Empirical Comparison of Tropical Maize Hybrids Selected Through Genomic and Phenotypic Selections.

Genomic selection predicts the genomic estimated breeding values (GEBVs) of individuals not previously phenotyped. Several studies have investigated the accuracy of genomic predictions in maize but there is little empirical evidence on the practical performance of lines selected based on phenotype in comparison with those selected solely on GEBVs in advanced testcross yield trials. The main objectives of this study were to (1) empirically compare the performance of tropical maize hybrids selected through phenotypic selection (PS) and genomic selection (GS) under well-watered (WW) and managed drought stress (WS) conditions in Kenya, and (2) compare the cost-benefit analysis of GS and PS. For this study, we used two experimental maize data sets (stage I and stage II yield trials). The stage I data set consisted of 1492 doubled haploid (DH) lines genotyped with rAmpSeq SNPs. A subset of these lines (855) representing various DH populations within the stage I cohort was crossed with an individual single-cross tester chosen to complement each population. These testcross hybrids were evaluated in replicated trials under WW and WS conditions for grain yield and other agronomic traits, while the remaining 637 DH lines were predicted using the 855 lines as a training set. The second data set (stage II) consists of 348 DH lines from the first data set. Among these 348 best DH lines, 172 lines selected were solely based on GEBVs, and 176 lines were selected based on phenotypic performance. Each of the 348 DH lines were crossed with three common testers from complementary heterotic groups, and the resulting 1042 testcross hybrids and six commercial checks were evaluated in four to five WW locations and one WS condition in Kenya. For stage I trials, the cross-validated prediction accuracy for grain yield was 0.67 and 0.65 under WW and WS conditions, respectively. We found similar responses to selection using PS and GS for grain yield other agronomic traits under WW and WS conditions. The top 15% of hybrids advanced through GS and PS gave 21%-23% higher grain yield under WW and 51%-52% more grain yield under WS than the mean of the checks. The GS reduced the cost by 32% over the PS with similar selection gains. We concluded that the use of GS for yield under WW and WS conditions in maize can produce selection candidates with similar performance as those generated from conventional PS, but at a lower cost, and therefore, should be incorporated into maize breeding pipelines to increase breeding program efficiency.

SASHAYDIALL: A SAS Program for Hayman's Diallel Analysis.

Different methods of diallel crossing are commonly used in plant breeding. The diallel cross analysis method proposed by Hayman is particularly useful because it provides information, among others, on additive and dominance effects of genes, average degree of dominance, proportion of dominance, direction of dominance, distribution of genes, maternal and reciprocal effects, number of groups of genes that control a trait and exhibit dominance, ratio of dominant to recessive alleles in all the parents, and broad-sense and narrow-sense heritability. In this paper, we fully describe a SAS-based software SASHAYDIALL for performing a complete diallel cross analysis based on Hayman's model with or without reciprocals. We demonstrate the use of SASHAYDIALL with two data sets; one is a published diallel cross data set with reciprocals in cabbage (Brassica oleracea L.), and the second is a data set from a multilocation diallel cross trial in maize (Zea mays L.) without reciprocals. With SASHAYDIALL, diallel experiments conducted in single sites can be analyzed to estimate various genetic parameters, and this analysis is extended over locations or environments to assess genetic effect × environment interaction. SASHAYDIALL is user-friendly software that provides detailed genetic information from diallel crosses involving any number of parents and locations.

Predicting grain yield using canopy hyperspectral reflectance in wheat breeding data.

BACKGROUND: Modern agriculture uses hyperspectral cameras to obtain hundreds of reflectance data measured at discrete narrow bands to cover the whole visible light spectrum and part of the infrared and ultraviolet light spectra, depending on the camera. This information is used to construct vegetation indices (VI) (e.g., green normalized difference vegetation index or GNDVI, simple ratio or SRa, etc.) which are used for the prediction of primary traits (e.g., biomass). However, these indices only use some bands and are cultivar-specific; therefore they lose considerable information and are not robust for all cultivars. RESULTS: This study proposes models that use all available bands as predictors to increase prediction accuracy; we compared these approaches with eight conventional vegetation indexes (VIs) constructed using only some bands. The data set we used comes from CIMMYT's global wheat program and comprises 1170 genotypes evaluated for grain yield (ton/ha) in five environments (Drought, Irrigated, EarlyHeat, Melgas and Reduced Irrigated); the reflectance data were measured in 250 discrete narrow bands ranging between 392 and 851 nm. The proposed models for the simultaneous analysis of all the bands were ordinal least square (OLS), Bayes B, principal components with Bayes B, functional B-spline, functional Fourier and functional partial least square. The results of these models were compared with the OLS performed using as predictors each of the eight VIs individually and combined. CONCLUSIONS: We found that using all bands simultaneously increased prediction accuracy more than using VI alone. The Splines and Fourier models had the best prediction accuracy for each of the nine time-points under study. Combining image data collected at different time-points led to a small increase in prediction accuracy relative to models that use data from a single time-point. Also, using bands with heritabilities larger than 0.5 only in Drought as predictor variables showed improvements in prediction accuracy.

