Quality Performance Evaluation Research Articles

Evaluation of Quality Performance in Paper Pulp vs. Polyethylene Nursery Pots for Green Sustainability

The use of biodegradable paper pulp pots has been gaining traction, especially among environmentally conscious consumers and horticultural practitioners who prioritize sustainability. The choice between paper pulp and polyethylene nursery pots in horticultural practices is a complex decision, involving considerations such as environmental impact, cost-effectiveness, durability, and overall sustainability. This study aims to provide practical insights into the comparative performance of paper pulp and polyethylene pots, specifically in terms of plant health, degradation, and techno-economic considerations. The study involved the growth performance assessment of four plant species, Cannonball Tomato, Celebrity Tomato, Parris Island Lettuce, and French Marigold, in a greenhouse experiment setup. Additionally, a degradation analysis was conducted to determine the average degradation rate and pattern. Finally, a techno-economic analysis compared the value of plant health and degradation with the market price. By evaluating the quality performance aspects of paper pulp pots, this study not only provides valuable insights but also identifies potential areas of improvement for other biodegradable pots, thereby contributing to the ongoing efforts to promote sustainable horticultural practices.

Automated Web-based Software for CT Quality Control Testing of Low-contrast Detectability using Model Observers.

The Channelized Hotelling observer (CHO) is well correlated with human observer performance in many CT detection/classification tasks but has not been widely adopted in routine CT quality control and performance evaluation, mainly because of the lack of an easily available, efficient, and validated software tool. We developed a highly automated solution - CT image quality evaluation and Protocol Optimization (CTPro), a web-based software platform that includes CHO and other traditional image quality assessment tools such as modulation transfer function and noise power spectrum. This tool can allow easy access to the CHO for both the research and clinical community and enable efficient, accurate image quality evaluation without the need of installing additional software. Its application was demonstrated by comparing the low-contrast detectability on a clinical photon-counting-detector (PCD)-CT with a traditional energy-integrating-detector (EID)-CT, which showed UHR-T3D had 6.2% higher d' than EID-CT with IR (p = 0.047) and 4.1% lower d' without IR (p = 0.122).

Sustainable biocomposites from pyrolyzed lignin and recycled nylon 6 with enhanced flame retardant behavior: Studies on manufacturing and quality performance evaluation

AbstractThe recycled nylon (RN)‐based biocomposites were fabricated by adding 25% lignin biocarbon. Lignin was pyrolyzed at 300, 600, and 900°C to produce Lig300, Lig600, and Lig900 biocarbon (BioC) samples, respectively. Higher functionality of Lig600 (unlike Lig900) allowed for improved interfacial interaction with the polar nylon matrix. Mechanical properties were further enhanced for RN_Lig600 composite with enhanced flexural and tensile strength by 18% and 8%, respectively, compared to neat polymer (RN). RN_Lig900 composite showed enhancement in tensile and flexural modulus by 32.6% and 51.1%, respectively, compared to RN. Incorporation of Lig900 in RN matrix resulted in 77.9% reduction in burning rate compared to RN. These results show the potential of lignin BioC as a filler in RN composites for flame retardant applications and mechanical enhancement, such as in the automotive industry.Highlights Effect of pyrolysis temperatures (300, 600, and 900°C) on lignin biomass. Composites prepared from recycled polyamide 6 from carpet waste and biocarbon. Improved interfacial adhesion of 600°C biocarbon with recycled nylon matrix. Enhanced thermal, mechanical properties, reduced flammability of biocomposites. Sustainable biocomposites with 900°C biocarbon reduced burning rate by 78%.

The Path to Continuous Development in Higher Education: Interplay between Quality Service, Student Satisfaction, and Performance Evaluation

This study explores the mutual interaction among quality services, student satisfaction, and performance evaluation in higher education and their impact on sustainable development. Through literature review and case analysis, it discusses how these elements collectively drive progress in higher education and enhance educational quality. The research findings indicate that effective quality services, satisfactory student experiences, and scientific performance evaluation are key factors in achieving sustained development in higher education.

Performance Evaluation of Power Quality in Shipboard Microgrid Under Different Working Conditions

Performance Evaluation of Power Quality in Shipboard Microgrid Under Different Working Conditions

Comparative Power Quality Performance Evaluation of Grid-Connected Solar PV System

Comparative Power Quality Performance Evaluation of Grid-Connected Solar PV System

Channelized hotelling observer-based low-contrast detectability on the ACR CT accreditation phantom: Part II. Repeatability study.

