Metabolic Body Weight Research Articles

Intake, digestibility, energy and nitrogen utilisation, and enteric methane emission in Holstein and Girolando-F1 cows during the transition period

ABSTRACT This study aimed to evaluate intake, energy and nitrogen balance as well as methane emission in Holstein and ½ Holstein ½ Gyr (Girolando-F1) cows during the transition period. Twenty-four cows (12 Holstein and 12 Girolando-F1) were used to evaluate feed intake, apparent digestibility, heat production and methane emission, carried out in two periods: from 28 to 19 days pre-calving and from 15 to 23 days post-calving. A completely randomised design was used and data were analysed by ANOVA within periods (pre- and post-calving) considering the main effect of genetic groups. Girolando-F1cows presented greater body condition score (BCS) compared with Holstein. During pre-calving, there were no differences between genetic groups, except for highest heat production per kilogram of metabolic body weight for Holstein cows. After calving, Holstein cows had greater intake of DM, nitrogen, NDF per kg of BW and produced more heat per kg of metabolic body weight. Holstein cows yielded more milk and fat-corrected milk (FCM4%) compared with Girolando-F1 cows. Holstein cows presented higher methane emission per unit of BW and of metabolic weight. Emissions of enteric methane per kilogram of milk and per kilogram of FCM4% tended to be lower for Holstein compared with Girolando-F1 cows. Nitrogen and energy retention were similar for both Holstein and Girolando-F1 at pre- and post-calving. Despite differences in BCS, DMI, and milk yield, Girolando-F1 and Holstein cows present overall similar energy efficiency, albeit Holstein cows tended to present less methane emission per kg of eligible product (milk).

Transition in metabolic health phenotypes across general adiposity categories and association with the risk of depression: a prospective analysis.

The association between obesity and depression may partly depend on the contextual metabolic health. The effect of change in metabolic health status over time on subsequent depression risk remains unclear. We aimed to assess the prospective association between metabolic health and its change over time and the risk of depression across body mass index (BMI) categories. Based on a nationally representative cohort, we included participants enrolled at the wave 2 (2004-2005) of the English Longitudinal Study of Ageing and with follow-up for depression at wave 8 (2016-2017). Participants were cross-classified by BMI categories and metabolic health (defined by the absence of hypertension, diabetes, and hypercholesterolemia) at baseline or its change over time (during waves 3-6). Logistic regression model was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for the risk of depression at follow-up stratified by BMI category and metabolic health status with adjustment for potential confounders. The risk of depression was increased for participants with metabolically healthy obesity compared with healthy nonobese participants, and the risk was highest for those with metabolically unhealthy obesity (OR 1.62, 95% CI 1.18-2.20). Particularly hypertension and diabetes contribute most to the increased risk. The majority of metabolically healthy participants converted to unhealthy metabolic phenotype (50.1% of those with obesity over 8years), which was associated with an increased risk of depression. Participants who maintained metabolically healthy obesity were still at higher risk (1.99, 1.33-2.72), with the highest risk observed for those with stable unhealthy metabolic phenotypes. Obesity remains a risk factor for depression, independent of whether other metabolic risk factors are present or whether participants convert to unhealthy metabolic phenotypes over time. Long-term maintenance of metabolic health and healthy body weight may be beneficial for the population mental well-being.

Accurate locomotor activity profiles of group-housed mice derived from home cage monitoring data.

Holistic phenotyping of rodent models is increasing, with a growing awareness of the 3Rs and the fact that specialized experimental setups can also impose artificial restrictions. Activity is an important parameter for almost all basic and applied research areas involving laboratory animals. Locomotor activity, the main form of energy expenditure, influences metabolic rate, muscle mass, and body weight and is frequently investigated in metabolic disease research. Additionally, it serves as an indicator of animal welfare in therapeutic, pharmacological, and toxicological studies. Thus, accurate and effective measurement of activity is crucial. However, conventional monitoring systems often alter the housing environment and require handling, which can introduce artificial interference and lead to measurement inaccuracies. Our study focused on evaluating circadian activity profiles derived from the DVC and comparing them with conventional activity measurements to validate them statistically and assess their reproducibility. We utilized data from metabolic studies, an Alzheimer's disease model known for increased activity, and included DVC monitoring in a project investigating treatment effects on activity in a type-1-like diabetes model. The DVC data yielded robust, scientifically accurate, and consistent circadian profiles from group-housed mice, which is particularly advantageous for longitudinal experiments. The activity profiles from both systems were fully comparable, providing matching profiles. Using DVC monitoring, we confirmed the hyperactivity phenotype in an AD model and reproduced a decline in activity in type-1-like diabetes model. In our work, we derived robust circadian activity profiles from the DVC data of group-housed mice, which were scientifically accurate, reproducible and comparable to another activity measurement. This approach can not only improve animal welfare according to the 3R principles but can also be implement in high-throughput longitudinal studies. Furthermore, we discuss the advantages and limitations of DVC activity measurements to highlight its potential and avoid confounders.

