Genome-enabled prediction through quantile random forest for complex traits / Predição genômica por meio do random forest quantílitico para características complexas

ABSTRACT: Quantile Random Forest (QRF) is a non-parametric methodology that combines the advantages of Random Forest (RF) and Quantile Regression (QR). Specifically, this approach can explore non-linear functions, determining the probability distribution of a response variable and extracting information from different quantiles instead of just predicting the mean. This evaluated the performance of the QRF in the genomic prediction for complex traits (epistasis and dominance). In addition, compare the accuracies obtained with those derived from the G-BLUP. The simulation created an F2 population with 1,000 individuals and genotyped for 4,010 SNP markers. Besides, twelve traits were simulated from a model considering additive and non-additive effects, QTL (Quantitative trait loci) numbers ranging from eight to 120, and heritability of 0.3, 0.5, or 0.8. For training and validation, the 5-fold cross-validation approach was used. For each fold, the accuracies of all the proposed models were calculated: QRF in five different quantiles and three G-BLUP models (additive effect, additive and epistatic effects, additive and dominant effects). Finally, the predictive performance of these methodologies was compared. In all scenarios, the QRF accuracies were equal to or greater than the methodologies evaluated and proved to be an alternative tool to predict genetic values in complex traits.

RESUMO: Quantile Random Forest (QRF) é uma metodologia não paramétrica, que combina as vantagens do Random Forest (RF) e da Regressão Quantílica (QR). Especificamente, essa abordagem pode explorar funções não lineares, determinando a distribuição de probabilidade de uma variável resposta e extraindo informações de diferentes quantis em vez de apenas prever a média. O objetivo deste trabalho foi avaliar o desempenho do QRF em predizer o valor genético genômico para características com arquitetura genética não aditiva (epistasia e dominância). Adicionalmente, as acurácias obtidas foram comparadas com aquelas advindas do G-BLUP. A simulação criou uma população F2 com 1.000 indivíduos genotipados para 4.010 marcadores SNP. Além disso, doze características foram simuladas a partir de um modelo considerando efeitos aditivos e não aditivos, com número de QTL (Quantitative trait loci) variando de oito a 120 e herdabilidade de 0,3, 0,5 ou 0,8. Para treinamento e validação foi usada a abordagem da validação cruzada 5-fold. Para cada um dos folds foram calculadas as acurácias de todos os modelos propostos: QRF em cinco quantis diferentes e três modelos do G-BLUP (com efeito aditivo, aditivo e epistático, aditivo e dominante). Por fim, o desempenho preditivo dessas metodologias foi comparado. Em todos os cenários, as acurácias do QRF foram iguais ou superiores às metodologias avaliadas e mostrou ser uma ferramenta alternativa para predizer valores genéticos em características complexas.

Genome-enabled prediction through quantile random forest for complex traits / Predição genômica por meio do random forest quantílitico para características complexas

Quantile Random Forest (QRF) is a non-parametric methodology that combines the advantages of Random Forest (RF) and Quantile Regression (QR). Specifically, this approach can explore non-linear functions, determining the probability distribution of a response variable and extracting information from different quantiles instead of just predicting the mean. This evaluated the performance of the QRF in the genomic prediction for complex traits (epistasis and dominance). In addition, compare the accuracies obtained with those derived from the G-BLUP. The simulation created an F2 population with 1,000 individuals and genotyped for 4,010 SNP markers. Besides, twelve traits were simulated from a model considering additive and non-additive effects, QTL (Quantitative trait loci) numbers ranging from eight to 120, and heritability of 0.3, 0.5, or 0.8. For training and validation, the 5-fold cross-validation approach was used. For each fold, the accuracies of all the proposed models were calculated: QRF in five different quantiles and three G-BLUP models (additive effect, additive and epistatic effects, additive and dominant effects). Finally, the predictive performance of these methodologies was compared. In all scenarios, the QRF accuracies were equal to or greater than the methodologies evaluated and proved to be an alternative tool to predict genetic values in complex traits.

Quantile Random Forest (QRF) é uma metodologia não paramétrica, que combina as vantagens do Random Forest (RF) e da Regressão Quantílica (QR). Especificamente, essa abordagem pode explorar funções não lineares, determinando a distribuição de probabilidade de uma variável resposta e extraindo informações de diferentes quantis em vez de apenas prever a média. O objetivo deste trabalho foi avaliar o desempenho do QRF em predizer o valor genético genômico para características com arquitetura genética não aditiva (epistasia e dominância). Adicionalmente, as acurácias obtidas foram comparadas com aquelas advindas do G-BLUP. A simulação criou uma população F2 com 1.000 indivíduos genotipados para 4.010 marcadores SNP. Além disso, doze características foram simuladas a partir de um modelo considerando efeitos aditivos e não aditivos, com número de QTL (Quantitative trait loci) variando de oito a 120 e herdabilidade de 0,3, 0,5 ou 0,8. Para treinamento e validação foi usada a abordagem da validação cruzada 5-fold. Para cada um dos folds foram calculadas as acurácias de todos os modelos propostos: QRF em cinco quantis diferentes e três modelos do G-BLUP (com efeito aditivo, aditivo e epistático, aditivo e dominante). Por fim, o desempenho preditivo dessas metodologias foi comparado. Em todos os cenários, as acurácias do QRF foram iguais ou superiores às metodologias avaliadas e mostrou ser uma ferramenta alternativa para predizer valores genéticos em características complexas.

