关键词: 紫花苜蓿, 耐阴性, 综合评价, 多元统计分析, 鉴定指标

Abstract: Alfalfa (Medicago sativa L.) is an important forage in the intercropping system. However, the extreme weak light environment in the intercropping system often leads to a significant decrease in alfalfa yield, and breeding shade-tolerant cultivars is the main way to solve this bottleneck problem. In this experiment, 20 alfalfa germplasm resources were used as test materials, and the shading rates were 0% (full light), 52.9% and 71.8%. Three shading treatments were used to determine the changes in six morphological indexes (stem diameter, height, primary lateral root, root nodule, root crown tiller, angle of stem to leaf), seven growth indexes (leaf weight, plant biomass, leaf area, specific leaf area, leaf mass ratio, stem mass ratio, root mass ratio), and five physiological indexes (chlorophyll a content, chlorophyll b content, total chlorophyll content, carotenoid, chlorophyll a/b ratio) during the tillering stage of alfalfa under different light intensities. Based on the shading tolerance coefficients of 0% and 52.9%, principal component analysis, membership function analysis, cluster analysis, and stepwise regression analysis were used to comprehensively evaluate the shade tolerance of alfalfa germplasm resources and screen their identification indicators. The results showed that the stem diameter, the number of root nodule, and the number of root neck tillering of alfalfa decreased with the decrease of light intensity. The total chlorophyll content showed an increasing trend. The number of primary lateral root, leaf dry weight, biomass per plant, and leaf area showed a trend of first increasing and then decreasing, while the trends of other indexes were inconsistent, and there were significant differences among different cultivars. Combining principal component analysis, membership function analysis and cluster analysis, the 20 test materials could be divided into three types according to their shade tolerance: shade tolerant (4 test materials), semi-shade tolerant (8 test materials), and sensitive (8 test materials). By stepwise regression analysis, the optimal regression equation was established: D=-0.108+0.071X10+0.049X6+0.208X14+0.027X4+0.096X7+0.052X3+0.048X5, the precision of estimation was above 93.72%, Seven indexes, including leaf area, leaf dry weight, angle between stem and leaf, number of root nodules, primary lateral roots, number of root neck tillering, and chlorophyll a content were selected as shade tolerance identification indexes of alfalfa. The research results can provide good materials and scientific basis for the breeding of alfalfa cultivars with shade tolerance, and contribute to the construction and optimization of alfalfa intercropping systems.

Key words: Alfalfa, Shade tolerance, Comprehensive evaluation, Multivariate statistical analysis, Identification indexes