Estimated Energy Requirements Research Articles

Prospective life cycle approach to buildings' adaptation for future climate and decarbonization scenarios

The existing building stock is crucial for enhancing decarbonization targets and mitigating climate change. This article delves into a methodological approach that combines prospective life cycle assessment, building thermal simulation using projected future climate data, and global sensitivity analysis to pinpoint the most influential parameters under current climate conditions and future scenarios. The methodology covers plausible decarbonization pathways for the electricity mix, considering the growing utilization of renewable sources, which are influenced by the building locations. An adaptive reuse process involves converting a historic residence into an office building to validate the proposed methodology. Several retrofit strategies are assessed, such as exterior wall insulation, roof insulation, and window replacement. The findings reveal a 12% rise in average usage impacts and a 7% increase in cradle-to-use impacts from the base scenario to future climate projections. Embodied impacts surpass use-phase impacts by 23% in future climates and 33% in certain baseline scenarios. Utilizing future climate data in the life cycle analysis to estimate energy requirements can aid in forecasting building performance under climate change, especially in adapting the existing building stock for enhanced thermal comfort with minimal environmental impact.

Sources and determinants of free sugars intake by 5-year-old Australian children in the SMILE cohort.

Reducing free sugars intake is important for the prevention of dental caries and obesity in children. The study aimed to determine the amount and sources of free sugars known to contribute to dental caries, and identify sociodemographic determinants of intake by children aged 5 years in Australia. Cross-sectional analysis of dietary data from a cohort study, collected using a customized food frequency questionnaire were used to calculate free sugars intake as grams/day and percentage contribution to Estimated Energy Requirement (EER).The percent contribution of food sources to free sugars intake was derived. Sociodemographic determinants of achieving intakes within WHO thresholds (i.e., <5% and <10% Energy were explored with multinomial logistic regression. Complete data were available for 641 children (347 boys, 294 girls). Median (IQR)free sugars intake (g/day) was 31.6 (21.3-47.6) in boys and 28.1 (19.6-47.9) in girls. The median (IQR)percentage contribution to EER was 7.9 (5.4-12.7); 21% and 42% of children had intakes <5% EER and between 5% and<10%, respectively. The main sources of free sugars were: (1) Cakes, Biscuits and Cereal Bars; (2) Sweetened Milk Products (predominantly yoghurts) and (3) Desserts. Maternal university education, single-parent household, and maternal place of birth being Australia or New Zealand were associated with free sugars intake <5% EER. In conclusion, less than a quarter of 5-year-old children in the SMILE cohort achieved the WHO recommendations to limit free sugars to <5% EER. Strategies to lower free sugars intake could target priority populations such migrants, populations with lower levels of education or health literacy and identify areas for intervention in the wider food environments that children are exposed to.

Triple burden of malnutrition among Vietnamese 0·5-11-year-old children in 2020-2021: results of SEANUTS II Vietnam.

SEANUTS II Vietnam aims to obtain an in-depth understanding of the nutritional status and nutrient intake of children between 0.5-11.9 years old. Cross-sectional survey. A multistage cluster systematic random sampling method was implemented in different regions in Vietnam: North Mountainous, Central Highlands, Red River Delta, North Central and Coastal Area, Southeast and Mekong River Delta. 4001 children between 6 months and 11.9 years of age. Prevalence of stunting and underweight was higher in rural than in urban children, whereas overweight and obese rates were higher in urban areas. 12.0% of the children had anemia and especially children 0.5-1-year-old were affected (38.6%). Low serum retinol was found in 6.2% of children ≥ 4 years old. Prevalence of vitamin D insufficiency was 31.1% while 60.8% had low serum zinc. For nutrient intake, overall, 80.1% of the children did not meet the estimated energy requirements. For calcium intake, ∼60% of the younger children did not meet the RNI while it was 92.6% in children >7 years old. For vitamin D intake, 95.0% of the children did not meet RNI. SEANUTS II Vietnam indicated that overnutrition was more prevalent than undernutrition in urban areas, while undernutrition was found more in rural areas. The high prevalence of low serum zinc, vitamin D insufficiency and the inadequate intakes of calcium and vitamin D are of concern. Nutrition strategies for Vietnamese children should consider three sides of malnutrition and focus on approaches for the prevention malnutrition.

