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We investigated the effects of finely ground wheat bran on the nutrient digestibility, digesta passage rate, and gut microbiota structure in sows. A 3 × 3 Latin square design with 3 test periods and 3 experimental diets was used. Six non-pregnant sows (parity: 5 to 7) were randomly assigned to 3 experimental diets with 2 replicates per treatment in each period. Each period lasted 19 d (12 d for adaptation and 7 d for experiment). The experimental diets included (a) a basal corn and soybean meal diet (CON), (b) a basal diet with 20% coarse wheat bran (CWB; particle size: 605 μm), and (c) a basal diet with 20% fine wheat bran (FWB; particle size: 438 μm). The results demonstrated that the apparent total tract digestibility of neutral detergent fiber, acid detergent fiber and energy were reduced (

A comprehensive understanding of the fractal properties of concrete meso-structure is important because it is associated with the complex and random mechanical behaviors of the concrete. The fractal dimensions of aggregates and cement are derived and discussed. An experimentation is devised using X-ray and computed tomography (CT) to determine the fractal dimensions of each component of the concrete meso-structure. The fractal dimension of the aggregates is constant and equal to three, whereas that of cement is a real number less than three. The definition for the fractal dimension of the concrete meso-structure was introduced based on these two observations. A comparison with the theoretical derivation indicates that the box-counting dimension of the concrete meso-structure is slightly greater than the theoretical value. Moreover, concrete with similar gradations have a similar fractal dimensions for the meso-structures.

Life cycle assessment of buildings has become popular recently, due to the significant potential of emission reduction. Previous studies have contributed much to the quantification of emissions, yet the issue of uncertainties needs to be further investigated. In general, the uncertainty in life cycle assessment is mainly due to the errors in input parameters, definition of system boundary and scenario assumptions, and choice of analytical models, which could be summarized as parameter, scenario, and model uncertainties. In the present study, data quality indicators were adopted and a semi-quantitative method was modeled accordingly, relevant to the uncertainty analysis of building emission assessment. A case study building was analyzed comparing the deterministic and stochastic approaches, and the results indicate that the uncertainty in input parameters could result in a standard deviation of 3106 tCO2e for the sample mean of 61504 tCO2e, which is in line with the deterministic results. Further scenario analyses investigated the influence of scenario and modelling alternatives. Relevant results emphasized the definition of system boundary and energy efficiency to control uncertainties, and suggested applying statistical distribution for key parameters in analysis. Overall, the present study could provide useful information on the uncertainty of life cycle emission assessment, and, therefore, be helpful in decision-making regarding the low-carbon development of building industry.

The present study was conducted to investigate the effects of feeding level and dietary supplementation with crystalline amino acids (AA) on the determination of energy contents in corn for growing pigs. A total of 36 barrows with an average initial body weight of 41.4 ± 2.0 kg were allocated across six treatments in a 2 × 3 factorial arrangement that included 2 feeding levels (2400 kJ ME/kg BW0.6 per day or ad libitum) and 3 dietary AA supplementation patterns (corn diet with no AA; corn + 3AA diet with addition of lysine, threonine and tryptophan; corn + 5AA diet with greater levels of crystalline lysine, threonine and tryptophan supplementation than those in corn + 3AA diet plus crystalline methionine and isoleucine supplementation). The experiment was conducted in 6 consecutive periods. During each period, 6 pigs were allotted to 1 of 6 treatments, and each treatment corresponded to 1 of 6 respiration chambers. In each period, pigs were individually housed in metabolism crates and fed their respective diets at two feeding levels for 13 d, including 7 d adaptation to the feed, metabolism crate and environmental conditions. On d 8, the pigs were transferred to respiration chambers. Total feces and urine samples were collected and heat production was measured from d 8 to 12. On the last day of each period, the pigs were fasted for 24 h and fasting heat production was subsequently measured. The apparent total tract digestibility (ATTD) of dry matter (DM), organic matter (OM) and gross energy (GE) in diets and corn were not affected by feeding level; however, increasing feeding level tended (P = 0.09) to decrease the ATTD of crude protein (CP). Nitrogen retention increased (P

The building sector contributes substantially to worldwide greenhouse gas emissions, and efforts to meet emission reduction targets have been gaining importance. Accordingly, the present study investigates the importance of building embodied emissions to the entire life cycle and potential approaches for low-carbon development in China. Life-cycle assessment was proposed for the analysis of building emissions, dividing the life cycle into production, construction, operation, and disposal phases. The temporal perspectives of emissions were considered, including the potential improvements to energy efficiency and the weighted average impacts for delayed emissions in the operation and disposal phases. A case study of a residential building in a cold region was analyzed, and scenario analyses were conducted. The results indicated that the relative contribution of embodied emissions (10551 tCO2e) considering the temporal perspectives could be twice that of conventional calculations. Further discussion revealed that the payback time of constructing a new building could be 45 years compared to the current regional average buildings. Hence, with respect to the high costs and technical limits of passive houses, renovating old buildings with energy saving measures might be the most appropriate approach for implementing the short-term low-carbon development target. Overall, the present study is helpful to better understand the importance of embodied emissions and for policy-making in the regional building sector.

