Mixed Model Methodology Research Articles

Triamcinolone Acetonide in the Treatment of Perennial Allergic Rhinitis: A post hoc Efficacy Analysis of a Phase III Study Performed in Russia

Introduction: Allergic rhinitis (AR) is a disease which affects >24% of the population in Russia. Triamcinolone acetonide (TAA) is a corticosteroid used for treating AR. This post hoc analysis assesses the efficacy of intranasal TAA in improving perennial AR (PAR) symptom scores over 4 weeks. Methods: NASANIF (NCT03317015) was a double-blind, parallel-group, multicenter, prospective, non-inferiority, phase III clinical trial in which patients with PAR were randomized (1:1) to receive TAA or fluticasone propionate (FP) over 4 weeks. Our post hoc analysis evaluates weekly change in PAR symptoms using the reflective Total Nasal Symptom Score (rTNSS), overall and for individual symptoms (sneezing, nasal itching, rhinorrhoea, and nasal obstruction). Proportion of patients and time to achieve a ≥50 or ≥75% reduction in rTNSS were assessed. For rTNSS endpoints, a linear mixed-model methodology was used; for time-to-event endpoints, cumulative incidence functions were estimated using the Kaplan-Meier method, in the per-protocol population. Results: Of 260 patients, 128 each completed the study and were randomized to receive TAA or FP. From baseline to week 4, the changes in total rTNSS were −7.78 (95% CI: −8.1701 to −7.3967; p < 0.001) and −7.52 (−7.9053 to −7.1320; p < 0.001) for TAA and FP, respectively. Individual symptoms improved significantly from baseline. The proportion of patients achieving ≥50 and ≥75% reductions in total rTNSS was 88.0 and 67.2%, respectively in the TAA group. No significant differences were observed between the TAA and FP in any analyses. Conclusions: TAA produced effective and prolonged improvement of PAR symptoms over a 4-week treatment period.

Effect of dietary black cumin seed (Nigella sativa) on performance, immune status, and serum metabolites of small ruminants: A meta-analysis

A growing number of publications are identified toward the use of black cumin seeds (Nigella sativa L) on small ruminant animals since many beneficial evidences have been reported in humans and animals. This study used a meta-analysis approach to quantify the effect of black cumin seeds (BCS) supplementation on the productive performance, nutrients utilization, and blood metabolites profile of small ruminant animals. Following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) protocols, a total of 23 studies were aggregated in a database and were analyzed using mixed model methodology classifying the studies as random effects and levels of BCS as fixed effects in the models. Results found that interaction between BCS levels and animal species tended to be significant whereas increasing dietary BCS levels linearly increased average daily gain (ADG) (p < 0.01, R2 = 0.538) and dry matter intake in lambs (p < 0.01, R2 = 0.958) but had no effect on sheep. Nitrogen (N) intake, and N digested were found to be significantly increased (p < 0.01) as inclusion rates of BCS increased while organic matter (OM), crude protein (CP), and ether extract (EE) intakes tended to increased (p < 0.10). In addition to other immune responses, strong positive relationships were found on the increase of concentration of IgA (R2 = 0.922) and IgG (R2 = 0.939) (p < 0.05) in response to increasing BCS supplementation. To conclude, black cumin seeds can be used as a safe and beneficial feed supplement to promote the growth of small ruminant animals such as lambs, sheep, and goats.

Power and sample-size calculations for trials that compare slopes over time: Introducing the slopepower command.

Trials of interventions that aim to slow disease progression may analyze a continuous outcome by comparing its change over time-its slope-between the treated and the untreated group using a linear mixed model. To perform a sample-size calculation for such a trial, one must have estimates of the parameters that govern the between- and within-subject variability in the outcome, which are often unknown. The algebra needed for the sample-size calculation can also be complex for such trial designs. We have written a new user-friendly command, slopepower, that performs sample-size or power calculations for trials that compare slope outcomes. The package is based on linear mixed-model methodology, described for this setting by Frost, Kenward, and Fox (2008, Statistics in Medicine 27: 3717-3731). In the first stage of this approach, slopepower obtains estimates of mean slopes together with variances and covariances from a linear mixed model fit to previously collected user-supplied data. In the second stage, these estimates are combined with user input about the target effectiveness of the treatment and design of the future trial to give an estimate of either a sample size or a statistical power. In this article, we present the slopepower command, briefly explain the methodology behind it, and demonstrate how it can be used to help plan a trial and compare the sample sizes needed for different trial designs.

