The objective of this study was to estimate the results ofthe upland rice {Oryza sativa L.) breeding program conducted by the Brazilian Agricultural Research Corporation (Embrapa) and collaborators over the period of 1984 to 2009 covering 25 annual steps of improvement. The best lines generated by this program are evaluated in "value for cultivation and use (VCU) trials." This study used data from 603 VCU trials conducted in seven Brazilian States. The group of lines entering VCU in each year was faken as a sample of the elife program in that year. Best linear unbiased estimates (BLUEs) of the means of groups were computed, and the regression of the BLUEs on years was taken as an estimate of the efficiency of the breeding program.

No abstract

The relative performance of one genotype is not identical in different environments due to genotype-environment interaction (G9E). Thus, for a breeding program to successfully develop cultivars, it is fundamental that candidate elite-lines are tested in several target environments and that the data are analysed for yield, adaptability and stability. The objective of this work was to study the G9E for upland rice using a mixed model and, using the harmonic mean of relative performance of genotypic values (HMRPGV) method, to analyse cultivars and elite-lines over time to identify those that aggregate high grain yield (GY) with high genotypic adaptability and stability. A large dataset of ''value for cultivation and use trials'' collected by the Brazilian Agricultural Research Corporation (Embrapa) and collaborators from 1984 to 2010, involving seven states that represent upland rice crops in the Midwest, North and Northeast regions of Brazil, was used. The effect of location was shown to be more important than the effect of year for promoting crossover interaction. The CNA 8555 had the best GY associated with adaptability and stability, presenting a superiority of 13.28 % above the general mean of all elite-lines. Using already-released cultivars and potential elite-lines, the generalised linear regression analysis revealed significant progress of the stability and adaptability associated with GY over time. The HMRPGV method was shown to be an important tool and allowed identification of three elite-lines in the Embrapa pipeline (AB 062008, AB 062041 and AB 062037), each with high stability, adaptability and yield potential to be released commercially.Keywords Oryza sativa Á HMRPGV Á BLUP Á REML Á G9E Á Genetic progress Abbreviations BLUPBest linear unbiased predictor REML Restricted maximum likelihood GY Grain yield VCU Value for cultivation and use G9EGenotype-environment interaction G9LGenotype-location interaction G9YGenotype-year interaction G9L9YGenotype-location-year interaction HMRPGV Harmonic mean of relative performance of genotypic values

Rice is the most important food crop in the developing world. For rice production systems to address the challenges of increasing demand and climate change, potential and on-farm yield increases must be increased. Breeding is one of the main strategies toward such aim. Here, we hypothesize that climatic and atmospheric changes for the upland rice growing period in central Brazil are likely to alter environment groupings and drought stress patterns by 2050, leading to changing breeding targets during the 21st century. As a result of changes in drought stress frequency and intensity, we found reductions in productivity in the range of 200-600 kg/ha (up to 20%) and reductions in yield stability throughout virtually the entire upland rice growing area (except for the southeast). In the face of these changes, our crop simulation analysis suggests that the current strategy of the breeding program, which aims at achieving wide adaptation, should be adjusted. Based on the results for current and future climates, a weighted selection strategy for the three environmental groups that characterize the region is suggested. For the highly favorable environment (HFE, 36%-41% growing area, depending on RCP), selection should be done under both stress-free and terminal stress conditions; for the favorable environment (FE, 27%-40%), selection should aim at testing under reproductive and terminal stress, and for the least favorable environment (LFE, 23%-27%), selection should be conducted for response to reproductive stress only and for the joint occurrence of reproductive and terminal stress. Even though there are differences in timing, it is noteworthy that stress levels are similar across environments, with 40%-60% of crop water demand unsatisfied. Efficient crop improvement targeted toward adaptive traits for drought tolerance will enhance upland rice crop system resilience under climate change.

The identification of rice drought tolerant materials is crucial for the development of best performing cultivars for the upland cultivation system. This study aimed to identify markers and candidate genes associated with drought tolerance by Genome Wide Association Study analysis, in order to develop tools for use in rice breeding programs. This analysis was made with 175 upland rice accessions (Oryza sativa), evaluated in experiments with and without water restriction, and 150,325 SNPs. Thirteen SNP markers associated with yield under drought conditions were identified. Through stepwise regression analysis, eight SNP markers were selected and validated in silico, and when tested by PCR, two out of the eight SNP markers were able to identify a group of rice genotypes with higher productivity under drought. These results are encouraging for deriving markers for the routine analysis of marker assisted selection. From the drought experiment, including the genes inherited in linkage blocks, 50 genes were identified, from which 30 were annotated, and 10 were previously related to drought and/or abiotic stress tolerance, such as the transcription factors WRKY and Apetala2, and protein kinases.