
|
|
|
eOrganic webinar |
Completed |
May 2022 |
|
|
|
|
|
|
|
|
c. Rumen microbiome DNA analysis1 |
Rumen microbial DNA isolation and sequencing |
Completed |
September 2021 |
Isom |
|
|
Microbiome population/DNA analysis |
Completed |
June 2023 |
|
|
|
Statistical analyses |
Ongoing |
February 2024 |
|
|
|
Manuscript |
|
August 2024 |
|
|
|
|
|
|
|
|
d. Heifer DNA analysis1 |
Blood and/or ear notch samples collected for 2 years |
Completed |
September 2021 |
Isom |
|
|
DNA extractions |
Completed |
December 2023 |
|
|
|
DNA commercial lab analysis/Index scores |
Ongoing |
February 2024 |
|
|
|
Statistical analyses |
|
March 2024 |
|
|
|
Manuscript |
|
October 2024 |
|
|
|
|
|
|
|
|
2. Evaluate the influence of dairy breed on nutrient leaching |
|
|
|
Miller |
|
|
Leachate and soil samples of 4 breeds collected for 3 yrs |
Completed |
May 2022 |
|
|
|
Fecal and Urine samples of 4 breeds collected for 3 years |
Completed |
September 2021 |
|
|
|
Urine, fecal, and leachate samples analyzed for available N and nutrient cycling for Jersey heifers – Reference point for 4-breed study |
Ongoing |
March 2024 |
|
|
|
Jersey heifer nutrient cycling reference point published in peer-reviewed journal |
|
November 2024 |
|
|
|
Leachate from 4 breeds analyzed for nitrate-nitrite |
|
December 2024 |
|
|
|
Soil samples from 4 breeds analyzed for available N |
|
June 2025 |
|
|
|
Nutrient cycling and statistical analyses of 4 breeds |
|
December 2025 |
|
|
|
Manuscript |
|
December 2025 |
|
|
|
Webinar |
|
January 2026 |
|
|
|
Fact sheet |
|
February 2026 |
|
|
|
|
|
|
|
|
3. Ascertain the influence of dairy breed on the economic sustainability of pasture-based heifer development |
|
|
|
Larsen |
|
|
Partial budgets |
Ongoing |
February 2024 |
|
|
|
Calculate economic values: impact of performance and pasture type |
Ongoing |
March 2024 |
|
|
|
Statistical analyses of net annual financial impact |
|
March 2024 |
|
|
|
Prepare Tables, etc for inclusion in heifer growth manuscript |
|
March 2024 |
|
|
|
Fact sheet |
|
April 2024 |
|
1Not part of the proposal for SW21-97. However, the data and samples from SW21-97 are being leveraged to help complete these two sub-objectives as part of two M.S. theses in the USU Animal, Dairy and Veterinary Sciences Dept.
Objective 1: Determine the influence of dairy breed on DMI and feed efficiency
Grazing dry matter intake and feed efficiency
January 2024
- This component of the study was previously completed. The published interpretative summary and abstract, which summarize the results from this study, as well as 'lessons learned' have been added to this report.
-
Interpretative Summary: Decreased dry-matter intake (DMI) of pasture by dairy cattle limits growth and milk production, however, pasture type and dairy breed may alter DMI. In a comparison of four dairy breed-types grazing grass or grass-legume mixtures, heifers grazing grass-legume mixtures had greater DMI than those grazing grass-only pastures, but heifers on grass-only pastures were twice as efficient at converting the feed to growth. Holsteins had the greatest overall DMI, but Jerseys had the most favorable feed efficiency. However, the lack of interactions between breed-type and pasture-type indicated that no breed-type was better adapted to pastures with contrasting levels of nutritive value.
