Evaluating the Sustainability of Beef Cattle Breeding Systems

Final Report for LNC12-340

Project Type: Research and Education
Funds awarded in 2012: $199,995.00
Projected End Date: 12/31/2016
Region: North Central
State: North Dakota
Project Coordinator:
Dr. Carl Dahlen
North Dakota State University
Expand All

Project Information

Summary:

The purpose of the project is to evaluate two beef cattle breeding systems with a focus on understanding three key areas of sustainability within each system: production, performance, and profit. Within herds at each location, cows were assigned to one of two breeding systems: 1) cows will be bred via natural service bulls (NS); and 2) cows will be bred via artificial insemination followed by exposure to natural service bulls (AI).

Producers at each location worked closely with their country Extension agent to accomplish research objectives and project personnel were on location at each operation at least four times in order to accomplish research objectives. The project was split into 2 cohorts, one starting in 2013 and one in 2014.  Three meetings are held separately for each cohort of producers.  At each meeting surveys and tests are administered to gather data and focus group sessions are held to discuss topics pertinent to the current stage of the project.  In addition, focus group sessions are held with participating county Extension staff at each meeting to gather input about their perceptions of the effort and how the project has impacted them professionally and personally.

Cooperating operations beginning project in in Year 1 (2013) included Sorenson Ranch in Watford City, ND, Alme Farm & Ranch in Balfour, ND, Enge Farm & Ranch in Stanley, ND, and Hintz Stock Farms in New Salem, ND. In Year 2 (2014) 6 commercial beef operations (Cohort 2) began their collaborations with the effort: Cooperating operations added in Jim Enge in Stanley ND, TJ Alme in Balfour, ND, Aaron Hintz in Year 2 include Jerid and Camie Janikowski in Bowman, ND, Klein Ranch in Hazen, ND, Kent and Judy Oland in Sheldon, ND, Dustin Roise in Powers Lake, ND, Chris and Nadine Tedford in McKlusky, ND, and Rodney and Karen Schmidt in Streeter, ND.

A midpoint meeting was held for Cohort 2 participants in early 2015 to field questions from participating producers about what to anticipate during their upcoming calving season, and to have focus group conversations about project activities and how their herd production, performance, and profit measures could be used to improve their operation’s sustainability.  A joint summary meeting was held jointly for producers in Cohort 1 and Cohort 2 to summarize calving and weaning information, make appropriate data comparisons, and discuss the sustainability of each breeding system on producer operations. Data collection from Year 1 was completed in late 2014/2015, whereas data collection from Year 2 was completed in late 2015/2016.  Analysis of all data revealed that no differences (P = 0.54) were present in season ending pregnancy rates between cows in the NS (93.1%) and AI (93.2%) treatments. Cows in the TAI treatment calved 7.7 d earlier (P < 0.001) in the calving season compared with NS cows. A greater proportion (P < 0.001) of TAI cows (45.6%) gave birth in the first 21 d of the calving season compared with NS cows (24.7%).  From d 22 to 42, a greater proportion (P < 0.001) of NS cows (41.9%) gave birth compared to TAI cows (27.3%), and a greater proportion of NS cows (24.7%) gave birth from d 42 to the end of the calving season compared with TAI cows (18.6%).  Calf weaning weights were greater (P < 0.001) for calves from the AI treatment (549.8 lb.) compared with calves from the NS treatment (533.9 lb.).  

Partial budget analyses were completed for each herd to discuss how the effort has impacted the outlook each producer has regarding their operation and what subsequent steps each producer plans to take to position their operation for long-term sustainability. Two scenarios were considered for a total of 2 partial budget analyses for each operation: 1) clean-up bull numbers remained similar to previous years when TAI was not utilized (stocking rate of 1 bull per 25 cows), and 2) clean-up bull numbers were reduced to the mean number used in the industry after AI is implemented (1 bull per 39 cows; Dahlen et at., 2015). When evaluating scenario 1 and the average profit or loss for the participating herds, 5 producers made money, 5 producers lost money (assuming cost to implement AI were incurred by producers rather than grant funds) with a mean results of -$12.04/cow with the addition of an AI breeding system compared with a NS breeding system. In scenario 2, however, 9 of 10 producers made money with a mean increase in profit averaging $13.84/cow exposed to AI.

We documented that participating producers have increased skills, awareness and knowledge of breeding systems, herd performance, and financial aspects of their operation. We also documented that all producers have shared information regarding the project with other producers and 8 of 9 producers responding to survey questions indicated that they have changed their breeding systems as a result of their participation in the project.

