Dataset Information

Transcriptome dataset of ethylene-treated Klutuk Wulung banana.

ABSTRACT: Klutuk Wulung banana (Musa balbisiana Colla, BB Group) is a climacteric fruit whose ripening is influenced by ethylene production. This banana fruit has a relatively slow ripening process time and long shelf-life compared with A genome banana (Musa acuminata, AA). Bananas are usually harvested at a pre-climacteric stage and ripened artificially by exogenous ethylene. Hence, the application of exogenous ethylene at the pre-climacteric stage can accelerate the Klutuk Wulung banana ripening. However, there is no report regarding the effect of exogenous ethylene treatment on Klutuk Wulung banana global gene expression. The knowledge of global gene expression of ethylene treated Klutuk Wulung banana will help to understand this fruit ripening process. In this study, global gene expression data of untreated and ethylene treated Klutuk Wulung banana fruit during ripening were available. Total RNA was extracted from fruit pulp for differential expressed gene analysis using RNA-Seq. The RNA-Seq results obtained were ranged from 34,565,252 to 44,752,129 total reads, with 80.5% to 86.7% of reads were mapped against Klutuk Wulung banana genome reference derived from The Banana Genome Hub. In total, 29,968,128 to 37,776,907 transcripts were detected. The transcriptome data discussed in this article were deposited into NCBI's Gene Expression Omnibus (GEO) Series with an accession number GSE162077. These data can be used as information to identify gene candidates involved in fruit ripening for the application in banana postharvest program.

SUBMITTER: Dwivany FM

PROVIDER: S-EPMC8455975 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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Transcriptome dataset of ethylene-treated Klutuk Wulung banana.

Dwivany Fenny Martha FM Nugrahapraja Husna H Sari Lutfi Dewi Nirmala LDN Putri Rika Rahma RR Novianti Cindy C

Data in brief 20210916

Klutuk Wulung banana (<i>Musa balbisiana</i> Colla, BB Group) is a climacteric fruit whose ripening is influenced by ethylene production. This banana fruit has a relatively slow ripening process time and long shelf-life compared with A genome banana (<i>Musa acuminata</i>, AA). Bananas are usually harvested at a pre-climacteric stage and ripened artificially by exogenous ethylene. Hence, the application of exogenous ethylene at the pre-climacteric stage can accelerate the Klutuk Wulung banana ri ...[more]

PMID: 34584916

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Project description:Agriculture is the art and science of cultivating the soil, growing crops and raising livestock. Enhancing crop yield becomes essential to improve economy in agriculture sector. Crops need 16 essential nutrients in balanced factor for their proper growth. Deficiency among these essential nutrients causes stunted growth often leading to significant crop loss. Symptoms of nutrient deficiency in plants can be observed visually which needs to be diagnosed correctly to rectify the problem, so that plants can grow healthily, increasing its yield. Among various crops, banana is one of the staple foods for millions of people across country and world. They contain essential nutrients that can have a defending impact on health of the human beings. The year-round availability, affordability, varietal range, taste, nutritive of banana and medicinal value makes it the favorite fruit among all classes of people. In addition, it also has good export potential. Few of the symptoms due to nutrient's deficiency in banana leaves are like curling of leaves, appearance of yellow strips, yellowing of the leaves, bluish color of young leaves. Deficiency symptoms can be visualized prominently on the leaves of the plant. Further, Machine Learning models can be developed to detect nutrient deficiency in leaves and help farmers in taking relevant measures. Thus, a fully labelled dataset becomes essential to train and test these models to detect nutrient deficiency accurately. The dataset created consists of banana leaf images of various categories like Musa acuminata (Dwarf Cavendish), Robusta, Rasthali, Poovan, Monthan, Elakkibale. Images depict deficiency in eight class of nutrients: boron, calcium, iron, potassium, manganese, magnesium, sulphur and zinc. Table 1 summarizes the essential nutrients and their deficiency symptoms visible on the leaves. Dataset also contains images of healthy leaves. Machine Learning Models can be developed by researchers and students and train them by using the created banana dataset to obtain high accuracy.

Dataset Information

Transcriptome dataset of ethylene-treated Klutuk Wulung banana.

Publications

Transcriptome dataset of ethylene-treated Klutuk Wulung banana.

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