Efficacy of fine needle aspiration in the diagnosis of spontaneous mammary tumors / Eficácia da citologia aspirativa no diagnóstico de tumores mamários espôntaneos / La eficacia de la aspiración con aguja fina en el diagnóstico de tumores mamarios espontáneos

The cytopathology exam has been utilized to diagnose mammary disorders in female dogs. The success of cytopathology results depends on, among other factors, the diagnostic accuracy of the exam. The present study aimed to compare the cytopathological and histopathological findings from mammary disorder cases in female dogs and evaluate the lesion cytopathology exam accuracy. The concordance degree was evaluated between the cytopathology and histopathology exams of 67 female dogs, carriers of palpable breast lumps, cared for at the university hospital from which the following indicators were calculated: sensitivity, specificity, positive predictive value, negative predictive value, false positives, false negatives, and exam accuracy. The sensitivity was 95.23%, the specificity 75%, positive predictive value 98.36%, negative predictive value 60%, and accuracy 94.02%. There were 2 false negatives and 1 false positive. In conclusion the cytopathology exam can be amply utilized as a means of diagnosis with high accuracy and sensitivity in the first examination of female dogs with mammary tumors.(AU)

O exame citológico tem sido utilizado no diagnóstico das afecções mamárias das cadelas. O êxito no resultado da citologia dependerá, além de outros fatores, da acurácia diagnóstica deste exame. O objetivo deste estudo foi comparar os achados citológicos e histológicos das afecções mamárias de cadelas e avaliar a acurácia do exame citológico nestas lesões. Avaliou-se o grau de concordância entre os exames citológico e histológico de 67 cadelas, portadoras de nódulo mamário palpável, atendidas em um hospital universitário e foram calculados os indicadores: sensibilidade, especificidade, valor preditivo positivo, valor preditivo negativo, falso positivo, falso negativo e acurácia do exame. A sensibilidade foi de 95,23%, a especificidade de 75%, o valor preditivo positivo de 98,36%, o valor preditivo negativo de 60% e a acurácia de 94,02%. Ocorreu 1 resultado falso positivo e 2 falso negativos. Conclui-se que o exame citológico pode ser amplamente utilizado como meio de diagnóstico com elevada acurácia e sensibilidade no atendimento primário das cadelas com tumor de mama.(AU)

El examen citológico se ha usado en el diagnóstico de cáncer de mama en perras. El éxito de la citología depende, entre otros factores, la precisión diagnóstica de este examen. El objetivo de este estudio fue comparar los resultados de citología y examen histológico de las enfermedades de mama en las perras y evaluar la exactitud de la citología de estas lesiones. Se evaluó el grado de acuerdo entre los exámenes citológicos e histológicos de 67 perros, que sufren de bulto palpable en la mama atendidos en un hospital universitario y se calcularon los indicadores: sensibilidad, especificidad, valor predictivo positivo, valor predictivo negativo, falsos positivos, falsos negativo y exactitud de la prueba. La sensibilidad fue del 95,23%, especificidad 75%, valor predictivo positivo del 98,36%, valor predictivo negativo del 60% y el 94,02% de precisión. Hubo un resultado positivo falso y dos falsos negativos. Se concluye que el examen citológico puede ser ampliamente utilizado como una herramienta de diagnóstico de alta precisión y sensibilidad en la atención primaria de perros con cáncer de mama. (AU)

Methodology to filter out outliers in high spatial density data to improve maps reliability

The considerable volume of data generated by sensors in the field presents systematic errors; thus, it is extremely important to exclude these errors to ensure mapping quality. The objective of this research was to develop and test a methodology to identify and exclude outliers in high-density spatial data sets, determine whether the developed filter process could help decrease the nugget effect and improve the spatial variability characterization of high sampling data. We created a filter composed of a global, anisotropic, and an anisotropic local analysis of data, which considered the respective neighborhood values. For that purpose, we used the median to classify a given spatial point into the data set as the main statistical parameter and took into account its neighbors within a radius. The filter was tested using raw data sets of corn yield, soil electrical conductivity (ECa), and the sensor vegetation index (SVI) in sugarcane. The results showed an improvement in accuracy of spatial variability within the data sets. The methodology reduced RMSE by 85 %, 97 %, and 79 % in corn yield, soil ECa, and SVI respectively, compared to interpolation errors of raw data sets. The filter excluded the local outliers, which considerably reduced the nugget effects, reducing estimation error of the interpolated data. The methodology proposed in this work had a better performance in removing outlier data when compared to two other methodologies from the literature.