Diabesity and Dietary Interventions: Evaluating the Impact of Mediterranean Diet and Other Types of Diets on Obesity and Type 2 Diabetes Management.

Diabesity, the intersection of obesity and diabetes, presents a global health crisis with profound implications. Addressing diabesity requires multifaceted strategies, with diet playing a pivotal role. Over the last 15 years, clinical studies have intensified their exploration of various dietary approaches in diabesity management. This literature review aims to synthesize findings from clinical studies conducted in the last 15 years, shedding light on the efficacy, mechanisms, and nuances of different diet types in diabesity management with special focus on the Mediterranean diet (MD). Thorough research of academic databases yielded a collection of relevant clinical studies. These studies encompassed a range of dietary strategies, including the MD, low-carbohydrate diets, plant-based diets, high-protein diets, low-fat regimens, and intermittent fasting. Key findings, methodologies, and outcomes were thoroughly extracted and analyzed. The last 15 years have witnessed considerable improvements in recognizing the role of human nutritional habits in diabesity management. The MD appears to be the most well-recognized diet, exerting favorable effects against both obesity and diabetes. Low-carbohydrate diets were found to enhance glycemic regulation and decrease insulin resistance. Plant-based diets demonstrated potential benefits in weight management and cardiometabolic health. High-protein, low-fat dietary models exhibited positive effects on satiety and body weight decline. Intermittent fasting regimens also exerted metabolic improvements and body weight decline. Personalization emerged as a crucial factor in dietary recommendations. Clinical studies from the last 15 years underscore the intricate relationship between diet types and diabesity management. The above results contribute to an increasing body of evidence, emphasizing the need for tailored dietary approaches and especially the MD. Healthcare providers can utilize this knowledge to offer personalized dietary recommendations for individuals with diabesity, potentially curbing the rise of these twin epidemics and improving the well-being of affected populations.

Влияние триметазидина на метаболизм L-аргинина в лейкоцитах и панкреасе в АС- режиме химиотерапии

The AC-chemotherapy regimen had a cardiotoxic effect in healthy rats associated with body weight loss. At the same time, lipid peroxidation (LPO) processes and arginase activity are stimulated, and production of bioavailable nitric oxide (NO) in leukocytes and pancreas decreases which may be involved in (DOX-CY)-induced cardiovascular complications. Correlations were also observed between these metabolic parameters and body weight. Trimetazidine had a cardioprotective effect in the AC-chemotherapy regimen that correlated with the increase in body weight of animals. There was found a regulatory effect of the drug on LPO processes, arginase activity, and bioavailable NO production, which were simultaneously correlated with weight changes and can participate in the drug’s pleiotropic and systemic effects and clinical efficacy.

Diet Digestibility and Partitioning of Nutrients in Adult Male Alpacas Fed a Blend of Oat Hay and Alfalfa Pellets at Two Levels of Intake

Alpacas are well adapted to consume the poor-quality forages present in the arid conditions of the Andean Altiplano. However, studies focusing on understanding the relationship between diet digestibility and intake are scarce. The aim of this study was to evaluate the effects of two levels of dry matter intake (DMI) on a metabolic body weight (BW0.75) basis. The effects of a maintenance level of intake and an ad libitum level of intake (40 and 50 g of dry matter (DM) per kg of BW0.75, respectively) on the apparent diet digestibility and partitioning of specific nutrients (energy, carbon (C), and nitrogen (N)) of alpacas that were fed a blend of oat hay and alfalfa pellets (70:30 ratio as a percentage on a fed basis) were evaluated. Five adult intact male alpacas (BW = 62.9 ± 8.09 kg at the beginning of the study) were fed with the experimental diet and trained to be allocated in metabolism crates for 30 days. After the completion of this phase, two separate experiments for each level of intake were carried out, each lasting for twenty-six days (with the final five days taken for samples and raw data collection). In both experiments, the animals responded differently in terms of nutrient supply and changes in BW (−140 and 100 g/d for the maintenance and ad libitum levels of intake, respectively). Oat hay consumption was rather similar in both experiments, which may be explained by a reduced ingredient selectivity at the ad libitum level of intake. Diet digestibility was similar in both experiments, despite the greater fecal output of nutrients with the increased level of diet intake. In line with this, diet metabolizability, calculated as the ratio between metabolizable energy (ME) and gross energy (GE) contents, indicated a similar energy utilization of the diet. The apparent digestibility of the organic matter (OMD) ranged from 655 to 669 g/kg DM. Water consumption at the ad libitum level of intake was 21% higher than the observed mean at the maintenance level of intake. Fecal outputs of dietary energy, C, and N accounted for the largest source of excreted nutrients, regardless of the level of intake. The N retention increased from 0.439 at the maintenance level of intake, to 0.473 g of DM/kg BW0.75 when the alpacas were fed ad libitum.

