CMC – Learn More
There are many resources describing modern colostrum management, transfer of passive immunity, and the use of simulation to evaluate biological systems in which inputs and outcomes vary. Here are a few, in no particular order. Links to external sites are not endorsements of their content, products, or services.
Modern Colostrum Feeding Recommendations
Modern colostrum programs have moved beyond simply preventing failure of passive transfer in individual calves. Current recommendations increasingly emphasize the distribution of passive immunity within the herd and the proportion of calves achieving excellent, good, fair, or poor transfer of passive immunity.
- Consensus recommendations on calf- and herd-level passive immunity in dairy calves in the United States – Lombard et al., 2020
- Colostrum Management for Dairy Calves – Godden, Lombard, and Woolums, 2019
- Invited review: The importance of colostrum in the newborn dairy calf – Lopez and Heinrichs, 2022
- Colostrum management practices that improve the transfer of passive immunity in neonatal dairy calves: A scoping review – Uyama et al., 2022
- A Scoping Review of On-Farm Colostrum Management Practices for Optimal Transfer of Immunity in Dairy Calves – Robbers et al., 2021
Calf Notes About Colostrum
Calf Notes has addressed colostrum feeding and passive immunity since the first Calf Note was published in 1997. These are several of the most recent Notes dealing with colostrum management, IgG absorption, and the interpretation of passive immunity.
- Calf Note #277 – Plasma Volume: The Hidden Variable in AEA
- Calf Note #273 – Why Apparent Efficiency of Absorption Is Only Apparent
- Calf Note #271 – What’s Happening? Episode 9 – Colostrum Storage
- Calf Note #269 – What’s Happening? Episode 7 – Measuring Colostrum Quality
Monte Carlo Simulation in Science and Agriculture
Monte Carlo simulation is widely used when the inputs to a system are variable or uncertain. Rather than calculating a single outcome from average inputs, the method repeatedly samples values from probability distributions and calculates the resulting range and probability of possible outcomes. This same basic approach is used in CMC to represent variation among calves, colostrum, and management.
- Monte Carlo Tool – National Institute of Standards and Technology (NIST)
- Monte Carlo Methods in the Physical Sciences – U.S. Department of Energy
- Food Risk Analysis: Monte Carlo Simulation Methods in Risk Assessment Modeling – USDA Agricultural Research Service
- Alley Cropping as an Alternative Under Changing Climate and Risk – USDA Forest Service
- Monte Carlo Simulations for Farm Planning – U.S. International Trade Commission
Monte Carlo simulation is particularly useful for CMC because a dairy herd is not composed of identical calves receiving identical colostrum at identical times. Simulation provides a way to combine these sources of variation and estimate the distribution of outcomes expected from a colostrum management program, rather than predicting the response of only an average calf.