An increase in rice production is urgent, because the populations of major rice-producing countries are expected to consume 70% more rice by the year 2025 [2]. However, it is difficult to expand the area devoted to rice production because most arable land suitable for this purpose has already been developed with urban infrastructure.

Further increase in rice production must be achieved largely by increasing yield per unit area. Improving rice yield has accordingly become one of the major objectives of breeders and growers in many countries over the past several decades. Grain yield is the result of a complex causal mechanism of Panobinostat manufacturer plant ontogeny. From the beginning of a plant’s life, environmental factors affect plant and crop traits, which, in turn, determine the final GY. Complex causal systems have been developed to study the traits that influence the final GY during plant development [3], [4], [5] and [6]. Many investigators have studied the correlations and causal associations of rice GY and yield-related traits, such as PH, PW, SP,

GD, HM, and GW [4], [7], [8], [9], [10] and [11]. Although simple correlation analysis may not sufficiently explain the causal system, path analysis, developed by Wright [12], enables study of the complex relationships among traits of interest. Kozak et al. [13] performed a path analysis of a complex causal mechanism among 15 traits in lowland rice that determined GY and milling

quality. For GY per plant, they found the highest positive correlation with the number of branches per panicle, followed by PN, PH, and Pirfenidone mw flag leaf area. Sarawgi et al. [14] used path analysis to interpret the correlations of traits with GY and harvest index in tested rice accessions. All of these studies focused on GY per plant. Although GY per unit area is the product of GY per plant and plant density, GY per plant is influenced by plant SPTLC1 density, meaning traits that correlate causally with GY per plant are different from those of GY per unit area. Moreover, several traits closely correlated with GY show large variation across years and sites [15], [16] and [17], possibly producing unstable GY results. Traits with unstable results cannot be recommended to breeders as an effective index for improving the yield potential. Stability analysis of yield-related traits is accordingly important for construction of a breeding index. The highest rice yield records in China were > 13 t ha− 1[18], [19] and [20] and 18.5 t ha− 1[21] obtained in Taoyuan village, Yongsheng county, Yunnan province. Taoyuan is a well-known location for evaluating high-yield potential of rice, owing to its favorable ecological conditions such as light and temperature resources. In this study, several new hybrid cultivars or genotypes were collected from different provinces of China and grown in Taoyuan during the 2007 and 2008 growing seasons.