Major themes from focus group sessions conducted after all data were returned to producers revealed that some benefits of breeding systems evaluated are not short-term and were not accounted for in partial budget analysis. Specifically, items including improved genetics of cow herd, value of replacement heifers, and improved value of calves that are sold direct to feedyards or through auction markets that was not directly related to final weight (i.e. phenotypic differences or perceptions by buyers of differing value from calves originating from the respective breeding systems).  Producers were divided as to the relative value they perceived from being involved in a cow herd record keeping program (CHAPS) and had strong feelings as to whether they would continue with the program.  All were in agreement, however, regarding the importance of some type of financial record keeping system and that such a system can positively contribute to the long term sustainability of their operation.

Introduction:

Commercial cattlemen represent the vast majority of beef producers in the U.S. (managed on 90.5% of beef operations; NAHMS 2009a) and contribute greatly to maintaining diversity in our natural landscapes and healthy rangeland ecosystems. The area of production most critical in terms of profit potential in commercial cow-calf operations is the ability of a cow to give birth and raise a healthy calf until weaning.  Reproductive performance is variable among herds (Larson et al., 2006; Dahlen et al., 2010) and estimates indicate the beef industry loses $1.06 billion in revenue annually as a result of infertility (Lamb et al., 2008).  Identifying reproductive techniques or management practices that enhance reproductive performance would have a significant economic impact.

Incorporating estrous synchronization (ES) and artificial insemination (AI) into beef operations may result in improved reproductive performance, weaning weight, carcass quality, and genetic value, along with reduced calving difficulty (Sprott, 1999). While much research has been conducted to develop estrous synchronization protocols to facilitate AI (Lauderdale, 2009), a great majority of research is designed to compare one type of estrous synchronization protocol with another type of synchronization protocol and the study is completed upon collection of final pregnancy data. 

For commercial cattlemen these types of studies offer little insight into the potential effects of incorporating estrous synchronization and AI into their operations. The control group best suited for commercial cattlemen without experience with AI is their default breeding management system; natural service (bull breeding).  In addition, effects of a breeding strategy are present long after a final pregnancy examination.  Changes in calving season, and calf characteristics both at birth and at weaning contribute greatly to a cattlemen’s decision of whether to incorporate a given strategy.

Breeding systems that have the potential to alter the proportion of cows giving birth to calves and coincident calf characteristics are inherently entwined with the concepts of sustainability.  This project will focus on production, performance, and profit aspects of natural service and artificial insemination breeding systems and provide sound data to help beef producers decipher whether it is worth the required opportunity cost to dedicate three additional days to the cow herd in order to accomplish AI during a season when time and labor resources are very precious commodities.

Project Objectives:

Short term outcomes:

  1. Determination of production, performance, and profit responses of two beef cattle breeding systems implemented on each of 10 cooperating producer operations.
  2. Increased skills, awareness and knowledge of cooperating producers regarding breeding systems, herd performance, and beef production system finances
  3. Continuing education for NDSU Extension and ND Farm Business Management groups
  4. Creation of a network of producers and Extension agents that fosters discussion and group learning related to the sustainability of beef production systems

 

Intermediate outcomes:

  1. Documented changes over time in perception of participating collaborators and producers regarding breeding systems, herd performance, and beef production system finances  
  2. Increased use of the tested breeding strategies, herd performance evaluation and Farm Business Management services by producers participating in the project
  3. Improved sustainability (optimization of profitability and quality of life) for participating producers
  4. Increased awareness and knowledge of breeding systems, herd performance, and beef production system finances of producers, students, veterinarians, and members of allied industries attending programs, receiving educational materials produced via grant-related activities, or otherwise interacting with personnel involved with the proposed project.

Cooperators

Click linked name(s) to expand
  • Andrea Bowman
  • Raquel Dugan-Dibble
  • Dr. Gary Goreham
  • Ron Haugen
  • Jim Hennessy
  • Mark Holkup
  • Mark Miller
  • Dr. Kris Ringwall
  • Rick Schmidt
  • Andy Swenson
  • Calli Thorne
  • Jerry Tuhy
  • Brian Zimprich

Research

Materials and methods:

Parameter 1: On-Farm Treatment Application:

All cattle were managed according to the Federation of Animal Science Guide for the Care and Use of Agricultural Animals in Agriculture Research and Teaching (FASS, 1999). All procedures were reviewed and approved by the Institutional Animal Care and Use Committee of North Dakota State University.

Treatments

Two thousand three hundred and ninety-nine crossbred commercial cows originating from 10 commercial beef herds in the state of North Dakota were used to compare pregnancy rates, calving distribution, and calf weaning weights of beef cows exposed to two different breeding systems. County Extension Agents from the North Dakota State University system identified commercial cattle producers who did not use breeding systems that incorporated estrous synchronization or AI as a part of their management strategy for participation in this experiment. Within each herd, females were stratified by d postpartum and randomly assigned to one of 2 treatments (Figure 1); 1) only exposed to natural service herd bulls (CON; n = 1,114) or 2) exposed to ovulation synchronization and fixed-time AI followed by natural service bulls (TAI, n = 1,285).