Does innovation capacity reduce tax evasion? Moderating effect of intellectual property rights

The purpose of this study is two-fold: (i) investigate the association between innovation capacity and tax evasion; (ii) examine the moderating effect of intellectual property rights (IPR) on innovation capacity and tax evasion. Thus, the study provides policy guidance to reduce tax evasion. We collected data for 139 countries from several sources and merged them for the common period (2006–2015). The analytical tool (i.e., the linear mixed model methodology) enabled us to examine the topic under time-varying analysis. The fundamental results show that innovation capacity and IPR may be two significant mechanisms in alleviating tax evasion. We also found that IPR is a significant moderator between innovation capacity and tax evasion. However, this moderating effect is not homogeneous for all levels of innovation capacity—the moderating effect reduces and increases tax evasion at lower and higher levels, respectively. The Granger causality test confirmed the bidirectional relationship between innovation capacity and tax evasion. The robustness of the results was further confirmed by constructing two sub-samples—developed and developing countries. Finally, implications are suggested for policymaking to alleviate tax evasion behavior.

An IBD-based mixed model approach for QTL mapping in multiparental populations

Key messageThe identity-by-descent (IBD)-based mixed model approach introduced in this study can detect quantitative trait loci (QTLs) referring to the parental origin and simultaneously account for multilevel relatedness of individuals within and across families. This unified approach is proved to be a powerful approach for all kinds of multiparental population (MPP) designs.Multiparental populations (MPPs) have become popular for quantitative trait loci (QTL) detection. Tools for QTL mapping in MPPs are mostly developed for specific MPPs and do not generalize well to other MPPs. We present an IBD-based mixed model approach for QTL mapping in all kinds of MPP designs, e.g., diallel, Nested Association Mapping (NAM), and Multiparental Advanced Generation Intercross (MAGIC) designs. The first step is to compute identity-by-descent (IBD) probabilities using a general Hidden Markov model framework, called reconstructing ancestry blocks bit by bit (RABBIT). Next, functions of IBD information are used as design matrices, or genetic predictors, in a mixed model approach to estimate variance components for multiallelic genetic effects associated with parents. Family-specific residual genetic effects are added, and a polygenic effect is structured by kinship relations between individuals. Case studies of simulated diallel, NAM, and MAGIC designs proved that the advanced IBD-based multi-QTL mixed model approach incorporating both kinship relations and family-specific residual variances (IBD.MQMkin_F) is robust across a variety of MPP designs and allele segregation patterns in comparison to a widely used benchmark association mapping method, and in most cases, outperformed or behaved at least as well as other tools developed for specific MPP designs in terms of mapping power and resolution. Successful analyses of real data cases confirmed the wide applicability of our IBD-based mixed model methodology.

Accuracy of three-dimensional soft tissue profile prediction in orthognathic surgery.

To evaluate the accuracy of three-dimensional (3D) soft tissue prediction in bimaxillary orthognathic surgery. Cone-beam computed tomographs of 88 patients with class II (n = 46) and class III (n = 42) malocclusions, who underwent bimaxillary orthognathic surgery, were included in this retrospective study. 3D soft tissue prediction and postoperative outcome were compared by using ten landmarks of facial soft tissues. Patients' sex and age were also assessed. Results were analyzed using a mixed model methodology (p < 0.05). The success criterion adopted was a mean discrepancy of < 2mm. Most mandibular landmarks indicated a tendency for underprediction with a downward direction in class II patients, with some values > 2mm. In class III, there was overprediction with a downward direction for the mandibular landmarks, with values < 2mm. More accurate results were found in female and older patients. 3D surgical planning showed clinically acceptable results for predicting soft tissues in patients undergoing bimaxillary orthognathic surgery, with more accurate results for class III patients. Although some differences were found when age and sex were interacted, a consistent association between these variables could not be stated. These results support the clinician, as accuracy can provide a strong guide to the surgeon when planning surgical orthodontic treatment.