Methodology to filter out outliers in high spatial density data to improve maps reliability

The considerable volume of data generated by sensors in the field presents systematic errors; thus, it is extremely important to exclude these errors to ensure mapping quality. The objective of this research was to develop and test a methodology to identify and exclude outliers in high-density spatial data sets, determine whether the developed filter process could help decrease the nugget effect and improve the spatial variability characterization of high sampling data. We created a filter composed of a global, anisotropic, and an anisotropic local analysis of data, which considered the respective neighborhood values. For that purpose, we used the median to classify a given spatial point into the data set as the main statistical parameter and took into account its neighbors within a radius. The filter was tested using raw data sets of corn yield, soil electrical conductivity (ECa), and the sensor vegetation index (SVI) in sugarcane. The results showed an improvement in accuracy of spatial variability within the data sets. The methodology reduced RMSE by 85 %, 97 %, and 79 % in corn yield, soil ECa, and SVI respectively, compared to interpolation errors of raw data sets. The filter excluded the local outliers, which considerably reduced the nugget effects, reducing estimation error of the interpolated data. The methodology proposed in this work had a better performance in removing outlier data when compared to two other methodologies from the literature.(AU)

Methodology to filter out outliers in high spatial density data to improve maps reliability

ABSTRACT The considerable volume of data generated by sensors in the field presents systematic errors; thus, it is extremely important to exclude these errors to ensure mapping quality. The objective of this research was to develop and test a methodology to identify and exclude outliers in high-density spatial data sets, determine whether the developed filter process could help decrease the nugget effect and improve the spatial variability characterization of high sampling data. We created a filter composed of a global, anisotropic, and an anisotropic local analysis of data, which considered the respective neighborhood values. For that purpose, we used the median to classify a given spatial point into the data set as the main statistical parameter and took into account its neighbors within a radius. The filter was tested using raw data sets of corn yield, soil electrical conductivity (ECa), and the sensor vegetation index (SVI) in sugarcane. The results showed an improvement in accuracy of spatial variability within the data sets. The methodology reduced RMSE by 85 %, 97 %, and 79 % in corn yield, soil ECa, and SVI respectively, compared to interpolation errors of raw data sets. The filter excluded the local outliers, which considerably reduced the nugget effects, reducing estimation error of the interpolated data. The methodology proposed in this work had a better performance in removing outlier data when compared to two other methodologies from the literature.

A statistical approach to static and dynamic tests for Global Navigation Satellite Systems receivers used in agricultural operations

The adaptation of the Global Navigation Satellite Systems (GNSS) technology to fit the needs of farmers requires knowledge of the accuracy level delivered by a GNSS receiver in working conditions. To date, no methodology indicates the minimum number of replications to perform a statistical comparison. This study aims to advance knowledge on the methodological approach for evaluating the static and dynamic performance of GNSS receivers commonly used in agricultural operations. For the static test, a supporting frame in the ground carried all the receivers with coordinates properly transported. In the dynamic test, a circular rail with a 9.55 m radius was installed at ground level with a platform driven by an electric motor to carry the receivers at a constant speed. The transversal error of the receiver to the circular reference line was measured. The error with 95 % probability (E95) to receivers without differential correction ranged between 4.22 m and 0.85 m in the static test, and 2.25 m and 0.98 m in the dynamic test. Receivers with differential correction had E95 values below 0.10 m in the static test and 0.16 m in the dynamic test. Receivers with C/A code require five replications at minimum and 13 replications are needed for L1/L2 with differential correction signals in the dynamic test. The static test needs nine replications for C/A and five for L1/L2 with differential correction signals.(AU)

A statistical approach to static and dynamic tests for Global Navigation Satellite Systems receivers used in agricultural operations

The adaptation of the Global Navigation Satellite Systems (GNSS) technology to fit the needs of farmers requires knowledge of the accuracy level delivered by a GNSS receiver in working conditions. To date, no methodology indicates the minimum number of replications to perform a statistical comparison. This study aims to advance knowledge on the methodological approach for evaluating the static and dynamic performance of GNSS receivers commonly used in agricultural operations. For the static test, a supporting frame in the ground carried all the receivers with coordinates properly transported. In the dynamic test, a circular rail with a 9.55 m radius was installed at ground level with a platform driven by an electric motor to carry the receivers at a constant speed. The transversal error of the receiver to the circular reference line was measured. The error with 95 % probability (E95) to receivers without differential correction ranged between 4.22 m and 0.85 m in the static test, and 2.25 m and 0.98 m in the dynamic test. Receivers with differential correction had E95 values below 0.10 m in the static test and 0.16 m in the dynamic test. Receivers with C/A code require five replications at minimum and 13 replications are needed for L1/L2 with differential correction signals in the dynamic test. The static test needs nine replications for C/A and five for L1/L2 with differential correction signals.

Digital soil class mapping in Brazil: a systematic review

In Brazil several digital soil class mapping studies were carried out from 2006 onwards to maximize the use of existing maps and information and to provide estimates for wider areas. However, there is no consensus on which methods have produced superior results in the predictive value of soil maps. This study conducts a systematic review of digital soil class mapping in Brazil and aims to analyze the factors which can improve the accuracy of digital soil class maps. Data from 334 digital soil class mapping studies were grouped and analyzed by Student's t-test, Wilcoxon-Mann-Whitney test and Kruskal-Wallis test. When conventional maps were used for validation, the studies showed average values of 63 % and when field samples were used, 56 % for Overall Accuracy. Studies compatible with the Planimetric Cartographic Accuracy Standard for Digital Cartographic Products (PEC-PCD) averaged between 4 % and 15 % higher accuracy than those of the incompatible group. There seems to be no evidence that increasing the number of variables and samples results in more accurate soil map prediction, but studies using variables related to four soil-forming factors enhanced accuracy. From a density of 0.08 MU km-² and upwards, it became more difficult for studies to obtain greater accuracy. Artificial neural network classifiers and Decision Tree models seem to be producing more accurate digital soil class maps.