All TAI females were exposed the 7-d CO-Synch + CIDR (Larson et al., 2006) consisting of inserting a controlled internal drug releasing insert (CIDR,1.38 g Progesterone, Zoetis, Inc., Florham, NJ, USA) and 100 µg Gonadotrophin Releasing Hormone (GnRH) i.m. (2 mL Factrel, Zoetis, Inc.), followed in 7 d by CIDR removal and 25 mg PGF2α i.m. (5 mL Lutalyse, Zoetis, Inc.), followed in 60-66 hr by 100 µg GnRH i.m. and fixed-time artificial insemination (AI). At the time of CIDR insertion, body condition scores (BCS) were recorded on all TAI females. Body condition scores are a visual method for evaluating the nutritional status of an animal and are based on a 1-9 scale, with 1 being emaciated and 9 being obese (5-6 being ideal; Richards et al., 1986). Each producer for their given herd was responsible for the selection of AI sires for the TAI treatment.

Participating producers were responsible for the selection of AI sires to be bred to females in the TAI treatment group. Criteria for selection included a $20 per unit of semen max and bull breeds would be similar to those used as clean-up for TAI and bulls for NS matings.

Within each herd, females from both treatments were comingled on common pastures and managed together. Bulls were placed into breeding pastures a minimum of 1 d after TAI. The presence of a viable fetus was determined by the herd veterinarian of each operation, at least 45 d after the conclusion of the producer defined breeding season. Birth date was recorded at parturition and individual calf weights were collected at weaning. Calves born from cows exposed to TAI will be referred to as TAI calves and calves born from dams only exposed to NS will be referred to as NS calves.

In the current study, the start of the calving season was defined as the date that the third calf was born for each producer operation to remove any early born outliers in the calving season. Calves were then divided into three 21-d interval calving groups based their respective date of birth: born in the first 21 d of the calving season (≤ 21), born from d 22 to 42 (22-42), and born after d 42 of the calving season (≥ 42). If a female was determined to be pregnant at the end of the breeding season but failed to calve the calving group was referred to as no calf. The proportion of cows in the TAI group in the first 21 d of the calving season will serve as a proxy for cows that became pregnant to TAI.

Calf body weights were recorded at the time of weaning at each producer location. Due to the variation in timeframe of when calves were weaned at each location, adjusted weights were calculated. Calf weaning weight was divided by the difference in weaning date and birth date and then multiplied by 205. Weaning weight per cow exposed was also calculated where the weaning weight recorded for cows that did not calve was entered as a zero.

 

Parameter 2: Producer Focus Groups:

Instruments

A series of meetings throughout the project period were also attended by both agents and producers. A total of three meetings over the project time period in which 10 producers and nine North Dakota State University county extension agents attended. Focus groups discussions were conducted to evaluate the perceptions of both producers regarding the performance, production, and profit components of the project. Focus group discussions were also used to describe the quality of life changes of producers and their operations. Questions asked during the discussion remained similar throughout the series of meetings, however, were altered slightly from an anticipated result (pre) to during the project (mid) to after conclusion of project (post). During the final meeting, summary information was discussed and much of the focus group session focused on the concept of sustainability of producer operations with each project component in mind (production, performance, and profit). Interview guides were developed to focus the information discussed with general probes that included possible anticipated results or thoughts.

Data Collection

Cattle within each producer herd were randomly assigned to one of two breeding systems, natural service breeding (herd bulls only) or estrous synchronization and timed-AI followed by exposure to natural service bulls. In addition, producers were enrolled in a cow herd performance evaluation (Cow Herd Appraisal Performance Software program; CHAPS) and farm business management (FBM) program for two years to determine the true economic impact of each breeding system. Data originating from focus groups were collected during the course of three meetings.

General topics for discussion at each meeting are as follows:

Meeting 1) Concepts of sustainability, details of breeding systems, selecting natural service and AI bulls, collecting data for CHAPS evaluation, tracking farm income and expenditures

Meeting 2) Summary of pregnancy data, what to anticipate during the calving season, Perception vs. reality; how did your herd compare?, using production, performance, and profit measures to improve sustainability, suggestions for improving programs

Meeting 3) Summary of calving and weaning data, appropriate data comparisons workshop, sustainability of each breeding system on your operation, how did each project component contribute to long-term sustainability of herd.   

Data Analysis

Focus group discussions were evaluated by meeting . Within each meeting, a series of four questions were discussed and each question was evaluated independently. Responses were transcribed and color aggregated into themes by a single individual. Major themes were first evaluated, then moving into more specific discussion topics. Common themes throughout each question subject were then grouped by topic and summarized. The information provided in the following sections outline the progression through question topics and discussion themes. Although not an all-inclusive list, summary themes included in the results were similar across producer participants.

