The quality index method (QIM) is a leading method of assessing the freshness (and thus quality) of seafood that is based on relatively few sensory attributes considered relevant. These characteristics are scored using a 0 to 3 demerit points' scale, the sum of which is designated the quality index (QI) and quantifies the specimens' lack of freshness. The linear relationship between QI and storage time allows for the estimation of remaining shelf-life. Moreover, QIM is deemed species-specific.

Meta-analysis was carried to attest the species-specificity of QIM schemes or if, otherwise, biological, ecological, procedural and methodological parameters, alone or in combination, justify schemes' categorization. The variation among the QIM schemes was analyzed using random/mixed-effects models of 68 primary studies. The correlation coefficient associated with linear relationship between the QIM scores and storage time was the designated effect.

This study is the first to use of meta-analysis to summarize QIM schemes developed since the inception of the method in the early 1980s. The initial random-effects meta-analysis model indicated that the correlation coefficients associated with QIM averaged 0.982 (95% CI: 0.978–0.986). The considerable remaining heterogeneity (Q = 152.06, p < 0.0008) was further investigated as a function of moderator variables. Several moderator variables, per se or in combination, namely seafood group (bluefish, whitefish, Selachii, cephalopods and crustaceans), storage procedure (ice, water, air, vacuum and modified atmosphere packaging) and temperature (°C), family and habitat (marine and freshwater), and maximum number of demerit points in QIM were found to have significant effects (QM, 0.0002 < p < 0.0919) on correlation coefficients derived from QIM schemes. Notwithstanding, at this stage of the analysis none clearly justified the categorization of QIM schemes since substantial residual heterogeneity remained unexplained in almost every case and there were issues with influential studies. Then, in a mixed-effects meta-analysis of a subset of studies for whole specimens stored in ice, seafood groups and maximum number of demerit points were found to be significant moderators (QM, p = 0.0018 and p = 0.0173, respectively). Correlation coefficients were higher in studies developing QIM schemes for cephalopods compared to the other seafood groups and in studies with lower sum of demerit points. The potential issues with publication bias and influence analysis are discussed. We cannot rule out the species-specificity of QIM schemes that have been stated previously and that constitutes a relative advantage compared to other methods of assessment seafood freshness based on sensory analysis, particularly the EU grading scheme.

质量指标方法（QIM）是评估海鲜新鲜度（进而评价质量）的一种主要方法，该方法基于相对较少的相关感官属性。使用0到3个记分点的等级对这些特征进行评分，总和称为质量指数（QI），并量化标本的新鲜度。QI和存储时间之间的线性关系允许估算剩余的货架寿命。此外，QIM被认为是特定于物种的。

进行荟萃分析，以证明QIM计划的物种特异性，或者单独或组合使用生物学，生态，程序和方法学参数来证明计划的分类合理。使用68项主要研究的随机/混合效应模型分析了QIM方案之间的差异。与QIM得分和保存时间之间的线性关系相关的相关系数是指定的效果。

这项研究是首次使用荟萃分析来总结自1980年代初该方法问世以来开发的QIM方案。最初的随机效应荟萃分析模型表明，与QIM相关的相关系数平均为0.982（95％CI：0.978-0.986）。 进一步研究了相当大的剩余异质性（Q = 152.06，p <0.0008），这是调节变量的函数。几个调节变量本身或组合使用，即海鲜组（蓝鱼，白鱼，Selachii，头足类和甲壳类动物），存储程序（冰，水，空气，真空和气调包装）和温度（°C），家庭和栖息地（海洋和淡水），并发现QIM中的最大扣分数具有显着影响（QM，0.0002 <  p QIM方案得出的相关系数<0.0919）。尽管如此，在分析的这一阶段，没有明确的证据证明QIM方案的分类是正确的，因为几乎在每种情况下都无法解释大量的残余异质性，并且存在影响研究的问题。然后，在对存储在冰中的整个标本的一部分研究的混合效应荟萃分析中，发现海鲜组和最大记分点是重要的调节剂（QM，p  = 0.0018和p 分别为0.0173）。与其他海鲜产品组相比，在开发针对头足类动物的QIM方案的研究中，相关系数更高，而在扣分总和较低的研究中，相关系数更高。讨论了出版偏见和影响分析的潜在问题。我们不能排除先前所述的QIM计划的种类特异性，并且与基于感官分析的其他评估海鲜新鲜度的方法（尤其是欧盟分级计划）相比，它具有相对优势。