Nutrient Requirements Of Animals Research Articles

328 Comparison of Predicted Nutritional Requirements of Two Feeding Systems for Dairy Cattle Implemented in a Monte-Carlo Simulation Model of Herd Dynamics

Abstract There is increased interest in precision-feeding systems that account for individual-animal variation and temporal dairy herd dynamics to increase feed-efficiency and reduce environmental footprints. The Ruminant Farm Systems (RuFaS; Hansen et al., 2021) model simulates individual animals on a daily timestep using a stochastic, Monte Carlo framework to represent the phenotypic diversity and population dynamics expected in a dairy herd. Within RuFaS, individual animal nutrient requirements are used to inform pen-level diet formulations and feed delivery. However, nutritional requirements for feeding dairy cattle were recently updated via consideration of both animal and diet-related factors. Our aim was to calculate individual animal predictions for dry matter intake (DMI), as well as energy and metabolizable protein requirements, and compare the methods described in the 7th (NRC, 2001) and 8th (NASEM, 2021) editions of the Nutrient Requirements for Dairy Cattle. For that purpose, we simulated dairy herds (ca. 6,000 individual Holstein animals per simulation, mean adult body weight = 671 kg, standard deviation = 79, mean daily milk production = 39.8 kg·day-1·cow-1 , standard deviation = 7.5) for 10+ year time periods with an updated version of RuFaS. The simulated herds provided a wide range of values with which to test the nutrient requirement models, and their implications. The NASEM DMI estimates were less across the board but began to converge towards NRC calculated values at the larger simulated animal body weights. The principal differences in energy requirements between the two models (NRC vs. NASEM) were: 1) predicted requirements for pregnancy were significantly greater for NASEM than NRC across all life history stages; 2) NASEM displayed slightly greater energy requirements for growth in first and second lactation cows, and; 3) NASEM predicted decreased maintenance requirements for all heifer stages but the opposite was true for mature cows. Metabolizable protein requirements were greater following NASEM calculations in heifers over 300 kg, but strikingly similar to NRC-computed values for lactating cows. Overall, results from this modeling study align with our expectations and demonstrate successful implementation of the two nutrition models within the RuFaS model. These outputs confirm the usefulness of data obtained to explore applications of the two nutrient requirement models under different precision feeding management practices and, to some extent, to quantitatively evaluate their viability of the models in edge cases that can occur within the expected variation of a herd’s population. Future work will explore downstream consequences of the nutrient requirement models within the automated, least-cost ration formulation framework using nonlinear programming and metrics related to manure output and storage. These data will guide further developments of RuFaS as whole farm simulation model and provide insights into expected variation in nutritional requirements within a dynamic set of animals.

Effects of forage phosphorous content on faecal phosphorous excretion and possible markers of low phosphorous intake in foals fed forage-only diets.

Knowledge of endogenous nutrient losses is important when estimating the nutrient requirements of animals. It has been suggested that faecal endogenous phosphorus (P) losses differ between growing and adult horses, but studies on foals are scarce. In addition, studies on foals on forage-only diets with different P contents are lacking. Thus this study: (1) assessed faecal endogenous P losses in foals fed a grass haylage-only diet close to or below estimated P requirements; (2) evaluated use of serum cross-linked carboxyterminal telopeptides of type-I collagen (CTx) as a marker of bone resorption secondary to low-P intake; and (3) examined whether analysis of faecal P concentration on a dry matter (DM) basis could be used as an indicator of P intake. Six foals were fed three grass haylages (fertilised to contain different amounts of P: 1.9, 2.1, 3.0 g/kg DM) for 17-day periods in a Latin square design. Total collection of feaces was performed by the end of each period. Faecal endogenous P losses were estimated using linear regression analysis. There was no difference in the concentration of CTx in plasma between diets in samples collected on the last day of each period. A correlation was found (y = 0.64x - 1.51; r2 = 0.75, p < 0.0001) between P intake and faecal P content, but regression analysis indicated that underestimation as well as overestimation of intake is likely if faecal P content is used to assess intake. It was concluded that faecal endogenous P losses in foals are low, probably no higher than in adult horses. It was also concluded that plasma CTx cannot be used to assess short-term low-P intake in foals and that faecal P content cannot be used to assess differences in P intake, at least not when P intake is close to or below estimated P requirements.

