Variation in urea kinetics associated with ruminant species, dietary characteristics, and ruminal fermentation: A meta-analysis.

The objective of this meta-analysis was to quantitatively summarize variations in urea kinetics related to ruminant species, diet composition, and ruminal fermentation. A database of 31 studies measuring urea recycling kinetics were used to derive 2 sets of linear mixed-effects regression models. Study was used as a random intercept and regressions were weighted by 1 divided by the standard error of the mean observation. Models were compared, when appropriated, using the concordance correlation coefficient, root estimated variance associated with study (σˆs) and error (σˆe) and corrected Akaike information criterion values. From a dietary standpoint, most response variables were affected by measures reflecting dietary crude protein [(CP; e.g., N-NH3 or rumen-degradable protein (RDP)] and by variables reflecting dietary energy content [e.g., total digestible nutrients (TDN), dietary starch, or ruminal pH]. Dietary CP, N-NH3, and TDN typically had positive slopes on urea N entry rate (UER; g/d and g/kg0.75), whereas starch and TDN/RDP had negative slopes on UER (g/kg0.75). On the other hand, increasing TDN increased gastrointestinal entry rate (GER; g/kg0.75), whereas an opposite effect was observed for RDP. Increasing diet RDP content reduced the urea N returned to ornithine cycle (ROC; g/kg0.75) in most models. Ruminal variables also reflected the importance of N and energy supplies. Ruminal ammonia concentration significantly affected ROC (g/d and g/kg0.75), used for anabolism (UUA; g/kg0.75), ROC:GER, UUA:GER, and the incorporation of recycled urea N into microbial N relative to gastrointestinal entry rate of urea. Ruminal pH significantly affected GER:UER and ROC:GER ratios. Total digestible nutrients had a positive slope on UUA (g/kg0.75). Increasing the ratio of energy to protein (TDN:RDP) increased the GER:UER ratio, decreased the ROC:GER ratio, and increased the UUA:GER ratio and the incorporation of recycled urea N into microbial N relative to gastrointestinal entry rate of urea N. Comparison among models revealed that species was an important explanatory variable affecting most response variables. However, whether these differences are related to the intrinsic N metabolism of each species or due to the diet variation remains unclear. Understanding these differences could lead to improvements in N use efficiency in ruminant diets by formulating more precise low-N diets considering the particularities for each species.

What Would Be Good for All Veterinarians to Know About Equine Nutrition.

Nutrition and management have enabling and supporting roles to play in the health, welfare, and performance of equines. Poor or inappropriate nutrition may therefore impose limits on an animal's ability to perform and adversely affect health and welfare. Understanding the gastrointestinal tract from a nutrition perspective can help to reduce the risk of certain clinical problems. This article outlines key factors with respect to the equine digestive tract and discusses relevant aspects of ration formation. Forage is highlighted, because inappropriate forage provision is one of the key limitations in many horse diets.

Equation to predict feed intake response by lactating cows to factors related to the filling effect of rations.