Determination of optimal energy system and level for growing pigs.

This study mainly evaluated the responses in growth performance of growing pigs to different energy systems and energy levels in diets. Subsequently, we compared the nutrient digestibility and digestible nutrient concentrations of each energy level diet. In experiment 1, a total of 144 growing pigs with an average initial body weight (BW) of 26.69 ± 7.39 kg were randomly allotted to six dietary treatments (four pigs/pen; six replicates/treatment) according to a 2 × 3 factorial arrangement resulting from two energy systems (metabolizable energy [ME] and net energy [NE]) and three energy levels (low [LE], recommended [C], and high energy [HE]). Pigs were fed the experimental diets for 6 weeks and were allowed free access to feed and water during the experimental period. In experiment 2, 12 growing pigs with an average initial BW of 27.0 ± 1.8 kg were randomly allotted to individual metabolism crates and fed the six diets in a replicated 6 × 6 Latin square design. The six dietary treatments were identical to those used in the growth trial. Pigs were fed their respective diets at 2.5 times the estimated energy requirement for maintenance per day, and this was divided into two equal meals provided twice per day during the experimental period. Differences in energy systems and energy levels had no significant effect on the growth performance or nutrient digestibility (except acid-hydrolyzed ether extract [AEE]) of growing pigs in the current study. However, the digestible concentrations of ether extract, AEE, and acid detergent fiber (g/kg dry matter [DM]) in diets significantly increased (p < 0.05) with increasing energy levels. Additionally, there was a tendency (p = 0.09) for an increase in the digestible crude protein content (g/kg DM) as the energy content of the diet increased. Consequently, differences in energy systems and levels did not affect the BW, average daily gain, and average daily feed intake of growing pigs. This implies that a higher variation in dietary energy levels may be required to significantly affect growth performance and nutrient digestibility when considering digestible nutrient concentrations.

Navigating Nutritional Strategies: Permissive Underfeeding in Critically Ill Patients.

Nutritional support is a critical component of care for critically ill patients, impacting their recovery and overall prognosis. Traditional approaches to feeding in the intensive care unit (ICU) have focused on meeting estimated energy requirements, often resulting in unintended consequences such as overfeeding and associated complications. Permissive underfeeding, a concept gaining attention recently, offers a more controlled approach by intentionally providing fewer calories than traditionally recommended. This comprehensive review explores the rationale, evidence, and practical considerations surrounding permissive underfeeding in critically ill patients. We discuss the physiological basis of permissive underfeeding, its potential benefits in mitigating the risks of overfeeding, and the challenges associated with implementation in clinical practice. Through an analysis of critical studies and clinical trials, we evaluate the comparative effectiveness of permissive underfeeding versus traditional feeding methods and examine its impact on patient outcomes. Recommendations for patient selection, monitoring, and future research directions are provided to guide clinicians in optimizing nutritional support strategies for critically ill individuals. By considering the role of permissive underfeeding alongside traditional feeding approaches, healthcare professionals can tailor nutritional interventions to individual patient needs, ultimately improving outcomes in the ICU.

A simplified dynamic tool for building heating and cooling energy requirements estimation on a daily time scale

A persistent dilemma in building energy modeling consists of finding the proper trade-off between accurate results, data availability and limited modelling effort. In fact, quasi-steady state models require a limited number of inputs, however providing often rough results; dynamic tools are instead usually very accurate but involve a huge effort to obtain all the needed information and implementing it into the tool. In this context, we propose a simplified dynamic model for building heating and cooling demand estimation on a daily basis, according to the assessment of all the involved heat transfer mechanisms of the thermal zone. The required inputs are limited and comparable to those needed for other quasi-steady state models, but three tuning coefficients allow the simulation to be performed at the daily time scale. The proposed tool is here successfully tested on a wide set of test cases, differing for building structure, external climate, and occupants’ profile. In addition, reliable results are provided also in case of multi-year application and availability of a little amount of data for calibration, with average errors typically below 10% in daily cooling and heating energy requirement estimation, compared to benchmark demands. Finally, an example of application explores the application field of the tool.