Genetic divergence for adaptability and stability in sugarcane: Proposal for a more accurate evaluation.

The best agro-industrial performance presented by a crop genotype in one environment may not be reproduced in another owing to complex edaphoclimatic variations. Therefore, breeding programs are constantly attempting to obtain, through artificial hybridization, novel genotypes with high adaptability and stability potential. The objective of this study was to analyze genetic divergence in sugarcane based on the genotypic values of adaptability and stability. A total of 11 sugarcane genotypes were analyzed for eight agro-industrial traits. The genotypic values of the traits were determined using mixed model methodology, and the genetic divergence based on phenotypic and genotypic values was measured using the Mahalanobis distance. The distance matrices were correlated using the Mantel test, and the genotypes were grouped using the Tocher method. Genetic divergence is more accurate when based on genotypic values free of genotype–environment interactions and will differ from genetic divergence based on phenotypic data, changing the genotype allocations in the groups. The above methodology can be applied to assess genetic divergence to obtain novel sugarcane genotypes with higher productivity that are adapted to intensive agricultural systems using diverse technologies. This methodology can also be tested in other crops to increase accuracy in selecting the parents to be crossed.

Effects of saponin on enteric methane emission and nutrient digestibility of ruminants: An in vivo meta-analysis

Although saponin originated from plants has been used to control methanogenesis performed by archaea methanogens in the rumen, its effect has been inconsistent. The objective of this study was to evaluate the effect of dietary saponin on enteric methane emission and nutrient digestibility of ruminants across various studies by employing a meta-analysis method. A database was developed by integrating data from 17 studies that originated from 11 articles. Different ruminant species, i.e., both small and large ruminants were included in the database. Data on related in vitro studies were excluded. Papers should be based on in vivo studies only that simultaneously reported dietary saponin and methane emission. Treatments were divided into control (no saponin), low saponin (saponin level less than 0.5% DM) and high saponin (saponin level above 0.5% DM). The treatments were considered as fixed effects whereas various studies were considered as random effects in the statistical mixed model methodology. Results showed that dietary saponin decreased enteric methane emission of ruminants as compared to control (P<0.05), and this was true for both low and high levels of saponin. Interestingly, low level of dietary saponin increased dry matter digestibility, organic matter digestibility, neutral detergent fiber digestibility and acid detergent fiber digestibility in comparison to control (P<0.05). However, saponin at high administration level reduced these nutrient digestibility than that of control (P<0.05). In conclusion, saponin is effective to mitigate enteric methane emission from ruminants in vivo and enhances nutrient digestibility provided that the level use should not exceed 0.5% DM.

Urea treatment of rice straw: A modelling approach of its degradation kinetics in the rumen

This study aimed to compare between rice straw and urea-treated rice straw with regard to their chemical composition and degradation kinetics in the rumen by employing a modelling approach. Data were collected from various journal articles that comprised of chemical composition (crude protein [CP], neutral detergent fiber [NDF], acid detergent fiber [ADF] and lignin) and degradation kinetic parameters of organic matter (soluble fraction, degradable, undegradable, degradation rate and lag time). Comparison was performed by using a statistical mixed model methodology in which treatments (control vs urea-treated rice traw) were considered as fixed effects whereas different studies were considered as random effects. These data were then used as parameters to build a dynamic model of rice straw degradation in the rumen. Results showed that urea treatment increased CP (P<0.001) while decreased NDF (P<0.01) contents of rice straw. The ADF and lignin contents were similar between the control and urea-treated rice straw. Proportion of degradable fraction and degradation rate of rice straw were enhanced due to urea treatment (P<0.001). However, the treatment did not influence soluble fraction and lag time of the material. Microbial biomass and total volatile fatty acid production in the rumen changed dynamically over time and the values were higher for the urea-treated rice straw.

