Abstract
2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Investigators discuss new findings in Machine Lea rning. According to news reporting originating in Ghaziabad, India, by NewsRx jo urnalists, research stated, "Adulteration during processing of turmeric powder n ot only causes health risks for the consumers but also affects its quality. Ther e is a need for rapid and non-invasive analysis of its active ingredient, curcum in, during the supply-chain." The news reporters obtained a quote from the research from Academy Science & Innovation Research, "In the present study a total six IR instruments ranging fr om hand-held (NIR), portable (NIR) and standalone (FTNIR and FTIR) were used to obtain spectral data of 160 different turmeric samples. The curcumin content qua ntified using HPLC procedure was used as the response variable for analytical mo del using machine learning tools. Real coded genetic algorithm (RCGA) as the var iable selection procedure provided most critical variables in the sets of 10, 20 , 30 and 40 variables. Sensitivity analysis has revealed the most critical finge rprint (s) in authenticating curcumin across all the instruments. The hand-held (NIR) device with only 20 spectral variables resulted in 93 % accu racy using SVM classifier, and RP (regression co-efficient of prediction) values of 0.970 and 0.997 using RF and XGBoost, respectively. In case of FTNIR and FTI R instruments 100% classification accuracy was achieved using SVM, whereas RF and XGBoost resulted in RP values greater than 0.93."
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