Effect of Supplementing a Bacillus Multi-Strain Probiotic to a Post-Weaning Diet on Nutrient Utilisation and Nitrogen Retention of Piglets

Probiotics are suggested to improve pig health, nutrient utilisation, performance, and they may reduce nitrogen (N) pollution. However, the effectivity of a single strain might be different from that of a multi-strain. The study was conducted to investigate the effect of a novel Bacillus multi-strain on nutrient digestibility, energy utilisation, and N retention in weaned piglets using an European diet. The experiment consisted of a control diet (CD) and a supplemented diet (SD). The probiotic used for SD consisted of B. amyloliquefaciens—516 and B. subtilis—541. A total of eight boars/treatment were weaned (day 0; 8.5 kg body weight). Only boars were used to ease the collection of urine. Until day 10, piglets were fed ad libitum and were housed in pairs; from day 11, piglets were fed semi ad libitum (feeding level 3.2× metabolic body weight) and were housed individually. From day 14, faecal and urine were collected twice daily. Piglets were humanely euthanised at day 19 (15.0 kg bodyweight) after which the jejunum, ileum, and colon content were collected. In faeces, the apparent total tract digestibility (ATTD) of, amongst others, DM, organic matter (OM), crude protein (CP), non-starch polysaccharides (NSP), and subsequently net energy (NE) were calculated using titanium dioxide as an indigestible marker. In the jejunum and ileum, the apparent digestibility of CP was estimated, and in the ileum, the apparent AA digestibility was measured. In urine, the N content was measured to determine N retention. The volatile fatty acid (VFA), branched-chain fatty acid (BCFA), and lactic acid content were analysed in the colon and faeces. The apparent CP digestibility in the jejunum and ileum was not affected by treatment (p > 0.05), and no effect was observed on the apparent ileal digestibility of AA (p > 0.05). Supplementation with the multi-strain probiotic improved the ATTD of DM (p = 0.01; +1.3%) and OM (p = 0.02; +1.2%) and tended to improve the ATTD of CP (p = 0.10; +2.2%) and NSP (p = 0.07; +1.9%). The multi-strain probiotic also improved the NE value (p = 0.02; +0.2 MJ/kg DM) and improved N retention (p = 0.05; +1.6%). Supplementation did not influence the VFA, BCFA, and lactic acid content in the faeces (p > 0.05). However, in the colon, supplementation did influence the lactic acid content (lower; p = 0.01) and tended to influence the valeric acid content (higher; p = 0.09). In conclusion, results from the current study suggest that the multi-strain probiotic has the potential to contribute to improve nutrient efficiency in weaned piglets. More research needs to be conducted to identify the impact of the improved nutrient utilisation on gut health in post-weaned pigs as well as environmental pollution.

Age-Dependent Changes in the Effects of Androgens on Female Metabolic and Body Weight Regulation Systems in Humans and Laboratory Animals

In recent years, the effects of androgens on metabolic and body weight regulation systems and their underlying mechanisms have been gradually revealed in females. In women and experimental animals of reproductive age, androgen excess can adversely affect metabolic functioning, appetite, and body weight regulation. In addition, excess androgens can increase the risk of metabolic disorders, such as obesity, insulin resistance, and diabetes. These unfavorable effects of androgens are induced by alterations in the actions of hypothalamic appetite-regulatory factors, reductions in energy expenditure, insulin resistance in skeletal muscle, and β-cell dysfunction. Interestingly, these unfavorable effects of androgens on metabolic and body-weight regulation systems are neither observed nor evident in ovariectomized animals and post-menopausal women, indicating that the adverse effects of androgens might be dependent on the estrogen milieu. Recent findings may provide novel sex- and age-specific strategies for treating metabolic diseases.

PSIX-13 Intake Differences in Small Dogs Suggest a Need for Size-Specific Energy Considerations