Optimal harvest number and genotypic evaluation of total dry biomass, stability, and adaptability of elephant grass clones for bioenergy purposes

For elephant grass breeding for bioenergy purposes, selection should be based on repeated harvests to maximize the selection efficiency. Selecting genotypes with high total dry biomass, associated with high adaptability and stability, is extremely important. Thus, the objective of this study was to estimate the minimum number of harvests required for total dry biomass to enable an accurate selection of elephant grass clones in multiple environmental trials. Additionally, the relative performance of genetic values (HMRPGV) and centroid methods were used to cluster and rank the best clones on the basis of their total dry biomass, adaptability, and stability. Nineteen clones and two checks were evaluated in six environments. Two or four harvests were performed in each environment. A mixed model methodology (REML/BLUP) was used to estimate the variance components and predict the genotypic values. The repeatability coefficient for total dry biomass was 0.20. The accuracies of performing two and four harvests were 59% and 72%, respectively. The increase in selection efficiency by performing two, four, and seven harvests instead of just one was 29%, 57%, and 76%, respectively. Finally, the clones were clustered into four classes according to their total dry biomass, adaptability, and stability. We conclude that at least seven harvests are required to achieve an accuracy of 80%, and that the HMRPGV and centroid methods are practical, visual, and reliable for simultaneously clustering, ranking, and selection of clones based on their adaptability, stability, and total dry biomass production.

Backcross Aiming at the Resistance of Passion Fruit to Soil Pathogen

Brazil is the world&amp;#39;s largest producer of passion fruit, however, the crop suffers from serious phytosanitary problems, as well as those caused by soil fungi. Thus, the objective of the present work was to estimate the genetic parameters and to select genotypes resistant to Fusarium solani species complex&amp;mdash;FSSC in a segregating population from the first generation of backcross among P. edulis and interspecific hybrids, aiming at advancing generation in the genetic improvement program of passion fruit. The Interspecific Hybrid was used (IH) UNEMAT 142 resistant to colon rot, for generation advancement and to cultivate BRS Sol do Cerrado (Passiflora edulis Sims). In order to evaluate the resistance of the 27 genotypes of the first generation of backcrosses, inoculation with the FSUNEMAT 40 (F. solani) inoculum was performed. To estimate the components of variances, the method of maximum restricted likelihood (REML) was used and to select the best genotypes by the non-addicted linear prediction (BLUP). The variables that showed the highest heritability values were the survival period and the area under the lesion length expansion curve. The three families of backcrosses presented genotypes resistant to the fungus F. solani, however, by the methodology of mixed models REML/BLUP, only the genotypes BC1-22/1, BC1-22/2, BC1-22/3, BC1-22/4, BC1-22/6, BC1-22/7, BC1-113/3, BC1-113/7 and BC1-113/8, were selected to advance the generation of the UNEMAT passion fruit breeding program, therefore, they presented among the ten placed, mainly for the variable survival period (SP).

Prospecting on Passiflora backcross families: implications for breeding aiming at CABMV resistance

Passion fruit woodiness disease induced by Cowpea aphid-borne mosaic virus (CABMV) is currently the most harmful viral disease affecting passion fruit crops. Given the economic importance of this fruit crop in Brazil, it is essential that passion fruit breeding programs invest in developing resistant and productive cultivars. The goals of this study were to estimate genetic parameters of agronomic and resistance traits via restricted maximum likelihood (REML) and select individuals found to be resistant to CABMV and agronomically superior, in order to provide the basis for further studies on passion fruit breeding, with the aim to develop cultivars resistant to CABMV. The study was conducted in randomized block design, with four replicates. Three full-sib families from the recombination of RC1 parents were evaluated. Based on the severity data, the area below the mean disease progress curve (AUDPCM) was estimated. Five traits relating to fruit yield and quality were also assessed. The components of variance and genetic values were estimated by the REML/best linear unbiased prediction (BLUP) mixed model methodology. A difference in the severity of CABMV symptoms was recorded among the 119 genotypes evaluated. AUDPCM values varied from 750 to 1252.5 for individuals 202 and 161, respectively. Family 1 distinguished itself with the largest number of individuals selected for resistance; for agronomic traits, families 1 and 2 contributed most of the selected genotypes. Genotypes 167, 24, 34, 23 and 202 achieved the lowest AUDPCM values, being selected for most of the agronomic traits; these results indicate the potential of these genotypes to be chosen and recombined for the advancement of generations in breeding programs aimed at developing resistance to CABMV. The strategy of recombining resistant genotypes from RC1 populations appears to be promising for breeding for resistance to CABMV, of which the heritability is complex.

