Nutrient Quality of 39 Germplasm Accessions of Seed Lotus
This study aims to screen out the seed lotus(Nelumbo nucifera)germplasm accessions with high nutrient quality.Eleven nutrient indicators of lotus seeds,including protein content,amylase content,and mineral content,in 39 germplasm accessions of seed lotus were measured.Principal component analysis and subordinate function analysis were performed to evaluate the nutrient quality of lotus seeds comprehensively.The results showed that the nutrient indicators varied significantly among different accessions of seed lotus,with the coefficients of variation(CVs)ranging from 0.27 to 0.76.Specifically,α-amylase,zinc content,and vitamin C(VC)content exhibited high CVs,while lotus seed weight,moisture content,and potassium(K)content had low CVs.There were correlations between nutrient indicators.VC had positive correlations with phosphorus(P)and K and a negative correlation with β-amylase.The content of analyzed minerals showed positive correlations between each other.P,K,Fe,and VC were identified as the indicators for evaluating the nutrient quality of lotus seeds.Considering the overall nutrient quality,we screened out seven elite germplasm accessions:'Jianxuan 17','Taikonglian 2','Jiuhuahaoyue','Taikonglian 36','Caisanghulian','Xuanlian 6',and'Baixianglian'.Additionally,'Rihuacunsanlian'with the highest content of VC and total mineral elements,'Taiwanzilian'with the highest β-amylase content,and'Ganlian 62'with the highest moisture content demonstrated application potential in different aspects.The comprehensive evaluation indicated that the lotus seeds of the seven germplasm accessions('Jianxuan 17','Taikonglian 2','Jiuhuahaoyue','Taikonglian 36','Caisanghulian','Xuanlian 6',and'Baixianglian')screened out had higher nutrient quality.Considering both yield and nutrient quality,these germplasm accessions can be prioritized in production and serve as parents in breeding.
seed lotusnutrient qualityprincipal component analysissubordinate function analysiscomprehensive evaluation
NETL
NSTL
万方数据
