|
|
|
| Comprehensive Evaluation of Nutritional Quality Using Multivariate Statistical Analysis in Brassica juncea |
| LI Jianzhong1，2，DAI Yun1，YE Xinyu1，2，LI Guoliang1，ZHANG Shifan1，LI Fei1，ZHANG Hui1，YUAN Lingyun2，CHEN Guohu2，WANG Chenggang2，ZHANG Shujiang1* |
| 1State Key Laboratory of Vegetable Biobreeding，Institute of Vegetables and Flowers，Chinese Academy of Agricultural Sciences，Beijing 100081，China；2College of Horticulture，Anhui Provincial Engineering Laboratory of Horticultural Crop Breeding，Anhui Agricultural University，Hefei 230036，Anhui，China |
|
|
|
|
Abstract To establish a standardized evaluation system for assessing the nutritional quality and to identify varieties of superior quality in Brassica juncea，this study comprehensively assessed nine quality indices：dry matter，vitamin C（VC），crude protein，crude fiber，glucose，fructose，oxalic acid，malic acid，and citric acid across 14 Brassica juncea lines．Multivariate statistical analysis methods，including correlation analysis，principal component analysis，fuzzy mathematical subordinate function analysis，and cluster analysis were employed in this study．The results revealed significant difference at coefficients of variation ranging from 16.46% to 66.67%．This indicated substantial variability among the individual indices of different Brassica juncea lines．Principal component analysis identified the‘1917012’‘1917396’and‘1917381’lines showing superior overall performance，whereas the‘1917351’and‘Xiangrui 182’lines were less favorable．According to fuzzy mathematical affiliation function analysis and cluster analysis，the‘1917396’‘1917397’and‘1917381’lines contained high nutritional quality，in contrast to the‘1917152’and‘Xiangrui 182’lines．Consequently，the‘1917396’and‘1917381’lines excelled in this evaluation system，indicating that they were rich in dry matter，VC，etc．This study demonstrated that the evaluation method could effectively decrease the impact of individual index variations，offering guidance for the selection．
|
|
Received: 01 June 2023
|
|
|
|
|
|
|
