Breeding for high yield potential has been and continue to be a major objective of most rice programs. Several approaches have been used by different people (Kush, 2005; Yonezawa, 1997) but not much progress has been made. Small gains were reported by some groups (Peng et al 1999, Peng et al 2000;Tabien et al 2008). Hybrid rice was developed to break the yield potential barrier,and hybrids have shown a yield advantage of 10 – 20% over best inbred varieties (Cheng, et al 2007). Yan et al (2007) reported that the yield advantage in hybrids was associated with large sink size due to large panicles and the capacity to maintain a balance between panicle number per unit area and spikelet number per panicle. The objective of this work was to evaluate contrasting rice lines, in terms of number of grains per panicle and number of tillers by square meter. Several lines out-yielded the checks in each location but none was superior in all locations.Table 3 shows differences in some agronomic traits among genotypes, including harvest index. Table 4 shows phenotypic correlations between grain yield (kg ha -1 ) and some yield component. Evaluation of Long Panicles Rice Lines in Several Environments Cesar P. Martinez 1, Edgar A. Torres 2, Silvio James Carabali 2, Luis E. Berrio 2, Cristo Perez 3 and Eduardo Graterol 4, (1)CIAT - Intl Center for Tropical Agriculture, Medley, FL, (2)Rice Program, CIAT, Cali, Valle del Cauca, Colombia, (3)Rice Breeding, FEDEARROZ, Bogota,DE, Colombia, (4)Research Director, DANAC, Maracaibo, Venezuela. Increasing number of grains per panicles is a strategy followed by the CIAT- FLAR breeding program to increase yield potential in rice. The objective of this study was to evaluate contrasting rice lines and checks in several locations in Colombia and Venezuela for yield, yield components, and agronomic traits. Twelve genotypes were evaluated in yield trials in Colombia (Palmira and Monteria), and Venezuela(Portuguesa and Calabozo) during the dry season Data showed several long panicles lines with higher yields than checks in all locations; however, none of the line was superior in all environments due to significant gxe interaction. In general, number of grains per panicle was positively associated with yield, but negatively with panicle number per square meter indicating compensation between yield components. Also, long panicles lines had higher index harvest in Palmira and higher yields across locations. There was no relationship between number of grains per panicle and stability; some long panicle lines had high yield but unstable and some had high yield but stable. Data suggest that breeding for more grains per panicle is a correct strategy to increase yield potential in rice; however, it is necessary to take into account the interrelationships and compensations between yield components, while maintaining good plant type and short plant height, tolerance to lodging and low sterility. Results suggest that a breeding strategy based on specific adaptation could be more successful. Abstract Results and Discussion Background Materials and Methods Twelve rice genotypes were used including eight having differences in yield components, Fedearroz 50, FL01028(long panicle donor), and local checks. There were two locations in Colombia (Palmira and Monteria), and two in Venezuela (Calabozo, and Portuguesa). A complete randomized block design was used with three blocks and plot size of 20 m 2 (5x4). Best crop management practices were applied. At maturity one sub-plot 0.25 m 2 within each plot was sampled by cutting plants at the soil level. Plants were threshed by hand and separated into grain and straw; total and effective culms were counted. Grain samples were oven dried at 70 °C for three days and filled and empty spikelets counted. Filled grains and total grain per square meter, spikelets per panicle, 1000-grains weight, sterility percentage, and harvest index were calculated. Harvest index was determined in Palmira. Grain yield was determined in 12 m 2 area and adjusted to 14% moisture content. The percent of sterility was transformed using the arsine of the square root. A combined