Chitosan as a feed additive: Its modulatory effect on methane emission and biohydrogenation under artificial rumen system

This study aimed to determine the effects of chitosan addition on methane emission, fatty acid biohydrogenation and fermentation profile of rumen simulation technique (rusitec). Four studies reported chitosan use as a feed additive in the rusitec system were integrated into a database. Treatments were categorized into control (no chitosan addition) and chitosan addition at different levels. Various studies were treated as random effects whereas treatments were considered as fixed effects. Data were analyzed by using mixed model methodology. Significance was declared when P<0.05 and tendency was stated when P<0.1. Results showed that chitosan addition reduced methane emission in comparison to control by as much as 28% (P<0.05). Total volatile fatty acid concentration was not altered due to chitosan, but acetate proportion was decreased (P<0.05) while propionate proportion tended to elevate in the addition of chitosan (P<0.1). Chitosan did not influence ruminal pH, ammonia concentration and nutrient digestibility (organic matter, crude protein and neutral detergent fiber) of substrate. Proportions of vaccenic acid (P<0.01) and conjugated linoleic acid (P<0.001) were increased by the addition of chitosan. In conclusion, chitosan may provide beneficial effects in the rumen by mitigating methane emission and elevating fatty acids contributing to human health.

Accounting for competition in multi-environment tree genetic evaluations: a case study with hybrid pines

Key message A novel multi-environment competition individual-tree mixed model resulted in better fit, and greater individual narrow- and broad-sense heritabilities than the model without competition, notably for traits showing competition. In multi-environment tests, the proposed model would allow tree breeders to select genotypes with the best performance in both additive direct and competition breeding values, increasing forest productivity. ContextGenetic merit of trees is known to be affected and interact with local competition effects as well as changes across environmental conditions. Recent studies showed that competition genetic effects can affect the genetic variance and bias the tree breeding values, and its covariance with direct breeding values has been variable across traits.AimsThe present paper extends a mixed-model methodology to the problem of accounting for competition in a multi-environment set of forest genetic trials and exploring its impact on genetic variances as well as the multi-environment genetic correlation.MethodsThe proposed model is illustrated using data from two full-sib trials of Pinus elliottii var. elliottii × Pinus caribaea var. hondurensis F1. Dispersion parameters and (co)variance of total breeding values were estimated for diameter at breast height, total tree height, and stem straightness at age 10.ResultsFor traits showing competition effects (diameter at breast height and total tree height), the proposed multi-environment competition model gave better fit than the simpler model. Accounting for competition increased the direct additive variance, reduced the residual variances, and did not change significantly the across-site additive genetic correlation. However, for diameter at breast height, top 5% best genetic rankings showed differences.ConclusionWhen traits are strongly affected by inter-tree competition, the use of the proposed model in multi-environment analyses can efficiently identify the phenomenon with general benefits in the fitting of genetic components and open the door to select on the basis of competitiveness.

Genetic parameters of breech strike, neck wrinkles, dags and breech cover over the lifetime of crutched Merino ewes in a Mediterranean environment