Parameter 3: Survey of Program Impacts for Participating Producers:

A survey addressing short- and intermediate-term objectives was distributed to project participants.  Survey questions were developed using a 5-point Likert scale to report level of knowledge, understanding, skill, ability, and satisfaction regarding project components.  In addition, producers were asked to report whether additional changes were made to the management of their operation as a result of the program, whether and how they have shared information or experiences with others, and how the program has impacted their management and their profitability.

Research results and discussion:

Parameter 1: On-Farm Treatment Application:

In the current study, breeding system did not affect the proportion (P = 0.54) of cows that were pregnant at the end of the producer defined breeding season (TAI: 93.2 ± 0.01 and NS: 93.1 ± 0.01). Pregnancy rate did, however, differ by herd (P = 0.01), where Herd 7 had the smallest proportion of females pregnant (89.1%) and Herd 6 had the greatest (96.3%; Figure 2). The CIDR included in the use of the 7-d CO-Synch + CIDR protocol provides increased concentrations of progesterone for the period of time in which it is inserted. The greater the concentration of progesterone found in the blood, during estrus, the greater the chance of conception (Echternkamp et al., 2011). The addition of a CIDR with an estrous synchronization protocol provided supplementary progesterone that improved pregnancy rates to TAI when compared to a CO-Synch protocol without the use of a CIDR (Larson et al., 2006). Even with increased concentrations of progesterone presumably occurring with the use of a CIDR (as concentrations of progesterone were not evaluated) pregnancy was not increased over females receiving no additional progesterone.

Effects of AI on pregnancy attainment vary in the published literature. Previous research in Bos indicus cattle demonstrated an increase in pregnancy rates to TAI compared with those from natural service breeding (Sá Filho et al., 2013). Similarly, when evaluated for the first 21-d period of the calving season, pregnancy rates did not differ for TAI and natural bred cows, however, by d 49 greater proportions of cows bred to TAI were pregnant compared with cows bred with natural service breeding (81.7 and 77.5 percent respectively; Steichen, 2013). By the end of the breeding season, pregnancy rates were again similar between TAI and natural service bred females. Season ending pregnancy rates for the study by Steichen (2013) are similar to those observed in dairy cattle when both TAI and natural service breeding were evaluated, pregnancy rate was not different (Lima et al., 2009). To date, limited studies are available that evaluate season ending pregnancy rates for Bos taurus cattle bred to TAI or natural service. The current study includes crossbred cattle on commercial beef (76 percent of the beef industry) operations which represent a large proportion of the U.S. beef industry (NAHMS, 2009).

Season ending pregnancy rates were not affected by the interval from calving to breeding, as rates were similar (P = 0.34) between cows exposed to TAI and those only exposed to natural service breeding (CON), with an average of 65.2 ± 0.69 d. When categorized as previously described, DPP affected (P = 0.05) pregnancy rate, with the pregnancy rate increasing as DPP increased (< 40 DPP: 85.1% ± 0.03; 41-70 DPP: 93.4% ± 0.01; and 71-100 DPP: 94.8% ± 0.01). Rutter and Randel (1984) concluded that cows that could maintain their body condition after calving had a shorter postpartum interval of anestrous. Cows that were able to maintain body condition also had greater GnRH-induced LH release than those losing condition after calving (Rutter and Randel, 1984). Although maintenance of body condition score was not evaluated in the current study, greater pregnancy rates were observed for those females with greater BCS. For every unit increase in BCS over the value of 3, the cyclicity of cows increases 11.5 percent (Larson et al., 2006). Additionally, a greater proportion (P = 0.01) of cows in the TAI treatment with higher body condition scores (BCS) became pregnant when compared to cows with lower BCS (<4: 87.1% ± 0.01; 4: 92.4% ± 0.01; 5: 95.7% ± 0.01; and > 5: 97.8% ± 0.0.1).  Cows calving with a BCS > 5 became cyclic earlier than those calving with a BCS < 4 (Richards et al., 1986). Earlier cyclicity of cows with a greater BCS may explain greater pregnancy rates for heavier conditioned cows in the current study.

Advantages of TAI in terms of pregnancy rate were not observed in the current study. Further evidence, however, for the importance of greater body condition scores and increased intervals between calving and breeding were realized. Although DPP cannot be increased indefinitely, as females need to have a calf each year, greater proportions of cows that calve earlier in the calving season will become pregnant. Culling females that calve at the end of the calving season may increase the DPP of a herd, increasing reproductive performance.

