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A semi-automated method for daily age estimation in larval populations by discriminant function models

机译:基于判别函数模型的半自动化日龄幼虫种群估计方法

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Discriminant analysis including the best age-correlated variables selected by SMLR's to construct a predictive model based on somatic and otolith biometry was applied. Age of anchovy larvae ranging from 10 to 12 mm collected along Western Mediterranean coasts during MEDIAS209 survey were estimated by otolith microstructure analysis and compared with the number of daily increments estimated by the model. The model compound by Perimeter(2) + Area(2) was able to estimate correctly the age of the otoliths in 75% of the cases assuming +/- 1 day of error increasing to 90% assuming +/- 2 days of error with mean values of APE (3.33%) and CV (4.71%) systematically low. The results indicate the precision of the increment estimates. Moreover, no differences between the estimated ages from direct readings and those estimated by the model were observed. The proposed method implies a reduction in the subjectivity factor and the cost/benefit ratio for ageing studies in fish larvae
机译:应用判别分析,包括由SMLR选择的最佳年龄相关变量,以基于体细胞和耳石生物学来构建预测模型。通过耳石微结构分析估算了在MEDIAS209调查期间沿西地中海沿岸收集的10鱼幼虫的年龄,范围为10至12 mm,并与该模型估算的日增重数进行了比较。通过Perimeter(2)+ Area(2)制作的模型化合物能够正确估计7.5%情况下的耳石的年龄,假设+/- 1天的误差增加到90%假设+/- 2天的误差, APE(3.33%)和CV(4.71%)的平均值较低。结果表明增量估计的精度。此外,在直接阅读的估计年龄与模型估计的年龄之间未发现差异。拟议的方法意味着减少了主观因素,降低了鱼幼虫衰老研究的成本/收益比

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