Abstract The domestic dog is one of the most diverse mammalian species in the world. However, knowledge regarding potential differences in metabolism and disparities in nutritional considerations due to body size is limited. The primary focus of this study was to investigate differences in energy needs of small dogs compared with medium and large dogs by analyzing longitudinal intake for individuals of varying body sizes. A secondary aim was to assess age-associated differences in the energy needs of small dogs by comparing longitudinal intake between young and old small dogs. Caloric intake (kcal/d), metabolic body weight (MBW)-adjusted caloric intake (kcal/kg0.75/d; MBW-Kcal), and BW were assessed in a population of mature adult dogs dogs (10.8 ± 1.9 yr; n = 58) categorized into three size groups based on ideal body weight; small (≤11 kg; n = 19), medium (11 < x < 22 kg; n = 29), nd large (≥ 22 kg; n = 10). The second study population was made up of small dogs less than seven years old (1.2 ± 0.8 yr; ≤11 kg; n = 46). All dogs were fed to maintain ideal BW. Intake was measured daily; BW was recorded monthly. The activity factor (AF) of each dog was calculated by dividing daily caloric intake by their resting energy requirement. ANOVA was used to assess effects of size and age on all data. Nonparametric test of medians was conducted to evaluate the distribution of MBW-Kcal. As expected, caloric intake increased as size increased (P < 0.001); however, this effect was not attenuated by adjusting for MBW (P < 0.001). Mean MBW-Kcal was greater in small dogs than medium (P < 0.001) and large dogs (P = 0.031). The variance of MBW-Kcal in small dogs was greater than in large (P < 0.001) and medium dogs (P < 0.001), indicating that small dogs had a larger range in the distribution of caloric intake even when adjusted for MBW (Figure 1). Mean AF of small dogs (1.7) was also greater than large (1.5; P = 0.030) and medium dogs (1.5; P < 0.001), but the AF of medium and large dogs were similar (P = 0.650). MBW-kcal and AF were similar between small old and young dogs (P > 0.05). These data demonstrate that even when adjusted for MBW, small dogs may require more calories to maintain BW than their medium- and large-breed counterparts, and this increased caloric need appears to be sustained in both dmall young and old dogs. These results suggest that small breed dogs have different metabolic factors driving caloric needs compared with larger dogs and further emphasize that nutritional guidelines should be updated to better reflect the energy needs of small dogs across life stages.

325 Understanding Variation in Residual Feed Intake of Brahman Steers Fed Two Different Diets

Abstract Improving feed efficiency in cattle is a long-standing aim of the beef industry. However, discrepancies in the ranking of bulls based on the diets used and calculation methods employed for defining feed efficiency have been observed. Hence, the objective of this research was to assess the extent to which different factors influence feed efficiency in Brahman steers. Individual DMI and ADG were measured, and residual feed intake (RFI) calculated using linear regression of DMI on ADG and midtest metabolic body weight. Eight-nine steers were initially fed a low-protein diet (LP, 8.8% CP) for 70 days, followed by a high-protein (HP, 13.5% CP) diet for another 70 days. The genetic variation among steers and the proportion of Bos indicus genes were determined using the GGP Indicus 50K assay (Neogen Corporation, Ipswich, Australia). Rumen bacteriome variation was determined with 16S rRNA gene sequencing of rumen fluid collected before and after feeding. Daily diet refusals were visually scored for the proportion of pellets versus hay and expressed as a diet selection index (1 to 3). Organic matter digestibility (OMD) was determined using total feces collection in metabolism crates. Plasma urea nitrogen (PUN) was measured in blood samples collected at four time points. The diet-animal fractionation of nitrogen isotopes (Δ15Ntail hair) was quantified in tail hair using isotope-ratio mass spectroscopy to indicate differences in nitrogen metabolism. Finally, carcass characteristics were determined at slaughter. Including carcass fat depth improved (P = 0.01) DMI prediction (R2 increased from 78.4 to 80.4%) in the LP diet but had a smaller effect (P = 0.39) in the HP diet (R2 increased from 75.0 to 75.2%). In the LP diet, the variation in carcass fat-correct RFI (RFIc) could be explained by DMI (14.5% of the variation), rumen bacteriome (5.89%), diet selection index (3.08%), PUN (1.88%), genetic distance (0.76%) and OMD (0.50%), accounting for a total of 26.6% of the RFIc variation. In the HP diet, the regression model explained 35.3% of the RFIc variation, with DMI explaining 25.9%, diet selection index 7.19%, rumen bacteriome 1.02%, genetic distance 0.73% and Δ15Ntail hair 0.50%. In conclusion, this study highlights the importance of measuring diet selection to accurately determine RFI in cattle. The results also suggest that variations in the rumen bacteriome and nitrogen metabolism parameters play a role in individual variations of feed efficiency. However, most of the variation in feed efficiency remained unexplained.