Calving Distribution

In the current study, cows exposed to TAI calved 7.7 d earlier (P < 0.001) than CON cows (27.1 ±0.81 and 34.8 ± 0.82, respectively). Cows bred to TAI were exposed to ovulation synchronization and bred on a single d compared to cows only exposed to natural service, of which were bred any time during the breeding season. Steichen et al. (2012), reported similar findings, with cows bred to TAI calving six d earlier than those bred to natural service. A greater (P < 0.001) proportion of TAI cows (45.6 ± 0.02%) calved in the first 21 d of the calving season period compared with CON cows (24.7 ± 0.02%; Figure 3). In contrast, more (P < 0.001) CON cows calved from d 22-42 and from d 42 to the end of the calving season compared with TAI cows (when evaluating the second and third 21 d periods, a greater proportion of CON females calved in each respective period (21-42: 41.9 ± 0.02 and 27.4 ± 0.02 and > 42: 24.7 ± 0.02 and 18.6 ± 0.01, CON and TAI, respectively). Finally, there was no difference in the proportion of cows that did not calve (P = 0.59).

Incorporation of estrous synchronization and AI increase the number of calves born in the early in the calving season in previous literature. A similar distribution to the one observed in the current study was observed when the calving season was distributed into 10 d calving intervals, as greater proportions of cows bred with TAI calved earlier than cows bred with natural service (Rodgers et al., 2012). It is often theorized that AI can decrease the length of the calving season (Sprott, 1999, Larson et al., 2006, Lamb et al., 2010). The length of the calving season is however solely a function of bull exposure and the amount of time a bull is with females.

Weaning Weights

Weights of calves born from each breeding systems were recorded at each producer location at the time of weaning. Greater (P < 0.001) weights were observed for the TAI calves compared with CON calves (249.9 ± 1.6 kg and 242.7 ± 1.7 kg, respectively). Calculated 205-d weights, however, were not different (P = 0.703) between treatment groups (CON: 243.6 ± 1.7 kg and TAI: 244.9 ± 1.7 kg). When including calving group in the statistical model, a treatment × calving group interaction was also present for weaning weight. Greater (P < 0.001) weaning weights were observed for TAI calves born in the first 21 d of the calving season (269.3 ± 2.1 kg) compared with CON calves born during the same period (257.6 ± 3.0 kg; Figure 4.).

A treatment × calving group interaction was also present for calculated 205-d weights, where larger weights were observed for TAI calves born in the first 21 d of the calving season compared with CON calves (252.9 ± 2.3 and 245.1 ± 3.3, respectively; Figure 5). Increased calf weaning weights of calves born from AI exposed females are attributed to calves being older in addition to improvements in genetic parameters related to growth (Johnson, 2002). Results are similar to those observed by Rodgers et al. (2012), where weaning weights per cow exposed to treatments were greater for cows exposed to estrous synchronization and TAI compared with natural service. Calves born earlier in the calving season may have a faster preweaning rate of gain and therefore may be able to utilize forage better than those born later in the calving season (Lesmeister et al., 1973). Greater (P = 0.05) weaning weights were observed for CON calves born in the second 21-d period of the calving season compared with TAI calves (246.7 ± 2.3 kg and 239.7 ± 2.8 kg, respectively). No differences (P = 0.23) were present in the third 21-d period of the calving season when evaluating weaning weights of calves as well as the second and third 21-d period of the calving season when evaluating calculated 205-d weaning weights.

Parameter 2: Producer Focus Groups:

Summary of main themes generated at each respective meeting include:

Meeting 1 (conducted before breeding systems were implemented on each herd):

  1. Excitement over potential improvements in genetics and value of replacement heifers.

"I expect to retain better heifers and improve the quality of my herd."

2. Concern over time and labor requirements needed to implement the AI breeding system on their operations.

"As far as time and as far as… is it going to be worth my effort to go through this AI process versus just herding the bulls out the way that I have been doing it."

3. Intensiveness of records and whether information would be useful.  Some thought that CHAPS may be helpful while others weren't quite as convinced:

"I can judge whether I got a poor cow or a poor calf in there and I can go out and do the same thing as what you’re doing in the CHAPS program and go out and sell it.

4. Getting others (family members and/or associates) more involved in the record-keeping process

5. Quality of thorough evaluation of financial aspects of operation may lead to better-informed decisions regarding many aspects of herd management.

"Where I can cut costs to where I can put a little more money in than I need to or I can afford to put more money where it makes sense."

6. When asked to consider factors related to quality of life that participants thought may be impacted by components of the program they identified spending time with family and friends, pride in their herds, and time available to complete necessary tasks.

Meeting 2 (conducted after implementation of breeding system but before calves were born):

  1. The process of implementing AI breeding was more than natural service, yet went smoother than anticipated.

"Yea I thought it all went pretty good I guess. It wasn’t much to it. It was a pretty simple deal."

2. Scheduling is more intensive with AI when considering not only scheduling time for specific activities related to the breeding systems but also with regards to the altered schedules of labor and other farming tasks.

3. Increased family involvement and potential to bring younger family members into the management activities of the herd. 

