preprints.org > biology and life sciences > biochemistry and molecular biology > doi: 10.20944/preprints202204.0228.v1

Preprint Review Version 1 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 25 April 2022 / Approved: 26 April 2022 / Online: 26 April 2022 (06:00:45 CEST)

Conventional phenotyping breeding approaches for vegetable crops like Solanaceae, Bulb, Root crops, have made a significant contribution by developing many varieties. Despite this, conventional phenotyping approaches are not sufficient due to the longer time taken to develop a variety, low genetic gain, environmental factors and some other externalities that affect the phenotype-based selection. To address the challenges of conventional phenotype, a new recent method of high throughput phenotyping (HTP) is considered a promising tool. The development of high-throughput phenotyping technology began in the preceding decade as advancements in sensor, computer vision, automation, and advanced machine learning technologies. HTP platforms are being utilized to undertake non-destructive assessments of the complete plant system in a range of crops. HTP provides the precise measurements and suggests the collection of high-quality and accurate data which is necessary for standardizing phenotyping for the collection of genetic dissection and genomic assisted breeding such as genome-wide association studies (GWAS), linkage mapping, marker-assisted selection (MAS), genomic selection (GS). The remainder of this chapter discusses how high-throughput phenotyping technologies can be used in genomic-assisted breeding for vegetable crops

vegetables; high throughput phenotyping; genomic assisted breeding

Biology and Life Sciences, Biochemistry and Molecular Biology

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