This review paper comprehensively explores the potential of high throughput phenotyping (HTP) in assessing and combating salinity stress in cotton production. Salinity stress presents a significant challenge for global cotton crop, impacting the plant's physiological and molecular functions. HTP emerges as a potentially transformative tool for understanding and addressing this issue, employing advanced imaging techniques, spectral reflectance, and molecular technologies to rapidly and accurately measure plant traits. While HTP holds considerable promise, its implementation is not without challenges. The review dissects these barriers, ranging from technical hurdles associated with data acquisition, storage, and analysis to economic considerations involving equipment and maintenance costs. Notably, advancements in machine learning and artificial intelligence (AI) offer promising solutions to many of these challenges, with proven applications in image analysis, trait prediction and data integration. The review showcases the successful application of HTP across various global case studies, demonstrating its potential to revolutionize plant research and breeding. Further, the integration of AI and machine learning is poised to significantly enhance the capabilities of HTP, ushering in a new era of data-driven, efficient plant phenotyping. The paper concludes with a set of research and policy recommendations to optimize the use of HTP for salinity stress in cotton. These include promoting the integration of genomics and phenomics, improving image analysis algorithms, developing predictive models, and standardizing phenotypic data. At the policy level, the authors call for investments in HTP infrastructure, increased collaboration and data sharing, capacity building, and the incorporation of HTP into breeding programs. This review illustrates the immense potential of HTP to revolutionize our approach to salinity stress in cotton, ultimately contributing to more sustainable and resilient cotton production.
KeyWords:
Cite to this Article
*Corresponding author: noumankhalidpbg@gmail.com
Copyright 2023 TBPS