More dietary advice may be needed to support healthy body composition for children with cerebral palsy in Aotearoa New Zealand

The available literature on the nutritional status of children with cerebral palsy (CP) worldwide has identified high rates of malnutrition, specifically undernutrition(1). However, there is a current lack of clear CP-specific dietary guidelines for children with CP across all functional levels. Standard reference tools such as estimated energy requirement (EER) and recommended dietary intake (RDI) may overestimate requirements in children with CP, especially those with reduced mobility and activity levels. Furthermore, for children with severe CP, body composition data indicates higher risks of obesity and obesity-related conditions(2). There can be a wide range of functional abilities, classifiable with tools such as the Gross Motor Function Classification System (GMFCS) and the Eating and Drinking Ability Classification System (EDACS). The majority of nutrition-related CP literature focuses on children requiring assistance for feeding (EDACS IV-V) with little information available for children with higher levels of functional independence. The aim of this study was to determine whether children with CP had received any prior dietary guidance for healthy body composition and to summarise the type of advice received. Children aged 5-12 years and their whānau were invited to participate in a study where a purpose-developed questionnaire captured their history of receiving tailored dietary recommendations for CP. Body composition was assessed via whole-body dual-energy X-ray absorptiometry scan. Nine participants (6 males, median age: 10y, n = 2 Māori), across GMFCS levels I-IV and EDACS levels I-III took part in the study. Out of 9 children, 5 (55%) indicated that their child had never received dietary advice, 3 of whom were classified as obese or overweight based on growth chart percentiles using their measures of body fat percentage, 1 was classified as underweight and 1 was within the healthy ranges. Of the 4 who had previously received advice, its nature was reported as in support of weight gain (n = 3), and weight loss (n = 1). All 4 received dietary advice from a dietitian and 1 reported some additional advice from a pediatrician and/or orthopedic doctor. Two of the children who had received dietary advice fell within a healthy body fat percentage based on the growth chart percentiles at the time of the study, while the other two were classified as overweight or obese. The results indicate the importance of developing clear dietary guidance for children with CP which may differ from that for typically developing children, particularly depending upon CP subtype diagnosis and functional level, in order to support healthy body composition.

Diet and well-being of 1st year Medical Interns during hospital placement

Hospital placement is essential training for medical interns, involving shift work and high-pressure environments. This can increase physiological and psychological stress, which may be mediated by metabolites of microbial digestion(1). Nutrients of interest include those accessible to microbial digestion and associated with altered signalling within the microbiota-gut-brain axis (MGBA)(1). Fibre is fermented by gut microbes to produce short-chain fatty acids(2) and is associated with improved psychological outcomes(3). Tryptophan, a precursor to gut-derived serotonin(2), has been negatively associated with anxiety(4). Processed foods contain food additives, excess sugars, and saturated fats that may disrupt gut homeostasis(1) and impact psychological well-being(4). Lastly, total energy intake may determine the level of substrate available for microbial fermentation(2). Therefore, this research explores how microbiota-accessible food components interact with physical and psychological well-being in a cohort of medical interns undertaking their first-year of hospital placement. Participants were healthy medical interns, during first-year hospital placement (n = 21) from the Hunter New England Local Health District, NSW, Australia. Participants completed diet and wellbeing surveys at baseline and every 2 months over a 10-month period. 24-hour diet diaries were self-recorded from participants using a mobile application (Easy Diet Diary) and analysed using AusNut and the NOVA classification system of ultra-processed foods (ULP). Wellbeing surveys include depression, anxiety, stress scale (DASS), and PROMIS survey for mental (M), physical (P), and sleep well-being. Current data represents an ‘in-progress’ of the longitudinal data collection. This study utilised Spearman correlation and Tukey’s post hoc test for mixed methods analysis. From baseline to timepoint 3 (T3, 4 months) daily energy intake was consistent with cohort estimated energy requirements (EER). However, consumption ranged from 37% to 167% of EER, indicating a large variation of intakes. Energy consumed from ULP ranged from 30% to 34% (p = 0.6875). Baseline tryptophan intake (x¯ = 1139mg) was within the suggested target, whilst fibre intake (x¯ = 23g) was below the recommended intake. Neither saw significant changes from baseline to T3. Fibre intake was positively correlated with mental and physical well-being at baseline (x¯ = 23.1g, M: r = 0.474, p = 0.04, P: r = 0.608, p = 0.007), and timepoint 2 (x¯ = 31.5g, M: r = 0.647,p = 0.026, P: r = 0.780, p = 0.004) but not at T3. In addition, baseline consumption of sugar (x¯ = 18g) and poly-unsaturated fats (x¯ = 15g) were both negatively correlated with mental and physical well-being. Overall, no significant dietary changes were evident from baseline to mid-year collection in a first-year medical intern cohort during hospital placements. Fibre was significantly associated with mental and physical well-being, building on current understanding of fibre’s role in the MGBA. Planned metabolite analysis will explore the mechanisms of proposed microbiome-accessible nutrients alongside diet, well-being, and microbiota data. Findings from this study will identify how diet-microbiome interactions change under stress, with wider positive implications on intense workplace environments with the aim to preserve individual wellbeing.