The importance of the meso-scale analysis of concrete has been a controversial topic. The accuracy and efficiency of numerical modelling directly influence the results and computational cost. In this study, we propose a versatile fractal-geometry-based modelling method that can generate an aggregate model with a known gradation curve. Two numerical meso-model groups generated by the random fractal method are measured and analysed considering the gradation curve, coarse aggregate content, and fractal dimension as evaluation indices. It is verified that the evaluation indices of the numerical models are consistent with the actual ones. Based on sampling statistical analysis, the geometrical homogenization of the meso-model generated by the random fractal method is found to be satisfactory for meso-scale applications. Furthermore, the random fractal method is shown to have low algorithm complexity.

In recent years, fully grouted reinforced concrete block masonry shear walls have been widely used as key structural elements for seismic resistance in medium- and high-rise buildings. However, accurately estimating their shear strength is truly challenging owing to the complex behavior of masonry walls under in-plane loads. This paper proposes the application of artificial neural network and adaptive neuro-fuzzy inference system models for predicting the shear strength of grouted reinforced concrete block masonry walls. To construct these models, an experiment was conducted and additional experimental data were gathered from published literature. Eleven main parameters were considered to be input parameters: compressive strength of grouted concrete block masonry, wall height, wall length, wall thickness, effective wall length, axial load, longitudinal and transverse reinforcement ratios, horizontal reinforcement spacing, and yield strength of longitudinal and transverse reinforcements. The prediction values of the well-trained artificial neural network and adaptive neuro-fuzzy inference system models agreed well with the experimental data. In addition, the comparison results showed that the two proposed models perform better than the existing empirical models. Therefore, they can be considered accurate and reliable models for estimating the shear strength of grouted reinforced concrete block masonry walls.

Owing to the extensive building projects that are currently underway in China, evaluation of the embodied emissions in the building construction phase is crucial for reducing the carbon footprint. Previous studies have focused on the quantity of emissions, whereas the present study focuses on the issue of uncertainty in building emission assessment. In this context, a semi-quantitative approach was adopted, and the probabilistic distributions of the quantities and emissions of building materials and energy were assessed based on data quality indicators. Further, a case study was conducted to compare the deterministic and stochastic emissions. The results showed that the sample mean of the stochastic results (5891.97 tCO 2e ) was consistent with that of the conventional method, while the relevant standard deviation was estimated as 248.90 tCO 2e owing to the uncertainty of input parameters. In addition, scenario analyses were conducted, including the system boundary, potential reduction of material consumption and emission, and adoption of local production and low-carbon energy to quantify the scenario uncertainty, and the transformation coefficients and temporal correlation to quantify the model uncertainty. The relevant analyses revealed the key factors (e.g. system boundary, steel, concrete, and masonry works, local production, and applicable period of the data) in reducing the embodied emissions and corresponding uncertainties. Overall, the present study can facilitate comprehensive assessment of the uncertainties in building embodied emissions, thereby contributing to low-carbon policy-making in the building industry.

Current onsite safety management always relies on time-consuming predefinitions of hazardous zones based on the managers’ personal capabilities. However, in a typical labor-intensive industry such as construction, the workers themselves can provide a wealth of information for hazard identification. Historical accident-free working locations on site provide a valuable means of recognizing safe workplaces. This paper presents an approach to the automated classification of construction site zones derived from the location tracks of workers collected from a real-time location system (RTLS). Through data mining, filtering and analysis, the location tracks are transformed into grid density maps and continuous density maps. These illustrate the characteristics of spatial-temporal activities onsite as well as providing a visual representation of the distribution of safe and hazardous individual workplaces. A personnel hazard map is generated automatically based on historical accident-free location tracks from a field project using the proposed approach. Compared with the actual workplaces in terms of accuracy, precision, sensitivity and specificity, the evaluation result reveals that the hazardous areas on a construction site can be automatically classified to improve the workplace management of individual workers. The contributions of this research include an automated zone classification algorithm and an evaluation framework consisting of four indicators for hazard awareness onsite.