- Abstract: Insufficient dry matter intake (DMI) of pasture by dairy cattle is a major factor limiting growth and milk production; however, it has been hypothesized that some dairy breeds may be more efficient grazers than others. This study was conducted to determine whether dairy breed types differ in DMI and feed efficiency when grazing either grass monoculture or grass-legume mixed pastures. The experiment compared 4 different dairy breed types (Jersey, Holstein, Holstein-Jersey crossbreds, and Montbéliarde-Swedish Red-Holstein 3-breed crossbreds) and 2 levels of pasture type [grass monoculture (MONO) and grass-birdsfoot trefoil (BFT) mixture (MX)] for a total of 8 treatments. Pastures were rotationally stocked with groups of 4 prepubertal heifers for 105 d for 3 yr, and DMI was determined from herbage disappearance. Feed conversion efficiency (FCE) and residual feed intake (RFI) were then derived from DMI, and heifer body weights (BW) and normalized to animal units (AU) as 40% metabolic mature BW of the corresponding dairy breed type to account for inherent differences in size and growth rates. We observed differences in DMI and feed efficiency among breed types and between pasture types. On average, Holsteins had the greatest overall DMI (4.4 kg/AU), followed by intermediate DMI by the crossbreds (4.0 kg/AU), and Jerseys had the least DMI (3.6 kg/AU). Heifers grazing MX pastures had on average 22% greater DMI than those grazing MONO, but heifers on grass monocultures were more efficient in converting DMI to BW gain (i.e., RFI/AU of 0.27 and−0.27, respectively; more negative RFI numbers indicate less DMI to achieve the expected gains). Overall, Jerseys had the most favorable feed efficiency; however, ranking of Holsteins and crossbreds depended upon the feed efficiency metric. This study is one of the first to compare the interaction of dairy breed and pasture quality on grazing efficiency. However, the lack of a breed type × pasture type interaction for DMI, FCE, or RFI indicated that none of these dairy breed types were better adapted than another breed type to pastures with contrasting levels of nutritive value.
- Lessons learned: The use of the rising plate meter (RPM) allows for more thorough sampling of paddocks than grab samples alone resulting in greater accuracy of herbage disappearance. In order to get meaningful DMI values, forage disappearance needs to be adjusted for daily herbage growth and a measure of grazing efficiency, which require prior planning. Therefore, in this study, we measured herbage regrowth and used published data to estimate grazing efficiency. Season-long grazing studies can be problematic due to bimodal herbage production (e.g., lots of growth in the spring, summer slump, and slight recovery in the fall). Our study used season-long set stocking rates, so we had to adjust for varying herbage by using low stocking rates (e.g. plenty of herbage throughout) but this requires some way to remove excess forage in the first grazing rotation. We used commercial mowers with either sweepers or blower/bag systems. In the future, estimating DMI per heifer, as opposed to groups of 4 heifers would be beneficial ... if possible. Different feed efficiency metrics result in different results, which requires thought on how to interpret.
April 2023
- In this reporting period, the thesis data were prepared and published in the Journal of Dairy Science (link to the paper here: Dry matter intake and feed efficiency of heifers from 4 dairy breed types grazing organic grass and grass-birdsfoot trefoil mixed pastures - ScienceDirect)
- Tables and figures for the bullet points of April 2022 report were updated to reflect the published version. The results were presented in an eOrganic webinar. This completes the DMI and feed efficiency component of Objective 1 (see milestone table).
April 2022
- Grazing intake and herbage measurements were collected during the 2019, 2020, and 2021 grazing seasons and used to determine dry matter intake (DMI) and feed efficiency. These data were analyzed and reported as part of the requirements for a Utah State University M.S. thesis (Michael Greenland). The main results of the thesis/publication were as follows:
- We used herbage disappearance to determine DMI. Both feed conversion efficiency (FCE) and residual feed intake (RFI) were derived using heifer weight and DMI. All measures were normalized to 40% metabolic mature body weight of the corresponding dairy breed to account for difference in size and growth of the heifers.
- We observed greater DMI on grass-BFT mixtures. Among breeds, Holstein had the greatest DMI, then the two crossbreds, and Jersey had the least (Figure 3).
- Feed efficiency was most favorable for Jersey, less efficient for both crossbreds, and Holsteins showed variable results depending upon efficiency measure (Figure 4 and 5).