한국 학령기 아동의 체중상태에 따른 식생활 특성 및 영양섭취 실태

Objectives This study aims to determine the status of obesity and underweight among school-age children in Korea and to compare and analyze dietary characteristics and nutrient intake status according to weight status.&#x0D; Methods Data from a total of 2,075 children aged 6 to 11 who participated in the 7th and 8th Korea National Health and Nutrition Examination Survey (KNHANES) conducted from 2016 to 2019 were used for analysis. The height and weight of participants were used to calculate body mass index (BMI). The participants were then classified into underweight, normal weight, and overweight/obese groups. Differences in socioeconomic and dietary characteristics for each weight group were analyzed. Energy, intake of the three main nutrients, rate of energy supply, nutrient intake ratio to dietary reference intake, and the ratio of those below the nutrient reference intake were calculated for each weight group.&#x0D; Results Results indicated that 9.45% of male children and 10.74% of female children were underweight, while 20.57% of male children and 18.10% of female children were overweight/obese. The lower the parents’ education level, the higher the rate of overweight/obesity in children. Children who skipped breakfast more than five times a week had a higher rate of overweight/obesity than children who skipped breakfast less than five times a week. Compared to the underweight group, the overweight/obese group consumed more vegetables, meat, fish, and seafood but less fruit. The intake ratio to the estimated energy requirements (EER) was 97% in the underweight group and 102 to 108% in the normal and overweight/obese groups. The intake ratio of protein to the recommended intake (RI) was 144 to 166%, exceeding the protein reference intakes for all weight groups. The intake ratios of vitamin A and calcium to the RI were low at 73 to 74% and 63 to 69% in all weight groups, respectively.&#x0D; Conclusions Thus, this study suggests that the government, community-related organizations, and schools should continue to cooperate to provide efficient intervention programs to manage the health and nutrition of obese and underweight children.&#x0D;

Environmental impact of Holstein Friesian and 3-breed crossbred dairy cows using a life cycle assessment approach applied to individual animals