Digital soil class mapping in Brazil: a systematic review

In Brazil several digital soil class mapping studies were carried out from 2006 onwards to maximize the use of existing maps and information and to provide estimates for wider areas. However, there is no consensus on which methods have produced superior results in the predictive value of soil maps. This study conducts a systematic review of digital soil class mapping in Brazil and aims to analyze the factors which can improve the accuracy of digital soil class maps. Data from 334 digital soil class mapping studies were grouped and analyzed by Student's t-test, Wilcoxon-Mann-Whitney test and Kruskal-Wallis test. When conventional maps were used for validation, the studies showed average values of 63 % and when field samples were used, 56 % for Overall Accuracy. Studies compatible with the Planimetric Cartographic Accuracy Standard for Digital Cartographic Products (PEC-PCD) averaged between 4 % and 15 % higher accuracy than those of the incompatible group. There seems to be no evidence that increasing the number of variables and samples results in more accurate soil map prediction, but studies using variables related to four soil-forming factors enhanced accuracy. From a density of 0.08 MU km-² and upwards, it became more difficult for studies to obtain greater accuracy. Artificial neural network classifiers and Decision Tree models seem to be producing more accurate digital soil class maps.(AU)

Assessing reduction of cluster size to estimate wood volume in an Amazonian forest / Avaliando a redução do tamanho do conglomerado para estimar o volume de madeira em uma floresta amazônica

While the Brazilian National Forest Inventory (NFI) is in progress, there is a growing demand to understand the effect of cluster size on the accuracy and precision of forest-attribute estimation. We aimed to find the minimum cluster size (in area) to estimate merchantable volume (MV) with the same accuracy and precision as the estimates derived from the original cluster of 8,000 m2. We used data from an inventory carried out in a forest unit (Bom Futuro National Forest) in the southwestern Brazilian Amazon, where 22 clusters were distributed as a two-stage sampling design. Three products were evaluated: (i) MV of trees with a diameter at breast height (DBH) ≥ 20 cm (P1); (ii) MV of trees with DBH ≥ 50 cm (P2); and (iii) MV of commercial species with DBH ≥ 50 cm and stem quality ‘level 1 or ‘level 2 (P3). We assessed ten scenarios in which the cluster size was reduced from 8,000 m2 to 800 m2. The accuracy of P1, P2 and P3 was highly significantly lower for reductions < 2,400 m². The precision was more sensitive to variations in cluster size, especially for P2 and P3. Minimum cluster sizes were ≥ 2,400 m² to estimate P1, ≥ 4,800 m² to estimate P2, and ≥ 7,200 m² to estimate P3. We concluded that it is possible to reduce the cluster size without losing the accuracy and precision given by the original NFI cluster. A cluster of 2,400 m² provides estimates as accurate as the original cluster, regardless of the evaluated product.(AU)

Enquanto o Inventário Florestal Nacional Brasileiro (IFN) está em andamento, há uma demanda crescente para entender o efeito da área do conglomerado sobre a exatidão e precisão da estimativa de atributos florestais. O objetivo deste estudo foi determinar a área mínima de um conglomerado para estimar o volume comercial (VC) com a mesma acurácia e precisão que as estimativas derivadas do conglomerado original de 8.000 m². A base de dados é proveniente de um inventário realizado em uma unidade florestal (Floresta Nacional do Bom Futuro) no sudoeste da Amazônia brasileira, onde 22 conglomerados foram distribuídos em um desenho amostral em dois estágios. Foram avaliados três produtos: (i) VC de árvores com diâmetro à altura do peito (DAP) ≥ 20 cm (P1); (ii) VC de árvores com DAP ≥ 50 cm (P2); e (iii) VC de espécies comerciais com DAP ≥ 50 cm e qualidade de fuste ‘nível 1 ou ‘nível 2 (P3). O estudo avaliou dez cenários em que a área do conglomerado foi reduzida de 8.000 a 800 m². A acurácia de P1, P2 e P3 foi significativamente menor para reduções < 2.400 m². A precisão foi mais sensível à variação no tamanho do conglomerado, sobretudo para P2 e P3. Os tamanhos mínimos de conglomerado foram ≥ 2.400 m² para estimar P1, ≥ 4.800 m² para estimar P2 e ≥ 7.200 m² para estimar P3. Concluímos que é possível reduzir a área do conglomerado sem perder acurácia e precisão do conglomerado original do IFN. Um conglomerado de 2.400 m² fornece estimativas com a mesma acurácia que o conglomerado original, independentemente do produto avaliado.(AU)

Comparação de métodos para avaliação de beta-hidroxibutirato em ovelhas / Comparison of methods for evaluation of beta-hydroxybutyrate in ewes