A Genomic Selection Index Applied to Simulated and Real Data.

A genomic selection index (GSI) is a linear combination of genomic estimated breeding values that uses genomic markers to predict the net genetic merit and select parents from a nonphenotyped testing population. Some authors have proposed a GSI; however, they have not used simulated or real data to validate the GSI theory and have not explained how to estimate the GSI selection response and the GSI expected genetic gain per selection cycle for the unobserved traits after the first selection cycle to obtain information about the genetic gains in each subsequent selection cycle. In this paper, we develop the theory of a GSI and apply it to two simulated and four real data sets with four traits. Also, we numerically compare its efficiency with that of the phenotypic selection index (PSI) by using the ratio of the GSI response over the PSI response, and the PSI and GSI expected genetic gain per selection cycle for observed and unobserved traits, respectively. In addition, we used the Technow inequality to compare GSI vs. PSI efficiency. Results from the simulated data were confirmed by the real data, indicating that GSI was more efficient than PSI per unit of time.

Rindsel: an R package for phenotypic and molecular selection indices used in plant breeding.

Selection indices are estimates of the net genetic merit of the individual candidates for selection and are calculated based on phenotyping and molecular marker information collected on plants under selection in a breeding program. They reflect the breeding value of the plants and help breeders to choose the best ones for next generation. Rindsel is an R package that calculates phenotypic and molecular selection indices.

Monitoreo de la posesión y uso de mosquiteros tratados con insecticidas de larga duración en un área endémica de malaria de la Amazonia Venezolana / Monitoramento da posse e uso de mosquiteiros tratados com inseticidas de longa duração em uma área endêmica de malária da Amazônia Venezuelana

OBJETIVOS: Evaluar la posesión y uso de mosquiteros tratados con insecticida de larga duración (MTILD) luego de seis meses de su distribución en Amazonas, Venezuela.MATERIALES Y MÉTODOS: Durante junio y julio del 2007, se distribuyeron 11.798 MTILD Olyset Net® en 56 comunidades de Amazonas, protegiendo 13.129 personas. Seis meses después, se realizaron visitas de monitoreo a los hogares de una muestra seleccionada al azar de 27 comunidades (48,2 por ciento del total), colectándose, mediante un cuestionario semiestructurado, los datos necesarios para el cálculo de indicadores de posesión y uso de los MTILD.RESULTADOS: La posesión de MTILD en hogares fue elevada (93,7 por ciento). La proporción de individuos que durmieron bajo un MTILD la noche previa a la encuesta fue de 93,7 por ciento. Para niños menores de 5 años del edad y gestantes, la proporción de los que durmieron bajo un MTILD fue de 94,3 por ciento y 89,2 por ciento, respectivamente. La mayoría de las características de los MTILD fue altamente aceptada (> 90 por ciento), con excepción de los agujeros grandes de la trama (70,3 por ciento) y la altura del MTILD (70,7 por ciento).CONCLUSIONES: El monitoreo realizado demostró elevada posesión y uso de los MTILD luego de seis meses de la distribución.

OBJETIVOS: Avaliar a posse e o uso de mosquiteiros tratados com inseticida de longa duração (MTILD) após seis meses da sua distribuição no Amazonas, Venezuela. MATERIAIS E MÉTODOS: Durante os meses de junho e julho de 2007, foram distribuídos 11.798 MTILD Olyset Net® em 56 comunidades do estado Amazonas, protegendo 13.129 pessoas. Seis meses depois foram realizadas visitas de monitoramento às residências de uma amostra selecionada aleatoriamente de 27 comunidades (48,2 por cento do total), tendo sido coletados, mediante questionário semiestruturado, os dados necessários para o cálculo de indicadores de posse e uso dos MTILD. RESULTADOS: A posse de MTILD em residências foi elevada (93,7 por cento). A proporção de indivíduos que dormiram sob um MTILD a noite prévia à pesquisa foi de 93,7 por cento. Para crianças menores a 5 anos de idade e gestantes, a proporção dos que dormiram sob um MTILD foi de 94,3 por cento e 89,2 por cento, respectivamente. A maioria das características dos MTILD foi altamente aceita (>90 por cento), com exceção dos furos grandes da trama (70,3 por cento) e a altura do MTILD (70,7 por cento). CONCLUSÕES: O monitoramento realizado demonstrou elevada posse e uso dos MTILD após 6 meses da sua distribuição.