This study aimed to set up a Life Cycle Assessment (LCA) approach at level of individual animals to assess the effects of a 3-breed crossbreeding program on the environmental impact of cows. It involved 564 cows, 279 purebred Holstein (HO) and 285 crossbreds (CR), originated from a 3-breed crossbreeding program based on the rotational use of Viking Red, Montebèliarde and HO sires and kept in 2 dairy herds of northern Italy (224 and 340 cows/herd, respectively). The reference unit of the LCA model was the lifetime of cows, from the birth to culling or death. Data were collected at different levels: individual animal-based data referred to the whole life (birth, calving, dry, cull or death dates, and milk production); individual test-date collection of body measures and BCS, used to predict body weight and to estimate energy requirements; common farm-based data concerning herd management (diets composition, and materials used). Data were used to compute: dry matter intake, milk and milk components production, gross income (GI) and income over feed costs (IOFC) pertaining to the lifespan of cows. An individual LCA-derived approach was set up to compute global warming potential (GWP), acidification and eutrophication potential (AP and EP, respectively), and land occupation (LO), which have been associated with different functional units (cow in her whole life or per d of life; kg of milk fat plus protein, and € of GI and of IOFC produced in the herd life). Data were analyzed using a generalized linear model including the fixed effects of genetic group (CR vs HO), farm and their interaction (genetic group x farm). Compared with HO, CR cows completed more lactations (+12%), had earlier first calving (-2 weeks), yielded more fat plus protein in milk both in the lifespan (+8%) and per d of life (+4%). Concerning the environmental impact, when compared with HO herd mates, CR cows had nominal greater emissions per cow in the whole life, similar emissions per d of life and nearly 3% lower GWP, AP and EP per kg of fat plus protein yielded in lifespan. Income over feed costs per unit of emission tended to be nearly 4% greater in CR compared with HO cows. Also the use of land tended to be lower in CR compared with HO in most indicators considered. In conclusion, LCA could be adapted to represent individual animals. Moreover, managing dairy cows according to a 3-breed rotational crossbreeding scheme may be regarded as a strategy that can contribute to mitigate the emissions and to improve the environmental impact of dairy operations.

Measured versus estimated energy requirement in hospitalized patients

Failure to identify a patient's energy requirement has a variety of consequences both physiological and economical. Previous studies have shown that predictive formulas, including the Harris Benedict equation (HB), both over- and underestimates energy requirement in severely ill patients and healthy younger adults, compared to the golden standard, indirect calorimetry (IC). The comparison between measured and estimated energy requirements in hospitalized patients in regular wards is underreported. The aim of this study was to assess the agreement between measured energy requirements and requirements estimated by HB in the individual hospitalized patients, and to investigate whether those findings were associated with other specific patient characteristics. IC (n=86) was used to measure resting energy expenditure (REE) and bioimpedance analysis (BIA) (n=67) was used for body composition in patients admitted to Aalborg University Hospital. Furthermore, height, weight, body mass index, calf circumference, while information regarding hospital ward, vital values, dieticians estimated energy requirements and blood samples were collected in the patients' electronic medical records. Bland-Altman plots, multiple linear regression analysis, and Chi2 tests were performed. On average a difference between IC compared with the HB (6.2%), dietitians' estimation (7.8%) and BIA (4.50%) was observed (p<0.05). Association between REE and skeletal muscle mass (SMM) (R2=0.58, β=149.0kJ), body fat mass (BFM) (R2=0.51, β=59.1kJ), and weight (R2=0.62, β=45.6kJ) were found (p<0.05). A positive association between measured REE and HB were found in the following variables (p<0.05): CRP, age, surgical patients, and respiratory rate. This study found a general underestimation of estimated energy expenditure compared to measured REE. A positive correlation between measured REE and SMM, BRM and weight was found. Lastly, the study found a greater association between CRP, age, surgical patients, and respiratory rate and a general greater than ±10% difference between measured and estimation of energy requirements.

Lab-scale engineered hydrochar production and techno-economic scaling-up analysis

Despite the extensive use of engineered hydrochar (EHC) for contaminants adsorption in water, little is known about the scaling-up of EHC production which has kept the technology at a low readiness level (TRL). Full-scale EHC production was simulated to help bridge this knowledge gap. A systematic analysis was performed where EHC was produced from rice straw using hydrothermal carbonization (HTC) at 200 °C with iron addition. A techno-economic evaluation model was employed to simulate the production process and to estimate energy requirements, configuration, and cost scenarios for the HTC process. The minimum selling price (MSP) analysis of the engineered hydrochar was found to be almost half compared to the market price for other similar sorbents ($ 76/t vs. $136/t) suggesting that EHC production is feasible for scaling up. Finally, as a trial, the resulting material was tested for its efficacy in the adsorption of an anionic organic contaminant (e.g., Congo Red, C32H22N6Na2O6S2) in water to identify its potential for water treatment. Experimental results showed that EHC adsorbed > 95% CR suggesting significant adsorption capability and feasibility for production scale-up.