Atualmente o uso de sensores portáteis para mensuração de corpos cetônicos está padronizado e difundido na rotina clínica, contudo estudos em ovinos são escassos. Assim, a presente pesquisa objetivou avaliar a acurácia dos sensores portáteis de uso humano e de uso veterinário para a determinação de beta-hidroxibutirato (BHB) em ovelhas no final da gestação e no pós-parto recente. Foram utilizadas 37 amostras de sangue provenientes de nove ovelhas mestiças Corriedale. A determinação bioquímica de BHB no soro, considerada como o padrão-ouro, foi realizada utilizando-se metodologia enzimática colorimétrica. A média obtida na bioquímica sérica foi de 0,497mmol/L; no sensor de uso humano, a média foi igual a 0,537mmol/L, enquanto no sensor de uso veterinário foi de 0,751mmol/L. Foi verificada alta correlação entre o dosímetro de uso humano e o padrão-ouro (r=0,93, P<0,001). A média do aparelho de uso veterinário diferiu das demais (51%; P<0,05), superestimando os resultados em ovelhas. As medições obtidas no aparelho veterinário também apresentaram menor precisão e veracidade. Concluiu-se que o sensor portátil de uso humano é mais acurado e mais preciso no diagnóstico precoce de toxemia da gestação em ovelhas.

Currently the use of portable sensors for measuring ketone bodies is standardized and diffused in the clinical routine, however, studies in sheep are scarce. Therefore, the present study aimed to evaluate the accuracy of the human portable sensor and the veterinary portable sensor for the determination of beta-hydroxybutyrate (BHB) in sheep at the end of gestation and postpartum. We used 37 samples of blood from nine crossbred Corriedale sheep. Biochemical determination of serum BHB, considered gold standard, was performed using colorimetric enzymatic methodology. The mean serum biochemistry was 0.497mmol/L, in the human sensor the mean was 0.537mmol/L, while in the veterinary sensor it was 0.751mmol/L. A high correlation was verified between the dosimeter for human use and the gold standard (r= 0.93, P< 0.001). The mean of the veterinary apparatus differed from the others, being 51% (P< 0,05), higher than the standard, that is, it was less accurate and had lower veracity, overestimating the results in sheep. It was concluded that the portable sensor for human use is more accurate and accurate in the early diagnosis of toxemia of pregnancy in sheep.

Comparação de métodos para avaliação de beta-hidroxibutirato em ovelhas / Comparison of methods for evaluation of beta-hydroxybutyrate in ewes

Atualmente o uso de sensores portáteis para mensuração de corpos cetônicos está padronizado e difundido na rotina clínica, contudo estudos em ovinos são escassos. Assim, a presente pesquisa objetivou avaliar a acurácia dos sensores portáteis de uso humano e de uso veterinário para a determinação de beta-hidroxibutirato (BHB) em ovelhas no final da gestação e no pós-parto recente. Foram utilizadas 37 amostras de sangue provenientes de nove ovelhas mestiças Corriedale. A determinação bioquímica de BHB no soro, considerada como o padrão-ouro, foi realizada utilizando-se metodologia enzimática colorimétrica. A média obtida na bioquímica sérica foi de 0,497mmol/L; no sensor de uso humano, a média foi igual a 0,537mmol/L, enquanto no sensor de uso veterinário foi de 0,751mmol/L. Foi verificada alta correlação entre o dosímetro de uso humano e o padrão-ouro (r=0,93, P<0,001). A média do aparelho de uso veterinário diferiu das demais (51%; P<0,05), superestimando os resultados em ovelhas. As medições obtidas no aparelho veterinário também apresentaram menor precisão e veracidade. Concluiu-se que o sensor portátil de uso humano é mais acurado e mais preciso no diagnóstico precoce de toxemia da gestação em ovelhas.(AU)

Currently the use of portable sensors for measuring ketone bodies is standardized and diffused in the clinical routine, however, studies in sheep are scarce. Therefore, the present study aimed to evaluate the accuracy of the human portable sensor and the veterinary portable sensor for the determination of beta-hydroxybutyrate (BHB) in sheep at the end of gestation and postpartum. We used 37 samples of blood from nine crossbred Corriedale sheep. Biochemical determination of serum BHB, considered gold standard, was performed using colorimetric enzymatic methodology. The mean serum biochemistry was 0.497mmol/L, in the human sensor the mean was 0.537mmol/L, while in the veterinary sensor it was 0.751mmol/L. A high correlation was verified between the dosimeter for human use and the gold standard (r= 0.93, P< 0.001). The mean of the veterinary apparatus differed from the others, being 51% (P< 0,05), higher than the standard, that is, it was less accurate and had lower veracity, overestimating the results in sheep. It was concluded that the portable sensor for human use is more accurate and accurate in the early diagnosis of toxemia of pregnancy in sheep.(AU)

Simplification of the analysis of dry matter in fluid milk / Simplificação da análise de matéria seca em leite fluído / Simplificación del análisis de materia seca en leche fluida

This study aims to evaluate a simpler methodology for determination of dry matter in three types of milk. The treatments consisted of three methodologies: AOAC (Association of Official Agricultural Chemists), characterized by the drying in porcelain capsules and pre-heating; use of analytical sand in the process of drying, as well as a simplified methodology characterized by drying in Petri dishes without analytical sand and pre-heating proceeding. The statistical analysis was performed with F test (5% significance level), Pearson's correlation and Lin's concordance correlation coefficient. All methodologies showed precision and accuracy in the measurement of the dry matter in milk, however, the simplified methodology was superior in material savings and shorter time consumption for the analysis.(AU)