- Grazing adaptation defined as change in DMI during successive 24+ h increments over the 3.5 d grazing period was also considered, and DMI declined throughout the grazing period for all breeds similarly on both pasture-types. In addition, no breed × pasture-type interactions were found for DMI, FCE, or RFI suggesting that no breed had an advantage on higher quality (grass-BFT mixture or early grazing period) or lower quality (grass monoculture or late grazing period) forage (Figure 6).
- Multivariate analyses will be conducted to identify forage quality parameters associated with growth performance, DMI, and feed efficiency.
Heifer growth performance
January 2024
-
The following is an update on the Animal Health and Performance data for the Lewiston project. A thesis was defended in August of 2021 on project data from 2019 and 2020. Since that time data has been gathered from the 2021 year and has been organized in preparation for statistics. Those statistics have been completed on all but one of these data sets with the last set to be completed in the next month. With the data from all three years of the project, graphs have been created on the data with the Prisim graphing software. These graphs are attached with this report. Our entire project group will have a chance to view/critique the data/graphs/statistics within the next month. The revision of the manuscript to include the extra year (i.e., 2021) of data is ongoing with the anticipation that the manuscript will be completed and submitted to a scholarly journal for publication by March 2024.
- Preliminary results based upon the most recent graphs are as follows:
-
Figure 1 (updated): Measurement of Average Daily Gain over the course of a 105-d grazing period for each of four breeds (HO: Holstein, JE: Jersey, HJ: Holstein/Jersey crossbred, PRO: ProCross) with the three assigned treatments (MIX: grass + BFT, MONO: grass only, TMR: total mixed ration). Average daily gains within the TMR group were at or above 0.75 kg/day with the MIX group having average daily gains just short of the 0.5 kg/day mark. All treatment groups were significantly different from one another (significance at P<0.05).
-
Figure 2 (updated): Effect of breed (A) and treatment (B-E) on the cumulative change in percent Mature Body Weight (MBW) over the course of a 105-d grazing period for each of the four breeds (HO: Holstein, JE: Jersey, HJ: Holstein/Jersey crossbred, PRO: ProCross) with the three assigned treatments (MIX: grass + BFT, MONO: grass only, TMR: total mixed ration). All breeds had positive increases in percent MBW with JE having the greatest change. Across all breeds, heifers in the TMR treatment had the greatest overall positive increase in percent MBW with heifers in the MONO treatment having the least positive gain.
- Figure 7: Effect of breed and treatment on the Body Condition Score (BCS) over the course of a 105-d grazing period for each of the four breeds (HO: Holstein, JE: Jersey, HJ: Holstein/Jersey crossbred, PRO: ProCross) with the three assigned treatments (MIX: grass + BFT, MONO: grass only, TMR: total mixed ration). PRO started and ended with higher BCS than all other breeds. TMR groups within breeds overall gained BCS over the 105 day trial period while the pasture groups (MIX and MONO) overall lost BCS.
-
Figure 8: Effect of breed (A) and treatment (B) on the fecal egg count (FEC) over the course of a 105-d grazing period for each of the four breeds (HO: Holstein, JE: Jersey, HJ: Holstein/Jersey crossbred, PRO: ProCross) with the three assigned treatments (MIX: grass + BFT, MONO: grass only, TMR: total mixed ration). Regardless of breed, treatment or starting egg load, all animals ended the trial with a minimal number of fecal eggs.
-
Figure 9: Effect of breed (A) and treatment (B) on the Blood Urea Nitrogen (BUN) concentration over the course of a 105-d grazing period for each of the four breeds (HO: Holstein, JE: Jersey, HJ: Holstein/Jersey crossbred, PRO: ProCross) with the three assigned treatments (MIX: grass + BFT, MONO: grass only, TMR: total mixed ration). BUN saw a large increase for all breeds between day 70 and day 105. Heifers on MONO pastures had the greatest variability in BUN levels over the entire study period.