Aims This study was undertaken to estimate the genetic parameters of breech strike and its indicator traits over the lifetime of crutched Merino ewes in a Mediterranean environment. Methods Breech strike records were collected on 3993 ewes over their lifetime where they were annually crutched. The ewes were scored at different times of the year for neck wrinkle, dag score and breech cover over their lifetime. A total of 13 577 breech strike records from birth up to 5 years of age were generated between 2006 and 2017. Face cover was only scored mid-year. Mixed model methodologies were used to estimate the genetic parameters of the different traits at different ages. Key results Breech strike was heritable (h2) and repeatable (t) on the observed scale (h2 = 0.07 ± 0.01; t = 0.13 ± 0.01), and as a binary trait on a logistic scale (h2 = 0.51 ± 0.10; t = 0.68 ± 0.10). Breech strike was genetically positively correlated across ages. Positive genetic correlations were found between breech strike and the indicator traits of neck wrinkle, face cover, breech cover and dags. Neck wrinkle and face cover, as well as breech cover and dag scored at different times of the year, were heritable and repeatable. Although high genetic correlations were found between different ages for neck wrinkle and post-shearing breech cover, these traits are not genetically the same traits at different ages. However, breech cover scored mid-year, before shearing and after shearing are genetically the same trait. The genetic relationship between dag at different ages is unclear as a moderate positive genetic correlation (rg = 0.25 ± 0.12) was found between hoggets and 2-year-old ewes, whereas a moderate negative correlation (rg = –0.30 ± 0.14) was found between 3- and 4-year-old ewes. The genetic correlations amongst the dag traits in older age groups were not significantly different from zero. Conclusions Breech strike and its indicator traits (i.e. neck wrinkle, breech cover, face cover and dags) were all heritable. Breech strike appears to be genetically strongly correlated across ages, however, the correlations had large standard errors. It was positively correlated with the indicator traits. Moderate to strong genetic correlations were found between ages for neck wrinkle and for breech cover. Dags, however, were poorly correlated across ages, indicating that dags are not genetically the same trait in mature ewes at different ages. Implications This study shows that selecting ewes for low breech strike, and for reduced neck wrinkle, lower breech cover and less dags will reduce breech strike in mature Merino ewes in future generations. However, as the phenotypic correlations were relatively low, culling ewes on these indicator traits will result in little gain in the current generation. It appears that dags at different ages is not genetically the same trait. Thus the benefit of selecting or culling ewes on dags will not be carried over to subsequent ages.

Clonal selection in S0 and S1 peach trees evaluated in a subtropical environment

Abstract The aims of this study were to estimate genetic parameters, predict genotypic values, and analyze the genotypic divergence in S0 and S1 peach trees evaluated in a subtropical environment by the mixed model methodology. For this, twenty-two clones were evaluated for plant and fruit traits. Genotypic variance among clones was significant. The individual broad-sense heritabilities ranged from 0.11 to 0.84, and the individual repeatability coefficients ranged from 0.15 to 0.89. The genotypic coefficients of variation were higher than 10% for most of the traits. Clustering based on plant and fruit traits led to the formation of two and five mutually exclusive groups, respectively. Multivariate analysis of principal components indicated that some traits could be excluded from genetic evaluation. Considering the yield trait and the selection of five clones, predicted gain from selection was 70%, which shows the possibility of considerable genetic progress from clonal selection in peach trees.

Cupuaçu tree genotype selection for an agroforestry system environment in the Amazon

Abstract: The objective of this work was to select cupuaçu (Theobroma grandiflorum) tree progenies and individuals based on their agronomic traits, and, indirectly, to identify those adapted to an agroforestry system (AFS) environment in the Brazilian Amazon. For this purpose, 25 full-sib progenies were planted and tested in consortium with black pepper (Piper nigrum), banana (Musa spp.), and bacuri (Platonia insignis) trees. The experiment was carried out in a randomized complete block design, with five replicates and three plants per plot, from 2005 to 2019. For the statistical analyses, the phenotypic averages for production and incidence of witches’ broom disease, evaluated during 11 harvests, were used. Superior progenies and individuals were identified using the mixed model methodology (REML/BLUP), which led to the selection of ten plants from five families with superior agronomic traits. Cupuaçu tree progenies 6, 36, 37, 49, and 52 are the ones that best adapt to the environment of a multispecies AFS in the Amazon region because of their agronomic traits under competitive conditions. Ten matrices show agronomic potential and indirect adaptation to the AFS and can be used as clonal cupuaçu cultivars in this environment.