377 Evaluation of Feed Intake, Feed Efficiency and Days on Trial in Growing Goats Fed a Total Mixed Diets Using Growsafe Feeding Technology

Abstract The objectives of this study were to evaluate the effects of breed and days on trial (DOT) on feed intake, growth rate, and feed efficiency of growing goats. Nineteen female goats (10 Alpine and 9 Spanish) with an initial BW of 38.8 ± 2.8 and 35.5 ±3.1 kg, respectively, were randomly assigned within breed to one of two pens (5 goats/pen), each equipped with GrowSafe feed bunks. A pelletized total mixed diet (TMD) was fed twice per day and goats had ad libitum access to feed and water throughout the 84-d trial. Daily feed intake (DMI) was collected with GrowSafe automated feeding system, and BW was measured biweekly. Linear regression of 14-d BW on DOT was used to derive ADG, mid-test metabolic BW (MBW) and expected DMI of individual goats at 42, 56, 70, and 84 DOT. Expected DMI was predicted by linear regression of DMI on MBW and ADG, with RFI calculated as a difference between actual and expected DMI for each DOT. Data were analyzed using a repeated-measures model with a fixed effect of breed, DOT as a repeated measure, and breed x DOT interaction with a pen as a random effect. The interaction was not significant for either of the response variables. Alpine goats had greater (P < 0.05) initial and final BW (37.6 kg and 51.7 kg, respectively) than Spanish goats (34.7 kg and 46.5 kg, respectively) although ADG (0.233 kg/d vs 0.191 kg/d) did not differ. DMI (P = 0.10) and RFI (P = 0.09) tended to be greater in Alpine than in Spanish goats (0.57 kg vs -0.64 kg). However, G:F was not affected (P > 0.70) by breed. As DOT increased from 42 to 84, MBW increased, while ADG, DMI, and G:F decreased. Further research is warranted to determine changes in phenotypic variances of ADG and DMI to determine the minimal DOT needed to accurately measure feed efficiency in growing goats. Our results suggest that Spanish goats tended to consume less feed and tended to be more efficient (negative RFI) than their counterpart Alpine goats. Further research is needed to compare the life-cycle efficiency of Alpine and Spanish goats.

95 Predicting Live Body Weight of Beef Heifers Using 3D Imaging

Abstract Accurately measuring body weight (BW) is of great importance for cow-calf producers in the United States, which can lead to better marketing and nutrient management decisions. Traditionally, BW has been recorded using a walk-over scale or approximated by visual observation. Recently, technology has come out that allows BW prediction using three-dimensional (3D) images. The objective of this study was to determine the efficacy of 3D imaging technology as a method to predict BW of beef heifers. Dorsal 3D images were collected on 69 Red Angus/Simmental yearling heifers. Heifers were approximately 12 mo of age that ranged from 282.1 to 440.0 kg of BW. For image collection, a depth camera (Kinect Azure, Microsoft) was placed above the animals, approximately 3 to 4 meters above the floor surface within the alley of a working facility. The image collection software was written in Python (version 3.8) programming language. For a high-quality image to be recorded, heifers needed to be handled in small groups and kept separate. Heifers also needed to have all four feet on the ground and no interference from other animals in the image. Corresponding scale-measured BW were also recorded for each animal concurrent with depth images collection. Heifers were limit fed and weighed in the morning before feeding for both scale measured BW and image collection. The depth images were analyzed using a customized program written in MATLAB (R2022a). Heifer dorsal projected volume was estimated by adding height pixel values that formed the heifer’s dorsal area, excluding the head region. Body weights were regressed from projected heifer body volumes extracted from the depth images, and then metabolic BW (MBW) was calculated using the 0.75 power adjustment of BW. Performance of the prediction model was analyzed using the coefficient of determination (R2) obtained from the regression of projected volume and actual scale BW and the standard error of the mean (SEM) of the predicted BW. Data were analyzed using the PROC REG and PROC CORR procedures in SAS (v9.4). Prediction of BW using image-extracted dorsal projected volume produced an R 2 = 0.89 and SEM = 3.3 kg. When analyzing the correlation of volume to BW, the Pearson correlation coefficient of r = 0.94 (P < 0.0001) was obtained. Regression of projected volume to MBW produced an R 2 = 0.89 and SEM = 0.57 kg. Results show that this model demonstrates the ability to accurately predict BW using depth images projected dorsal volumes on yearling heifers. These results illustrate that 3D images can be used to accurately measure BW of growing heifers that may enhance the ability of cow-calf producers to pro-actively manage grazing livestock.

PSV-12 Effects of Diet on Feed Intake, Weight Change, and Gas Emissions in Beef Cows