Objective and quantitative evaluation for low-contrast detectability that correlates with human observer performance is lacking for routine CT quality control testing. Channelized Hotelling observer (CHO) is considered a strong candidate to fill the need but has long been deemed impractical to implement due to its requirement of a large number of repeated scans in order to provide accurate and precise estimates of index of detectability (d'). In our previous work, we optimized a CHO model observer on the American College of Radiology (ACR) CT accreditation phantom and achieved accurate measurement of d' with only 1-3 repeat scans. In this work, we aim to validate the repeatability of the proposed CHO-based low-contrast evaluation on four scanner models using the ACR CT accreditation phantom. The repeatability test was performed on four different scanners from two major CT manufacturers: Siemens Force and Alpha; Canon Prism and Prime SP. An ACR CT phantom was scanned 10 times, each time after repositioning of the phantom. For each repositioning, 3 repeated scans were acquired at 24, 12, and 6 mGy on all four scanner models. CHO was applied at the measured dose levels for different low-contrast object sizes (4-6mm). The CHO was also applied to images created using deep learning-based reconstructions on Canon Prism and to four different scan/reconstruction modes on the Siemens Alpha, a photon-counting-detector (PCD)-CT. The repeatability was evaluated by the probability that a measurement would fall within the±15% tolerance (P<15% ). With the CHO setting optimized for the ACR phantom and the use of 3 repeated scans and 9 non-overlapping slices per scan, the CHO measurement could provide high repeatability with P<15% of 98.8%-99.9% at 12 mGy with IR reconstruction on all four scanners. On scanner A, P<15% were 91.5%-99.9% at the three dose levels and for all three object sizes while the numbers were 93.6%-99.998% on scanner B. P<15% were 96.5%-97.2% for the two deep learning reconstructions and 97.0%-99.97% for the four scan/reconstruction modes on the PCD-CT. The CHO provided highly repeatable measurements with over 95% probability that a CHO measurement would lie within the±15% tolerance for most of the dose levels and object sizes on the ACR phantom. The repeatability was maintained when the CHO was applied to images created with a commercial deep learning-based reconstruction and various scan/reconstruction modes on a PCD-CT. This study demonstrates that practical implementation of CHO for routine quality control and performance evaluation is feasible.

Content Based Recommendation System on Netflix Data

After pandemic, OTT platforms are the most common platform to provide entertainment to users. Among all platforms, Netflix has become most the popular one. Data visualization of Netflix data can provide valuable insights and benefits in many ways like understanding viewer preferences, content optimization, personalized recommendation, quality and content performance evaluation, fraud detection to name a few. This research provides exploratory data visualization and provide a content based recommendation system on Netflix data as in real world applications, company uses these recommendation system algorithms to determine which system are better to improve users’ engagement of the platform.

Evaluation of Quality Performance and Social Effectiveness of Arts and Humanities Journals Indexed in the Web of Science Database

This study aimed to evaluate the qualitative and Altmetrics status of 147 journals indexed in the Arts and Humanities Citation Index (AHCI). This practical-analytical study used qualitative indicators of journals and quantitative Altmetrics. Data was collected from Web of Science, Journal Citation Reports, and Altmetrics Explorer. The results showed that most of the journals this database covers are from European countries, and only one is from Asian countries. More than half of the reviewed journals have a score lower than average regarding Journal Citation Indicator, Eigenfactor Score, and Article influence score. In addition, 63 % of journals cite articles published less than 19 years ago. Nearly 20 % of journals were not on social media. There is a significant relationship between Journal Citation Indicator indices with Citing Half-life, Article influence score with Eigenfactor Score, and between qualitative and Altmetrics indicators. Most of the reviewed journals showed low-quality performance. These journals needed high scientific impact to increase their credibility and quality and remain in the Web of Science database.

