Routine, whole-herd deworming is giving way to a more strategic approach as veterinarians grapple with resistance, subclinical production losses, and changing management goals. In this episode, Dr. Megan Bollin and Dr. Nancy Jackson discuss diagnostics, refugia, combination therapy, and every day management practices shaping the future of parasite control in cattle.

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This episode brings together three expert perspectives to tackle milk fever from every angle. Together, they unpack why milk fever is more than just a calcium deficiency and how better transition cow management, nutrition and early intervention can reduce both clinical and subclinical cases.

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You can't see fertility, feed efficiency or disease risk, but genomics can. In this episode, host Andrea Bedford sits down with Dr. Tom Short and Dr. Kent Andersen to discuss how genomic testing is helping reduce risk, improve profitability and move from herd-level decisions to individual-animal precision.

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In a special episode coming from the National Cattlemen’s Beef Association Convention, I do a series of rapid-fire interviews with the companies behind the latest pharmaceuticals, tech, and equipment and finding the answer to the important question: How will these new products actually impact your daily veterinary practice

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Mastitis detection has advanced rapidly, with new technology promising better outcomes. In this episode, we explore mastitis as a systems-level problem shaped by housing, labor, management decisions, and data interpretation, not just pathogens. Dr. Justin Hess, a bovine veterinarian in Michigan, and Dr. Alon Arazi, chief veterinarian at Afimilk, discuss with me where current detection tools perform well, there they fall short, and why subclinical mastitis remains one of the biggest blind spots on dairies. We discuss how automated monitoring systems flag abnormal patterns, why they are not a diagnostic on their own, and how false positives can undermine trust if sensitivity and specificity are poorly balanced. The conversation also looks ahead to the future of mastitis detection, including earlier risk identification, predictive modeling, and the potential for insight into pathogen type.

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