Abstract The objective of this study was to examine the effects of diet energy density on ranking for dry matter intake (DMI), residual feed intake (RFI), and greenhouse gas emissions. Forty-two mature, gestating Angus cows [600 ± 69 kg body weight (BW); body condition score (BCS) 5.3 ± 1.1] with a wide range in DMI expected progeny difference (−1.38 to 2.91) were randomly assigned to two diet sequences; forage then concentrate (FC) or concentrate then forage (CF). The forage diet consisted of long-stem native grass hay plus protein supplement (HAY; 1.96 Mcal ME/kg DM). The concentrate diet consisted of 35% chopped grass hay and 65% concentrate feeds on a dry matter basis (MIX; 2.5 Mcal ME/kg DM). The GreenFeed Emission Monitoring system was used to determine carbon dioxide (CO2), oxygen (O2), and methane (CH4) flux. Cow performance traits, ultrasound back fat and rump fat, feed DMI, and gas flux data were analyzed in a crossover design using a mixed model including diet, period, and sequence as fixed effects and pen and cow within sequence as random effects. For all measured traits excluding DMI, there was a diet × sequence interaction (P < 0.05). The correlation between MIX and HAY DMI was 0.41 (P = 0.067) and 0.47 (P = 0.03) for FC and CF sequences, respectively. There was no relationship (P > 0.66) between HAY and MIX average daily gain (ADG), regardless of sequence. Fifty-seven percent of the variation in DMI was explained by metabolic BW, ADG, and BCS for both diets during the first period. During the second period, the same three explanatory variables accounted for 38% and 37% of the variation in DMI for MIX and HAY diets, respectively. The negative relationship between BCS and DMI was more pronounced when cows consumed the MIX diet. There was no relationship between MIX and HAY RFI, regardless of sequence (P > 0.18). During the first period, correlations for CO2, CH4, and O2 with MIX DMI were 0.69, 0.81, and 0.56 (P ≤ 0.015), respectively, and 0.76, 0.74, and 0.64 (P < 0.01) with HAY DMI. During the second period, correlations for CO2, CH4, and O2 with MIX DMI were 0.62, 0.47, and 0.56 (P ≤ 0.11), respectively. However, HAY DMI during the second period was not related to gas flux (P > 0.47). Results from this experiment indicate that feed intake of two energy-diverse diets is moderately correlated while ADG while consuming the two diets is not related. Further experimentation is necessary to determine if gas flux data can be used to predict feed intake in beef cows.

Association of Residual Feed Intake to Metrics of Tanganyika Shorthorn Zebu Cattle in Maswa and Misungwi Districts, Tanzania

Increasing competition for feed resources and greenhouse gases pollution have been compelling beef production systems to operate at higher feed utilization. These challenges imply the need to breed cattle for Residual Feed Intake (RFI) to lower feeding costs and enteric methane production per output. To explore relevant indicator traits of RFI, this study investigated the association of RFI to Tanganyika Shorthorn Zebu (TSZ) cattle metrics from the Misungwi and Maswa Districts of Tanzania, where Tarime and Sukuma ecotypes are common. A correlation study involving the fattening of twenty-eight TSZ bulls was conducted at Tanzania Livestock Research Institute -Mabuki. From the animals' body weight and feeding data, regression of daily feed intake on average daily gain and metabolic body weight was analyzed to estimate the animals' RFI. Subsequently, the correlation of RFI to metrics of belly, horn, hip, dewlap and body length was investigated. Residual Feed Intake and Belly Length (BeL) were highly positively correlated, while RFI and Dewlap Depth (DD) were moderately positively correlated. The results indicated prospects for using BeL and DD as indicator traits for RFI. Extensive studies are recommended to analyze the correlation of RFI to hump depth, ear length, muzzle circumference and kidney fat.

The Energy Contents of Broken Rice for Lactating Dairy Cows.

This study aimed to evaluate (1) the net energy for lactation of broken rice in dairy cows and (2) the effects of broken rice substituting in diets on feed intake, nutrient energy utilization, and milk production. An energy metabolism experiment was conducted using a respiration chamber system in four multiparous Holstein crossbred cows (88.6% Holstein × 11.4% Native Thai; body weight of 438 ± 16.0 kg; 70 ± 31 days in milk) according to a 4 × 4 Latin square design with four 21-d periods. The four dietary treatments included a basal diet substitution with broken rice at 0%, 12%, 24%, and 36%. Increasing the substitution rate of broken rice in the diet resulted in unaffected feed intake, milk yield and composition, and energy balance (p > 0.05); however, a linear increase in the digestibility of dry matter, organic matter, and neutral detergent fiber (p < 0.05). The estimated net energy for lactation of broken rice was 8.68 MJ/kg. The net energy requirement for maintenance was estimated at 504 kJ/kg of metabolic body weight. Our results indicated that broken rice is a good energy-feed resource and that increasing the proportion in the diet up to 36% had no adverse effect on dairy cows' production performance.

