title: Development of Prediction Model and Experimental Validation in Predicting the Curcumin Content of Turmeric (Curcuma longaL.).
abstract: The drug yielding potential of turmeric (Curcuma longaL.) is largely due to the presence of phyto-constituent 'curcumin.' Curcumin has been found to possess a myriad of therapeutic activities ranging from anti-inflammatory to neuroprotective. Lack of requisite high curcumin containing genotypes and variation in the curcumin content of turmeric at different agro climatic regions are the major stumbling blocks in commercial production of turmeric. Curcumin content of turmeric is greatly influenced by environmental factors. Hence, a prediction model based on artificial neural network (ANN) was developed to map genome environment interaction basing on curcumin content, soli and climatic factors from different agroclimatic regions for prediction of maximum curcumin content at various sites to facilitate the selection of suitable region for commercial cultivation of turmeric. The ANN model was developed and tested using a data set of 119 generated by collecting samples from 8 different agroclimatic regions of Odisha. The curcumin content from these samples was measured that varied from 7.2% to 0.4%. The ANN model was trained with 11 parameters of soil and climatic factors as input and curcumin content as output. The results showed that feed-forward ANN model with 8 nodes (MLFN-8) was the most suitable one withR2value of 0.91. Sensitivity analysis revealed that minimum relative humidity, altitude, soil nitrogen content and soil pH had greater effect on curcumin content. This ANN model has shown proven efficiency for predicting and optimizing the curcumin content at a specific site.
authors.affiliation: Center of Biotechnology, Siksha O Anusandhan University Bhubaneswar, India.
authors.forename: Abdul
authors.initials: A
authors.lastname: Akbar
authors.affiliation: Center of Biotechnology, Siksha O Anusandhan University Bhubaneswar, India.
authors.forename: Ananya
authors.initials: A
authors.lastname: Kuanar
authors.affiliation: Center of Biotechnology, Siksha O Anusandhan University Bhubaneswar, India.
authors.forename: Raj K
authors.initials: RK
authors.lastname: Joshi
authors.affiliation: Center of Biotechnology, Siksha O Anusandhan University Bhubaneswar, India.
authors.forename: I S
authors.initials: IS
authors.lastname: Sandeep
authors.affiliation: Center of Biotechnology, Siksha O Anusandhan University Bhubaneswar, India.
authors.forename: Sujata
authors.initials: S
authors.lastname: Mohanty
authors.affiliation: School of Life Sciences, Sambalpur University Sambalpur, India.
authors.forename: Pradeep K
authors.initials: PK
authors.lastname: Naik
authors.affiliation: Department of Soil Science, Orissa University of Agriculture and Technology Bhubaneswar, India.
authors.forename: Antaryami
authors.initials: A
authors.lastname: Mishra
authors.affiliation: Center of Biotechnology, Siksha O Anusandhan University Bhubaneswar, India.
authors.forename: Sanghamitra
authors.initials: S
authors.lastname: Nayak
keywords: artificial neural network; curcumin content; optimization; prediction; turmeric