Este estudo teve como objetivo avaliar metodologia simplificada de determinação de matéria seca em três tipos de leite. Os tratamentos consistiram de três metodologias: AOAC (Association of Official Agricultural Chemists), caracterizada pela secagem em cápsulas de porcelana e pré-secagem; uso de areia analítica no processo de secagem e utilização de metodologia simplificada baseada no uso de placas de Petri com secagem direta em estufa, sem o uso de areia analítica e procedimento de pré-secagem. A análise estatística envolveu o teste F ao nível de significância de 5%, correlação de Pearson e coeficiente de concordância de Lin. Todas as metodologias mostraram acurácia na determinação da matéria seca para todos os tipos de leite, mas a metodologia simplificada foi superior em economia e menor tempo de análise.(AU)

Este estudio tuvo como objetivo evaluar la metodología simplificada de determinación de materia seca en tres tipos de leche. Los tratamientos consistieron en tres metodologías: AOAC (Association of Official Agricultural Chemists), caracterizada por pre-secado y secado en cápsulas de porcelana; uso de arena analítica en el proceso de secado y utilización de metodología simplificada basada en el uso de placas de Petri con secado directo en invernadero, sin el uso de arena analítica y procedimiento de pre secado. El análisis estadístico involucró la prueba F al nivel de significancia del 5%, correlación de Pearson y coeficiente de concordancia de Lin. Todas las metodologías mostraron precisión en la determinación de la materia seca para todos los tipos de leche, pero la metodología simplificada fue superior en economía y menor tiempo de análisis.(AU)

Simplification of the analysis of dry matter in fluid milk / Simplificação da análise de matéria seca em leite fluído / Simplificación del análisis de materia seca en leche fluida

This study aims to evaluate a simpler methodology for determination of dry matter in three types of milk. The treatments consisted of three methodologies: AOAC (Association of Official Agricultural Chemists), characterized by the drying in porcelain capsules and pre-heating; use of analytical sand in the process of drying, as well as a simplified methodology characterized by drying in Petri dishes without analytical sand and pre-heating proceeding. The statistical analysis was performed with F test (5% significance level), Pearson's correlation and Lin's concordance correlation coefficient. All methodologies showed precision and accuracy in the measurement of the dry matter in milk, however, the simplified methodology was superior in material savings and shorter time consumption for the analysis.(AU)

Este estudo teve como objetivo avaliar metodologia simplificada de determinação de matéria seca em três tipos de leite. Os tratamentos consistiram de três metodologias: AOAC (Association of Official Agricultural Chemists), caracterizada pela secagem em cápsulas de porcelana e pré-secagem; uso de areia analítica no processo de secagem e utilização de metodologia simplificada baseada no uso de placas de Petri com secagem direta em estufa, sem o uso de areia analítica e procedimento de pré-secagem. A análise estatística envolveu o teste F ao nível de significância de 5%, correlação de Pearson e coeficiente de concordância de Lin. Todas as metodologias mostraram acurácia na determinação da matéria seca para todos os tipos de leite, mas a metodologia simplificada foi superior em economia e menor tempo de análise.(AU)

Este estudio tuvo como objetivo evaluar la metodología simplificada de determinación de materia seca en tres tipos de leche. Los tratamientos consistieron en tres metodologías: AOAC (Association of Official Agricultural Chemists), caracterizada por pre-secado y secado en cápsulas de porcelana; uso de arena analítica en el proceso de secado y utilización de metodología simplificada basada en el uso de placas de Petri con secado directo en invernadero, sin el uso de arena analítica y procedimiento de pre secado. El análisis estadístico involucró la prueba F al nivel de significancia del 5%, correlación de Pearson y coeficiente de concordancia de Lin. Todas las metodologías mostraron precisión en la determinación de la materia seca para todos los tipos de leche, pero la metodología simplificada fue superior en economía y menor tiempo de análisis.(AU)

Use of indigestible markers to estimate the apparent dry matter digestibility of diets containing a cocoa by-product / Indicadores na estimativa da digestibilidade aparente em dietas com inclusão de coproduto do cacau

Fecal production and apparent dry matter digestibility (ADMD) were evaluated using external markers (chromium oxide; titanium dioxide; isolated, purified, and enriched lignin (LIPE®); and isolated, purified, and enriched lignin nanoparticles (NANOLIPE®) and internal markers (indigestible DM (IDM), indigestible neutral detergent fiber (INDF), and indigestible acid detergent fiber (IADF) in diets based on Tifton 85 bermuda grass (Cynodon sp.) hay containing different concentrations of a cocoa by-product. Sixteen crossbred (Holstein × Zebu) dairy heifers with a mean live weight of 363.00 ± 27.70 kg were evaluated and distributed in a completely randomized block design with a split-plot arrangement. The plots corresponded to the diets, which differed in the substitution of bermuda grass hay with different concentrations (0, 8, 16, and 24% of DM) of the cocoa by-product, whereas the splitplots represented the indigestible markers. Chromic oxide, LIPE®, NANOLIPE®, and INDF accurately estimated ADMD and fecal production whereas titanium dioxide, IDM, and IADF did not accurately estimate these parameters.