Consistency of dry matter intake in Holstein cows: Heritability estimates and associations with feed efficiency

Resilience can be defined as the capacity to maintain performance or bounce back to normal functioning after a perturbation, and studying fluctuations in daily feed intake may be an effective way to identify resilient dairy cows. Our goal was to develop new phenotypes based on daily dry matter intake (DMI) consistency in Holstein cows, estimate genetic parameters and genetic correlations with feed efficiency and milk yield consistency, and evaluate their relationships with production, longevity, health, and reproduction traits. Data consisted of 397,334 daily DMI records of 6,238 lactating Holstein cows collected from 2007 to 2022 at 6 research stations across the United States. Consistency phenotypes were calculated based on the deviations from expected daily DMI for individual cows during their respective feeding trials, which ranged from 27 to 151 d in duration. Expected values were derived from different models, including simple average, quadratic and cubic quantile regression with a 0.5 quantile, and LOESS (Locally Weighted Scatterplot Smoothing) regression with span parameters 0.5 and 0.7. We then calculated the log of variance (log-Var-DMI) of daily deviations for each model as the consistency phenotype. Consistency of milk yield was also calculated, as a reference, using the same methods (log-Var-Milk). Genetic parameters were estimated using an animal model, including lactation, days in milk and cohort as fixed effects, and animal as random effect. Relationships between log-Var-DMI and traits currently considered in the US national genetic evaluation were evaluated using Spearman's rank correlations between sires' breeding values. Heritability estimates for log-Var-DMI ranged from 0.11 ± 0.02 to 0.14 ± 0.02 across models. Different methods (simple average, quantile regressions, and LOESS regressions) used to calculate log-Var-DMI yielded very similar results, with genetic correlations ranging from 0.94 to 0.99. Estimated genetic correlations between log-Var-DMI and log-Var-Milk ranged from 0.51 to 0.62. Estimated genetic correlations between log-Var-DMI and feed efficiency ranged from 0.55 to 0.60 with secreted milk energy, 0.59 to 0.63 with metabolic body weight (BW), and 0.26 to 0.31 with residual feed intake. Relationships between log-Var-DMI and the traits in the national genetic evaluation were moderate and positive correlations with milk yield (0.20 to 0.21), moderate and negative correlations with female fertility (-0.07 to -0.20), no significant correlations with health and longevity, and favorable correlations with feed efficiency (-0.23 to -0.25 with Feed Saved and 0.21 to 0.26 with RFI). We concluded that DMI consistency is heritable and may be an indicator of resilience. Cows with lower variation in the difference between actual and expected daily DMI (more consistency) may be more effective in maintaining performance in the face of challenges or perturbations, whereas cows with greater variation in observed versus expected daily DMI (less consistency) are less feed efficient and may be less resilient.

Liver and Muscle Transcriptomes Differ in Mid-Lactation Cows Divergent in Feed Efficiency in the Presence or Absence of Supplemental Rumen-Protected Choline.

Improving dairy cow feed efficiency is critical to the sustainability and profitability of dairy production, yet the underlying mechanisms that contribute to individual cow variation in feed efficiency are not fully understood. The objectives of this study were to (1) identify genes and associated pathways that are altered in cows with high- or low-residual feed intake (RFI) using RNA sequencing, and (2) determine if rumen-protected choline supplementation during mid-lactation would influence performance or feed efficiency. Mid-lactation (134 ± 20 days in milk) multiparous Holstein cows were randomly assigned to either supplementation of 0 g/d supplementation (CTL; n = 32) or 30 g/d of a rumen-protected choline product (RPC; 13.2 g choline ion; n = 32; Balchem Corp., New Hampton, NY, USA). Residual feed intake was determined as dry matter intake regressed on milk energy output, days in milk, body weight change, metabolic body weight, and dietary treatment. The 12 cows with the highest RFI (low feed efficient; LE) and 12 cows with the lowest RFI (high feed efficient; HE), balanced by dietary treatment, were selected for blood, liver, and muscle analysis. No differences in production or feed efficiency were detected with RPC supplementation, although albumin was greater and arachidonic acid tended to be greater in RPC cows. Concentrations of β-hydroxybutyrate were greater in HE cows. Between HE and LE, 268 and 315 differentially expressed genes in liver and muscle tissue, respectively, were identified through RNA sequencing. Pathway analysis indicated differences in cell cycling, oxidative stress, and immunity in liver and differences in glucose and fatty acid pathways in muscle. The current work indicates that unique differences in liver and muscle post-absorptive nutrient metabolism contribute to sources of variation in feed efficiency and that differences in amino acid and fatty acid oxidation, cell cycling, and immune function should be further examined.

