Image-based phenotyping for identification tolerant and sensitive rice varieties on salinity Andi Isti Sakinah (a), Yunus Musa (b*), Muh. Farid(b), Muhammad Fuad Anshori (b), Muh. Arifuddin (b), Adinda Asri Laraswati (a)
a) Agriculture System Graduate Scholar, Graduate School, Hasanuddin University
b) Agronomy Department, Agriculture Faculty, Hasanuddin University
*yunusmusa[at]yahoo.com
Abstract
Salinity is one of the main limitations of rice production in the world and based on several studies salinity also significantly affects the chlorophyll content. In plant breeding, it is necessary to assemble tolerance varieties and the process requires character selection. Plant phenotyping is the comprehensive assessment of complex plant traits such as growth, development, tolerance, physiology, yield, and the basic measurement of individual quantitative parameters that form the basis for more complex traits so that image-based phenotyping is expected to be a method for selecting tolerant and sensitive plants. This study aims to determine the character of selection using an image-based phenotyping approach and its correlation to chlorophyll response in salinity tolerant and sensitive rice. The research conducted in July-October 2021 at the Green House External Farm, Faculty of Agriculture Unhas and was carried out artificially by induction of salt in a pot. This study was designed with a separate plot design with the main plots of environmental conditions (NaCl 0 mM and NaCl 60 mM) and sub-plots of Inpari 34, Pokkali, IR29, IR20, and Ciherang varieties. Each experimental unit was repeated three times. The observed image-based phenotyping parameters were RGB (Red Green Blue), the ratio of the Red and Green color indexes, the area of the canopy, the area of the green area of the canopy, the ratio of the area of the green area and the area of the canopy. The chlorophyll parameters observed were chlorophyll a, chlorophyll b, and total chlorophyll. The results showed that the selection character with an image-based phenotyping approach that was well used was the area of the canopy. The canopy area was positively correlated with chlorophyll a (r=0.62), chlorophyll b (r=0.64) and total chlorophyll (r=0.62). So, the decrease in canopy area due to salt toxicity can be an indicator of a decrease in chlorophyll content in plant tissue.
Keywords: Cluster heatmap, Image processing, Plant phenotyping, Salt toxicity.
Topic: Emerging Technologies in Agricultural Production Systems
