Real Science Exchange

Please note the recording was before the new NASEM model was released. However, there is still a lot of good information from Dr. Weiss beyond those recommendations. This Real Science Exchange podcast episode was recorded during a webinar from Balchem’s Real Science Lecture Series. You can find it at balchem.com/realscience.Most ration formulation software uses the 2001 NRC mineral equations. The basic concept of the 2001 NRC mineral requirements is to feed enough absorbable minerals to maintain adequate labile body stores and fluid concentrations. Minerals are lost each day via excretion in feces and urine, milk production, and incorporation into tissues or the fetus in the case of growing or pregnant animals. We have decent data to predict mineral concentrations of milk, growth, and the fetus; however, the endogenous loss in feces is much harder to capture. Absorption coefficients (AC) for most minerals are exceedingly difficult to measure. (0:29)The NRC requirements are the means of several experiments. Feeding to the mean results in half the cows being fed adequately or in excess, and half are not fed enough. In human nutrition, recommended daily allowances for vitamins and minerals are calculated as the mean plus two standard deviations, which statistically meets the requirement for 97% of the population. Since the standard deviation of the requirement is hard to acquire, human nutrition uses the same standard deviation for energy metabolism, around 20%. Dr. Weiss feels this is a reasonable safety factor for minerals for animals as well. He recommends feeding about 1.2 times the NRC requirement while keeping an eye on the maximum tolerable limit for the mineral in question. (4:59)How do we measure absorption? We measure the minerals in the diet, we apply AC, and we get grams or milligrams of absorbed minerals available for the animal to use. Dr. Weiss details some of the complex methodology involved in trying to obtain AC. Feces contain not only unabsorbed dietary minerals but also endogenous/metabolic minerals (e.g., intestinal cells, enzymes, etc.) and homeostatic excretion of minerals (e.g., dumping excess minerals). In the 2001 NRC, the endogenous fecal for almost every mineral is a function of body weight, which is incorrect. It should be a function of dry matter intake. (8:40)Endogenous fecal losses can also be measured using stable or radioactive isotopes. This method is extremely expensive and if radioactive isotopes are used, management of radioactive waste becomes an issue. Thus, most of the AC for trace minerals that used these methods are 50-60 years old. (15:33)Dr. Weiss details some of the issues with calcium requirements in the 2001 NRC leading to overestimation of calcium absorption for many calcium sources and overestimation of the maintenance requirement due to endogenous fecal being calculated using body weight. Organic and inorganic phosphorus have different AC, so partitioning between organic and inorganic will give a more accurate estimate of the requirement. (16:33)Potassium has a linear antagonistic effect on magnesium. You can feed more magnesium to overcome this antagonism, but you won’t ever eliminate it. If you feed a few percent added fat as long-chain fatty acids, Dr. Weiss recommends feeding 10-20% more magnesium to account for soap formation in the rumen. (19:17)It’s much more difficult to measure AC for trace minerals due to multiple antagonists, interactions among different minerals, and regulated absorption. In addition, AC for trace minerals is very low, which means a small change in the AC can have a huge impact on diet formulation. All feeds in the NRC system have the same AC for each trace mineral and we know that’s not right.  (25:39)Dr. Weiss gives an overview of different trace mineral antagonisms and interactions and details his approach to formulation if he has absorption data for a particular ingredient. He also gives his estimates of revised AC for several minerals. (28:07)In summary, the factorial NRC approach only fits 50% of the population. Feeding an extra 10-20% above the NRC requirement includes about 97% of the population. We need to continue to account for more sources of variation in AC. Interactions need to be top of mind when considering mineral requirements and diet formulation. (37:39)Dr. Weiss takes a series of questions from the webinar audience. (40:50)Please subscribe and share with your industry friends to invite more people to join us at the Real Science Exchange virtual pub table.  If you want one of our Real Science Exchange t-shirts, screenshot your rating, review, or subscription, and email a picture to [email protected]. Include your size and mailing address, and we’ll mail you a shirt.