Foram avaliados a produção fecal e a digestibilidade dos nutrientes com o uso de indicadores externos (óxido crômico, dióxido de titânio, lignina isolada, purificada e enriquecida - LIPE® e lignina isolada, purificada e enriquecida em nanopartículas -NANOLIPE®) e internos (matéria seca indigestível - MSi, fibra em detergente neutro indigestível - FDNi e fibra em detergente ácido indigestível -FDAi) em dietas a base de feno de capim tifton 85 com inclusão de coproduto de cacau. Foram utilizadas dezesseis novilhas leiteiras mestiças Holandês X Zebu, peso vivo médio (363,00 ± 27,70 kg), distribuídas em delineamento inteiramente casualizado com arranjo em parcelas subdivididas. As dietas oferecidas foram as parcelas, que se diferenciavam quanto à substituição do feno de capim Tifton 85 (Cynodon sp) pelo coproduto do cacau em diferentes níveis (0, 8, 16 e 24% da MS) e, os indicadores, as subparcelas. Os indicadores óxido crômico, LIPE®, NANOLIPE® e FDNi estimaram com acurácia e precisão a digestibilidade aparente dos nutrientes e a produção fecal. Os indicadores dióxido de titânio, MSi e a FDAi foram ineficientes para estimar esses parâmetros.

Use of indigestible markers to estimate the apparent dry matter digestibility of diets containing a cocoa by-product / Indicadores na estimativa da digestibilidade aparente em dietas com inclusão de coproduto do cacau

Fecal production and apparent dry matter digestibility (ADMD) were evaluated using external markers (chromium oxide; titanium dioxide; isolated, purified, and enriched lignin (LIPE®); and isolated, purified, and enriched lignin nanoparticles (NANOLIPE®) and internal markers (indigestible DM (IDM), indigestible neutral detergent fiber (INDF), and indigestible acid detergent fiber (IADF) in diets based on Tifton 85 bermuda grass (Cynodon sp.) hay containing different concentrations of a cocoa by-product. Sixteen crossbred (Holstein × Zebu) dairy heifers with a mean live weight of 363.00 ± 27.70 kg were evaluated and distributed in a completely randomized block design with a split-plot arrangement. The plots corresponded to the diets, which differed in the substitution of bermuda grass hay with different concentrations (0, 8, 16, and 24% of DM) of the cocoa by-product, whereas the splitplots represented the indigestible markers. Chromic oxide, LIPE®, NANOLIPE®, and INDF accurately estimated ADMD and fecal production whereas titanium dioxide, IDM, and IADF did not accurately estimate these parameters.(AU)

Foram avaliados a produção fecal e a digestibilidade dos nutrientes com o uso de indicadores externos (óxido crômico, dióxido de titânio, lignina isolada, purificada e enriquecida - LIPE® e lignina isolada, purificada e enriquecida em nanopartículas -NANOLIPE®) e internos (matéria seca indigestível - MSi, fibra em detergente neutro indigestível - FDNi e fibra em detergente ácido indigestível -FDAi) em dietas a base de feno de capim tifton 85 com inclusão de coproduto de cacau. Foram utilizadas dezesseis novilhas leiteiras mestiças Holandês X Zebu, peso vivo médio (363,00 ± 27,70 kg), distribuídas em delineamento inteiramente casualizado com arranjo em parcelas subdivididas. As dietas oferecidas foram as parcelas, que se diferenciavam quanto à substituição do feno de capim Tifton 85 (Cynodon sp) pelo coproduto do cacau em diferentes níveis (0, 8, 16 e 24% da MS) e, os indicadores, as subparcelas. Os indicadores óxido crômico, LIPE®, NANOLIPE® e FDNi estimaram com acurácia e precisão a digestibilidade aparente dos nutrientes e a produção fecal. Os indicadores dióxido de titânio, MSi e a FDAi foram ineficientes para estimar esses parâmetros.(AU)

Evaluation of imputed genomic data in discrete traits using Random forest and Bayesian threshold methods / Avaliação de dados genômicos imputados em características distintas usando os métodos de Random Forest e de limiares Bayesianos

The objectives of this study were (1) to quantify imputation accuracy and to assess the factors affecting it; and (2) to evaluate the accuracy of threshold BayesA (TBA), Bayesian threshold LASSO (BTL) and random forest (RF) algorithms to analyze discrete traits. Genomic data were simulated to reflect variations in heritability (h2 = 0.30 and 0.10), number of QTL (QTL = 81 and 810), number of SNP (10 K and 50 K) and linkage disequilibrium (LD=low and high) for 27 chromosomes. For real condition simulating, we randomly masked markers with 90% missing rate for each scenario; afterwards, hidden markers were imputed using FImpute software. In imputed genotypes, a wide range of accuracy was observed for RF (0.164-0.512) compared to TBA (0.283-0.469) and BTL (0.272-0.504). Comparing to original genotypes, using imputed genotypes decreased the average accuracy of genomic prediction about 0.0273 (range of 0.024 to 0.036). Comparing to Bayesian threshold, using RF was improved rapidly accuracy of genomic prediction with increase in the marker density. Despite the higher accuracy of BTL and TBA at different levels of LD and heritability, the increase in accuracy was greater for RF. Furthermore, the best method for prediction of genomic accuracy depends on genomic architecture of population.(AU)

