基于CART决策树的中华绒螯蟹耐碱性能快速分类筛选

Rapid classification and screening of alkali tolerance in Eriocheir sinensis based on CART decision tree

  • 摘要:
    目的 为建立中华绒螯蟹耐碱胁迫能力的快速评估及筛选方法,解决传统碱胁迫实验耗时费力、破坏性强且难以规模化应用的问题。
    方法 本研究以204只山东地区养殖2龄雌性中华绒螯蟹为对象,进行60 mmol/L的NaHCO3碱胁迫实验,并测量头胸甲长(CL)、头胸甲宽(CW)、体重(BW)共3项性状指标,以经标准化处理得到的头胸甲长/头胸甲宽(X1)、体重/头胸甲长(X2)、体重/头胸甲宽(X3)3个性状比例参数作为输入特征,以耐碱等级为输出目标,通过SPSS软件构建CART决策树耐碱等级分类筛选模型。
    结果 不同耐碱等级群体的表型指标及性状比例参数存在显著差异,强耐碱群体X1显著低于弱耐碱群体,X2、X3则显著高于弱耐碱群体;构建的CART决策树模型整体准确率达60.78%,Kappa系数为0.41,模型对强耐碱个体的精确率高达82.14%,可满足实际育种筛选的精准性需求;从模型中提取出3条仅依赖X1、X2的强耐碱个体筛选规则,分别对应“头胸甲宽体基础型”“头胸甲宽体过渡型”和“体质量代偿型”共3类强耐碱个体,置信度分别达76.92%、83.33%和88.89%,形成覆盖全面、置信度高的筛选体系。验证试验表明,按规则筛选的个体在碱胁迫下存活率(73.33%±5.77%)显著高于不符合规则个体(26.67%±5.77%),进一步证实模型可靠有效。
    结论 本研究构建的CART决策树模型仅需常规形态测量即可实现中华绒螯蟹强耐碱个体的快速无损筛选,操作简便、现场适用性强,为盐碱水养殖中华绒螯蟹的定向育种提供了实用工具,也为其他水生生物抗逆性状的快速评估提供了方法参考。

     

    Abstract: Saline-alkali water is a huge potential aquaculture resource in China. However, saline-alkali stress can cause slow growth and low survival rate of cultured animals, which has severely restricted the aquaculture and promotion of Eriocheir sinensis and other saline-alkali tolerant species. In order to establish a rapid assessment and screening method for the ability to tolerate alkali stress of E. sinensis and address the limitation of traditional laboratory alkali stress experiments, such as time and labor consumption, strong destructiveness and difficulty in large-scale application. In this study,204 female two-year-old E. sinensis cultured in Shandong area were selected as the research objects, A 60 mmol/L NaHCO3 alkali stress experiment was conducted, and three phenotypic traits including carapace length (CL), carapace width (CW) and body weight (BW) were measured. Three trait ratio parameters obtained by standardization, namely carapace length/carapace width (X1), body weight/carapace length (X2) and body weight/carapace width (X3), were used as input features, with the alkali-tolerant survival grade under alkali stress as the output target. A CART decision tree classification and evaluation model for alkali tolerance was constructed by IBM SPSS22.0 software.10-fold cross-validation was used to verify the model performance, and indicators such as accuracy, Kappa coefficient and precision were calculated based on the confusion matrix to evaluate the classification effect of the model. The results showed that there were significant differences in phenotypic indicators and trait ratio parameters among groups with different alkali-tolerant grades: X1 of the strong alkali-tolerant group was significantly lower than that of the weak alkali-tolerant group, while X2 and X3 were significantly higher than those of the weak alkali-tolerant group. The survival time was significantly negatively correlated with X1 (R=−0.184), and significantly positively correlated with X2 and X3 (R=0.177, R=0.163), but the absolute values of all correlation coefficients were lower than 0.2, indicating a weak linear correlation between a single indicator and alkali tolerance. The overall accuracy of the constructed CART decision tree model reached 60.78% with a Kappa coefficient of 0.41, and the precision of the model for identifying strong alkali-tolerant individuals was as high as 82.14%, which could meet the accuracy requirements of actual breeding screening. Three screening rules for strong alkali-tolerant individuals only relying on X1 and X2 were extracted from the model, corresponding to three types of strong alkali-tolerant individuals: "broad-carapace basic type" (X1≤0.885 and X2≤1.914, confidence level 76.92%), "broad-carapace transitional type" (0.892<X1≤0.904 and 1.629<X2≤1.914, confidence level 83.33%) and "body weight compensatory type" (X1>0.915 and 2.022<X2≤2.106, confidence level 88.89%), thus forming a comprehensive and high-confidence screening system. The validation experiment showed that the conforming screening rule group (73.33%±5.77%) had a significantly higher survival rate than the non-conforming group (26.67%±5.77%). further confirming the reliability and effectiveness of the model. In conclusion, the CART decision tree model constructed in this study can realize rapid non-destructive screening of strong alkali-tolerant E. sinensis individuals only through conventional morphological measurement, with the advantages of simple operation and strong on-site applicability. It provides a practical tool for the directional breeding of E. sinensis in saline-alkali water culture, and also a methodological reference for the rapid assessment of stress resistance traits of other aquatic animals.

     

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