A complete understanding of the geometrical structure of concrete is important. Based on the geometrical characteristics of concrete, hypothesizing that graded aggregates have a fractal effect is reasonable. In the framework of fractal theory, the fractal dimensions of aggregates and cement were clarified, and a mathematical model of the fractal dimension was formed to describe the geometrical characteristics of concrete. Two numerical meso-model groups generated by the random fractal and traditional generation method were measured and analyzed considering the gradation curve, coarse aggregate content, and weighted mean size as evaluation indices. It was verified that the evaluation indices of the numerical models with the fractal dimension of actual concrete and those of actual concrete were the same, and the numerical simulation results were consistent with theory. Based on sampling statistical analysis, the geometrical homogenization of the meso-model generated by the random fractal method was found to be satisfactory for meso-scale applications.

This probabilistic study investigates the effect of material uncertainties on the numerical analysis of masonry wallette axial compressive strength. Detailed micro-modeling techniques are adopted to model hollow concrete block masonry by separately describing the specific equations for material constituents (blocks and mortar) and block-mortar interfaces. A Latin hypercube sampling technique is used to generate random input variables from the empirical distribution functions of the material parameters. A quasi-static nonlinear analysis is then carried out using a Monte Carlo simulation to evaluate the effect of the spatial variability of material parameters on the compressive behavior of masonry wallettes. The results show that ignoring the spatial variability of material properties may cause a model to overestimate the probability of compression failure. Additionally, the independent and cooperative effects of the material parameters on masonry compressive strength are investigated using first order, second order, and total sensitivity indices. The numerical results indicate that block tensile strength influences masonry compressive strength the most. Several parameters for masonry compressive strength are also ranked in order of importance.

The objective of this experiment was to determine the effects of dietary calcium (Ca) levels on growth performance and bone development of growing and finishing pigs. A total of 150 crossbred pigs (37.0 ± 4.0 kg BW) were randomly assigned to 5 treatment groups: (1) low Ca levels in both grower and finisher phases (LL), (2) low Ca level in grower phase and high Ca level in finisher phase (LH), (3) medium Ca levels in both grower and finisher phases (MM), (4) high Ca level in grower phase and low Ca level in finisher phase (HL), and (5) high Ca levels in both grower and finisher phases (HH). The dietary phosphorus (P) levels were fixed. The animal trial was conducted for 60 days. When the average pen BW reached approximately 60 kg, the pigs were switched to finisher diets. Pig performance was not affected by dietary treatments during either the grower or finisher phases. During the grower phase, the bone mineral density (BMD) and bending moment of the fourth metacarpal and metatarsal bones were lower (P

China is making efforts to reduce carbon emissions from the building industry, and carrying out an allocation and trading system for building emissions. However, to date, methods for using existing statistical data to assess the emissions of the construction sector and to make decisions affecting permit allocation are still unclear. In this context, a process is proposed in this study to calculate the life-cycle emissions of regional construction sectors in China, and a multi-criteria Gini coefficient is introduced as an indicator for emission permit allocation. Statistical data of the construction sector for 2004–2013 were analyzed. The results indicated an overall trend of increased emissions from China’s construction sector, of which the production phase of buildings was shown to be the largest contributor. Various characteristics for different life-cycle sub-processes were also discussed at the provincial level. Finally, a case study of emissions from the construction sector was conducted on the basis of a multi-criteria Gini coefficient. Relevant analyses revealed the major regions in carbon reduction practices from a comprehensive view of efficiency and equality. In addition, suggestions were provided for allocating emissions for regional construction sectors. Overall, the present study would be helpful in the calculation, assessment, and allocation of emissions from China’s construction sector. It should also provide insight into decision-making about low-carbon development policy of the building industry.

In China, the rapid development of the economy has currently led to the extensive construction work. Therefore, determining the carbon emissions embodied in building construction could contribute to successfully implementing the national policy of reducing greenhouse gas emissions. Accordingly, the purpose of this study is to provide a broad perspective on the carbon footprint of building construction. A comparative study was done on two alternative technics, namely, the process-based and the input-output analytical methods. The primary aim of this comparative study was to enhance the accuracy and detail of the data on the embodied carbon in building construction. Three buildings of differing heights and applications were assessed in the case study. The results indicated that materials manufacturing account for 80–90% of the total building embodied emissions. The main structure and the foundation work of the buildings were the sub-projects that contribute the most to embodied emissions (>60%). As both the process-level and the input-output methods have advantages and limitations, a hybrid approach was proposed that combines the advantages of the two methods. The results of this study could be helpful in the assessment and reduction of the embodied carbon typically associated with buildings.

