Morphological characterization of papaya accessions in Jember through multivariate analysis

R. Rusdiana, Halimatus Sa'diyah, Vega Kartika Sari, Kacung Hariyono, S. Hartatik
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Abstract

This study aimed to select the most informative morphological descriptors in characterizing and distinguishing papaya accessions in Jember. The multivariate analysis was used to i) determine the closeness between the papaya accessions collected based on morphology descriptors and ii) define a list of sufficient minimum descriptors to distinguish papaya accessions in Jember. Five quantitative and fifteen qualitative descriptors were used in evaluating 23 accessions. The data collected through quantitative descriptors were analyzed by the means of PCA­biplot analysis and qualitative descriptors were analyzed using entropy level. Statistical analysis was carried out by R studio software using two packages, i.e. biotools and factoextra packages. Based on the research results, the first two principal components of the PCA­biplot representation of 23 accessions were able to evaluate 67.18% of the total variability. The accessions located in KAL­SUK, GUM­PUR 1, and GUM­PUR 2 had similarities in tree diameter and width of mature leaf characters, while KAL­PLA, MUM­SUM 1, LED­SLA, MUM­LEN 1, SUM­RO 2, and SUM­JAM accessions shared similarities in the length of mature leaf, petiole, and peduncle. The minimum descriptors that could be used to characterize papaya plant accessions in Jember were two quantitative descriptors (tree diameter and length of mature leaf) and three qualitative descriptors (general shape of mature leaf teeth, height to first fruit, and stem color). The combination of quantitative­qualitative descriptors allowed the simple and rapid characterization of papaya accession. In addition, it could reduce costs and labor without losing information in the characterization of papaya plants.
基于多变量分析的木瓜种质形态特征分析
本研究旨在选择最具信息量的形态描述符来表征和区分琼伯木瓜材料。多元分析用于i)确定基于形态描述符收集的木瓜材料之间的接近度,以及ii)定义一个足够的最小描述符列表,以区分Jember中的木瓜材料。使用5个定量和15个定性描述符对23份材料进行了评价。通过定量描述符收集的数据采用主成分分析法进行分析,定性描述符采用熵水平进行分析。统计分析由R studio软件使用两个包进行,即biotools和factoextra包。根据研究结果,23份材料的主成分分析双批次代表性的前两个主要成分能够评估67.18%的总变异性。KAL­SUK、GUM­PUR 1和GUM­PUR 2的材料在树径和成熟叶片性状宽度方面具有相似性,而KAL­PLA、MUM­SUM 1、LED­SLA、MUM‐LEN 1、SUM­RO 2和SUM­JAM的材料在成熟叶片长度、叶柄和花序梗方面具有相似之处。可用于表征Jember木瓜植物材料的最小描述符是两个定量描述符(树径和成熟叶的长度)和三个定性描述符(成熟叶齿的一般形状、到第一个果实的高度和茎色)。定量-定性描述符的结合使得番木瓜登录的表征变得简单而快速。此外,它可以在不损失木瓜植物特征信息的情况下降低成本和劳动力。
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