Prediction of the daily nutrient requirements of gestating sows based on sensor data and machine-learning algorithms.

Precision feeding is a strategy for supplying an amount and composition of feed as close that are as possible to each animal's nutrient requirements, with the aim of reducing feed costs and environmental losses. Usually, the nutrient requirements of gestating sows are provided by a nutrition model that requires input data such as sow and herd characteristics, but also an estimation of future farrowing performances. New sensors and automatons, such as automatic feeders and drinkers, have been developed on pig farms over the last decade, and have produced large amounts of data. This study evaluated machine-learning methods for predicting the daily nutrient requirements of gestating sows, based only on sensor data, according to various configurations of digital farms. The data of 73 gestating sows was recorded using sensors such as electronic feeders and drinker stations, connected weight scales, accelerometers, and cameras. Nine machine-learning algorithms were trained on various dataset scenarios according to different digital farm configurations (one or two sensors), in order to predict the daily metabolizable energy and standardized ileal digestible lysine requirements for each sow. The prediction results were compared to those predicted by the InraPorc model, a mechanistic model for the precision feeding of gestating sows. The scenario predictions were also evaluated with or without the housing conditions and sow characteristics at artificial insemination usually integrated into the InraPorc model. Adding housing and sow characteristics to sensor data improved the mean average percentage error by 5.58% for lysine and by 2.22% for energy. The higher correlation coefficient values for lysine (0.99) and for energy (0.95) were obtained for scenarios involving an automatic feeder system (daily duration and number of visits with or without consumption) only. The scenarios including an automatic feeder combined with another sensor gave good performance results. For the scenarios using sow and housing characteristics and automatic feeder only, the root mean square error was lower with Gradient Tree Boosting (0.91 MJ/d for energy and 0.08g/d for lysine) compared with those obtained using linear regression (2.75 MJ/d and 1.07g/d). The results of this study show that the daily nutrient requirements of gestating sows can be predicted accurately using data provided by sensors and machine-learning methods. It paves the way to simpler solutions for precision feeding.

94 The Present and Future of Nasem Beef Nutrient Requirement Modeling

Abstract The precise and accurate prediction of animal nutrient requirements, feed intake, water intake, environmental impacts, and production efficiency is an essential function of nutrient requirement models when leveraged as tools to enhance the sustainability of livestock production systems. Historically, the legal standard for determining nutrient requirements of livestock within the United States has leveraged the National Academies of Sciences, Engineering, and Medicine (NASEM) nutrient requirement series (formerly referred to as the National Research Council (NRC) models). The objective of this work is to review the present advantages and future needs for the NASEM Beef Nutrient Requirement Models. Due to current production conditions prevalent within the United States beef industry, the adequate prediction of performance outcomes in commercial cattle in group feeding situations is arguably of the greatest importance. However, as the climate changes and interest in new genetics, production strategies, and feeding approaches expand, there will be an increasing need to additionally provide precise and accurate predictions of individual animals based on genetic potential, production system, and climate conditions. The NASEM 2016 Nutrient Requirements of Beef Cattle presented a stepwise improvement in model sophistication and customizability though the inclusion of a number of individually adjustable constants to adapt model predictions to animal performance in production settings, and through the expanded use of mechanistic solutions in estimating nutrient requirements. Another major advancement of this model release was the opportunity to push model updates and fixes as users identify challenges or issues with the model. The capacity to update nutrient requirement models in a more agile manner greatly contributes to the long-term need for more adaptable and flexible ration formulation tools. Although these improvements may enhance usability of the NASEM models, there are some additional opportunities for future iterations, including better capacity to explore individual animal requirements, leverage precision livestock farming technologies, and design rations to adapt animals to climate change.