Comparison of total daily energy expenditure with dietary reference intakes values in a sample of urban, relatively active Brazilian adults: A doubly labeled water study.

This report aimed to describe the results of total daily energy expenditure (TDEE) assessed by doubly labeled water (DLWTDEE) and the adequacy of the dietary reference intakes (DRI) equations to estimate energy requirements (DRIER). A cross-sectional and observational study in a convenience sample of 40 healthy Brazilian adults (≥20 years; 21 women) living in a tropical urban region. Basal metabolic rate (BMR) was measured by indirect calorimetry, DLWTDEE was compared with DRIER using individual calculated physical activity level (PAL = DLWTDEE/BMR) in its estimation. BMR (5043 ± 548 kJ/day in women and 6213 ± 656 kJ/day in men), DLWTDEE (8372 ± 1324 kJ/day and 11 453 ± 1834 kJ/day), and PAL (1.66 ± 0.17 and 1.85 ± 0.30, respectively) were significantly higher in men. The DRIER significantly overestimated DLWTDEE by 13.7 ± 8.3% and 12.7 ± 10.7% in women and men, respectively. In the present sample of relatively active urban Brazilian subjects, the DRIER yielded inaccurate estimation of DLWTDEE. More data from low- and moderate-income countries are necessary to develop accurate estimates of TDEE.

Carbon footprint and energy life cycle assessment of wind energy industry in Libya

The recent investigation has demonstrated that wind energy holds great potential as a viable and environmentally friendly energy source in Libya. The study employed a Life Cycle Assessment (LCA) methodology to evaluate various energy, economic, and environmental indicators for potential wind farm installations at multiple suitable locations across Libya. The assessment encompassed estimations of energy requirements and greenhouse gas (GHG) emissions associated with the conversion of wind energy into electricity throughout the entire life cycle of the proposed wind farms. In light of Libya not being a producer of wind energy converters, a novel approach was developed to define the system's boundaries. These boundaries included distinct subsystems, each corresponding to various stages within the life cycle of a wind energy system, encompassing factors such as shipping emissions from the manufacturer's location to Tripoli's marine ports, land transportation to the wind farm sites, energy and emissions associated with installation, operation, maintenance, and eventual disposal of wind turbines.Hourly climate data spanning a 25-year period from 1995 to 2020 were gathered from the SolarGis climate information site. The System Advisor Model (SAM) program was utilized to predict the energy yields of 100 MW capacity wind farms at 12 sites in Libya. Additionally, a novel eco-environmental indicator known as the Life Cycle Levelized Cost of Energy (LCLCOE) was introduced, which factors in all environmental damage costs throughout the entire lifespan of wind energy projects. The study's findings revealed that the Gamesa turbine, with a capital cost of $146,916,400 for a 100 MW capacity wind energy farm, exhibited the most favorable economic and environmental performance. GHG emission factors across all examined cities ranged from 32 to 70 gGHG/kWh, with carbon payback durations spanning from 4.5 to 12.3 months. The estimated energy payback period varied from 13 to 22 months, while the LCLCOE ranged from 4.8 to 8.4 ¢/kWh.

Energy – a scoping review for the Nordic Nutrition Recommendations 2023 project

We need energy intake to provide energy and nutrients to our cells. The amount of daily energy intake should aim for energy balance, which results in good health. Under- or overconsumption of total daily energy over a longer period leads to increased risk of diseases. In this scoping review, the components of daily energy requirement are defined. Several methods to estimate energy requirements and the amount of total daily energy intake (kJ) related to health are also discussed. Reference values for energy intake in children, adults and pregnant and postpartum women, and older adults are evaluated.&#x0D; Results show that it is challenging to set reference values for energy intake since existing methods are not accurate and precise, and there are several factors that influence the estimated amount of energy. Energy requirement is increased during growth as in childhood, pregnancy and lactation. We conclude that more research in this area is needed, and that new high-quality studies in both Nordic and Baltic countries are needed to obtain new recommendation numbers for energy intake.