Os objetivos deste estudo foram (1) quantificar a precisão de imputação e acessar os fatores que as afetam; e (2) avaliar a precisão do princípio de BayesA (TBA), do modelo Bayesiano LASSO (BTL), e o algoritmo Random Forest para analisar as características distintas. Dados genômicos foram simulados para indicar variações na herdabilidade (h2 = 0.30 e 0.10), número de QTL (QTL = 81 e 810), número de SNP (10 k e 50 k) e desequilíbrio de ligação (LD = baixo e alto) para 27 cromossomos. Para uma simulação mais realista, nós cobrimos os marcadores aleatoriamente com 90% da taxa ausente para cada cenário, depois, os marcadores foram imputados usando o software FImpute. Nos genótipos imputados uma grande oscilação de precisão foi observada pelo modelo RF (0.164-0.512) comparado com TBA (0.283 - 0.469) e BTL (0.272 - 0.504). Comparando com os genótipos originais, os genótipos imputados decaíram a precisão média da predição genômica em cerca de 0.0273 (oscilação de 0.024 para 0.036). Comparando-se ao princípio Bayesiano, o uso de RF melhorou a precisão de predição com o aumento da densidade do marcador. Além disso, o melhor método para predição de precisão genômica depende da arquitetura genômica da sua população.(AU)

Evaluation of imputed genomic data in discrete traits using Random forest and Bayesian threshold methods / Avaliação de dados genômicos imputados em características distintas usando os métodos de Random Forest e de limiares Bayesianos

The objectives of this study were (1) to quantify imputation accuracy and to assess the factors affecting it; and (2) to evaluate the accuracy of threshold BayesA (TBA), Bayesian threshold LASSO (BTL) and random forest (RF) algorithms to analyze discrete traits. Genomic data were simulated to reflect variations in heritability (h2 = 0.30 and 0.10), number of QTL (QTL = 81 and 810), number of SNP (10 K and 50 K) and linkage disequilibrium (LD=low and high) for 27 chromosomes. For real condition simulating, we randomly masked markers with 90% missing rate for each scenario; afterwards, hidden markers were imputed using FImpute software. In imputed genotypes, a wide range of accuracy was observed for RF (0.164-0.512) compared to TBA (0.283-0.469) and BTL (0.272-0.504). Comparing to original genotypes, using imputed genotypes decreased the average accuracy of genomic prediction about 0.0273 (range of 0.024 to 0.036). Comparing to Bayesian threshold, using RF was improved rapidly accuracy of genomic prediction with increase in the marker density. Despite the higher accuracy of BTL and TBA at different levels of LD and heritability, the increase in accuracy was greater for RF. Furthermore, the best method for prediction of genomic accuracy depends on genomic architecture of population.

Os objetivos deste estudo foram (1) quantificar a precisão de imputação e acessar os fatores que as afetam; e (2) avaliar a precisão do princípio de BayesA (TBA), do modelo Bayesiano LASSO (BTL), e o algoritmo Random Forest para analisar as características distintas. Dados genômicos foram simulados para indicar variações na herdabilidade (h2 = 0.30 e 0.10), número de QTL (QTL = 81 e 810), número de SNP (10 k e 50 k) e desequilíbrio de ligação (LD = baixo e alto) para 27 cromossomos. Para uma simulação mais realista, nós cobrimos os marcadores aleatoriamente com 90% da taxa ausente para cada cenário, depois, os marcadores foram imputados usando o software FImpute. Nos genótipos imputados uma grande oscilação de precisão foi observada pelo modelo RF (0.164-0.512) comparado com TBA (0.283 - 0.469) e BTL (0.272 - 0.504). Comparando com os genótipos originais, os genótipos imputados decaíram a precisão média da predição genômica em cerca de 0.0273 (oscilação de 0.024 para 0.036). Comparando-se ao princípio Bayesiano, o uso de RF melhorou a precisão de predição com o aumento da densidade do marcador. Além disso, o melhor método para predição de precisão genômica depende da arquitetura genômica da sua população.

Quantitative genetics theory for genomic selection and efficiency of genotypic value prediction in open-pollinated populations

Quantitative genetics theory for genomic selection has mainly focused on additive effects. This study presents quantitative genetics theory applied to genomic selection aiming to prove that prediction of genotypic value based on thousands of single nucleotide polymorphisms (SNPs) depends on linkage disequilibrium (LD) between markers and QTLs, assuming dominance and epistasis. Based on simulated data, we provided information on dominance and genotypic value prediction accuracy, assuming mass selection in an open-pollinated population, all quantitative trait loci (QTLs) of lower effect, and reduced sample size. We show that the predictor of dominance value is proportional to the square of the LD value and to the dominance deviation for each QTL that is in LD with each marker. The weighted (by the SNP frequencies) dominance value predictor has greater accuracy than the unweighted predictor. The linear × linear, linear × quadratic, quadratic × linear, and quadratic × quadratic SNP effects are proportional to the corresponding linear combinations of epistatic effects for QTLs and the LD values. LD between two markers with a common QTL causes a bias in the prediction of epistatic values. Compared to phenotypic selection, the efficiency of genomic selection for genotypic value prediction increases as trait heritability decreases. The degree of dominance did not affect the genotypic value prediction accuracy and the approach to maximum accuracy is asymptotic with increases in SNP density. The decrease in the sample size from 500 to 200 did not markedly reduce the genotypic value prediction accuracy.