Novel single-grain composition analysis technology was developed recently to help evaluate the eating quality of hybrid rice, according to a research team led by Professor WU Yuejin from the Institute of Intelligence, Hefei Institutes of Physical Science of Chinese Academy of Sciences.
They also found that the eating quality of hybrid rice is not only related to the chemical composition of rice but also influenced by the variation in single-grain chemical composition.
The results were published in Agriculture.
Rice is one of the major food crops worldwide. Amylose, protein, and fat are important quality traits of rice and have important effects on eating quality, storage quality, and processing quality. Near infrared (NIR) spectroscopy has the advantages of being nondestructive, rapid, and nonpolluting in detecting crop quality, but it' hard to achieve high-throughput accurate detection of single-grain quality traits in isolated populations for genetic breeding.
In previous research, the team designed and manufactured an intelligent single-grain crop quality detection and sorting instrument.
Based on this high-throughput single-grain quality NIR detection platform (2–3 grains/second), the team developed some models to explore the best conditions for detection and sorting. With these models, researchers successfully determined the amylose and fat content of individual rice grains.
They compared the data under two different conditions. Under static measurement conditions. The coefficient of determination (R2) values were 0.886 and 0.743 for the modeling of amylose and fat content. And under dynamic measurement conditions, R2 values were 0.666 and 0.765.
"The process was rapid and nondestructive," said CHENG Weimin, first author of the paper, "and when evaluating the eating quality of hybrid rice, we found the reasons for the varying eating quality of hybrid rice using single-grain quality trait analysis techniques."
According to the research, the high-quality hybrid rice had the following characteristics: firstly, the physicochemical indicators for a large sample size meeting the national standards were the determining requirement, and secondly, the small variation in the single-grain composition was the important requirement.
R2 of the eating quality model increased from 0.657 to 0.850 when the single-grain composition variations were added to the independent variables (amylose content, protein content, alkali spreading value, and gel consistency).
In addition, the effect of sterile lines on the eating quality of hybrid rice was greater than that of the restorer lines, so selecting high-quality sterile lines was particularly important for the selection of good-tasting combinations.
This was a new method to evaluate the eating quality of hybrid rice and laid the foundation for high yield and quality breeding of hybrid rice.
This work was supported by the National Natural Science Foundation of China, the Sanya City Yazhou Bay Science and Technology City Research Program, the Hefei Research Institute Fusion Fund, and major special projects in Anhui Province.
Fig. 1 The structure of NIR single-grain high-throughput quality analysis instrument. (Image by FAN Shuang)
Fig. 2 Schematic diagram of different platform-based methods for detecting composition of individual rice grains. (Image by FAN Shuang)
Fig. 3 The eating quality model of hybrid indica rice established with physicochemical indicators as independent variables (a), the dispersion indicators of single-grain composition and physicochemical indicators as independent variables (b) (Image by FAN Shuang)
