ses were not always effective in analyzing the MET data structure. The ANOVA is an additive model that The identification of the highest yielding cultivar for a specific describes main effects effectively and determines if GE environment on the basis of both genotype (G) and genotype ϫ environment (GE) interaction would be useful to breeders and producers since interaction is a significant source of variation, but it yield estimates based only on G and environment (E) effects are does not provide insight into the patterns of genotypes insufficient. The objective of this study was to demonstrate the usefulor environments that give rise to the interaction. The ness of additive main effects and multiplicative interactions (AMMI)PCA is a multiplicative model that contains no sources model analysis and G plus GE interaction (GGE) biplots, obtained

Literature on the path analyses of grain yield and at least 14 yield related traits in a path diagram that is organized with at least second order variables has been lacking. The objectives of this study were to obtain and interpret information on the nature of interrelationships between first‐, second‐, and third‐order yield‐related traits and rice (Oryza sativa L.) grain yield. Fifteen rice genotypes were used in this study to represent the combinations of low and high levels of four traits that were identified as important yield determinants — maximum number of tillers, grain size, panicle node number, and panicle size. ‘Lemont’ and ‘Teqing’ were two of these genotypes. The remaining genotypes were F9 lines from a Lemont × Teqing cross. Field experiments were conducted during the 1994 and 1995 cropping seasons at the Texas A&M University Agricultural Research and Extension Center near Beaumont, TX. The 1994 path coefficient (p) of panicle weight on grain yield (p = 0.72; r2 = 0.93) was used to predict the 1995 grain yield (r2 = 0.90). Based on a path analysis of the combined 1994 and 1995 data, the following traits had positive path coefficients on grain yield: panicle weight (p = 0.84), number of filled grains per panicle (p = 0.67), panicle density (p = 0.52), maximum filler density (p = 0.34), number of spikelets per panicle (p = 0.34), and 100‐grain weight (p = 0.23). The panicle node number has a negative path coefficient on grain yield (p = −0.23). These results may be useful to rice breeders for the indirect selection of grain yield during the early segregating generations when yield tests are not yet being conducted.

The presence of significant variation among rice (Oryza sativa L.) genotypes in total nonstructural carbohydrates (TNC) that is related to grain yield should be of interest to rice breeders. The effects of four important yield‐determining traits (maximum number of tillers, grain weight, panicle node number, and panicle size) on the TNC concentrations of plant structures at heading and harvest were determined. Path analysis was used to determine the path coefficients of the effect of changes in TNC content (Δ TNC) in leaves or stems on Δ panicle TNC at various stages of crop maturation. Fifteen rice genotypes were used in this study (‘Lemont’, ‘Teqing’, and 13 inbred lines obtained from a Lemont × Teqing cross) to represent the combinations of low and high levels of the four important yield determinants. Field experiments were conducted during the 1994 and 1995 cropping seasons at the Texas A&M University Agricultural Research and Extension Center, Beaumont, TX. Path coefficients for the significant direct effects of Δ stem TNC on Δ panicle TNC were −0.46 for the early‐ to late‐heading period and −0.59 for the late‐heading to grain hardening period. Significant genotype × developmental stage × plant structure interaction suggested the potential for selection of rice lines with high TNC concentration in stems at heading. Linear contrasts indicated that low‐grain weight genotypes had higher stem TNC concentration at harvest, which in turn suggested for the selection of high‐grain weight genotypes.

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Information on the contribution of plant breeding to changes in yields and other agronomic traits is useful for optimizing selection gains; thus, this study aimed to determine the contribution of Texas rice (Oryza sativa L.) breeding to changes in cultivars released during the 48 yr since the release of ‘Bluebonnet’ in 1944. Twenty‐three cultivars were evaluated in three environments and two N levels. Days to heading, plant height, whole and total milled rice percentages, and grain yield were measured. Significant variation among cultivars was found for all traits evaluated, while N affected all traits except milled rice. There was a linear decrease in days to heading in cultivars released from 1944 to 1992. Plant height decreased at 1.28 and 1.10 cm yr−1 for the 190 and 95 kg ha−1 N levels, respectively, mainly due to the incorporation of the semidwarf gene in many cultivars starting in 1981. Plant heights of recently released cultivars were more stable across N levels and less susceptible to lodging. Although whole and total milled rice percentages increased at 0.06 and 0.03% yr−1, respectively, environmental factors limited their genetic advances. Grain yield increased at 42.0 and 26.3 kg ha−1 yr−1 under the 190 and 95 kg ha−1 N levels, respectively, demonstrating that newer releases responded well to higher N. These show the remarkable progress in the Texas rice breeding program from 1944 to 1992.