Effects of Hydrolysable Tannin Supplementation on Nutrient Intake, Milk Production and Milk Somatic Cell Count in On-farm Dairy Cows

This study examined the effects of hydrolysable tannin (HT) supplementation on nutrient intake, milk production and milk somatic cell count in on-farm dairy cows. Fifty-four Holstein Friesian crossbred cows weighing 450 to 500 kg and were subjected to an experiment for 49 days. Dairy cows were divided into 3 groups, which were 1) the control group without HT supplementation and the HT supplementation groups, which received HT products (15 g/day), 2) one contains 3.15 g/day of HT and 3) another contains 6.30 g/day of HT. Hydrolysable tannin was extracted from sweet chestnut wood (Castanea Sativa Mill.). Dairy cows received HT products on the top of concentrate (22 % CP) in the morning after milking. Total mixed ration (TMR), pangola grass (Digitaria eriantha) hay and concentrate were offered according to animal nutrient requirements. The results showed that supplementation of HT has no influence (p &gt; 0.05) on the nutrient intake, milk yield and milk composition when compared to the control group. In addition, the increased levels of HT caused quadratic increases in fat:protein at pre-treatment and treatment periods (p &lt; 0.05; p = 0.06, respectively), while differential somatic cell count (DSCC) at treatment and post-treatment periods showed a quadratic decrease (p &lt; 0.05; p &lt; 0.05, respectively), with supplementation of HT product containing 6.30 g HT/day (p &lt; 0.05) being the lowest. Therefore, it can be concluded that supplementation with HT product does not affect nutrient intake, milk yield, however, it could reduce DSCC and probably improve udder health in on-farm dairy cows.&#x0D; HIGHLIGHTS&#x0D; &#x0D; A quantitative performance comparison of Radio over Free Space Optical links&#x0D; WDM increases the capacity while the MIMO links help to maintain the transmission range&#x0D; A combination of WDM and MIMO RoFSO links is identified to be the best&#x0D;

Dairy cattle nutrition and feed calculator-an android application.

The dairy farmers in the tropical region have limitations regarding "feedstuffs" available. A software program is required to meet the nutrient requirement with the available feeds at the cheapest cost. There are many techniques/software that are implemented to meet dairy animal nutrient requirements. However, there are no specific techniques that are appropriate for formulating rations for dairy cattle in the least cost manner. An android application Dairy Cattle Nutrition and Feed Calculator (DCN & FC) is developed with an aim of least-cost feed balancing system which will help a farmer to choose feeds to meet the nutrient requirement set for ration. The quantity of feed, fed to the cattle to meet the required needs, is determined by nutrient content, dry matter intake (DMI), crude protein (CP) and total digestible nutrients (TDN) of the feed. This program works in three phases. The first phase consists of creating equations for the estimation of DMI, TDN and CP based on the nutrient tables provided by ICAR (2013) for different categories of cattle such as Milch cattle, dry cattle, male calves, female calves and pre-ruminant animals for different physiological stages such as body weight, average daily gain, fat and milk, using regression analysis. The second phase is the development of a linear programming (LP) model to solve different cases of nutrient requirements for least cost. The final phase is the use of the android framework that uses linear programming to suggest sufficient feed that meets the nutrient requirements. The developed application is user friendly and available in different languages. With the combination of linear programming and regression analysis, the ration can be effectively formed using available feeds, and control the cost of the feeds.

PSXI-2 An update on the development of the Ruminant Farm Systems (RuFaS) model

Abstract Research, extension, and education communities often focus on the adoption of single strategies because they lack the tools to integrate opportunities at a farm level. Modeling is the best approach to synchronize the complex linkages between animal health, animal-based protein production, water resources, and soil health on dairy farms. Available farm systems models have limitations that prevent scalability and adaptation to evolving technologies and scientific knowledge. Participatory modeling with corporate partners and farmers is being used to create the Ruminant Farm Systems (RuFaS) model. RuFaS tracks the flows of nitrogen, carbon, and phosphorus through four biophysical modules: soil and crop, feed storage, animal herd, and manure. Users input farm variables through tiered files, from general farm information (e.g., crop type, animal numbers, field characteristics) to advanced inputs (e.g., soil characteristics, milk production parameters). The soil and crop module predicts alfalfa, corn, and soybean growth. The animal module uses a Monte-Carlo approach to determine individual animal characteristics and production, incorporating breed traits, reproduction protocols, and animal management decisions. RuFaS calculates animal nutrient requirements from NRC equations, which are averaged on a pen basis to reflect industry practices. A nutritional grouping algorithm can allocate lactating cows to different pens. Manure processing and feed storage modules are currently being developed. RuFaS is coded in python, a general-purpose programming language emphasizing readability. Pool and flux values are stored daily and transferred to an output generator before being cleared annually. Simulation data can be summarized to determine resource use, greenhouse gas emissions, and the cost of production. RuFaS will be available as open-source software to radically change users’ access to dairy farm systems models. The completed RuFaS model will be an essential tool for researchers to evaluate strategies for farm sustainability, and we anticipate the first version of RuFaS will be available in 2021.

