From simulation studies it is known that the allocation of experimental resources has a crucial effect on power of QTL detection as well as on accuracy and precision of QTL estimates. In this study, we used a very large experimental data set composed of 976 F 5 maize testcross progenies evaluated in 19 environments and cross-validation to assess the effect of sample size (N ), number of test environments (E ), and significance threshold on the number of detected QTL, the proportion of the genotypic variance explained by them, and the corresponding bias of estimates for grain yield, grain moisture, and plant height. In addition, we used computer simulations to compare the usefulness of two cross-validation schemes for obtaining unbiased estimates of QTL effects. The maximum, validated genotypic variance explained by QTL in this study was 52.3% for grain moisture despite the large number of detected QTL, thus confirming the infinitesimal model of quantitative genetics. In both simulated and experimental data, the effect of sample size on power of QTL detection as well as on accuracy and precision of QTL estimates was large. The number of detected QTL and the proportion of genotypic variance explained by QTL generally increased more with increasing N than with increasing E. The average bias of QTL estimates and its range were reduced by increasing N and E. Cross-validation performed well with respect to yielding asymptotically unbiased estimates of the genotypic variance explained by QTL. On the basis of our findings, recommendations for planning of QTL mapping experiments and allocation of experimental resources are given.

Molecular mapping of cultivated oats was conducted to update the previous reference map constructed using a recombinant inbred (RI) population derived from Avena byzantina C. Koch cv. Kanota x Avena sativa L. cv. Ogle. In the current work, 607 new markers were scored, many on a larger set of RI lines (133 vs. 71) than previously reported. A robust, updated framework map was developed to resolve linkage associations among 286 markers. The remaining 880 markers were placed individually within the most likely framework interval using chi2 tests. This molecular framework incorporates and builds on previous studies, including physical mapping and linkage mapping in additional oat populations. The resulting map provides a common tool for use by oat researchers concerned with structural genomics, functional genomics, and molecular breeding.

The southwestern corn borer (SWCB, Diatraea grandiosella Dyar) and sugarcane borer (SCB, Diatraea saccharalis Fabricius) are two related insect species that cause serious damage in maize production in subtropical and tropical regions of Central and Latin America. We analyzed quantitative trait loci (QTL) involved in resistance to the first generation of both borer species in two recombinant inbred line (RIL) populations from crosses CML131 (susceptible) x CML67 (resistant) and Ki3 (susceptible) X CML139 (resistant). Resistance was evaluated as leaf feeding damage (LFD) in replicated field trials across several environments under artificial infestation. Leaf protein concentration and leaf toughness were evaluated in one environment as putative components of resistance. The method of composite interval mapping was employed for QTL detection with RFLP linkage maps derived for each population of RIL. Estimates of the genotypic and genotype x environment interaction variances for SWCB LFD and SCB LFD were highly significant in both populations. Heritabilities ranged from 0.50 to 0.75. In Population CML131 x CML67, nine and eight mostly identical QTL were found for SWCB LFD and SCB LFD, respectively, explaining about 52% of the phenotypic variance (~'J) for each trait. In Population Ki3 x CML139, five QTL for SWCB LFD were detected, explaining 35.5% of 6-~. Several of these QTL were found in regions containing QTL for leaf protein concentration or leaf toughness. A low number of QTL in common between the two RIL populations and between RIL and corresponding populations of F2:3 indicated that the detection of QTL depended highly on the germplasm and population type. Consequently, chances of successful application of marker-based selection (MBS) for corn borer resistance are reduced when QTL are not identified in the germplasm in which the final selection will be carried out.

Maize varieties with improved nitrogen(N)‐use efficiency under low soil N conditions can contribute to sustainable agriculture. Tests were carried to see whether selection of European elite lines at low and high N supply would result in hybrids with differential adaptation to these contrasting N conditions. The objective was to analyze whether genotypic differences in N uptake and N‐utilization efficiency existed in this material and to what extent these factors contributed to adaptation to low N supply. Twenty‐four hybrids developed at low N supply (L × L) were compared with 25 hybrids developed at high N supply (H × H). The N uptake was determined as total above‐ground N in whole plants, and N‐utilization efficiency as the ratio between grain yield and N uptake in yield trials at four locations and at three N levels each. Highly significant variations as a result of hybrids and hybrids × N‐level interaction were observed for grain yield as well as for N uptake and N‐utilization efficiency in both hybrid types. Average yields of the L × L hybrids were higher than those of the H × H hybrids by 11.5% at low N supply and 5.4% at medium N level. There was no significant yield difference between the two hybrid types at high N supply. The L × L hybrids showed significantly higher N uptake at the low (12%) and medium (6%) N levels than the H × H hybrids. In contrast, no differences in N‐utilization efficiency were observed between the hybrid types. These results indicate that adaptation of hybrids from European elite breeding material to conditions with reduced nitrogen input was possible and was mainly the result of an increase in N‐uptake efficiency.

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