Bayesian and non-Bayesian analysis for the lifetime performance index based on generalized order statistics from Pareto distribution

&lt;p&gt;Modern businesses depend on efficient management and evaluation of product quality performance to assure that they are on the right track, and process capability analysis is used to gauge business performance in practice. Consequently, the lifetime performance index (LPI) , where is the lower specification limit, is used to gauge a process potential and performance. This paper examines distinct estimators of under Pareto distribution using generalized order statistics (GOS), which is very helpful in a variety of real-world applications. Results for progressive type II censoring (PTIIC) and first-failure censoring are two particular situations. Using symmetric and asymmetric loss functions, the Bayesian estimator was built, then utilized to produce the hypothesis testing technique. A simulation study and real data analysis have been investigated to study the behavior of different estimates for under different schemes, namely PTIIC and the progressive first failure censored scheme.&lt;/p&gt;

WQCrowd: Secure blockchain-based crowdsourcing framework with multi-tier worker quality evaluation

Crowdsourcing platforms play a crucial role in promoting transparency and collaborative engagement among participants while aiming to reduce resource consumption and costs. To achieve this, these platforms incorporate mechanisms for monitoring and evaluating worker quality performance. However, significant challenges persist. Centralized systems present trust issues due to their vulnerability to single-point failures. Moreover, data manipulation by malicious actors undermine confidence in the evaluation process, and biased assessments and reward distribution may lead to reduced worker motivation. Addressing these concerns necessitates the development of a decentralized system that ensures trustworthiness, tamper-resistance, accountability, reliability, transparency, and security. This paper introduces a secure multi-tier worker quality evaluation crowdsourcing framework based on blockchain technology. WQCrowd utilizes smart contracts and adopts a three-tier model comprising the Identity, Worker Activity, and Reputation tiers. Additionally, an automated game-based worker evaluation method is incorporated, enhancing the precision of performance assessments. Through our Proof of Concept (PoC) analysis, we demonstrate that the utilization of the blockchain system effectively addresses security concerns, including trust, privacy, and accountability, prevalent in current worker performance evaluation systems. Furthermore, the implementation of the game-based automated system enables our proposed solution to make informed decisions regarding worker quality performance evaluation.

Evaluation of growth performance and water quality of vannamei shrimp (Litopenaeus vannamei) in intensive cultivation systems

The success of shrimp cultivation is assessed based on the resulting performance, survival, growth, and total shrimp production. Apart from parent quality and feed quality, water quality is a determining factor in the success of shrimp cultivation. Good water quality will increase cultivation productivity. The research aims to measure the performance of vannamei shrimp using an intensive cultivation system at PT Bumi Cimandala Lestari by paying attention to the quality of cultivation waters. This research uses a descriptive method by following the entire series of cultivation production in the Bumi Cimandala Lestari shrimp pond. The activity lasts three months, from August to November 2022 at PT. Bumi Cimandala Lestari is located at Kp. Cipeundeuy, Surade Village, Sukabumi Regency. The results showed that the average survival rate from 8 cultivation ponds reached 67% with a growth rate of 0.26 g/day. The total production obtained was 55.42 tons with a size of 70-100 fish/kg. Water quality during the study was within the optimal range. The pH value of the water ranges from 7-9 with salinity ranging from 18.1 – 20.4 ppt. Dissolved oxygen value &gt; 5 mg/L, and alkalinity ranges from 122 – 183 mg/L. The research showed that cultivation ponds had a temperature range between 24.8-30.4 and DO ranging from 2.49-8.23 mg/L. Water quality conditions are thought to support the growth and survival of shrimp well

Review of Machine Learning Techniques for Power Quality Performance Evaluation in Grid-Connected Systems

In the current energy usage scenario, the demands on energy load and the tariffs on the usage of electricity are two main areas that require a lot of attention. Energy forecasting is an ideal solution that would help us to better understand future needs and formulate solutions accordingly. Some important factors to investigate are the quantity and quality of smart grids as they are significantly influenced by the transportation, storage, and load management of energy. This research work is a review of various machine learning algorithms for energy grid applications like energy consumption, production, energy management, design, vehicle-to-grid transfers, and demand response. Ranking is performed with the help of key parameters and is evaluated using the Rapid Miner tool. The proposed manuscript uses various machine learning techniques for the evaluation of power quality performance to validate an efficient algorithm ranking in a grid-connected system for energy management applications. The use of renewable energy resources in grid-connected systems is more common in modern power systems. Universally, the energy usage sector (commercial and non-commercial) is undergoing an increase in demand for energy utilization that has substantial economic and ecological consequences. To overcome these issues, an integrated, ecofriendly, and smart system that meets the high energy demands is implemented in various buildings and other grid-connected applications. Among various machine learning techniques, an evaluation of seven algorithms—Naïve Bayes, artificial neural networks, linear regression, support vector machine, Q-learning, Gaussian mixture model, and principle component analysis—was conducted to determine which algorithm is the most effective in predicting energy balance. Among these algorithms, the decision tree, linear regression, and neural networks had more accurate results than the other algorithms used. As a result of this research, a proposal for energy forecast, energy balance, and management was compiled. A comparative statement of various algorithms concludes with results which suit energy management applications with high accuracy and low error rates.

