Abstract
Improvement of edible bananas (a triploid and sterile crop) through conventional breeding is a challenging task owing to its recalcitrant nature for seed set, prolonged crop duration. In addition, the need of huge man power at different stages of progeny development and evaluation often leads to mislabeling, poor data management and loss of vital data. All this can be overcome by the application of advanced information technology source. This ensured secure and efficient data management such as storage, retrieval and data analysis and further could assist in tracking the breeding status in real time. Thus, a user-friendly web-based banana breeding tracker (BBT) has been developed using MySQL database with Hypertext Preprocessor (PHP). This BBT works on all operating systems with access to multiple users from anywhere at any time. Quick responsive (QR) code labels can be generated by the tracker, which can be decoded using QR scanner. Also for each and every updated progress in breeding stages, a new QR code can be generated, which in turn reduce labeling errors. Moreover, the tracker has additional tools to search, sort and filter the data from the data sets for efficient retrieval and analysis. This tracker is being upgraded with phenotypic and genotypic data that will be made available in the public domain for hastening the banana improvement program.
Highlights
Banana (Musa sp.) is one of the economically important fruit crops of the tropics and subtropics [1] regions that serves as a staple food in Africa and Pacific countries [2]
Success of conventional breeding method for the improvement of banana is very limited owing to its recalcitrant nature for the seed set and germination [7]
Retrieval of breeding information using traditional method of data maintenance such as field notebooks is cumbersome and often leading to human errors like mislabels that deteriorate and disorient the quality of the breeding information [6, 18]. This has been overcome by digitizing the entire information that can be converted into labels with Quick responsive (QR) code for easy retrieval and tracking
Summary
Banana (Musa sp.) is one of the economically important fruit crops of the tropics and subtropics [1] regions that serves as a staple food in Africa and Pacific countries [2]. Several literature evidence stated that certain wild or related species or some landraces are resistant/tolerant to abiotic and biotic stresses [6], which cannot be commercialized owing to their seediness and poor yield These resistant sources can be exploited for improving the commercial cultivars through conventional breeding complemented with markerassisted selection. Genomic selection (GS), a new approach for improving quantitative traits in large plant breeding populations requires marker data along with phenotypic and pedigree information [14]. This emphasizes the importance of maintaining the accurate breeding information for the present and future scientific applications in any crop improvement programs
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