-
- Lessons learned (ongoing): Heifer to heifer differences in growth performance were the greatest source of variation, indicating the importance of sample size for testers. The average of groups of 4 testers allowed us to separate treatments. Outbreaks of pinkeye could have affected growth performance, and the organic-management nature of this project made it difficult to treat. How to quickly respond to these outbreaks needs to be planned for in future experiments. Year to year average season-long temperature differences may have affected performance. Inclusion of shade shelters should be considered in future experiments. The 3-breed crossbreds did not perform as expected by the cooperating producers. They usually came into the study with the highest BCS but in most cases gained a lower percentage of weight than the other breeds and often lost body condition. We thought that it might be the difference between those coming from feed-lot versus grass pasture backgrounds, but that did not prove to be the case. Because of the breed differences in size and growth rate among heifers of approximately the same age, a method of standardizing growth performance is critical for breed comparisons. Though we could not find it widely published, we still believe that using the percent of mature body weight was an appropriate and effective method.
April 2023
- In this reporting period, the 2021 data were added to 2019 and 2020 data from Fonnesbeck's thesis, and the entire dataset underwent statistical analyses. Summary and manuscript preparation will begin in fall of 2023.
April 2022
- Heifers were weighed (BW), body condition scored (BCS), and blood and rumen fluid samples drawn at the initiation of grazing, and at the end of every 35 day grazing cycle during 2019, 2020, and 2021.
- The heifer growth performance data from 2019 and 2020 were analyzed and reported as part of the requirements for a Utah State University M.S. thesis (Sawyer Fonnesbeck). The main results of the thesis are summarized as follows:
- BFT significantly increased ADG for all breeds. Heifers which grazed the MIX treatments averaged 0.48 kg of gain/day, whereas heifers on MONO pastures averaged 0.28 kg/day. Overall changes in BCS were significantly affected by both the differences in pasture treatment and breed of the animals (Figure 1).
- The different treatments did not cause any significant differences in fecal egg count (FEC) or total rumen volatile fatty acids (VFA) concentrations.
- Overall, Jerseys were able to gain a higher percentage of their mature body weight and maintain their body condition better, while grazing, than heifers of other breeds (Figure 2).
- We determined that grazing BFT can have noticeable positive effects on ADG, BCS, and change in percent mature BW.
-
Sorting and weighing heifers on project SW21-927. 
Weighing heifers on project SW21-927.
Rumen fluid and rumen microbiome DNA analysis
- The rumen microbiome DNA analysis was not part of the original proposal for SW21-927. However, the data and samples from SW21-927 are being leveraged to help complete this sub-objective as part of a M.S. theses in the USU Animal, Dairy and Veterinary Sciences Dept. The rumen ammonia and VFA concentration results have been combined with this microbiome data for the thesis. This combined and expanded data will help us have a better understanding of varying livestock performance on different pastures.
January 2024
-
See Milestone table. Rumen ammonia concentrations have been measured for all three years of data. Statistics have been run and a graph has been made. Rumen ammonia concentrations will be added to the other data sets in the manuscript submitted to a scholarly journal. Microbial DNA has been isolated from rumen fluid, from all three years, and the samples have been sequenced. Analysis of the sequencing data is underway. A master thesis on the microbiome data, rumen ammonia concentration data, and VFAs for all three years is underway, with a goal of completion by the end of April. Setbacks for this project have been many (mostly related to Covid 19). Needed lab supplies that were necessary for the isolation of the microbial DNA were set back by over 8 months. We do not have all of the equipment and expertise needed to sequence and analyze the sequenced data on our own, within our lab. We had arrangements to send samples outside our lab to be sequenced and the turnaround time was longer than anticipated.
- Preliminary rumen ammonia and VFA results based upon the most recent graphs are as follows:
-
Figure 10. Rumen Ammonia Concentrations: Effect of breed (A) and treatment (B) on the rumen ammonia concentration over the course of a 105-d grazing period for each of the four breeds (HO: Holstein, JE: Jersey, HJ: Holstein/Jersey crossbred, PRO: ProCross) with the three assigned treatments (MIX: grass + BFT, MONO: grass only, TMR: total mixed ration). There are no statistical differences between breeds. Significance set at P<0.05. There was more variation (by time) in the heifers that grazed pastures (MIX and MONO) as compared to the heifers consuming the TMR.