Performance evaluation of lettuce (Lactuca sativa L.) growth, yield and quality under subtropical climate

Lettuce (Lactuca sativa L.) belongs to the family Asteraceae and is known as a leafy salad vegetable. It is rich in vitamins like Vitamin A and C, and also a good source of minerals such as iron, sodium, calcium etc. It is more popular in temperate regions and also performing well under subtropical climatic conditions during the winter season. Therefore, the present investigation was carried out to identify the suitable variety of lettuce for higher yield and quality under subtropical climate. The experiment was conducted with five treatments replicated thrice. Seeds of these five lettuce varieties viz., Tango, Bingo, Summer Star, Grand Rapid and Black Rose were sown in portrays prefilled with a combination of media made of coco peat, vermiculite and perlite in the ratio 3:1:1. After thirty days plants were plugged out and transplanted under field condition to study the performance of lettuce varieties. Among the studied varieties, the maximum yield (191.44 q/ha) was recorded with the variety Summer Star which was at par (190.32 q/ha) with the Bingo variety, followed by (129.50 q/ha) in Tango and the least (85.51 q/ha) by Black Rose. However, vitamin C content and total carotenoid content were significantly found highest (15.98 mg/ 100 g) and 8.06 mg/ 100 g in the Black Rose variety, respectively. Tango variety observed maximum chlorophyll ‘a’ (5.85 mg/ g FW), ‘b’ (2.01 mg/ g FW) and total chlorophyll (7.85 mg/ g FW) content among studied lettuce varieties.

Retracted: “The influence of performance quality evaluation in general education schools on the recognition of the educational values”

Retracted: “The influence of performance quality evaluation in general education schools on the recognition of the educational values”

Quality assessments, performance, and emissions evaluation of biodiesel from citrullus lanatus oil seeds and diesel blends in compression ignition engine

AbstractDue to limited stock of levels of fossil fuel resources and ecological issues, biodiesel is becoming an attractive alternative choice for replacing conventional fuels. Biodiesel can be used by mixing with different fuels like citrullus lanatus seeds, camphor, cleaner fuel injector, sunflower, safflower, soybean, cottonseed, rapeseed, palm, Jatropha, and Moringa oil seeds.This paper reviews use of biofuels blended with citrullus lanatus seeds. The citrullus lanatus biodiesel was mixed with diesel in different percentages by volume. Some physico‐chemical characteristics of blends and pure diesel were investigated and it was established that it conforms to the American Society of Testing Materials (ASTM) standards. The exceptions were the viscosity and specific gravity of the pure biodiesel B100 which were 0.09 and 0.018 mm2/s above the ASTM standard, respectively. All blends were run on a stationary 4‐cylinder diesel engine at 70% loading and speeds of 1500, 2000, and 2500 rpm. It was deduced that B10 gave the best brake power, thermal efficiency, and optimum specific fuel consumption at a speed of 2500 rpm. B15 gave the highest brake mean effective pressure. B25 and B100 gave the least values of brake power and brake thermal efficiency across the speeds. B100 gave the highest brake specific fuel consumption. Furthermore, the exhaust emission gases such as CO2, CO, NOx, and HC in different engine conditions stated above were recorded and analyzed. It was found that B25 emitted about 53% lesser CO2 and 37% lesser CO as compared to pure diesel with zero HC at 2500 rpm. The blends were better in terms of engine performance and also in reduction of emissions in most cases, than pure diesel fuel.Problem statement: Various emissions from engines like unburnt hydro carbons, particulate emissions, NOx, and CO have bad effects on ecology. This work presents an overview on use of novel hybrid fuels in compression ignition engines with an aim of mitigating effects of emissions on environment. Biodiesel was blended with Citrullus lanatus oil and pure diesel in different proportions to see effects on performance of diesel engines. The presented work may pave the way for use of alternative cheap and environmentally friendly fuels in automotive systems.