3 Overview of Poultry Modeling Evolution

Abstract This presentation aims to review advances in mathematical models used in poultry nutrition and production in the past decades and present an overview of the current status. Models have been developed to improve understanding of growth, voluntary feed intake, nutrient utilization, body composition, responses to nutrient supply, environmental changes, and stressors. Growth models for broilers, turkeys, ducks, layers, and breeders are available mainly based on the Gompertz curve, but a few other mathematical functions are also used. A few models can simulate egg production in layers and breeders. The EFG and Avinesp models, tools from feed additive and genetic companies, among others, will be described or mentioned. These models can describe genetic differences and estimate energy, amino acids, calcium, and phosphorus requirements or multiple biological responses to specific nutrient levels. Most models use the concept of ideal protein or balanced protein to describe responses to amino acid levels. However, very few models can describe responses to modifications of one or two specific amino acids. Compartmental models are mainly based on main chemical components such as water, body and feather protein, fat, and ash. Poultry models seldom consider variability due to feeding ingredient quality, fiber, fat, other mineral composition, or variation in nutrient digestibility. However, some models can predict responses to exogenous enzymes. Most applications can predict body weights and yields at a specific age, and some can estimate nitrogen, calcium, and phosphorus excretion. These models can be integrated with feed formulation software, economic data, and optimizers to simulate multiple conditions and estimate biological, economic, and environmental optimums. Poultry enterprise models can describe the whole production system, estimate the optimum combination of resources, aid in planning and scheduling, and determine strategies for growth. Currently, no official recommendations from academic or private groups are based only on models to estimate nutrient levels. Combinations of empirical data and model results are frequently used for nutritional decision-making. A few tools are available for specialized personnel to decide the energy and amino acid levels to use. The application of electronics and telecommunications triggered the fast production of enormous volumes of data from diverse poultry production sectors. This big data avalanche is starting to help modelers to integrate more accurate information and incorporate natural variability. However, integration between current models and significant data results is still under development. Despite increasing international collaboration in modeling, poultry model developments keep great independence and fundamental differences. One critical issue needed for faster development of poultry modeling is to increase education in modeling. The lack of academic programs offering modeling classes related to poultry caused the low current application of models. However, awareness about the benefits of modeling has increased in the past few years, and efforts are under development.

PSX-10 Pilot Study Estimating Energy Expenditure in Dogs Using a Quantified Health Approach Indicates Potential to Improve Estimation of Energy Requirements

Abstract Over 50% of dogs in the USA are overweight or obese indicating that owners find it difficult to know how much food their dog needs. Feeding guidelines are based on the average energy requirements of dogs and do not take into account measured activity levels, which may lead to overfeeding by well-intentioned owners. The most common published energy prediction equation is (RER*AF) where RER is Resting Energy Requirement [70*(BW kg)0.75)] and AF is the Activity Factor, which generally ranges between 1 (body weight loss) and 8 (heavy work). This equation requires the user to estimate activity levels when selecting an AF, which may result in under- or overfeeding. The objective of this pilot study was to determine the ability of collar-worn activity monitors to more accurately predict the energy expenditure of dogs. Ten weight-stable beagles were group-housed at the Hill’s Pet Nutrition Center in Topeka, KS. Dogs were provided daily access to open, outdoor play space and human interaction; water was freely available. Dogs were weighed before feeding on days 1 and 5 of each of the 2 test periods. Accelerometer-based activity monitors were attached to the collars of the dogs on day 1 of each test period and activity was continually measured throughout the study using the activity monitor. Daily food consumption in grams was recorded and was converted to energy intake using the caloric density of the food. Daily energy requirements were calculated for each dog using the standard RER equation and either a standard AF of 1.6 or the estimated energy required for activity, in which newly established algorithms for quantification of walking, trotting, and running behaviors were paired with estimated caloric expenditure based on level of exertion (quantified health approach). The mean absolute error (MAE) of each method was calculated as the absolute value of the difference between the daily energy requirement vs. the daily caloric intake for each dog. The MAE was averaged across all dogs and all days for each of the two methods. The MAE ± SD of the standard RER and AF was 103 ± 126 kcal/day (Range -21.5 to 216 kcal/day). The MAE ± SD of the quantified health approach was 86 ± 90 kcal/day (Range -37.6 to 164.4 kcal/day). Both approaches resulted in normal MAE distributions. In this pilot study, quantifying energy expenditure using a wearable activity monitor reduced over-feeding by 16.5% compared with standard equations. In the future, energy predictions based on measured activity could result in more accurate feeding recommendations than traditional approaches. Future research aimed at optimizing energy predictions may help address the problem of pet obesity. This study was approved by the Hill’s Internal Animal Care and Use Committee. Funding: This study was funded by Hill’s Pet Nutrition, Inc.