Phase-Feeding the Beef Herd for Improved Feed Utilization

The dairy industry utilizes the concept of differences in nutrient requirements of different cows within the herd and manages nutrient supply accordingly. In that regard, the dairy industry approaches different cow nutrient requirements by implementing phase feeding in the cow herd. Phase feeding is defined as: changing the nutrient concentrations in a series of diets formulated to meet an animal's nutrient requirements more precisely at a particular stage of growth or production. Phase feeding in the dairy industry is implemented based on placing cows into multiple feeding groups based on their lactation status. The phase feeding strategy is utilized to address the different nutrient requirements associated with milk production intensity. The dairy industry addresses the nutrient requirements of cows not on a singular basis but on a multiple nutrient basis. This document is AN157, one of a series of the Animal Sciences Department, UF/IFAS Extension. Original publication date October 2005.&#x0D; AN157/AN157: Phase-Feeding the Beef Herd for Improved Feed Utilization (ufl.edu)

Graphically Communicating Hay Test Results—A Tale of Two Nutrients

Our purpose with this article is to share the benefit of using a scatter plot created from hay test results for total digestible nutrients and protein to teach livestock producers four important forage and feeding concepts. The concepts are that a producer's hay is likely not of average quality, nutrients are not independent, hay quality varies on individual farms and across farms, and supplemental feed needs vary according to animal nutrient requirements and fall within one of four categories. Overall, our "tale of two nutrients" tool has served us well as an effective visual aid that can be adapted to meet local needs.

Planning livestock diet with fuzzy requirements

Formulation of a balanced diet, which provides all nutritional requirements of livestock in accordance with its special physiological conditions, is not possible totally. According to the frequency and salient increasing of the breeding center in the country and the shortage of forage and food materials considering the available resources, diet optimization is considered as an essential program. Linear programming used to in diet formulation. Fuzzy linear programming presents a new perspective for solving of different problems such as livestock diet formulation. The main feature of fuzzy forms is their mathematical design, which allows the decision makers to work with intervals. In the formulation of a balanced diet by using fuzzy linear programming, the economic power of stockbreeder and the satisfaction percentage of animal nutrient requirements will be considered and determined. According to the decision maker’s idea and with special accuracy, the diet problem can formulate in accordance with the amount of livestock requirements satisfaction. Amount of α can be estimated as an interval for the fixed price. Accordingly, more requirement satisfaction means less cost changes.This paper discusses animal diet problem with fuzzy requirements. Firstly, the fuzzy linear programming problem is converted to interval linear programming problem by α-cuts and then Tang Shaocheng method is used to solve the proposed problem. Finally, a practical example of fuzzy linear programming problem in relation to optimized animal diet is presented and solved. The result showed that the uncertainty of food requirements slightly affected the budget of animal diet.

Assessment of feeding varying levels of Metabolizable energy and protein on performance of transition Murrah buffaloes.

Fifteen close up pregnant Murrah buffaloes of mean body weight (668.3±24.03) kg, lactation number (2.8±0.17) and expected producing ability (EPA) (2125.7±46.34) were randomly distributed into three groups each of five animals to investigate the performance at different levels of metabolizable energy and protein. Control group was fed as per ICAR Nutrient requirements of animals (2013) recommendation whereas treatment group (1) high metabolizable energy and high metabolizable protein (HMEMP) and group (2) low metabolizable energy and low metabolizable protein (LMEMP) were offered with ration containing 15% more and 15% less ME and MP, respectively. The feeding trial was carried out for the period of 40days before parturition and continued for 120days after parturition. Intake of dry matter (DM) (%BW) was similar among experimental groups. Metabolizable energy (ME) (MJ/100kg BW) and metabolizable protein (MP) (g/100kg BW) intake was highest in HMEMP followed by control and LMEMP group, respectively. Digestibility trial of 7days was conducted at 60days post-partum and it was observed that apparent digestibility coefficients (%) of DM, organic matter (OM), crude protein (CP), ether extracts (EE), neutral detergent fiber (NDF) and acid detergent fiber (ADF) were similar among the experimental groups. Milk yield (kg/kg DMI) was similar among treatment groups whereas 6% fat corrected milk (FCM) was lower in LMEMP group as compared to HMEMP and control. No significant effect of dietary MP and ME levels on milk composition was observed among experimental groups. There were no significant difference in non esterified fatty acid (NEFA), blood urea nitrogen(BUN), growth hormone (GH) and insulin like growth factor-1(IGF-1) concentration among different experimental groups whereas concentration of immunoglobulin G (IgG) (μg/ml) was found to be lower in LMEMP. The study results indicate that nutrient digestibility and lactation performance was not affected with 15% variation in intakes of ME and MP in lactating Murrah buffaloes.

