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Revista Biociencias Julio 2010 Vol. 1 Núm. 1 Año 1 Páginas 4 a 18 4ResumenEl maíz es uno de los cultivos económicosen los que se ha investigado y avanzadoen la mejora genética, pero es necesario estudiarla diversidad local presente en las áreas rurales,la que es conservada y manejada in situ,en los huertos caseros y/o fincas de los agricultores,dada la importancia de este grano básicoen la subsistencia familiar. Los objetivos de estetrabajo fueron identificar y caracterizar las razasde maíz en pequeños predios rurales de dos zonasde Cuba aisladas geográficamente: Pinar delRío y Guantánamo. Se estudiaron 55 poblacionestradicionales y se evaluaron 14 caracteres (nuevecontinuos y cinco categóricos) en la mazorca y elgrano. Estos se procesaron empleando la estrategiaen dos pasos WARD-Método Local Modificado(MLM) para el agrupamiento de observaciones,utilizando variables continuas y categóricassimultáneamente. Como medida de similaridad seempleó la distancia de Gower, utilizando para sucálculo el paquete estadístico SAS 9.0. De esteanálisis se derivó la formación de seis grupos yse identificaron cuatro de las razas de maíz másimportantes para Cuba: Criollo, Canilla, Tusóny Argentino, lo que sugiere que los campesinosconservan in situ una parte importante de la diversidad de las razas presentes en el germoplasmacubano de maíz. Se sugiere el estudio enotras áreas del país, específicamente en la regiónOriental, provincia de Guantánamo, con el objetivode corroborar la presencia de otras razas descritaspara Cuba, ya que éstas sólo han sido ubicadas enmuy baja frecuencia en localidades específicas delValle de Caujerí, en Guantánamo.

CIMMYT is the source of improved maize (Zea mays L.) breeding material for a significant portion of the nontemperate maize growing world. Landraces which did not serve as sources for improved maize germplasm may contain untapped allelic variation useful for future breeding progress. Information regarding levels of diversity in different germplasm would help to identify sources for broadening improved breeding pools and in seeking genes and alleles that have not been tapped in modern maize breeding. The objectives of this study were to examine the diversity in maize landraces, modern open pollinated varieties (OPVs), and inbred lines adapted to nontemperate growing areas to find unique sources of allelic diversity that may be used in maize improvement. Twenty-five simple sequence repeat markers were used to characterize 497 individuals from 24 landraces of maize from Mexico, 672 individuals from 23 CIMMYT improved breeding populations, and 261 CIMMYT inbred lines. Number of alleles, gene diversity per locus, unique alleles per locus, and population structure all differ between germplasm groups. The unique alleles found in each germplasm group represent a great reservoir of untapped genetic resources for maize improvement, and implications for hybrid breeding are discussed.

Spot blotch is an important disease of wheat (Triticum aestivum L.) in South Asia. Division of test sites for this disease into homogenous subregions is expected to contribute to more efficient evaluation and better differentiation of cultivars. Data from a collaborative regional program of South Asia conducted by CIMMYT were analyzed to group testing sites into relatively homogenous subregions for spot blotch area under the disease progress curve (AUDPC). Five-year data of eight locations from Eastern Gangetic Plains Nursery (EGPSN) and five locations of the Eastern Gangetic Plains Yield Trial (EGPYT) conducted in three countries (India, Nepal, and Bangladesh) of South Asia were used. A hierarchical cluster analysis was used to group locations on the basis of genotype x location interaction effects for spot blotch AUDPC. Cluster analysis divided South Asia into two broad regions and four subregions. This classification was not entirely consistent with the geographic distribution of locations, but clusters mostly followed general geographicclimatic locations. The locations Varanasi (India) and Bhairahawa (Nepal) were identified as the most suitable sites for evaluation of spot blotch, followed by Rampur (Nepal). The major determinant for the clustering was mean temperature. The results suggest that the major wheat region of South Asia can be divided into subregions, which may reduce the cost of resistance evaluation and aid in developing wheat with resistance to this disease.