This Real Science Exchange podcast episode was recorded during a webinar from Balchem’s Real Science Lecture Series. You can find it at balchem.com/realscience.Feeding behavior of dairy cows is inherently tied to their dry matter intake (DMI) which is tied to milk production. If we want to change a cow’s DMI, it must be mediated by changing her feeding behavior. (00:23)In a multi-variable analysis, Dr. DeVries found that DMI was most associated with feeding time and meal frequency. It’s important to allow the cow to maximize the amount of time she can spend at the bunk eating, as well as the number of times she can get to the bunk each day. In one study, about 30% of the variability in milk fat content in cows on the same diet was explained by their meal frequency, where cows who had more meals per day had higher milk fat. Dr. DeVries also talks about the impacts of feeding behavior on cow efficiency and rumen dynamics. (2:13)As soon as a cow sorts the TMR put in front of her, she consumes a diet that’s variable in composition to what we expect. Cows who sorted against long feed particles had lower milk fat and milk protein concentrations. In another study, Dr. DeVries retrospectively analyzed cows with a low vs high risk of ruminal acidosis. Cows in both groups had similar DMI but a tendency for high-risk cows to have lower milk yield and numerically lower milk fat. Combining these resulted in significantly lower fat-corrected milk for the high-risk cows. Given that the diets and DMI were similar, the difference was attributed to sorting, which can have quite negative impacts on individual and herd-level production. (10:00)Cows spend nearly twice as much time ruminating as they do eating. Rumination reduces feed particle size and increases surface area, leading to increased rates of digestion and feed passage. In a recent study, Dr. DeVries’ group calculated the probability that cows were ruminating while lying down using automated monitoring data from previous experiments. Cows with a higher probability of ruminating while lying down had higher DMI, milk fat, and milk protein than cows who ruminated while standing. This highlights that cows need not only time to ruminate but also space for sufficient rest. (16:44)Diets and diet composition should be formulated to encourage frequent meals, discourage sorting, and stimulate rumination. Forage management factors including forage quality, forage quantity, forage type (dry vs ensiled), and particle size all play important roles. In a study with fresh cows, Dr. DeVries’ lab fed two different particle sizes of straw: 5-8 cm vs 2-3 cm in length. While DMI was the same over the first 28 days of lactation, cows fed the long straw spent more time with rumen pH below 5.8 because they were sorting against the straw. This also resulted in a yield difference, as the short straw-fed cows produced about 165 pounds more milk over the first 28 days compared to the long straw group. Dr. DeVries also comments on the use of feed additives on rumen stability and feeding behavior (22:54)More frequent feed delivery should generate more consistent consumption and better feeding behavior, and improve rumen health and milk component concentration. Shifting feed delivery away from return from milking, while still ensuring cows have abundant feed available, results in more consistent eating patterns. Dr. DeVries emphasizes that we push up feed to make sure it’s present at the bunk, not to stimulate cows to eat. We want to make sure that eating behavior is driven by the cow: when she's hungry and goes to the bunk, we need to make sure feed is there. (30:02)Dr. DeVries indicates we want to minimize the time cows are without feed completely. An empty bunk overnight plus a little overcrowding resulted in negative impacts on rumen health, including more acidosis and reduced fiber digestibility. Increased competition in overcrowding scenarios results in cows having larger meals, eating faster, and likely having a larger negative ruminal impact. In another study, every four inches of increased bunk space was associated with about 0.06% greater milk fat. Herds with high de novo fat synthesis were 10 times more likely to have at least 18 inches of bunk space per cow.  (40:04)In closing, Dr. DeVries’ biggest takeaway is that how cows eat is just as important as the nutritional composition of the feed in ensuring cow health, efficiency, and production. Collectively, with good quality feed and good feeding management, we can gain optimal performance from those diets. Dr. DeVries ends by taking questions from the webinar audience. (43:40)Please subscribe and share with your industry friends to invite more people to join us at the Real Science Exchange virtual pub table.  If you want one of our Real Science Exchange t-shirts, screenshot your rating, review, or subscription, and email a picture to [email protected]. Include your size and mailing address, and we’ll mail you a shirt.

