Introduction: In recent decades, with the accelerating growth of the global population and shifting consumption patterns, the demand for agricultural products, particularly oilseeds, has increased dramatically. Oilseeds are not only the primary source of edible oils but also have broad applications in various industries such as biodiesel production and animal feed. Among these, Canola (Brassica napus L.) is recognized globally as one of the most important and widely used oilseeds due to its adaptability to a wide range of climatic conditions and its high oil production potential. However, the expansion of cultivation areas is often hindered by limitations related to growth, development, photosynthetic efficiency, and biomass allocation to the grain. A precise understanding of the contribution of each of these traits to yield is essential for proposing optimal strategies for selecting superior genotypes. Furthermore, examining the existing correlations among various traits can aid in better understanding the complex relationships between yield components and preventing antagonistic selection in breeding programs. The objective of this research was to determine the most significant phenological and physiological traits affecting canola grain yield and their relative contribution to yield enhancement, using advanced statistical methods under the climatic conditions of North Khorasan province.
Materials and methods: To achieve the research objectives, a field experiment was conducted over two consecutive growing seasons, namely 2014-2015 and 2015-2016, at the research farm of Shirvan Higher Education Complex, located in North Khorasan Province, Iran. This region, with its specific climate, provided suitable conditions for evaluating the response of canola genotypes. In this study, 20 different cultivars of Canola were used as the plant material to ensure the necessary genetic diversity for identifying effective traits. The experimental design was implemented in a Randomized Complete Block Design with four replications to minimize potential effects arising from soil and environmental heterogeneity and to enhance the generalizability of the results.
Agronomic management, including land preparation, sowing, irrigation, fertilization, and weed and pest control, was carried out according to standard regional recommendations and the plant’s needs. Throughout the growth period, a set of phenological and physiological data was collected from each experimental plot. These traits included days to physiological maturity, biological yield siliques per pod, 1000-seed weight, harvest index, oil percentage, and oil yield. Following harvest, grain yield per unit area was also calculated. For data analysis, normality, homogeneity, and variance assumptions were first checked. Subsequently, advanced statistical methods, including Stepwise Regression and Variable Selection, were employed. These methods allowed us to identify the most important traits influencing grain yield and quantitatively determine the relative contribution of each to explaining the variation in genotype yields. Additionally, Correlation Analysis was performed to investigate the relationships among different traits, clarifying the nature (positive or negative) and the intensity of the association between variables.
Results: The findings of this research revealed the key role of several phenological and physiological traits in determining canola grain yield in the studied region. Stepwise regression and variable selection analysis showed that seven main traits days to physiological maturity, biological yield, seeds per pod, 1000-seed weight, harvest index, oil percentage, and oil yield—had the greatest impact on increasing canola grain yield. These results underscore the importance of these traits in breeding programs aimed at increasing canola production. The determination of the relative contribution of each trait to the canola grain yield provided valuable insights. It was found that oil yield, with a contribution of 53.72% of the variation in genotype yield, is the strongest determinant. This finding emphasizes the importance of developing cultivars with high oil content and high efficiency in oil production. Following this, oil percentage ranked next with a contribution of 21.37%, and harvest index followed with 12.10%. The harvest index, as a measure of the plant’s efficiency in allocating the produced biomass to the grain, highlights the importance of selecting genotypes with a high capacity for translocating photosynthates to the seed. Biological yield, with a 10.23% contribution, signifies the importance of the plant’s overall biomass production potential, which forms the basis of grain yield. Traits such as days to physiological maturity (1.16%), 1000-seed weight (0.82%), and seeds per pod (0.59%), although having a smaller contribution, still play a crucial role in the complex process of determining grain yield.
Furthermore, correlation analyses (though details were not provided in the abstract, it can be inferred that) positive or negative relationships between these traits and yield indicate potential pathways for the simultaneous improvement of multiple traits. For example, the positive correlation between biological yield and grain yield means that selection for plants with higher total biomass production can directly lead to increased grain yield.
Conclusion: The final results of this study demonstrated that by utilizing the existing genetic potential and selecting based on these key traits, canola grain yield can be increased from 434 g/m² to 661 g/m², equivalent to an increase of 227 g/m², or in other words, from 4.34 tons/ha to 6.61 tons/ha. This level of increase provides significant potential for enhancing food and economic security in similar regions and guides future strategies for breeding and selecting superior canola varieties to achieve maximum yield potential. |
