Phenotyping the Anthocyanin Content of Various Organs in Purple Corn Using a Digital Camera

Zhengxin Wang, Ye Liu, Ke Wang, Yusong Wang, Xue Wang, Jiaming Liu, Cheng Xu and Youhong Song ()
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Zhengxin Wang: School of Agronomy, Anhui Agricultural University, Hefei 230036, China
Ye Liu: Department of Geographical and Earth Sciences, University of Glasgow, Gilmorehill, Glasgow G12 8QQ, UK
Ke Wang: School of Agronomy, Anhui Agricultural University, Hefei 230036, China
Yusong Wang: School of Agronomy, Anhui Agricultural University, Hefei 230036, China
Xue Wang: School of Agronomy, Anhui Agricultural University, Hefei 230036, China
Jiaming Liu: School of Agronomy, Anhui Agricultural University, Hefei 230036, China
Cheng Xu: School of Economics and Management, Jingdezhen University, Jingdezhen 333400, China
Youhong Song: School of Agronomy, Anhui Agricultural University, Hefei 230036, China

Agriculture, 2024, vol. 14, issue 5, 1-16

Abstract: Anthocyanins are precious industrial raw materials. Purple corn is rich in anthocyanins, with large variation in their content between organs. It is imperative to find a rapid and non-destructive method to determine the anthocyanin content in purple corn. To this end, a field experiment with ten purple corn hybrids was conducted, collecting plant images using a digital camera and determining the anthocyanin content of different organ types. The average values of red (R), green (G) and blue (B) in the images were extracted. The color indices derived from RGB arithmetic operations were applied in establishing a model for estimation of the anthocyanin content. The results showed that the specific color index varied with the organ type in purple corn, i.e., AC CR for the grains, BRT for the cobs, AC CB for the husks, R for the stems, AC CB for the sheaths and BRT for the laminae, respectively. Linear models of the relationship between the color indices and anthocyanin content for different organs were established with R 2 falling in the range of 0.64–0.94. The predictive accuracy of the linear models, assessed according to the NRMSE, was validated using a sample size of 2:1. The average NRMSE value was 11.68% in the grains, 13.66% in the cobs, 8.90% in the husks, 27.20% in the stems, 7.90% in the sheaths and 15.83% in the laminae, respectively, all less than 30%, indicating that the accuracy and stability of the model was trustworthy and reliable. In conclusion, this study provided a new method for rapid, non-destructive prediction of anthocyanin-rich organs in purple corn.

Keywords: purple corn; anthocyanin; digital photography; image analysis (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
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