Abstract：Lettuce as one of the main varieties of leaf vegetables，its seedling quality plays an important role in promoting the yield and quality，mechanized transplanting and harvesting．This experiment took head lettuce‘Sheshou 101’as test material；on the basis of measuring 16 trait indexes，calculated the comprehensive evaluation index of seedlings by fuzzy comprehensive evaluation method；preliminarily constructed the strong seedling index model by principal component analysis method；carried out correlation analysis on comprehensive evaluation index；and obtained a large correlation but stable lettuce strong seedling index．This experiment also conducted verification using 3 different types of lettuce varieties‘Sheshou 101’（head lettuce），‘Lyudie’（half head lettuce），and‘Bolicui’（loose leaf lettuce）．The results showed that the comprehensive evaluation index of lettuce seedlings was distributed on 0.215-0.958，which could be used as evaluation basis for precision of strong seedling index．24 strong seedling index models were constructed by principal component analysis method，and 8 models with greater correlation were verified．Among them，the correlation of model X15“leaf area × average root diameter × underground fresh mass × width-length ratio”was the largest（0.749）．The verified correlation of these 3 lettuce varieties all were the highest，proving that this model could be used for accurate evaluation of seedling quality．Correlations of the other 7 models were also significantly higher than those of the contrast，but model X19“above ground fresh mass × total length of root system × underground fresh mass × width-length ratio”index measurement was relatively easy，which could be used as an alternative model for production application．
张斌，宫彬彬，边鑫宇，吴晓蕾，李敬蕊，吕桂云，高洪波. 基于模糊综合评价法的叶用莴苣壮苗指数模型建立与验证[J]. 中国蔬菜, 2022, 1(1): 67-73.
ZHANG Bin，GONG Binbin，BIAN Xinyu，WU Xiaolei，LI Jingrui，LYU Guiyun，GAO Hongbo. Establishment and Verification of Lettuce Strong Seedling Index Model Based on Fuzzy Comprehensive Evaluation. China Vegetables, 2022, 1(1): 67-73.