基于叶片离子组特征的油茶氮磷钾营养状态评估

Oil-tea Camellia is an important woody oil tree species in China. The diagnosis and evaluation of its nutritional status is the basis for research on nutrient utilization mechanism and germplasm resources screening. In view of the limitations and inaccuracy of the nutritional status diagnosis and evaluation method built on single mineral ion, it is difficult to analyze the nutrient utilization characteristics of different oil-tea Camellia genetic resources. Therefore, the evaluation of oil-tea Camellia plant’s nitrogen, phosphorus, potassium physiological status based on leaf ionome will be studied. The leaves are sampled for ICP-MS analysis in order to learn about the leaf ionome characteristics in response to nitrogen, phosphorus and potassium nutrition stress, explore the relationship among the ions and reveal the coordinated ions accompanied with the changes of nitrogen, phosphorus and potassium nutrition. The principal component variables of leaf ionome in response to nitrogen, phosphorus and potassium nutrition stress will be analyzed by improved PCA method and then multivariable logistic regression models used for oil-tea Camellia nutrition physiological status evaluation are built and optimized. The specificity, accuracy and validity of the models will be confirmed by test set built with different nutrition characteristic varieties of oil-tea Camellia in order to realize the valid evaluation of oil-tea Camellia plant’s nitrogen, phosphorus and potassium physiological status. The implementation of this project will further expand and enrich the nutritional diagnosis and evaluation system and provide a new path and theoretical basis for research on the mechanism of high efficient nutrition utilization and germplasm resources screening of oil-tea Camellia.

作为是我国重要的木本食用油料树种，油茶的树体营养状态评估是开展其养分利用机制研究和种质资源筛选的基础。鉴于目前以单一矿质离子为指标的营养状态评估方法的局限性和不准确性，难以实现对不同油茶遗传资源养分利用特征的评估和分析，本项目拟开展基于叶片离子组特征的油茶氮磷钾营养状态评估研究，通过高通量离子分析技术（ICP-MS）定量分析油茶叶片离子组，获悉氮磷钾营养胁迫的叶片离子组响应特征，探讨离子间的相互关系，揭示响应氮磷钾元素变化的协同变化离子及其变化规律；结合主成分分析法的改进，解析响应氮磷钾营养胁迫的叶片离子组主成分变量，构建和优化多变量逻辑回归模型；并通过不同营养利用特性油茶品种的营养胁迫测试群体，对该模型进行特异性、准确性和有效性验证，以期实现对油茶氮磷钾营养状态的有效评估。本项目的实施将进一步拓展和丰富油茶营养诊断和评估体系，为探索其养分高效利用机制及种质资源筛选提供新的研究思路和基础。

作为是我国重要的木本食用油料树种，油茶的树体营养状态评估是开展其养分利用机制研究和种质资源筛选的基础。鉴于目前以单一矿质离子为指标的营养状态评估方法的局限性和不准确性，难以实现对不同油茶遗传资源养分利用特征的评估和分析，本项目开展了基于叶片离子组特征的油茶氮磷钾营养状态评估研究。通过高通量离子分析技术定量分析了磷钾营养胁迫处理的油茶叶片离子组组分特征，发现氮磷钾胁迫处理不仅降低了叶片氮、磷、钾元素的含量，而且硼、铜、铁、镁离子含量也发生了变化，如氮胁迫处理的油茶叶片钾和硼元素含量显著降低，铜元素含量则显著增加，磷胁迫处理的油茶叶片氮元素含量显著下降，铁和铜元素含量显著升高，钾胁迫处理的油茶叶片氮硼镁元素含量显著下降，而铁和铜元素含量显著升高；基于协同变化离子特征，利用主成分分析方法，解析了响应氮磷钾胁迫的主成分变量，并进一步以解析形成的主成分变量为预测因子，利用多变量逻辑回归分析方法，构建了油茶氮磷钾营养状态评估模型，分别为logit(P)N = 0.169 - 0.942PC1 + 0.568PC2 + 2.031PC3, logit(P)P = 0.437 - 1.289PC1 + 4.215PC2 - 1.593PC3和logit(P)K = 0.146 - 1.781PC1 + 1.911PC2 - 3.339PC3. ROC 受试特征曲线分析表明，利用离子组特征构建磷钾营养状态的预测模型预测效率（预测准确率>85%）显著高于基于单一元素构建的预测模型（预测准确率<61%）；以磷营养逻辑回归评估模型为对象进行特异性和有效性验证，发现其磷营养状态评估准确率超过了80%，而单以叶片磷含量为指标的评估则没有预测能力。本项目的实施进一步拓展和丰富了油茶营养诊断和评估体系，为探索其养分高效利用机制以及种质资源筛选提供新的研究思路和基础。