Updated Estimated Energy Requirements: How Do They Measure up to Indirect Calorimetry?

Updated Estimated Energy Requirements: How Do They Measure up to Indirect Calorimetry?

Enhancing energy efficiency in a smart home through window-based support vector regression for energy consumption prediction

Efficient energy management is greatly facilitated by accurately predicting energy consumption in a smart home, benefiting both consumers and utilities alike. The conventional forecasting techniques rely on pre-trained statistical models built upon extensive historical data, which may experience performance degradation due to the dynamic nature of power load demands. To address this limitation, this study proposes a novel approach employing Window-based Support Vector Regression (WSVR) to accurately estimate energy requirements from a smart grid within a smart home. The dataset utilized for this research is sourced from Pecan Street in Texas, USA. To assess the efficacy of the proposed model, it is compared to several other time series data prediction models, including ARIMA, Holt Winter's, Linear Regression, Support Vector Machine, and Support Vector Regression. The performance of each model is evaluated, and the results are thoroughly examined and discussed.

Validation of predictive equations for resting energy expenditure in children and adolescents with different body mass indexes

BackgroundAccurate estimation of resting energy expenditure (REE) in children and adolescents is important to establish estimated energy requirements. The objective of this study was to assess the validity of existing equations in literature and a newly developed equation in estimating REE in children and adolescents.Methods275 participants (148 boys, 127 girls) aged 6–18 years included in the study were classified as normal-weighted, overweight, obese based on BMI z-scores for age according to WHO-2007 growth curves for 5–19 years of age. REEs were measured using an indirect calorimeter, with various equations, and a newly established equation [REE = 505.412+(24.383*FFM);Adjusted R2 = 0.649] were compared with REE measured using Bland-Altman and further validation parameters.ResultsWhen the predicted REEs were compared with the measured REEs, the highest prediction accuracy was achieved using the new Eq. (64.8%) and IOM (63.8%) for normal-weight participants, Müller FFM and new Eq. (59.6%) for overweight participants and Lazzer (44.9%) for obese participants. In normal and overweight participants, lowest root mean squared error (RMSE) values were acquired from Schmelzle’s equation (respectively 136.2;159.9 kcal/d), and the highest values were found in Kim’s Eq. (315.2; 295.2 kcal/d respectively). RMSE value of the new equation was 174.7 kcal/d for normal-weight children and adolescents, and 201.9 kcal/d for overweight ones. In obese participants, the lowest RMSE value was obtained from Schmelzle’s Eq. (305.4 kcal/d) and the new Eq. (317.4 kcal/d), while the highest value was obtained from IOM Eq. (439.9 kcal/d). RMSE was higher in obese groups compared to the other BMI groups.ConclusionIndirect-calorimeter is the most suitable method for REE measurement in especially obese children and adolescents. The new equation and Schmelzle’s equation appear to be most accurate equations for normal and overweight children and adolescents.