"We like working cattle together and when you get everybody there its usually good food and comradery and even if it’s just our family."

4. Excitement related to seeing the resultant calf crops being born and growing by their mother's side.

5. Anticipation of the upcoming calving season and more calves being born early in the calving season.

6. Preliminary use of the CHAPS program appears to yield an extensive amount of information.

7. It may take several years to see a true benefit from 3rd party evaluation of cattle production records.

8. Getting all required financial records could be a difficult task but once a system is in place for doing this regularly the burden is reduced.

9. Financial advisors have a major role in making the financial programs work.

10.  Having expenses categorizing makes many things easier; taxers, discussions with bankers, etc.

11.  With regards to quality of life: spent more time with family, increased learning and interest in AI, and increased workload during key stages of breeding system implementation. 

Meeting 3 (after calves have been born and all components of the project have been complete

  1. Each participant felt they had gained valuable information from the project regarding the short-term and potential long-term impacts of each breeding system on their operation.  Some continued using AI in their cow herd whereas a smaller proportion decided that natural service was the best long-term solution for their operation.
  2. Some benefits of breeding systems evaluated are not short-term and were not accounted for in partial budget analysis. Specifically, items including improved genetics of cow herd, value of replacement heifers, and improved value of calves that are sold direct to feedyards or through auction markets that was not directly related to final weight (i.e. phenotypic differences or perceptions by buyers of differing value from calves originating from the respective breeding systems). 
  3. Producers were divided as to the relative value they perceived from being involved in a cow herd record keeping program (CHAPS) and had strong feelings as to whether they would continue with the program. 
  4. All participants were in agreement, however, regarding the importance of some type of financial record keeping system and that such a system can positively contribute to the long term sustainability of their operation.
  5. The on-farm breeding system implementation and the financial evaluations were used to develop long-term strategies to increase profit in the herd.
  6. Producers stressed the importance of strategic marketing and adding value to calves that resulted from the AI breeding system.  In addition, one producer identified a savings of over $60,000 by strategic retention of bulls from AI breeding rather that purchase of outside genetics.

Parameter 3: Survey of Program Impacts for Participating Producers

A survey addressing short- and intermediate-term objectives was distributed to participants after project completion. A summary of a survey questions and participant responses follows:

Question

Before Participation

After Participation

Percentage Increase

Please rate your Knowledge and Understanding of each of the following areas:

Management of your operation

3.78

4.22

11.8%

Natural service breeding systems

3.78

4.11

8.8%

Artificial insemination breeding systems

2.67

3.78

41.7%

Cow herd performance analysis

3.0

3.78

25.9%

Production economics

3.44

3.75

8.9%

Rating Scale; 1 (Very Low) to 5 (Very High)

Please rate your Skill and Ability to implement each of the following in your cow herd:

Scheduling synchronization/AI activities

2.67

3.89

45.8%

Performing synchronization/AI tasks (inserting CIDRs, AI breeding, etc.)

2.44

3.67

50.0%

Cow Herd Appraisal Performance Software (CHAPS) performance records

2.56

3.44

34.8%

Farm Business Management financial records

3.0

3.44

14.7%

Rating Scale; 1 (Very Low) to 5 (Very High)

Please rate your level of satisfaction with each of the following:

Overall management of your herd

3.89

4.11

5.7%

Steps taken to obtain additional knowledge/understanding

3.44

4.11

19.4%

Steps taken to improve skills and abilities in herd management

3.56

4.22

18.8%

Efforts to increase the sustainability of your operation

3.75

4.25

13.3%

Rating Scale; 1 (Very Dissatisfied) to 5 (Very Satisfied)

Additional follow-up survey questions of program participants revealed:

88.8% have implemented AI in their operations since participation in the program

100% have shared information or experiences from the program with others

Examples include: other producers, friends, family, neighbors, bankers, field day tours, radio interviews, brought AI and natural service pens to county fair

88.9% have made changes to their operation (that did not include breeding techniques or breeding management) as a result of learning during the course of the program

Examples include: placed a lot of effort on making sure cow herd nutrition is appropriate, more attention to bull selection, bought higher value bulls, kept more detailed records, identified management areas that needed improving, improvements to cattle handling facilities, spent more time on herd health, put more value on cow herd (both time and financial), added haying enterprise because we were more confident in cost of production  

 

Responses to question about change in value of several facets of participants’ operations:

100% indicated an increase in the genetic value of their calves

87.5% indicated an increase in the value of replacement heifers retained

Reported estimate of increase in value was $503 per heifer generated

77.8% indicated an increase in whole herd value as a result of their participation

Reported estimated of increase in value of $15,500 per operation

Research conclusions:

Project design, concepts, and progress were shared with have been shared at Face to face with just over 2,000 producers through the granting period. Continuing education training sessions were held for ND Farm Business Management instructors and at 4 North Dakota State University Extension Agent training sessions.  Project coverage was further disseminated through written materials presented in state and regional press and project results were disseminated at local, regional, national, and international meetings.  This project was also recognized by NDSU as an “Extension program Excellence” award winner for its combination of Extension agent and producer involvement and its ability to generate true level 4 evaluation using the Kirkpatrick Evaluation Model (i.e.  measures of bottom line changes, impacts on overall profitability). An Impact Report was developed (Available at: http://tinyurl.com/BreedingSystemSustainability), and an overview of our effort to evaluate the sustainability of beef cattle breeding systems were presented in an NDSU publication “Annual Highlights of the ND Ag Experiment Station. We also documented that participating producers have increased skills, awareness and knowledge of breeding systems, herd performance, and financial aspects of their operation.  A defined shift in calving distribution was noted at participants’ operations after implementing the AI treatment and calf weaning weights were also heavier for calved born in the AI treatment. We also documented that all producers have shared information regarding the project with other producers and 8 of 9 producers responding to survey questions indicated that they have changed their breeding systems as a result of their participation in the project.  Further, we defined what quality of life components participants felt are important and potentially impacted by breeding system of choice.  We also were able to document (via focus groups) the changes in producer perceptions of the effort required to complete tasks associated with each respective breeding system and the overall value they associated with 3rd party beef cattle production record evaluation as well as 3rd party farm financial record keeping. Results provide sound data to producers regarding the challenges and potential benefits of implementing different breeding systems in their commercial cow herds.  Economic analysis revealed that for optimal profitability 2 management changes should be made 1) implement AI, and 2) reduce number of breeding bulls maintained (in scenarios where 3 or more bulls are managed win a single group of females).  Producers also unanimously reported that working with a financial advisor impacted the long-term sustainability of their beef operation.

Economic Analysis

A partial budget analysis was completed for each operation to determine the economic implications of estrous synchronization and TAI. After determining the income generated or saved as well as the costs associated with the addition of estrous synchronization and TAI, net profit or loss was calculated. Table 1 details the financial items considered in the analysis. In terms of the current study, some factors that may affect increased returns will not be included in the analysis (i.e. improvement in herd genetics and uniformity).  Improvements in genetics can be made by breeding to high quality AI sires that are highly proven with the use of expected progeny differences (EPD’s). Additionally, because females are bred at a single time point with timed AI and often times to a small number of bulls, calves may appear more uniform in their phenotype, allowing producers to sell calves in large groups.

Table 1. Partial budget overview for AI use on commercial beef operations.

Increased returns Decreased returns
  • heavier calves
  • fewer cull bulls (scenario 2 only)
Decreased costs Increased costs
  • reduced number of bulls purchased (scenario 2 only)
  • labor
  • supplies (drugs, gloves, etc.)
  • technician
  • semen

Increased returns (A) were calculated by determining the average calf weaning weights for both cow treatments (CON or TAI). Natural service weaning weights were subtracted from TAI weights to evaluate the increased size and gain of calves from each respective treatment group. Average weaning weights for each operation were multiplied by the average price/pound received for calves.For each operation, partial budget scenarios for alterations in natural service bull numbers were evaluated. For each operation, two scenarios were used to evaluate the cost/profit differences: 1) clean-up bull numbers remained similar to previous years when TAI was not utilized (stocking rate of 1 bull per 25 cows), and 2) clean-up bull numbers were reduced to the mean number used in the industry after AI is implemented (1 bull per 39 cows; Dahlen and Stoltenow, 2015).

 

Results

In the analysis that included a bull to cow ratio of 1 to 25, producers lost an average of -$12.04 per cow by implementing estrous synchronization and AI (Figure 6.). An increase in the profit made in 5 of the 9 herd reporting sufficient data to conduct the analysis. Of important note, data from one operation (herd 10) is impacted by a pre-existing advantage in weaning weight of cows assigned to the natural service treatment, and therefore a perceived advantage to the natural service treatment in the economic analysis.  At the time of randomization and assignment to treatment these data were not available to evaluate.  However, after collecting weaning weight data on calves suckling at the time of breeding (i.e. those NOT impacted by treatment) the advantage of the natural service treatment was discovered.  With data from all herds included in the dataset he increased returns based on increases in calf weaning weight were not great enough to offset the cost of purchasing and raising bulls for natural service breeding.  Recall, however, that producers identified that potential genetic improvements and value of replacement heifers are not accounted for in the partial budgeting exercise.

In the analysis including a bull to cow ratio of 1 to 39, an average of $56.30 per cow profit was generated with the implementation of estrous synchronization and TAI. In contrast to the analysis in which no change in bull number was made, only a single operation lost profit due to the implementation of AI (which was also herd 10- see notes in previous paragraph). Due to the increased bull to cow ratio, decreased costs were included in the analysis as well as a reduction in returns caused by culling and selling fewer bulls.