-
Figure 11. Acetate % of Total VFAs: Effect of breed (A) and treatment (B) on the percent acetate of the total VFAs over the course of a 105-d grazing period for each of the four breeds (HO: Holstein, JE: Jersey, HJ: Holstein/Jersey crossbred, PRO: ProCross) with the three assigned treatments (MIX: grass + BFT, MONO: grass only, TMR: total mixed ration). Acetate levels at day 0 varied among breed but eventually ended at similar points on day 105. Acetate was unchanged among treatment types except for the TMR group at day 35.
- Figure 12. Propionate % of Total VFAs: Effect of breed (A) and treatment (B) on the percent propionate of the total VFAs over the course of a 105-d grazing period for each of the four breeds (HO: Holstein, JE: Jersey, HJ: Holstein/Jersey crossbred, PRO: ProCross) with the three assigned treatments (MIX: grass + BFT, MONO: grass only, TMR: total mixed ration). Propionate levels had their greatest variation among breed and treatment at day 35 with minimal differences at other timepoints.
-
-
- Figure 13. Acetate:Propionate Ratio: Effect of breed (A) and treatment (B) on the acetate:propionate ratio over the course of a 105-d grazing period for each of the four breeds (HO: Holstein, JE: Jersey, HJ: Holstein/Jersey crossbred, PRO: ProCross) with the three assigned treatments (MIX: grass + BFT, MONO: grass only, TMR: total mixed ration). There was some separation among breeds at day 35 in that the JE and HJ had higher A:P ratios than the PRO and HO. A:P ratio shown by treatment did not see much difference among the three treatments except for a lower A:P ratio for the TMR group at day 35.
-
- Figure 14. Butyrate % of Total VFAs: Effect of breed (A) and treatment (B) on the percent butyrate of the total VFAs over the course of a 105-d grazing period for each of the four breeds (HO: Holstein, JE: Jersey, HJ: Holstein/Jersey crossbred, PRO: ProCross) with the three assigned treatments (MIX: grass + BFT, MONO: grass only, TMR: total mixed ration). No differences were seen among breeds for butyrate levels. The TMR treatment had slightly higher butyrate levels than the other pasture treatments.
- Example of the data coming from rumen microbiome study.
- See Figure 15 and 16.
April 2023
- In this reporting period, rumen microbiota DNA from the 2020 grazing season were extracted using commercial kits. The processing of the 2021 grazing season samples was initiated and is continuing. Preliminary results suggest that pasture-type (grass monoculture or grass-BFT mixture) affects the diversity in the rumen microbiome.
April 2022
- Rumen fluid collection was previously completed (see previous subobjective and milestone table).
- Rumen microbiome DNA assays are ongoing. The rumen microbiome genetics will be characterized to determine how pasture types affect the diversity and quantity of different microbiome populations in the rumen. This research was delayed due to the COVID-related difficulty of getting DNA extraction/analysis kits.
Heifer DNA analysis
January 2024
- DNA had previously been extracted from the blood taken from the 2020 heifers. DNA has now been extracted from the ear notches taken from the 2021 heifers. The DNA samples have been prepped and sent to Neogen. Index scores from Neogen for the individual heifers are expected in February 2024. This M.S. level student has undergone three brain surgeries (2 in June 2022 and 1 in February 2023) for a brain tumor, which has delayed his progress. It is anticipated that the study will be completed during 2024.
April 2023
- In this reporting period, heifer DNA from blood samples from the 2020 grazing season were extracted using commercial kits. The processing of the 2021 grazing season samples was initiated and is continuing.
April 2022
- Heifer DNA assays and analysis is ongoing. The heifer DNA analysis is to determine if the genotype of any breed or sire groups have a benefit over another in feed intake and growth in a pasture environment. This research was delayed due to the COVID-related difficulty of getting DNA extraction/analysis kits.
On-farm trials
April 2023
- In this reporting period, the producers reported their organic milk companies provided a service contract for satellite-based NDVI estimates of pasture forage. They used the RPM to 'truth check' NDVI estimates and reported close agreement; allowing them to use the service to provide organic certifiers with accurate estimates of percentage pasture forage in the cattle's diet.
April 2022
- The three collaborating producers received rising plate meters (RPM) and training about how to use the RPM to determine pre- and post-grazing herbage mass and estimate subsequent intake.
