An overview of image-based phenotyping as an adaptive 4.0 technology for studying plant abiotic stress: A bibliometric and literature review

Muhammad Fuad Anshori; Andi Dirpan; Trias Sitaresmi; Riccardo Rossi; Muh Farid; Aris Hairmansis; Bambang Sapta Purwoko; Willy Bayuardi Suwarno; Yudhistira Nugraha

doi:10.1016/j.heliyon.2023.e21650

An overview of image-based phenotyping as an adaptive 4.0 technology for studying plant abiotic stress: A bibliometric and literature review

Heliyon. 2023 Nov 2;9(11):e21650. doi: 10.1016/j.heliyon.2023.e21650. eCollection 2023 Nov.

Authors

Muhammad Fuad Anshori¹, Andi Dirpan^{2

3}, Trias Sitaresmi⁴, Riccardo Rossi⁵, Muh Farid¹, Aris Hairmansis⁴, Bambang Sapta Purwoko⁶, Willy Bayuardi Suwarno⁶, Yudhistira Nugraha⁴

Affiliations

¹ Department of Agronomy, Hasanuddin University, Makassar, 90245, Indonesia.
² Department of Agricultural Technology, Hasanuddin University, Makassar, 90245, Indonesia.
³ Center of Excellence in Science and Technology on Food Product Diversification, 90245, Makassar, Indonesia.
⁴ Research Center for Food Crops, Research Organization for Agriculture and Food, National Research and Innovation Agency, 16911, Cibinong, Indonesia.
⁵ Department of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence (UNIFI), Piazzale delle Cascine 18, 50144, Florence, Italy.
⁶ Department of Agronomy and Horticulture, Faculty of Agriculture, IPB University, Bogor, 11680, Indonesia.

Abstract

Improving the tolerance of crop species to abiotic stresses that limit plant growth and productivity is essential for mitigating the emerging problems of global warming. In this context, imaged data analysis represents an effective method in the 4.0 technology era, where this method has the non-destructive and recursive characterization of plant phenotypic traits as selection criteria. So, the plant breeders are helped in the development of adapted and climate-resilient crop varieties. Although image-based phenotyping has recently resulted in remarkable improvements for identifying the crop status under a range of growing conditions, the topic of its application for assessing the plant behavioral responses to abiotic stressors has not yet been extensively reviewed. For such a purpose, bibliometric analysis is an ideal analytical concept to analyze the evolution and interplay of image-based phenotyping to abiotic stresses by objectively reviewing the literature in light of existing database. Bibliometricy, a bibliometric analysis was applied using a systematic methodology which involved data mining, mining data improvement and analysis, and manuscript construction. The obtained results indicate that there are 554 documents related to image-based phenotyping to abiotic stress until 5 January 2023. All document showed the future development trends of image-based phenotyping will be mainly centered in the United States, European continent and China. The keywords analysis major focus to the application of 4.0 technology and machine learning in plant breeding, especially to create the tolerant variety under abiotic stresses. Drought and saline become an abiotic stress often using image-based phenotyping. Besides that, the rice, wheat and maize as the main commodities in this topic. In conclusion, the present work provides information on resolutive interactions in developing image-based phenotyping to abiotic stress, especially optimizing high-throughput sensors in image-based phenotyping for the future development.

Keywords: Analytic review; Digitalization 4.0 technology; High-throughput phenotyping; Plant breeding; Salinity stress; Water deficit.

Publication types

Review