Evaluation of the National Research Council (2001) dairy model and derivation of new prediction equations. 1. Digestibility of fiber, fat, protein, and nonfiber carbohydrate

Evaluation of ration balancing systems such as the National Research Council (NRC) Nutrient Requirements series is important for improving predictions of animal nutrient requirements and advancing feeding strategies. This work used a literature data set (n = 550) to evaluate predictions of total-tract digested neutral detergent fiber (NDF), fatty acid (FA), crude protein (CP), and nonfiber carbohydrate (NFC) estimated by the NRC (2001) dairy model. Mean biases suggested that the NRC (2001) lactating cow model overestimated true FA and CP digestibility by 26 and 7%, respectively, and under-predicted NDF digestibility by 16%. All NRC (2001) estimates had notable mean and slope biases and large root mean squared prediction error (RMSPE), and concordance (CCC) ranged from poor to good. Predicting NDF digestibility with independent equations for legumes, corn silage, other forages, and nonforage feeds improved CCC (0.85 vs. 0.76) compared with the re-derived NRC (2001) equation form (NRC equation with parameter estimates re-derived against this data set). Separate FA digestion coefficients were derived for different fat supplements (animal fats, oils, and other fat types) and for the basal diet. This equation returned improved (from 0.76 to 0.94) CCC compared with the re-derived NRC (2001) equation form. Unique CP digestibility equations were derived for forages, animal protein feeds, plant protein feeds, and other feeds, which improved CCC compared with the re-derived NRC (2001) equation form (0.74 to 0.85). New NFC digestibility coefficients were derived for grain-specific starch digestibilities, with residual organic matter assumed to be 98% digestible. A Monte Carlo cross-validation was performed to evaluate repeatability of model fit. In this procedure, data were randomly subsetted 500 times into derivation (60%) and evaluation (40%) data sets, and equations were derived using the derivation data and then evaluated against the independent evaluation data. Models derived with random study effects demonstrated poor repeatability of fit in independent evaluation. Similar equations derived without random study effects showed improved fit against independent data and little evidence of biased parameter estimates associated with failure to include study effects. The equations derived in this analysis provide interesting insight into how NDF, starch, FA, and CP digestibilities are affected by intake, feed type, and diet composition.

Supplementation and sustainable grazing systems1

The purpose of this review is to emphasize rangeland and landscape attributes that effect animal grazing behavior while highlighting successful approaches that have utilized this knowledge to devise supplementation strategies that improve the sustainability of grazing systems through modification of grazing behavior and pasture distribution, irrespective of animal nutrient requirements. Consequently, supplementation strategies are no longer formulated with the sole objective of addressing animal nutrient requirements. One of the principle drivers for this change in management philosophy is rangelands have become valued for many ecological services beyond forage for livestock. The threat of litigation and/or legal mandates that require land managers to consider the ecological, social, and economic impact of management decisions has increased scrutiny of livestock grazing. This has resulted in a significant body of research evaluating the ability of supplementation strategies to maintain or improve rangeland health and ecological function in a way that is economically viable. Herein, we will review the use of supplementation practices to alter livestock grazing location and control invasive species. Also, we will discuss the use of complimentary forages to bridge periods of inadequate forage quality. Rangeland-based livestock producers utilizing extensive landscapes will continue to face management challenges including changes in public land policy, anthropogenic development, climatic variability, invasive weeds, wildfire, water quality, and threatened and endangered species concerns. As an industry and a discipline we must continue to improve or ability to manage for “designed” landscapes that improve the economics of livestock production while maintaining or enhancing rangeland health and ecological function, thereby improving the long-term sustainability of grazing systems.