A good understanding of the target environment and the extent of genotype x environment (G x E) interaction is essential for all cereal breeding programs. Differential adaptation of bread wheat (Triticum aestivum L.) to various heat-stressed environments around the world was analyzed by cumulative cluster analysis of locations and genotypes in 9 yr of CIMMYT's High Temperature Wheat Yield Trial (HTWYT). The grouping pattern of yield-testing environments could largely be explained by the temperature at different growth stages and relative humidity at booting. A clear distinction was observed between sites with heat stress and more temperate locations, and the heat-stressed environments could be grouped into sites experiencing high temperature throughout the season and sites with more specific terminal heat stress. In addition, dry and humid heat-stressed locations tended to differentiate. The ability of individual locations to predict yield in different heat-stressed environments was studied by the shifted multiplicative model (SHMM) site clustering method, and identified locations like Tandojam (Pakistan), which associated well with both heat-stressed and temperate environments. The good ability of the January planting date in Ciudad Obregon (Mexico) to predict yield performance in many heat-stressed environments was also confirmed. Genotypes grouped according to their relative performance in different locations, and specific adaptation to the various types of heat-stressed environments was apparent. However, a subset of genotypes was identified that showed stable, and high yield across all types of environments, both heat-stressed and temperate., BREAD WHEAT is a widely adapted crop that can be grown in many different environments. Although it is best adapted to cool or temperate growing conditions, it is grown in [...]

A shrinkage estimation method, herein named the CCC method, for multiplicative models has been shown to improve predictions of cell means in multienvironment cultivar trials; however, better estimations of shrinkage factors are needed. Objectives of this study were (i) to develop shrinkage factors for AMMI (Additive Main effect and Multiplicative Interaction) multiplicative terms based on the eigenvalue partition (EVP) method and (ii) to compare AMMI models fitted by EVP and CCC shrinkage methods, unshrunken AMMI models chosen by cross validation, and best linear unbiased prediction (BLUP) based on a fixed main effects and random genotype x environment interaction (GEI) model. The prediction methods were applied to three multienvironment cultivar trials, and also to simulated data. The four alternative prediction methods were compared by cross validation with the root mean squared predictive difference (RMSPD). According to the RMSPD cross validation criterion, the EVP shrinkage estimation method produced the most accurate predictions in almost all cases. When error variance was of a small to moderately large magnitude, results for EVP and CCC methods were in close agreement, CCC being slightly worse; EVP became better as error variance became very large, probably because of the unreliability of Gollobs degrees of freedom as a measure of error variance absorption by the principal components (PC) when data are extremely noisy. Shrunken EVP models were generally more predictively accurate than truncated least squares-fitted AMMI models and BLUPs, which was also true for CCC except when error variance was large. The EVP shrinkage method appears to be promising for obtaining improved predictions of cultivar performance in multienvironment cultivar trials., SEVERAL STATISTICAL MODELS have been used for predicting cultivar responses in multienvironment cultivar trials. Multiplicative models, such as the AMMI model, the genotypes regression (GREG) model, the sites regression (SREG) [...]

Many studies have shown the practical advantages of applying the additive main effects and multiplicative interaction (AMMI) model to multienvironment trials; however, a theory about the contributions of error and genotype x environment interaction (GEI) variance components to interaction principal components (PCs) in AMMI models is needed. The objectives of this work were to (i) develop an eigenvalue partition (EVP) method for separating variation attributable to each AMMI interaction PC into interaction variance and error variance components: (ii) develop root mean square predictive difference (RMSPD) on the basis of the EVP theory (RMSPEVP), for selecting the best truncated AMMI model; (iii) apply the RMSP[D.sub.EVP] criterion to three multienvironment cultivar trials and to simulation data generated for selecting the best truncated AMMI model; and (iv) validate the EVP method by comparing results of the RMSP[D.sub.EVP] criterion with those obtained with the criterion conventionally used to choose a truncated AMMI model by cross validation (RMSP[D.sub.CV]). A data resampling method was devised to estimate the contribution of error variance to the eigenvalues. The coefficients of the structural GEI variance component were always larger than those of the error variance component for the earlier PC axes. As the error associated with the cell means decreased and the number of replications increased, the portion of the cumulative GEI explained by the earlier AMMI PC axes generally increased, whereas the portion of the error sum of squares (SS) explained by the earlier AMMI PC axes decreased. The RMSP[D.sub.EVP] and RMSP[D.sub.CV] methods selected similar truncated AMMI models. The RMSP[D.sub.EVP] criterion is useful for selecting the best truncated AMMI models with the advantage that it can be applied to all trial replications., IN PLANT BREDDING, evaluated in multienvironment trials to test their performance across environments and to select the best genotypes in specific environments. Variance due to GEI is an important component [...]

