Non Technical Summary
Mastitis is the most common and costly disease affecting organic dairy cows, ranking within the top two reasons for early removal of cows within US organic herds. Effective mastitis control is of utmost importance, but options for prevention and treatment are limited in organic herds. The long-term goal of this integrated proposal is to identify and develop cost-effective management solutions that will control mastitis, improve milk quality, promote welfare, and enhance the sustainability of the organic dairy community. The overall goal is to develop and assess an integrated systems approach for mastitis control and welfare. The central hypothesis is that combining environmental and animal-level solutions will be effective to control mastitis and improve milk quality and cow welfare. We propose the following specific objectives: 1) Developing and delivering a comprehensive mastitis and milk quality Extension program with emphasis on prevention and control practices. 2) Assessing the effect of management practices during the dry period on early lactation mastitis and testing the efficacy of novel interventions at dry-off to develop mastitis control solutions; 3) Developing a mastitis index as financial and welfare measures of the mastitis and milk quality burden to identify top areas for improvement; 4) Evaluating the impact of cow comfort on mastitis and milk quality by using precision technologies; and 5) Identifying leading risk factors associated with mastitis and milk quality in organic dairies. Developing and delivering an integrated approach with best solutions will reduce mastitis, improve milk quality, and enhance the long-term sustainability of organic dairy herds.
Animal Health Component
Research Effort Categories
Goals / Objectives
Thelong-term goal of this integrated proposal is to identify and develop cost-effective managementsolutions that will control mastitis, improve milk quality, promote welfare, and enhance thesustainability of the organic dairy community. The overall goal is to develop and assess anintegrated systems approach for mastitis control and welfare. The central hypothesis is thatcombining environmental and animal-level solutions will be effective to control mastitis, improvemilk quality, and cow welfare. We propose the following specific objectives: 1) Developing anddelivering a comprehensive mastitis and milk quality Extension program with emphasis onprevention and control practices. 2) Assessing the effect of management practices during the dryperiod on early lactation mastitis and testing the efficacy of novel interventions at dry-off todevelop mastitis control solutions; 3) Developing a mastitis index as financial and welfaremeasures of the mastitis and milk quality burden to identify top areas for improvement; 4)Evaluating the impact of cow comfort on mastitis and milk quality by using precisiontechnologies; and 5) Identifying leading risk factors associated with mastitis and milk quality inorganic dairies. Developing and delivering an integrated approach with best solutions will reducemastitis, improve milk quality, and enhance the long-term sustainability of organic dairy herds.
Objective 1 (Extension)Sub-objective 1A and 1B: With the continuous assistance of the advisory panel and considering the diverse organic dairy farm community, educational needs will be identified for the workshops and webinars starting in year 1 through year 4. Findings from the research Objectives will also be integrated and used during the educational training. Workshops will consist of 1-day training modules. All training workshops and webinars will be offered at no cost and open to all stakeholders. Each identified educational topic or area will be developed around common themes with several interconnected topics delivered using short webinar to support the overall theme. The webinar series will be recorded and available online. The content of the modules will be captured digitally and loaded to electronically assessable formats. We will promote participants' interaction through short oral presentations followed by discussion and hands-on demonstrations. For Sub-objective 1C, we will focus on changes in attendees' satisfaction, knowledge gain, and willingness to adopt best management practices evaluated by 1) pre- and post-tests of knowledge and questionnaire surveys that will be developed to set a baseline on performance of herds and to measure willingness to adopt best management practices. Participants will have the opportunity to evaluate the program and instructors and provide feedback using predesigned evaluation instruments and the Evaluation of Effective Extension Teaching (The Ohio State University). Objective 2 (Dry-off methods)Sub-objective 2.A.: We will perform a controlled experiment to evaluate the effect of two separated strategies at dry-off: i) Gradual cessation of milking before dry-off; and ii) Intramammary application of a natural product based on carvacrol administered at dry-off. Based on records indicating the future dates for dry-off, 1,764 cows will be randomly assigned to be submitted to either abrupt or gradual dry-off (1x/day final week of lactation. Fifty percent of the cows in each group will be administered a natural product based on essential oils containing carvacrol after the final milking at dry-off. Milk samples will be collected