Invited review: Experimental design, data reporting, and sharing in support of animal systems modeling research.

The National Animal Nutrition Program "National Research Support Project 9" supports efforts in livestock nutrition, including the National Research Council's committees on the nutrient requirements of animals. Our objective was to review the status of experimentation and data reporting in animal nutrition literature and to provide suggestions for the advancement of animal nutrition research and the ongoing improvement of field-applied nutrient requirement models. Improved data reporting consistency and completeness represent a substantial opportunity to improve nutrition-related mathematical models. We reviewed a body of nutrition research; recorded common phrases used to describe diets, animals, housing, and environmental conditions; and proposed equivalent numerical data that could be reported. With the increasing availability of online supplementary material sections in journals, we developed a comprehensive checklist of data that should be included in publications. To continue to improve our research effectiveness, studies utilizing multiple research methodologies to address complex systems and measure multiple variables will be necessary. From the current body of animal nutrition literature, we identified a series of opportunities to integrate research focuses (nutrition, reproduction and genetics) to advance the development of nutrient requirement models. From our survey of current experimentation and data reporting in animal nutrition, we identified 4 key opportunities to advance animal nutrition knowledge: (1) coordinated experiments should be designed to employ multiple research methodologies; (2) systems-oriented research approaches should be encouraged and supported; (3) publication guidelines should be updated to encourage and support sharing of more complete data sets; and (4) new experiments should be more rapidly integrated into our knowledge bases, research programs and practical applications.

An optimal dietary non-phytate phosphorus level of broilers fed a conventional corn–soybean meal diet from 4 to 6 weeks of age

It is imperative to evaluate precise nutrient requirements of animals in order to optimize productivity and minimize feed cost and nutrient excretions. The current non-phytate phosphorus (NPP) recommendation for broilers is based on the papers published 30 years ago. However, today’s commercial birds are quite different from those before 30 years. Therefore, the present experiment was conducted with growing male broiler chickens to evaluate an optimal dietary NPP level of broiler chickens fed a conventional corn–soybean meal diet from 4 to 6 weeks of age. The 1-day-old chicks were fed corn–soybean meal diet containing 0.39% NPP from 1 to 3 weeks of age. At 22 days of age, 360 birds were selected and randomly allotted by BW to one of 10 dietary treatments with six replicate cages of six birds per cage for each treatment. Birds were fed the P-unsupplemented corn–soybean meal basal diet and the basal diet supplemented with inorganic P as CaHPO4·H2O ranging from 0.00% to 0.45% with 0.05% increment from 4 to 6 weeks of age. The dietary NPP levels were 0.09%, 0.14%, 0.20%, 0.24%, 0.30%, 0.34%, 0.38%, 0.45%, 0.49% and 0.54%, respectively, and the dietary Ca level was fixed at 0.90% for all treatments. The results showed that average daily gain, serum inorganic P concentration, tibia bone strength, tibia ash percentage and P percentage, tibia bone mineral content (BMC) and density (BMD), middle toe ash percentage and P percentage, middle toe BMC, total body BMC and BMD were affected (P<0.0001) by dietary NPP level, and increased linearly (P<0.0001) and quadratically (P<0.003) as dietary NPP levels increased. Optimal dietary NPP levels estimated based on fitted broken-line models (P<0.0001) of the above indices are 0.21%, 0.29%, 0.29%, 0.29%, 0.29%, 0.31%, 0.29%, 0.30%, 0.27%, 0.29% and 0.28%, respectively. It is suggested that the total body BMC and BMD, and middle toe ash P and BMC might be new, sensitive and non-invasive criteria to evaluate the dietary NPP requirements of broilers. The optimal dietary NPP level would be 0.31% for broiler chickens fed a conventional corn–soybean meal diet from 4 to 6 weeks of age.