Soybean productivity, stability, and adaptability through mixed model methodology

ABSTRACT: The genotype × environment (G×E) interaction plays an essential role in phenotypic expression and can lead to difficulties in genetic selection. Thus, the present study aimed to estimate genetic parameters and to compare different selection strategies in the context of mixed models for soybean breeding. For this, data referring to the evaluation of 30 genotypes in 10 environments, regarding the grain yield trait, were used. The variance components were estimated through restricted maximum likelihood (REML) and genotypic values were predicted through best linear unbiased prediction (BLUP). Significant effects of genotypes and G×E interaction were detected by the likelihood ratio test (LRT). Low genotypic correlation was obtained across environments, indicating complex G×E interaction. The selective accuracy was very high, indicating high reliability. Our results showed that the most productive soybean genotypes have high adaptability and stability.

Genotypic superiority of Psidium Guajava S1 families using mixed modeling for truncated and simultaneous selection

The purpose of this study was to conduct selection, genetic parameter estimation, and prediction of genetic values for 18 S1 families of guava trees using mixed model methodology and simultaneous selection of traits by means of the additive selection index, multiplicative selection index, and mean rank adapted from Mulamba. All families analyzed were obtained by means of self-fertilization of superior genotypes (full siblings) from the genetic breeding program of guava trees at the Universidade Estadual do Norte Fluminense. An experimental randomized block design with 18 S1 families, three replicates, and ten plants per plot was used. A total of 540 genotypes (individual plants) of guava tree were evaluated. Genetic parameter estimation and selection of the best genotypes based on the genetic value were performed using the statistical procedure, from the Selegen-REML/BLUP program. The analyses of the additive selection index, multiplicative selection index, and the sum of rank adapted from Mulamba were also performed under the Selegen program. During the evaluation by the individual BLUPs, families 1, 12, 4, 6, and 8 contributed to most of the genotypes selected for the traits under evaluation, suggesting their significant potential to generate high quality and high yield genotypes. In the selection indexes via mixed models, the multiplicative index showed higher values for genetic gains (74 %), followed by the mean rank index adapted from Mulamba (19 %), and the additive index (2 %).

Essential oils as growth-promoting additives on performance, nutrient digestibility, cecal microbes, and serum metabolites of broiler chickens: a meta-analysis.

ObjectiveThe purpose of this meta-analysis was to evaluate the effect of dietary essential oils (EOs) on productive performance, nutrient digestibility, and serum metabolite profiles of broiler chickens and to compare their effectiveness as growth-promoting additives against antibiotics.MethodsPeer-reviewed articles were retrieved from Web of Science, Science Direct, PubMed, and Google scholar and selected based on pre-determined criteria. A total of 41 articles containing 55 experiments with 163 treatment units were eligible for analyses. Data were subjected to a meta-analysis based on mixed model methodology considering the doses of EOs as fixed effects and the different studies as random effects.ResultsResults showed a linear increase (p<0.001) on body weight gain (BWG) where Antibiotics (FCR) and average daily feed intake decreased (p<0.001) linearly with an increasing dose of EOs. Positive effects were observed on the increased (p<0.01) digestibility of dry matter, crude protein, ether extract, and cecal Lactobacillus while Escherichia coli (E. coli) population in the cecum decreased (p<0.001) linearly. There was a quadratic effect on the weight of gizzard (p<0.01), spleen (p<0.05), bursa of fabricius (p<0.001), and liver (p< 0.10) while carcass, abdominal fat, and pancreas increased (p<0.01) linearly. The dose of EOs linearly increased high density lipoprotein, glucose, protein, and globulin concentrations (p<0.01). In comparison to control and antibiotics, all type of EOs significantly reduced (p<0.001) FCR and tended to increase (p<0.1) BWG and final body weight. Cinnamaldehyde-compound was the only EOs type showing a tendency to increase (p<0.1) carcass weight, albumin, and protein of serum metabolites while this EOs together with EOs-Blend 1 decreased (p<0.01) E. coli population. Low density lipoprotein concentration decreased (p<0.05) with antibiotics and carvacrol-based compound when compared to the control group.ConclusionThis evidence confirms that EOs are suitable to be used as growth promoters and their economical benefit appears to be promising.