Quantitative evaluation of Tarocco sweet orange fruit shape using optoelectronic elliptic Fourier based analysis
Quantitative evaluation of Tarocco sweet orange fruit shape using optoelectronic elliptic Fourier based analysis
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DOI：
10.1016/j.postharvbio.2009.05.001
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发表时间：
2009-10-01
影响因子：
7
通讯作者：
Recupero, Giuseppe Reforgiato
中科院分区：
文献类型：
--
作者：
Costa, Corrado;Menesatti, Paolo;Recupero, Giuseppe Reforgiato
甜橙子[Citrus sinensis（L）Osbeck]的血橙橙子栽培品种与普通甜橙子组（瓦伦西亚晚、华盛顿脐、Navelina）的不同之处在于在果肉中并且有时在果皮中存在红色花青素苷色素。在血橙子品种中，塔罗科因其独特的特性而变化最大。几个塔罗科品种的存在，往往具有相似的成熟期，需要准确的果实采后评价。特别是外观，因为这是消费者偏好的主要标准。在这项工作中，分析了属于17种不同Tarocco基因型总共929个果实。利用光电技术，利用椭圆傅立叶分析（EFA）分析果实的横向形状，以区分果实的形状。根据IPGRI e柑橘行业分类对不同基因型的果实形状进行分类。这些方法的效率进行了测试，通过重新分类果形类型学的k-means分析。我们还通过在MatLab中实现合适的脚本来计算k（4）的最佳数目。通过多变量分类技术筛选结果（即，PSLDA），以评估组分类的效率。结合EFA和K-均值分析提高了效率的基因型分类的基础上，水果形状的描述性方法相比。例如，将两个模型与5个组（柑橘工业和k-means-5）进行比较，独立测试数据集中正确分类的百分比在k-means-5模型中分别更高。46.6%与26.0%相比，随机分类概率为20%）。EFA可以测量单个果实的形状，允许在参考标准内比较它们的一致性。结果设置的基础上，不同的塔罗科品种的形状描述的定量形态统计，一种做法，到现在为止，已经进行了专门的描述方式。因此，我们的工作代表了首次根据果实形状区分同一物种的遗传不同品种。(C)2009爱思唯尔有限公司版权所有。
Blood orange cultivars of the sweet orange [Citrus sinensis (L) Osbeck] differ from the common sweet orange group (Valencia Late, Washington navel, Navelina) by the presence in the flesh and sometimes in the rind, of red anthocyanin pigments. Among blood orange varieties, Tarocco is the most variable due to its particular characteristics. The presence of several Tarocco varieties, often characterized by similar maturation periods, necessitates accurate postharvest fruit evaluation. particularly appearance, since this is a primary criterion of consumer preference. in this work a total of 929 fruit belonging to 17 different Tarocco, genotypes were analyzed. Optoelectronic techniques were used to discriminate among fruit shapes using elliptic Fourier analysis (EFA) to analyse fruit lateral shapes. Fruit shape for different genotypes was classified according to the IPGRI e Citrus Industry classification. The efficiency of these methods was tested by reclassifying fruit shape typologies by k-means analysis. We also computed the best number of k (4) by implementing a suited script in MatLab. Results were screened by multivariate classification techniques (i.e., PSLDA) in order to evaluate the efficiency of the group classifications. The combined EFA and k-means analysis increased the efficiency of genotype classification based on fruit shape in comparison with reported descriptive methods. For example, comparing the two models with 5 groups (Citrus Industry and k-means-5), the percentage of correct classification in the independent test dataset was higher in the k-means-5 model (respectively. 46.6% vs. 26.0% compared to a random probability of classification of 20%). EFA could measure single fruit shape allowing the comparison of their conformity within a standard of reference. The results set the basis for a shape description of different Tarocco varieties based on quantitative morphological statistics, a practice that, until now, has been carried out exclusively in a descriptive fashion. Consequently, our work represents the first discrimination of genetically different cultivars of the same species based on fruit shape. (C) 2009 Elsevier B.V. All rights reserved.