| Correlation analysis between main phenotypic traits and grain folic acid content of millet |
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| DOI：10.7606/j.issn.1000-7601.2024.05.06 |
| Key Words: millet grain folic acid content phenopyte correlation cluster analysis |
| Author Name | Affiliation | | YANG Furong | College of Agriculture, Henan University of Science and Technology, Henan Dryland Crop Germplasm Resources Utilization Engineering Research Center, Luoyang, Henan 471000, China | | DU Bing | College of Agriculture, Henan University of Science and Technology, Henan Dryland Crop Germplasm Resources Utilization Engineering Research Center, Luoyang, Henan 471000, China | | GUO Haojie | College of Agriculture, Henan University of Science and Technology, Henan Dryland Crop Germplasm Resources Utilization Engineering Research Center, Luoyang, Henan 471000, China | | WANG Cheng | College of Agriculture, Henan University of Science and Technology, Henan Dryland Crop Germplasm Resources Utilization Engineering Research Center, Luoyang, Henan 471000, China | | ZHANG Fuhou | College of Agriculture, Henan University of Science and Technology, Henan Dryland Crop Germplasm Resources Utilization Engineering Research Center, Luoyang, Henan 471000, China | | MENG Chaomin | College of Agriculture, Henan University of Science and Technology, Henan Dryland Crop Germplasm Resources Utilization Engineering Research Center, Luoyang, Henan 471000, China |
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| Abstract: |
| In June 2022, a randomized block group design was employed to plant 66 new superior millet varieties at Ruyang County farm, Luoyang City, Henan Province. The aim was to evaluate eight agronomic traits, twelve quality traits, and seed folate content in millet varieties at the maturity stage. The goal was to identify high\|folate millet varieties and establish evaluation indexes for high folate content in millet using coefficient of variation analysis, correlation analysis, cluster analysis, and principal component analysis. The study found that among the 66 millet varieties, the agronomic traits varied between 7.69% and 22.36%, with the length of the internode under the spike having the highest coefficient of variation and the width of the leaf having the lowest. The quality traits varied between 1.45% and 39.34%, with the crude fiber content having the highest coefficient of variation and the carbohydrate content having the lowest. The folate content of the seeds ranged from 0.89 μg·g-1 to 2.80 μg·g-1. Jinuomi 2 had the highest folate content, while Zhonggu 989 had the lowest. The results of the correlation analyses indicated that millet folate content was positively correlated with carbohydrate and methionine content, and the correlation coefficients were 0.120 and 0.108, respectively. The millet folate content was negatively correlated with water content, crude protein dry basis, crude fat, lysine, phenylalanine, and threonine content, and the correlation coefficients were -0.131, -0.150, -0.152, -0.113, -0.134 and -0.129, respectively. These correlations were highly significant. The cluster analysis results indicated that the 66 millet varieties could be classified into three groups. Group I consisted of shorter plants with smaller spike length and internode length under the spike. Group II had higher nutrient and folate contents. Group III had longer spike length and larger spike and stem thickness. The principal component analysis results showed that the 21 millet indexes could be divided into 7 principal components, cumulatively contributing to 86.144%. In summary, there was a strong correlation between the folate content and quality traits in millets. Carbohydrate and methionine content can serve as important indicators for screening high folate millet varieties. |
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