Evaluation of Growth Performance, Carcass Composition and Meat Quality of Broiler Chickens Fed Rations Containing Guar Meal and Enzyme Preparations

The study aimed to determine the growth performance, carcass composition, and meat quality of broiler chickens fed rations with different levels of guar meal and feed enzymes. Two hundred and forty one-day-old, sexed chicks were assigned to six equinumerous groups (C4, C8, R4, R8, V4 and V8), with five subgroups each. The birds were fed ad libitum with Starter (1-21 days of life), Grower (22-35 days of life) and Finisher (36-42 days of life) comprised of maize meal, soybean meal, guar meal (4 or 8%), oil, and mineral and vitamin additives, in a two-factor pattern as follows: groups C4 4% guar meal without enzyme preparation, C8 8% guar meal without enzyme preparation, R4 4% guar meal + R enzyme preparation, R8 8% guar meal + R enzyme preparation, V4 4% guar meal + V enzyme preparation, V8 8% guar meal + V enzyme preparation. It was demonstrated that a higher (8%) percentage of guar meal in broiler chicken rations significantly contributed to body weight reduction (by 8%) and increased feed conversion ratio (by 3%). Simultaneously, it reduced the dressing percentage (by 2%) and carcass muscularity (by 3%). Feed rations supplemented with enzymes (R or V) did not improve growth performance and did not impact the dressing percentage, carcass muscularity and fatness. The use of 8% guar meal in broiler chicken feed decreased the crude ash content in the muscles, which, by contrast, increased due to enzyme supplementation. A higher level of guar meal reduced the content (by 4%) and fat quality measured as the ratio between n6:n3 PUFA and the index of AI, TI and HH. The results of the study imply that 4% guar meal inclusion in feed rations for broiler chickens not supplemented with enzymes should be recommended.

Using a BBWM-PROMETHEE model for evaluating mobile commerce service quality: A case study of food delivery platform

In the age of COVID-19, many governments imposed social distancing, work-from-home, and crowd control measures, which continue to affect economic development and forces service providers to be increasingly reliant on e-commerce and m-commerce platform technology. Moreover, due to the availability of 5G network speeds, cell phone applications and the Internet services have become indispensable for future smart lifestyles, prompting brick-and-mortar businesses to shift their sales models to mobile network operators (MNOs). To popularize the use of m-commerce, it is critical to ensure that service platforms operate well and give the customer what they want. It is thus essential to create a comprehensive and complete performance framework for the evaluation of m-commerce services. In this paper, a hybrid model is developed to explore this issue and the effectiveness and robustness of the model is illustrated by an application to two major food delivery platforms in Taiwan. The Bayesian Best Worst Method (BBWM) is applied to identify the criteria weights and ranks. The judgments of 14 experts are integrated to obtain the optimal group criteria weights. The performance data were obtained from a survey of 210 experienced users of these delivery platforms. The difference between the actual performance of each delivery platform and the aspiration level (AL) was calculated using the modified Preference Ranking Organization Method for Enrichment Evaluations (modified PROMETHEE) to determine an overall score for each delivery platform. A sensitivity analysis was also conducted and comparison made with other Multiple Criteria Decision-Making (MCDM) methods. The results show that information security and privacy, integrity, and mobile transaction service are the most important criteria, with Food Panda performing better than the other mobile food delivery service provider. The proposed evaluation framework is useful for performance evaluation of mobile commerce service quality, and providing effective suggestions to assist decision-makers in creating development strategies.

Quality Performance Evaluation of the Largest COVID-19-Designated Intensive Care Unit in the Western Region of Saudi Arabia.

Introduction Mortality is generally higher among patients with coronavirus disease 2019 (COVID-19) than non-COVID-19 patients, especially critically ill patients. The Acute Physiology and Chronic Health Evaluation IV (APACHE IV) predicts mortality rate (MR); however, it was not designed for COVID-19 patients. Multiple indicators have been utilized in healthcare to measure the performance of intensive care unit (ICU) departments, including length of stay (LOS) and MR. The 4C mortality score was recently developed using the ISARIC WHO clinical characterization protocol. This study aims to evaluate intensive care unit performance using LOS, MR, and 4C mortality scores at East Arafat Hospital (EAH), Makkah region, which is considered the largest COVID-19-designated intensive care unit in the Western region of Saudi Arabia. Materials and methods A retrospective observational cohort study was conducted on data from patients' records during the COVID-19 pandemic, from March 1, 2020, to October 31, 2021, at EAH, Makkah Health Affairs. Data to calculate LOS, MR, and 4C mortality scores were collected from the eligible patients' files by a trained team. Demographic (age and gender) and clinical data on admission were collected for statistical purposes. Results A total of 1298 patient records were included in the study; 417 (32%) of the patients were female and 872 (68%) were male. The cohort included 399 deaths (total MR=30.7%). Most deaths occurred in the 50-69-year age group, with significantly more deaths among female patients than male patients (p=0.004). A significant association was found between the 4C mortality score and death (p<0.000). Furthermore, the mortality odds ratio (OR) was significant (OR=1.3, 95% CI=1.178-1.447) for each added 4C score. Conclusion Our study metrics regarding LOS were generally higher than most internationally reported values and slightly lower than locally reported values. Our reported MR was comparable with overall published MRs. The ISARIC 4C mortality score was highly compatible with our reported MR between scores 4 and 14; however, the MR was higher for scores 0-3 and lower for scores ≤15. The overall performance of the ICU department was considered generally good. Our findings are helpful for benchmarking and motivating better outcomes.