Challenges for Plant Breeders from the View of Animal Nutrition

The question of how to feed the growing world population is very old, but because of the increase of population and possible climate change, currently it has an explosive impact. Plant breeding can be considered as the starting point for the whole human food chain. Therefore, high, stable and highly digestible yields of phytogenic biomass with low external inputs of non-renewable resources, such as water, fuel, arable land, fertilizers, etc.; low emissions of gases with greenhouse potential during cultivation; and high resistance against biotic and abiotic stressors, including adaptation to potential climate change, and a low concentration of undesirable substances in the plants are real challenges for plant breeders in the future. Virtually unlimited resources such as sunlight, nitrogen and carbon dioxide from the air as well as the genetic pool of microbes, plants and animals can be used to breed/develop optimal plants/crops. Biofortification of plants may also be an objective of plants breeders, but it is more important for human nutrition to avoid micronutrient deficiencies. A lower concentration of undesirable substances in the plants can be considered as more important than higher concentrations of micronutrients in plants/feeds. Animal nutritionists have various possibilities for feed additive supplementation to meet animal nutrient requirements. Examples to reduce undesirable substances in feed plants are discussed and shown in the paper. In summary, plant breeding has a large and strategic potential for global feed and food security. All breeding technologies may contribute to solving important global challenges, such as sustainable use of limited global resources, improved use of unlimited resources, adaption to climate change and lowering global greenhouse gas emission. More publically supported research seems to be necessary in this field. All methods of plant breeding that contribute to a more resource-efficient production of high and stable yields of available biomass should be used/combined.

Modeling the trade-off between diet costs and methane emissions: A goal programming approach

Enteric methane emission is a major greenhouse gas from livestock production systems worldwide. Dietary manipulation may be an effective emission-reduction tool; however, the associated costs may preclude its use as a mitigation strategy. Several studies have identified dietary manipulation strategies for the mitigation of emissions, but studies examining the costs of reducing methane by manipulating diets are scarce. Furthermore, the trade-off between increase in dietary costs and reduction in methane emissions has only been determined for a limited number of production scenarios. The objective of this study was to develop an optimization framework for the joint minimization of dietary costs and methane emissions based on the identification of a set of feasible solutions for various levels of trade-off between emissions and costs. Such a set of solutions was created by the specification of a systematic grid of goal programming weights, enabling the decision maker to choose the solution that achieves the desired trade-off level. Moreover, the model enables the calculation of emission-mitigation costs imputing a trading value for methane emissions. Emission imputed costs can be used in emission-unit trading schemes, such as cap-and-trade policy designs. An application of the model using data from lactating cows from dairies in the California Central Valley is presented to illustrate the use of model-generated results in the identification of optimal diets when reducing emissions. The optimization framework is flexible and can be adapted to jointly minimize diet costs and other potential environmental impacts (e.g., nitrogen excretion). It is also flexible so that dietary costs, feed nutrient composition, and animal nutrient requirements can be altered to accommodate various production systems.

Effect of prill fat supplementation on hormones, milk production and energy metabolites during mid lactation in crossbred cows

Materials and Methods The ability of the dairy cows to increase daily energy intake depends on the net energy density of the diet. The daily Dry Matter Intake (DMI) is highly regulated by animal nutrient requirements, metabolic states, and the type and temporal absorption of fuels. Fat supplements from different sources, its form and type has different hypophagic effects [1]. Previous reports indicate that feeding of fatty acid (FA) supplements including calcium salts of palm FA linearly decreases DMI with increasing dietary concentration, whereas hydrogenated FA had no effect on DMI [2,3]. However, dietary fat feeding induces decrease in milk protein concentration in animals. Milk yield changes in by pass fat cows could be due to the changes in ruminal fermentation, endocrine signaling, or mammary nutrient metabolism [4]. A linear decrease in milk crude protein (CP) yield with abomasal unsaturated fatty acid (FA) infusion [2] and a decrease in milk casein yield with C18 unsaturated FA infusion compared with saturated FA [4] indicated that FA profile has an important role in fat-stimulated decreased milk protein. The maintenance of lactation of dairy cows depends on the balanced feeding during postpartum period. It has been found that hydrogenated palm oil triglyceride provide a better energy supply for high-yielding dairy cows in negative energy balance than calcium soaps of palm oil fatty acids around calving [4]. Prill fat is a non-hydrogenated vegetable oil and contains more than 85% palmitic acid with high melting point. Due to this reason it does not melt at low pH, by pass rumen degradation and is digested in small intestine by lipase enzyme. Prill fat is prepared by liquefying mixture of fatty acid by spraying it under pressure into a cooled atmosphere. prill fat remain inert in the rumen and resist hydrolysis and association with the bacterial cells of feed particles. Thus total supplemented energy in diet of a lactating animal is available for the productive processes. Considering the importance of prill fat as an energy source in diet of lactating animals, the present experiment was conducted to find out the effect of prill fat supplementation on plasma hormones and milk production in crossbred cows so that this technology, if proved beneficial, could be used to augment lactation under field and farm conditions.