Our objective was to predict the dry matter intake (DMI) response during ration formulation to factors related to the filling effect of rations and their interaction with milk yield (MY) by lactating cows past peak lactation. A data set was developed consisting of 134 treatment means from 34 experiments reported in 32 peer-reviewed articles published from 1990 through 2015. The data set included data for cows ranging from 60 to 309 d postpartum with mean DMI ranging from 17.6 to 30.6 kg/d and MY ranging from 20.3 to 51.1 kg/d. Ration composition among treatments ranged from 12.7 to 21.8% of dry matter (DM) for crude protein, 11.5 to 31.0% of DM for acid detergent fiber (ADF), 25.5 to 48.2% of DM for neutral detergent fiber (NDF), 9.9 to 39.3% of DM for forage NDF (FNDF), and 0.45 to 0.84 for the ratio of ADF% to NDF% (ADF/NDF). Laboratory measures of digestibility of NDF (in vitro or in situ, FNDFD) for the sole or major forage ranged from 24.1 to 72.7%. The model included the random effect of study to account for various experiment-specific effects including different methods of measurement of NDF and FNDFD among studies. The full model also included linear and quadratic effects of crude protein, ADF, NDF, FNDF, ADF/NDF, and FNDFD, as well as their linear and quadratic interactions, and mean MY for each study and its interaction with ration factors. The proposed prediction equation is DMI (kg/d) = 12.0 - 0.107 × FNDF + 8.17 × ADF/NDF + 0.0253 × FNDFD - 0.328 × (ADF/NDF - 0.602) × (FNDFD - 48.3) + 0.225 × MY + 0.00390 × (FNDFD - 48.3) × (MY - 33.1) with mean bias = 0.00 kg/d, root mean square error = 1.55 kg/d, and concordance correlation coefficient = 0.827. Dry matter intake was positively related to MY and ADF/NDF and negatively related to FNDF, and FNDFD was positively related to DMI for cows with high MY but negatively related to MY for cows with low MY. In addition, DMI was positively related to FNDFD for low ADF/NDF but negatively related to FNDFD for high ADF/NDF. The ADF/NDF was included to represent differences in forage fragility between grasses and legumes. The proposed model was compared with the equation recommended by the National Research Council (2001) that was developed using only animal factors by fitting each equation to a subset of the data set that included the required inputs for both. The National Research Council (2001) equation without diet factors had a higher root mean square error and over-predicted DMI at high DMI and under-predicted DMI at low DMI. Our proposed equation should be useful to predict DMI response to factors related to the filling effects of rations during ration formulation.

Variation in nutrients formulated and nutrients supplied on 5 California dairies.

Computer models used in ration formulation assume that nutrients supplied by a ration formulation are the same as the nutrients presented in front of the cow in the final ration. Deviations in nutrients due to feed management effects such as dry matter changes (i.e., rain), loading, mixing, and delivery errors are assumed to not affect delivery of nutrients to the cow and her resulting milk production. To estimate how feed management affects nutrients supplied to the cow and milk production, and determine if nutrients can serve as indexes of feed management practices, weekly total mixed ration samples were collected and analyzed for 4 pens (close-up cows, fresh cows, high-milk-producing, and low-milk-producing cows, if available) for 7 to 12 wk on 5 commercial California dairies. Differences among nutrient analyses from these samples and nutrients from the formulated rations were analyzed by PROC MIXED of SAS (SAS Institute Inc., Cary, NC). Milk fat and milk protein percentages did not vary as much [coefficient of variation (CV) = 18 to 33%] as milk yield (kg; CV = 16 to 47 %) across all dairies and pens. Variability in nutrients delivered were highest for macronutrient fat (CV = 22%), lignin (CV = 15%), and ash (CV = 11%) percentages and micronutrients Fe (mg/kg; CV = 48%), Na (%; CV = 42%), and Zn (mg/kg; CV = 38%) for the milking pens across all dairies. Partitioning of the variability in random effects of nutrients delivered and intraclass correlation coefficients showed that variability in lignin percentage of TMR had the highest correlation with variability in milk yield and milk fat percentage, followed by fat and crude protein percentages. But, variability in ash, fat, and lignin percentages of total mixed ration had the highest correlation with variability in milk protein percentage. Therefore, lignin, fat, and ash may be the best indices of feed management to include effects of variability in nutrients on variability in milk yield, milk fat, and milk protein percentages in ration formulation models.

Improving live weight gain of crossbred Limousin bulls with cassava peel silage.