This paper proposes the use of artificial neural networks and adaptive neuro-fuzzy inference systems for estimating the compressive strength of hollow concrete block masonry prisms. Three main influential parameters, namely the prisms’ height-to-thickness ratio and the compressive strengths of hollow concrete blocks and mortars, were used as input to the models. The two models were trained and tested using 102 data sets obtained from the tests conducted by the authors as well as published technical literatures and then verified by comparison with other empirical calculation methods. The results showed that the proposed models have excellent prediction ability with insignificant error rates.

With respect to global climate change, energy consumption and carbon emissions of the building sector has become an increasingly crucial issue in the sustainable development of China. While process-based analyses have been performed in previous research, in the present study, we propose a hybrid input-output approach that could account for supply-chain energy and emissions by China’s building sector. In terms of energy and emission sources, three scopes are defined, primarily aimed at the entire life-cycle of building sector. By dividing the life-cycle into construction, operation, and disposal stages, both scope-based and stage-based analyses are made using domestic statistical data, within the range 1997–2012. The results demonstrate that supply-chain energy and emissions of Scope 3 contribute significantly to the overall life-cycle impacts of building sector, which might be underestimated in a process-based assessment. Although the operation stage appears to be the one with the largest consumption and emissions in the lifespan of a single building, attention should also be paid to the construction stage. The energy and emissions during construction make up the largest share (over 60%) in the life-cycle of the building sector due to the large number of building projects every year. Energy and carbon-intensive components are also evaluated, and possible measures for energy-saving and carbon reduction are discussed. Accordingly, this study provides some useful methods and relevant analysis results, which will be critical for the future of sustainable development of China’s building industry.

This paper addresses the challenge to design an effective method for managers to efficiently process hazardous states via recorded historical data by developing a stochastic state sequence model to predict discrete safety states – represent the hazardous level of a project or individual person over a period of time through a Real-Time Location System (RTLS) on construction sites. This involves a mathematical model for state prediction that is suitable for the big-data environment of modern complex construction projects. Firstly, an algorithm is constructed for extracting incidents from pre-analysis of the walk-paths of site workers based on RTLS. The algorithm builds three categories of hazardous region distribution – certain static, uncertain static and uncertain dynamic – and employs a frequency and duration filter to remove noise and misreads. Key regions are identified as either ‘hazardous’, ‘risky’, ‘admonitory’ or ‘safe’ depending on the extent of the hazard zone from the object’s boundary, and state recognition is established by measuring incidents occurring per day and classifies personal and project states into ‘normal’, ‘incident’, ‘near-miss’ and ‘accident’. A Discrete-Time Markov Chain (DTMC) mathematical model, focusing on the interrelationship between states, is developed to predict states on construction sites. Finally, a case study is provided to demonstrate how the system can assist in monitoring discrete states and which indicates it is feasible for the construction industry.

In this study, an innovative integrated concrete masonry wall (ICMW) system is proposed to improve the seismic behavior of infill masonry in reinforced masonry structures. The ICMW system consists of a load-bearing component comprising two reinforced concrete masonry walls and a partition component comprising one ungrouted masonry wall and autoclaved aerated concrete blocks. Four ICMW specimens were designed for cyclic loading test and the effects of the section type of the load-bearing component and infill on the seismic performance of the specimens were investigated. An obvious pinching effect was observed on the load-displacement curves of all specimens. Different flexural and shear failure modes occurred in the specimens due to the section type of the load-bearing components, whereas the infill heightened the crack propagation. The results indicated that the stiffness degradation, displacement ductility, energy dissipation, and equivalent viscous damping ratio of the specimens were obviously influenced by the section type owing to different failure modes. Moreover, it was observed that the infill had a beneficial influence on the ductility coefficient of the specimens because of its timely separation. Based on these results, it is concluded that the ICMW is an effective construction system in which the partition component participates in the specimen loading process at the initial stage and separates from the specimen to protect it and prevent out-of-plane damage at the final stage.