Practical supplementation of shrimp and fish feeds with crystalline amino acids

Abstract In 2011, aquaculture accounted for almost 64 million MT of fish, crustaceans and mollusks (FAO, 2012). Fish meal has historically been the protein source of choice in aquatic feeds, but global supplies have reached a plateau making it less available and more expensive. As a consequence, the use of cheaper proteins made from processed plant proteins, byproducts from agriculture, fisheries or the slaughtering of terrestrial production animals was popularized within the aquaculture feed industry. Although these alternative ingredients may contain a crude protein (CP) content comparable to fish meal, they may be less digestible and deficient in one or more of the ten essential amino acids (EAAs). This has required the adoption of more modern formulation approaches which take into account nutrient availability, especially in regard to EAAs. EAA requirements have been established for a number of species of fish and shrimp. Methionine (Met) followed by lysine (Lys) are the first limiting amino acids in plant and rendered animal byproducts. Formulating for EAAs by simply increasing the dietary inclusion levels of the feedstuffs that contain intact sources of the targeted EAAs can lead to overformulated feeds with excessive levels of CP and other nutrients. A more rational approach is to supplement the diet with crystalline amino acids (CAAs). A first step to the application of a nutrient-based formulation approach is knowledge of the digestible EAA content of the ingredients available for use in the formula. It is highly desirable to formulate on a CP, EAA and energy digestibility basis in line with current formulation practices of most modern feed companies. Further expansion of current EAA digestibility values across ingredients and farmed aquatic species will further enable nutrient based formulation. By formulating on an EAA basis across farmed aquatic species, nutritionists have realized least cost formulation opportunities with the use of CAAs which are now available throughout the world at accessible prices. The CAAs mostly used by the animal feed industry, in order of usage, are the following: dl -methionine or Met analogs, l -lysine, l -threonine, l -tryptophan, l -isoleucine and l -valine. Met and Lys are the most currently used due to their wide availability and importance as most limiting EAAs in plant protein ingredients, such as soy and corn based meals. There is a relatively wide variation in the dietary Met and Lys requirement values for farmed fish and shrimp. This is due to differences in species requirements, culture systems, developmental stage and composition of experimental diets. The dietary Met requirements for fish and shrimp range from 0.5 to 1.5% and from 0.7 to 0.9% of the diet, respectively (NRC, 2011). The dietary Lys requirements range from 1.2% to 3.3% of the diet for cultured fish and from 1.6 to 2.1% of the diet for cultured shrimp. Appropriate dietary Met and Lys levels improve the use of other EAAs because they have the ability to reduce the oxidation rate of other amino acids. The present review discusses bioavailability, requirements and sources of EAAs and practical considerations for their application in aquaculture feeds. The appropriate supplementation of crystalline amino acids in feeds for fish and shrimp represents an opportunity to reduce formulation costs in the face of the volatile commodity market of protein ingredients and the short supply of fish meal. Competitiveness in the aquatic animal feed industry today depends upon application of modern and environmentally-sound formulation techniques based on nutrient value and supplementation with crystalline EAA to meet animal nutrient requirements.

Zeytin Yağı Yan Ürünlerinin Ruminant Beslemede Kullanım

Nowadays, meeting adequately nutrient requirements of animal is a major problem due to cost of feed. This situation results in the feed manufacturers to search alternative feed source in order to provide more economical feeding in animal nutrition. In Turkey known as a paradise of olive, a number of substances were discharged to the environment during olive processing. After pressing of olive, the olive remains such as olive cake and black water cause off-odour, groundwater pollution, visual pollution and formation of a fly in environment. Among these by-products, olive cake has been extensively used as fuel. However, olive cake and black water can be used as alternative animal feed due to their high nutrient contents. In this review, the importance and use of the olive cake and black water in animal nutrition will be discussed.