-
-
Dairy heifers grazing pastures on project SW21-927. 
Jersey heifers grazing on project SW21-927
-
Objective 2: Evaluate the influence of dairy breed on nutrient leaching
January 2024
- No sample analysis has been completed due to needing to validate the sample analysis protocols and establish a reference line to compare to by finishing the nitrogen cycling analysis from samples collected as part of WSARE project SW17-046, which only includes the Jersey breed. This has delayed completion of the proposed comparison of 4 dairy breeds on nutrient cycling (see next bullet points) (see milestone table).
- Due to some personnel issues, many errors were found for the nutrient cycling data from SW17-046. After collecting the field samples for SW21-927, Dr. Miller went back to the SW17-046 data and has worked on cleaning up file labels and notes, eliminating duplicate files, eliminating bad data (from bad peaks), and compiling/analyzing the data. She now has been able to analyze some of the corrected data.
- Preliminary nitrogen cycling results for grazing Jersey dairy heifers.
- Urine samples were analyzed for urea-N on a Lachat FIA analyzer. Fecal samples were analyzed for total N and total carbon by combustion analysis using an Elementar varioMAX CN elemental analyzer. Soil water (leachate) N was monitored by means of zero-tension lysimeters bi-weekly during the growing season, and as much as possible in the spring and fall. Leachate samples were analyzed for nitrate-nitrite concentration on a Lachat FIA analyzer. The amount of leachate produced from each lysimeter was measured, and total Leachate N determined. Nutrient cycling in the urine and feces were analyzed and compared to the overall protein levels in the forage.
- Both the urea-N concentration in the urine (Figure 17), and the fecal N content (Figure 18) were higher in the grass-legume mixtures than the grass monocultures (Hadfield et al., 2021). This is most likely the result of being fed a higher protein content diet in the grass-legume mixtures.
- Although the grass monocultures were not heavily fertilized, and the protein content of the monocultures was lower than that of the grass-legume mixtures, nitrogen leaching observed in the leachate was generally higher under the grass monocultures (Figure 19).
- Grass-legume mixtures may be able to more effectively capture nitrogen due to the differences in the rooting structure and the microbial populations. The grass-legume mixtures were also better economically.
April 2023
- In this reporting period, soil and leachate samples were collected for the year following the end of grazing treatments, as described above, to fully monitor the effects of grazing.
April 2022
- Nutrient leaching data were collected during the 2019, 2020, and 2021 grazing seasons, including the following:
- 1) plant samples were collected before and after each grazing event and dried for later analysis.
- 2) soil samples were collected in the fall at the beginning of the study for a baseline reading, and in the spring, prior to grazing, and in the fall after the growing season using a Giddings® soil extraction instrument to a depth of 1.524 meters. Soil samples were also collected in the spring of the third year to monitor nutrient movement.
- 3) soil water (leachate) nitrogen was monitored by lysimeters, and leachate collected every two weeks during the growing seasons, and as close as possible to every two weeks during the winter months.
- 4) urine and feces were collected from heifers at weigh-ins.
- Samples will be analyzed for nitrate, ammonia, urea, and total nitrogen and carbon.
Objective 3: Ascertain the influence of dairy breed on the economic sustainability of pasture-based heifer development.
January 2024
- Heifer growth performance data has been made available allowing partial budgets and economic values to calculated. This is now in progress and will be completed February/March of 2024 and included in the growth performance peer-reviewed manuscript (see milestone table).
April 2023
- Nothing to-date to report on economic analysis. These analyses, using the 3-years of heifer growth performance data, will be conducted such that it can be published with growth data.
Table and Figures for Research Results
Research Outcomes
Education and Outreach
Participation Summary:
Consultations (up to date as of January 31, 2024):
- Responded to 50 questions (phone calls, emails, on-site visits) about grass-legume mixtures for pasture, including how to establish and manage grazing.
Webinars, talks and presentations (up to date as of January 31, 2024):
Fonnesbeck, Sawyer. Influence of cattle breed and forage type on organic dairy heifer performance. M.S. thesis defense presentation. Utah State University, Logan. August 11, 2021. Participants: 3 farmers/ranchers, 2 agricultural professionals, 35 academia.