a b s t r a c t This study was conducted to determine whether supplemental conjugated linoleic acid (CLA) fed during late gestation affects reproductive performance, colostrum production and colostral immunoglobulin (Ig) levels of multiparous sows. Forty-eight, pregnant, Lan- drace × Large White, multiparous sows were allotted to four dietary treatments (n = 12), control (CTR, no CLA addition) and 7.5, 15.0, or 22.5 g/kg CLA supplementation from d 85 of gestation until farrowing. The CLA was added at the expense of soybean oil. All sows were fed the same commercial lactation diet postpartum. Blood samples were collected from sows on d 85, 100 and 112 of gestation while blood samples were obtained from neonatal piglets 24 h postpartum. Colostrum was collected immediately after farrowing and its production was estimated for 24 h starting with the birth of the first piglet. Neither the body weight nor backfat thickness of sows were altered by dietary CLA. Reproduc- tive performance, piglet growth and calculated colostrum production were also unaffected. Compared with the CTR diet, dietary CLA supplementation during late gestation decreased (P < 0.01) the colostral fat, and increased (P < 0.01) the concentrations of IgG, IgA, and IgM in colostrum (P < 0.01). The concentrations of serum Ig and interleukin-2 on d 112 of gestation were increased (P < 0.01) in sows receiving CLA, although those factors did not differ among different levels of CLA supplementation. Serum IgG, IgA, and IgM concentrations in piglets from sows fed diets containing CLA were increased (P < 0.05) 24 h postpartum. This study indicates that dietary CLA has potential immunomodulatory effects in gestating sows and neonatal piglets, whereas there were no differences within the CLA treatments.

Concrete is widely applied in various industries as a composite material, and the relationship between the structure and properties of concrete has been a topic of common interest. An understanding of the composite mechanical behavior of concrete is useful for concrete mix design and damage prediction. This prompted the proposal of an analysis based on the mesoscopic approach for modeling the behavior of concrete. The quality of the finite element analysis that is used to analyze the concrete meso-model depends on the shape, spatial distribution, and orientation of the simulated aggregates. This paper describes a versatile method for simulating the meso-model of concrete aggregates with the result of the sieving test affirmed, based on the formulation of three principal hypotheses. As the aggregates in concrete resemble those generated by random fractal iteration, the particular model is assumed to be random convex quadrilateral in 2D space, and random convex hexahedral in 3D space, and several parameters influencing the modeling result are defined and devised. Prior to generating the meso-model, an idealized model is mathematically defined, with reference to the fractal method, in which several property parameters of the mix conditions of the graded aggregates are explicitly described by mathematical expressions. Based on a comparison between the numerical and experimental tests performed on the concrete under uniaxial compression, it is validated that the random fractal method could basically be used to generate the meso-model of concrete aggregates. Several modifications and prospects expected from future work are discussed.

The construction industry plays an important role in economic and social development, yet it is also a primary source of carbon emissions. Accordingly, owing to global climate change, energy conservation and carbon reduction have become critical issues in the construction industry. However, to date, no established theory has been proposed for the life-cycle carbon assessment of typical buildings in China. To address this, the present study proposes a detailed carbon emission inventory for buildings and divides the life-cycle of a typical building into three stages based on material and energy flow: the materialization stage, the operation stage, and the disposal stage. Additionally, an analytical framework and evaluation indices are established and the proposed methodology is applied to three case studies. The results demonstrate that residential and office buildings with a reinforced concrete block masonry structure could reduce carbon emissions by 38–112 kgCO2/m2 compared with either a reinforced concrete structure or a brick–concrete structure. Although the operation stage appears to contribute approximately 82–86% of the total emissions, the materialization stage is also of considerable importance in alleviating the present environmental pressure. Furthermore, possible measures to control carbon during the materialization stage are proposed and evaluated, including optimization design of building structures based on carbon emissions and the selection of insulation materials. Accordingly, this study provides a standard method for life-cycle carbon assessment of buildings, which will be critical for future low-carbon development.