analysis, in which genotypic effects were fixed and sites and blocks in sites were considered as random effects, was done using the model (1). Table 3. Mean values for grain yield (kg ha -1 ), number of panicles per square meter (Pan m -2 ), number of grains per panicle (G/pan), sterility percentage (Spfert), 1000 grain weight (GW), harvest index (IH) and days to 50% flowering (Fl), across three locations in dry season Burgueño, J.; Crossa, J. and Vargas, M Graphing GE and GGE biplots. Kang. M (ed.). Hanbook of formulas and software for plant geneticists and breeders. Food Products Press. New York, pag Peng, S.; Laza RC.; Visperas, RM.; Cassman, K.G and Khush, G.S Grain yield of cultivars and lines developed in Phillipines since Crop Science 40: Yang, W.; Peng, S.; Laza, R.; Visperas, R. and Dionisio-Sese M Grain yield and yield attributes of new plant type and hybrid rice. Crops Science 47: 1393 – Table 4. Phenotypic correlations between grain yield (kg ha -1 ), number of panicles per square meter (Pan/m 2 ), number of grains per panicle (G/pan), sterility percentage (Spfert.), 1000 grain weight (GW) The General Linear Model procedure of SAS (SAS Institute, 2002) was used for location and combined analysis. Yield stability was done by using the AMMI analysis (Gauch, 1992), and a SAS program written by Burgueño et al (2003). Tables 1, and 2 show that locations effects were highly significant (p<0.01) for yield, yield components and flowering; genotypic effects and G x E interaction were highly significant (p<0.01) for all characters indicating not only differences in all characters between lines but also differential response of cultivars in different locations. The AMMI analysis indicated: A) Genotypes differed not only for mean yields, but also for their interaction effects; B)Genotypes were different in number of grains per panicle and panicle number per square meter. Lines 3817 and 3371 had consistently bigger panicles than FL1028 suggesting that genetic gain is possible; C) None of the lines had higher yields in all locations; however, lines with higher number of grains per panicle also had higher yields in each location. Additionally, lines with large panicles had better harvest index at Palmira (3399, 3817, 3371 and FL1028). Results suggest that breeding for more grains per panicle could be a correct strategy to increase yield potential in rice. However, since there were negative relationships between yield components it is essential to keep balance between yield components to achieve high yield. A breeding strategy based on specific adaptation could be more successful. FUNDING PROVIDED BY: CIAT – FLAR, AND COLOMBIAN MINISTRY OF AGRICULTURE AND DEVELOPMENT References Table 2. Grain yield (kg ha -1 ) at three locations during the dry season Means followed by different letters are significant different according with REGWQ multiple range test. LineMonteríaPalmiraPortuguesa b a ab ab ab a ab bc abc ab abc abc ab ab bc a ab abc ab ab ab ab c c Fedearroz a abc ab FL ab ab7026.2b c Location Mean SourcedfKg ha -1 FlPan m -2 G/PanSpfertGW Locations ** ** ** **0.238**29.58** block(loc) ns3.29ns ns142.77ns0.004ns2.33ns Genotypes **70.13** ** **0.039**31.97** GenxLoc **9.94** **430.68**0.017**10.38** Pooled error Total86 CV (%) Mean ** significant at 0.01 level, ns non-significant by F-test Table 1. Mean squares for grain yield (kg ha -1 ), days to 50% flowering (Fl), number of panicles per square meter (Pan m -2 ), number of grains per panicle (G/pan), sterility percentage (Spfert.) and 1000 grain weight (GW) at three locations in dry season GenKg ha -1 Pan m -2 GpanPestP1000IH ‡ FL Fedearroz FL ‡ Harvest index measured only in Palmira Kg ha -1 Pan/m2GpanPestP1000 Kg ha -1 Montería * ns ns 0.35 ns Palmira ** 0.69*-0.43 ns 0.48 ns Portuguesa ns 0.17 ns ns 0.34 ns Pan/m2Montería ns ns 0.40 ns Palmira ** ns ns Portuguesa ** 0.05 ns 0.14 ns GpanMontería ns ns Palmira *-0.14 ns Portuguesa ns ns PestMontería ns Palmira ns Portuguesa * P1000Montería 1.0 Palmira1.0 Portuguesa 1.0 ** Correlation coeficiente (r) highly significant (p<0.01), * significant (p<0.05), ns non significant CIAT- Colombia. A.A. 6713