Miller, R. L., S. Isom, B. Waldron, K. Rood, E. Creech, M. Peel. 2021. The Nutrient Cycle of Pastured Heifers. Stock and Flock. October 8, 2021. Logan, UT: Utah State University Extension. Available at: https://www.youtube.com/watch?v=upmrnf_hdlU&t=10s. Views (as of August 1, 2023): 212.
Miller, R., B. Waldron, C. Isom, K. Thornton-Kurth, K. Rood, E. Creech, M. Peel, M. Rose, and J. Hadfield. 2021. Nutrient Cycling in an Organic Dairy Grazing System. In 2021 American Society of Agronomy Abstracts. Madison, WI: American Society of Agronomy.
Miller, R., B. Waldron, S. C. Isom, K. Thornton-Kurth, K. Rood, E. Creech, M. Peel, J. Hadfield, R. Larson, and M. Rose. 2022. Improving Production and Minimizing Nutrient Loss in Grazing Systems through the Use of Grass-Legume Mixtures. Waste to Worth. Oregon, OH. April 18-22, 2022. Available at: https://lpelc.org/improving-production-and-minimizing-nutrient-loss-in-grazing-systems-through-the-use-of-grass-legume-mixtures/. Participants: 50 farmers/ranchers, 200 agricultural professionals, 100 academia.
Greenland, Michael. Dairy Breed, Grass-Birdsfoot Trefoil Mixture, and Pasture Nutrition Effects on Intake, Feed Efficiency and Grazing Adaptation. M.S. thesis defense presentation. Utah State University, Logan. May 2, 2022. Attendees: 3 farmers/ranchers, 2 agricultural professionals, 30 academia.
Greenland, Michael. Dairy Breed, Grass-Birdsfoot Trefoil Mixture, and Pasture Nutrition Effects on Intake, Feed Efficiency and Grazing Adaptation. eOrganic webinar. May 6, 2022. Available at: Dairy Breed, Grass-Birdsfoot Trefoil Mixture, and Pasture Nutrition Effects on Intake, Feed Efficiency and Grazing Adaptation | eOrganic. Attendees: 44; Views (as of August 1, 2023): 535.
Goodey, Chase. Measures of rumen health and function in organic pasture-raised dairy heifers. Presentation at ADVS Student Research Symposium. Utah State University, Logan. August 3, 2022. Attendees: 70.
Waldron, Connor. Genotypic influence of developing organic dairy heifers. Poster at ADVS Student Research Symposium. Utah State University, Logan. August 3, 2022. Attendees: 50.
Workshop / field days (up to date as of January 31, 2024):
#2. Utah State University/University of Idaho Extension/USDA Irrigated Pasture Field Day. July 13, 2023. Participants: 35 total. 13 farmers/ranchers, 14 agricultural professionals, 8 academia.
The following presentations related to this project were given:
-
Topics and Speakers:
Stop 1 – By the new planting.
- Welcome and overview of history and future of USU grazing research – Earl Creech and Ross Israelson
- Establishing new pastures – choice of plants, methods, and weed control – Drs. Earl Creech and Corey Ransom (USU)
Stop 2 – Pasture C – Ryegrass/BFT and temporary chute.
- Sweetening up the pasture by planting legumes into established grass and choice of legumes – Dr. Mike Peel (USDA)
- Troublesome weeds in pasture and emerging issues with pasture herbicide residual in manure/composting – Dr. Corey Ransom (USU)
Walk and view 4 grasses mixed with BFT – Pasture D west side (Northeast pasture)
- Extension resources for pastures and grazing – Bracken Henderson (Univ of Idaho Extension, Franklin County Idaho) and Justin Clawson (Utah State University Extension, Cache County).
- Dairy Heifer/Grazing research – Dr. Clay Isom (USU)
- Overview of 3 grazing studies – including Jersey study
- The effect of dairy breed and pasture-type (grass and grass-legume mixtures) on heifer growth performance – Sawyer Fonnesbeck, Univ. of Idaho Extension, Onieda County (former graduate student)
- The effect of dairy breed and pasture-type (grass and grass-legume mixtures) on rumen microbes – Chase Goodey, grad student.