There is a growing demand for beef products across developing countries. Formulating rations to include locally available waste products has the potential to increase the live weight gain (LWG) of cattle and improve the livelihoods of smallholder farmers; however, upper limit inclusion levels of cassava peel products require investigation. An experiment evaluated the effect of using cassava peel silage (CPS) at the DM inclusion levels of 30, 40, 50, 60 and 70% (with the remainder protein meals and maize stover in the diet) on the LWG of crossbred Limousin × Ongole bulls (269 ±â€¯48.8 kg). Thirty bulls, approximately two years of age, were allocated in a completely randomised block design with six blocks based on initial live weight (LW) and five treatments based on level of CPS. The combination of CPS (with 2% urea of the CPS) and protein meals significantly affected LWG with the highest values obtained at levels of 30 and 50% inclusion of CPS (1.16-1.35 kg/day) (P < 0.05). Polynomial analysis of LWG data revealed the optimal LWG is theoretically achieved at 37% CPS with a LWG of 1.31 kg/day; however, LWG was similar from 30 to 50% inclusion levels and then declined. There was little significant difference at CPS inclusion levels of 30-60%, for DM intake (DMI) which ranged from 2.3 to 2.6% LW, organic matter (OM) digestibility (77.8-81.6%), feed conversion ratio (FCR) (6.56-7.56 kg DM/kg LWG) and feed cost of gain (Indonesia rupiah (IDR)/kg LW 18 612 - 21 398). At a high (70%) level of CPS inclusion, these values were markedly changed when compared to the 30% inclusion level of CPS. Feed treatments did not affect rumen pH, NH3-N, concentration or molar percentage of volatile fatty acids or protozoal population (P < 0.05). Rumen pH measured three hours after morning feed ranged from 6.7 to 6.8 and NH3-N ranged from 14.1 to 19.3 mg NH3-N/dl. It was concluded that inclusion of CPS up to 60% mixed with protein meals and urea and 20% maize stover maximised LWG and profitability of the production system.

FeedMaster: A least-cost feed formulation App for minimizing the cost and maximizing milk yield.

Objective: The study aimed to develop and assess an Android app designed for farmers with a low educational status that can formulate a least-cost ration. Materials and Methods: First, a computer-android-based app named BLRI FeedMaster was developed to guide users in formulating a balanced ration at the least cost. A survey was conducted on 30 livestock officers and 18 farmers with 50 cattle to evaluate its efficacy at the field level. The study outcomes were milk yield, feeding cost, milk composition, time, and cost for management before and after using the BLRI FeedMaster app. Descriptive statistics and paired sample t-tests were used to analyze the data. Results: After adopting the BLRI FeedMaster app, a significant increase was observed in daily average milk yield (9.39 ± 0.32 l from 8.37 ± 0.36 l), while a considerable decrease was observed in daily average feed quantity (4.88 ± 0.15 kg from 5.60 ± 0.17 kg) and feed cost (BDT 28.00 ± 0.50 from BDT 29.75 ± 0.49). Besides, the number of visits, time, and cost for seeking professional services regarding feed, health care, and other information was significantly minimized. The number of visits decreased to 0.36 ± 013 from 3.07 ± 0.38, and the consumed time was reduced from 270 ± 34.30 to 235.71 ± 59.42 min (p < 0.05) after adopting the app. Conclusion: Hence, this app was very beneficial for farmers with a low economic and educational background and may ultimately help farmers with profitable animal farming and sustainable production in the least developed countries like Bangladesh.

An improved algorithm for solving profit-maximizing cattle diet problems.

Feeding cattle with on-pasture supplementation or feedlot diets can increase animal efficiency and system profitability while minimizing environmental impacts. However, cattle system profit margins are relatively small and nutrient supply accounts for most of the costs. This paper introduces a nonlinear profit-maximizing diet formulation problem for beef cattle based on well-established predictive equations. Nonlinearity in predictive equations for nutrient requirements poses methodological challenges in the application of optimization techniques. In contrast to other widely used diet formulation methods, we develop a mathematical model that guarantees an exact solution for maximum profit diet formulations. Our method can efficiently solve an often-impractical nonlinear problem by solving a finite number of linear problems, that is, linear time complexity is achieved through parametric linear programming. Results show the impacts of choosing different objective functions (minimizing cost, maximizing profit and maximizing profit per daily weight gain) and how this may lead to different optimal solutions. In targeting improved ration formulation on feedlot systems, this paper demonstrates how profitability and nutritional constraints can be met as an important part of a sustainable intensification production strategy.

Transition cow nutrition and feeding management for disease prevention.

In this article, an overview is presented of nutrient modeling to define energy and protein requirements of the late pregnant cow, and metabolic relationships between fetus and cow as they relate to nutrient utilization and risk for postparturient disease are discussed. Recommendations for formulating dry cow diets are provided, with emphasis on opportunities to minimize variation and risk for postparturient disease events.