Enteric Methane Emissions, Rumen Fermentation Characteristics, and Energetic Efficiency of Holstein Crossbred Bulls Fed Total Mixed Ration Silage with Cassava instead of Rice Straw

This study investigated the effects of substituting rice straw with cassava in total mixed ration silage on feed intake, digestibility, rumen fermentation, ruminating activity, and energy balance. An energy balance experiment was conducted to determine nutrient and energy utilization in dairy bulls. Four Holstein Friesian (HF) crossbred young bulls (93.19% HF × 6.81% Native Thai; average age of 12.08 ± 0.22 months and body weight of 266 ± 9.80 kg) were used in a 4 × 4 Latin square design with four 28-d periods. The four dietary treatments included substituting cassava with rice straw on a 50, 150, 250, and 350 g/kg dry matter basis. Increasing the amount of cassava in the diet resulted in linearly decreased rumination behaviors and enteric methane emissions (p &lt; 0.05) but a linear increase in feed intake and digestibility, total volatile fatty acid concentration, and propionic acid: acetic acid ratio in the rumen fluid (p &lt; 0.05), thus leading to a greater energy balance status (p &lt; 0.01). Our results indicated that replacing cassava with rice straw from 5% to 35% in the ration of Holstein bulls resulted in a substantial reduction in physically effective fiber and chewing time but improved nutrient and energy supply. The metabolizable energy requirement for the maintenance of crossbred dairy bulls was estimated to be 599.9 kJ/kg metabolic body weight and the efficiency of metabolizable energy used for growth was 0.88. We concluded that cassava is a good energy feed resource for Holstein crossbred bulls in the tropics.

Estimation of genetic parameters for feed efficiency traits using random regression models in dairy cattle

Feed efficiency has become an increasingly important research topic in recent years. As feed costs rise and the environmental impacts of agriculture become more apparent, improving the efficiency with which dairy cows convert feed to milk is increasingly important. However, feed intake is expensive to measure accurately on large populations, making the inclusion of this trait in breeding programs difficult. Understanding how the genetic parameters of feed efficiency and traits related to feed efficiency vary throughout the lactation period is valuable to gain understanding into the genetic nature of feed efficiency. This study used 121,226 dry matter intake (DMI) records, 120,500 energy-corrected milk (ECM) records, and 98,975 metabolic body weight (MBW) records, collected on 7,440 first-lactation Holstein cows from 6 countries (Canada, Denmark, Germany, Spain, Switzerland, and the United States), from January 2003 to February 2022. Genetic parameters were estimated using a multiple-trait random regression model with a fourth-order Legendre polynomial for all traits. Weekly phenotypes for DMI were re-parameterized using linear regressions of DMI on ECM and MBW, creating a measure of feed efficiency that was genetically corrected for ECM and MBW, referred to as genomic residual feed intake (gRFI). Heritability (SE) estimates varied from 0.15 (0.03) to 0.29 (0.02) for DMI, 0.24 (0.01) to 0.29 (0.03) for ECM, 0.55 (0.03) to 0.83 (0.05) for MBW, and 0.12 (0.03) to 0.22 (0.06) for gRFI. In general, heritability estimates were lower in the first stage of lactation compared with the later stages of lactation. Additive genetic correlations between weeks of lactation varied, with stronger correlations between weeks of lactation that were close together. The results of this study contribute to a better understanding of the change in genetic parameters across the first lactation, providing insight into potential selection strategies to include feed efficiency in breeding programs.

Estimating breeding values for feed efficiency in dairy cattle by regression on expected feed intake.

The efficiency with which a dairy cow utilises feed for the various physiological and metabolic processes can be evaluated by metrics that contrast realised feed intake with expected feed intake. In this study, we presented a new metric - regression on expected feed intake (ReFI). This metric is based on the idea of regressing DM intake (DMI) on expected DMI using a random regression model, where energy requirement formulations are applied for the calculation of expected DMI covariables. We compared this new metric with the metrics residual feed intake (RFI) and genetic residual feed intake (gRFI), by applying them on 18581 feed efficiency records from 654 primiparous Nordic Red dairy cows. We estimated variance components for the three metrics and their respective genetic correlations with intake and production traits. In addition, we examined the phenotypes of superior cows. With ReFI, we estimated for feed efficiency a higher genetic variation (4.7%) and heritability (0.23) compared to applying RFI or gRFI. The ReFI metric was genetically uncorrelated with DMI and negatively correlated within energy-corrected milk (ECM), whereas the RFI metric was genetically positively correlated with DMI and metabolic BW. The gRFI metric was genetically positively correlated with DMI and uncorrelated with energy sink traits. Overall, the estimated SE were large. The ReFI metric resulted in a different ranking of cows compared to those based on RFI or gRFI and was superior in selecting the most efficient animals. When the selection was based on ReFI breeding values, then the 10% most efficient cows produced 12.3% more ECM per unit metabolisable energy intake, whereas the corresponding values were only 4.3 or 5.9% when using RFI or gRFI breeding values, respectively. Based on ReFI, superior cows had also higher milk production, whereas based on RFI or gRFI milk production either decreased or was unaffected, respectively. The superiority of the ReFI metric in selecting efficient cows was due to a better modelling of the expected feed intake. The ReFI metric simplified modelling of feed utilisation efficiency in dairy cattle and resulted in breeding values that are equal to percentages of feed saved.