- The effect of dairy breed genetics on grazing efficiency and – Connor Waldron, grad student.
- The effect of dairy breed and pasture-type (grass and grass-legume mixtures) on herbage intake and grazing efficiency – Dr. Blair Waldron (USDA)
Walk and view 4 grasses in monoculture without BFT – Pasture D eastside
- Fencing for rotational grazing – Jacob Hadfield (USU Extension, Juab County; former graduate student)
- Pasture fertility – options other than commercial fertilizer – Greg Bingham (dairy farmer/producer)
- Economics of grazing – Dr. Ryan Larson
#1. Utah State University Lewiston Pasture Research Farm field day. July 28, 2021. Lewiston, Utah. Participants: 41 total. 15 farmers/ranchers, 11 agricultural professionals, 5 academia. The following presentations related to this project were given:
- Clay Isom. Dairy heifer grazing project overview.
- Michael Greenland, USU graduate student. Dry Matter Intake and Feed Efficiency of Four Dairy Breeds in Pasture-Based Heifer Development.
- Sawyer Fonnesbeck, Idaho State University Extension and former graduate student on project. The Influence of Cattle Breed and Forage Type on Dairy Heifer Performance
- Rhonda Miller. N-Cycling in Organic Dairy Grazing Systems.
Other Educational and Outreach Activities (up to date as of January 31, 2024):
A web site for the project was established through eOrganic in a previous related Western SARE grant, SW17-046 (found at https://eorganic.info/node/33809; verified 4/28/22). The project SW21-927 is an extension and continuation and will be using the same website. Information on the website will be updated to reflect the new project. As publications, presentations and trial results from the projects become available, we will make them available here.
- eOrganic webinar. May 6, 2022. link: Dairy Breed, Grass-Birdsfoot Trefoil Mixture, and Pasture Nutrition Effects on Intake, Feed Efficiency and Grazing Adaptation | eOrganic.
Publications (up to date as of January 31, 2024):
Fonnesbeck, Sawyer. Influence of cattle breed and forage type on organic dairy heifer performance. M.S. thesis, Utah State University, Logan. 2021.
Miller, R., B. Waldron, S. C. Isom, K. Thornton-Kurth, K. Rood, E. Creech, M. Peel, J. Hadfield, R. Larson, and M. Rose. 2022. Improving Production and Minimizing Nutrient Loss in Grazing Systems through the Use of Grass-Legume Mixtures. eXtension Waste to Worth: Advancing Sustainability in Animal Agriculture. Waste-to-Worth Proceedings. Oregon, OH. April 18-22, 2022. Available at: https://lpelc.org/improving-production-and-minimizing-nutrient-loss-in-grazing-systems-through-the-use-of-grass-legume-mixtures/.
Greenland, Michael. Dairy Breed, Grass-Birdsfoot Trefoil Mixture, and Pasture Nutrition Effects on Intake, Feed Efficiency and Grazing Adaptation. M.S. thesis, Utah State University, Logan. 2022.
Greenland, Michael S., Blair L. Waldron, S. Clay Isom, Sawyer D. Fonnesbeck, Michael D. Peel, Kerry A. Rood, Kara J. Thornton, Rhonda L. Miller, Jacob A. Hadfield, Brecken Henderson, and J. Earl Creech. 2023. Dry matter intake and feed efficiency of heifers from 4 dairy breed types grazing organic grass and grass-birdsfoot trefoil mixed pastures. Journal of Dairy Science. 106:3918-3931. https://doi.org/10.3168/jds.2022-22858. (Accepted 12/30/22; Published 4/25/23).
Education and Outreach Outcomes
- Grass-legume mixtures improve dairy heifer forage intake, health, and performance compared to grass monocultures.
- Dairy breeds differ in amount of forage intake and efficiency of converting that intake into growth.
Choosing the best forages to include in pasture mixtures.
Moving towards more Jersey's in herd due to their greater grazing efficiency compared to other tested dairy breeds.