 

These analysis point out several key items:

  1. Variation exists among operations in terms of profit response generated by implementing an AI breeding system
  2. For optimal profit response 2 management changes should be considered; implementing AI and reducing the number of bulls used to breed females that do not become pregnant to AI. Caution must be used with this approach and may be appropriate only when default management calls for 3 or more bulls to be are used on a single breeding pasture and stocking rates are normally 1 bull per 25 cows.
  3. Results are confined to impacts of changed calf weight as a results on implementing AI and do not include other economic considerations deemed important by participants.  Specifically:

    Responses to survey questions about change in value of several facets of participants’ operations:

    100% indicated an increase in the genetic value of their calves

    87.5% indicated an increase in the value of replacement heifers retained

    Reported estimate of increase in value was $503 per heifer generated

    77.8% indicated an increase in whole herd value as a result of their participation

    Reported estimated of increase in value of $15,500 per operation

 

Farmer Adoption

The greatest benefit of this project was for the producers directly participating in the on-farm research components of the project.  A survey revealed that 9 of 10 participants have continued to use AI in their operations.  Certainly there was conversations regarding how their future implementation may be different that what was used within the confines of the current project.

 

Project participants also reported a high degree (100%) of sharing project-related information.  This information was shared informally at community events and attendance of friends and neighbors on project work days as well as at formal field days held on producer operations and cattle brought to county fairs.  These activities as well as face to face interactions and written and TV exposure have the potential to play a role in the decisions made by producers of whether to implement AI.

 

Increased adoption rates of breeding systems that optimize producer profitability and quality of life was certainly a long-term goal of the project.  As indicated in the original proposal, however, we will be unable to document long term goals within the time frame of the grant period

 

Participation Summary

Educational & Outreach Activities

Participation Summary:

Education/outreach description:

Project design, concepts, and progress were shared with have been shared at Face to face with just over 2,000 producers at 37 meetings through the granting period. Results and/or project overviews were shared with groups in ND, MN, MT, SD, IA, NE, FL, KY, NJ, and OR as well as with groups in Brazil and China.  Continuing education training sessions were held for ND Farm Business Management instructors and at 4 North Dakota State University Extension Agent training sessions.  Project coverage was further disseminated through written materials presented in state and regional press and project results were disseminated at local, regional, national, and international meetings.  Radio and TV media were also used to present project overviews and/or results to larger audiences of producers and non-producers.

 

Publications arising from this effort include:

  1. Ph.D. Dissertation to be submitted Spring 2017. Mellissa Crosswhite. Thesis title “The Impact of Reproductive Technologies on Cattle and Management”
  2. Crosswhite, M.R., D.N. Black, S.R. Underdahl, T.L. Neville, and C.R. Dahlen. 2016. Effects of breeding system of origin (natural service or artificial insemination) on pregnancy rates, distribution of calving, and calf weaning weights of commercial beef cow herds in North Dakota. J. Anim. Sci. 94(E-Suppl. 5):119.
  3. Crosswhite, M.R., D.N. Black, T.L. Neville, S.R. Underdahl, and C.R. Dahlen. 2016. Effects of breeding system of origin (natural service or artificial insemination) on pregnancy rates, distribution of calving and calf weaning weights of commercial beef cow herds in North Dakota. 2016 North Dakota Beef Report (AS-1815):62-65.
  4. Dahlen, C.R. 2016. North Dakota State University Progress report of regional research project NC-1201. 2016 Annual Meeting of NC-1201 Regional Project Group.
  5. Dahlen, C.R. 2015. Is AI right for My Commercial Cows? The North Dakota Stockmen. April 2015.
  6. Dahlen, C.R. 2014. Fixed-time insemination in commercial beef herds. Carrington REC Annual Field Day handouts.
  7. Dahlen, C.R. 2013. The Research Corner: Evaluating the Sustainability of Beef Cattle Breeding Systems. The Ranch Hand August 2013.
  8. Dahlen, C.R. 2015. Evaluating the Sustainability of Beef Cattle Breeding Systems. Available at: http://tinyurl.com/BreedingSystemSustainability
  9. An overview of our effort to evaluate the sustainability of beef cattle breeding systems were presented in an NDSU publication “Annual Highlights of the ND Ag Experiment Station.

Project Outcomes

Recommendations:

Areas needing additional study

Factors that contribute to maximal pregnancy rates when using natural service mating (still the predominant breeding system in commercial beef herds).

Impact of different mineral supplementation programs on performance or beef herds (reproduction, calf wt, calving difficulty, etc).  Producers have MANY questions and relatively little data exist to address their concerns.

Evaluating differing numbers of females that can be placed with bulls after AI without reducing pregnancy rates (i.e. spending less money on bulls).

 

Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture or SARE.