Dr. Weiss and Dr. St-Pierre co-authored this episode’s journal club paper in Applied Animal Science (ARPAS Journal). Bill and Normand share a career-long interest in how feedstuffs and diet variation impact cows. (6:31)Bill and Normand discuss sources of variation, which they divide into true variation and observer variation. True variation means the feed has changed: a different field, change during storage, etc. Observer variation includes sampling variation and analytical variation. Some feeds may exhibit a lot of true variation and others may exhibit a lot of observer variation. And some feeds are high in both types of variation. Highly variable feeds should be sampled more frequently. Some feeds are so consistent that using book values makes more sense than sending in samples for analysis. Bill and Normand go on to give some examples and share sampling and analysis tips for different types of feedstuffs. (12:41)Bill would often be asked if users should continue to average new samples with older ones or just use the new numbers from the most recent sample. He and Normand debate the pros and cons of the two approaches as well as discuss the use of a weighted average where recent samples would be weighted to contribute more. (26:02)Next, our guests discuss how multiple sources of a nutrient reduce the TMR variation for that specific nutrient. For example, alfalfa NDF is more variable than corn silage NDF on average. Yet if you use a blend of these two ingredients, you end up with less variation in NDF than if you used all corn silage. Normand details the mathematical concepts behind this relationship. Both Bill and Normand emphasize that diets must be made correctly for the best results. (32:26)How do feedstuffs and diet variations impact cows? Both guests describe different experiments with variable protein and NDF concentrations in diets. Some were structured, like alternating 11% CP one day and 19% CP the next for three weeks. Some were random, like randomly alternating the NDF over a range of 20-29% with much higher variation than we’d ever see on-farm. The common thread for all these experiments is that the diet variations had almost no impact on the milk production of the cows. (38:04)Clay asks how variation in dry matter might affect cows. Bill describes an experiment where the dry matter of silage was decreased by 10 units by adding water. Cows were fed the wet silage for three days, twice during a three-week study. To ensure feed was never limited, more as-fed feed was added when the wet silage was fed. It took a day for cows on the wet silage treatment to have the same dry matter intake (DMI) as the control cows and milk production dropped when DMI was lower. However, when switching abruptly back to the dry silage diet, DMI increased the day following the wet silage and stayed high for two days, so the cows made up for the lost milk production. Bill and Normand underline that it is critical for the cows not to run out of feed and described experiments where feed was more limiting, yielding less desirable outcomes. (46:17)In the last part of the paper, our guests outlined seven research questions that they feel need to be answered. Normand shares that his number one question is how long will cows take to respond to a change in the major nutrients? He feels that we spend an inordinate amount of money on feedstuffs analysis, and there are some feeds we should analyze more and some feeds we should quit analyzing. Bill’s primary research question revolves around controlled variation. What happens if you change the ratio of corn silage and alfalfa once a week? Will that stimulate intake? Data from humans, pets, and zoo animals indicate that diet variation has a positive impact and Bill finds this area of research intriguing. (50:43)In closing, Clay encourages listeners to read this paper (link below) and emphasizes the take-home messages regarding sampling and research questions. Normand advises that if you are sampling feed, take a minimum of two samples, and try as much as you can to separate observer variation from true variation. He also reminds listeners to concentrate on a few critical nutrients with more repeatability for analyses. Bill encourages nutritionists to sit down and think when they get new data - before they go to their computer to make a diet change. If something changed, why did it change, and is it real? Take time to think it through. (1:01:38)You can find this episode’s journal club paper from Applied Animal Science here: https://www.appliedanimalscience.org/article/S2590-2865(24)00093-4/fulltextPlease subscribe and share with your industry friends to invite more people to join us at the Real Science Exchange virtual pub table.  If you want one of our Real Science Exchange t-shirts, screenshot your rating, review, or subscription, and email a picture to [email protected]. Include your size and mailing address, and we’ll mail you a shirt.