Understanding the way different environments differentiate cultivars for yield allows the plant breeder to optimize choice of parents, germplasm screening, yield testing, and resource use within the target region. To determine the associations among yield testing environments, wheat (Triticum aestivum L.) yield data from 963 replicated trials sown across a 20-yr period were analyzed by means of pattern analysis and the shifted multiplicative model (SHMM) to group sites within and across years. Pattern analysis identified four primary clusters of sites and four representative locations within these dusters were identified by squared Euclidean distances. Group-1 represented primarily Mediterranean and West Asian locations and South American sites. Group-2 was comprised of generally warmer sites in southern and eastern Asia. Group-3 comprised higher rainfall locations in South America and eastern Africa and Group-4 represented cooler sites in South America and West Asia. The respective key locations for each of the four groups were Sakha, Egypt; Quezaltenango, Guatemala; Londrina, Brazil; and Pirsabak, Pakistan. The four key sites were then used to examine site clusters within each year by SHMM. The sites at Pirsabak and Sakba associated best across all global wheat-growing regions where a combined total of 700 of 1117 (62%) possible clusters with other global wheat locations were realized. This compared with 52% for Quezaltenango and 38% for Londrina. Factors with a primary influence on site clustering were cropping season moisture availability and temperature. Genotype performance at Pirsabak and Sakha can be used to enhance genetic progress in a range of related wheat growing environments thereby improving the effectiveness of global wheat breeding., THE BREAD WHEAT BREEDING PROGRAM at the International Maize and Wheat Improvement Center (CIMMYT) develops spring wheat germplasm for the wheat production environments of developing countries. Much of this germplasm [...]

Diverse and varied crop genetic resources are necessary (though not sufficient) for adequate food production in a rapidly changing world. Since the scientific community first raised public concern several decades ago, modern cultivars have been viewed as the cause of declining diversity in the world's crop genetic resources. This paper tests the hypothesis of increasing genetic uniformity in modern spring bread wheat (Triticum aestivum L.) cultivars from 1965, a year which marks the release of some of the first modern semidwarf cultivars carrying Rht1 and Rht2 genes in the developing world. Results from previously published studies are summarized. Preliminary molecular analyses, and new analyses of cultivar numbers, areas, ages, and genealogies are presented. An estimated 77% of the spring bread wheat area in the developing world today is sown to CIMMYT-related wheats, but this does not imply that they are genetically uniform. The hypothesis of increasing genetic uniformity is tested by assessing changes in the diversity of leading progenitors over three decades, in terms of several dimensions of diversity. Latent dimensions include genetic distance and genealogies. Apparent dimensions include performance with respect to yield potential, maintenance and stability across management (input use), and growing environments. The data are not consistent with the view that the genetic diversity of modern semidwarf wheat grown in the developing world has decreased over time. Moreover, since national programs in developing countries cross CIMMYT lines with their own materials before releasing them, the genetic diversity in their cultivars is at least as great as that present among CIMMYT lines., NEARLY 30 YR HAVE PASSED since in a landmark study, the National Research Council (1972) alerted the scientific community and the public about the dangers of restricting crop improvement to [...]

Two maize (Zea mays L) lines, susceptible and resistant to first-generation southwestern corn borer (SWCB), Diatraea grandiosella Dyar, were hybridized then backcrossed to the susceptible parent to form a population that was selected over three backcross generations by either marker-assisted or conventional selection for resistance to first generation SWCB leaf feeding. Quantitative trait loci (QTL) mapping was done by B[C.sub.1][F.sub.1] genotyping and B[C.sub.1][F.sub.2] infestation with SWCB. Three putative QTL were identified on chromosomes 7, 9, and 10 accounting for 28% of the phenotypic variance. Marker-assisted selection (MAS) proceeded by selecting plants heterozygous at the QTL regions and homozygous for the recurrent parent genotype outside the QTL regions in the B[C.sub.1][F.sub.1] and B[C.sub.2][F.sub.1] generations. B[C.sub.2][F.sub.2] individuals were selected for the homozygous donor genotype in the QTL regions. Conventional selection initiated from the most resistant 30 B[C.sub.1][F.sub.2] lines. Conventional trials of B[C.sub.2][F.sub.2] and B[C.sub.2][F.sub.3] families were infested with SWCB and based on leaf damage ratings selected selfed progeny of the former generation formed the subsequent trial entries. A comparative trial of B[C.sub.2][F.sub.3] lines, selected by the two methods, was evaluated under SWCB infestation at three locations. Leaf damage ratings were taken at all locations and larvae weight was taken at one location. No significant differences for leaf damage ratings or larvae weight were found between lines selected by the two methods. Both methods produced lines significantly improved over the susceptible parent for SWCB leaf feeding damage indicating that the methods were equivalent as conducted in this experiment., SUBSTANTIAL RESOURCES have been invested in developing maize with host-plant resistance to tropical insects by the International Maize and Wheat Improvement Center (CIMMYT) (Mihm, 1985, 1997; Smith et al., 1989; [...]