AJUSTE DE MODELOS PARA PREDECIR EL RENDIMIENTO Y CARACTERÍSTICAS DE LA CANAL EN BASE A VARIABLES PRODUCTIVAS ANTEMORTEM DE OVINOS EN ENGORDA CON ALIMENTACIÓN INTENSIVA

&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Instrumental evaluation of carcass characteristics, meat quality and sheep performance, require specialized equipment, therefore it is necessary to have available technological and economic resources, which sometimes result expensive throughout the meat chain production value of sheep. Prediction of sheep carcass characteristics based on mathematical models, is a good, economic, confident and repeatable method. &lt;strong&gt;Objective: &lt;/strong&gt;To adjust, through two methods of estimation, prediction equations of &lt;em&gt;postmortem&lt;/em&gt; variables by means of &lt;em&gt;antemortem&lt;/em&gt; productive variables of intensive fattening sheep slaughtered in the valley of Toluca, Estado de México. &lt;strong&gt;Methodology:&lt;/strong&gt; A total of 175 records of fattening sheep, slaughtered in small slaughterhouse of barbecue cookers in Capulhuac Municipality of the Estado de México were used. There were used 8 &lt;em&gt;antemortem&lt;/em&gt; variables, in order to estimate prediction equations of 18 variables associated with performance, morphometry, muscular conformation, and grade of sheep carcass greasy. Carcasses were classified according with their similarity and grouped in principal components (PC), then were carried out multiple linear regression (MLR) analysis over original variables and factorial loads with extraction methods of principal components (PC). &lt;strong&gt;Results: &lt;/strong&gt;The adjusted equations with MLR, showed a &lt;em&gt;R&lt;/em&gt;&lt;sup&gt;2&lt;/sup&gt; ≥ 0.42 for HCW (hot carcass weight), CCW (cold carcass weight), LP (leg perimeter), RW (rump width), TD (thorax depth), and CI (compactness index). The assumptions of MLR were verified and the statistics Tol, VIF, DFBETAS and DFFITS demonstrated multicollinearity between variables. For the regression analysis, the principal components (RPC), were obtained three PC that explained 82.78% of the σ&lt;sup&gt;2 &lt;/sup&gt;(variance), and the adjustment of MLR over factorial loads obtained equations for HCW, CCW, PL, RW and CI with &lt;em&gt;R&lt;/em&gt;&lt;sup&gt;2&lt;/sup&gt; ≥ 0.37, up to 0.73. It should be noted the importance of the adjusted equation for CCW because of its relation with carcass price and its weight as a predictor variable of primary and commercial cuts. &lt;strong&gt;Implications&lt;/strong&gt;: It is useful and necessary that the adjustment of prediction equations for performance variables in animal science, can be accompanied with results of their respective tests of the model assumptions of multiple regression analysis. Our findings, confirm the need to carefully examine the adjustment of prediction equations with the aim of estimating equations with less bias and higher confidence. &lt;strong&gt;Conclusions: &lt;/strong&gt;The multiple regression analysis over original variables and vectors of principal components determined prediction equations with different grades of adjustment for performance variables (HCW, CCW, CI) and carcass quality (LP, RW, TD). In the adjusted equations over original variables, the betas with higher prediction power were for slaughter weight, initial live weight and final live weight. While for the adjustment of prediction equations with factorial loads of PC, the betas with higher power of prediction were for PC1 y PC2, characterized by having higher factorial loads. The values of multicollinearity and autocorrelation bias, determination coefficient and explained variance, showed that practical application of these prediction equations allowed to a real approximation to estimation of &lt;em&gt;postmortem&lt;/em&gt; variables; however, these values should be taken considering their reliability.&lt;strong&gt;&lt;/strong&gt;&lt;/p&gt;