This Real Science Exchange episode was recorded during a webinar, which was part of a series. Watch all the presentations from this series here: https://balchem.com/animal-nutrition-health/resources-categories/real-science-lecture-series/previous-lectures/page/10/Early in lactation, the cow is incapable of eating enough to meet her dramatically increased requirements. As the cow’s intake decreases near calving, there are fewer nutrient contributions from dry matter intake and she must alter nutrient partitioning to meet her increased needs by mobilizing fat and muscle stores. (1:18)Triglycerides from fat stores are broken down into non-esterified fatty acids (NEFA) and glycerol. NEFA has two different fates in the postpartum cow: to the mammary gland as a precursor for milk fat synthesis, or to the liver to be oxidized for energy production. Glycerol enters the gluconeogenic pathway in the liver as a glucose precursor. (4:41)The capacity for the liver to use NEFA for energy is limited by the capacity of the TCA cycle. When the TCA cycle is at capacity, excess NEFA can either undergo incomplete oxidation to ketones or be repackaged back into triglycerides. If the capacity for other tissues to use ketones for energy is exceeded, then blood concentrations of ketones rise and negative outcomes from subclinical and clinical ketosis can occur. If triglycerides accumulate in the liver, negative outcomes associated with fatty liver can occur. Triglycerides can be transported out of the liver via very low-density lipoprotein (VLDL) export; however, VLDL export does not keep up with triglyceride concentration during the transition period in dairy cows, largely because of a limiting amount of phosphatidylcholine. (5:51)Dr. White describes a series of experiments in her lab using liver cells in culture to investigate the relationship between choline supplementation and VLDL export. As choline supplementation to the cell culture increased, so did VLDL export from the cells into the media. In addition, increasing choline supplementation to the cell culture also decreased cellular triglyceride content. (10:54)Using gene expression and radiolabeled tracers over a series of experiments, Dr. White’s group found that as choline supplementation increased, so did complete oxidation of NEFA to energy. This was accompanied by decreased incomplete oxidation to ketone bodies and decreased accumulation of lipids in the liver cells. Glucose and glycogen were also increased with increasing choline supplementation to the cell culture, and a decrease in reactive oxygen species was observed. In addition, choline-supplemented cultures exhibited an increase in metabolic pathways associated with methionine regeneration and methyl donation. (15:29)Dr. White then details the complexity of the metabolic pathways that intersect between choline and methionine. In similar experiments supplementing cell cultures with increasing amounts of methionine and choline, there were no effects of methionine on lipid export, oxidative pathways, or glucose metabolism. The main benefit of methionine was a marked increase in glutathione production. It’s important to note that no interactions between choline and methionine were observed in this series of experiments. (19:37)There seems to be a clear biological priority for different sets of pathways for choline and methionine. Choline seems to be influencing lipid, glucose, and oxidative pathways, while methionine is primarily serving its role as an essential amino acid for cellular protein structure and generation, acting as a methyl donor, and impacting inflammation. Importantly, both the choline and methionine results observed in cell culture are paralleled in transition dairy cow studies. (24:14)Dr. White’s lab further investigated the impact of methionine on inflammation. When cells were challenged with LPS to provoke an inflammatory response, methionine mitigated the inflammatory response. Similar results have been observed in liver tissue samples of transition cows. Methionine mitigated inflammatory markers and increased glutathione but did not influence reactive oxygen species. Conversely, choline decreased reactive oxygen species but did not change glutathione. (27:47)Choline and methionine are both essential nutrients, there are biological priorities for them as methyl donors, and they are not mutually exchangeable. The lack of interaction between choline and methionine in vivo or in vitro supports the idea of different biological roles for these nutrients. (32:09)Dr. White takes questions from the webinar audience. (34:53)Please subscribe and share with your industry friends to invite more people to join us at the Real Science Exchange virtual pub table.  If you want one of our Real Science Exchange t-shirts, screenshot your rating, review, or subscription, and email a picture to [email protected]. Include your size and mailing address, and we’ll mail you a shirt.