Four experiments were conducted with 120 pregnant Sprague-Dawley rats to determine effects of dietary arginine supplementation on embryonic survival. Rats were fed a nonpurified diet supplemented with 1.3% (wt:wt) L-arginine-HCl or 2.2% (wt:wt) L-alanine (isonitrogenous control) throughout pregnancy (Expt. 1), between d 1 and 7 of gestation and then the nonpurified diet until parturition (Expt. 2), between d 1 and 7 of gestation for determining the number of surviving embryos on d 7 (Expt. 3), or between d 1 and 4 of pregnancy for blood sampling on d 5 after overnight food deprivation (Expt. 4). Litter size increased (P < 0.01) in response to arginine supplementation throughout pregnancy (14.5 +/- 0.62 vs. 11.3 +/- 0.61) or during the first 7 d of pregnancy (14.7 +/- 0.33 vs. 11.3 +/- 0.37). The number of surviving embryos was greater (P < 0.01) when arginine was supplemented between d 1 and 7 of pregnancy (14.7 +/- 0.39 vs. 11.4 +/- 0.66). Concentrations of nitric-oxide metabolites, arginine, proline, glutamine, and ornithine were higher (P < 0.05), but urea levels were lower (P < 0.05) in the serum of arginine-supplemented rats compared with the control group. The arginine treatment increased (P < 0.05) protein levels for inducible and constitutive nitric-oxide synthase at implantation sites by 35-37%. These results indicate that dietary arginine supplementation enhances embryonic survival, therefore increasing litter size by 30% at term birth. This novel finding has important implications for preventing early pregnancy loss and enhancing reproductive performance in mammals.

Dietary supplementation of glutamine prevents intestinal dysfunction and atrophy in weanling piglets, but the underlying mechanism(s) are largely unknown. This study was conducted to test the hypothesis that weaning or glutamine may modulate expression of genes that are crucial for intestinal metabolism and function. In Expt. 1, we obtained small intestine from 28-d-old pigs weaned at 21 d of age and from age-matched suckling piglets. In Expt. 2, piglets were weaned at 21 d of age and then had free access to diets supplemented with 1% L-glutamine (wt:wt) or isonitrogenous L-alanine (control). At d 28, we collected small intestine for biochemical and morphological measurements and microarray analysis of gene expression using the Operon Porcine Genome Oligo set. Early weaning resulted in increased (52-346%) expression of genes related to oxidative stress and immune activation but decreased (35-77%) expression of genes related to macronutrient metabolism and cell proliferation in the gut. Dietary glutamine supplementation increased intestinal expression (120-124%) of genes that are necessary for cell growth and removal of oxidants, while reducing (34-75%) expression of genes that promote oxidative stress and immune activation. Functionally, the glutamine treatment enhanced intestinal oxidative-defense capacity (indicated by a 29% increase in glutathione concentration), prevented jejunal atrophy, and promoted small intestine growth (+12%) and body weight gain (+19%) in weaned piglets. These findings reveal coordinate alterations of gene expression in response to weaning and aid in providing molecular mechanisms for the beneficial effect of dietary glutamine supplementation to improve nutrition status in young mammals.

Five hundred and four 40-wk-old Brown Dwarf hens (1.51 +/- 0.08 kg BW) were fed corn-soybean meal diets containing 0, 1, 2, 3, 4, 5, or 6% conjugated linoleic acid (CLA) for 56 d to measure the effects of dietary CLA on laying hen productivity and egg quality during refrigerated storage. Four hens were placed in 1 cage, and 3 cages were grouped as 1 replicate resulting in 6 replicates per treatment. After feeding the experimental diets for 11 d, eggs were collected to determine the fatty acid composition of egg yolks. From d 12 to 18, eggs from hens fed diets containing 0, 2, 4, and 6% CLA diets were stored at 4 degrees C for up to 28 d. At designated times (1, 14, or 28 d), eggs were taken, broken, and shelled to evaluate water content, pH, and ion concentration. Firmness of hard-cooked egg yolk was also determined. With increased dietary CLA, feed intake, BW gain, rate of egg production, egg weight, and feed efficiency all decreased linearly (P < 0.01). The weight of the yolk, albumen, and shell decreased linearly (P < 0.01) with increasing dietary CLA. Concentration of CLA in the yolk lipids increased quadratically (P < 0.01), with increasing dietary CLA. Concurrent increases (P < 0.01) in the concentration of myristic, palmitic, and stearic acids and decreases (P < 0.01) in oleic, linoleic, linolenic, and archidonic acids in egg yolk lipids were observed. Days of storage and CLA (P < 0.01) increased yolk firmness. Egg yolk water content and pH increased with storage and CLA content (P < 0.01). Corresponding decreases were observed in albumen pH. Regardless of dietary treatment, the concentrations of Na, K, and Mg in egg yolks increased with longer storage time. At 28 d of storage, there was a linear (P < 0.01) increase in Na, K, and Mg content in egg yolks as dietary CLA increased. In contrast to the egg yolk, the concentrations of Na, K, and Mg in egg albumen decreased with storage time. On d 28, there was a linear decrease (P < 0.01) in the Na content of albumen with increasing CLA. This study suggests that the greater firmness of CLA-fed eggs might be related to the change of pH, water content, and ion concentrations during refrigerated storage.