at the last milking and within the first 3 days of lactation for culture and for somatic cell count (SCC). A third sample will be collected at 15 days in milk for SCC. Culture data and SCC will be compared among the four groups. Occurrence of clinical mastitis within 30 days in milk is another relevant outcome of interest. Milk analyses will be completed at the Quality Milk Production Services, Animal Health Diagnostic Center at Cornell University.Objective 3 (Mastitis index)Sub-objective 3.A.: We will rely on the Co-PDs contacts and the assistance of the Advisory Committee members (especially Dr. Guy Jodarski, Organic Valley Veterinarian) to reach our target farms for surveying. Co-PDs and graduate students will perform field visits using a survey instrument that will be pre-tested in a focus group. The surveys will collect data about specific risk factors associated with on-farm management aspects related to mastitis and milk quality, including housing, milking, and dry period management. Study personnel will score cows for udder hygiene and teat condition. Information regarding pasture and crop management and nutritional quality will be made available to us (Organic Valley databases).Sub-objective 3.B.: We will calculate failure costs of mastitis in organic dairy cows using methodology in the literature, including milk loss, reduced reproductive performance, increased culling, loss of organic status, and lower milk quality. We will use the dynamic programming approach of De Vries (2004, 2006) and new extensions for cow specific modeling currently in development (USDA NIFA FACT 2019-67021-28823) and from Cha et al. (2011) and other published mastitis models. This modeling approach is needed because failure cost depends on the best decision made and the opportunityand their costs that directly or indirectly help prevent mastitis on organic dairy farms using data from our sub-objective 3A surveys and the approach of Van Soest et al. (2016). The financial mastitis index will be expressed in dollars per cow per year).Our methodology of the financial mastitis index allows to be approximated by organic dairy farms by entering their data in a user-friendly tool. Sub-objective 3.C.: We will identify on-farm practices that lead to low mastitis index values using analysis of variance. These practices are top management opportunities for reducing the mastitis burden.Objective 4 (Cow behavior)Sub-objective 4.A. and 4B: Methods to collect precision dairy behavior data and other cow event data include backups from on-farm software and access to cloud-storage of dairy data.We will use SAS to organize the data due to our long-term experience with that data management and statistical software. We will analyze the collected database with classical regression as well as random forest machine learning methods. For the association analyses, data from affected cows will be matched with healthy controls and analyzed to determine relationships between behavioral traits indicative of cow comfort and the risk of developing mastitis. Objective 5 (Risk factors)Sub-objective 5.A. Farm data provided by Dairy Herd Improvement Association (DHIA) and Organic Valley will be edited and organized in lactation records, differentiating organic and conventional farms. Data from individual cows will be the base for herd level calculations. Files will be prepared in a format that is adequate for the subsequent analyses to be completed with SAS (SAS institute Inc., Cary, NC).Sub-objective 5.B. Statistical analyses will depend on the nature of the variables under analysis (continuous/categorical). Briefly, ANOVA, logistic regression, and time to event analysis will be considered for the analyses. The focus will be placed on characterizing mastitis and milk quality at the individual and at the herd level, comparing variables related to the cow and the herd, as well as considering the organic and conventional status of farms.Sub-objective 5.C. Association analysis will help identify important risk factors for mastitis and suboptimal milk quality. Of special interest for organic dairies are breed, longevity, milk yield, dry-off and dry period characteristics, among others. Herd level variables include herd size, type of housing, location, seasonality, etc. Univariate calculations of incidence risk for mastitis will be used to describe overall disease frequency. Additionally, univariate survival analysis will be used to determine the Kaplan-Meier median DIM to the first occurrence of mastitis event per lactation. Associations between risk factors and udder health outcomes will be assessed through multivariable logistic regression.Sub-objective 5.D.: Datasets from 8 large organic herds in CO and TX, including 95,000 lactations will be organized into records with the data collection starting at the dry-off date from the previous lactation in multiparous cows or at calving in primiparous cows. Milk yield and SCC are also available. Incidence risk for mastitis will be calculated considering stratification by multiple variables, such as parity number, 305 d ME milk yield during the previous lactation, last milk yield recorded before dry-off, season of dry-off, access to grazing at dry-off, length of the dry period, length of the close-up period, gestation length, season of calving, access to grazing at calving, and concurrent health conditions.